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Introduction to Action research

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• What Is Action Research? | Definition & Examples

What Is Action Research? | Definition & Examples

Published on January 27, 2023 by Tegan George . Revised on January 12, 2024.

Table of contents

Types of action research, action research models, examples of action research, action research vs. traditional research, advantages and disadvantages of action research, other interesting articles, frequently asked questions about action research.

There are 2 common types of action research: participatory action research and practical action research.

• Participatory action research emphasizes that participants should be members of the community being studied, empowering those directly affected by outcomes of said research. In this method, participants are effectively co-researchers, with their lived experiences considered formative to the research process.
• Practical action research focuses more on how research is conducted and is designed to address and solve specific issues.

Both types of action research are more focused on increasing the capacity and ability of future practitioners than contributing to a theoretical body of knowledge.

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Action research is often reflected in 3 action research models: operational (sometimes called technical), collaboration, and critical reflection.

• Operational (or technical) action research is usually visualized like a spiral following a series of steps, such as “planning → acting → observing → reflecting.”
• Collaboration action research is more community-based, focused on building a network of similar individuals (e.g., college professors in a given geographic area) and compiling learnings from iterated feedback cycles.
• Critical reflection action research serves to contextualize systemic processes that are already ongoing (e.g., working retroactively to analyze existing school systems by questioning why certain practices were put into place and developed the way they did).

Action research is often used in fields like education because of its iterative and flexible style.

After the information was collected, the students were asked where they thought ramps or other accessibility measures would be best utilized, and the suggestions were sent to school administrators. Example: Practical action research Science teachers at your city’s high school have been witnessing a year-over-year decline in standardized test scores in chemistry. In seeking the source of this issue, they studied how concepts are taught in depth, focusing on the methods, tools, and approaches used by each teacher.

Action research differs sharply from other types of research in that it seeks to produce actionable processes over the course of the research rather than contributing to existing knowledge or drawing conclusions from datasets. In this way, action research is formative , not summative , and is conducted in an ongoing, iterative way.

As such, action research is different in purpose, context, and significance and is a good fit for those seeking to implement systemic change.

Action research comes with advantages and disadvantages.

• Action research is highly adaptable , allowing researchers to mold their analysis to their individual needs and implement practical individual-level changes.
• Action research provides an immediate and actionable path forward for solving entrenched issues, rather than suggesting complicated, longer-term solutions rooted in complex data.
• Done correctly, action research can be very empowering , informing social change and allowing participants to effect that change in ways meaningful to their communities.

Disadvantages

• Due to their flexibility, action research studies are plagued by very limited generalizability  and are very difficult to replicate . They are often not considered theoretically rigorous due to the power the researcher holds in drawing conclusions.
• Action research can be complicated to structure in an ethical manner . Participants may feel pressured to participate or to participate in a certain way.
• Action research is at high risk for research biases such as selection bias , social desirability bias , or other types of cognitive biases .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2024, January 12). What Is Action Research? | Definition & Examples. Scribbr. Retrieved August 12, 2024, from https://www.scribbr.com/methodology/action-research/

Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education (8th edition). Routledge.

Naughton, G. M. (2001).  Action research (1st edition). Routledge.

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Action Research in Education

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This paper presents a view of action research (AR) as a valuable way in which teachers can pose fertile questions and engage in inquiry with transformative possibilities. This counters claims of its being at best a sterile method of teacher research and at worst a perilous trap for teachers. Chris Higgins has argued that AR has lost its original intention of empowering teachers and sealing the theory practice divide. He claims that it has degenerated into a method devoid of thought. In its social science versions, it is harmful to the teacher–student relationship and teachers have been mislead into an impoverished idea of professional development. The impossible challenge for action research is to recover its original intention; impossible because the landscape of educational policy militates against it. The authors challenge Higgin’s deep pessimism, his versions of AR and his negative account of the intellectual capacity of teachers. We argue that AR does empower teachers, integrates theory and practice and is alive and well, even though conditions in schools are not optimum. This argument is exemplified with numerous illustrations of actual AR projects, which evidence teachers’ participatory and collaborative work, in which they engage in positive change. There is scope for teachers wishing to develop ‘customised’ AR projects of their own in current conditions which have transformative potential in changing the practice of the individual teacher. This in turn supports building and participating in a ‘community of practice’, which strengthens the communal endeavour to contribute to good teaching and good education.

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Twenty years into democracy in South Africa, poverty and disease continue to limit the life prospects of the majority of people. Researchers in higher education have an opportunity, not to mention a moral obligation, to direct their research towards finding ways to ensure that the expected fruits of democracy can be more evenly dispersed throughout society. Yet, in general, the knowledge produced by the academy has had little positive impact on the quality of life of those on whom research is conducted. This article argues for the need to adopt more inclusive and participatory paradigms and methodologies that challenge entrenched views that research is the prerogative of the academy. In particular, the author proposes that an action research paradigm may offer suitable ways to navigate new educational pathways suited for improving and sustaining social life in the 21st century. Such an approach will help to ensure that academic research remains relevant in today's complex and fast-changing world.

