education system peer reviewed articles

Advertisement

How can education systems improve? A systematic literature review

• Published: 07 April 2022
• Volume 24 , pages 479–499, ( 2023 )

Cite this article

• Ignacio Barrenechea   ORCID: orcid.org/0000-0002-4673-3862 1 ,
• Jason Beech 2 &
• Axel Rivas 1  

2484 Accesses

10 Citations

11 Altmetric

Explore all metrics

Understanding what contributes to improving a system will help us tackle the problems in education systems that usually fail disproportionately in providing quality education for all, especially for the most disadvantage sectors of the population. This paper presents the results of a qualitative systematic literature review aimed at providing a comprehensive overview of what education research can say about the factors that promote education systems’ improvement. This literature is emerging as a topic of empirical research that merges comparative education and school effectiveness studies as standardized assessments make it possible to compare results across systems and time. To examine and synthesize the papers included in this review we followed a thematic analysis approach. We identify, analyze, and report patterns in the papers included in this systematic review. From the coding process, four drivers for system improvement emerged: (1) system-wide approaches; (2) human capital; (3) governance and macro–micro level bridges; and (4) availability of resources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Background, Aims, and Theories of the Comparative Large-Scale Studies in Education

Background, Aims and Theories of the Comparative Large-Scale Studies in Education

Comparing Systems

Explore related subjects.

• Artificial Intelligence

For example, Improving schools https://journals.sagepub.com/aims-scope/IMP .

School effectiveness and school improvement https://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=nses20 .

For example, International Congress for School Effectiveness and Improvement https://www.icsei.net/about-icsei/ .

Our search countries were Albania, Qatar, Estonia, Portugal, Poland, Peru, Ireland, Russia, Israel, and Slovenia.

Addey, C., Sellar, S., Steiner-Khamsi, G., Lingard, B., & Verger, A. (2017). The rise of international large-scale assessments and rationales for participation.  Compare: A Journal of Comparative and International Education ,  47 (3), 434–452.

Alves, F. (2008). Educational policies and school performance in the Brazilian capitals of states. Cadernos De Pesquisa, 38 (34), 413–440.

Article   Google Scholar  

Arnove, R. F. (2015). Comparative education: Dimensions and trends: A contribution to the 50th anniversary celebration of the Japan comparative education society. Comparative Education, 2015 (50), 168–177.

Auld, E., & Morris, P. (2016). PISA, policy and persuasion: Translating complex conditions into education' best practice'. Comparative Education , 52 (2), 202–229. https://doi.org/10.1080/03050068.2016.1143278 .

Barber, M., Kihn, P., & Moffit, A. (2011). Deliverology 101: A field guide for educational leaders . Corwin Press.

Barber, M., & Mourshed, M. (2007). How the world’s best-performing school systems come out on top . McKinsey & Company.

Becker, G. S. (1976). The economic approach to human behavior . University of Chicago Press.

Beech, J., & Lista, E. (2012). Flowing Discourses and Border Crossing: The Slogan of ‘Respect for Diversity’in Latin America. In World Yearbook of Education 2012 (pp. 391–410). Routledge.

Beech, J., & Rizvi, F. (2017). Revisiting Jullien in an era of globalisation. Compare: A Journal of Comparative and International Education , 47 (3), 374–387.

Betts, J. R., Zau, A., & King, K. (2005). From blueprint to reality: San Diego’s education reforms . Public Policy Institute of California.

Bin Mahfooz, S., & Hovde, K. (2010). Successful education reform: lessons from Poland.  ECA Knowledge Brief ,  34 (11).

Boman, B. (2020). What makes Estonia and Singapore so good? Globalisation, Societies and Education, 18 (2), 181–193.

Booth, A., Papaioannou, D., & Sutton, A. (2012). Systematic approaches to a successful literature review . Sage Publications.

Campbell, C. (2020). Educational equity in Canada: The case of Ontario’s strategies and actions to advance excellence and equity for students. School Leadership & Management , 1–20.

Carvalho, L. M., Costa, E., & Gonçalves, C. (2017). Fifteen years looking at the mirror: On the presence of PISA in education policy processes (Portugal, 2000–2016). European Journal of Education, 52 (2), 154–166.

Coffield, F. (2012). Why the McKinsey reports will not improve school systems. Journal of Education Policy, 27 (1), 131–149.

Coffield, F., & Williamson, B. (2011). From Exam Factories to Communities of Discovery. Adults Learning, 23 (2), 24–25.

Cogan, L. S., Schmidt, W. H., & Wiley, D. E. (2001). Who takes what math and in which track? Using TIMSS to characterize US students’ eighth-grade mathematics learning opportunities. Educational Evaluation and Policy Analysis, 23 (4), 323–341.

Cohen, D. K., & Spillane, J. P. (1992). Chapter 1: Policy and practice: The relations between governance and instruction. Review of research in education , 18 (1), 3–49. American Educational Research Association.

Cox, C. (2004). Innovation and reform to improve the quality of primary education: Chile. Unpublished manuscript, Ministry of Education, Santiago .

Crato, N. (2021). Setting up the Scene: Lessons Learned from PISA 2018 Statistics and Other International Student Assessments. In  Improving a Country’s Education  (pp. 1–24). Springer, Cham.

Cueto, S., Miranda, A., León, J., & Vásquez, M. C. (2016b). Education trajectories: From early childhood to early adulthood in Peru.

Cueto, S., León, J., & Muñoz, I. G. (2016a). Conductas, estrategias y rendimiento en lectura en PISA: análisis para el Perú. REICE: Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación , 14 (3), 5–31.

David, J. L., & Talbert, J. E. (2012). Turning around a high-poverty school district: Learning from Sanger Unified’s success. SH Cowell Foundation .

Deaton, A. (2020). Randomization in the tropics revisited: A theme and eleven variations . Working Paper No. 27600. National Bureau Of Economic Research.

Dhaliwal, I., Duflo, E., Glennerster, R., & Tulloch, C. (2013). Comparative costeffectiveness analysis to inform policy in developing countries: a general framework with applications for education. Education policy in developing countries, 17 , 285–338.

Dinham, S., Crowther, F., Robinson, V. M., McNaughton, S., & Timperley, H. (2011). Building capacity in a self‐managing schooling system: The New Zealand experience. Journal of Educational Administration .

Dykstra, T. (2006). High performance and success in education in Flemish Belgium and the Netherlands . National Center on Education and the Economy.

Edwards, D. B., Jr. (2018). Global education policy, impact evaluations, and alternatives: The political economy of knowledge production . Springer.

Elmore, R. (2007). Educational improvement in Victoria. Unpublished internal communication.

Elmore, R. F., & Burney, D. (1998). Continuous improvement in community district# 2 . University of Pittsburgh, HPLC Project, Learning Research, and Development Center.

Fazlagić, J., & Erkol, A. (2015). Knowledge mobilisation in the Polish education system. Journal of Education for Teaching, 41 (5), 541–554.

Feniger, Y., & Lefstein, A. (2014). How not to reason with PISA data: An ironic investigation. Journal of Education Policy, 29 (6), 845–855.

Fernandez Cano, A. (2016). A methodological critique of the PISA evaluations. Relieve, 22 (1), 1–16. Disponible en: https://www.uv.es/RELIEVE/v22n1/RELIEVEv22n1_M15eng.pdf .

Fleisch, B. (2016). System-wide improvement at the instructional core: Changing reading teaching in South Africa. Journal of Educational Change, 17 (4), 437–451.

Fuhrman, S. (1993). Designing coherent education policy: Improving the system . Jossey-Bass.

Fullan, M., & Rincon-Gallardo, S. (2016). Developing high-quality public education in Canada: The case of Ontario. In Global Education Reform (pp. 169–193). Routledge.

Fullan, M. (2016). The elusive nature of whole system improvement in education. Journal of Educational Change, 17 (4), 539–544.

Glaser, B. G., & Strauss, A. (1967). The discovery of grounded theory . Aldine.

Gómez, R. L., & Suárez, A. M. (2020). Do inquiry-based teaching and school climate influence science achievement and critical thinking? Evidence from PISA 2015. International Journal of STEM Education, 7 (1), 1–11.

Graczewski, C., Knudson, J., & Holtzman, D. J. (2009). Instructional leadership in practice: What does it look like, and what influence does it have? Journal of Education for Students Placed at Risk, 14 (1), 72–96.

Hallinger, P., & Heck, R. H. (2011). Collaborative leadership and school improvement: Understanding the impact on school capacity and student learning. In International handbook of leadership for learning (pp. 469–485). Springer.

Hanushek, E. A. & Woessmann, L. (2007). Calidad de la educación y crecimiento económico . En Documento N° 39. PREAL.

Harris, A. (2010). Leading system transformation. School Leadership and Management, 30 (3), 197–207.

Harris, A., & Jones, M. S. (2017). Professional learning communities: A strategy for school and system improvement? Wales Journal of Education, 19 (1), 16–38.

Hood, C. (1991). A public management for all seasons? Public Administration, 69 (1), 3–19.

Hopfenbeck, T. N., Lenkeit, J., El Masri, Y., Cantrell, K., Ryan, J., & Baird, J. A. (2018). Lessons learned from PISA: A systematic review of peer-reviewed articles on the programme for international student assessment. Scandinavian Journal of Educational Research, 62 (3), 333–353.

Hopkins, D. (2007). Every school a great school: Realizing the potential of system leadership . McGraw-Hill Education.

Hopkins, D., Ahtaridou, E., Matthews, P., Posner, C., & Toledo, F. D. (2007). An analysis of the Mexican school system in light of PISA 2006 . London Centre for Leadership in Learning, University of London.

Hussen, T. (1994). Problems of Educational Reforms in a Changing Society. En A. Yogev y V. Rust (Eds.), International perspectives on education and society . Jai Press.

Jakubowski, M. (2015). Opening up opportunities: Education reforms in Poland. IBS Policy Paper, 1 , 2015.

Google Scholar  

Jessop, B. (1998). The narrative of enterprise and the enterprise of narrative: Place marketing and the entrepreneurial city. En The entrepreneurial city: Geographies of politics, regime and representation . John Wiley.

Lapping, M. B. (2004). Education in a restoration democracy: The case of Estonia. Citizenship, Social and Economics Education, 6 (2), 101–115.

Levin, B. (2012). System-wide improvement in education. Education Policy Series, 13 , 1–38.

Lindblad, S., Pettersson, D., & Popkewitz, T. S. (2015). International comparisons of school results: A systematic review of research on large-scale assessments in education . Swedish Research Council.

LLECE-UNESCO. (2013). Análisis del clima escolar: ¿Poderoso factor que explica el aprendizaje en América Latina y el Caribe? OREALC-UNESCO Santiago.

Masino, S., & Niño-Zarazúa, M. (2016). What works to improve the quality of student learning in developing countries? International Journal of Educational Development, 48 , 53–65.

McAleavy, T., & Elwick, A. (2016). School improvement in London: A global perspective . Education Development Trust. Highbridge House, 16–18 Duke Street, Reading Berkshire, England RG1 4RU, United Kingdom.

McEwan, P. J. (2015). Improving learning in primary schools of developing countries: A meta-analysis of randomized experiments. Review of Educational Research, 85 (3), 353–394.

Mikk, J. (2015). Explaining the difference between PISA 2009 reading scores in Finland and Estonia. Educational Research and Evaluation, 21 (4), 324–342.

Morris, P. (2015). Comparative education, PISA, politics and educational reform: A cautionary note. Compare: A Journal of Comparative and International Education , 45 (3), 470–474.

Morris, P. (1996). Asia’s four little tigers: A comparison of the role of education in their development. Comparative Education, 32 (1), 95–110.

Mourshed, M., Chijioke, C., & Barber, M. (2010). How the world’s most improved school systems keep getting better. McKinsey & Company (En español: Mourshed, M., Chijioke, C. y Barber, M. (2012). Cómo continúan mejorando los sistemas educativos de mayor progreso en el mundo. Documento N° 61. PREAL).

Murnane, R. J., & Ganimian, A. (2014). Improving educational outcomes in developing countries: Lessons from rigorous impact evaluations . Working Paper No. 20284. NBER.

Murphy, J., & Hallinger, P. (1988). Characteristics of instructionally effective school districts. The Journal of Educational Research, 81 (3), 175–181.

Nguyen, X. T., Roemmele, D., & Peel, D. (2013). Education reform in Vietnam: A critical analysis of inclusion and management discourses. Journal of Asian Critical Education , 2 .

Noah, H. J., & Eckstein, M. A. (1969). Toward a science of comparative education . Macmillan.

Nóvoa, A., & Yariv-Mashal, T. (2014). Comparative research in education: A model of governance or a historical journey. En T. Fenwick, E. Mangez y J. Ozga (Eds.), World yearbook of education 2014: Governing knowledge comparison, knowledge-based technologies and expertise in the regulation of education. Routledge.

O’Day, J. A., & Smith, M. S. (2016). Quality and equality in American education: Systemic problems, systemic solutions. In The dynamics of opportunity in America (pp. 297–358). Springer.

O’Day, J., & Quick, H. E. (2009). Assessing instructional reform in San Diego: A theory-based approach. Journal of Education for Students Placed at Risk, 14 (1), 1–16.

OECD. (2019).  PISA 2018 assessment and analytical framework . PISA, OECD Publishing.  https://doi.org/10.1787/b25efab8-en .

Osborne, D., & Gaebler, T. (1992). Reinventing government . Reading, MA: Addison-Wesley.

Osmond-Johnson, P., & Campbell, C. (2018). Transforming an education system through professional learning: Developing educational change at scale in Ontario. Educational Research for Policy and Practice, 17 (3), 241–256.

Pang, N. S. K., & Miao, Z. (2017). The roles of teacher leadership in Shanghai education success. Bulgarian Comparative Education Society .

Paterson, G. D. (2019). Improving student learning through professional learning communities: Employing a system-wide approach. Canadian Journal for New Scholars in Education/Revue canadienne des jeunes chercheures et chercheurs en éducation , 10 (1).

Porter, C. (2002). Measuring the content of instruction: Uses in research and practice. In 2002 Presidential address . University of Wisconsin.

Quick, H. E., Holtzman, D. J., & Chaney, K. R. (2009). Professional development and instructional practice: Conceptions and evidence of effectiveness. Journal of Education for Students Placed at Risk, 14 (1), 45–71.

Rindermann, H., & Ceci, S. J. (2009). Educational policy and country outcomes in international cognitive competence studies. Perspectives on Psychological Science, 4 (6), 551–568.

Rivas, A. (2015). América Latina después de PISA: Lecciones aprendidas sobre la educación en siete países . CIPPEC, Natura e Instituto Natura.

Rivas, A. et al. (2020): Las llaves de la educación. Estudio comparado sobre la mejora de los sistemas educativos subnacionales en América Latina, Fundación Santillana, Madrid.

Rivas, A., & Scasso, M. G. (2021). Low stakes, high risks: The problem of intertemporal validity of PISA in Latin America. Journal of Education Policy, 36 (2), 279–302.

Rizvi, F., & Beech, J. (2017). Global mobilities and the possibilities of a cosmopolitan curriculum. Curriculum Inquiry, 47 (1), 125–134.

Sahlberg, P. (2011). The fourth way of Finland. Journal of Educational Change, 12 (2), 173–185.

Sam, C., & Riggan, M. (2013). Building district capacity for system-wide instructional improvement in Cincinnati public schools. Working Paper. GE Foundation" Developing Futures "™ in Education Evaluation Series. Consortium for Policy Research in Education .

Schleicher, A. (2012). Preparing teachers and developing school leaders for the 21st century: Lessons from around the world . OECD Publishing. 2, rue Andre Pascal, F-75775 Paris Cedex 16, France.

Schleicher, A. (2018). How to build a 21st-century school system . OECD Publishing.

Schmidt, W. H., & Prawat, R. S. (2006). Curriculum coherence and national control of education: Issue or non-issue? Journal of Curriculum Studies, 38 (6), 641–658.

Schmidt, W. H., Wang, H. C., & McKnight, C. C. (2005). Curriculum coherence: An examination of US mathematics and science content standards from an international perspective. Journal of Curriculum Studies, 37 , 525–559.

Schneider, B. R., Estarellas, P. C., & Bruns, B. (2019). The politics of transforming education in Ecuador: Confrontation and continuity, 2006–2017. Comparative Education Review, 63 (2), 259–280.

Sellar, S., & Lingard, B. (2013). The OECD and the expansion of PISA: New global modes of governance in education. British Educational Research Journal, 40 (6), 917–936.

Snilstveit, B., Stevenson, J., Menon, R., Phillips, D., Gallagher, E., Geleen, M., et al. (2016). The impact of education programmes on learning and school participation in low-and middle-income countries.

Snipes, J., Doolittle, F., & Herlihy, C. (2002). Foundations for success: Case studies of how urban school systems improve student achievement. Council of the Great City Schools.

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104 , 333–339.

Steiner-Khamsi, G. (2019a). Randomized controlled trials: League leader in the hierarchy of evidence?. En R. Gorur y S. Sellar (Eds.), World yearbook of education 2019a: Comparative methodology in the era of big data and global networks . Routledge.

Steiner-Khamsi, G. (2019b). Conclusions: What policy-makers do with PISA. Understanding PISA’s attractiveness: Critical analyses in comparative policy studies , 233.

Steiner-Khamsi, G. (2016). New directions in policy borrowing research. Asia Pacific Education Review, 17 (3), 381–390.

Tan, C. (2019). Parental responses to education reform in Singapore, Shanghai and Hong Kong. Asia Pacific Education Review, 20 (1), 91–99.

Trace, A. (1961) What Ivan knows that Johnny doesn’t: A comparison of Soviet and American school programs. Harper.

Tucker, M. (Ed.). (2011). Surpassing Shanghai. An agenda for American education built on the world’s leading systems . Harvard Education Press.

Tyack, D. B. and Cuban, L. (1995). Tinkering toward utopia . Harvard University Press.

Valverde, G. A. (2014). Educational quality: global politics, comparative inquiry, and opportunities to learn. Comparative Education Review, 58 (4), 575–589.

Verger, A., Novelli, M., & Altinyelken, H. K. (2012). Global education policy and international development: An introductory framework.  Global education policy and international development: New agendas, issues and policies , 3–32.

Wenger, E., McDermott, R. A., & Snyder, W. (2002). Cultivating communities of practice: A guide to managing knowledge . Harvard Business Press.

Zavadsky, H. (2016). Bringing effective instructional practice to scale in American schools: Lessons from the Long Beach Unified School District. Journal of Educational Change, 17 (4), 505–527.

Download references

Author information

Authors and affiliations.

Universidad de San Andrés, Victoria, Argentina

Ignacio Barrenechea & Axel Rivas

Monash University, Clayton, VIC, Australia

Jason Beech

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ignacio Barrenechea .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Barrenechea, I., Beech, J. & Rivas, A. How can education systems improve? A systematic literature review. J Educ Change 24 , 479–499 (2023). https://doi.org/10.1007/s10833-022-09453-7

Download citation

Accepted : 03 March 2022

Published : 07 April 2022

Issue Date : September 2023

DOI : https://doi.org/10.1007/s10833-022-09453-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Educational change
• System-wide improvement
• Comparative education
• International education
• Find a journal
• Publish with us
• Track your research

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Understanding the Influence of Race/Ethnicity, Gender, and Class on Inequalities in Academic and Non-Academic Outcomes among Eighth-Grade Students: Findings from an Intersectionality Approach

* E-mail: [email protected]

Affiliation Centre on Dynamics of Ethnicity, Department of Social Statistics, University of Manchester, Manchester, United Kingdom

Affiliation Australian National University, Acton, Australia

• Laia Bécares, 
• Naomi Priest

• Published: October 27, 2015
• https://doi.org/10.1371/journal.pone.0141363
• Reader Comments

Socioeconomic, racial/ethnic, and gender inequalities in academic achievement have been widely reported in the US, but how these three axes of inequality intersect to determine academic and non-academic outcomes among school-aged children is not well understood. Using data from the US Early Childhood Longitudinal Study—Kindergarten (ECLS-K; N = 10,115), we apply an intersectionality approach to examine inequalities across eighth-grade outcomes at the intersection of six racial/ethnic and gender groups (Latino girls and boys, Black girls and boys, and White girls and boys) and four classes of socioeconomic advantage/disadvantage. Results of mixture models show large inequalities in socioemotional outcomes (internalizing behavior, locus of control, and self-concept) across classes of advantage/disadvantage. Within classes of advantage/disadvantage, racial/ethnic and gender inequalities are predominantly found in the most advantaged class, where Black boys and girls, and Latina girls, underperform White boys in academic assessments, but not in socioemotional outcomes. In these latter outcomes, Black boys and girls perform better than White boys. Latino boys show small differences as compared to White boys, mainly in science assessments. The contrasting outcomes between racial/ethnic and gender minorities in self-assessment and socioemotional outcomes, as compared to standardized assessments, highlight the detrimental effect that intersecting racial/ethnic and gender discrimination have in patterning academic outcomes that predict success in adult life. Interventions to eliminate achievement gaps cannot fully succeed as long as social stratification caused by gender and racial discrimination is not addressed.

Citation: Bécares L, Priest N (2015) Understanding the Influence of Race/Ethnicity, Gender, and Class on Inequalities in Academic and Non-Academic Outcomes among Eighth-Grade Students: Findings from an Intersectionality Approach. PLoS ONE 10(10): e0141363. https://doi.org/10.1371/journal.pone.0141363

Editor: Emmanuel Manalo, Kyoto University, JAPAN

Received: June 10, 2015; Accepted: October 6, 2015; Published: October 27, 2015

Copyright: © 2015 Bécares, Priest. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Data Availability: All ECLS-K Kindergarten-Eighth Grade Public-use File are available from the National Center for Education Statistics website ( https://nces.ed.gov/ecls/dataproducts.asp#K-8 ).

Funding: This work was funded by an ESRC grant (ES/K001582/1) and a Hallsworth Research Fellowship to LB.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The US racial/ethnic academic achievement gap is a well-documented social inequality [ 1 ]. National assessments for science, mathematics, and reading show that White students score higher on average than all other racial/ethnic groups, particularly when compared to Black and Hispanic students [ 2 , 3 ]. Explanations for these gaps tend to focus on the influence of socioeconomic resources, neighborhood and school characteristics, and family composition in patterning socioeconomic inequalities, and on the racialized nature of socioeconomic inequalities as key drivers of racial/ethnic academic achievement gaps [ 4 – 10 ]. Substantial evidence documents that indicators of socioeconomic status, such as free or reduced-price school lunch, are highly predictive of academic outcomes [ 2 , 3 ]. However, the relative contribution of family, neighborhood and school level socioeconomic inequalities to racial/ethnic academic inequalities continues to be debated, with evidence suggesting none of these factors fully explain racial/ethnic academic achievement gaps, particularly as students move through elementary school [ 11 ]. Attitudinal outcomes have been proposed by some as one explanatory factor for racial/ethnic inequalities in academic achievement [ 12 ], but differences in educational attitudes and aspirations across groups do not fully reflect inequalities in academic assessment. For example, while students of poorer socioeconomic status have lower educational aspirations than more advantaged students [ 13 ], racial/ethnic minority students report higher educational aspirations than White students, particularly after accounting for socioeconomic characteristics [ 14 – 16 ]. Similarly, while socio-emotional development is considered highly predictive of academic achievement in school students, some racial/ethnic minority children report better socio-emotional outcomes than their White peers on some indicators, although findings are inconsistent [ 17 – 22 ].

In addition to inequalities in academic achievement, racial/ethnic and socioeconomic inequalities also exist across measures of socio-emotional development [ 23 – 26 ]. And as with academic achievement, although socioeconomic factors are highly predictive of socio-emotional outcomes, they do not completely explain racial/ethnic inequalities in school-related outcomes not focused on standardized assessments [ 11 ].

