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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.

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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.

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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.”

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George, T. (2024, January 12). What Is Action Research? | Definition & Examples. Scribbr. Retrieved August 19, 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 Design

• First Online: 10 November 2021

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• Michael Blankenagel 3  

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This chapter addresses the peculiarities, characteristics, and major fallacies of action research design. This research design is a change-oriented approach. Its central assumption is that complex social processes can best be studied by introducing change into these processes and observing their effects. The fundamental basis for action research is taking actions to address organizational problems and their associated unsatisfactory conditions. Also, researchers find relevant information on how to write an action research paper and learn about typical methodologies used for this research design. The chapter closes with referring to overlapping and adjacent research designs.

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Hunziker, S., Blankenagel, M. (2021). Action Research Design. In: Research Design in Business and Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34357-6_7

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Linking Research to Action: A Simple Guide to Writing an Action Research Report

What Is Action Research, and Why Do We Do It?

Action research is any research into practice undertaken by those involved in that practice, with the primary goal of encouraging continued reflection and making improvement. It can be done in any professional field, including medicine, nursing, social work, psychology, and education. Action research is particularly popular in the field of education. When it comes to teaching, practitioners may be interested in trying out different teaching methods in the classroom, but are unsure of their effectiveness. Action research provides an opportunity to explore the effectiveness of a particular teaching practice, the development of a curriculum, or your students’ learning, hence making continual improvement possible. In other words, the use of an interactive action-and-research process enables practitioners to get an idea of what they and their learners really do inside of the classroom, not merely what they think they can do. By doing this, it is hoped that both the teaching and the learning occurring in the classroom can be better tailored to fit the learners’ needs.

You may be wondering how action research differs from traditional research. The term itself already suggests that it is concerned with both “action” and “research,” as well as the association between the two. Kurt Lewin (1890-1947), a famous psychologist who coined this term, believed that there was “no action without research; no research without action” (Marrow, 1969, p.163). It is certainly possible, and perhaps commonplace, for people to try to have one without the other, but the unique combination of the two is what distinguishes action research from most other forms of enquiry. Traditional research emphasizes the review of prior research, rigorous control of the research design, and generalizable and preferably statistically significant results, all of which help examine the theoretical significance of the issue. Action research, with its emphasis on the insider’s perspective and the practical significance of a current issue, may instead allow less representative sampling, looser procedures, and the presentation of raw data and statistically insignificant results.

What Should We Include in an Action Research Report?

The components put into an action research report largely coincide with the steps used in the action research process. This process usually starts with a question or an observation about a current problem. After identifying the problem area and narrowing it down to make it more manageable for research, the development process continues as you devise an action plan to investigate your question. This will involve gathering data and evidence to support your solution. Common data collection methods include observation of individual or group behavior, taking audio or video recordings, distributing questionnaires or surveys, conducting interviews, asking for peer observations and comments, taking field notes, writing journals, and studying the work samples of your own and your target participants. You may choose to use more than one of these data collection methods. After you have selected your method and are analyzing the data you have collected, you will also reflect upon your entire process of action research. You may have a better solution to your question now, due to the increase of your available evidence. You may also think about the steps you will try next, or decide that the practice needs to be observed again with modifications. If so, the whole action research process starts all over again.

In brief, action research is more like a cyclical process, with the reflection upon your action and research findings affecting changes in your practice, which may lead to extended questions and further action. This brings us back to the essential steps of action research: identifying the problem, devising an action plan, implementing the plan, and finally, observing and reflecting upon the process. Your action research report should comprise all of these essential steps. Feldman and Weiss (n.d.) summarized them as five structural elements, which do not have to be written in a particular order. Your report should:

• Describe the context where the action research takes place. This could be, for example, the school in which you teach. Both features of the school and the population associated with it (e.g., students and parents) would be illustrated as well.
• Contain a statement of your research focus. This would explain where your research questions come from, the problem you intend to investigate, and the goals you want to achieve. You may also mention prior research studies you have read that are related to your action research study.
• Detail the method(s) used. This part includes the procedures you used to collect data, types of data in your report, and justification of your used strategies.
• Highlight the research findings. This is the part in which you observe and reflect upon your practice. By analyzing the evidence you have gathered, you will come to understand whether the initial problem has been solved or not, and what research you have yet to accomplish.
• Suggest implications. You may discuss how the findings of your research will affect your future practice, or explain any new research plans you have that have been inspired by this report’s action research.

The overall structure of your paper will actually look more or less the same as what we commonly see in traditional research papers.

What Else Do We Need to Pay Attention to?

We discussed the major differences between action research and traditional research in the beginning of this article. Due to the difference in the focus of an action research report, the language style used may not be the same as what we normally see or use in a standard research report. Although both kinds of research, both action and traditional, can be published in academic journals, action research may also be published and delivered in brief reports or on websites for a broader, non-academic audience. Instead of using the formal style of scientific research, you may find it more suitable to write in the first person and use a narrative style while documenting your details of the research process.

However, this does not forbid using an academic writing style, which undeniably enhances the credibility of a report. According to Johnson (2002), even though personal thoughts and observations are valued and recorded along the way, an action research report should not be written in a highly subjective manner. A personal, reflective writing style does not necessarily mean that descriptions are unfair or dishonest, but statements with value judgments, highly charged language, and emotional buzzwords are best avoided.

Furthermore, documenting every detail used in the process of research does not necessitate writing a lengthy report. The purpose of giving sufficient details is to let other practitioners trace your train of thought, learn from your examples, and possibly be able to duplicate your steps of research. This is why writing a clear report that does not bore or confuse your readers is essential.

Lastly, You May Ask, Why Do We Bother to Even Write an Action Research Report?

It sounds paradoxical that while practitioners tend to have a great deal of knowledge at their disposal, often they do not communicate their insights to others. Take education as an example: It is both regrettable and regressive if every teacher, no matter how professional he or she might be, only teaches in the way they were taught and fails to understand what their peer teachers know about their practice. Writing an action research report provides you with the chance to reflect upon your own practice, make substantiated claims linking research to action, and document action and ideas as they take place. The results can then be kept, both for the sake of your own future reference, and to also make the most of your insights through the act of sharing with your professional peers.

Feldman, A., & Weiss, T. (n.d.). Suggestions for writing the action research report . Retrieved from http://people.umass.edu/~afeldman/ARreadingmaterials/WritingARReport.html

Johnson, A. P. (2002). A short guide to action research . Boston, MA: Allyn & Bacon.

Marrow, A. J. (1969). The practical theorist: The life and work of Kurt Lewin . New York, NY: Basic Books.

Tiffany Ip is a lecturer at Hong Kong Baptist University. She gained a PhD in neurolinguistics after completing her Bachelor’s degree in psychology and linguistics. She strives to utilize her knowledge to translate brain research findings into practical classroom instruction.

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Best Practices and Lessons Learned for Action Research in eHealth Design and Implementation: Literature Review

Kira oberschmidt.

1 eHealth Cluster, Roessingh Research and Development, Enschede, Netherlands

2 Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands

Christiane Grünloh

Femke nijboer, lex van velsen, associated data.

Full overview of all categories and description of settings for each category.

Full list of categories per setting variable.

Action research (AR) is an established research framework to introduce change in a community following a cyclical approach and involving stakeholders as coresearchers in the process. In recent years, it has also been used for eHealth development. However, little is known about the best practices and lessons learned from using AR for eHealth development.

This literature review aims to provide more knowledge on the best practices and lessons learned from eHealth AR studies. Additionally, an overview of the context in which AR eHealth studies take place is given.