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What is Action Research - PowerPoint PPT Presentation

What is Action Research

Action research is reflection and inquiry conducted by educators who want to ... action research is an effective way for teachers to learn because teachers ... – powerpoint ppt presentation.

• What is Action Research ?
• Action Research is reflection and inquiry conducted by educators who want to improve what they do and how they do it, and aims to make research methods useful on a daily basis in the classroom and the school.
• Participants examine their own practice, systematically and carefully, using the techniques of research. Action research is an effective way for teachers to learn because teachers explore topics related to their work and in which they already have an interest.
• Using the techniques of research, teachers draft questions, collect data, analyze data, and act on what they learn. Unlike traditional forms of research, action research is more responsive to the discoveries that researchers make along the way. That means action researchers must be flexible and willing to follow their questions wherever the information takes them
• What are the benefits of AR?
• It is a professional tool for investigating practical mathematical issues
• It promotes reflective practices in TL
• It can be a basis for further academic investigation
• Strategic Intent
• To promote Action Research in East Zone schools
• To enhance the capacity of teachers
• To drive Innovation and Creativity in
• Teaching and Learning
• Strategic Outcomes
• To have at least 1 AR training programme for teachers
• b) To have 4 AR projects to be completed by Oct 05
• COE for Schools Philosophy
• your full participation is important !
• we cannot succeed unless you succeed
• How do you benefit ?
• part of your teachers professional development (competency cluster in EPMS)
• support your departmental work in promoting IE
• you may use the AR project to address specific issues in Mathematics Teaching and Learning
• it is supported by COE () !
• What is the plan?
• Conduct AR Needs Assessment for schools (Feb 05)
• Determine the level of learning needed (Feb 05)
• Work on the time frame for learning
• (Mar May 05)
• d) Completion of AR projects (Oct 05)
• e) Do a review of action taken (Nov 05)
• What do I need to do?
• Complete the Needs Assessment Survey
• Check your department workplan to see how AR can supplement or be aligned to what you are doing
• Talk to your teachers
• TOGETHER WE CAN SUCCEED !

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What is action research?

Oct 22, 2014

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What is action research?. Action research is part of a broad movement that has been going on in education. It is related to the ideas of “reflective practice” where the teacher become researcher. ( Anne Burns, 2010).

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Presentation Transcript

What is action research? Action research is part of a broad movement that has been going on in education. It is related to the ideas of “reflective practice” where the teacher become researcher. ( Anne Burns, 2010). AR make teachers take into a consideration how well are they doing, what problems they have in class, how they can solve those problems. http://www.youtube.com/watch?v=ZHiZdh85R3w

Planning • Research Process In this part you as a teacher identify a problem, and you have some questions, doubts. And you want to find possible answers for them At this step you need to make some research, look for the materials you will need Clarify your ideas and focus in the area you need to work on it.

Acting • Research Process Involvesinteractions into your teaching situation. Put into action the plan Trialing, collecting, questioning

Observing • Research Process This phase involves teachers in observing, Analyze, report, share.

Reflecting • Research Process Evaluate, implement, revise Sharing and communicate the results Reflect on the process.

Real Action Research Projects • Action Research Project on Problem-Based Learning in Math. • http://centerx.gseis.ucla.edu/principal-leadership/fw-examples/meise/project-webpages/project-6-action-research-project-problem-based-learning-in-math • Effect of Technology on Enthusiasm for learning science. • http://www.sagepub.com/mertler3study/resources/reports/88896_sr1.pdf • Action Research in Language Teaching. • http://www2.uah.es/master_tefl_alcala/pdf/arp_article.pdf

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This paper is in the following e-collection/theme issue:

Published on 12.8.2024 in Vol 26 (2024)

Enhancing Patient Understanding of Laboratory Test Results: Systematic Review of Presentation Formats and Their Impact on Perception, Decision, Action, and Memory

Authors of this article:

• Frederieke A M van der Mee 1 * , MD   ; 
• Fleur Schaper 2, 3 * , PhD   ; 
• Jesse Jansen 1 , PhD   ; 
• Judith A P Bons 3 , PhD   ; 
• Steven J R Meex 3 , PhD   ; 
• Jochen W L Cals 1 , MD, Prof Dr  

1 Department of Family Medicine, Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands

2 Department of Clinical Chemistry, Reinier Medical Diagnostic Center, Delft, Netherlands

3 Central Diagnostic Laboratory, Maastricht University Medical Center+, Maastricht, Netherlands

*these authors contributed equally

Corresponding Author:

Frederieke A M van der Mee, MD

Department of Family Medicine

Care and Public Health Research Institute

Maastricht University

P. Debyeplein 1

Maastricht, 6229 HA

Netherlands

Phone: 31 883887059

Email: [email protected]

Background: Direct access of patients to their web-based patient portal, including laboratory test results, has become increasingly common. Numeric laboratory results can be challenging to interpret for patients, which may lead to anxiety, confusion, and unnecessary doctor consultations. Laboratory results can be presented in different formats, but there is limited evidence regarding how these presentation formats impact patients’ processing of the information.