Further complexity in understanding how academic and non-academic outcomes are patterned by socioeconomic factors, and how this contributes to racial/ethnic inequalities, is added by the multi-dimensional nature of socioeconomic status. Socioeconomic status is widely recognized as comprising diverse factors that operate across different levels (e.g. individual, household, neighborhood), and influence outcomes through different causal pathways [ 27 ]. The lack of interchangeability between measures of socioeconomic status within and between levels (e.g. income, education, occupation, wealth, neighborhood socioeconomic characteristics, or past socioeconomic circumstances) is also well established, as is the non-equivalence of measures between racial/ethnic groups [ 27 ]. For example, large inequalities have been reported across racial/ethnic groups within the same educational level, and inequalities in wealth have been shown across racial/ethnic that have similar income. It is therefore imperative that studies consider these multiple dimensions of socioeconomic status so that critical social gradients across the entire socioeconomic spectrum are not missed [ 27 ], and racial/ethnic inequalities within levels of socioeconomic status are adequately documented. It is also important that differences in school outcomes are considered across levels of socioeconomic status within and between racial/ethnic groups, so that the influence of specific socioeconomic factors on outcomes within specific racial/ethnic groups can be studied [ 28 ]. However, while these analytic approaches have been identified as research priorities in order to enhance our understanding of the complex ways in which socioeconomic status and race/ethnicity intersect to influence school outcomes, research that operationalizes these recommendations across academic and non-academic outcomes of school children is scant.

In addition to the complexity that arises from race/ethnicity, socioeconomic status, and intersections between them, different patterns in academic and non-academic outcomes by gender have also received longstanding attention. Comparisons across gender show that, on average, boys have higher scores in mathematics and science, whereas girls have higher scores in reading [ 2 , 3 , 29 ]. In contrast to explanations for socioeconomic inequalities, gender differences have been mainly attributed to social conditioning and stereotyping within families, schools, communities, and the wider society [ 30 – 35 ]. These socialization and stereotyping processes are also highly relevant determining factors in explaining racial/ethnic academic and non-academic inequalities [ 35 , 36 ], as are processes of racial discrimination and stigmatization [ 37 , 38 ]. Gender differences in academic outcomes have been documented as differently patterned across racial/ethnic groups and across levels of socioeconomic status. For example, gender inequalities in math and science are largest among White and Latino students, and smallest among Asian American and African American students [ 39 – 43 ], while gender gaps in test scores are more pronounced among socioeconomically disadvantaged children [ 44 , 45 ]. In terms of attitudes towards math and sciences, gender differences in attitudes towards math are largest among Latino students, but gender differences in attitudes towards science are largest among White students [ 39 , 40 ]. Gender differences in socio-developmental outcomes and in non-cognitive academic outcomes, across race/ethnicity and socio-economic status, have received far less attention; studies that consider multiple academic and non-academic outcomes among school aged children across race/ethnicity, socioeconomic status and gender are limited in the US and internationally.

Understanding how different academic and non-academic outcomes are differently patterned by race/ethnicity, socio-economic status, and gender, including within and between group differences, is an important research area that may assist in understanding the potential causal pathways and explanations for observed inequalities, and in identifying key population groups and points at which interventions should be targeted to address inequalities in particular outcomes [ 28 , 46 ]. Not only is such knowledge critical for population level policy and/or local level action within affected communities, but failing to detect potential factors for interventions and potential solutions is argued as reinforcing perceptions of the unmodifiable nature of inequality and injustice [ 46 ].

Notwithstanding the importance of documenting patterns of inequality in relation to a particular social identity (e.g. race/ethnicity, gender, class), there is increasing acknowledgement within both theoretical and empirical research of the need to move beyond analyzing single categories to consider simultaneous interactions between different aspects of social identity, and the impact of systems and processes of oppression and domination (e.g., racism, classism, sexism) that operate at the micro and macro level [ 47 , 48 ]. Such intersectional approaches challenge practices that isolate and prioritize a single social position, and emphasize the potential of varied inter-relationships of social identities and interacting social processes in the production of inequities [ 49 – 51 ]. To date, exploration of how social identities interact in an intersectional way to influence outcomes has largely been theoretical and qualitative in nature. Explanations offered for interactions between privileged and marginalized identities, and associated outcomes, include family and teacher socialization of gender performance (e.g. math and science as male domains, verbal and emotional skills as female), as well as racialized stereotypes and expectations from teachers and wider society regarding racial/ethnic minorities that are also gendered (e.g. Black males as violent prone and aggressive, Asian females as submissive) [ 52 – 57 ]. That is, social processes that socialize and pattern opportunities and outcomes are both racialized and gendered, with racism and sexism operating in intersecting ways to influence the development and achievements of children and youth [ 58 – 60 ]. Socioeconomic status adds a third important dimension to these processes, with individuals of the same race/ethnicity and gender having access to vastly different resources and opportunities across levels of socioeconomic status. Moreover, access to resources as well as socialization experiences and expectations differ considerably by race and gender within the same level of socio-economic status. Thus, neither gender nor race nor socio-economic status alone can fully explain the interacting social processes influencing outcomes for youth [ 27 , 28 ]. Disentangling such interactions is therefore an important research priority in order to inform intervention to address inequalities at a population level and within local communities.

In the realm of quantitative approaches to the study of inequality, studies often examine separate social identities independently to assess which of these axes of stratification is most prominent, and for the most part do not consider claims that the varied dimensions of social stratification are often juxtaposed [ 56 , 61 ]. A pressing need remains for quantitative research to consider how multiple forms of social stratification are interrelated, and how they combine interactively, not just additively, to influence outcomes [ 46 ]. Doing so enables analyses that consider in greater detail the representation of the embodied positions of individuals, particularly issues of multiple marginalization as well as the co-occurrence of some form of privilege with marginalization [ 46 ]. It is important to note that the languages of statistical interaction and of intersectionality need to be carefully distinguished (e.g. intersectional additivity or additive assumptions, versus additive scale and cross-product interaction terms) to avoid misinterpretation of findings, and to ensure appropriate application of statistical interaction to enable the description of outcome measures for groups of individuals at each cross-stratified intersection [ 46 ]. Ultimately this will provide more nuanced and realistic understandings of the determinants of inequality in order to inform intervention strategies.

This study fills these gaps in the literature by examining inequalities across several eighth grade academic and non-academic outcomes at the intersection of race/ethnicity, gender, and socioeconomic status. It aims to do this by: identifying classes of socioeconomic advantage/disadvantage from kindergarten to eighth grade; then ascertaining whether membership into classes of socioeconomic advantage/disadvantage differ for racial/ethnic and gender groups; and finally, by contrasting academic and non-academic outcomes at the intersection of race/ethnicity, gender and socioeconomic advantage/disadvantage. Intersecting identities of race/ethnicity, gender, and socioeconomic characteristics are compared to the reference group of White boys in the most advantaged socioeconomic category, as these are the three identities (male, White, socioeconomically privileged) that experience the least marginalization when compared to racial/ethnic and gender minority groups in disadvantaged socioeconomic positions.

This study used data on singleton children from the Early Childhood Longitudinal Study—Kindergarten (ECLS-K). The ECLS-K employed a multistage probability sample design to select a nationally representative sample of children attending kindergarten in 1998–99. In the base year the primary sampling units (PSUs) were geographic areas consisting of counties or groups of counties. The second-stage units were schools within sampled PSUs. The third- and final-stage units were children within schools [ 62 ]. Analyses were conducted on data collected from direct child assessments, as well as information provided by parents and school administrators.

Ethics Statement

This article is based on the secondary analysis of anonymized and de-identified Public-Use Data Files available to researchers via the Inter-University Consortium for Political and Social Research (ICPSR). Human participants were not directly involved in the research reported in this article; therefore, no institutional review board approval was sought.

Outcome Variables.

Eight outcome variables, all assessed in eighth grade, were selected to examine the study aims: two measures relating to non-cognitive academic skills (perceived interest/competence in reading, and in math); three measures capturing socioemotional development (internalizing behavior, locus of control, self-concept); and three measures of cognitive skills (math, reading and science assessment scores).

For the eighth-grade data collection, children completed the 16-item Self Description Questionnaire (SDQ) II [ 63 ], where they provided self-assessments of their academic skills by rating their perceived competence and interest in English and mathematics. The SDQ also asked children to report on problem behaviors with which they might struggle. Three subscales were produced from the SDQ items: The SDQ Perceived Interest/Competence in Reading, including four items on grades in English and the child’s interest in and enjoyment of reading. The SDQ Perceived Interest/Competence in Math, including four items on mathematics grades and the child’s interest in and enjoyment of mathematics. And the SDQ Internalizing Behavior subscale, which includes eight items on internalizing problem behaviors such as feeling sad, lonely, ashamed of mistakes, frustrated, and worrying about school and friendships [ 62 ].

The Self-Concept and Locus of Control scales ask children about their self-perceptions and the amount of control they have over their own lives. These scales, adopted from the National Education Longitudinal Study of 1988, asked children to indicate the degree to which they agreed with 13 statements (seven items in the Self-Concept scale, and six items in the Locus of Control Scale) about themselves, including “I feel good about myself,” “I don’t have enough control over the direction my life is taking,” and “At times I think I am no good at all.” Responses ranged from “strongly agree” to “strongly disagree.” Some items were reversed coded so that higher scores indicate more positive self-concept and a greater perception of control over one’s own life. The seven items in the Self-Concept scale, and the six items in the Locus of Control were standardized separately to a mean of zero and a standard deviation of 1. The scores of each scale are an average of the standardized scores [ 62 ].

Academic achievement in reading, mathematics and science was measured with the eighth-grade direct cognitive assessment battery [ 62 ].

Children were given separate routing assessment forms to determine the level (high/low) of their reading, mathematics, and science assessments. The two-stage cognitive assessment approach was used to maximize the accuracy of measurement and reduce administration time by using the child’s responses from a brief first-stage routing form to select the appropriate second-stage level form. First, children read items in a booklet and recorded their responses on an answer form. These answer forms were then scored by the test administrator. Based on the score of the respective routing forms, the test administrator then assigned a high or low second-stage level form of the reading and mathematics assessments. For the second-stage level tests, children read items in the assessment booklet and recorded their responses in the same assessment booklet. The routing tests and the second-stage tests were timed for 80 minutes [ 62 ]. The present analyses use the standardized scores (T-scores), allowing relative comparisons of children against their peers.

Individual and Contextual Disadvantage Variables.

Latent Class Analysis, described in greater detail below, was used to classify students into classes of individual and contextual advantage or disadvantage. Nine constructs, measuring characteristics at the individual-, school-, and neighborhood-level, were captured using 42 dichotomous variables measured across the different waves of the ECLS-K.

Individual-level variables captured household composition, material disadvantage, and parental expectations of the children’s success. Measures included whether the child lived in a single-parent household at kindergarten, first, third, fifth and eighth grades; whether the household was below the poverty threshold level at kindergarten, fifth and eighth grades; food insecurity at kindergarten, first, second and third grades; and parental expectations of the child’s academic achievement (categorized as up to high school and more than high school) at kindergarten, first, third, fifth and eighth grades. An indicator of whether parents had moved since the previous interview (measured at kindergarten, first, third, fifth and eighth grades) was included to capture stability in the children’s life. A household-level composite index of socioeconomic status, derived by the National Center for Education Statistics, was also included at kindergarten, first, third, fifth and eighth grades. This measure captured the father/male guardian’s education and occupation, the mother/female guardian’s education and occupation, and the household income. Higher scores reflect higher levels of educational attainment, occupational prestige, and income. In the present analyses, the socioeconomic composite index was categorized into quintiles and further divided into the lowest first and second quintiles, versus the third, fourth and fifth quintiles.

Two variables measured the school-level environment: percentage of students eligible for free school meals, and percentage of students from a racial/ethnic background other than White non-Hispanic. These two variables were dichotomized as more than or equal to 50% of students belonging to each category. Both variables were measured in the kindergarten, first, third, fifth and eighth grade data collections.

To capture the neighborhood environment, a variable was included which measured the level of safety of the neighborhood in kindergarten, first, third, fifth and eighth grades. Parents were asked “How safe is it for children to play outside during the day in your neighborhood?” with responses ranging from 1, not at all safe, to 3, very safe. For the present analyses, response categories were recoded into 1 “not at all and somewhat safe,” and 0 “very safe.”

Predictor Variables.

The race/ethnicity and gender of the children were assessed during the parent interview. In order to empirically measure the intersection between race/ethnicity and gender in the classes of disadvantage, a set of six dummy variables were created that combined racial/ethnic and gender categories into White boys, White girls, Black boys, Black girls, Latino boys, and Latina girls.

Statistical Analyses

This study used the manual 3-step approach in mixture modeling with auxiliary variables [ 64 , 65 ] to independently evaluate the relationship between the predictor auxiliary variables (the combined race/ethnicity and gender groups), the latent class variable of advantage/disadvantage, and the outcome (non-cognitive skills, socioemotional development, cognitive assessments). This is a data-driven, mixture modelling technique which uses indicator variables (in this case the variables described under Individual and Contextual Disadvantage Variables section) to identify a number of latent classes. It also includes auxiliary information in the form of covariates (the race/ethnicity and gender combinations described under Predictor Variables) and distal outcomes (the eight outcome variables), to better explore the relationships between the characteristics that make up the latent classes, the predictors of class membership, and the associated consequences of membership into each class.

The first step in the 3-step procedure is to estimate the measurement part of the joint model (i.e., the latent class model) by creating the latent classes without adding covariates. Latent class analyses first evaluated the fit of a 2-class model, and systematically increased the number of classes in subsequent models until the addition of latent classes did not further improve model fit. For each model, replication of the best log-likelihood was verified to avoid local maxima. To determine the optimal number of classes, models were compared across several model fit criteria. First, the sample-size adjusted Bayesian Information Criterion (BIC) [ 66 ] was evaluated; lower relative BIC values indicate improved model fit. Given that the BIC criterion tends to favor models with fewer latent classes [ 67 ], the Lo, Mendell, and Rubin likelihood ratio test (LMR-LRT) statistic [ 68 ] was also considered. The LMR-LRT can be used in mixture modeling to compare the fit of the specified class solution ( k -class model) to a model with fewer classes ( k -1 class model). A non-significant chi-square value suggests that a model with one fewer class is preferred. Entropy statistics, which measure the separation of the classes based on the posterior class membership probabilities, were also examined; entropy values approaching 1 indicate clear separation between classes [ 69 ].

After determining the latent class model in step 1, the second step of the analyses used the latent class posterior distribution to generate a nominal variable N , which represented the most likely class [ 64 ]. During the third step, the measurement error for N was accounted for while the model was estimated with the outcomes and predictor auxiliary variables [ 64 ]. The last step of the analysis examined whether race/ethnic and gender categories predict class membership, and whether class membership predicts the outcomes of interest.

All analyses were conducted using MPlus v. 7.11 [ 70 ], and used longitudinal weights to account for differential probabilities of selection at each sampling stage and to adjust for the effects of non-response. A robust standard error estimator was used in MPlus to account for the clustering of observations in the ECLS-K.

Four distinct classes of advantage/disadvantage were identified in the latent class analysis (see Table 1 ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0141363.t001

Class characteristics are shown in Table A in S1 File . Trajectories of advantage and disadvantage were stable across ECLS-K waves, so that none of the classes identified changed in individual and contextual characteristics across time. The largest proportion of the sample (47%; Class 3: Individually and Contextually Wealthy) lived in individual and contextual privilege, with very low proportions of children in socioeconomic deprived contexts. A class representing the opposite characteristics (children living in individually- and contextually-deprived circumstances) was also identified in the analyses (19%; Class 1: Individually and Contextually Disadvantaged). Class 1 had the highest proportion of children living in socioeconomic deprivation, attending schools with more than 50% racial/ethnic minority students, and living in unsafe neighborhoods, but did not have a high proportion of children with the lowest parental expectations. Class 4 (19%; Individually Disadvantaged, Contextually Wealthy) had the highest proportion of children with the lowest parental expectations (parents reporting across waves that they expected children to achieve up to a high school education). Class 4 (Individually Disadvantaged, Contextually Wealthy) also had high proportions of children living in individual-level socioeconomic deprivation, but had low proportions of children attending a school with over 50% of children eligible for free school meals. It also had relatively low proportions of children living in unsafe neighborhoods and low proportions of children attending diverse schools, forming a class with a mixture of individual-level deprivation, and contextual-level advantage. The last class was composed of children who lived in individually-wealthy environments, but who also lived in unsafe neighborhoods and attended diverse schools where more than 50% of pupils were eligible for free school meals (13%; Class 2: Individually Wealthy, Contextually Disadvantaged; see Table A in S1 File ).

The combined intersecting racial/ethnic and gender characteristics yielded six groups consisting of White boys (n = 2998), White girls (n = 2899), Black boys (n = 553), Black girls (n = 560), Latino boys (n = 961), and Latina girls (n = 949). All pairs containing at least one minority status of either race/ethnicity or gender (e.g., Black boys, Black girls, Latino boys, Latina girls) were more likely than White boys to be assigned to the more disadvantaged classes, as compared to being assigned to Class 3, the least disadvantaged (see Table B in S1 File ).

Racial/Ethnic and Gender Differences in Eighth-Grade Academic Outcomes

Table 2 shows broad patterns of intersecting racial/ethnic and gender inequalities in academic outcomes, although interesting differences emerge across racial/ethnic and gender groups. Whereas Black boys achieved lower scores than White boys across all classes on the math, reading and science assessments, this was not the case for Latino boys, who only underperformed White boys on the science assessment within the most privileged class (Class 3: Individually and Contextually Wealthy). Latina girls, in contrast, outperformed White boys on reading scores within Class 4 (Individually Disadvantaged, Contextually Wealthy), but scored lower than White boys on science and math assessments, although only when in the two most privileged classes (Class 3 and 4). For Black girls the effect of class membership was not as pronounced, and they had lower science and math scores than White boys across all but one instance.

https://doi.org/10.1371/journal.pone.0141363.t002

In general, the largest inequalities in academic outcomes across racial/ethnic and gender groups appeared in the most privileged classes. For example, results show no differences in math scores across racial/ethnic and gender categories within Class 4, the most disadvantaged class, but in all other classes that contain an element of advantage, and particularly in Class 3 (Individually and Contextually Wealthy), there are large gaps in math scores across racial/ethnic and gender groups, when compared to White boys. These patterns of heightened inequality in the most advantaged classes are similar for reading and science scores (see Table 2 ).

Racial/Ethnic and Gender Differences in Eighth-Grade Non-Academic Outcomes

Interestingly, racialized and gendered patterns of inequality observed in academic outcomes were not as stark in non-cognitive academic outcomes (see Table 3 ).

https://doi.org/10.1371/journal.pone.0141363.t003

Racial/ethnic and gender differences were small across socioemotional outcomes, and in fact, White boys were outperformed on several outcomes. Black boys scored lower than White boys on internalizing behavior and higher on self-concept within Classes 2 (Individually Wealthy, Contextually Disadvantaged) and 4 (Individually Disadvantaged, Contextually Wealthy), and Black girls scored higher than White boys on self-concept within Classes 2 and 3 (Individually Wealthy, Contextually Disadvantaged, and Individually and Contextually Wealthy, respectively). White and Latina girls, but not Black girls, scored higher than White boys on internalizing behavior (within Classes 3 and 4 for White girls, and within Classes 1 and 3 for Latina girls; see Table 3 ).

As with academic outcomes, most racial/ethnic and gender differences also emerged within the most privileged classes, and particularly in Class 3 (Individually and Contextually Wealthy), although in the case of perceived interest/competence in reading, White and Latina girls performed better than White boys. White girls also reported higher perceived interest/competence in reading than White boys in Class 4: Individually Disadvantaged, Contextually Wealthy.

This study set out to examine inequalities across several eighth grade academic and non-academic outcomes at the intersection of race/ethnicity, gender, and socioeconomic status. It first identified four classes of longstanding individual- and contextual-level disadvantage; then determined membership to these classes depending on racial/ethnic and gender groups; and finally compared non-cognitive skills, academic assessment scores, and socioemotional outcomes across intersecting gender, racial/ethnic and socioeconomic social positions.

Results show the clear influence of race/ethnicity in determining membership to the most disadvantaged classes. Across gender dichotomies, Black students were more likely than White boys to be assigned to all classes of disadvantage as compared to the most advantaged class, and this was particularly strong for the most disadvantaged class, which included elements of both individual- and contextual-level disadvantage. Latino boys and girls were also more likely than White boys to be assigned to all the disadvantaged classes, but the strength of the association was much smaller than for Black students. Whereas membership into classes of disadvantage appears to be more a result of structural inequalities strongly driven by race/ethnicity, the salience of gender is apparent in the distribution of academic assessment outcomes within classes of disadvantage. Results show a gendered pattern of math, reading and science assessments, particularly in the most privileged class, where girls from all ethnic/racial groups (although mostly from Black and Latino racial/ethnic groups) underperform White boys in math and science, and where Black boys score lower, and White girls higher, than White boys in reading.

With the exception of educational assessments, gender and racial/ethnic inequalities within classes are either not very pronounced or in the opposite direction (e.g. racial/ethnic and gender minorities outperform White males), but differences in outcomes across classes are stark. The strength of the association between race/ethnicity and class membership, and the reduced racial/ethnic and gender inequalities within classes of advantage and disadvantage, attest to the importance of socioeconomic status and wealth in explaining racial/ethnic inequalities; should individual and contextual disadvantage be comparable across racial/ethnic groups, racial/ethnic inequalities would be substantially reduced. This being said, most within-class differences were observed in the most privileged classes, showing that benefits brought about by affluence and advantage are not equal across racial/ethnic and gender groups. The measures of advantage and disadvantage captured in this study relate to characteristics afforded by parental resources, implying an intergenerational transmission of disadvantage, regardless of the presence of absolute adversity in childhood. This pattern of differential returns of affluence has been shown in other studies, which report that White teenagers benefit more from the presence of affluent neighbors than do Black teenagers [ 71 ]. Among adult populations, studies show that across several health outcomes, highly educated Black adults fare worse than White adults with the lowest education [ 72 ]. Intersectional approaches such as the one applied in this study reveal how power within gendered and racialized institutional settings operates to undermine access to and use of resources that would otherwise be available to individuals of advantaged classes [ 72 ]. The present study further contributes to this literature by documenting how, in a key stage of the life course, similar levels of advantage, but not disadvantage, lead to different academic outcomes across racial/ethnic and gender groups. These findings suggest that, should socioeconomic inequalities be addressed, and levels of advantage were similar across racial/ethnic and gender groups, systems of oppression that pattern the racialization and socialization of children into racial/ethnic and gender roles in society would still ensure that inequalities in academic outcomes existed across racial/ethnic and gender categories. In other words, racism and sexism have a direct effect on academic and non-academic outcomes among 8 th graders, independent of the effect of socioeconomic disadvantage on these outcomes. An important limitation of the current study is that although it uses a comprehensive measure of advantage/disadvantage, including elements of deprivation and affluence at the family, school and neighborhood levels through time, it failed to capture these two key causal determinants of racial/ethnic and gender inequality: experiences of racial and gender discrimination.

Despite this limitation, it is important to note that socioeconomic inequalities in the US are driven by racial and gender bias and discrimination at structural and individual levels, with race and gender discrimination exerting a strong influence on academic and non-academic inequalities. Racial discrimination, prevalent in the US and in other industrialized nations [ 38 , 73 ] determines differential life opportunities and resources across racial/ethnic groups, and is a crucial determinant of racial/ethnic inequalities in health and development throughout life and across generations [ 37 , 38 ]. In the context of this study’s primary outcomes within school settings, racism and racial discrimination experienced by both the parents and the children are likely to contribute towards explaining observed racial/ethnic inequalities in outcomes within classes of disadvantage. Gender discrimination—another system of oppression—is apparent in this study in relation to academic subjects socially considered as typically male or female orientated. For example, results show no difference between Black girls and White boys from the most advantaged class in terms of perceived interest and competence in math but, in this same class, Black girls score much lower than White boys in the math assessment. This difference, not explained by intrinsic or socioeconomic differences, can be contextualized as a consequence of experienced intersecting racial and gender discrimination. The consequences of the intersection between two marginalized identities are found throughout the results of this study when comparing across broad categorizations of race/ethnicity and gender, and in more detailed conceptualizations of minority status. Growing up Black, Latino or White in the US is not the same for boys and girls, and growing up as a boy or a girl in America does not lead to the same outcomes and opportunities for Black, Latino and White children as they become adults. With this study’s approach of intersectionality one can observe the complexity of how gender and race/ethnicity intersect to create unique academic and non-academic outcomes. This includes the contrasting results found for Black and Latino boys, when compared to White boys, which show very few examples of poorer outcomes among Latino boys, but several instances among Black boys. Results also show different racialization for Black and Latina girls. Latina girls, but not Black girls, report higher internalizing behavior than White boys, whereas Black girls, but not Latina girls, report higher self-concept than White boys. Black boys also report higher self-concept and lower internalizing behavior than White boys, findings that mirror research on self-esteem among Black adolescents [ 74 , 75 ]. In cognitive assessments, intersecting racial/ethnic and gender differences emerge across classes of disadvantage. For example, Black girls in all four classes score lower on science scores than White boys, but only Latina girls in the most advantaged class score lower than White boys. Although one can observe differences in the racialization of Black and Latino boys and girls across classes of disadvantage, findings about broad differences across Latino children compared to Black and White children should be interpreted with caution. The Latino ethnic group is a large, heterogeneous group, representing 16.7% of the total US population [ 76 ]. The Latino population is composed of a variety of different sub-groups with diverse national origins and migration histories [ 77 ], which has led to differences in sociodemographic characteristics and lived experiences of ethnicity and minority status among the various groups. Differences across Latino sub-groups are widely documented, and pooled analyses such as those reported here are masking differences across Latino sub-groups, and providing biased comparisons between Latino children, and Black and White children.