A semisystematic review of 44 papers reporting on 40 different AR projects was conducted to identify the best practices and lessons learned in the research studies while accounting for the particular contextual setting and used AR approach.

Recommendations include paying attention to the training of stakeholders’ academic skills, as well as the various roles and tasks of action researchers. The studies also highlight the need for constant reflection and accessible dissemination suiting the target group.

Conclusions

This literature review identified room for improvements regarding communicating and specifying the particular AR definition and applied approach.

Introduction

The way health care is organized and executed is of great societal concern, as it affects our quality of life. Hence, health care systems and eHealth technologies used to support health care should be designed in a way that meets the needs and expectations of their stakeholders. One way of doing this is through action research (AR). According to Bradbury and Lifvergren [ 1 ], AR in health care “seeks to (1) improve patient experiences and the health of populations, (2) reduce the per capita cost, (3) improve the work life of those who deliver care, and (4) bring health care providers into circumstances that allow for continuous learning together with patients.” AR has been used as a research framework in nursing and health care, for example, to improve the quality of patient care and investigate changes in action [ 2 ]. AR is a collaborative approach, where people affected by the change envisioned in AR become active members of the research team. AR is often used in the design of eHealth systems. However, existing literature reviews of AR in eHealth predominantly focus on the development of new frameworks [ 3 - 5 ] but not on how eHealth AR is currently carried out. Therefore, this literature review outlines the state of the art of AR in eHealth design.

eHealth projects cover a wide variety of topics and technologies and can therefore greatly benefit patients, professionals, and many other health care stakeholders. However, to gain the most from eHealth systems and technologies, it is crucial that they match with what is needed in practice [ 6 ]. To ensure such a match, Van Gemert-Pijnen and colleagues [ 6 ] suggest, among other things, working together with relevant stakeholders in all stages of the project, implementing the study results in practice, and continuously evaluating the process. Similarly, co-design has been mentioned as a useful technique for creating eHealth systems that suit the needs of the end users [ 3 ]. These ideas fit well with the principles of AR, which will be outlined below.

Definitions of AR have changed over the years. AR originated with Kurt Lewin [ 7 ], who described it as several consecutive circles of planning, action, and reflection. These cycles are shown in Figure 1 , developed by Williamson and colleagues [ 2 ]. In later definitions, the cyclical nature of AR remains one of its key features. Reason and Bradbury [ 8 ], who build on Lewin’s work, define AR as research that (1) involves stakeholders not only as participants but also as members of the research team, (2) consists of (at least) 1 cycle of planning, action, and reflection, (3) establishes direct changes, and (4) then evaluates those changes in and with the community. Their work [ 8 ] includes many interesting examples of AR from various fields. Furthermore, Bradbury and colleagues defined 7 “choice points for quality in action research” [ 9 ], criteria that can be used to plan, conduct, report, and assess AR projects .

Action research cycles (adapted from Kurt Lewin [ 7 ] by Williamson and colleagues [ 2 ]).

Within AR, different variations exist, such as action design research (ADR) or participatory action research (PAR). Usually, there is agreement on the main principles of AR explained earlier, but some authors or groups emphasize some aspects over others. For example, as the name suggests, ADR incorporates elements of design research into AR [ 10 ], whereas PAR highlights the involvement of the community [ 11 ]. For a more detailed overview of the similarities and differences between some of these approaches, see Williamson et al [ 2 ] or Coghlan and Brannick [ 11 ].

In general, AR and AR approaches such as ADR are similar to participatory design (PD) approaches that are used in human computer interaction (HCI) research. However, AR emphasizes reflection on and learning from the process that was carried out, whereas the main aim of PD is to create a solution [ 12 ]. AR, as opposed to PD, does not start with a clear goal of what needs to be developed but defines this throughout the process together with stakeholders. Additionally, AR is more immersive and calls for stakeholder involvement for a longer period of time due to its iterative cycles [ 13 ]. Nevertheless, in some cases, studies that are described as PD-related ones also meet Reason and Bradbury’s criteria [ 8 ] for AR [ 14 ]. Hayes [ 12 ] argues that AR and HCI research can supplement each other, as both often provide solutions on a local scale. As Hughes [ 15 ] describes, there is no standard way of implementing AR in health care due to the broadness of the field. Instead, there is a variety regarding the why, how, and with whom AR in health care is carried out [ 15 , 16 ]. For example, levels of stakeholder engagement and the context in which AR takes place can vary [ 16 ]. Other differences among AR studies include the topic, country, project duration, main target group, and methods used. Therefore, these aspects are considered in this review. The purpose of this review is to give an overview of the current literature on eHealth AR and summarize the best practices and points of improvement for future eHealth AR projects. Special attention is paid to the contextual variables of the research (eg, setting, duration, number of stakeholders), as this is expected to influence the outcomes, best practices, and points of improvement of a study. To provide an overview of AR in eHealth, this literature review addresses the following subquestions:

• What is the context of AR eHealth projects?
• How do eHealth AR studies define and operationalize AR?
• What are the best practices for conducting AR in concrete eHealth studies?
• What are the lessons learned from conducting AR in concrete eHealth studies?

Study Selection and Screening

The search was carried out in June 2020. PubMed, Scopus, and Google Scholar were searched using combinations of the search terms “action research” or “participatory design” and “eHealth,” “health technology,” “digital health,” or “telemedicine.” PubMed was chosen for its extensive medical database, and Scopus and Google Scholar were chosen as large scientific databases. Searching for “action research” turns up articles that include similar and related keywords like “participatory action research,” “action design research,” or “action-based research.” “Participatory design” was included as a search term because PD has significant overlap with AR, and both are sometimes used to supplement each other. The list of synonyms for “eHealth,” although not exhaustive, is expected to cover the various facets of the field. The initial search yielded 739 results. Articles were included if they (1) used and explicitly mentioned AR and (2) were about eHealth or health technology. Papers were excluded if they (1) were not written in English, (2) only included a study protocol but did not report results, or (3) only included a review of other articles. Full-text screening of the same 15 articles was performed by 2 authors (KO and CG); the authors discussed whether to include the studies until an agreement was reached. Next, the first author screened the full texts of the remaining articles, with some exceptions where a second opinion was necessary. These were again discussed between the first and second authors until an agreement was reached. Ultimately, 44 articles were included, reporting on 40 different projects. Figure 2 shows the flowchart of the inclusion process.

Inclusion flowchart of the literature search and screening process.

Data Extraction

For each study, the definition of AR that was provided by the authors, and the related AR approaches that they cited (if any) were extracted. Additionally, information about contextual variables of the study was derived. Specifically, we identified the topic, country, organizational context, project duration, types of stakeholders involved, the main target group of the research, and methods used. The types of involved stakeholders were grouped according to the framework described by Schiller et al [ 17 ], in which they define the main stakeholder categories as the public, policy makers, and governments, the research community, practitioners and professionals, health and social service providers, civil society organizations, and private businesses. Finally, the best practices and lessons learned were derived. The best practices and lessons learned were activities that could move forward and benefit the AR project, without necessarily being recognized as standard components of AR. The difference between what was seen as a best practice and as a lesson learned was based on the timing and reporting of these actions. An activity was labeled as a best practice if researchers already planned their project with this in mind (eg, mentioning it in the description of the methods). On the other hand, lessons learned were those points that researchers came to know during their project, which were reported mainly in the discussion section. From the first 5 articles, the best practices and lessons learned were extracted by 2 authors (KO and CG), and they compared their results. The remaining data were extracted by 1 author (KO) in consultation with the second author where a second opinion was necessary. Furthermore, 5 authors published not 1 but 2 papers about their project. For these papers, the same study context was described whereas the definition of and approach to AR and the best practices and lessons learned were reported separately, as these sometimes differed between the articles. A reflection on 2 projects was included in 1 article. In this case, each project context was reported separately whereas only 1 AR definition and approach as well as one set of best practices and lessons learned were outlined.