Objective: This study aims to synthesize the evidence on effective formats for presenting numeric laboratory test results with a focus on outcomes related to patients’ information processing, including affective perception, perceived magnitude, cognitive perception, perception of communication, decision, action, and memory.

Methods: The search was conducted in 3 databases (PubMed, Web of Science, and Embase) from inception until May 31, 2023. We included quantitative, qualitative, and mixed methods articles describing or comparing formats for presenting diagnostic laboratory test results to patients. Two reviewers independently extracted and synthesized the characteristics of the articles and presentation formats used. The quality of the included articles was assessed by 2 independent reviewers using the Mixed Methods Appraisal Tool.

Results: A total of 18 studies were included, which were heterogeneous in terms of study design and primary outcomes used. The quality of the articles ranged from poor to excellent. Most studies (n=16, 89%) used mock test results. The most frequently used presentation formats were numerical values with reference ranges (n=12), horizontal line bars with colored blocks (n=12), or a combination of horizontal line bars with numerical values (n=8). All studies examined perception as an outcome, while action and memory were studied in 1 and 3 articles, respectively. In general, participants’ satisfaction and usability were the highest when test results were presented using horizontal line bars with colored blocks. Adding reference ranges or personalized information (eg, goal ranges) further increased participants’ perception. Additionally, horizontal line bars significantly decreased participants’ tendency to search for information or to contact their physician, compared with numerical values with reference ranges.

Conclusions: In this review, we synthesized available evidence on effective presentation formats for laboratory test results. The use of horizontal line bars with reference ranges or personalized goal ranges increased participants’ cognitive perception and perception of communication while decreasing participants’ tendency to contact their physicians. Action and memory were less frequently studied, so no conclusion could be drawn about a single preferred format regarding these outcomes. Therefore, the use of horizontal line bars with reference ranges or personalized goal ranges is recommended to enhance patients’ information processing of laboratory test results. Further research should focus on real-life settings and diverse presentation formats in combination with outcomes related to patients’ information processing.

Introduction

An increasing number of patients have direct access to their own web-based patient portal. This includes diagnostic test results ordered by their health care professional, such as laboratory test results [ 1 , 2 ]. Providing patients with web-based access to patient portals aims to enhance patient involvement in their health management. Improving patients’ knowledge and self-efficacy may enhance disease self-management and interactions with health care providers, and ultimately lead to better health outcomes and increased satisfaction with care [ 3 - 6 ].

However, patient access to web-based patient portals also has potentially negative consequences. For example, misinterpretation or inaccurate knowledge could lead to underestimation of test results and promote a false sense of security [ 7 ]. Similarly, gaining insight into medical test results might trigger feelings of insecurity, anxiety, and confusion [ 8 - 12 ]. Previous studies have shown that poor understanding of test results can lead to an increase in telephone calls or doctor consultations, emergency department visits, and even hospitalizations [ 13 - 15 ]. As a result, the overall utility or benefit of providing lab results directly to patients may depend on how these data are presented to and interpreted by the patient [ 16 , 17 ].

Limited health literacy and numeracy skills are significant barriers to the effective use of web-based patient portals and understanding of laboratory test results [ 18 , 19 ]. Although patient understanding can be improved to some extent by avoiding medical jargon and using plain language, overcoming the problem of incomprehension in its entirety remains an ongoing challenge [ 19 - 21 ]. One of the key issues is the numerical presentation of test results, especially for patients with low numeracy skills (ie, those with limited ability to derive meaning from numbers), who have been shown to have difficulties in interpreting basic laboratory test results and identifying results that fall outside the reference range [ 18 ]. The lack of supporting information and guidance on interpretation of results contributes to the problem of misinterpretation. This challenge becomes even more pronounced when a larger number of test results are presented [ 18 ].

Basic patient portals typically present laboratory test results in a numerical format, often accompanied by a reference range (ie, the range that represents normal values for a particular test) [ 10 , 22 , 23 ]. An alternative approach to communicating test results is the use of visual displays, such as colors or graphics. These formats require less health literacy and numeracy skills for interpretation and may improve patients’ understanding of the results [ 24 - 28 ]. Previous studies have examined a variety of presentation formats for communicating laboratory test results. However, direct comparisons between these studies can be challenging due to the variety of presentation options and clinical contexts. In addition, not all formats may be appropriate for every clinical situation [ 29 ].

There is only limited evidence on the effect of specific presentation formats on patients’ information processing. As highlighted by Witteman and Zikmund-Fisher [ 17 ], laboratory test results often lack meaning for the patients receiving them. Test results represent data, which differs from information and actual knowledge patients commonly encounter in daily life [ 30 , 31 ]. Patients have to complete several steps to go from data perception to usable knowledge. Ancker et al [ 32 ] described these steps as well, based on the Wickens model of human information processing [ 33 ]. In a sequential order, patients need perception and behavioral intention to achieve actual health behavior. Therefore, it is important that these separate steps of information processing are taken into account when presentation formats are evaluated.