Poorer performance of girls and racial/ethnic minority students in science and math assessments (but not in self-perceived competence and interest) might result from stereotype threat, whereby negative stereotypes of a group influence their member’s performance [ 78 ]. Stereotype threat posits that awareness of a social stereotype that reflects negatively on one's social group can negatively affect the performance of group members [ 35 ]. Reduced performance only occurs in a threatening situation (e.g., a test) where individuals are aware of the stereotype. Studies show that early adolescence is a time when youth become aware of and begin to endorse traditional gender and racial/ethnic stereotypes [ 79 ]. Findings among youth parallel findings among adult populations, which show that adult men are generally perceived to be more competent than women, but that these perceptions do not necessarily hold for Black men [ 80 ]. These stereotypes have strong implications for interpersonal interactions and for the wider structuring of systemic racial/ethnic and gender inequalities. An example of the consequences of negative racial/ethnic and gender stereotypes as children grow up is the well-documented racial/ethnic and gender pay gap: women earn less than men [ 81 ], and racial/ethnic minority women and men earn less than White men [ 82 ].

In addition to the focus on intersectionality, a strength of this study is its person-centered methodological approach, which incorporates measures of advantage and disadvantage across individual and contextual levels through nine years of children’s socialization. Children live within multiple contexts, with risk factors at the family, school, and neighborhood level contributing to their development and wellbeing. Individual risk factors seldom operate in isolation [ 83 ], and they are often strongly associated both within and across levels [ 84 ]. All risk factors captured in the latent class analyses have been independently associated with increased risk for academic problems [ 10 , 71 , 85 , 86 ], and given that combinations of risk factors that cut across multiple domains explain the association between early risk and later outcomes better than any isolated risk factor [ 83 , 84 ], the incorporation of person-centered and intersectionality approaches to the study of racial/ethnic, gender, and socioeconomic inequalities across school outcomes provides new insight into how children in marginalized social groups are socialized in the early life course.

Conclusions

The contrasting outcomes between racial/ethnic and gender minorities in self-assessment and socioemotional outcomes, as compared to standardized assessments, provide support for the detrimental effect that intersecting racial/ethnic and gender discrimination have in patterning academic outcomes that predict success in adult life. Interventions to eliminate achievement gaps cannot fully succeed as long as social stratification caused by gender and racial discrimination is not addressed [ 87 , 88 ].

Supporting Information

S1 file. supporting tables..

Table A: Class characteristics. Table B: Associations between race/ethnicity and gender groups and assigned class membership (membership to Classes 1, 2 or 4 as compared to Class 3: Individually and Contextually Wealthy).

https://doi.org/10.1371/journal.pone.0141363.s001

Acknowledgments

This work was funded by an ESRC grant (ES/K001582/1) and a Hallsworth Research Fellowship to LB. Most of this work was conducted while LB was a visiting scholar at the Institute for Social Research, University of Michigan. She would like to thank them for hosting her visit and for the support provided.

Author Contributions

Conceived and designed the experiments: LB. Performed the experiments: LB. Analyzed the data: LB. Wrote the paper: LB NP.

• 1. Jencks C, Phillips M. The Black-White Test Score Gap. Washington, D.C.: Brookings Institution Press; 1998.
• 2. (NCES) NCfES. The Nation’s Report Card: Science 2011(NCES 2012–465). Washington, D.C.: Institute of Education Sciences, U.S. Department of Education, 2012.
• 3. (NCES) NCfES. The Nation’s Report Card: A First Look: 2013 Mathematics and Reading (NCES 2014–451). Washington, D.C.: Institute of Education Sciences, U.S. Department of Education, 2013.
• View Article
• Google Scholar
• PubMed/NCBI
• 12. Ogbu J. Low performance as an adaptation: The case of blacks in Stockton, California. In: Gibson M, Ogbu J, editors. Minority Status and Schooling. New York: Grand Publishing; 1991.
• 41. Coley R. Differences in the gender gap: Comparisons across racial/ethnic groups in education and work. Princeton, NJ: Educational Testing Service, 2001.
• 47. Hankivsky O, Cormier R. Intersectionality: Moving women’s health research and policy forward. Vancouver: Women’s Health Research Network; 2009.
• 48. Dhamoon K, Hankivsky O. Why the theory and practice of intersectionality matter to health research and policy. In: Hankivsky O, editor. Health Inequities in Canada: Intersectional Frameworks and Practices. Vancouver: UBC Press; 2011. p. 16–50.
• 50. Crenshaw K. Demarginalizing the intersection of race and sex: a black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum. 1989:139–67.
• 62. Tourangeau K, Nord C, Lê T, Sorongon A, Najarian M. Early Childhood Longitudinal Study, Kindergarten Class of 1998–99 (ECLS-K), Combined User’s Manual for the ECLS-K Eighth-Grade and K–8 Full Sample Data Files and Electronic Codebooks (NCES 2009–004). Washington, DC.: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education., 2009.
• 63. Marsh HW. Self Description Questionnaire (SDQ) II: A theoretical and empirical basis for the measurement of multiple dimensions of adolescent self-concept. An interim test manual and a research monograph. Sydney: University of Western Sydney: 1992.
• 64. Asparouhov T, Muthén B. Auxiliary Variables in Mixture Modeling: 3-Step Approaches Using Mplus. Mplus Web Notes [Internet]. 2013 April 2014. Available from: www.statmodel.com/examples/webnotes/webnote15.pdf ‎.
• 67. Dayton C. Latent class scaling analysis. Thousand Oaks, CA: Sage, 1998.
• 70. Muthén L, Muthén B. Mplus User's Guide. Seventh Edition. Los Angeles, CA.: 2012.
• 72. Jackson P, Williams D. The intersection of race, gender, and SES: Health paradoxes. In: Schulz A, Mullings L, editors. Gender, Race, Class, & Health: Intersectional Approaches. San Francisco, CA: Jossey-Bass; 2006. p. 131–62.
• 76. Ennis S, Rios-Vargas M, Albert N. The Hispanic Population: 2010. United Census Bureau, 2011.
• 88. Rouse C, Brooks-Gunn J, McLanahan S. School Readiness: Closing racial and ethnic gaps. Washington, DC: Brookings Press, 2005.

Peer mentorship and professional identity formation: an ecological systems perspective

• Lalit Kumar Radha Krishna 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ,
• Nur Amira Binte Abdul Hamid 2 ,
• Gillian Li Gek Phua 3 , 4 , 9 ,
• Stephen Mason 6 ,
• Ruaraidh Hill 8 ,
• Crystal Lim 10 ,
• Simon Yew Kuang Ong 2 , 4 , 11 ,
• Eng Koon Ong 2 , 3 , 4 , 12 &
• Halah Ibrahim 13  

BMC Medical Education volume  24 , Article number:  1007 ( 2024 ) Cite this article

Metrics details

Mentoring can help shape how medical students think, feel, and act as physicians. Yet, the mechanism in which it influences this process of professional identity formation (PIF) remains poorly understood. Through the lens of the ecological systems theory, this study explores the interconnected and dynamic system of mentoring relationships and resources that support professional development and growth within the Palliative Medicine Initiative (PMI), a structured research peer mentoring program.

A secondary analysis of transcripts of semi-structured interviews with peer mentors and mentees and a review of their mentoring diaries was conducted to explore the impact of participation in a longitudinal peer mentoring program on both mentees and peer mentors on their personal and professional development through the lens of the mentoring ecosystem model. The Systematic Evidence-Based Approach was adapted to analyze the data via content and thematic analysis.

Eighteen mentees and peer mentors participated and described a supportive community of practice within the research program, with discrete micro-, meso-, and macro-environments that are dynamic, reflexive, and interconnected to form a mentoring ecosystem. Within this ecosystem, reflection is fostered, and identity work is done—ultimately shaping and refining self-concepts of personhood and identity.

This study underscores the nuances and complexities of mentorship and supports the role of the mentoring ecosystem in PIF. A deeper understanding of the multiple factors that converge to facilitate the professional development of mentees can help educators develop and implement structured peer mentorship programs that better support reflective practice and identity work.

Peer Review reports

Introduction

Medical education employs mentoring to foster the development of altruistic, ethical, humanistic, and accountable clinicians through Professional Identity Formation (PIF), or how medical students learn to think, feel, and act as physicians [ 1 , 2 , 3 ]. However, there is a limited understanding of mentoring relationships and the dynamics between mentors, mentees, and the host organizations. The impact of contextual, sociocultural, and programmatic influences on PIF is also often unaddressed [ 4 , 5 , 6 , 7 , 8 ], hampering the effective use of mentoring in medical education [ 4 , 5 , 6 ].

The ecological systems model provides a framework for understanding the multiple factors that directly or indirectly influence behavior and relationships between individuals and between individuals and organizations [ 9 ]. It asserts that a phenomenon such as PIF within the PMI results from a convergence of factors spanning interrelated levels of influence, namely the microsystem (individual), mesosystem (group), exosystem (organizational), macrosystem (cultural and societal), and chronosystem (impact of time and life transitions) [ 9 , 10 , 11 , 12 ].

Through the ecological systems theory [ 13 ], we explore the interconnected and dynamic system of mentoring relationships and resources that support the mentoring environment and PIF within the Palliative Medicine Initiative (PMI), a structured research peer-mentoring program [ 3 , 14 , 15 ]. This study aims to investigate the mentees’ progress in the program and their development of professional identity through the lens of the mentoring ecosystem [ 3 , 14 , 15 ].

The Palliative Medicine Initiative (PMI)

In Singapore, undergraduate medical education typically involves a five-year program leading to a Bachelor of Medicine and Bachelor of Surgery (MBBS) degree. Postgraduate medical education is structured, competency-based training in various medical specialties following a United States residency training model [ 16 ].

The PMI is a voluntary research mentoring program based at the National Cancer Centre Singapore (NCCS) that includes medical students and residents from Duke-NUS Medical School, National University of Singapore’s (NUS) Yong Loo Lin School of Medicine (YLLSoM), and the Lee Kong Chian Medical School. Most research projects focus on palliative care, professionalism and PIF, well-being, and medical ethics. The PMI uses a peer mentoring model, which involves collaboration between trainees of similar training stages and experiences facilitated by a senior mentor. Mentees who successfully complete at least one mentored research project to publication learn how to mentor, assess, and provide feedback to others as peer mentors [ 11 ]. The PMI’s research mentoring program is designed on best practices derived from prior systematic reviews on mentoring relationships [ 5 , 17 ], and studies of the mentoring environment [ 18 ], mentor training [ 19 , 20 ], and ethical issues in mentoring [ 21 , 22 , 23 ]. The PMI has supported over 100 mentee-led publications in peer-reviewed journals over the past 10 years [ 4 , 24 ]. This success has been attributed to the PMI’s mentoring structure and culture that nurture enduring and personalized mentoring relationships [ 5 , 17 , 25 ].

The PMI has several key design elements [ 14 , 15 ]. First, it is a structured program with a formal curriculum overseen by the Divisions of Supportive and Palliative Care and Cancer Education at NCCS (host organization). The host organization ensures a learning environment with a consistent mentoring approach, clearly delineated expectations and codes of practice, and competency-based assessments [ 4 , 5 , 6 ]. Next, the PMI is designed around structured research mentoring stages: mentee initiation, matching, initial meetings, data gathering, data analysis, manuscript writing, submission, and post-submission [ 26 ]. Each stage is characterized by clear competencies to be achieved and objectives to be met. Progress through the stages creates a mentoring trajectory. Further, the program employs a blend of mentoring, coaching, career guidance, and role modeling to support mentors, peer mentors, and mentees. Finally, peer mentors and mentees complete mentoring diaries that map their development and encourage reflective practice [ 27 ]. The mentoring diaries are reviewed by PMI faculty, who assess the quality of mentoring interactions and offer advice, mentoring support, and counselling support as needed [ 28 ].

Mentoring ecosystem

The PMI encompasses a mentoring environment comprised of formal, informal, and hidden (contextual, sociocultural, ethical, and professional) influences. Together with the mentoring structure, these comprise the mentoring ecosystem [ 29 ]. The mentoring ecosystem impacts, and is impacted by, the progress of individual stakeholders. Each stakeholder operates within a discrete micro-environment [ 3 ]. Each micro-environment is shaped by five aspects of each stakeholder: 1) beliefs and principles (belief system); 2) motivations, attitudes, abilities, and experience (narratives) [ 30 , 31 , 32 , 33 , 34 , 35 ]; 3) clinical, academic, cultural, organizational, and societal spheres (contextual considerations) [ 17 ]; 4) developing skills, knowledge, motivations, levels of engagement, and evolving goals (developing competencies); and 5) personal development [ 18 ].

As personal micro-environments become embedded in the mentoring ecosystem, they progress to a more central position in the program as they interact with the program’s culture and structure and with other micro-environments [ 36 , 37 , 38 , 39 , 40 , 41 ]. Interactions between individual micro-environments create the meso-environment [ 42 ]. Within the meso-environment, each stakeholder’s evolving belief systems, contextual considerations, developing competencies, and the nature and dynamics of pre-existing relationships with one another impact other surrounding micro-environments. The program structure includes codes of practice and boundaries to prevent breaches of professional standards.

The mentoring culture and structure create the macro-environment, which helps align “identities in a manner that is congruent with the regime of competence within that… institution” [ 43 ] . This process of integrating the PMI’s values, beliefs, and principles and nurturing mentees to become peer mentors and peer mentors to become mentors—the socialization process—is critical to PIF [ 36 ]. In some cases, it involves “crossing a threshold leading to a change in knowing, doing, being, and future learning possibilities” [ 44 ]. Identity work, the active process and adaptations made to develop and shape professional identity, is guided by mentoring support and feedback. Pratt et al. [ 45 ] suggest that there are two forms of identity work. The first is an inexperienced mentee adopting a former identity to ‘splint’ and protect their vulnerable, developing professional identity. The second is a more experienced mentee calling upon their perception of an ideal physician to ‘permanently patch up holes’ in their existing identity (patching) .

Methodology

This study is a secondary analysis of narratives from mentoring diaries and transcripts from semi-structured interviews conducted in 2021 to explore mentoring experiences within the PMI. In this study, we seek to provide deeper insights into contextual and programmatic influences on PIF to answer our research question: does the mentoring ecosystem model explain how PIF evolves within the PMI?

We adopt Krishna’s Systematic Evidence-Based Approach (SEBA) methodology to guide our efforts. SEBA enhances the rigor and transparency of research by combining systematic review techniques with qualitative synthesis [ 7 , 14 , 15 , 25 , 26 ]. The key components include a systematic literature review, qualitative data collection through semi-structured interviews, thematic analysis, and integrating the qualitative findings with existing literature [ 7 , 14 , 15 , 25 , 26 ]. This approach allows us to explore the contextual and programmatic influences on PIF within the PMI and provides a structured framework to support our findings.

The series of semi-structured interviews with individual mentees and peer mentors conducted in 2021 were triangulated against mentoring diaries and recently published accounts of mentee and peer mentor experiences in the PMI [ 3 , 4 , 26 , 46 ]. Ethics approval was obtained from the SingHealth Combined Institutional Review Board (CIRB Ref 2020/3056).

Systematic Evidence-Based Approach ( SEBA )

An expert team comprised of a medical librarian, local educational experts and clinicians, and PMI alumni oversaw each aspect of the research process to ensure consistency, reproducibility, and transparency. Semi-structured interview questions were based on published accounts of mentoring experiences in the PMI [ 4 , 46 ] and a recent review of mentoring programs, practices, and assessments [ 19 ]. The interview guide was also influenced by theories of communities of practice [ 31 , 42 ] and PIF [ 8 , 36 , 47 , 48 , 49 , 50 , 51 ].

Data collection

We conducted a purposive sampling of mentees and peer mentors actively involved in the PMI who had successfully completed at least one project to publication. Email invitations containing a participant information sheet and consent forms were sent to eligible participants. The invitations emphasized participant anonymity and the right to withdraw from the study at any point without prejudice. Upon the receipt of signed consent forms, semi-structured interviews were arranged with individual mentees and peer mentors. The interviews were conducted by two non-clinician researchers who had no dependent relationship with the participants and were briefed on the study aims. The interviews took approximately 30 to 45 min each and were conducted over the Zoom video conferencing platform between February and May 2021 in quiet offices to ensure privacy and facilitate in-depth exploration of personal beliefs and experiences. Verbal consent was obtained before interviews were audiotaped. The audio recordings were transcribed verbatim using NVivo 12 software [ 52 ] and the transcripts were anonymized. Mentees and peer mentors who consented to have their mentoring diaries analyzed had their entries anonymized by independent research team members not involved in the PMI or the semi-structured interviews. Data collection and analysis were conducted concurrently and led to iterative adjustments to the interview guide. Participant recruitment continued until no new themes emerged.

Data analysis

From August through September 2023, the de-identified transcripts and diaries were reviewed and coded by two independent teams. Each team consisted of 3 mentees and was led by a peer mentor. A senior clinician supervised the data analysis. Inductive and deductive analysis were used concurrently. Using Braun and Clarke [ 53 ] qualitative data analysis methodology, one team engaged in iterative and cyclic constant comparison analysis. Any disagreements were negotiated through in-depth conversations. Through consensus, themes were identified and then applied to all transcripts. A codebook was maintained to enhance the reproducibility and trustworthiness of the data. The second group employed Hsieh and Shannon’s [ 54 ] approach to directed content analysis. Using Krishna et al.’s [ 3 ] study and Teo et al.’s [ 29 ] review, a priori coding categories were identified and applied to the transcripts to help confirm and expand the ecological systems theory to the mentoring setting [ 13 ]. The reviewers within each team achieved consensus on their analyses through discussion and negotiation before comparing with the other team. Conducting both thematic and content analyses allowed us to omit calculating Cohen’s Kappa to gauge the degree of consensus between different researchers [ 55 ].

Next, the overlapping themes and categories from each set of transcripts were combined to construct overarching themes/categories [ 56 , 57 , 58 ]. This process was repeated for the peer mentor and mentee mentoring diaries. Finally, the themes/categories derived from the mentoring diaries and interviews were compared, creating the domains that framed the discussion.

Team reflexivity

As both researchers and participants in the PMI, we acknowledge our dual roles in the study. Our insider status provided valuable insights into the context and nuances of the mentorship program but also risked introducing bias. We implemented several strategies to mitigate this risk, including regular team discussions to challenge assumptions and interpretations and proactively distinguish between our personal experiences and the experiences reported by study participants. We also engaged clinicians and educators external to the PMI as co-researchers and co-authors to help leverage our insider knowledge while maintaining critical distance.

Of 18 peer mentors and 10 mentees eligible to participate in the study, twelve peer mentors and seven mentees were recruited for the semi-structured interviews. Tables 1 and 2 depict participant demographics and their experience within the PMI.

Domain 1. mentoring ecosystem

Features of a community of practice were reported [ 59 ]. M4 described the development of a social network of individuals who shared and developed overlapping knowledge bases, values, and experiences:

“At first, I was rather stressed writing the paper. But then, as you communicate with the other mentees that were on the same stage with you, you realize that everybody is equally stressed and equally lost. And that kind of gave some comfort because we were stressed together. And then we would freak out together. So, it was a bit like a community that you could find comfort in, even though everybody was lost together. But we could also find our way out and explore and work things out together. So, it was a very supportive system in the sense that although it might be stressful, we knew that we were not alone.” M4

This domain further contains the subdomains of micro-, meso-, and macro-environments, consistent with the mentoring ecosystem.

Sub-domain 1. Micro-environment

Mentees and peer mentors revealed the internal elements shaping their micro-environments. M1’s vignette reflected on how individual characteristics and beliefs could affect the micro-environment:

“Initially, I felt it was very hard to say no. So even if I wasn’t confident in the project or keen, I would still do it anyway because I...am a people pleaser… I did not want to disappoint my mentor. So initially, it was more of like whatever my mentor wanted me to do, I’d just say yes to it. Even though I didn’t know what to do [or] feel like doing it…” M1

Internal motivations included the mentees’ desire to gain opportunities and refine their skills in order to advance their research ambitions and enhance their CVs:

“I wanted to learn how to properly do a research paper, learn the relevant skills.” M10

“We all wanted to take up every single thing that came our way. So, for me then, it was really maximizing all the opportunities that came my way and trying to do as much as I could.” M4

At times, participants expressed the chasm between the expectations of their identity as a peer mentor and their personal dispositions:

“So, because of who I am and my character, I tend to [be] really lighthearted... But when it comes to being a near-peer, ... because I’m so lighthearted…even though I’m leading a project, I do not see myself as a leader, as someone who tells people what to do… That affected my mentorship or my ability to lead.” NP1

Moreover, changes in motivations, competencies, and maturing mentoring relationships were influenced by changes in contextual and personal circumstances and evolved over time:

“At first, I had a lot of doubts that maybe this wasn’t for me, because I really didn’t know what was happening… but after that, I decided to give it another try, to take on a few more papers. Throughout the process, I realized that actually I do understand if I put in the effort to seek clarifications earlier and also communicate more with the seniors to find out more on what’s happening and what is required of me.” M4

“I guess at the start when you’re new, you try to learn and pick up all these skills you need to write a paper. But now, your goals change a little because you actually want to write something meaningful—write something that will benefit, or think will benefit, the community in the future.’ M10

Sub-domain 2. Meso-environment

Mentees and peer mentors acknowledged the influence of interactions with other mentees, peer mentors, and other stakeholders in nurturing their micro-environments and in forming meso-environments. The formation of these meso-environments built confidence and relationships, guided personalized support, and changed thinking and conduct, ultimately informing their professional identity.

Mentees and peer mentors believed that their mentors’ micro-environments were informed by their respective mentoring experience, working style, characteristics, motivations, and clinical, contextual, and personal factors:

“I think my senior mentors were quite astute and quite experienced, and wise. So, they knew when something was happening in my personal life and helped me...” M2

“I think it’s helpful when our mentors do more than just guide us in writing the paper but challenge us to question why we do certain things .” M Diary 1

The host organization’s structure, culture, approach, oversight, and ability to accommodate choice to personalize the mentoring trajectory and experiences shaped the meso-environment:

“I think, generally, this program has given me a lot of freedom to communicate... and prioritize research.” M3

“The PMI allowed talk about other stuff, such as ...medical school, career guidance, advice, even ... personal life...” NP1

Sub-domain 3. Macro-environment

The macro-environment encompassed the program’s collaborative environment and the influence of culture, nature, and dynamics of mentoring interactions. The collaborative culture of the PMI promotes open communication and mutual support, which facilitate professional growth:

“The nature of the work as a doctor is working in a team. So, I think this idea of being able to communicate effectively with your team members and provide constructive feedback will be important in any team-based work. At the same time, part of this culture or spirit of being a doctor is that many times we learn on the job. So, I think the same sort of spirit of giving and teaching are sort of being passed down from the senior. In the same way, I think I see doctors as also having a role of teaching, whether it’s to medical students or to peers”. NP3

“It has made me more aware of the importance of research in the field of medicine and how research is a good avenue to give back to the medical community… and create opportunities for medical students to gain exposure and network.” M Diary 4

The micro-, meso-, and macro-environments formed the mentoring ecosystem (Fig.  1 ).

Adapted Mentoring Ecosystem. The green circles symbolize the mentees, light yellow circles reflect peer mentors and dark brown circles represent the mentor

Domain 2. Professional identity formation

Sub-domain 1. threshold events.