A general overview of all the included studies describing the AR approach, AR definition, and contextual variables was obtained. The contextual variables (topic, location, target group, stakeholders, duration, and methods used) were categorized. Furthermore, the studies were mapped in a matrix based on the study duration and the types and number of different stakeholders that participated in the study. The contextual data were coded and categorized inductively. To identify which AR approach was the most used, the citation frequency of each approach in the included studies was recorded. Furthermore, the cited AR approaches that were available were accessed and checked for cross-referencing. All cited AR definitions were mapped to show the relationship between them. The AR definitions used, best practices, and lessons learned were coded by 1 author (KO). The best practices and lessons learned were coded individually first and then combined for both categories.

The setting of the included studies was described based on 6 categories (topic, location, duration, involved stakeholders, target group, and methods). Multimedia Appendix 1 presents all the categories and the description of the setting for each study. The most common aspects of each category will be discussed below.

We identified 9 broader categories of the research topics in the 44 included studies (see Table 2.1 in Multimedia Appendix 2 for the full list). The most common were home care and telemonitoring, and health promotion and education (both n=8), followed by electronic medical records and health information systems (n=7), and mental health services (n=5).

The studies were set in 21 different countries, Australia being the most common (n=5) followed by the United States (n=4) and Canada, Sweden, and the United Kingdom (all n=3). Some studies from nonwestern countries, like Tanzania or Colombia were included, but no country was represented more than once or twice. Within the different countries, studies took place in various contexts, the most prevalent of which were rural areas (n=6) and hospitals (n=5). All contexts and countries can be found in Tables 2.2 and 2.3 of Multimedia Appendix 2 .

Target Groups

Among the 44 studies, 2 studies explicitly focused on 2 different target groups at the same time, whereas all other studies had 1 main target group. In most cases, the target groups were patients (n=11). Of these, the most common group was patients with cancer (n=3). There were 6 studies each focusing on clinicians as well as children and young adults, and 5 studies targeted older adults (see Table 2.4 in Multimedia Appendix 2 for the full list of target groups).

Stakeholders

In many cases, several stakeholders were included in the study, up to 6 different types of stakeholders included in some cases. In summary, 20 different types of stakeholders were involved (see Table 2.5 in Multimedia Appendix 2 for the full list). Health care workers (n=18) and patients and their representatives (n=12) were involved the most, followed by governmental bodies (n=9) and general nonmedical staff members (n=8). When clustering these stakeholder types according to the framework defined by Schiller and colleagues [ 17 ], the largest group consisted of practitioners and professionals (n=48), followed by members of the public (n=38). Policy makers and government bodies (n=13), the research community (n=10), private businesses (n=6), and civil society organizations (n=3) were represented less often. The only group that was not represented at all included health and social service providers.

Not all of the 44 studies reported the duration of the project (n=7). Studies that did report the duration (n=33) lasted from a few months (n=5) to more than 10 years (n=2). The majority (n=13) of these studies reported a project duration between 2 and 3 years, and the average project duration was 2.7 years. Figure 3 shows the distribution of the 10 most frequently involved types of stakeholders for the different project durations in the 33 projects that reported the project duration. Stakeholder types are shown in the order of how many times they were involved in total; however, because some studies did not report project durations, the numbers in this graph differ from those described above. The 2 biggest stakeholder groups, health care workers and patients, were rarely, or in the case of patients even not at all, involved in long-term studies.

Heat map showing the most commonly involved types of stakeholders against the project duration.

In Figure 4 , the study duration is mapped against the number of different stakeholders that were involved in each of the 33 projects that reported a project duration. Studies that did not report the overall project duration are not included in the figure. Most of the included studies lasted for up to 2 years, including 2 or 3 stakeholder groups. There are some longer studies including more stakeholder groups.

Heat map showing the number of stakeholders involved against the project duration.

Research Methods Used

As mentioned earlier, AR is a framework that does not advise the use of a single methodology, and studies can therefore include a variety of different research methods. Most of the 44 included studies indeed used several methods, with some studies employing up to 6 different methods . Interviews were used most frequently (n=24), followed by focus groups (n=22), workshops (n=14), and surveys (n=13). On average, studies used nearly 3 different methods (average 2.8). All methods can be found in Table 2.6 of Multimedia Appendix 2 .

AR Definitions

The articles contained 44 definitions of AR. They could be grouped according to 4 different aspects that they emphasized. First, 21 studies emphasized that in AR projects, practitioners and other stakeholders become (co)researchers (n=21). Second, AR is a cyclical process that includes different stages (n=19). Third, 14 studies described how AR focuses on solving a practical issue and aims to extend research knowledge. The fourth aspect was that AR takes place in a community setting (n=10). Further, 2 studies included 3 of these aspects in their definitions, and only 2 other studies mentioned all 4 aspects. Most studies included either 1 (n=16) or 2 (n=17) of the aspects, whereas 7 studies included none of these points in their definition or did not at define AR in detail. Table 1 provides an overview of the number of mentions per aspect and the studies mentioning these aspects.

Number of mentions and studies mentioning the aspects of the AR definition.

AR Approaches

Table 2 gives an overview of the AR approaches that were cited at least twice in the included articles. The AR approach was not cited in 4 studies. In some cases, different papers from the same authors were cited; however, as these eventually described the same approach, the citation count was added up. The most commonly cited approach was that proposed by Reason and Bradbury [ 8 ]. As described earlier, the key elements of this approach are that AR (1) involves stakeholders as coresearchers, (2) consists of plan, act, and reflect cycles, (3) makes a change in practice, and (4) evaluates the said changes in and with the community. Overall, most definitions share these main aspects but differ in terms of the aspects that are particularly emphasized. For example, Baskerville and colleagues [ 55 ] highlight the duality of practical work and scientific knowledge, whereas Baum and colleagues [ 56 ] underline the need for reflective practice that includes all stakeholders. Figures 5 and ​ and6 6 depict the cited approaches in more detail. There are 3 independent researchers or groups that are mentioned as being the origin of AR, namely Lewin [ 7 ], Trist and colleagues [ 57 ], and Freire [ 58 ]. Wherever the origin of AR was mentioned, some cases have named 2 of these, as observed in Figure 5 . The cited AR approaches also frequently refer to each other and sometimes authors collaborate with each other, for example on books about AR (see Figure 6 ). There are no very distinct groups conducting their own AR, but the different AR groups are often connected and build upon each other’s work.

Overview of the most cited action research approaches in the included articles per author or research group, including the number of citations.

Overview of the action research approaches referred to in the included articles, indicating those papers that are mentioned as “the origin” of action research. Studies that either name an approach as being the origin of action research, or are being named as such, are highlighted in blue for better readability.

Overview of action research approaches referred to in the included articles. Arrows indicate citations between the action research approach papers. The number of times that the articles included in this review cited each approach is indicated in the box. We have used different arrow thicknesses for better readability. Blue boxes indicate those papers that were available and checked for citations.

Best Practices and Lessons Learned

As previously described, an activity was identified as a “best practice” if researchers already planned their project with this in mind (eg, mentioning it in the description of methods). Lessons learned were those points that researchers came to know during their project. These were mostly reported in the discussion section. In total, 85 best practices and 66 lessons learned were identified, which were clustered into 22 categories of best practices and 16 categories of lessons learned. Among the 44 papers, 3 papers did not indicate any best practices that they followed, whereas 12 papers did not include any identifiable lessons learned. There were 8 overlapping categories, identified as best practices in some articles and as lessons learned in others. These will be discussed in more detail below.