Our systematic review aims to synthesize the existing evidence on effective components of presentation formats for laboratory test results focusing on patients’ perception, decision, action, and memory. In this review, we will specifically focus on numeric laboratory test results, and not on results containing only textual or nonnumeric findings.

This review was reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; Multimedia Appendix 1 ) [ 34 ]. A protocol for this review was not previously registered.

Search Strategy

The search was conducted in 3 databases (PubMed, Web of Science, and Embase) from inception up to May 31, 2023. In each database, a search was performed, which was developed by the first author (FM) together with an experienced librarian and contained both thesaurus and free text terms. For the search in Embase, a filter was applied to remove preprint records and to exclude MEDLINE citations, since the latter were already covered by the PubMed search. Additionally, 2 authors (FM and FS) performed backward snowballing by screening reference sections of all selected articles to identify relevant publications missed with the search strategy. A fully reproducible search can be found in Multimedia Appendix 2 .

Study Selection and Eligibility Criteria

All identified titles and abstracts were downloaded to reference management software (Endnote) and duplicates were removed. Two authors (FM and FS) independently screened for potential eligible articles using Covidence, a Cochrane’s technology platform [ 35 ]. First, titles and abstracts were screened against the eligibility criteria. Second, full texts of potentially suitable articles were rescreened using the same criteria. In case of disagreement, consensus was reached by discussion or screening by a third reviewer (JC).

We considered articles fitting for inclusion if they were original research. Studies describing or comparing different ways of presenting diagnostic laboratory test results to patients were included. Only studies examining numeric laboratory test results were included. Furthermore, studies are needed to evaluate the effect of communicating test results on patients’ comprehensibility, attitudes, or experiences. Studies conducted in primary care and secondary/tertiary care settings were eligible, as well as studies including healthy volunteers. Studies had to be written in English or Dutch.

Studies were excluded if they (1) were protocols, reviews, systematic reviews, meta-analyses, book chapters, editorials, letters, practice pointers, oral presentations, or poster presentations; (2) were about development, implementation, or adoption of web-based patient portals in general, or about the type of notification of laboratory test results, if they did not consider patients’ interpretation of the lab results; (3) focused on web-based access to notes, and not to laboratory test results; (4) did not mention type of presentation format of lab results; (5) focused on the development of web-based lifestyle interventions or web-based applications to collect patient-reported outcomes; (6) focused on the safety or privacy issues of web-based patient portals; (7) were about the effect of communicating test results in web-based patient portals on patients’ medication management; (8) tested the effect of test result communication on health care providers; (9) examined communication of other types of diagnostic test results (eg, pharmacogenomics or genomics, radiology, pathology, or microbiology); and (10) examined communication of test results in the context of screening programs.

Data Extraction

Two authors (FM and FS) independently extracted data from the eligible studies into a prepared spreadsheet. The spreadsheet was developed by the multidisciplinary team and piloted by both authors. For each study, the year of publication, country in which the study was performed, study design, number of participants, description of the study population, and the inclusion and exclusion criteria were assessed. Furthermore, information about the presentation of test results in the portal, the type of laboratory tests studied, and whether real or mock data were used, was extracted.

Outcome Measures

Previous research regarding this subject focused on a variety of outcomes related to patients’ information processing. As stated above, Ancker et al [ 32 ] introduced a taxonomy to categorize different outcome measures when communicating numbers in health care. These categories include sequentially; perception, decision/behavioral intention, action/actual health behavior, and memory. Perception is further divided into 4 subcategories: affective perception, perceived magnitude, cognitive perception, and perception of communication [ 32 , 36 , 37 ]. An explanation of the categorized outcome measures can be found in Textbox 1 [ 32 ]. For this review, the outcome measures of each study were extracted and classified into the categories described.

Affective perception

• Feelings about the laboratory result communicated.

Perceived magnitude

• Perceived size of risk associated with a test result, captured with measures as “how large or small does this value seem to you?”

Cognitive perception

• Understanding whether a laboratory result is elevated, normal, or below normal. Being able to identify direction of a trend over time.

Perception of communication

• Preference for presentation format of test result.
• Intention to seek more information or to change behavior after viewing results.
• Change in actual health behavior (eg, search for more information).
• Recall of a specific test result after viewing (ie, verbatim recall).

Quality Assessment

To assess the quality and risk of bias of all included studies, the Mixed Methods Appraisal Tool (MMAT) was used [ 38 ]. The MMAT is designed to concomitantly appraise studies with different designs, such as qualitative, quantitative, and mixed methods studies [ 39 ]. Question sets are specific to the study design, notably qualitative studies, quantitative randomized controlled trials, quantitative nonrandomized studies, quantitative descriptive studies, and mixed methods studies. For each suitable study, the appropriate category was chosen and the criteria stated for this specific category were rated as “yes,” “no,” or “can’t tell.”

Two authors (FM and FS) discussed both data and quality extraction until a consensus was reached.

Data Synthesis

Due to the heterogeneity of study designs and primary outcomes, meta-analysis was considered inappropriate. Instead, narrative synthesis was used to integrate the findings into descriptive summaries regarding ways of presenting laboratory test results and outcomes of interest.