Threshold events invite changes in thinking and conduct, as well as enhanced possibilities in future learning. Participants explored how participation in the PMI directly impacted their professional identity:

“I think research became a significant part of my medical school identity… it provides me with some meaning beyond just academics. So not only am I able to gain research skills, I also feel that I’m playing a part in helping the medical community through research. And getting to know my peers who are in the projects better.” M3

Mentoring diaries and interviews provided glimpses of the influence of the program on the thinking, decision-making, and conduct of mentees and peer mentors.

“I feel before being a near-peer, this idea of being genuine, true to who I am, and being supportive and generous in giving... still stayed the same. But I think some of these got more reinforced. Let’s say this idea of being generous or paying it forward or giving back to people got reinforced during my process as a near-peer.” NP3

“I think everyone has a certain level of communication skills. And I think that the process of me leading the team helped to strengthen that.” NP4

Sub-domain 2. Identity work

The participants realized that, at times, adaptations were necessary to maintain their overall identity. NP2, for instance, recalled how they adapted their working style to uphold the identity of a competent peer mentor:

“I did feel I had to alter my working style at times. It was about striking a balance. At times, you may need to take a harder approach to get them to respond or turn up work in time. Because if you are too lax, they may keep pushing deadlines, but at the same time, there’s also a balance in terms of not being too harsh on people, and also giving enough time for them to discover things for themselves.” NP2

With greater experience, access to longitudinal mentoring support, and growing knowledge of the mentoring process, environment, and relationships, participants reported greater confidence and competence, which often extended beyond their role in the PMI.

“Although I sometimes still find myself a bit lost, or having some struggles, I feel that I’m capable of finding a way for myself to get through them. To have more confidence, persevere, and tell myself that I’m able to do well eventually.” M3

“Initially, I think when I was a mentee, I was just more focused on my own development. Subsequently, when I see from the eyes… of a near-peer, I think the idea was also to see how I can support other people in their development, how I can be more sensitive to what their needs [are] and provide advice…. So I think the perspective changed from focusing on myself to focusing on others.” NP3

The participants recognized how their involvement in the PMI helped to shape their professional identities. NP2 and NP10 described how interactions with their mentor influenced their perceptions of an ideal physician:

“The influence from a mentor has changed the way I look at certain specialties and changed my outlook on life. It has made me more focused on being less materialistic and more on fields of work where I can provide a listening ear to people, and generally provide more holistic care because that’s what my mentor did for me.” NP2

“I think one of the greater positive things that my mentors in the PMI have impressed upon me is this amazing sense of patience and really caring about what others are going through.” NP10

Sub-domain 3. Reflection

Peer mentors reflected as they deliberated on their options more than their less experienced mentees. These reflections assumed two forms: reflection-in-action [ 60 ] and reflection-on-action [ 61 ]. Reflection-in-action informed advanced decisions on adaptations to the belief system:

“I picked up the importance of how to set goals effectively, not just by seeing my mentors do it, but also through the research that I’m involved with, and seeing the effects and importance of it right from the beginning.” NP1

“The one point that is immediately relevant to me now is how my research on professional identity formation (PIF) has made me very acutely aware of how I am being influenced during my clinical postings. I am now able to put a name to what I am experiencing or relate it to a theory.” NP Diary 5

Conversely, when critical events were not recognized at the moment or when responses were felt to be inadequate, peer mentors and mentees reveal reflection-on-action or reflection after the fact. This practice was especially evident amongst mentees. Lessons learned influenced thinking and planning and informed later practice, as described in the following accounts:

“When we first started, we did not always ask for clarifications, because we thought that this [was] something that we should know already. We tried to figure it out ourselves but by the time we tried to… we realized that none of us [knew how to] do it and we were already in too deep.” M4

“When I face very difficult or bad experiences where there are ethical issues, or when I get scolded or receive criticism, I will always reflect on how I can go about changing and going further to become better...” NP3

Sub-domain 4. Splinting and patching

Mentees and peer mentors also unveiled instances of identity work through splinting and patching . A less experienced mentee discusses an example of splinting:

“If there are other more experienced people on the team, I will tend to take a step back and just listen to and follow instructions.” M4

Meanwhile, NP1’s refinement of their mentoring approach based on role modeling provided an example of patching :

“ From mentoring and leadership experiences, I realized that I do not see myself as someone who tells people what to do. That affected my mentorship or my ability to lead… So what I learned [was] the need to demand a certain sort of command over people, especially when you are leading a project because, without a proper hierarchy, or a proper flow or chain of command, it does affect… the process. ” NP1.

This study explores the multiple converging factors that support the development of mentees’ and peer mentors’ professional identities as they navigate stages of the mentoring trajectory within the mentoring ecosystem of a peer mentoring program. This professional development is fostered through the interaction of individual, group, and system-level facets. We have previously described PIF within the PMI, focusing on the individual experiences of the mentees and peer mentors [ 11 ]. Here, the multiple levels of the ecological systems framework help to advance our understanding of the complex factors that contribute to the evolution of PIF [ 9 ]. The theory has been recently used to better understand interactions in health professions education. Hamwey et al. used the model to illustrate the numerous factors that impact the academic performance of health professions learners [ 62 ]. Bluteau and colleagues demonstrated that students in a longitudinal interprofessional education program are better able to consider the factors that affect healthcare from individual (micro) to group (meso) and, ultimately, to higher organizational (exo) and cultural (macro) levels as they progressed through their training [ 63 ].

Examining complexities in an interrelated manner is a strength of systems theories [ 9 ]. Accordingly, our study highlighted that the components of the mentoring ecosystem are dynamic and interconnected. Contextual factors, such as a participant’s personal characteristics or motivation, play an important role in shaping mentoring relationships and outcomes and can both enable and constrain mentoring and identity formation. The participants acknowledged the role of stakeholders, including the PMI program itself, in providing resources, opportunities, and a support network/community within the mentoring ecosystem. Exposure to the PMI’s belief system and culture also impacts the mentoring experience, progress, and outcomes.

This adapted mentoring ecosystem also considers the mentee’s reinvolvement in the PMI as a peer mentor, where they revisit the same mentoring stages, albeit in different roles that accord more responsibilities. This extended mentoring trajectory toward the more central role in the PMI that mentors usually play provides a better appreciation of the impact of interactions between stakeholders and the effects of reflection on new life experiences upon individual belief systems as professional identity is formed. It also provides further depth to our appreciation of mentoring processes.

Notably, the trajectory within the mentoring ecosystem is not rigid. Rather, it acknowledges variations in the belief systems, narratives, contextual considerations, developing competencies, and environmental and contextual considerations of each member. It also impacts and is impacted by the mentoring structure, culture, organization, and the healthcare and education system in which it exists. To guide this personalized, longitudinal, and holistic support, the process relies on stage-based and competency-based assessments that can direct trained mentors and peer mentors, as well as a mentoring structure that limits external influences upon this process and confines responses within program expectations and codes of practice. This fosters greater confidence and the ability to ‘think on your feet’ or practice reflection-in-action [ 9 , 10 , 11 , 12 ]. With more experience, mentees and peer mentors move towards adopting and trialing the desired characteristics role modeled by senior mentors ( patching ) [ 45 ]. Perhaps just as importantly, the theory highlights how reflection-in-action and identity work both influence, and are influenced by, the mentee’s ability to analyze, reflect upon, and learn from interactions within the meso-environment and the macro-environment. The mentee’s ability ultimately shapes the developing self-concepts of personhood and identity.

The insights provided suggest similarities with Communities of Practice (CoP), “a persistent, sustaining social network of individuals who share and develop an overlapping knowledge base, set of beliefs, values and history and experiences focused on a common practice and/or enterprise” [ 8 ]. This notion is underscored by the presence of the mentoring ecosystem’s structured approach and mentoring trajectory that moves participants from legitimate peripheral participation to a central role at the heart of the program (Fig.  1 ). This movement is fostered by longitudinal and personalized mentoring support and a nurturing mentoring environment. Imagining the mentoring ecosystem as a CoP, a key element in nurturing PIF, allows a deeper understanding of mentoring’s impact on PIF.

Our findings have educational implications. The ecological systems theory underscores the importance of considering the interaction of various factors and stakeholders when designing a mentoring program, including ensuring mentor support, comprehensive peer mentor training, and a nurturing organizational culture. This holistic approach acknowledges the interconnectedness of the mentoring ecosystem, where each component, from individual relationships to broader cultural influences, plays a vital role in supporting PIF.

Limitations

The use of single time-point interviews and retrospective accounts as the primary source of data in this study is susceptible to recall and social desirability biases [ 64 ]. This is suggested by the predominantly positive mentoring narratives, with little discussion of the known hierarchal and unequal power distributions inherent to many mentoring relationships [ 65 ]. Further, although professional identity formation occurs within the context of cultural and societal norms and expectations, particularly within a multi-ethnic and multi-cultural country like Singapore, we did not explore the impact of the mentees’ or peer mentors’ gender or socio-cultural backgrounds on their experiences within the PMI or on their mentoring interactions. There are also limitations due to the small sample size and the depth of the data collected.

In this study of mentorship within the PMI, the mentoring ecosystem model underscores the nuances and complexities of mentorship and provides a framework for PIF. A deeper understanding of the multiple factors that converge to facilitate the professional development of mentees can help educators develop and implement structured peer mentorship programs that better support reflective practice and identity work.

Availability of data and materials

The dataset(s) supporting the conclusions of this article is(are) included within the article (and its additional file(s)).

Abbreviations

• Professional identity formation

Palliative medicine initiative

National cancer centre Singapore

Systematic evidence-based approach

• Community of practice

Cruess RL, Cruess SR, Boudreau JD, Snell L, Steinert Y. Reframing medical education to support professional identity formation. Acad Med. 2014;89(11):1446–51.

Article   Google Scholar  

Sarraf-Yazdi S, Teo YN, How AEH, Teo YH, Goh S, Kow CS, et al. A scoping review of professional identity formation in undergraduate medical education. J Gen Intern Med. 2021;36(11):3511–21.

Krishna LKR, Tan LHE, Ong YT, Tay KT, Hee JM, Chiam M, et al. Enhancing mentoring in palliative care: an evidence based mentoring framework. J Med Educ Curric Dev. 2020;7:2382120520957649.

Krishna LKR, Toh YP, Mason S, Kanesvaran R. Mentoring stages: A study of undergraduate mentoring in palliative medicine in Singapore. PLoS ONE. 2019;14(4): e0214643.

Sng JH, Pei Y, Toh YP, Peh TY, Neo SH, Krishna LKR. Mentoring relationships between senior physicians and junior doctors and/or medical students: A thematic review. Med Teach. 2017;39(8):866–75.

Tan YS, Teo SWA, Pei Y, Sng JH, Yap HW, Toh YP, et al. A framework for mentoring of medical students: thematic analysis of mentoring programmes between 2000 and 2015. Adv Health Sci Educ. 2018;23(4):671–97.

Toh RQE, Koh KK, Lua JK, Wong RSM, Quah ELY, Panda A, et al. The role of mentoring, supervision, coaching, teaching and instruction on professional identity formation: a systematic scoping review. BMC Med Educ. 2022;22(1):531.

Cruess RL, Cruess SR, Boudreau JD, Snell L, Steinert Y. A Schematic Representation of the Professional Identity Formation and Socialization of Medical Students and Residents: A Guide for Medical Educators. Acad Med. 2015;90(6):718–25.

Boud D, Keogh R, Walker D, editors. Reflection: Turning Experience into Learning. 1st ed: Routledge; 1985.

Schön DA. Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. San Francisco, CA, US: Jossey-Bass; 1987. xvii, 355-xvii.

Epstein RM, Siegel DJ, Silberman J. Self-monitoring in clinical practice: a challenge for medical educators. J Contin Educ Health Prof. 2008;28(1):5–13.

Iqbal MZ. Reflection-in-Action: A Stimulus Reflective Practice for Professional Development of Student Teachers. Bulletin of Education and Research. 2017;39(2):65-82

Bronfenbrenner U. The ecology of human development: Experiments by nature and design: Harvard university press; 1979.

Krishna LKR, Pisupati A, Ong YT, Teo KJH, Teo MYK, Venktaramana V, Quek CWN, Chua KZY, Raveendran V, Singh H, Wong SLCH, et al. Assessing the effects of a mentoring program on professional identity formation. BMC Med Educ. 2023;23(1):799.

Krishna LKR, Pisupati A, Teo KJH, Teo MYK, Quek CWN, Chua KZY, Venktaramana V, Raveendran V, Singh H, et al. Professional identity formation amongst peer-mentors in a research-based mentoring programme. BMC Med Educ. 2023;23(1):787.

Archuleta S, Ibrahim H, Stadler DJ, Shah NG, Chew NW, Cofrancesco J Jr. Perceptions of Leaders and Clinician Educators on the Impact of International Accreditation. Acad Med. 2015;90(11 Suppl):S83-90.

Lim SYS, Koh EYH, Tan BJX, Toh YP, Mason S, Krishna LKR. Enhancing geriatric oncology training through a combination of novice mentoring and peer and near-peer mentoring: A thematic analysis ofmentoring in medicine between 2000 and 2017. J Geriatr Oncol. 2020;11(4):566–75.

Hee JM, Yap HW, Ong ZX, Quek SQM, Toh YP, Mason S, Krishna LKR. Understanding the mentoring environment through thematic analysis of the learning environment in medical education: a systematic review. J Gen Intern Med. 2019;34:2190–9.

Ng YX, Koh ZYK, Yap HW, Tay KT, Tan XH, Ong YT, et al. Assessing mentoring: A scoping review of mentoring assessment tools in internal medicine between 1990 and 2019. PLoS ONE. 2020;15(5):e0232511.

Sheri K, Too JYJ, Chuah SEL, Toh YP, Mason S, Radha Krishna LK. A scoping review of mentor training programs in medicine between 1990 and 2017. Med Educ Online. 2019;24(1):1555435.

Kow CS, Teo YH, Teo YN, Chua KZY, Quah ELY, Kamal N, et al. A systematic scoping review of ethical issues in mentoring in medical schools. BMC Med Educ. 2020;20(1):246.

Lee FQH, Chua WJ, Cheong CWS, Tay KT, Hian EKY, Chin AMC, et al. A Systematic Scoping Review of Ethical Issues in Mentoring in Surgery. J Med Educ Curric Dev. 2019;6:2382120519888915.

Cheong CWS, Chia EWY, Tay KT, Chua WJ, Lee FQH, Koh EYH, et al. A systematic scoping review of ethical issues in mentoring in internal medicine, family medicine and academic medicine. Adv Health Sci Educ. 2020;25:415–39.

Radha Krishna LK, Renganathan Y, Tay KT, Tan BJX, Chong JY, Ching AH, et al. Educational roles as a continuum of mentoring’s role in medicine – a systematic review and thematic analysis of educational studies from 2000 to 2018. BMC Med Educ. 2019;19(1):439.

Venktaramana V, Ong YT, Yeo JW, Pisupati A, Krishna LKR. Understanding mentoring relationships between mentees, peer and senior mentors. BMC Med Educ. 2023;23(1):76.

Ong YT, Quek CWN, Pisupati A, Loh EKY, Venktaramana V, Chiam M, et al. Mentoring future mentors in undergraduate medical education. PLoS ONE. 2022;17(9):e0273358.

Tay KT, Tan XH, Tan LHE, Vythilingam D, Chin AMC, Loh V, et al. A systematic scoping review and thematic analysis of interprofessional mentoring in medicine from 2000 to 2019. J Interprof Care. 2021;35(6):927–39.

Chia EWY, Tay KT, Xiao S, Teo YH, Ong YT, Chiam M, et al. The Pivotal Role of Host Organizations in Enhancing Mentoring in Internal Medicine: A Scoping Review. Journal of Medical Education Curricular Development. 2020;7:2382120520956647.

Teo KJH, Teo MYK, Pisupati A, Ong RSR, Goh CK, Seah CHX, et al. Assessing professional identity formation (PIF) amongst medical students in Oncology and Palliative Medicine postings: a SEBA guided scoping review. BMC Palliat Care. 2022;21(1):200.

Crampton PES, Afzali Y. Professional identity formation, intersectionality and equity in medical education. Med Educ. 2021;55(2):140–2.

Wyatt TR, Balmer D, Rockich-Winston N, Chow CJ, Richards J, Zaidi Z. ‘Whispers and shadows’: A critical review of the professional identity literature with respect to minority physicians. Med Educ. 2021;55(2):148–58.

Chow CJ, Byington CL, Olson LM, Ramirez KPG, Zeng S, López AM. A Conceptual Model for Understanding Academic Physicians’ Performances of Identity: Findings From the University of Utah. Acad Med. 2018;93(10):1539–49.

Surbone A, Baider L. Personal values and cultural diversity. Journal of Medicine and the Person. 2013;11(1):11–8.

Koon OE, Krishna LKR. Perspective from Singapore. NUS Press; 2014.

Ong EK, Krishna LK, Neo PSH. The sociocultural and ethical issues behind the decision for artificial hydration in a young palliative patient with recurrent intestinal obstruction. Ethics & Medicine: An International Journal of Bioethics. 2015;31:39+.

Cruess RL, Cruess SR, Steinert Y. Medicine as a Community of Practice: Implications for Medical Education. Acad Med. 2018;93(2):185–91.

Harvey A, Brown MEL, Byrne MHV, Alexander L, Wan JCM, Ashcroft J, et al. ‘I don’t feel like I’m learning how to be a doctor’: early insights regarding the impact of Covid-19 on UK medical student professional identity. medRxiv. 2021:2021.08.01.21261101.

Hoff TJ, Pohl H, Bartfield J. Creating a learning environment to produce competent residents: the roles of culture and context. Acad Med. 2004;79(6):532–9.

Merton RΚ. The Student-Physician: Introductory Studies in the Sociology of Medical Education. In: Merton RK, Reader GG, Kendall P, editors.: Harvard University Press; 2013. p. 3–80.

Wenger E. Communities of practice: Learning, meaning, and identity. New York, NY, US: Cambridge University Press; 1998. xv, 318-xv, p.

Hee J, Toh YL, Yap HW, Toh YP, Kanesvaran R, Mason S, et al. The Development and Design of a Framework to Match Mentees and Mentors Through a Systematic Review andThematic Analysis of Mentoring Programs Between 2000 and 2015. Mentoring & Tutoring: Partnership in Learning. 2020;28(3):340–64.

Ong YT, Kow CS, Teo YH, Tan LHE, Abdurrahman A, Quek NWS, et al. Nurturing professionalism in medical schools. A systematic scoping review of training curricula between 1990–2019. Med Teach. 2020;42(6):636–49.

Cantillon P, D’Eath M, De Grave W, Dornan T. How do clinicians become teachers? A communities of practice perspective. Adv Health Sci Educ. 2016;21(5):991–1008.

Barradell S, Peseta T. Promise and challenge of identifying threshold concepts: a cautionary account of using transactional curriculum inquiry. J Furth High Educ. 2014;40:1–14.

Google Scholar  

Pratt MG, Rockmann KW, Kaufmann JB. Constructing Professional Identity: The Role of Work and Identity Learning Cycles in the Customization of Identity among Medical Residents. Acad Manag J. 2006;49(2):235–62.

Krishna LKR, Tay KT, Yap HW, Koh ZYK, Ng YX, Ong YT, et al. Combined novice, near-peer, e-mentoring palliative medicine program: A mixed method study in Singapore. PLoS ONE. 2020;15(6):e0234322.

Jarvis-Selinger S, MacNeil KA, Costello GR, Lee K, Holmes CLJAM. Understanding professional identity formation in early clerkship: a novel framework. 2019;94(10):1574–80.

Sawatsky AP, Santivasi WL, Nordhues HC, Vaa BE, Ratelle JT, Beckman TJ, et al. Autonomy and professional identity formation in residency training: a qualitative study. Med Educ. 2020;54(7):616–27.

Barnhoorn PC, Houtlosser M, Ottenhoff-de Jonge MW, Essers G, Numans ME, Kramer AWM. A practical framework for remediating unprofessional behavior and for developing professionalism competencies and a professional identity. Med Teach. 2019;41(3):303–8.

Mak-van der Vossen M, Teherani A, van Mook W, Croiset G, Kusurkar RA. How to identify, address and report students’ unprofessional behaviour in medical school. Medical Teacher. 2020;42(4):372–9.

Wald HS, Anthony D, Hutchinson TA, Liben S, Smilovitch M, Donato AA. Professional identity formation in medical education for humanistic, resilient physicians: pedagogic strategies for bridging theory to practice. Acad Med. 2015;90(6):753–60.

Lumivero. Nvivo. (Version 12) 2017. Available from: www.lumivero.com .

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.

Hsieh H-F, Shannon SE. Three Approaches to Qualitative Content Analysis. Qual Health Res. 2005;15(9):1277–88.

Nowell LS, Norris JM, White DE, Moules NJ. Thematic analysis: Striving to meet the trustworthiness criteria. Int J Qual Methods. 2017;16(1):1609406917733847.

Kamal NHA, Tan LHE, Wong RSM, Ong RRS, Seow REW, Loh EKY, et al. Enhancing education in palliative medicine: the role of systematic scoping reviews. Palliat Med Care. 2020;7(1):1–11.

Ong RRS, Seow REW, Wong RSM. A systematic scoping review of narrative reviews in palliative medicine education. Palliat Med Care. 2020;7(1):1–22.

Mah ZH, Wong RSM, Seow REW, Loh EKY, Kamal NHA, Ong RRS, et al. A systematic scoping review of systematic reviews in palliative medicine education. Palliat Med Care. 2020;7(1):1–12.

Barab SA, MaKinster JG, Scheckler R. Designing system dualities: characterizing a web-supported professional development community. Inf Soc. 2003;19(3):237–56.

Schön DA. The reflective practitioner: How professionals think in action. 1 ed. London: Routledge; 2017;2017.

Bennett NL. Donald A. Schön, Educating the reflective practitioner. San Francisco: Jossey-Bass Publishers, 1987. 355 pages. Journal of Continuing Education in the Health Professions. 1989;9(2):115–6.

Hamwey M, Allen L, Hay M, Varpio L. Bronfenbrenner’s bioecological model of human development: applications for health professions education. Acad Med. 2019;94(10):1621.

Bluteau P, Clouder L, Cureton D. Developing interprofessional education online: An ecological systems theory analysis. J Interprof Care. 2017;31(4):420–8.

Mahtani K, Spencer EA, Brassey J, Heneghan C. Catalogue of bias: observer bias. BMJ Evid Based Med. 2018;23(1):23–4.

Cooke K, Patt D, Prabhu R. The Road of Mentorship. Am Soc Clin Oncol Educ Book. 2017;37:788–92.

Download references

Acknowledgements

The authors would like to dedicate this paper to the late Dr. S Radha Krishna and A/Prof Cynthia Goh whose advice and ideas were integral to the success of this review and Thondy, Maia Olivia and Raja Kamarul whose lives continue to inspire us.

The authors would also like to thank the anonymous reviewers for their helpful comments which greatly enhanced this manuscript.

No funding was received for this review.

Author information

Authors and affiliations.