Best Practices

The identified best practices in the 44 studies were most often related to the use of a specific method (n=9), namely personas (n=2), world café, journey mapping, role play, scenarios, case studies, design cards, and mixing different types of data collection methods (all n=1). Other best practices were a continuous evaluation of the project and a reflection on the process by the research team (n=8). The importance of establishing active contact between researchers and stakeholders and raising the confidence and skills of stakeholders was emphasized by 7 studies. The improvement of stakeholder skills mainly referred to research and analytical skills, allowing stakeholders to set up their own studies or continue the work after the project was finished. There were several specific suggestions to improve the regular project team meetings, for example, to always use the same agenda or to share a common area (office space) to make contact easier. Some other best practices concern the reporting and presentation of outcomes (n=6). The complete list of best practice categories can be found in Table 3 .

Overview of all best practice categories and number of mentions per category (N=44).

Lessons Learned

Apart from the best practices, the lessons learned from each study were identified. The most common lessons learned were increasing stakeholder knowledge and skills (n=8) and continuous evaluation of the project and reflection on the process (n=6). Both of these had been identified as best practices in other articles (more on this overlap below). Recommendations for the use of specific methods were also common (n=5). Lessons learned regarding reporting, adapting the project to fit the needs of stakeholders, fostering a welcoming environment, and the questionable replicability of the research were each mentioned 4 times. All lessons learned are shown in Table 4 .

Overview of all lessons learned categories and number of mentions per category (N=44).

Overlapping Best Practices and Lessons Learned

As stated earlier, some aspects were identified as best practices in some articles and as lessons learned in others. In total, we identified 7 such overlapping aspects. Overall, the most mentioned aspect was the importance of raising stakeholder skills and confidence (n=15, where best practices= 7 and lessons learned=8). Many articles reported the need for stakeholders to learn new skills, for example related to academic research, or the need to be convinced about their ability to perform these tasks. Almost all the studies that reported this as a best practice or lesson learned involved health care professionals as stakeholders. Other commonly mentioned points were recommendations for specific methods, even though the suggested methods differed (n=14, where best practices=9 and lessons learned=5) and there was continuous reframing and evaluation of the project (n=14, where best practices=8 and lessons learned=6). Continuous reframing often referred to the iterations of planning, action, and evaluation in AR projects. Studies that described this mostly did not include this cyclical nature of AR in their definition of it. In total, there were 10 recommendations regarding the reporting and presentation of results (best practices=6 and lessons learned=4), for example calling for open and accessible publishing of outcomes. The best practices and lessons learned included recommendations about meeting regularly (n=9, where best practices=7 and lessons learned=2), adapting to the needs of stakeholders (n=8, where best practices=3 and lessons learned=5), and investing in the relationship between partners (n=6, where best practices=3 and lessons learned=3).

Chronology of Overlapping Best Practices and Lessons Learned

When observing the publication timeline, most of the overlapping aspects appeared as a lesson learned in earlier publications, and then as a best practice in papers published at a later point in time. This was the case regarding stakeholder skills, appearing as a lesson learned in 1999 [ 33 ] and as a best practice in 2016 [ 25 ]; continuous reframing of the project was a lesson learned in 2003 [ 19 ] and best practice in 2009 [ 42 ]; further, having regular meetings was a lesson learned in 2006 [ 72 ] and a best practice in 2018 [ 27 ], and adapting the research to stakeholder needs was a lesson learned in 2007 [ 32 ] and a best practice in 2016 [ 77 ]. Such a clear timeline could not be seen for accessible reporting, appearing as a lesson learned in 2017 [ 78 ] and a best practice in 2007 [ 45 ], and the relationship between partners appearing as a lesson learned in 2017 [ 36 ] and as a best practice in 2008 [ 38 ].

Principal Results

To identify recommendations on how to conduct AR in eHealth studies, this literature review analyzed the setting, AR description, and best practices and lessons learned in 44 studies. The most important recommendations from this review, which will be discussed in more detail below, are as follows: actively raising stakeholder skills and confidence; fulfilling multiple roles and tasks as a researcher; fostering constant reflection and evaluation; ensuring open and accessible dissemination; reporting in a more structured and comprehensive way.

These recommendations are not exclusively related to eHealth, despite them being derived from a review of eHealth AR studies. Hence, it is possible that the recommendations are also relevant for AR in various other fields. Therefore, where possible, examples from different disciplines are discussed below to explain or supplement a recommendation.

Stakeholder Skills and Confidence

Being involved in a project as coresearcher can potentially increase stakeholders’ confidence, besides teaching them new skills [ 79 ]. However, this does not happen automatically. Similar to our findings, the narrative review conducted by Harrison and colleagues [ 80 ] also identified educating the research team as the most important task when stakeholders are involved in health care research. Nevertheless, there is limited research on how skill training for stakeholders could look like, and this can vary greatly between studies. Stakeholders in some eHealth studies might need to learn content-related information [ 81 ], whereas other studies require methodological or statistical skills [ 54 ]. Researchers should provide adequate training and material for their project and encourage stakeholders to make use of it. The studies included in this review that recommended stakeholder skill training almost exclusively worked with health care professionals. The relationship between recommending skill training and working mainly with health care professionals remains unclear. A possible explanation could be that other stakeholder groups in other studies already had the necessary skills and thus did not require any additional training. Another possibility is that other stakeholders were not given the same roles that health care professionals held, and therefore, they did not need skill training. Finally, as we will discuss later, reporting of AR activities was not always very extensive. Thus, stakeholders outside the health care sector were possibly trained, and these studies did not report on this aspect. Generally, not all participants prefer the same level of engagement in a project, and researchers should respect these preferences [ 82 ].

Tasks and Roles of the Researcher

Different aspects of the role and tasks of the researcher in an AR project are discussed. Brydon-Miller and Aragón describe the many different tasks that action researchers need to fulfil as their “500 hats” [ 83 ]. These are not specific to eHealth studies, but they can occur in any AR study. As researchers and stakeholders have many varied duties, their roles are not fixed and might change over the course of the project [ 19 ]. One main task of the researchers that continues throughout the project is the need to foster a welcoming environment for all stakeholders [ 42 ]. Researchers should also be present and actively involve themselves at a higher level than that needed in non-AR projects [ 38 ]. Additional AR-specific tasks for the researchers include investing in partner relationships [ 35 ] or breaking down power structures [ 28 ]. Generally, AR studies demand more self-reflection and awareness from the researchers than other projects and researchers should keep this in mind when entering an AR project.

Constant Reflection

The importance of continuous reframing and evaluation of the project was emphasized in several studies. Although evaluation is 1 of the AR cycles, studies providing recommendations on this topic rarely included this in their definition of AR. Owing to the lack of reports on AR cycles, which will be discussed below, it is unclear if these studies still followed the AR cycles without reporting on them. However, sometimes, it seems that periodic planned evaluation is not enough. Instead, the participants need to regularly reflect on the current status of the project and their role in it. Therefore, new AR projects should create suitable spaces for evaluation and reflection in ways that fit the projects and stakeholders. This is especially important because reflection can become difficult once a person is in the middle of the project [ 49 ]. Holeman and Kane [ 53 ] emphasize that reflection should not only take place within the project, but it should also be explicitly reported to help other researchers. If action researchers take reflection seriously and include honest evaluations in their publishing, the AR community members can learn from each other. Additionally, researchers and other stakeholders within the project learn and benefit from constant reflection [ 9 ].