The initial search identified 10,537 references. A total of 3490 duplicate records were removed. After applying the exclusion criteria in the primary title and abstract screening, another 6900 records were removed. During full-text screening of the remaining articles (n=146), it appeared that 1 full text was not available. Furthermore, 127 articles were excluded because they did not meet the eligibility criteria. Describing the implementation of web-based patient portals, unrelated to laboratory test results, was the most common exclusion criterion (55/127, 43.3%; Figure 1 ). A total of 18 studies were found eligible for this systematic review. Cohen κ for interrater reliability was 0.62 for title and abstract screening and 0.80 for full-text screening, indicating respectively a moderate and strong agreement between the 2 reviewers [ 40 ].

Study Characteristics

A total of 2 qualitative studies, 11 quantitative studies, and 5 mixed methods studies were included (n=18). The included studies were published between 2012 and 2021, and the majority were conducted in the United States (n=13, 72%). The total sample size of the included studies was 12,225 participants, ranging from 8 to 6766 participants. Among the articles reporting the following characteristics, sex was almost equally distributed (6219/13,155, 47.3% female), and participants were predominantly middle-aged (mean 51.1 years) and White (8429/10,865, 77.6% on average). Fourteen (78%) of the 18 studies reported educational level, with 48% (5676/11,813) of the participants reporting a higher education (defined as college-degree or higher). Overall characteristics of the included studies and populations are summarized in Table 1 .

a Low education: primary school. Middle education: secondary, high, or trade school or some college. High education: 4-year, college, associate, university, undergraduate, bachelor’s, master’s, advanced, professional, or doctorate degree.

b Not available.

c The following articles are pilot and main studies: Morrow et al (2017) [ 46 ] and (2019) [ 47 ], as well as Zhang et al (2020) [ 15 ] and (2021) [ 53 ].

d The following articles originate from the same parent study: Zikmund-Fisher et al (2017) [ 22 ] and (2018) [ 54 ].

The most frequently used laboratory tests were lipid profile (n=10) and hemoglobin A 1c (HbA 1c ) or glucose (n=5). In total, 4 studies used real patients as study population, other studies used healthy volunteers, a convenience sample, or a mixed sample (n=12) or did not define their study population (n=3). Studies used mock test results (ie, hypothetical results; n=16), real results (n=1, with real patients), or both (n=1). The majority of studies used numerical values with reference ranges (n=12) or horizontal line bars with colored blocks (n=12; Table 2 ). A more detailed overview of the different ways of presenting test results is provided in Multimedia Appendix 3 [ 7 , 15 , 22 , 23 , 41 - 54 ]. An explanation of the different presentation formats can be found in Figure 2 .

a HDL: high-density lipoprotein.

b LDL: low-density lipoprotein.

c eGFR: estimated glomerular filtration rate.

d TG: triglycerides.

e HbA 1c : hemoglobin A1c.

f TSH: thyroid stimulating hormone.

g ALT: alanine aminotransferase.

The quality assessment tool (MMAT) includes 5 assessment criteria per study design, each of which is given a score of 20% if present ( Multimedia Appendix 4 [ 7 , 15 , 22 , 23 , 41 - 54 ]). Both qualitative articles (n=2) scored 100%, indicating excellent quality. Quantitative articles (n=11) scored between 0% and 100%, indicating a broad range of quality. These articles lost points mainly for sampling issues (biased sampling strategies and unrepresentative samples), randomization issues (unclear randomization process and incomparable groups at baseline), unclear blinding process, and lack of clarity about the completeness of outcome data and nonresponse bias. Mixed methods articles (n=5) scored between 60% and 100% (low-to-high quality), for the same reasons as described above. In addition, weaknesses in these articles included having an unclear rationale for using a mixed methods design, unclear presentation format, and failure to adequately interpret the results of the integration of qualitative and quantitative findings.

In all 18 studies, perception was an outcome measure, further categorized into affective perception (n=7), perceived magnitude (n=6), cognitive perception (n=10), and perception of communication (n=14; Table 3 and Textbox 1 ). Additionally, 10 studies assessed behavioral intention, while memory was considered as an outcome measure in 3 of the included studies.

Affective Perception

Several studies explored participants’ confidence and concerns while viewing and interpreting laboratory results [ 15 , 44 , 47 , 49 , 51 ]. Talboom-Kamp et al [ 51 ] demonstrated that presenting laboratory test results in horizontal line bar format with colored blocks and evaluative labels (ie, textual explanation) enhanced participants confidence in managing their own health, although this effect was not significant. No comparison between different presentation formats and the influence on confidence was described. These comparisons were also lacking in the other studies.

When results were presented in a horizontal line bar format with colored blocks and a personalized goal range, the negative affect was significantly higher than when results were presented without colored blocks [ 49 ].

Scherer et al [ 49 ] studied the use of personalized reference values or goal ranges. A type 2 diabetes mellitus scenario was studied, in which standard reference ranges are often not applicable. Replacing standard ranges with goal ranges significantly reduced perceived discouragement compared with situations without goal display, highlighting a positive effect of goal ranges on affective perception [ 49 ]. Furthermore, 2 other studies recommended the use of personalized reference ranges in their discussion [ 44 , 51 ].