Yong Loo Lin School of Medicine, National University of Singapore, NUHS Tower Block, Level 111E Kent Ridge Road, Singapore, 119228, Singapore

Lalit Kumar Radha Krishna

Division of Cancer Education, National Cancer Centre Singapore, 30 Hospital Boulevard, Singapore, 168583, Singapore

Lalit Kumar Radha Krishna, Nur Amira Binte Abdul Hamid, Simon Yew Kuang Ong & Eng Koon Ong

Division of Supportive & Palliative Care, National Cancer Centre Singapore, 30 Hospital Boulevard, Singapore, 168583, Singapore

Lalit Kumar Radha Krishna, Gillian Li Gek Phua & Eng Koon Ong

Duke-NUS Medical School, National University of Singapore, 8 College Road, Singapore, 169857, Singapore

Lalit Kumar Radha Krishna, Gillian Li Gek Phua, Simon Yew Kuang Ong & Eng Koon Ong

Centre for Biomedical Ethics, National University of Singapore, Block MD11, 10 Medical Drive, Singapore, 117597, Singapore

End of Life Care Centre, Palliative Care Institute Liverpool, University of Liverpool, Academic Palliative &200 London Road, Liverpool, L3 9TA, UK

Lalit Kumar Radha Krishna & Stephen Mason

PalC, The Palliative Care Centre for Excellence in Research and Education, Singapore PalC c/o Dover Park Hospice, 10 Jalan Tan Tock Seng, Singapore, 308436, Singapore

Health Data Science, University of Liverpool, Whelan Building, The Quadrangle, Brownlow Hill, Liverpool, L69 3GB, UK

Lalit Kumar Radha Krishna & Ruaraidh Hill

Duke-NUS Medical School, Lien Centre for Palliative Care, National University of Singapore, 8 College Road, Singapore, 169857, Singapore

Gillian Li Gek Phua

Medical Social Services, Singapore General Hospital, Outram Road, Singapore, 169608, Singapore

Crystal Lim

Division of Medical Oncology, National Cancer Centre Singapore, 30 Hospital Boulevard, Singapore, 168583, Singapore

Simon Yew Kuang Ong

Assisi Hospice, 832 Thomson Road, Singapore, 574627, Singapore

Eng Koon Ong

Khalifa University College of Medicine and Health Sciences, Abu Dhabi, United Arab Emirates

Halah Ibrahim

You can also search for this author in PubMed   Google Scholar

Contributions

All authors LKRK, NABAH, GLGP, SM, RH, CL, SYKO, EKO and HI were involved in data curation, formal analysis, investigation, preparing the original draft of the manuscript as well as reviewing and editing the manuscript. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Lalit Kumar Radha Krishna .

Ethics declarations

Ethics approval and consent to participate.

Ethics approval (CIRB Ref 2020/3056: Supporting Mentee Development: Milestones and Assessments in the Palliative Medicine Initiative) was obtained from the SingHealth Combined Institutional Review Board. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Krishna, L.K.R., Hamid, N.A.B.A., Phua, G.L.G. et al. Peer mentorship and professional identity formation: an ecological systems perspective. BMC Med Educ 24 , 1007 (2024). https://doi.org/10.1186/s12909-024-05992-0

Download citation

Received : 11 October 2023

Accepted : 04 September 2024

Published : 15 September 2024

DOI : https://doi.org/10.1186/s12909-024-05992-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Professionalism
• Palliative medicine

BMC Medical Education

ISSN: 1472-6920

• General enquiries: [email protected]

Warning: The NCBI web site requires JavaScript to function. more...

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

Smedley BD, Stith AY, Colburn L, et al.; Institute of Medicine (US). The Right Thing to Do, The Smart Thing to Do: Enhancing Diversity in the Health Professions: Summary of the Symposium on Diversity in Health Professions in Honor of Herbert W.Nickens, M.D.. Washington (DC): National Academies Press (US); 2001.

The Right Thing to Do, The Smart Thing to Do: Enhancing Diversity in the Health Professions: Summary of the Symposium on Diversity in Health Professions in Honor of Herbert W.Nickens, M.D..

• Hardcopy Version at National Academies Press

Inequality in Teaching and Schooling: How Opportunity Is Rationed to Students of Color in America

Linda Darling-Hammond

Stanford University School of Education

Despite the rhetoric of American equality, the school experiences of African-American and other “minority” students in the United States continue to be substantially separate and unequal. Few Americans realize that the U.S. educational system is one of the most unequal in the industrialized world, and that students routinely receive dramatically different learning opportunities based on their social status. In contrast to European and Asian nations that fund schools centrally and equally, the wealthiest 10% of school districts in the United States spend nearly 10 times more than the poorest 10%, and spending ratios of 3 to 1 are common within states. Poor and minority students are concentrated in the least well-funded schools, most of which are located in central cities or rural areas and funded at levels substantially below those of neighboring suburban districts. Recent analyses of data prepared for school finance cases in Alabama, New Jersey, New York, Louisiana, and Texas have found that on every tangible measure—from qualified teachers to curriculum offerings—schools serving greater numbers of students of color had significantly fewer resources than schools serving mostly white students.

Not only do funding systems allocate fewer resources to poor urban districts than to their suburban neighbors, but studies consistently show that, within these districts, schools with high concentrations of low-income and “minority” students receive fewer instructional resources than others in the same district. And tracking systems exacerbate these inequalities by segregating many low-income and minority students within schools (Kozol, 1991; Taylor & Piche, 1991). In combination, policies associated with school funding, resource allocations, and tracking leave minority students with fewer and lower-quality books, curriculum materials, laboratories, and computers; significantly larger class sizes; less qualified and experienced teachers; and less access to high-quality curriculum.

The end results of these educational inequalities are increasingly tragic. More than ever before in our nation's history, education is not only the ticket to economic success, but also to basic survival. Whereas a high school dropout had two chances out of three of getting a job 20 years ago, today he or she has less than one chance out of three, and the job he or she can get pays less than half of what would have been earned 20 years earlier (WT Grant Foundation, 1988). The effects of dropping out are much worse for young people of color than for whites. In 1993, a recent school dropout who was black had only a one in four chance of being employed, whereas the odds for his or her white counterpart were about 50% (NCES, 1995, p. 88). Even recent graduates from high school struggle to find jobs. Among African-American high school graduates not enrolled in college, only 42% were employed in 1993, as compared with 72% of white graduates. Those who do not succeed in school are becoming part of a growing underclass, cut off from productive engagement in society. In addition, working class young people and adults who were prepared for the disappearing jobs of the past teeter on the brink of downward social mobility.

Because the economy can no longer absorb many unskilled workers at decent wages, lack of education is increasingly linked to crime and welfare dependency. Women who have not finished high school are much more likely than others to be on welfare, while men are much more likely to be in prison. National investments in the last decade have tipped heavily toward incarceration rather than education. Nationwide, during the 1980s, federal, state, and local expenditures for corrections grew by over 900%, and for prosecution and legal services by more than 1000% (Miller, 1997), while prison populations more than doubled (U.S. Department of Commerce, 1996, p. 219). During the same decade, per pupil expenditures for schools grew by only about 26% in real dollar terms, and much less in cities (NCES, 1994). The situation is worse in some parts of the country. While schools in California have experienced continuous cutbacks over the last decade, the prison population there has increased by more than 300%.

In 1993, there were more African-American citizens on probation, in jail, in prison, or on parole (1,985,000) than there were in college (1,412,000) (U.S. Department of Commerce, table numbers 281 and 354, pp. 181 and 221). Increased incarceration, and its disproportionate effects upon the African-American community, are a function of new criminal justice policies and ongoing police discrimination (Miller, 1997) as well as lack of access to education. More than half the adult prison population has literacy skills below those required by the labor market (Barton & Coley, 1996), and nearly 40% of adjudicated juvenile delinquents have treatable learning disabilities that went undiagnosed in the schools (Gemignani, 1994).

Meanwhile, schools have changed slowly. Most are still organized to prepare only about 20% of their students for “thinking work” —those students who are tracked very early into gifted and talented, “advanced,” or honors courses. These opportunities are least available to African-American, Latino, and Native American students. As a consequence of structural inequalities in access to knowledge and resources, students from racial and ethnic “minority” groups in the United States face persistent and profound barriers to educational opportunity. As I describe below, schools that serve large numbers of students of color are least likely to offer the kind of curriculum and teaching needed to meet the new standards being enacted across the states and to help students attain the skills needed in a knowledge work economy. In most states, schools serving minority and low-income students lack the courses, materials, equipment, and qualified teachers that would give students access to the education they will need to participate in today's and tomorrow's world.

• CLOSING THE GAP: CHANGES IN EDUCATIONAL ACHIEVEMENT

While the demands for knowledge and skill are growing, the gap in educational opportunity between majority and minority students has been widening. Although overall educational attainment for black Americans increased steadily between 1960 and 1990, this trend is reversing in some states that have imposed graduation exams without improving opportunities to learn. By 1995, 74% of black Americans had completed four or more years of high school—up from only 20% in 1960. However, dropout rates have been increasing for black male students since 1994. Recent evidence from individual states like Texas, Florida, and Georgia where exit exams have been instituted indicates that dropout and pushout rates have increased substantially for African-American and Hispanic students during the 1990s (Haney, 1999).

On national assessments in reading, writing, mathematics, and science, minority students' performance lags behind that of white students, and the gap has widened in most areas during the 1990s. The situation in many urban school systems deteriorated throughout the 1980s and 1990s as drops in per pupil expenditures have accompanied tax cuts while immigration and enrollments have grown. Urban schools serve increased numbers of students who do not speak English as their native language and growing proportions requiring special educational services. These students are increasingly served by growing numbers of unqualified teachers who have been hired since the late 1980s.

In addition, many urban systems have focused their curricula more on rote learning of “basic” skills than on problem solving, thoughtful examination of serious texts and ideas, or assignments requiring frequent and extended writing (Cooper & Sherk, 1989; Darling-Hammond, 1997). As new tests in many states (and the National Assessment of Educational Progress, 1994) focus more on higher-order skills, problem solving, analytic and writing ability, they diverge from the lower-level skills taught in many texts and tested by widely used multiple choice examinations. Students whose education is guided mostly by workbooks compatible with basic skills tests find themselves at a growing disadvantage when they confront the more challenging expectations of new standards and the assessments that accompany them.

• INEQUALITY AND ACHIEVEMENT

The concentration of minority students in high-minority schools facilitates inequality. Nearly two-thirds of “minority” students attend predominantly minority schools, and one-third of black students attend intensely segregated schools (90% or more minority enrollment), most of which are in central cities (Schofield, 1991, p. 336). By 1993, 55% of all students in central city schools were black or Hispanic (National Center for Educational Statistics, NCES, 1995, p. 121). As Taylor and Piche (1991) noted:

Inequitable systems of school finance inflict disproportionate harm on minority and economically disadvantaged students. On an inter -state basis, such students are concentrated in states, primarily in the South, that have the lowest capacities to finance public education. On an intra -state basis, many of the states with the widest disparities in educational expenditures are large industrial states. In these states, many minorities and economically disadvantaged students are located in property-poor urban districts which fare the worst in educational expenditures. In addition, in several states economically disadvantaged students, white and black, are concentrated in rural districts which suffer from fiscal inequity (pp. xi–xii).

Not only do funding systems and tax policies leave most urban districts with fewer resources than their suburban neighbors, but schools with high concentrations of “minority” students receive fewer resources than other schools within these districts. And tracking systems exacerbate these inequalities by segregating many “minority” students within schools, allocating still fewer educational opportunities to them at the classroom level. In their review of resource allocation studies, MacPhail-Wilcox and King (1986) summarized the resulting situation as follows:

School expenditure levels correlate positively with student socioeconomic status and negatively with educational need when school size and grade level are controlled statistically…Teachers with higher salaries are concentrated in high-income and low-minority schools. Furthermore, pupil-teacher ratios are higher in schools with larger minority and low-income student populations… Educational units with higher proportions of low-income and minority students are allocated fewer fiscal and educational resources than are more affluent educational units, despite the probability that these students have substantially greater need for both (p. 425).

These inequalities are increasingly the subject of legal action. The State of New York provides a recent example. Studies have found that by virtually any resource measure—state and local dollars per pupil, student-teacher ratios and student-staff ratios, class sizes, teacher experience, and teacher qualifications— districts with greater proportions of poor and minority students receive fewer resources than others (Berne, 1995). In January 2001, the New York State Supreme Court declared the funding system unconstitutional because it denies students in high-need, low-spending districts like New York City the opportunities to learn needed to meet the state's standards, including well-qualified teachers and curriculum supports ( Campaign for Fiscal Equity v. State of New York ). A similar suit is now pending in the Superior Court of California ( Williams v. State of California ).

A critical problem is that shortages of funds make it difficult for urban and poor rural schools to compete in the marketplace for qualified teachers. When districts do not find qualified teachers, they assign the least able individuals to the students with the least political clout. In 1990, for example, the Los Angeles City School District was sued by students in predominantly minority schools because their schools were not only overcrowded and less well funded than other schools, they were also disproportionately staffed by inexperienced and unprepared teachers hired on emergency credentials ( Rodriguez et al. v. Los Angeles Unified School District, Superior Court of the County of Los Angeles #C611358. Consent decree filed August 12, 1992). In 1999, students in California's predominantly minority schools were 10 times more likely to have uncertified teachers than those in predominantly white schools (Shields et al., 1999).

A growing body of research suggests that inequitable distributions of qualified teachers are a major cause of the achievement gap. Recent studies have found that differential teacher effectiveness is an extremely strong determinant of differences in student learning, far outweighing the effects of differences in class size and heterogenity. Students who are assigned to several ineffective teachers in a row have significantly lower achievement gains—creating differences of as much as 50 percentile points over three years—than those who are assigned to several highly effective teachers in a row (Sanders & Rivers, 1996). These studies also find evidence of bias in assignment of students to teachers of different effectiveness levels, including indications that African American students are nearly twice as likely to be assigned to the most ineffective teachers and about half as likely to be assigned to the most effective teachers.

Analyzing a data set covering 900 Texas school districts, Ronald Ferguson (1991) found that the single most important measurable cause of increased student learning was teacher expertise, measured by teacher performance on a state certification exam, along with teacher experience and master's degrees. Together these variables accounted for about 40% of the measured variance in student test scores. Holding socioeconomic status (SES) constant, the wide variation in teachers' qualifications in Texas accounted for almost all of the variation in black and white students' test scores. That is, after controlling for SES, black students' achievement would have nearly equaled that of whites if they had been assigned equally qualified teachers.

Ferguson also found that class size, at the critical point of a teacher/student ratio of 1:18, was a statistically significant determinant of student outcomes (Ferguson, 1991), as was small school size. Other data also indicate that black students are more likely to attend large schools than white students (Paterson Institute, 1996), with much larger than average class sizes (NCES, 1997a, p. A-119), and confirm that smaller schools and classes make a difference for student achievement (for a review, see Darling-Hammond, 1997).

Ferguson repeated this analysis in Alabama, and still found sizable influences of teacher expertise and smaller class sizes on student achievement gains in reading and mathematics (Ferguson & Ladd, 1996). They found that 31% of the predicted difference in mathematics achievement between districts in the top and bottom quartiles was explained by teacher qualifications and class sizes, while 29.5% was explained by poverty, race, and parent education.

These findings are confirmed elsewhere. For example, in North Carolina, Strauss and Sawyer (1986) found a strong influence on average school district test performance of teachers' average scores on the National Teacher Examinations (NTE) measuring subject matter and teaching knowledge. After taking account of community wealth and other resources, teachers' test scores had a strikingly large effect on students' success on the state competency examinations: a 1% increase in teacher quality (as measured by NTE scores) was associated with a 3% to 5% decline in the percentage of students failing the exam. The authors' conclusion is similar to Ferguson's:

Cumulative effects of teacher effectiveness. Student test scores (5th grade math) by effectiveness level of teachers over a three-year period, for two metropolitan school systems. SOURCE: W.L.Sanders and J.C.Rivers. Cumulative and Residual Effects of (more...)

Of the inputs which are potentially policy-controllable (teacher quality, teacher numbers via the pupil-teacher ratio and capital stock) our analysis indicates quite clearly that improving the quality of teachers in the classroom will do more for students who are most educationally at risk, those prone to fail, than reducing the class size or improving the capital stock by any reasonable margin which would be available to policy makers (p. 47).

These findings are reinforced by a recent review of 60 production function studies, which found that teacher education, ability, and experience—along with small schools and lower teacher-pupil ratios—are associated with significant increases in student achievement (Greenwald, Hedges, & Laine, 1996). In this study's estimate of the achievement gains associated with expenditure increments, spending on teacher education swamped other variables as the most productive investment for schools.

Effects of educational investments: size of increase in student achievement for every $500 spent on: Achievement gains were calculated as standard deviation units on a range of achievement tests in the 60 studies reviewed.

• WHAT MATTERS IN TEACHING?

Unfortunately, policymakers have nearly always been willing to fill teaching vacancies by lowering standards so that people who have had little or no preparation for teaching can be hired, especially if their clients are minority and low-income students. Although this practice is often excused by the presumption that virtually anyone can figure out how to teach, research consistently shows that fully prepared and certified teachers—those with both subject matter knowledge and knowledge of teaching and learning—are more highly rated and more successful with students than teachers without full preparation (Druva & Anderson, 1983; Greenberg, 1983; Evertson, Hawley, & Zlotnik, 1985; Ashton & Crocker, 1986, 1987; Darling-Hammond, 1992). As Evertson and colleagues (1985) concluded:

(T)he available research suggests that among students who become teachers, those enrolled in formal preservice preparation programs are more likely to be effective than those who do not have such training. Moreover, almost all well planned and executed efforts within teacher preparation programs to teach students specific knowledge or skills seem to succeed, at least in the short run (p. 8).

A number of studies have found that teachers who enter the teaching profession without full preparation are less able to plan and redirect instruction to meet students' needs (and less aware of the need to do so), less skilled in implementing instruction, less able to anticipate students' knowledge and potential difficulties, and less likely to see it as their job to do so, often blaming students if their teaching is not successful (Bledsoe, Cox, & Burnham, 1967; Copley, 1974; Gomez & Grobe, 1990; Grossman, 1989; 1990; Bents & Bents, 1990; Rottenberg & Berliner, 1990;). Most important, their students learn at lower levels (See figure 3 ).

Effects on student achievement of teacher certification in mathematics. ANOVA results: *p < .01 **p < .001 SOURCE: P.Hawk, C.Coble, and M.Swanson. Certification: It Does Matter. Journal of Teacher Education, 36 (3) May–June 1985; (more...)

Teacher expertise and curriculum quality are interrelated, because expert teachers are a prerequisite for the successful implementation of challenging curriculum. Teachers who are well-prepared are better able to use teaching strategies that respond to students' needs and learning styles and that encourage higher-order learning (Peikes, 1967–1968; Skipper & Quantz, 1987; Hansen, 1988). Since the novel tasks required for problem solving are more difficult to manage than the routine tasks associated with rote learning, lack of knowledge about how to manage an active, inquiry-oriented classroom can lead teachers to turn to passive tactics that “dumb down” the curriculum, busying students with workbooks rather than complex tasks that require more skill to orchestrate (Carter & Doyle, 1987; Doyle, 1986; Cooper & Sherk, 1989). Teacher education is also related to the use of teaching strategies that encourage higher-order learning and the use of strategies responsive to students' needs and learning styles. Thus, policies that resolve shortages in poor districts by hiring unprepared teachers serve only to exacerbate the inequalities low-income and minority children experience.

Access to Good Teaching

In “Closing the Divide,” Robert Dreeben (1987) described the results of his study of reading instruction and outcomes for 300 black and white first graders across seven schools in the Chicago area. He found that differences in reading outcomes among students were almost entirely explained not by socioeconomic status or race, but by the quality of instruction the students received:

Our evidence shows that the level of learning responds strongly to the quality of instruction: having and using enough time, covering a substantial amount of rich curricular material, and matching instruction appropriately to the ability levels of groups…When black and white children of comparable ability experience the same instruction, they do about equally well, and this is true when the instruction is excellent in quality and when it is inadequate (p. 34).

However, the study also found that the quality of instruction received by African-American students was, on average, much lower than that received by white students, thus creating a racial gap in aggregate achievement at the end of first grade. In fact, the highest ability group in Dreeben's sample was in a school in a low-income, African-American neighborhood. These students, though, learned less during first grade than their lower-aptitude white counterparts because their teacher was unable to provide the quality instruction this talented group deserved.

The National Assessment of Educational Progress (NAEP) has documented that the qualifications and training of students' teachers are among the correlates of reading achievement. Students of teachers who are fully certified, who have master's degrees, and who have had professional coursework in literature-based instruction do better on reading assessments. Furthermore, teachers who have had more professional coursework are more likely to use an approach that integrates literature and writing, which is associated with stronger achievement. For example, teachers with more staff development hours in reading are much more likely to use a wide variety of books, newspapers, and materials from other subject areas and to engage students in regular writing, all of which are associated with higher reading achievement. They are also less likely to use reading kits, basal readers, and workbooks which are associated with lower levels of reading achievement (NAEP, 1994).

Curricular differences like these are widespread, and they explain much of the disparity between the achievement of white and minority students and between those of higher- and lower-income levels (Oakes, 1985; Lee & Bryk, 1988). When students of similar backgrounds and initial achievement levels are exposed to more and less challenging curriculum material, those given the richer curriculum opportunities outperform those placed in less challenging classes (Alexander & McDill, 1976; Oakes, 1985; Gamoran & Behrends, 1987).

Most studies have estimated effects statistically based on natural occurrences of different tracking policies. However, one study that randomly assigned 7th grade “at-risk” students to remedial, average, and honors mathematics classes found that at the end of the year, the at-risk students who took the honors class offering a pre-algebra curriculum outperformed all other students of similar backgrounds (Peterson, 1989).

Another study of African-American high school youth randomly placed in public housing in the Chicago suburbs rather than in the city, found similar results. Compared to their comparable city-placed peers who were of equivalent income and initial academic attainment, the students who were enabled to attend largely white and better-funded suburban schools had better educational outcomes across many dimensions. They were substantially more likely to have the opportunity to take challenging courses, receive additional academic help, graduate on time, attend college, and secure good jobs (Kaufman & Rosenbaum, 1992).

These examples are drawn from carefully controlled studies that confirm what many other studies have suggested. Much of the difference in school achievement found between African-American students and others is due to the effects of substantially different school opportunities, and in particular, greatly disparate access to high-quality teachers and teaching (Barr & Dreeben, 1983; College Board, 1985; Dreeben & Gamoran, 1986; Dreeben & Barr, 1987; Oakes, 1990; Darling-Hammond & Snyder, 1992).

The Unequal Distribution Of Teachers

Minority and low-income students in urban settings are most likely to find themselves in classrooms staffed by inadequately prepared, inexperienced, and ill-qualified teachers because funding inequities, distributions of local power, labor market conditions, and dysfunctional hiring practices conspire to produce teacher shortages of which they bear the brunt. By every measure of qualifications, unqualified and underprepared teachers continue to be found disproportionately in schools serving greater numbers of low-income or minority students (NCES, 1997a). In 1994, just over 20% of newly hired public school teachers were hired without having met regular certification requirements (NCTAF, 1997). The vast majority of these teachers were assigned to the most disadvantaged schools in central city and poor rural school districts.

Districts with the greatest concentrations of poor children, minority children, and children of immigrants are also those where incoming teachers are least likely to have learned about up-to-date teaching methods or about how children grow, learn, and develop—and what to do if they are having difficulties. In addition, when faced with shortages, districts often hire substitutes, assign teachers outside their fields of qualification, expand class sizes, or cancel course offerings. These strategies are used most frequently in schools serving large numbers of minority students (NCES, 1997a; NCTAF, 1997). No matter what strategies are adopted, the quality of instruction suffers.

This situation is partly a function of real shortages, but it is also due to urban district hiring practices that are often cumbersome, poorly managed, insensitive to teacher qualifications, and delayed by seniority transfer rules and a variety of other self-inflicted procedures (National Commission on Teaching and America's Future, 1996). Furthermore, since many of the more expert, experienced teachers transfer to more desirable schools and districts when they are able, new teachers and those without training are typically given assignments in the most disadvantaged schools that offer the fewest supports (Wise, Darling-Hammond, & Berry, 1987; Murnane et al., 1991). Because they confront challenging assignments without mentoring or other help, attrition rates for new teachers, especially in cities, average 30% or more over the first five years of teaching (Grissmer & Kirby, 1987; Wise, Darling-Hammond, & Berry, 1987; NCES, 1997b).

This adds additional problems of staff instability to the already difficult circumstances in which central city youth attend school. Where these practices persist, many children in central city schools are taught by a parade of short-term substitute teachers, inexperienced teachers without support, and underqualified teachers who are not really familiar with either their subject matter or effective methods. The California Commission on the Teaching Profession (1985) concluded that disproportionate numbers of minority and poor students are taught throughout their entire school careers by the least qualified teachers. This sets up the school failure that society predicts for them.

Oakes' (1990) nationwide study of the distribution of mathematics and science opportunities confirmed these pervasive patterns. Based on teacher experience, certification status, preparation in the discipline, degrees, self-confidence, and teacher and principal perceptions of competence, it is clear that low-income and minority students have less contact with the best-qualified science and mathematics teachers. Students in high-minority schools have only a 50% chance of being taught by a math or science teacher who is certified at all, and an even lower chance of being taught by teachers who are fully qualified for their teaching assignment by virtue of the subject area(s) they are prepared to teach. Oakes concluded:

Our evidence lends considerable support to the argument that low-income, minority, and inner-city students have fewer opportunities…They have considerably less access to science and mathematics knowledge at school, fewer material resources, less-engaging learning activities in their classrooms, and less-qualified teachers… (p. x–xi).