Accessible Dissemination

Another important aspect concerns paying attention to open and understandable dissemination of results within the community and among researchers. Action researchers need to communicate findings to the academic world while also finding ways to inform the target group about the project in ways that suit the target users’ needs. An example of open and accessible dissemination can be found in Canto-Farachala and Larrea [ 83 ]. They present the results of their AR project regarding territorial development on an interactive website, allowing others to learn from their work. However, it seems that accessible reporting is still not the norm in AR, as Avison and colleagues [ 62 ] describe that many AR studies are generally “published in books rather than as articles. Action researchers have large and complicated stories to tell.” Future AR projects should attempt to narrate their stories in such a way that others can learn from them.

Comprehensive Reporting

The different way of describing AR studies also leads to another issue, incomplete and elusive reporting. Although most studies did provide at least a short description of what they saw as AR, 7 studies provided no definition at all. Additionally, there were only 4 studies that included 3 or all of the 4 aspects of the AR definition in their description. Even the most mentioned aspects appeared in less than half of the included papers. Even though most papers did cite an AR approach of definition, some did not. In combination with the often-limited descriptions of AR, this makes it difficult to obtain a clear picture of how AR is perceived and performed in a particular study. This resonates with what Bradbury and colleagues [ 9 ] describe as 1 of the quality points of AR, namely “action research process and related methods (should be) clearly articulated and illustrated.” The best practices and lessons learned that were extracted from the included studies were seldom mentioned explicitly. Best practices were often hidden in the description of the project, without much reasoning. Similarly, lessons learned were often described as adaptations made during the project or as plans for the future. Although we observed that some lessons learned turned into best practices over time, we think that researchers could benefit more from each other’s work by providing concrete recommendations. This review is a step in that direction. Both aspects show that the reporting of AR studies in eHealth can be improved to show more clearly what eHealth AR projects can look like and help others in setting up such projects with specific recommendations.

Limitations

Approximately a third of the included papers (14 out of 44) were published more than 10 years ago. This also means that some of the technologies that are described in the older papers are now relatively old. However, this literature review focuses mainly on the AR methodology and lessons learned about doing action research. Therefore, there was no exclusion criterium regarding the publication date of the papers.

The search yielded several PD-related papers. These papers could have been included, given that some definitions of PD are very similar to AR. However, as our aim was to provide an overview of how AR is done, these were excluded as the researchers of these studies themselves did not identify their studies as being related to AR (ie, not referring to, mentioning, or describing AR). Although this offers a clearer picture of how researchers conduct AR, it also creates a potential limitation in that best practices and lessons learned could be enriched from PD literature.

This overview of AR approaches focuses mostly on the interconnectedness among the approaches, without a comprehensive comparison of the content. Comparing the approaches with regard to the specific aspects of AR that they describe would be a review in and of itself, going beyond the scope of this current review. Therefore, we decided to focus on the definitions that the authors themselves provided even when they also cited AR approaches, as these are most likely to reflect their own vision of AR.

This review illustrates how AR is conducted in eHealth studies. Studies that fulfilled the inclusion criteria mainly took place in western countries and lasted for 2 to 3 years. Different stakeholders were involved, but the most commonly involved groups were health care professionals and patients. As for the methods used, most studies opted for focus groups and interviews. Even though many studies cited the AR approach proposed by Reason and Bradbury [ 8 ], their own definitions of AR were often not explicit in terms of how they implemented AR. Future projects should report their AR definition as well as the best practices and lessons learned more clearly. Other recommendations include paying attention toward developing the skill and confidence of the stakeholders, being aware of the changing role of the researcher, frequently evaluating the project, and disseminating results in an understandable manner.

Abbreviations

Multimedia Appendix 1

Multimedia appendix 2.

Authors' Contributions: KO performed the literature search and analysis and was a major contributor in designing the study and writing the manuscript. CG contributed to the design of the study, assisted with the search and analysis, and made major contributions to the manuscript. FN and LvV contributed to the design of the study and substantially revised the manuscript. All authors read and approved the final manuscript. This project has received funding from the European Union’s Horizon 2020 research and innovation program (grant 857188).

Conflicts of Interest: None declared.

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Parts of an Action Research and How to Conduct

What action research is and is not.

The Action Research Process

INITIAL STEPS

IN CONDUCTING AN

ACTION RESEARCH

STEP 1: MAKING THE COMMITMENT TO INQUIRY

• A professional stance
• A way of learning about your classroom
• A way of learning about yourself as a teacher
• Using the 5whQ
• Possible questions:

Why do the boys in my class….?

What happens when I …..?

I wonder what happens when  I …..?

Starting points to identify an issue you would like to research (Caro-Bruce, 2000):

Sometimes it helps to use a variety of questions such as:

I would like to improve ____________________________________

I am perplexed by________________________________________

I am really curious about __________________________________

Something I think would really make a difference is ___________

Something I would like to change is _______________________

What happens to student learning in my classroom when I _____?

How can I implement ____________________________________?

How can I improve ______________________________________?

Step 2:   Read , Research, Reflect

• Framing a good question

Avoid yes or no questions

Avoid questions to which you already know the answer

• A good question is

free of educational jargons,

use simple everyday words ,

do not prejudge the result

Characteristics of Good Research Questions

A good classroom action research question should:

• Be meaningful, compelling, and important to you as a teacher-researcher.
• Be manageable and within your sphere of influence.
• Be important for learners.
• Benefits your students by informing your teaching and the curriculum, by providing new insights about students and their learning , by broadening and deepening your perspectives, or by improving practice.
• Lead to taking an action
• What happens to the quality of student writing when I implement peer editing in my English classes?
• How does the use of computers affect the student writing process in my class?
• What happens to student understanding of specific geometrical concepts when I incorporate exploratory exercises into the teaching of geometry in my classroom?
• What happens to students’ academic performance in the classrooms when the school observes the heterogeneous system during cooperative learning activities?

Conducting a Literature Review (Holly, Arhar, and Kasten ,2005)

• Read broadly and generally, at first, then read more narrowly.
• When you are researching a novel topic that seems to have few resources, look for related topics and then synthesize them.
• Consult primary resources as possible.
• Ask for help.
• Read enough to get started, but not so much that you become too exhausted to conduct your study .
• Read with a critical eye.

Step 3: Make changes or try a new idea   

What are you going to do?

How will you measure the result?

Identifying Data Sources

• Why are we collecting the data?
• How are the data related to the research question?
• What kind of data will yield the best information? What counts as data?
• What data will we collect? How much data will we collect? Will data be easy or difficult to collect?
• Who will be using the data?
• What data sources will we use to collect information?
• How will the data be collected and analyzed? How systematic will data collection be?
• How will the data be organized? How will the data be displayed?
• What criteria will be used to analyze the data?
• How will the data be recorded and shared?

Step 4:  Evaluate and Reflect

How can you be sure that your conclusions are fair and accurate?

Step 5: Improve or amend your practice

How will I do things differently?

What have you learned from the project?

Have your questions been answered?

How will you share the results?

Could they be useful to others in your school/ community?

Context and Rationale of the Study

• Cite Literature review
• What is the general situation/circumstance that makes you develop your research proposal?
• Why is this situation/ circumstance important?
• What do you intend to do?
• This is the aim of your study. This should also be embedded in your main arguments.
• The significance of your research
• Why is your study important?
• Who or what industry will benefit? Why?
• What would be the potential contribution or insight of my research?