In 3 studies, whether laboratory test results were within reference ranges seemed to be more important than the presentation format. As results moved further from the reference range, positive emotions decreased and negative emotions increased [ 15 , 46 , 47 ]. This change in affective perception was not influenced by message format.

Perceived Magnitude

The perceived magnitude of risk of extremely out-of-range results remained unaffected by the presentation formats in all studies. However, for near-normal or slightly out-of-range results participants encountered difficulties in estimating test result severity. Accurate risk perception was lacking, since the severity of these results was inconsistently overestimated or underestimated [ 7 , 22 , 41 , 47 , 54 ]. Zikmund-Fisher et al [ 54 ] demonstrated that the incorporation of harm anchors (ie, a threshold line outside the reference range labeled “many doctors are not concerned until here”) significantly enhanced adequate estimations of test result severity for slightly out-of-range results.

Three studies investigated the effect of presentation format on the perceived size of risk [ 22 , 23 , 47 ]. Morrow et al [ 47 ] compared horizontal line bars with both numerical and video-enhanced formats. For both low- and borderline-risk scenarios, the perceived magnitude of risk was significantly higher when horizontal line bars were used, indicating that participants tend to overestimate risk for normal results [ 47 ]. Tao et al [ 23 ] did not specify whether result normality affected risk perception using different types of horizontal line bars. However, when personalized information was added to the line bar, the risk was perceived as significantly higher. Interestingly, despite this, participants expressed a preference for personalized line bars [ 23 ]. Zikmund-Fisher et al [ 22 ] compared different types of horizontal line bars with a numerical format. Participants expressed the highest risk perception when near-normal results were presented in a numerical format with a reference range, whereas the perceived risk was lowest when horizontal line bars with gradient colors were used [ 22 ].

Cognitive Perception

In all 10 studies assessing this outcome, participants consistently demonstrated the ability to understand or identify out-of-range results. There was consensus among these studies that presenting numbers with a reference range only was insufficient and that tailored information was needed [ 45 , 52 , 53 ]. A qualitative study revealed that participants preferred the inclusion of evaluative labels [ 43 ]. In 2 studies using horizontal line bars as the presentation format, the understanding was significantly increased when color, text, or personalized information (eg, goal range) was added [ 23 , 49 ].

Perception of Communication

The majority of included studies observed a significant association between presentation format, participant satisfaction, and ease of use. In general, satisfaction and ease of use were rated higher when test results were presented using horizontal line bars with colored blocks, as compared with other presentation formats [ 22 , 23 , 42 , 43 , 47 , 51 , 53 ]. In one qualitative study, numerical presentation with reference ranges was deemed insufficient, while graphs were considered too complex for easy comprehension [ 43 ]. Both quantitative and qualitative studies demonstrated that adding evaluative labels, such as explanations about the meaning and normality of test results, and background information about testing, enhanced understanding and effective use of results. Particularly, the use of lay terms played an important role [ 15 , 23 , 44 , 45 , 48 , 51 - 53 ]. Furthermore, 2 studies found a significant positive effect on participant satisfaction when personalized information or goal ranges were incorporated [ 23 , 51 ]. This addition was also recommended by 2 qualitative studies [ 43 , 53 ]. Zikmund-Fisher et al [ 54 ] specifically studied different types of horizontal line bars and showed no significant differences in participants’ preferences among the studied formats.

The behavioral intention was assessed in 10 studies, with varying focuses among them. Some authors examined whether participants would contact their physician [ 7 , 22 , 48 , 49 , 54 ], while others inquired about participants seeking additional web-based information [ 41 , 45 , 48 ], or making lifestyle changes after reviewing lab results [ 47 , 48 , 51 ].

Two studies demonstrated that the presentation format did not significantly influence participants’ need to contact their health care provider [ 7 , 49 ]. Conversely, Zikmund-Fisher et al [ 22 , 54 ] demonstrated in 2 studies that participants who viewed near-normal results in a numerical format were significantly more likely to contact their doctor compared with those viewing the same results in one of the horizontal line formats. The use of harm anchors in horizontal line bars substantially reduced the number of participants who would want to contact their physician [ 22 , 54 ].

Participants’ tendency to seek web-based information was significantly influenced by the presentation format, with a significantly higher inclination observed for the numerical format compared with the textual format [ 41 ]. Kelman et al [ 45 ] and Nystrom et al [ 48 ] similarly found that approximately half of the participants would look for additional information after receiving test results in numerical format with reference ranges and evaluative labels, or horizontal line bars with colored blocks, respectively. However, no comparison was made between presentation formats in these studies [ 45 , 48 ].

Intention to make lifestyle changes after viewing laboratory results was mentioned as an outcome in 3 studies [ 47 , 48 , 51 ]. Only one of these studies compared several presentation formats but found no significant differences between using a numerical format, horizontal line bars with colored blocks, or video-enhanced format in terms of health-beneficial intentions [ 47 ].