Access to High-Quality Curriculum

In addition to being taught by teachers less qualified than those of their white and suburban counterparts, urban and minority students face dramatic differences in courses, curriculum materials, and equipment. Unequal access to high-level courses and challenging curriculum explains much of the difference in achievement between minority students and white students. For example, analyses of data from the High School and Beyond surveys demonstrate dramatic differences among students of various racial and ethnic groups in course taking in such areas as mathematics, science, and foreign languages (Pelavin & Kane, 1990). These data also demonstrate that for students of all racial and ethnic groups, course taking is strongly related to achievement. For students with similar course taking records, achievement test score differences by race or ethnicity narrow substantially (Jones, 1984; College Board, 1985, p. 38; Moore & Smith, 1985; Jones et al., 1986).

One source of inequality is the fact that high-minority schools are much less likely to offer advanced and college preparatory courses in mathematics and science than are schools that serve affluent and largely white populations of students (Matthews, 1984; Oakes, 1990). Schools serving predominantly minority and poor populations offer fewer advanced courses and more remedial courses in academic subjects, and they have smaller academic tracks and larger vocational programs (NCES, 1985; Rock et al., 1985). The size and rigor of college preparatory programs within schools vary with the race and socioeconomic status of school populations (California State Department of Education, 1984). As plaintiffs noted in the New Jersey school finance case, wealthy and predominantly white Montclair offers foreign languages at the preschool level, while poor and predominantly black Paterson does not offer any until high school— and then, relatively few. And while 20% of 11 th and 12 th graders in wealthy Moorestown participate in Advanced Placement courses, none are even offered in any school in poor and predominantly black Camden and East Orange (ETS, 1991, p. 9).

When high-minority, low-income schools offer any advanced or college preparatory courses, they offer them to only a very tiny fraction of students. Thus, at the high school level, African American, Hispanics, and Native Americans have traditionally been underrepresented in academic programs and overrepresented in general education or vocational education programs, where they receive fewer courses in areas such as English, mathematics, and science (College Board, 1985). Even among the college-bound, non-Asian minority students take fewer and less demanding mathematics, science, and foreign language courses (Pelavin & Kane, 1990).

The unavailability of teachers who could teach these upper-level courses, or who can successfully teach heterogeneous groups of students, reinforces these inequalities in access to high-quality curricula. Tracking persists in the face of growing evidence that it does not substantially benefit high achievers and tends to put low achievers at a serious disadvantage (Kulik & Kulik, 1982; Oakes, 1985; 1986; Slavin, 1990; Hoffer, 1992), in part because good teaching is a scarce resource, and thus must be allocated. Scarce resources tend to get allocated to the students whose parents, advocates, or representatives have the most political clout. This results, not entirely but disproportionately, in the most highly qualified teachers teaching the most enriched curricula to the most advantaged students. Evidence suggests that teachers themselves are tracked, with those judged to be the most competent, experienced, or with the highest status assigned to the top tracks (Rosenbaum, 1976; Finley, 1984; Davis, 1986; Oakes, 1986; Talbert, 1990; NCTAF, 1996).

Tracking in U.S. schools is much more extensive at much earlier grade levels than in most other countries. Starting in elementary schools with the designation of instructional groups and programs based on test scores and recommendations, it becomes highly formalized by junior high school. The result of this practice is that challenging curricula are rationed to a very small proportion of students, and far fewer of our students ever encounter the types of curricula that students in other countries typically experience (McKnight et al., 1987; Usiskin, 1987; Useem, 1990; Wheelock, 1992).

Although test scores and prior educational opportunities partially explain these differential placements, race and socioeconomic status play a distinct role. Even after test scores are controlled, race and socioeconomic status determine assignments to high school honors courses (Gamoran, 1992), as well as vocational and academic programs and more or less challenging courses within them (Useem, 1990; Oakes, 1992). This is true in part because of prior placements of students in upper tracks in earlier grades, in part due to counselors' views that they should advise students in ways that are “realistic” about their futures, and in part because of the greater effectiveness of parent interventions in tracking decisions for higher-SES students (Moore & Davenport, 1988).

From “gifted and talented” programs at the elementary level through advanced courses in secondary schools, teachers who are generally the most skilled offer rich, challenging curricula to select groups of students, based on the theory that only a few students can benefit from such curricula. Yet the distinguishing feature of such programs, particularly at the elementary level, is not their difficulty, but their quality. Students in these programs are given opportunities to integrate ideas across fields of study. They have opportunities to think, write, create, and develop projects. They are challenged to explore. Though virtually all students would benefit from being similarly challenged, the opportunity for this sort of schooling remains acutely restricted.

Meanwhile, students placed in lower tracks are exposed to a limited, rote-oriented curriculum and ultimately achieve less than students of similar aptitude who are placed in academic programs or untracked classes (Gamoran & Mare, 1989; Oakes, 1985, 1990; Gamoran, 1990). Teacher interaction with students in lower track classes is less motivating, less supportive, and less demanding of higher-order reasoning and responses (Good & Brophy, 1987). These interactions are also less academically oriented, and more likely to focus on behavioral criticisms, especially for minority students (Oakes, 1985; Eckstrom & Villegas, 1991). Presentations are less clear and less focused on higher-order cognitive goals (Oakes, 1985).

In addition, many studies have found that students placed in the lowest tracks or in remedial programs—disproportionately low-income and minority students—are most apt to experience instruction geared only to multiple-choice tests, working at a low cognitive level on test-oriented tasks that are profoundly disconnected from the skills they need to learn. Rarely are they given the opportunity to talk about what they know, to read real books, to write, or to construct and solve problems in mathematics, science, or other subjects (Oakes, 1985; Davis, 1986; Trimble & Sinclair, 1986; Cooper & Sherk, 1989).

• POLICY FOR EQUALITY: TOWARD EQUALIZATION OF EDUCATIONAL OPPORTUNITY

The common presumption about educational inequality is that it resides primarily in those students who come to school with inadequate capacities to benefit from what education the school has to offer. The fact that U.S. schools are structured such that students routinely receive dramatically unequal learning opportunities based on their race and social status is simply not widely recognized. If the academic outcomes for minority and low-income children are to change, reforms must alter the caliber and quantity of learning opportunities they encounter. These efforts must include equalization of financial resources, changes in curriculum and testing policies, and improvements in the supply of highly qualified teachers to all students.

Resource Equalization

Progress in equalizing resources to students will require attention to inequalities at all levels—between states, among districts, among schools within districts, and among students differentially placed in classrooms, courses, and tracks that offer substantially disparate opportunities to learn. As a consequence of systematic inequalities at each of these levels, minority and low-income students are frequently “at risk” not from their homes or family factors but from the major shortcomings of the schools they attend.

Special programs such as compensatory or bilingual education will never be effective at remedying underachievement as long as these services are layered on a system that so poorly educates minority and low-income children to begin with. The presumption that “the schools are fine, it's the children who need help” is flawed. The schools serving large concentrations of low-income and minority students are generally not fine, and many of their problems originate with district and state policies and practices that fund them inadequately, send them incompetent staff, require inordinate attention to arcane administrative requirements that fragment educational programs and drain resources from classrooms, and preclude the adoption of more promising curriculum and teaching strategies.

Current initiatives to create special labels and programs for “at-risk” children and youth—including mass summer school programs and mandatory Saturday classes for the hundreds of thousands of students who are threatened with grade retention under new promotion rules—are unlikely to succeed if they do not attend to the structural conditions of schools that place children at risk. In the pursuit of equity, our goal should be to develop strategies that improve the core practices of schooling rather than layering additional programs and regulations on foundations that are already faulty. The pressures to respond to special circumstances with special categorical programs are great, and the tradition of succumbing to those pressures in an add-on fashion is well established, in education as in other areas of national life. But special programs, with all their accoutrements of new rules and procedures, separate budgets, and fragmented, pull-out programs will be counterproductive as long as the status quo remains unchanged in more significant ways.

As the 1992 interim report of an independent commission on Chapter 1 observed: “Given the inequitable distribution of state and local resources, the current notion that Chapter 1 provides supplemental aid to disadvantaged children added to a level playing field is a fiction” (Commission on Chapter 1, 1992, p. 4). The Commission proposed that each state be held accountable for assuring comparability in “vital services” among all its districts as well as in all schools within each district. Among these vital services, perhaps the most important is highly qualified teachers, not just for specific Chapter 1 services but for all classrooms.

Ferguson's (1991) recommendation that equalization focus on district capacity to hire high-quality teachers is an important one. In addition to the weight of evidence indicating the central importance of qualified teachers to student learning, there is real-world experience with the positive effects on teacher quality and distribution of such policies. When Connecticut raised and equalized beginning teacher salaries under its 1986 Education Enhancement Act, shortages of teachers (including those that had plagued urban areas) evaporated. By 1989, most teaching fields showed surpluses. The state raised standards for teacher education and licensing, initiated scholarships and forgivable loans to recruit high-need teachers into the profession (including teachers in shortage fields, those who would teach in high-need locations, and minority teachers), created a mentoring and assessment program for all beginning teachers, and invested money in high-quality professional development, with special aid to low-achieving districts. The state also developed a low-stakes, performance-oriented assessment program focused on higher-order thinking and performance skills, which is used to provide information to schools and districts, but not to punish children or teachers. By 1998, Connecticut had surpassed all other states in 4 th grade reading and mathematics achievement on the NAEP and scored at the top in 8 th grade mathematics, science, and writing. Although Connecticut still has an achievement gap it is working to close, black students in Connecticut score significantly higher than their counterparts elsewhere in the county (Baron, 1999; Wilson, Darling-Hammond, & Berry, 2000).

The new wave of school finance lawsuits that are challenging both within state and within district resource allocation disparities are also promising. These suits are increasingly able to demonstrate how access to concrete learning opportunities is impaired by differential access to money, and how these learning opportunities translate into academic achievement for students. As standards are used to articulate clearer conceptions of what students need to learn to function in today's society and what schools need to do to support these levels of learning, lawsuits like ones recently won in Alabama and New York may be linked to definitions of the quality of education that is “adequate” to meet the state's expectations for student achievement. Such cases are requiring remedies that link levels of funding to minimum standards of learning and teaching. As suits brought on the adequacy theory establish that learning experiences depend on resources and influence outcomes, they establish a principle of “opportunity to learn” that could allow states to define a curriculum entitlement that becomes the basis for both funding and review of school practices.

Opportunity to Learn Standards

The idea of opportunity to learn standards was first articulated by the National Council on Education Standards and Testing (NCEST), which argued for student performance standards but acknowledged they would result in greater inequality if not accompanied by policies ensuring access to resources, including appropriate instructional materials and well-prepared teachers (NCEST, 1992, E12–E13). The Commission's Assessment Task Force proposed that states collect evidence on the extent to which schools and districts provide opportunity to learn the curricula implied by standards as a prerequisite to using tests for school graduation or other decisions (NCEST, 1992, F17–F18).

Opportunity-to-learn standards would establish, for example, that if a state's curriculum frameworks and assessments outlined standards for science learning that require laboratory work and computers, specific coursework, and particular knowledge for teaching, resources must be allocated and policies must be fashioned to provide for these entitlements. Such a strategy would leverage both school improvement and school equity reform, providing a basis for state legislation or litigation where opportunities to learn were not adequately funded. Opportunity-to-learn standards would define a floor of core resources, coupled with incentives for schools to work toward professional standards of practice that support high-quality learning opportunities. Such standards would provide a basis for:

• state legislation and, if necessary, litigation that supports greater equity in funding and in the distribution of qualified teachers;
• information about the nature of the teaching and learning opportunities made available to students in different districts and schools across the state;
• incentives for states and school districts to create policies that ensure adequate and equitable resources, curriculum opportunities, and teaching to all schools;
• a school review process that helps schools and districts engage in self-assessments and external reviews of practice in light of standards; and
• identification of schools that need additional support or intervention to achieve adequate opportunities to learn for their students.

Curriculum and Assessment Reform

As noted above, the curriculum offered to many students—and to most African American students—in U.S. schools is geared primarily toward lower-order “rote” skills—memorizing pieces of information and conducting simple operations based on formulas or rules—that are not sufficient for the demands of modern life or for the new standards being proposed and enacted by states and national associations. These new standards will require students to be able to engage in independent analysis and problem solving, extensive research and writing, use of new technologies, and various strategies for accessing and using resources in new situations. Major changes in curriculum and resources will be needed to ensure that these kinds of activities are commonplace in the classrooms of minority students and others.

These efforts to create a “thinking curriculum” for all students are important to individual futures and our national welfare. They are unlikely to pay off, however, unless other critical changes are made in curriculum, in the ways students are tracked for instruction, and the ways teachers are prepared and supported. Although mounting evidence indicates that low-tracked students are disadvantaged by current practice and that high-ability students do not benefit more from homogeneous classrooms (Slavin, 1990), the long-established American tracking system will be difficult to reform until there is an adequate supply of well-trained teachers—teachers who are both prepared to teach the more advanced curriculum that U.S. schools now fail to offer most students and to assume the challenging task of teaching many kinds of students with diverse needs, interests, aptitudes, and learning styles in integrated classroom settings.

Other important changes concern the types and uses of achievement tests in U.S. schools. As a 1990 study of the implementation of California's new mathematics curriculum framework points out, when a curriculum reform aimed at problem solving and higher-order thinking skills encounters an already mandated rote-oriented basic skills testing program, the tests win out (Cohen et al., 1990; Darling-Hammond, 1990b). As one teacher put it:

Teaching for understanding is what we are supposed to be doing… (but) the bottom line here is that all they really want to know is how are these kids doing on the tests? …They want me to teach in a way that they can't test, except that I'm held accountable to the test It's a Catch 22… (Wilson, 1990, p. 318).

Students in schools that organize most of their efforts around the kinds of low-level learning represented by commercially developed multiple-choice tests will be profoundly disadvantaged when they encounter more rigorous evaluations that require greater analysis, writing, and production of elaborated answers. Initiatives in some states (e.g., Connecticut, Kentucky) and cities (e.g., New York, San Diego) to develop more performance-oriented assessments that develop higher-order skills may begin to address this problem.

An equally important issue is how tests are used. If new assessments are used, like current tests are, primarily for sorting, screening, and tracking, the quality of education for minority students is unlikely to improve. Qualitatively better education will come only from developing and using assessment not for punishment but as a tool for identifying student strengths and needs as a basis for adapting instruction more successfully (Glaser, 1981, 1990). Robert Glaser (1990) argued that schools must shift from an approach “characterized by minimal variation in the conditions for learning” in which “a narrow range of instructional options and a limited number of paths to success are available,” (p.16) to one in which “conceptions of learning and modes of teaching are adjusted to individuals—their backgrounds, talents, interests, and the nature of their past performances and experiences” (p. 17).

The outcomes of the current wave of curriculum and assessment reforms will depend in large measure on the extent to which developers and users of new standards and tests use them to improve teaching and learning rather than merely reinforcing our tendencies to sort and select those who will get high-quality education from those who will not. They will also need to pursue broader reforms to improve and equalize access to educational resources and support the professional development of teachers, so that new standards and tests are used to inform more skillful and adaptive teaching that enables more successful learning for all students.

Investments in Quality Teaching

A key corollary to this analysis is that improved opportunities for minority students will rest, in large part, on policies that professionalize teaching by increasing the knowledge base for teaching and ensuring mastery of this knowledge by all teachers permitted to practice. This means providing all teachers with a stronger understanding of how children learn and develop, how a variety of curricular and instructional strategies can address their needs, and how changes in school and classroom practices can support their growth and achievement.

There are two reasons for this approach. First, the professionalization of an occupation raises the floor below which no entrants will be admitted to practice. It eliminates practices that allow untrained entrants to practice disproportionately on underserved and poorly protected clients. Second, professionalization increases the overall knowledge base for the occupation, thus improving the quality of services for all clients, especially those most in need of high-quality teaching (Wise & Darling-Hammond, 1987; Darling-Hammond, 1990a).

The students who have, in general, the poorest opportunities to learn—those attending the inner-city schools that are compelled by the current incentive structure to hire disproportionate numbers of substitute teachers, uncertified teachers, and inexperienced teachers and that lack resources for mitigating the uneven distribution of good teaching—are the students who will benefit most from measures that raise the standards of practice for all teachers. They will also benefit from targeted policies that provide quality preparation programs and financial aid for highly qualified prospective teachers who will teach in central cities and poor rural areas. Providing equity in the distribution of teacher quality requires changing policies and long-standing incentive structures in education so that shortages of trained teachers are overcome, and that schools serving low-income and minority students are not disadvantaged by lower salaries and poorer working conditions in the bidding war for good teachers.

Building and sustaining a well-prepared teaching force will require local, state, and federal initiatives. To recruit an adequate supply of teachers, states and localities will need to upgrade teachers' salaries to levels competitive with those of college graduates in other occupations, who currently earn 20% to 50% more, depending on the field. States should also strengthen teacher education and certification. In almost all states, teacher education is more poorly funded than other university departments (Ebmeier, Twombly, & Teeter, 1990). It has long been used as a revenue producer for programs that train engineers, accountants, lawyers, and doctors. Rather than bemoaning the quality of teacher training, policy makers should invest in its improvement, require schools of education to become accredited, and insist that teachers pass performance examinations for licensing that demonstrate they can teach well. Shortages should be met by enhanced incentives rather than by lowering standards, especially for those who teach children in central cities and poor rural schools.

The federal government can play a leadership role in providing an adequate supply of well-qualified teachers just as it has in providing an adequate supply of qualified physicians. When shortages of physicians were a major problem more than 30 years ago, Congress passed the 1963 Health Professions Education Assistance Act to support and improve the caliber of medical training, to create and strengthen teaching hospitals, to provide scholarships and loans to medical students, and to create incentives for physicians to train in shortage specialties and to locate in underserved areas. Similarly, federal initiatives in education should seek to:

Recruit new teachers, especially in shortage fields and in shortage locations, through scholarships and forgivable loans for high-quality teacher education.

Strengthen and improve teachers' preparation through improvement incentive grants to schools of education and supports for licensing reform.

Improve teacher retention and effectiveness by improving clinical training and support during the beginning teaching stage when 30% leave. This would include funding mentoring programs for new teachers in which they receive structured coaching from expert veterans.

If the interaction between teachers and students is the most important aspect of effective schooling, then reducing inequality in learning has to rely on policies that provide equal access to competent, well-supported teachers. The public education system ought to be able to guarantee that every child who is forced by law to go to school is taught by someone who is knowledgeable, competent, and caring. That is real accountability. As Carl Grant (1989) put it:

Teachers who perform high-quality work in urban schools know that, despite reform efforts and endless debates, it is meaningful curricula and dedicated and knowledgeable teachers that make the difference in the education of urban students (p. 770).

When it comes to equalizing opportunities for students to learn, that is the bottom line.