ACTION RESEARCH QUESTIONS

Reflect on your experiences and identify the most critical problem that affects your students’ learning

PROPOSED INTERVENTION, INNOVATION, STRATEGY

• Explain the intervention and cite literature that supports /validate the strategy to be used
• The teacher-researchers will develop an M.A.D (Modified Awareness Design) Tool : Contextualized and Localized Instructional Learning Material with seven (7) lessons where its objectives are based on the least mastered skills. The development of the IM anchors the simplified process of ADDIE Model which follows: Phase I – Preparation, Phase II – Development, Phase III – Validation, Phase IV – Try-Out.

Methodology

* PARTICIPANTS – All Grade 8 OHSP learners will serve as the respondents of this study.

* SOURCES OF DATA/ INFORMATION – The following are the data collection tools which will be utilized this study:

• Research constructed questionnaire
• Pretest/ post-test
• Summative test scores

* DATA GATHERING METHODS

• In developing the instructional learning material, the concept of ADDIE will utilize where:
• Phase I- The preparation stage involves administering the pretest using the teacher-made test validated by the Grade 8 teachers. It will use to determine the least mastered skills of the Grade 8 OHSP learners. The contents and components of the MAD Tool: Contextualized and Localized IM will base on the result of the pretest.
• Phase II – The development stage involves the following phases; deciding on the format of the module, the process of writing the module and the initial revisions needed to improve the first draft of the module.
• Phase III – In the validation stage, English teachers (peers and experts) will ask to assess the module in terms of its objectives

Plans for Dissemination and Utilization

• The results of the study will be presented and disseminated during learning action cells , teacher’s quality circle , conference after the study and will be presented through infographics which will be part of the initiatives of the school administrators and the subject area teachers.

  Teachers must continue to give frequent positive feedback that supports pupil’s beliefs that they can do well; ensure opportunities for student’s success by assigning tasks that are either too easy nor too difficult; help students find personal meaning and value of the material; and help students feel that they are valued members of a learning community.

Sample of Reflection

As I reflect on my first journey as a teacher-researcher, I breathe a sigh of relief. The light at the end of this long, winding tunnel is finally in sight. I found the process of conducting an action research project very complex and often overwhelming. However, at the same time, I found it to be extremely enlightening and rewarding.

It is self-perception about the study.

Best, J.W., & Kahn, J.V. (1998). Research in education (8th ed.). Needham Heights, MA: Allyn and Bacon.

Borg, W. (1981). Applying educational research: A practical guide for teachers. New York: Longman.

Brennan, M., & Williamson, P. (1981). Investigating learning in schools. Victoria, Australia: Deakin University Press.

Calhoun, E.F. (1994). How to use action research in the self-renewing school. Alexandria, VA: Association for Supervision and Curriculum Development.

Cochran-Smith, M., & Lytle, S.L. (Eds.). (1993). Inside/outside: Teacher research and knowledge. New York: Teachers College Press.

Corey, S.M. (1953). Action research to improve school practices. New York: Teachers College Press.

Johnson, B.M. (1995, Fall). Why conduct action research? Teaching and Change,1, 90-105.

source: SDO Las Pinas

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The Journal of Extension (JOE) is the flagship journal for Extension education.

As of January 1 st , 2021, the Journal of Extension is published by Clemson University Press.

As we enter JOE 's sixtieth year, we are excited to announce a significant change to our submission policies: Beginning with issue 60 (1), word count limits for most submission categories will be increased. We hope that this will allow authors the chance to more fully explore important topics in Feature Articles and Research In Brief submissions. We also remain committed, of course, to providing concise, practical articles in the form of Ideas at Work and Tools of the Trade submissions. Commentary submission guidelines have not changed. The word count limits for each category are as follows:

Feature Article: Up to 5000 words

Research in Brief: Up to 3000 words

Ideas at Work: Up to 2000 words

Tools of the Trade: Up to 1250 words

Commentary: Up to 1500 words (no change)

Prospective authors are invited to view the full submission guidelines by visiting the link in the sidebar.

Current Issue: Volume 62, Number 2 (2024)

Feature article.

Nebraska Conventional Farmers’ Perspectives Toward Agricultural Hemp: A Qualitative Insight Guided by the Diffusion of Innovations Theory Blake C. Colclasure, Nicholas Gray, and Laura E. Young

Research in Brief

Perceived Beef Producer Challenges and Competencies for a Value-Added Beef Extension Program Sarah J. Al-Mazroa Smith and Greg Miller

Educator Feedback on a Farm Tractor and Machinery Safety Training Program: Implications for Program Content and Success Linda Fetzer, Brenna Butler, and Judd Michael

Workshop Wine Wednesdays: Improving knowledge and motivations about local wines. Aude A. Watrelot, Sarah Al-Mazroa Smith, and Sarah L. Francis

Extension Efforts to Address the Current National Housing Crisis Michael J. Dougherty, Melissa B. Hamilton, and Bradley Neumann

Heirs Property And The Necessary Role Of Extension In Preventing Land Loss Through Partitioning Kurt Smith

Incorporating Subjective Measures of Problematic Money Issues in Extension Workshops Lucy M. Delgadillo Ph.D and Luke Erickson

Health Rocks!: An 11-year evaluation Dan Wang, Yan Xia, Maria Rosario de Guzman, Jeong-Kyun Choi, Yunqi Wang, and Zhenqiao Yang

Cooperative Extension’s Role in Addressing the Opioid Overdose Crisis: Best Practices from the HEART Initiative Model Hailey Judd, Alise Williams Condie, Ashley C. Yaugher, Mateja R. Savoie-Roskos, Gabriela Murza, Timothy Keady, Sadie Wilde, Rachel Myrer, and Maren Wright Voss

Tools of the Trade

Recentering Community Nutrition Education: A New Framework for Food Insecurity Understanding Chasity Tompkins

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• As Ozempic’s Popularity Soars, Here’s What to Know About Semaglutide and Weight Loss JAMA Medical News & Perspectives May 16, 2023 This Medical News article discusses chronic weight management with semaglutide, sold under the brand names Ozempic and Wegovy. Melissa Suran, PhD, MSJ
• Patents and Regulatory Exclusivities on GLP-1 Receptor Agonists JAMA Special Communication August 15, 2023 This Special Communication used data from the US Food and Drug Administration to analyze how manufacturers of brand-name glucagon-like peptide 1 (GLP-1) receptor agonists have used patent and regulatory systems to extend periods of market exclusivity. Rasha Alhiary, PharmD; Aaron S. Kesselheim, MD, JD, MPH; Sarah Gabriele, LLM, MBE; Reed F. Beall, PhD; S. Sean Tu, JD, PhD; William B. Feldman, MD, DPhil, MPH
• What to Know About Wegovy’s Rare but Serious Adverse Effects JAMA Medical News & Perspectives December 12, 2023 This Medical News article discusses Wegovy, Ozempic, and other GLP-1 receptor agonists used for weight management and type 2 diabetes. Kate Ruder, MSJ
• GLP-1 Receptor Agonists and Gastrointestinal Adverse Events—Reply JAMA Comment & Response March 12, 2024 Ramin Rezaeianzadeh, BSc; Mohit Sodhi, MSc; Mahyar Etminan, PharmD, MSc
• GLP-1 Receptor Agonists and Gastrointestinal Adverse Events JAMA Comment & Response March 12, 2024 Karine Suissa, PhD; Sara J. Cromer, MD; Elisabetta Patorno, MD, DrPH
• GLP-1 Receptor Agonist Use and Risk of Postoperative Complications JAMA Research Letter May 21, 2024 This cohort study evaluates the risk of postoperative respiratory complications among patients with diabetes undergoing surgery who had vs those who had not a prescription fill for glucagon-like peptide 1 receptor agonists. Anjali A. Dixit, MD, MPH; Brian T. Bateman, MD, MS; Mary T. Hawn, MD, MPH; Michelle C. Odden, PhD; Eric C. Sun, MD, PhD
• Glucagon-Like Peptide-1 Receptor Agonist Use and Risk of Gallbladder and Biliary Diseases JAMA Internal Medicine Original Investigation May 1, 2022 This systematic review and meta-analysis of 76 randomized clinical trials examines the effects of glucagon-like peptide-1 receptor agonist use on the risk of gallbladder and biliary diseases. Liyun He, MM; Jialu Wang, MM; Fan Ping, MD; Na Yang, MM; Jingyue Huang, MM; Yuxiu Li, MD; Lingling Xu, MD; Wei Li, MD; Huabing Zhang, MD
• Cholecystitis Associated With the Use of Glucagon-Like Peptide-1 Receptor Agonists JAMA Internal Medicine Research Letter October 1, 2022 This case series identifies cases reported in the US Food and Drug Administration Adverse Event Reporting System of acute cholecystitis associated with use of glucagon-like peptide-1 receptor agonists that did not have gallbladder disease warnings in their labeling. Daniel Woronow, MD; Christine Chamberlain, PharmD; Ali Niak, MD; Mark Avigan, MDCM; Monika Houstoun, PharmD, MPH; Cindy Kortepeter, PharmD