There was limited data concerning the actions patients take to comprehend their test results. One mixed methods study used a numerical format with reference ranges as a presentation format [ 15 ]. Participants with abnormal test results were significantly more likely to take action compared with those with normal test results. As no comparison between presentation formats was investigated, the effect of format on action remains unstudied.

Variation in the presentation format of test results, using either a numerical format with reference ranges and evaluative labels, horizontal line bars with colored blocks, video presentation, or grouped presentation, did not significantly impact participant recall [ 7 , 42 , 47 ]. However, one study found a small but statistically significant effect of test result normality on memory [ 47 ].

Struikman et al [ 50 ] looked at patient health engagement (PHE), a composite measure comprising affective perception, cognitive perception, and behavioral intention. When test results were presented with explanatory text and visualization, PHE was significantly higher compared with when no explanatory information was provided [ 50 ].

Principal Findings

Based on reviewing 18 articles assessing various presentation formats of laboratory test results, we can conclude there is not only one optimal presentation format in terms of patients’ perception, decision, action, and memory. Nevertheless, the results do indicate that presentation format is important for patients’ information processing.

Presentation formats differed between articles, but numerical values with reference ranges or horizontal line bars with colored blocks were most commonly used. All included studies investigated perception as an outcome measure, most frequently perception of communication (n=14). Patients’ cognitive perception and perception of communication improved when results were presented using horizontal line bars accompanied with colored blocks and evaluative labels or textual information. Incorporation of reference ranges or personalized goal ranges further enhanced patients’ perception levels. Using horizontal line bars with harm anchors significantly reduced the number of participants who would want to contact their physician compared with using a numerical format. Furthermore, using the numerical format significantly increased participants’ tendency to search for web-based information, compared with a textual format. Therefore, although no specific format is dissuaded in the included studies, the results suggest that presenting only numbers with reference ranges is suboptimal. Furthermore, adding too many colors and other information to test results could lead to an overload of visual information for some patients, and therefore ultimately decrease the amount of usable knowledge [ 49 ]. Action and memory were less frequently studied, respectively in 1 and 3 studies. Action was studied in a descriptive study not comparing different presentation formats, while memory was not significantly impacted by presentation format.

Several studies highlighted that patients’ affective perception, action, and memory were not only influenced by presentation format, but also by whether test results were within or outside the reference range. Presentation format appeared to be secondary to test result normality if results were extremely out-of-range. Nevertheless, when results were near-normal, presentation format was more important than result normality regarding effects on patients’ information processing.

Overall, the results of this review indicate that presentation format affects patients’ information processing, especially in the case of normal or near-normal test results.

Strengths and Limitations

A multidisciplinary team of general practitioners, behavioral scientists, and clinical chemists was involved in this review, which is one of its strengths. Both presentation formats and outcomes used in the included studies were standardized by the authors using a published taxonomy to enable comparison of different studies. As the results of our review are narrative, there is a potential risk of bias when describing them, introduced by the authors. Furthermore, selection bias arising from the heterogeneity of studies represents a notable limitation of this review.

A limitation of the included studies is the use of volunteers or participants recruited via convenience sampling. Only 3 out of 18 studies used real patients, of which one study used real test results. Sixteen studies used mock test results. Displaying mock data is common practice in system evaluation. This method involves less burden and privacy risks for participants, as no personal medical data are collected. Nonetheless, participants lack personal relevance of test results when hypothetical scenarios are used. Therefore, it is possible that most of the included studies did not reflect how participants would respond in real life to their own personal health information. This may limit the generalizability of the findings. However, using personal test results could have negatively affected the comparability between studies, as each participant would have encountered different data.

Among the articles reporting educational level, 48% (5676/11,813) of the participants reported a higher education level, which is higher than in the general population. This may limit the generalizability of the findings to the overall population. Another limitation is the study heterogeneity. Included articles varied widely in methods, presentation formats, and outcome measures used. Comparison of presentation formats is challenging, especially since laboratory test result communication can have a wide range of possible purposes, from interpreting one single value to identifying important trends on time [ 24 ]. Therefore, useful presentation formats may vary per clinical scenario, which presents new challenges for designing a preferred format.

As stated above, patients have to complete several steps to go from data perception to usable knowledge [ 17 , 32 ]. The majority of the included studies studied the first 2 steps of this taxonomy, perception and decision. Only one study examined action as outcome measure, and 3 studies obtained information about memory. Therefore, little is known about the impact of presentation formats on actual health behavior and usable knowledge.