• Alexander, K.L., & McDill, E.L. (1976). Selection and allocation within schools: Some causes and consequences of curriculum placement . American Sociological Review, 41, pp.963–980.
• Ashton, P., & Crocker, L. (1986). Does teacher certification make a difference? Florida Journal of Teacher Education , 38(3), pp.73–83.
• Ashton, P., & Crocker, L. (1987, May–June). Systematic study of planned variations: The essential focus of teacher education reform . Journal of Teacher Education , 38, pp.2–8.
• Baron, J.B. (1999). Exploring high and improving reading achievement in Connecticut . Washington, DC: National Educational Goals Panel.
• Barr, R., & Dreeben, R. (1983). How schools work . Chicago: University of Chicago Press.
• Barton, Paul E. & Coley, R.J. (1996). Captive students: Education and training in America's prisons . Princeton, N.J.: Educational Testing Service.
• Bents, M., & Bents, R.B. (1990). Perceptions of good teaching among novice, advanced beginner and expert teachers . Paper presented at the Annual Meeting of the American Educational Research Association , Boston.
• Berne, R. (1995). Educational input and outcome inequities in New York State . In R. Berne, editor; and L.O.Picus, editor. (eds.), Outcome Equity in Education , pp.191–223. ThousandOaks, CA.: Corwin Press.
• Bledsoe, J.C., Cox, J.V., & Burnham, R. (1967). Comparison between selected characteristics and performance of provisionally and professionally certified beginning teachers in Georgia . Washington, D.C.: U.S. Department of Health, Education, and Welfare.
• California Commission on the Teaching Profession (1985). Who will teach our children? Sacramento: California Commission on the Teaching Profession.
• California State Department of Education (1984). California high school curriculum study: Path through high school . Sacramento: California State Department of Education.
• Carter, K., & Doyle, W. (1987). Teachers' knowledge structures and comprehension processes . In J.Calderhead, editor. (Ed.), Exploring Teacher Thinking , pp.147–160. London: Cassell.
• Cohen, D., et al. (1990). Case Studies of Curriculum Implementation, Educational Evaluation and Policy Analysis , 12(3).
• College Board (1985). Equality and excellence: The educational status of black Americans . New York: College Entrance Examination Board.
• Commission on Chapter 1 (1992). High performance schools: No exceptions, no excuses . Washington, D.C.: Author.
• Cooper, E. & Sherk, J. (1989). Addressing urban school reform: Issues and alliances . Journal of Negro Education , 58(3), pp.315–331.
• Copley, P.O. (1974). A study of the effect of professional education courses on beginning teachers . Springfield, MO: Southwest Missouri State University. ERIC Document No. ED 098–147.
• Darling-Hammond, L. (1990. a). Teacher quality and equality . In J.Goodlad, editor; , & P.Keating, editor. (Eds.), Access to Knowledge: An Agenda for Our Nation's Schools , pp.237–258. NY: College Entrance Examination Board.
• Darling-Hammond, L. (1990. b). Instructional policy into practice: “The power of the bottom over the top.” Educational Evaluation and Policy Analysis , 12(3), pp.233–242.
• Darling-Hammond, L. (1992). Teaching and knowledge: Policy issues posed by alternate certification for teachers . Peabody Journal of Education , 67(3), pp.123–154.
• Darling-Hammond, L. (1997). The right to learn: A blueprint for creating schools that work . San Francisco: Jossey-Bass.
• Darling-Hammond, L. & Snyder, J. (1992). Traditions of curriculum inquiry: The scientific tradition . In P.W.Jackson, editor. (Ed.), Handbook of Research on Curriculum . New York: Macmillan.
• Davis, D.G. (1986). A pilot study to assess equity in selected curricular offerings acrossthree diverse schools in a large urban school district . Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco .
• Doyle, W. (1986). Content representation in teachers' definitions of academic work . Journal of Curriculum Studies , 18, pp.365–379.
• Dreeben, R. (1987, Winter). Closing the divide: What teachers and administrators can do to help black students reach their reading potential, American Educator , 11(4), pp.28–35.
• Dreeben, R. & Barr, R. (1987). Class composition and the design of instruction . Paper presented at the Annual Meeting of the American Education Research Association , Washington, D.C.
• Dreeben, R. & Gamoran, A. (1986). Race, instruction, and learning . American Sociological Review , 51(5), pp.660–669.
• Druva, C.A., & Anderson, R.D. (1983). Science teacher characteristics by teacher behavior and by student outcome: A meta-analysis of research . Journal of Research in Science Teaching , 20(5), pp.467–479.
• Ebmeier, H., Twombly, S., & Teeter, D. (1990). The comparability and adequacy of financial support for schools of education . Journal of Teacher Education , 42(3): pp.226–235.
• Eckstrom, R., & Villegas, A.M. (1991). Ability grouping in middle grade mathematics: Process and consequences. Research in Middle Level Education , 15(1), pp.1–20.
• Educational Testing Service (1991). The state of inequality . Princeton, NJ: ETS.
• Evertson, C., Hawley, W., & Zlotnick, M. (1985). Making a difference in educational quality through teacher education . Journal of Teacher Education , 36(3), pp.2–12.
• Ferguson, R.F. (1991, Summer). Paying for public education: New evidence on how and why money matters . Harvard Journal on Legislation 28(2), pp.465–498.
• Ferguson, R.F. & Ladd, H.F. How and why money matters: An analysis of Alabama schools .
• Finley, M.K. (1984). Teachers and tracking in a comprehensive high school. Sociology of Education , 57, pp.233–243.
• Gamoran, A. (1990). The consequences of track-related instructional differences for student achievement . Paper presented at the Annual Meeting of the American Educational Research Association , Boston.
• Gamoran, A. (1992). Access to excellence: Assignment to honors English classes in the transition from middle to high school . Educational Evaluation and Policy Analysis , 14(3), pp.185–204.
• Gamoran, A., & Berends, M. (1987). The effects of stratification in secondary schools: Synthesis of survey and ethnographic research . Review of Educational Research , 57, pp.415–436.
• Gamoran, A., & Mare, R. (1989). Secondary school tracking and eduational inequality: Compensation, reinforcement or neutrality? American Journal of Sociology , 94, pp.1146–1183.
• Gemignani, Robert J. (1994, October). Juvenile correctional education: A time for change. Update on research. Juvenile Justice Bulletin . Washington, DC: U.S. Department of Justice, Office of Juvenile Justice and Delinquency Prevention.
• Glaser, R. (1981). The future of testing: A research agenda for cognitive psychology and psychometrics . American Psychologist , 39(9), pp.923–936.
• Glaser, R. (1990). Testing and assessment: O temporal O mores! Pittsburgh, PA: University of Pittsburgh, Learning Research and Development Center .
• Gomez, D.L., & Grobe, R.P. (1990). Three years of alternative certification in Dallas: Where are we? Paper presented at the Annual Meeting of the American Educational Research Association , Boston.
• Good, T.L., & Brophy, J. (1987). Looking in Classrooms . New York: Harper and Row.
• Grant, C.A. (1989, June). Urban teachers: Their new colleagues and curriculum . Phi Delta Kappan , 70(10), pp.764–770.
• Greenberg, J.D. (1983). The case for teacher education: Open and shut . Journal of Teacher Education , 34(4), pp.2–5.
• Greenwald, R., Hedges, L.V., and Laine, R.D. (1996). The effect of school resources on student achievement, Review of Educational Research , 66: pp.361–396.
• Grissmer, D.W. & Kirby, S.N. (1987). Teacher attrition: The uphill climb to staff the nation's schools . Santa Monica: Rand Corporation.
• Grossman, P.L. (1989). Learning to teach without teacher education . Teachers College Record , 91(2), pp.191–208.
• Grossman, P.L. (1990). The making of a teacher: Teacher knowledge and teacher education . New York: Teachers College Press.
• Haney, W. (1999). Supplementary report on Texas Assessment of Academic Skills Exit Test (TAAS–X) . Boston: Center for the Study of Testing, Evaluation, and Educational Policy.
• Hansen, J.B. (1988). The relationship of skills and classroom climate of trained and untrained teachers of gifted students . Unpublished doctoral dissertation, Purdue University.
• Hawk, P., Coble, C.R., & Swanson, M. (1985). Certification: It does matter , Journal of Teacher Education , 36(3): pp.23–15.
• Hoffer, T.B. (1992). Middle school ability grouping and student achievement in science and mathematics . Educational Evaluation and Policy Analysis , 14(3), pp.205–227.
• Jones, L.V. (1984). White-black achievement differences: The narrowing gap . American Psychologist , 39, pp.1207–1213.
• Jones, L.V., Burton, N.W., & Davenport, E.C. (1984). Monitoring the achievement of black students . Journal for Research in Mathematics Education , 15, pp.154–164.
• Kaufman, J.E., & Rosenbaum, J.E. (1992). Education and employment of low-income black youth in white suburbs . Educational Evaluation and Policy Analysis , 14(3), pp.229–240.
• Kozol, J. (1991). Savage inequalities . New York: Crown.
• Kulik, C.C., & Kulik, J.A. (1982). Effects of ability grouping on secondary school students: A meta-analysis of evaluation findings . American Education Research Journal , 19, pp.415–428.
• Lee, V., & Bryk, A. (1988). Curriculum tracking as mediating the social distribution of high school achievement . Sociology of Education , 61, pp.78–94.
• MacPhail-Wilcox, B. & King, R.A. (1986). Resource allocation studies: Implications forschool improvement and school finance research . Journal of Education Finance , 11, pp.416–432.
• Matthews, W. (1984). Influences on the learning and participation of minorities in mathematics . Journal for Research in Mathematics Education , 15, pp.84–95.
• McKnight, C.C., Crosswhite, J.A., Dossey, J.A., Kifer, E., Swafford, S.O., Travers, K.J., & Cooney, T.J. (1987). The underachieving curriculum: Assessing U.S. school mathematics from an international perspective . Champaign, IL: Stipes Publishing.
• Miller, J.G. (1997, June). African American males in the criminal justice system . Phi Delta Kappan , pp. K1–K12.
• Moore, D., & Davenport, S. (1988). The new improved sorting machine . Madison, WI: National Center on Effective Secondary Schools.
• Moore, E.G. & Smith, A.W. (1985). Mathematics aptitude: Effects of coursework, household language, and ethnic differences . Urban Education , 20, pp.273–294.
• Murnane, R.J. & Phillips, B.R. (1981, Fall). Learning by doing, vintage, and selection: Three pieces of the puzzle relating teaching experience and teaching performance . Economics of Education Review , 1(4), pp.453–465.
• Murnane, R.J., Singer, J.D., Willett, J.B., Kemple, J.J., & Olsen, R.J. (1991). Who will teach? Policies that matter . Cambridge, MA: Harvard University Press.
• National Assessment of Educational Progress ( 1994). NAEP Trial State Assessment . Washington, D.C.: U.S. Department of Education.
• National Center for Education Statistics ( 1985). The condition of education, 1985 . Washington, D.C.: U.S. Department of Education.
• National Center for Education Statistics (NCES) (1994). Digest of education statistics, 1994 . Washington, D.C.: U.S. Department of Education.
• National Center for Education Statistics ( 1995). The condition of education, 1995 . Washington, D.C: U.S. Department of Education.
• National Center for Education Statistics (NCES) (1996). Schools and staffing in the United States: A statistical profile, 1993–94 . Washington, D.C.: U.S. Department of Education.
• National Center for Education Statistics (NCES) ( 1997. a). America's teachers: Profile of a profession, 1993–94 . Washington, D.C.: U.S. Department of Education.
• National Center for Education Statistics (NCES) (1997. b). Characteristics of stayers, movers, and leavers: Results from the Teacher Followup Survey, 1994–95 . Washington, D.C.: U.S. Department of Education.
• National Commission on Teaching and America's Future (NCTAF) (1996). What matters most: Teaching for America's future . New York: Author.
• National Commission on Teaching and America's Future (NCTAF) (1997). Unpublished tabulations from the 1993–94 Schools and Staffing Surveys.
• National Council on Education Standards and Testing (NCEST). (1992). Raising standards for American education . Washington, D.C.: U.S. Government Printing Office.
• Oakes, J. (1985). Keeping track . New Haven: Yale University Press.
• Oakes, J. (1990). Multiplying inequalities: The effects of race, social class, and tracking on opportunities to learn mathematics and science . Santa Monica: The RAND Corporation.
• Oakes, J. (1992, May). Can tracking research inform practice? Technical, normative, and political considerations. Educational Researcher , 21(4), pp.12–21.
• Oakes, J. (June 1986). “Tracking in secondary schools: A contextual perspective.” Educational Psychologist , 22:pp.129–154.
• Paterson Institute (1996). African American data book . Arlington, VA: Paterson Institute.
• Peikes, V.A. ( 1967–1968 ). Junior high schools science teacher preparation, teaching behavior, and student achievement . Journal of Research in Science Teaching , 6(4): pp. 121–126.
• Pelavin, S.H. & Kane, M. (1990). Changing the odds: Factors increasing access to college . New York: College Entrance Examination Board.
• Peterson, P. (1989). Remediation is no remedy. Educational Leadership , 46(60); pp.24–25.
• Rock, D.A., Hilton, T.L., Pollack, J., Ekstrom, R.B., & Goertz, M.E. (1985). A study of excellence in high school education: Educational policies, school quality, and student outcomes . Washington, D.C.: National Center for Education Statistics.
• Rosenbaum, J. (1976). Making inequality: The hidden curriculum of high school tracking . New York: Wiley.
• Rottenberg, C.J. & Berliner, D.C. (1990). Expert and novice teachers' conceptions of common classroom activities . Paper presented at the annual meeting of the American Educational Research Association .
• Sanders, W.L. & Rivers, J.C. Cumulative and Residual Effects of Teachers on Future Student Academic Achievement . Knoxville: University of Tennessee, 1996.
• Schofield, J.W. (1991). School desegregation and intergroup relations . In G.Grant, editor. (Ed.), Review of Research in Education , 17, pp.335–409. Washington, DC: American Educational Research Association.
• Shields, P.M., Esch, C., Humphrey, D.C., Young, V.M., Gaston, M., & Hunt, H. (1999). The status of the teaching profession: Research findings and policy recommendations . A report to the Teaching and California's Future Task Force . Santa Cruz, CA: The Center for the Future of Teaching and Learning.
• Skipper, C.E. and Quantz, R. 1987). Changes in educational attudies of education and arts and science students during four years of college . Journal of Teacher Education , May–June: pp.39–44.
• Slavin, R.E. (1990). Achievement effects of ability grouping in secondary schools: A best evidence synthesis. Review of Educational Research , 60(3), pp.471–500.
• Strauss, R.P. & Sawyer, E.A. (1986). Some new evidence on teacher and student competencies . Economics of Education Review , 5(1): pp.41–48.
• Strickland, D. (1985). Early childhood development and reading instruction . In C.Brooks, editor. (Ed.), Tapping potential: English and language arts for the black learner. National Council of Teachers of English.
• Sutton, R.E. (1991). Equity and computers in the schools: A decade of research . Review of Educational Research , 61(4), pp.475–503.
• Talbert, J.E. (1990). Teacher tracking: Exacerbating inequalities in the high school . Stanford, CA: Center for Research on the Context of Secondary Teaching, Stanford University.
• Taylor, W.L., & Piche, D.M. (1991). A report on shortchanging children: The impact of fiscal inequity on the education of students at risk . Prepared for the Committee onEducation and Labor, U.S. House of Representatives . Washington, DC: U.S. Government Printing Office.
• Trimble, K., & Sinclair, R.L. (1986). Ability grouping and differing conditions for learning: An analysis of content and instruction in ability-grouped classes . Paper presented at the annual meeting of the American Educational Research Association, San Francisco .
• U.S. Department of Commerce (1996). Statistical abstract of the United States: 1996. , 116th edition. Washington, DC: Bureau of the Census.
• Useem, E.L. (1990, Fall). You're good, but you're not good enough: Tracking students out of advanced mathematics . American Educator , 14(3), pp. 24–27, 43–46.
• Usiskin, Z. (1987). Why elementary algebra can, should, and must be an eighth grade course for average students . Mathematics Teacher , 80, pp.428–438.
• Wheelock, A. (1992). Crossing the tracks . New York: The New Press.
• William T. Grant Foundation, Commission on Work, Family and Citizenship (1988). The forgotten half: Non-college youth in America . Washington, D.C.: Author.
• Wilson, S. (1990). A conflict of interests: Constraints that affect teaching and change . Educational Evaluation and Policy Analysis , 12(3), pp.309–326.
• Wilson, S.M., Darling-Hammond, L, & Berry, B. (2000). Teaching policy: Connecticut's long term efforts to improve teaching and learning . Seattle: Center for the Study of Teaching and Policy, University of Washington.
• Winkler, J.D., Shavelson, R.J., Stasz, C., Robyn, A., & Feibel, W. (1984). How effective teachers use microcomputers for instruction . Santa Monica, CA: The RAND Corporation.
• Wise, A.E., & Darling-Hammond, L. (1987). Licensing teachers: Design for a teaching profession . Santa Monica, CA: RAND Corporation.
• Wise, A.E., Darling-Hammond, L., & Berry, B. (1987). Effective teacher selection: From recruitment to retention . Santa Monica, CA: The RAND Corporation.
• Cite this Page Smedley BD, Stith AY, Colburn L, et al.; Institute of Medicine (US). The Right Thing to Do, The Smart Thing to Do: Enhancing Diversity in the Health Professions: Summary of the Symposium on Diversity in Health Professions in Honor of Herbert W.Nickens, M.D.. Washington (DC): National Academies Press (US); 2001. Inequality in Teaching and Schooling: How Opportunity Is Rationed to Students of Color in America.
• PDF version of this title (2.3M)

In this Page

Recent activity.

• Inequality in Teaching and Schooling: How Opportunity Is Rationed to Students of... Inequality in Teaching and Schooling: How Opportunity Is Rationed to Students of Color in America - The Right Thing to Do, The Smart Thing to Do

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Author Biographies
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

The effectiveness of individualized oral hygiene education in preventing dental diseases: a clinical study.

Share and Cite

Simon, F.; Szabó, G.; Orsós, M.; Mijiritsky, E.; Németh, O. The Effectiveness of Individualized Oral Hygiene Education in Preventing Dental Diseases: A Clinical Study. J. Clin. Med. 2024 , 13 , 5481. https://doi.org/10.3390/jcm13185481

Simon F, Szabó G, Orsós M, Mijiritsky E, Németh O. The Effectiveness of Individualized Oral Hygiene Education in Preventing Dental Diseases: A Clinical Study. Journal of Clinical Medicine . 2024; 13(18):5481. https://doi.org/10.3390/jcm13185481

Simon, Fanni, Gyula Szabó, Mercédesz Orsós, Eitan Mijiritsky, and Orsolya Németh. 2024. "The Effectiveness of Individualized Oral Hygiene Education in Preventing Dental Diseases: A Clinical Study" Journal of Clinical Medicine 13, no. 18: 5481. https://doi.org/10.3390/jcm13185481

Article Metrics

Article access statistics, supplementary material.

ZIP-Document (ZIP, 101 KiB)

Further Information

Mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

2024 NIDA International Forum Executive Summary

June 14-15, 2024                 Montreal, Canada

After three years of virtual meetings, the 2024 NIDA International Forum returned to an in-person format. The meeting, which was held on June 14 and 15 in Montreal in conjunction with the College on Problems of Drug Dependence (CPDD) Annual Scientific Meeting, was cochaired by NIDA International Program’s leadership, Dr. Tom Clarke and Dr. Lindsey Friend. It was attended by over 200 individuals from 73 countries. The meeting included several plenary sessions, four breakout sessions, and an international research poster session featuring 90 posters presented by substance use and addiction researchers from 26 countries.

The Forum began on June 14 with two sessions on advancing quality of addiction study programs and on addiction neuroscience research in Bulgaria, as well as a workshop on how to get addiction research published in peer-reviewed journals.

Day 2 started with the official welcome and updates on NIDA’s programs. This was followed by four breakout sessions on addiction treatment and criminal justice systems, professional healthcare education regarding medical cannabis, addressing opioid stigma in pharmacies, and effective interventions to increase treatment access and intake in real-world settings across the globe. The meeting concluded with two plenary sessions that discussed substance use and associated health problems in humanitarian settings and addressed two current global topics, namely, emerging synthetic drugs in Latin America and the Caribbean and the treatment of children with substance use problems. Rounding out the program were a joint workshop conducted by NIDA staff and staff from the CPDD, as well as a poster session.

Following are brief summaries of the topic sessions presented at this year’s International Forum.

Welcome and NIDA Update

Dr. Clarke provided a high-level overview of NIDA’s research priorities. In the United States, the most pressing problem continues to be the opioid overdose crisis, which is currently driven by co-use of fentanyl and stimulants and disproportionately affects American Indian/Alaska Native and Black communities. Also highly concerning are continued high rates of unintentional fentanyl-related overdose deaths in youths ages 15-19. In response, NIDA’s 2022 to 2026 strategic plan has identified five core research priorities, including (1) understanding drugs, the brain, and behavior; (2) prevention, treatment, and recovery; (3) the intersection of substance use and HIV; (4) implementation science; and (5) innovative heath applications.

Dr. Clarke also introduced several large programs that NIDA supports — partly together with other NIH Institutes — to address the opioid public health crisis. One of these efforts is the Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative® — an NIH-wide effort to speed scientific solutions to the opioid health crisis that is jointly led by NIDA and the National Institute on Neurological Disorders and Stroke. Other major NIDA-supported research efforts include the longitudinal HEALthy Brain and Child Development (HBCD) and Adolescent Brain Cognitive Development (ABCD) studies, the HEALing Communities Study, the Justice Community Opioid Innovation Network (JCOIN), the Harm Reduction Research Network, and the NIDA Clinical Trials Network. Together, these efforts address challenges, such as emerging drugs (e.g., xylazine), increasing fentanyl and polysubstance use, persistent stigma, better care for hard-to-reach and underserved populations, continuity of care for substance use disorders (SUDs), and novel harm reduction approaches.

Dr. Friend summarized the activities of the NIDA International Program and its role in international policy development, information, exchange, research, and training. In particular, NIDA supports international research through grants awarded to U.S. researchers partnering with foreign investigators. NIDA’s international training and research programs include INVEST postdoctoral fellowships and Hubert H. Humphrey Fellowships. INVEST fellowships offer a 12-month postdoctoral research training with a NIDA grantee that includes professional development activities to establish personal relationships between the fellows and NIDA grantees and NIDA officials. They are for international researchers with a doctoral degree and a minimum of 2 years postdoctoral experience. Hubert H. Humphrey Fellowships are mid-career fellowships to approximately 12 individuals per year that include a 10-month research fellowship at Virginia Commonwealth University as well as 6-week professional affiliations, allowing fellows to make connections to advance their ongoing work. Additionally, NIDA offers the Distinguished International Scientist Collaboration Awards (DISCA) that fund innovative collaborations between international and NIDA-funded senior researchers. Dr. Friend also highlighted NIH’s Research Portfolio Online Reporting Tool, NIH RePORTER ( https://reporter.nih.gov ), as an excellent tool for learning about NIDA-funded projects or investigators funded in other countries.

Addiction Treatment and Criminal Justice Systems: Drug Policy Reforms and Implications

This breakout session was chaired by Dr. Gregory Bunt from the International Society of Addiction Medicine (ISAM), who introduced the International Consortium for Alternatives to Incarceration (ICATI). ICATI works with countries, organizations, professionals, and program sites to support the global development of treatment, care, and accountability as alternatives to incarceration for individuals who use drugs and become involved with the justice system. At various stages in the judicial process, the justice system can divert people to treatment and services in the community instead of incarcerating them. This has been shown to reduce recidivism. To help adopt and implement such measures, ICATI promotes and supports all phases of national and regional planning, training, technical assistance, evaluation, and implementation; identifies, develops, and provides resources; and helps establish international networks.

In lieu of Dr. Carl Erik Fisher from Columbia University in New York, who was not able to attend the meeting, Dr. Bunt also gave Dr. Fisher’s presentation on the “Portuguese model” of decriminalization as an alternative harm reduction approach for treating SUDs in minoritized communities. Decriminalization means elimination of criminal penalties for drug possession for personal use; it differs from depenalization, which generally means that criminal penalties are reduced or not enforced but are not legally eliminated, and from legalization of drug use. This approach was first implemented in Portugal, where drug possession was decriminalized in 2001 but people carrying a personal drug supply had to get mandatory treatment. This was accompanied by several other socio-medical and harm-reduction interventions for a holistic approach with wrap-around services. However, because existing laws against personal drug use had already been only loosely enforced, decriminalization may ultimately have formalized existing practices rather than drive new norms and attitudes. In the United States, a similar approach has been implemented in Oregon but has been less successful because people were not diverted to effective treatment. This suggests that even the best reform programs do not guarantee success because drug-related problems are shaped by additional factors, such as cultural attitudes, social support networks, or mental health resources.

Dr. David Martell from the Canadian Society of Addiction Medicine reported on Canada’s drug decriminalization efforts. Canada has a history of targeted exemptions from penalizing drug use, from prescription maintenance programs and wide availability of opioid agonist therapy to supervised consumption sites and drug checking programs. Dr. Martell also listed various legislative approaches to drug decriminalization, such as the 2017 “Good Samaritan Drug Overdose Act” or cannabis legalization in 2018, which legalized personal use but maintained criminal penalties for certain offenses. This legalization resulted in increased cannabis use for most age groups and a temporary increase in the cannabis industry, but more Canadians now get cannabis legally. A newer decriminalization pilot program started in 2023 decriminalizes use of small amounts of opioids, crack, cocaine, methamphetamine, or MDMA at certain sites (e.g., private residences, but also overdose prevention, drug checking, or supervised consumption sites). The aim is to eliminate the harms associated with drug seizure, help connect people who use drugs to services and support, and enhance public awareness and understanding. However, over the first 12 months, the project has not yielded benefits, and many issues are also still unaddressed. Dr. Martell concluded that Canada’s national drug policy landscape is still fragmented and the search for the best approach continues.

Dr. Hamed Ekhtiari from the University of Minnesota and ISAM Regional Council chair, discussed how the ISAM Global Expert Network (ISAM GEN) can contribute to global drug policy reforms. ISAM’s organizational hierarchy allows for representation and policy involvement across the globe through regional representatives, national ambassadors, addiction medicine societies, and 10 country experts for each country who represent the ISAM GEN. By eliciting information from these experts and conducting a range of global surveys, ISAM GEN can help map and reshape global policies. ISAM GEN has established a well-honed road map for conducting their surveys, from idea development and steering committee formation all the way to manuscript submission. ISAM GEN’s first global survey assessed treatment service provision for opioid use disorder by querying national addiction societies and organizations in 39 countries from six continents. It gathered valuable information on availability of different types of opioids and availability of different types of treatment services for opioid use disorder, harm reduction facilities, and 12-step programs. Researchers interested in establishing their own international working groups or developing surveys can contact ISAM for further information.

Medical Cannabis in Professional Healthcare Education: Multinational Policies, Perspectives, and Competencies

In this breakout session, which was moderated by Dr. Richard Isralowitz from the Ben-Gurion University of the Negev—RADAR Center in Israel, Dr. Richard Rawson, professor emeritus from the University of California, Los Angeles, first provided a historical overview of substance use training in professional curricula. He noted that information on substance use and its impact has only recently been integrated into professional healthcare training rather than being covered only in ad-hoc separate training events. Since 2000, training in substance use and its treatment has become more formalized, with exams and certification processes offered by national and international certification organizations. International training activities are coordinated by the International Consortium of Universities for Drug Demand Reduction (ICUDDR), which facilitates networking among universities to promote high-quality education and training for prevention, treatment, and public health intervention purposes. As a result, many universities now integrate alcohol, tobacco, and other drug content into their curricula, often within many specialty areas; however, cannabis and medical marijuana remain a new curriculum topic.

Dr. Yuval Zolotov from the Albert Einstein College of Medicine in the Bronx, New York, summarized the results of an international survey among healthcare professions’ students in Israel, Malta, Greece, Cyprus, Russia, Belarus, Thailand, and the United States regarding their attitudes, beliefs, and knowledge about medical cannabis. Participants were 4,427 students (70% female) of medicine, nursing, social work, and psychology; 74% came from countries where medical cannabis was legal. Dr. Zolotov reported that, overall, respondents expressed relatively high levels of support for medical cannabis, but also concerns about potential risks and harms. Almost all respondents believed that medical cannabis should be included in their education and practical experiences, but almost 87% reported receiving no formal education in this area. As a result, about 70% of respondents felt unprepared to answer patient questions about medical cannabis. Dr. Zolotov concluded that a great need for formal education in medical cannabis exists and that standardized curricula can help bridge the existing gaps.

Dr. Mazen Sakka from the Substance Abuse Research Center, Palestine, summarized a similar survey among medical staff at two hospitals and students at four universities in the Palestinian territories (West Bank, Gaza Strip) about their knowledge, beliefs, and attitudes regarding medical cannabis. The survey also explored the roles of gender, religiosity, and legal status of medical cannabis on these domains. In the Palestinian territories, cannabis is considered a schedule I substance, together with other addictive drugs. The survey found that while most medical staff and many students believed that medical cannabis can help certain patients, they also saw a high risk of mental and physical health problems. However, many respondents had only limited knowledge on the subject. Additionally, attitudes and beliefs differed somewhat between males and females and were affected by religious views and the fact that cannabis is considered an illegal drug. Nevertheless, Dr. Sakka noted that most respondents seemed open to more information or training on medical marijuana, supporting efforts to enhance such activities.