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Sodhi M , Rezaeianzadeh R , Kezouh A , Etminan M. Risk of Gastrointestinal Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists for Weight Loss. JAMA. 2023;330(18):1795–1797. doi:10.1001/jama.2023.19574

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Risk of Gastrointestinal Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists for Weight Loss

• 1 Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
• 2 StatExpert Ltd, Laval, Quebec, Canada
• 3 Department of Ophthalmology and Visual Sciences and Medicine, University of British Columbia, Vancouver, Canada
• Medical News & Perspectives As Ozempic’s Popularity Soars, Here’s What to Know About Semaglutide and Weight Loss Melissa Suran, PhD, MSJ JAMA
• Special Communication Patents and Regulatory Exclusivities on GLP-1 Receptor Agonists Rasha Alhiary, PharmD; Aaron S. Kesselheim, MD, JD, MPH; Sarah Gabriele, LLM, MBE; Reed F. Beall, PhD; S. Sean Tu, JD, PhD; William B. Feldman, MD, DPhil, MPH JAMA
• Medical News & Perspectives What to Know About Wegovy’s Rare but Serious Adverse Effects Kate Ruder, MSJ JAMA
• Comment & Response GLP-1 Receptor Agonists and Gastrointestinal Adverse Events—Reply Ramin Rezaeianzadeh, BSc; Mohit Sodhi, MSc; Mahyar Etminan, PharmD, MSc JAMA
• Comment & Response GLP-1 Receptor Agonists and Gastrointestinal Adverse Events Karine Suissa, PhD; Sara J. Cromer, MD; Elisabetta Patorno, MD, DrPH JAMA
• Research Letter GLP-1 Receptor Agonist Use and Risk of Postoperative Complications Anjali A. Dixit, MD, MPH; Brian T. Bateman, MD, MS; Mary T. Hawn, MD, MPH; Michelle C. Odden, PhD; Eric C. Sun, MD, PhD JAMA
• Original Investigation Glucagon-Like Peptide-1 Receptor Agonist Use and Risk of Gallbladder and Biliary Diseases Liyun He, MM; Jialu Wang, MM; Fan Ping, MD; Na Yang, MM; Jingyue Huang, MM; Yuxiu Li, MD; Lingling Xu, MD; Wei Li, MD; Huabing Zhang, MD JAMA Internal Medicine
• Research Letter Cholecystitis Associated With the Use of Glucagon-Like Peptide-1 Receptor Agonists Daniel Woronow, MD; Christine Chamberlain, PharmD; Ali Niak, MD; Mark Avigan, MDCM; Monika Houstoun, PharmD, MPH; Cindy Kortepeter, PharmD JAMA Internal Medicine

Glucagon-like peptide 1 (GLP-1) agonists are medications approved for treatment of diabetes that recently have also been used off label for weight loss. 1 Studies have found increased risks of gastrointestinal adverse events (biliary disease, 2 pancreatitis, 3 bowel obstruction, 4 and gastroparesis 5 ) in patients with diabetes. 2 - 5 Because such patients have higher baseline risk for gastrointestinal adverse events, risk in patients taking these drugs for other indications may differ. Randomized trials examining efficacy of GLP-1 agonists for weight loss were not designed to capture these events 2 due to small sample sizes and short follow-up. We examined gastrointestinal adverse events associated with GLP-1 agonists used for weight loss in a clinical setting.

We used a random sample of 16 million patients (2006-2020) from the PharMetrics Plus for Academics database (IQVIA), a large health claims database that captures 93% of all outpatient prescriptions and physician diagnoses in the US through the International Classification of Diseases, Ninth Revision (ICD-9) or ICD-10. In our cohort study, we included new users of semaglutide or liraglutide, 2 main GLP-1 agonists, and the active comparator bupropion-naltrexone, a weight loss agent unrelated to GLP-1 agonists. Because semaglutide was marketed for weight loss after the study period (2021), we ensured all GLP-1 agonist and bupropion-naltrexone users had an obesity code in the 90 days prior or up to 30 days after cohort entry, excluding those with a diabetes or antidiabetic drug code.

Patients were observed from first prescription of a study drug to first mutually exclusive incidence (defined as first ICD-9 or ICD-10 code) of biliary disease (including cholecystitis, cholelithiasis, and choledocholithiasis), pancreatitis (including gallstone pancreatitis), bowel obstruction, or gastroparesis (defined as use of a code or a promotility agent). They were followed up to the end of the study period (June 2020) or censored during a switch. Hazard ratios (HRs) from a Cox model were adjusted for age, sex, alcohol use, smoking, hyperlipidemia, abdominal surgery in the previous 30 days, and geographic location, which were identified as common cause variables or risk factors. 6 Two sensitivity analyses were undertaken, one excluding hyperlipidemia (because more semaglutide users had hyperlipidemia) and another including patients without diabetes regardless of having an obesity code. Due to absence of data on body mass index (BMI), the E-value was used to examine how strong unmeasured confounding would need to be to negate observed results, with E-value HRs of at least 2 indicating BMI is unlikely to change study results. Statistical significance was defined as 2-sided 95% CI that did not cross 1. Analyses were performed using SAS version 9.4. Ethics approval was obtained by the University of British Columbia’s clinical research ethics board with a waiver of informed consent.

Our cohort included 4144 liraglutide, 613 semaglutide, and 654 bupropion-naltrexone users. Incidence rates for the 4 outcomes were elevated among GLP-1 agonists compared with bupropion-naltrexone users ( Table 1 ). For example, incidence of biliary disease (per 1000 person-years) was 11.7 for semaglutide, 18.6 for liraglutide, and 12.6 for bupropion-naltrexone and 4.6, 7.9, and 1.0, respectively, for pancreatitis.