Comparison With Prior Work

An increasing number of patients can directly access their laboratory test results via web; thus, it is becoming more important to make the available data meaningful to laypeople [ 55 ]. As highlighted in this review, presentation format affects patients’ information processing as described above. In cognitive science, this principle is generally known as information evaluability, in other words using relevant contextual reference information to make it easier to evaluate the meaning of in this case numerical laboratory test results (eg, is this test result good or bad, is it normal or abnormal) [ 56 , 57 ]. The presentation formats for laboratory test results as studied in this review could be considered as different forms of contextual information, or evaluative categories [ 58 ]. Prior research has shown that these evaluative categories add both affective and cognitive meaning to numeric test results. This enhances patients’ information processing by adding meaning and evaluability to numeric information [ 58 - 60 ]. Furthermore, our findings are in line with recommendations made by Witteman and Zikmund-Fisher [ 17 ]. The authors formulated 10 recommendations to communicate laboratory test results via web-based portals in ways that support understanding and actionable knowledge for patients. Our findings align with several of their recommendations, such as the importance of providing a clear takeaway message for each result, establishing thresholds for concern and action whenever feasible, and personalizing the frame of reference by permitting custom reference ranges.

This review explored different strategies to improve patients’ interpretation and comprehension of their laboratory test results. The included studies predominantly focused on the effect of graphical presentation only including a subset of the available visualization options. Other formats such as clocks or pie charts been shown in the broader numeracy literature to improve cognitive outcomes and could be the focus of further research in the context of communicating laboratory test results [ 61 ]. Graphical presentation formats might mitigate the effects of low numeracy. However, it is important to acknowledge that graphical information may not be automatically useful for individuals with limited graph literacy [ 62 ]. Besides numeracy and graph literacy, other factors such as age, educational level, health literacy, and statistical literacy (eg, understanding of concepts of uncertainty and chance) also influence patients’ information processing of such graphical results [ 61 - 63 ]. If one of these factors causes patients to not completely understand a specific presentation format, they may consider this format as not suitable. Therefore, some patients may require extra instructions to be able to adequately process and interpret graphical presentation formats [ 61 ]. For that reason, the interaction between patients’ literacy, numeracy, age, and educational level should be taken into account when performing future work around test result interpretation.

Several initiatives aim to inform and educate patients about laboratory test results while incorporating the insights described above. One example is Lab Tests Online, a website that provides patients with general information about laboratory tests and their meaning [ 64 ]. Recently, the usability of ChatGPT (ie, an upcoming tool based on natural language processing) to interpret laboratory test results were examined [ 65 ]. ChatGPT appeared to provide somewhat superficial interpretations, which were not always correct, and is therefore not yet usable as a primary information source for patients. However, this may change in the future with the further development of these types of tools. While our review focused on different presentation formats of laboratory test results, interpretative comments provided by laboratory specialists were not studied. Laboratory specialists often add comments to test results to assist general practitioners [ 66 , 67 ]. A pilot study by Verboeket-van de Venne et al [ 68 ] demonstrated a positive impact on patient empowerment when patients had access to these patient-specific comments. Therefore, further research should explore the impact of adding interpretative comments to laboratory test results on patients’ information processing.

Patients now have web-based access to not only their laboratory test results but also to medical imaging and microbiology results. Given the variations in these types of diagnostic test results, further research is warranted to explore effective components for communicating these other types of test results to patients in their web-based patient portal.

Conclusions

As patients increasingly receive their diagnostic laboratory test results via web-based patient portals, it is becoming more and more important to make test results meaningful to them. Unnecessary confusion or anxiety should be avoided, especially when test results are outside of the reference range. The data from our systematic review suggest that horizontal line bars with colored blocks and reference ranges or personalized goal range increase patients’ cognitive perception and perception of communication. Furthermore, this format might reduce patients’ concerns and their tendency to contact their physicians. Therefore, to improve patients’ understanding of near-normal laboratory test results and prevent anxiety and concerns after viewing these results, implementing horizontal line bars with colored blocks and reference ranges or personalized goal ranges in web-based patient portals would be a prudent choice. Our review highlights the importance of taking end users (ie, patients) into consideration when designing new presentation formats. These results can guide the development and improvement of (new) web-based patient portals. Nevertheless, there is a need for further research that involves more comprehensive data collection and reporting, as well as more systematic evaluation methods. By using these findings, further research could inform the development of an interpretation support tool for laboratory test results.

Acknowledgments

This study received funding from a partnership between Care Research Netherlands and the Medical Sciences domain of the Dutch Research Council (Dutch abbreviation ZonMW; project 08391052120002). ZonMW had no direct involvement in any facet of the design of the study, analysis or interpretation of the data, or writing of the manuscript.

Authors' Contributions

All authors contributed to the conception of the review. FM and FS conducted the screening and data extraction. FM and FS drafted the manuscript. JJ, JB, SM, and JC gave guidance throughout the whole research process. All authors critically revised and approved the manuscript.

Conflicts of Interest

None declared.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 checklist.

Search strategy for PubMed, Web of Science, and Embase up to May 31, 2023.

Detailed overview of laboratory test results presentation formats in all included studies (n=18).

Detailed overview of quality assessment of all included studies (n=18).

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Abbreviations

Edited by A Mavragani; submitted 26.10.23; peer-reviewed by B Zikmund-Fisher, B Steitz; comments to author 26.02.24; revised version received 07.04.24; accepted 27.05.24; published 12.08.24.

©Frederieke A M van der Mee, Fleur Schaper, Jesse Jansen, Judith A P Bons, Steven J R Meex, Jochen W L Cals. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.08.2024.

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