Given the apparent need for and interest in professional healthcare education on medical cannabis, Dr. Mikhail Kogan from George Washington University and Dr. Leslie Mendoza Temple from the University of Chicago described a Delphi process to identify teaching standards and essential medical cannabis education competencies. The Drug Enforcement Agency in the United States is set to reschedule cannabis to a lower status, which would require all pharmacies in the United States to carry cannabis products. After a 2021 scoping review found that healthcare trainees lack proper education and knowledge about medical cannabis, implementation of expanded competencies-based curricula is essential. Drs. Kogan and Temple described the Delphi process methodology, which relies on synthesizing opinions among a group of experts via repeated rounds of discussion until a consensus is reached. In this case, the process involved 23 experts with different areas of expertise, who identified six core competencies to guide development of medical school curricula in the United States and Canada. These included (1) understanding the basics of the endocannabinoid system, (2) describing the main components of the cannabis plant and their effects, (3) reviewing the legal and regulatory landscape on cannabis in the United States, (4) describing the evidence base for health conditions that are commonly managed with cannabis, (5) understanding the potential risks of medical cannabis use, and (6) understanding basic clinical management with medical cannabis.

Addressing Opioid Stigma in Pharmacies — Developing Strategies for Pharmacy Professionals

This breakout session with Dr. Beth Sproule and Dr. Braiden Cutmore from the Canadian Centre for Addiction and Mental Health and Dr. Sarah Bhatti from the Public Health Agency of Canada (PHAC) centered on the stigma that people who use drugs and people with chronic pain frequently face. The session focused specifically on stigma from pharmacy professionals. As Dr. Bhatti noted, experiences of stigma may decrease use of treatment and social services as well as quality of care. A 2019 report by the Canadian Chief Public Health Officer concluded that responding to stigma in the health system requires a comprehensive approach through education, training, practice, and policy. PHAC conducted a literature review to clarify the nature and manifestations of stigma; assess stigma related to treatment with naloxone, opioid agonist therapy, harm reduction approaches, and opioid treatment for pain in pharmacy professionals; as well as anti-stigma approaches. The review identified several key ingredients for anti-stigma programs, such as repeated social contact, demonstration of recovery, myth busting, and enthusiastic facilitation. Dr. Bhatti also indicated that targeted education is more successful than general education.

Dr. Cutmore described several stakeholder roundtables organized by PHAC that discussed definitions of stigma, experiences of stigma, positive experiences with pharmacies, and potential messages for pharmacy professionals. The roundtables included people with opioid use disorder, people with chronic pain, and pharmacy professionals, respectively. Based on the feedback from the three stakeholder groups, six messages for pharmacists were drafted that addressed the main themes raised — for example, that pharmacy professionals need to see patients as a whole person and treat them with dignity and respect, that they need to understand the patient’s opioid medication experience and act as allies to support patients, or that they need to proactively engage and empower patients through education. Agreement with these messages was then assessed in an anonymous survey among roundtable participants. According to Dr. Cutmore, the roundtables and resulting messages highlighted that it is crucial for pharmacy professionals to challenge negative attitudes and beliefs by reflecting on their assumptions toward people taking opioids and recognize their impact. Additionally, they need to help empower through communication their patients who are prescribed opioids.

Dr. Sproule then presented a newly developed tool kit delineating strategies for pharmacy professionals to address opioid stigma in pharmacies. It highlights eight key strategies to support people who use opioids, such as respecting all customers equally, getting to know customers, offering support through education, explaining and reviewing pharmacy process, providing harm reduction services, delivering compassionate healthcare, respecting the right to privacy, and raising public awareness. The toolkit also provides tips on how to put those strategies into practice. One concept Dr. Sproule highlighted is the idea that “words matter” — that how one talks to or about people who use substances can either reinforce or, in contrast, counter stigmatizing attitudes, views, and actions. The toolkit also includes social media assets and posters to raise awareness of and address opioid stigma in pharmacies. Infographics, videos, courses, and other resources are also available. The toolkit was launched in February 2024 with a webinar attended by more than 250 pharmacy professionals and other stakeholders.

Successful Real-World Evidence-Based Interventions That Have Increased Treatment Access and Intake in Different Countries

This breakout session was chaired by Dr. Adrian Abagiu from the Romanian National Institute for Infectious Diseases and Dr. Matei Bals from the ARENA OST Center in Romania. Dr. Abagiu reported on a program in Romania to increase adherence to antiretroviral therapy (ART) among people living with HIV (PLWH) who were incarcerated. He described that some of these individuals refused ART due to restrictions according to detention regulations. To improve ART adherence, they developed an information program involving a 20-minute PowerPoint presentation, a 10-minute Q&A session, and information leaflets for small groups of PLWH at one of the prisons. The intervention improved adherence, but the effect declined after 4 months. As a result, the program was refined further and assessed in a study comparing 100 PLWH who received the intervention with 50 PLWH who did not in one jail. Before the intervention, ART refusal rates were the same in both groups. After the intervention, refusal rates declined in the intervention group, but remained relatively stable in the control group; again, the effect was lost at 4 months after the intervention. Based on these findings, the intervention was delivered every 2 months to all new PLWH arriving at the prison, and while it had to be halted during the COVID-19 pandemic, it was resumed after the end of the pandemic.

Next, Dr. Dace Svikis from Virginia Commonwealth University described the Expanding Medical Prevention and Outreach While Enhancing Recovery and Retention (EMPOWER) project that seeks to increase engagement and retention in SUD and HIV treatment for underserved Black people in Baltimore, Maryland. Dr. Svikis explained that Baltimore has one of the highest rates of new HIV cases and also has the highest fatal overdose rates among large cities in the United States, but is also a leader in SUD treatment and harm reduction approaches. EMPOWER was assessed within the Recovery Enhanced by Access to Comprehensive Healthcare (REACH) Health Services Program that offers comprehensive outpatient SUD treatment as well as mental health counseling. However, Black individuals in the program were less likely to engage in SUD treatment, more likely to drop out of care, and thus less access to HIV-related testing and care. The EMPOWER program seeks to address these disparities using tailored, patient-focused, evidence-based interventions to engage and retain Black individuals in treatment. Importantly, the EMPOWER team includes people who have lived experience and represent the population of focus, such as peer recovery specialists and nurse care managers. EMPOWER uses evidence-based interventions, such as motivational interviewing, continency management, safer sex skill building, and Seeking Safety, a cognitive behavioral therapy for post-traumatic stress disorder and SUD. The EMPOWER program started recruitment in February 2024 and will last 6 months, after which regular REACH services will continue. Preliminary findings indicate that EMPOWER can increase treatment retention at 3 months compared with the normal REACH program; additional data will be gathered in the coming months.

The third presenter was current Hubert H. Humphrey Fellow Thinzar Tun from Myanmar, director of the Asian Harm Reduction Network (AHRN) and Best Shelter Myanmar, who reported on a program she is spearheading to increase treatment access and intake for people who use drugs (PWUD) or inject drugs (PWID). She explained that Myanmar has about 93,000 PWID, about 35% of whom have HIV. AHRN provides facility-based harm reduction, treatment, and care, whereas Best Shelter offers community-based harm reduction, prevention, referral, and care. Specific services include outreach, health education, self-help groups, job creation efforts, peer education, counseling, and treatment. Some services are specifically aimed at women as a particularly vulnerable population, such as services to improve sexual and reproductive health, as well as pre- and postnatal care, and services to curb gender-based violence. Ms. Tun specifically described their needle and syringe programs, including efforts to return and safely dispose of used needles and syringes, as well as HIV testing and treatment. These are implemented either during outreach with mobile units or at fixed locations in clinics or in the community. Ms. Thun reported that for 2022, about 18 million needles and syringes were distributed, with a return rate of 86%. For HIV testing, the program brought testing closer to the PWID and their families, allowed for effective linkage to care and rapid ART initiation, as well as testing and treatment in hard-to-reach locations. The program reduced the proportion of PWID who were HIV positive and achieved high linkage to treatment and ART initiation for both PWUD and PWID and their sexual partners. Ms. Tun concluded that to address drug use and HIV in countries such as Myanmar, understanding the context and needs of clients is essential, and that community inclusion and harm reduction approaches work.

Substance Use and Associated Health Problems in Humanitarian Settings — Responding to the Needs of Affected Populations

This plenary session was started by Dr. Anja Busse from the United Nations Office on Drugs and Crime (UNODC), who provided an update on addressing substance use in humanitarian emergencies. Dr. Busse explained that humanitarian emergencies (e.g., disasters, armed conflicts, epidemics) threaten the lives and well-being of very large numbers of people or a very large percentage of a population, often result in displacement, and require assistance from multiple sectors. There is only limited evidence on substance use among displaced persons; however, there seem to be regional differences regarding the most commonly used substances. Displaced populations or people in humanitarian emergencies may face particular challenges related to drug use, such as sudden interruptions of patterns of drug use, disruption of treatment services, and resumption of drug use with increased risk of overdose; these compound social and mental health problems associated with humanitarian crises. Dr. Busse noted that substance use is included in humanitarian health guidance as part of mental health interventions. A Desk Review by the United Nations High Commissioner for Refugees (UNHCR) found that community-based, peer-led programs and training of healthcare workers in SUD treatment are feasible in low-resource and refugee settings and that brief interventions have significant potential. Opioid agonist therapy may also be possible in humanitarian settings with support from international donors and organizations. Several international policy documents have provided policy direction for addressing SUDs in humanitarian emergencies. UNODC and the World Health Organization (WHO) have a joint program for such situations, and the UNODC/WHO International Standards for Treatment of Drug Use Disorders can be adapted for humanitarian emergencies. A handbook by UNODC, UNHCR, and WHO will soon be published, disseminated, and field-tested. It creates an implementation framework for both the acute phase and the protracted phase of the emergency. It has identified two main principles — saving lives first (i.e., addressing life-threatening concerns such as overdose and withdrawal first), and full inclusion of people with SUD in other support available.

Dr. Dzmitry Krupchanka from the WHO described the organization’s approach to addressing substance use during humanitarian emergency responses. He noted that people in humanitarian settings have much higher rates of mental health problems than other populations; moreover, mental and physical health conditions are often comorbid with SUDs. Dr. Krupchanka mentioned a 2024 WHO draft resolution on strengthening mental health and psychosocial support (MHPSS) before, during, and after humanitarian emergencies. The resolution includes MHPSS as an integral component of preparedness, response, and recovery activities in all emergencies. He then reviewed the Inter-Agency Standing Committee (IASC) Guidelines on Mental Health and Psychosocial Support in Emergency Settings, which delineate key actions to minimize harm related to alcohol and other substance use. These measures aim to conduct rapid assessments, prevent harmful alcohol and other substance use and dependence, facilitate harm reduction interventions in the community, and manage withdrawal and other acute problems. An open, free course is available to learn about this, as well as some cultural adaptations. Additionally, several WHO resources to address substance use and its consequences in humanitarian settings will be forthcoming.

Dr. Karen Paul from the IASC Reference Group for Mental Health and Psychosocial Support in Emergencies talked about interagency collaboration regarding substance use and SUD in humanitarian emergencies. She emphasized that a multi-sector response is needed in such situations, and some of these sectors are also addressed in the IASC Guidelines mentioned by Dr. Krupchanka. Dr. Paul also described the IASC MHPSS Reference Group, which is cochaired by WHO, UNODC, and UNHCR and involves over 11 member agencies as well as five observers. Their current priority is developing materials for training and orienting various groups of humanitarian workers on substance use, from materials for basic communication to materials on advanced interventions. For example, orientation materials are being developed on SUDs as health conditions, how to provide support, life-threatening conditions related to substance use, and similar topics. These materials are currently being field tested, with an eye to adapting them to various cultures and contexts. A substance use module for integrating MHPSS into disaster risk management and preparedness training is also being developed, including a framework for assessment and action.

Finally, Dr. Mustafa al’Absi from the Duluth Global Health Research Institute and the University of Minnesota discussed the implications of traumatic stress and substance use in the context of humanitarian emergencies. He noted that trauma exposure, particularly in children and adolescents, is associated with an increased risk for SUD; moreover, substance use can impact the course and severity of traumatic stress symptoms. Increases in political conflicts as well as natural disasters have led to rising mental health and substance use problems. Consequently, it is important to integrate mental health and substance use services in emergency responses and increase capacity for trauma-informed care among humanitarian workers. Dr. al’Absi presented case studies from recent conflicts and natural disasters, such as the conflicts in Syria, Yemen, and Afghanistan, or the an earthquake in Turkey. Each of these has unique features regarding substance use that need to be considered. The crisis in Afghanistan also provided an example of partnerships between WHO, UNODC, and others for treatment of SUDs to improve the health and well-being of vulnerable populations. Dr. al’Absi concluded that guidelines informed by epidemiological, intervention, and implementation knowledge are needed to address the challenge of SUD in humanitarian settings. He also issued a call to action for improving substance use services capacity and integration in humanitarian emergencies in order to help prioritize the well-being of affected populations in emergency response efforts. These efforts also must address the issue of stigma in order to be effective.

Current Global Topics: Synthetic Drugs in Latin America and the Caribbean and Treating Children for Substance Use Problems

In this session moderated by Dr. Andrew Thompson from the Bureau of International Narcotics and Law Enforcement Affairs (INL), Dr. Marya Hynes from the Inter-American Observatory on Drugs reported on emerging synthetics and new psychoactive substances (NPS) in Latin America and the Caribbean. She noted that synthetic drugs have proliferated in those drug markets, particularly since 2013, and that NPS also have become more common. Of concern are amphetamine-type stimulants (ATS), such as amphetamines and prescription stimulants, methamphetamine, synthetic hallucinogens, and synthetic opioids. Information on NPS is coming from drug seizures and early warning data that are reported to the Early Warning System for the Americas. These notifications have highlighted several trends, such as appearance of “pink cocaine” (a mixture of various synthetic compounds); increasing prevalence of benzodiazepines in females in every population studied; greater presence of stimulants, particularly among females; synthetic cannabinoids; and a variety of synthetics sold as other drugs. As Dr. Hynes emphasized, even at low prevalences, these trends are concerning because they indicate that people are using more and more mixed and adulterated substances that have unknown composition, unknown effects, often high potency, and often rapid onset and long duration of effects. The most severe implications are for countries with fragile health care systems. These developments affect particularly teenagers and young adults, including health risks and mental health issues that drive drug use and are themselves driven by drug use. These developments need to inform efforts for detection, treatment, and prevention.

Dr. Antonio Pascale from the University of Montevideo further described the health impacts of NPS and increasing availability of adulterated drugs among younger users. For example, adulterants may potentiate the toxicity of the original drugs or induce unintended toxic effects. ATS are associated with harmful effects, such as hyperthermia, which can be exacerbated by the settings where these drugs are often consumed (e.g., clubs with high temperatures, poor ventilation, and intense physical activity); serotonergic syndrome; and hyponatremia. Synthetic cannabinoids, which are increasingly used by young people as well as other vulnerable populations, can be associated with acute toxicity as well as greater morbidity and mortality in the context of polydrug use. Synthetic opioids (e.g., fentanyl and its analogues, nitazenes) are an increasing problem in Latin America with the associated acute toxicity and risk of fatal overdoses. An emerging concern is illicit use of benzodiazepines (often as adulterants of other drugs), which is associated with acute intoxication and altered consciousness that increases vulnerability to sexual crimes and other harms. Dr. Pascale concluded that to address this public health problem effectively, it is essential to strengthen networks involving government agencies, clinical and forensic laboratories, universities, toxicology centers, and nongovernment agencies with access to PWUD.

Dr. Hendrée Jones from the University of North Carolina at Chapel Hill provided an overview of the Child Intervention for Living Drug-free (CHILD) program to treat children under age 12 for substance use problems. Dr. Jones explained that children are increasingly victims of drug trafficking and drug use within their families and communities, leading to children as young as 5-12 years having an SUD. The CHILD intervention was developed to respond to this growing threat. It is a global, evidence-based program with an integrated health approach, full spectrum of services, and family involvement. It includes professional development and a tailored program for each country that uses techniques (e.g., motivational interviewing, mindfulness, dialectic behavior therapy, art therapy) that can be translated into language and activities appealing to children. The program has been disseminated to numerous countries through “training of trainers,” webinars, and “Echo” training. Dr. Jones also shared information on a randomized clinical trial of the CHILD intervention in children ages 7-12 in India. Preliminary results indicate that it reduces substance use in these children at 12 months after treatment better than usual care.

Advancing Quality in Addiction Studies Programs

In this session chaired by Dr. Carly Searcy from ICUDDR, Mr. Jordan Turner, also from ICUDDR, provided an overview of the current state of quality assurance in specialty addiction studies programs. He shared results from a survey of 322 ICUDDR members that assessed program quality along six dimensions of care in members’ curricula. Among the 88 respondents, 63% addressed quality improvement through their curriculum plans. However, qualitative data indicated a minimal focus on quality of care among institutions; barriers within member institutions that prevented quality of care to be addressed, and a need for ICUDDR’s assistance in curriculum building. Mr. Turner concluded that the study positioned ICUDDR to work with members to create frameworks for addressing quality and quality improvement.

Dr. Amelie Lososová from the Charles University in Prague presented previous research on establishing quality assurance at the university level. Several organizations, such as the Substance Abuse and Mental Health Services Administration, American Society of Addiction Medicine, and American Psychiatric Association in the United States, as well as the WHO have addressed quality standards in education programs. Similarly, two projects (WAVE project and FENIQS-EU project) have been conducted in Europe, and for the WAVE project, several project papers will be published soon. Dr. Lososová noted the importance of making education a research focus and highlighted several future research questions and challenges—for example, whether international standards are really needed, what areas of addiction research should be included; which educational programs should apply the standards; and how regional, cultural, and communication differences can be accommodated.

Dr. Dennis McCarty from the Oregon Health & Science University discussed what kind of research is needed. Examples included integration of research into educational standard development, integration of outcome measures into training processes and systems of care, assessments of the impact of standards on care delivery and outcomes, and cross-national comparisons of training and training standards. Dr. McCarty pointed out that each country is unique, and it is therefore important to determine which facets of addiction studies programs are replicable and generalizable. The relatively new areas of dissemination and implementation research are also crucial to determine how research findings can be translated into standards of practice on an international scale.

In the final presentation, Dr. Victor Capoccia from the Technical Assistance Collaborative discussed the development a certification framework for addiction studies programs as a documentation of program quality. He also highlighted questions that would need to be addressed in this process. For example, what should be included in a certification according to international standards (e.g., minimum content for the curriculum, minimum hours of exposure to content, number and qualifications of faculty). Equally important is an understanding of factors that drive differences in standards across the globe. Levels of education and credentialing desired (e.g., nondegree certification, associate, baccalaureate, master’s), cultural and historical contexts of drug use, governmental/legal context, health system infrastructure, and medical traditions all need to be considered. In fact, one set of standards may not be appropriate for all international scenarios. Thus, development of any certification or accreditation process must first determine what components are nonnegotiable and must be uniform and what country or regional characteristics might be accommodated in variations from the standards.

Twenty Years of Addiction Neuroscience Research in Bulgaria: Lessons Learned and Future Directions

This session presented the results of three sets of studies conducted by a large multinational team of researchers in Bulgaria over the past 20 years. As the first presenter, Dr. Jasmin Vassileva from Virginia Commonwealth University, explained, Bulgaria is well suited for their studies of people who use opiates and stimulants because it is located on one of the main heroin trafficking routes into Europe and is a major center for amphetamine production. Dr. Vassileva is investigating which dimensions of impulsivity are associated with addiction in general or specific drug classes. Her team used computational approaches to address this question, including data-driven, machine learning processes for classification and prediction, as well as theory-driven cognitive modeling to increase precision of neurocognitive phenotyping. Dr. Vassileva presented results of several of their studies that have been published in recent years. The findings indicated that some dimensions of impulsivity are common across addictions, whereas others are unique to specific drug classes. The studies also demonstrated that computational approaches have significant potential as phenotyping tools, for identifying markers for addictions, for increasing precision of neurocognitive assessments, and for prognosis and diagnosis. They may also help refine neurocognitive phenotypes and identify different biotypes of addictions with different underlying mechanisms, which may have implications for prevention and intervention.

Dr. Elena Psederska from the New Bulgarian University presented on studies assessing the interplay of personality and neurocognitive function in stimulant and opioid use disorders. Specifically, the team studied the effects of psychopathy on neurocognitive domains of impulsivity in people who previously had used heroin and amphetamine. They assessed the effects of the interpersonal/affective domain and the impulsive/antisocial domain of psychopathy on impulsive choice and impulsive action in both groups. The analyses identified an interaction between the two dimensions of psychopathy and dependence on specific classes of drugs. Some profiles were common across SUDs, whereas others were unique for specific drugs. Another investigation assessed neurocognitive impulsivity in people who used heroin at different times of abstinence. These analyses demonstrated that while some deficits in impulsive choice and impulsive action may only occur in early abstinence, others may persist even with sustained periods of abstinence. Overall, Dr. Psederska concluded that personality influences both common and unique profiles of impairments in neurocognitive impulsivity in people who use opioids or stimulants, and that these impairments may persist even with sustained abstinence. Thus, extended treatment and rehabilitation approaches that are tailored to individual personality profiles are needed.

The final presentation by Dr. James Bjork from Virginia Commonwealth University addressed similarities and differences in brain recruitment by reward, inhibition, and memory in people with different SUDs. The study included individuals with opioid, stimulant, or polysubstance use disorder as well as controls and compared individual differences in brain activation as measured by MRI while participants were conducting three different tasks. The study is still ongoing, but there is preliminary evidence that brain areas activated by specific tasks can be correlated with characteristics determined in addictions neuroclinical assessments, such as emotion-related impulsivity, cognitive difficulties in daily life, or inattention.

Publishing Workshop: How to Get Your Addiction Research Published in Peer-Reviewed Journals

In this workshop, Adam Gordon and Casy Calver from the International Society of Addiction Journal Editors (ISAJE) highlighted three essential aspects to publishing addiction research: choosing a journal, submission and peer review, and authorship. They noted that there are over 100 peer-reviewed addiction journals, and journals from other disciplines also publish addiction articles. They listed 15 factors to consider when choosing a journal as well as questions to ask of a journal (e.g., whether it reaches the specific audience authors want to target, the journal’s mission and content area). Practical aspects, such as editorial support provided or cost of publication/open access, are also important, as are various metrics associated with the journal. These include journal metrics (e.g., impact factor), public impact metrics (e.g., Altmetric attention score), editorial efficiency metrics (e.g., time to first decision, acceptance rate), and author metrics.

For submitting manuscripts, authors first need to check author guidelines, select an appropriate article type, and obtain approval from all authors to submit. Once a manuscript is submitted, a multistep peer-review process follows that may include one or more author revision steps. Peer review is essential to advise the editorial decision-making process, justify rejections, improve the quality of acceptable manuscripts, and identify instances of ethical or scientific misconduct. While the reviewers make recommendations, the editors make the final decision and may even disagree with reviewer recommendations. If the decision is to revise and resubmit the paper, authors should decide if they want to resubmit the paper and, if so, respond to each criticism by either modifying the manuscript or debating/refuting the criticism.

The issue of authorship is increasingly important. The authors on a manuscript certify a public responsibility for the truth of the publication. Authorship also is an indicator of productivity, promotion, and prestige, and credit should be assigned equitably. Especially in addiction research, inclusion of people with lived experience (e.g., patient coauthors in case studies) is important but authors also need to be aware of and sensitive to ethical considerations. Several measures can be taken to avoid authorship problems (e.g., early agreement on the precise roles of all contributors; periodic review of authorship credit status, and adherence to authorship guidelines). Overall, authors must avoid the “seven deadly sins” of carelessness, redundant publication, unfair authorship, undeclared conflict of interest, human subjects’ violations, plagiarism, and other fraud. To avoid plagiarism, all sources must be appropriately acknowledged and permission for use of large amounts of others’ written or illustrative materials obtained. This also applies to self-plagiarism, as authors are not allowed to reuse previously published materials when rights have been assigned to the publisher. The ISAJE provides author resources on their website ( https://www.isaje.net/ ); additional information is available in the JAMA Users’ Guide to Medical Literature and from the Committee on Publication Ethics (COPE) ( https://publicationethics.org ).