Use of GLP-1 agonists compared with bupropion-naltrexone was associated with increased risk of pancreatitis (adjusted HR, 9.09 [95% CI, 1.25-66.00]), bowel obstruction (HR, 4.22 [95% CI, 1.02-17.40]), and gastroparesis (HR, 3.67 [95% CI, 1.15-11.90) but not biliary disease (HR, 1.50 [95% CI, 0.89-2.53]). Exclusion of hyperlipidemia from the analysis did not change the results ( Table 2 ). Inclusion of GLP-1 agonists regardless of history of obesity reduced HRs and narrowed CIs but did not change the significance of the results ( Table 2 ). E-value HRs did not suggest potential confounding by BMI.

This study found that use of GLP-1 agonists for weight loss compared with use of bupropion-naltrexone was associated with increased risk of pancreatitis, gastroparesis, and bowel obstruction but not biliary disease.

Given the wide use of these drugs, these adverse events, although rare, must be considered by patients who are contemplating using the drugs for weight loss because the risk-benefit calculus for this group might differ from that of those who use them for diabetes. Limitations include that although all GLP-1 agonist users had a record for obesity without diabetes, whether GLP-1 agonists were all used for weight loss is uncertain.

Accepted for Publication: September 11, 2023.

Published Online: October 5, 2023. doi:10.1001/jama.2023.19574

Correction: This article was corrected on December 21, 2023, to update the full name of the database used.

Corresponding Author: Mahyar Etminan, PharmD, MSc, Faculty of Medicine, Departments of Ophthalmology and Visual Sciences and Medicine, The Eye Care Center, University of British Columbia, 2550 Willow St, Room 323, Vancouver, BC V5Z 3N9, Canada ( [email protected] ).

Author Contributions: Dr Etminan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Sodhi, Rezaeianzadeh, Etminan.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Sodhi, Rezaeianzadeh, Etminan.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Kezouh.

Obtained funding: Etminan.

Administrative, technical, or material support: Sodhi.

Supervision: Etminan.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was funded by internal research funds from the Department of Ophthalmology and Visual Sciences, University of British Columbia.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement .

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ASCP’s AMA Delegates Represent Pathologists’ Interests at AMA Meeting … and Receive a Surprise

August 09, 2024

ASCP delegates exemplified leadership and the Society’s “Stronger Together” mantra while representing the pathologists’ perspective at the American Medical Association (AMA) 2024 Annual Meeting of the House of Delegates (HOD) in June. ASCP delegates Ed Donoghue Jr., MD, MASCP; Jennifer Stall, MD, FASCP; ASCP Past Presidents Steve Kroft, MD, MASCP, and William Finn, MD, MASCP; as well as Clifford H. Sullivan, MD, FASCP; and Nirali M. Patel, MD, FASCP, discussed issues pertinent to pathology with partner organizations and represented pathology on the floor of the House of Medicine. In recognition of the outstanding work of ASCP’s AMA delegation, ASCP President Robert Goulart, MD, MASCP, has awarded the delegation the 2024 ASCP President’s Award. (Read more below about the award.) 

Artificial Intelligence 

The use of artificial intelligence (AI) in the healthcare setting and the risks/benefits associated with the technology was among the timely topics discussed in the House of Delegates. During the Pathology Section Council meeting (and reflected in a recent  Medscape   article ), Dr. Steve Kroft raised concerns about unintended consequences that could occur within the scientific research community through the use of unregulated AI, specifically from his perspective as Editor in Chief of the  American Journal of Clinical Pathology  ( AJCP ).

Dr. Kroft asked the AMA to address "a significant omission in an otherwise comprehensive [trustees’] report" — the need to protect the integrity of study results that can direct patient care. According to the  Medscape  article, Dr. Kroft noted, "While sham science is not a new issue, large language models make it far easier for authors to generate fake papers and far harder for editors, reviewers, and publishers to identify them. This is a rapidly growing phenomenon that is threatening the integrity of the literature. These papers become embedded in the evidence bases that drive clinical decision-making." It is significant for the AMA to address this important issue raised by Dr. Kroft.

Attendees also discussed changing the term from “artificial intelligence” to “augmented intelligence” to more accurately reflect AI’s role in assisting physicians and the entire healthcare team.

Medicare Physician Payment

Medicare physician payment continues to be a priority area for ASCP and the AMA. It was a key topic of discussion during the AMA meeting. Specifically, ASCP recently sent an Action Alert to all members asking them to urge Congress to fix problems with the Medicare Physician and Clinical Laboratory Fee Schedules. (Click  here  to participate in this campaign.)

Other key issues discussed include: 

• Prior authorization
• Cybersecurity
• Substance use disorder and mental health treatment
• Expanded healthcare coverage for Medicare and Medicaid patients

Diversity, Equity, and Inclusion

Throughout the meeting, the AMA HOD adopted a number of policies that aligned with ASCP’s own DEI priorities. These include:

• Policies to protect patient access to healthcare;
• Policies aimed at improving the health care of minority communities in rural areas, including several related to tobacco and nicotine;
• Policies intended to improve health outcomes for American Indians and Alaska Natives; and
• Policies aimed at equity in clinical trials and research. Specifically, delegates adopted policy to ensure more women and sexual and gender minority populations are included in clinical trials and medical research.

2024 ASCP President’s Award

ASCP is pleased to announce that its ASCP AMA delegation has received the 2024 ASCP President’s Award for its work representing pathology and the laboratory community in the House of Medicine at the November 2023 AMA Interim meeting. ASCP delegates provided valuable testimony related to the U.S. Food and Drug Administration (FDA) Proposed Rule on Laboratory Developed Tests.

Their testimony highlighted the potential adverse effects of the FDA’s rule to clinical colleagues within the HOD. Their efforts led to an agreement from other professional medical societies and physicians, recognizing that the FDA rules could hinder the provision of necessary testing services, particularly in the absence of FDA-approved tests. Ultimately, the AMA HOD adopted an ASCP resolution calling for the AMA to urge the FDA to extend the comment period on its laboratory developed tests (LDT) proposed rule, for which they were commended.

The President’s Award is a highlight of the  ASCP 2024 Annual Meeting  and will be presented by ASCP President Robert Goulart, MD, MASCP, on September 5, in Chicago, IL. The 2024 President’s Award recognizes the delegates’ significant contributions on behalf of the specialty, particularly in advocating for changes to the FDA's proposed rule on LDTs.

ASCP delegates will continue to address emerging challenges in pathology and healthcare policy, ensuring that pathologists' and laboratory professionals’ perspectives continue to be represented effectively within the House of Medicine.

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Translating research results into policy insights to underpin climate action in Ireland

This chapter presents innovative processes that have been developed and used to bridge the interface between the research ecosystem and policy-making ecosystem. It focuses on a specific case study, namely how energy systems modelling has been used to inform energy and climate mitigation policies in Ireland. We trace the development of energy systems modelling tools and capacity in Ireland over the past 15 years, and the key role it has played in addressing important policy questions related to delivery of a number of UN Sustainable Development Goals (SDGs). We also outline the parallel evolution of novel research communications methods, proactive engagement programmes with policy practitioners and co-production processes.

Prof Brian Ó Gallachóir ,  Dr. Fionn Rogan ,  Dr. Paul Deane

Ó Gallachóir, B., Deane, P., Rogan, F. (2024). Translating Research Results into Policy Insights to Underpin Climate Action in Ireland. In: Labriet, M., Espegren, K., Giannakidis, G., Ó Gallachóir, B. (eds) Aligning the Energy Transition with the Sustainable Development Goals. Lecture Notes in Energy, vol 101. Springer, Cham. https://doi.org/10.1007/978-3-031-58897-6_15

Specific examples of energy and climate mitigation policies are highlighted to demonstrate how the research results have been used together with the communication and engagement methods not only to inform but also to underpin policy developments. The contributions of this work to the SDGs are highlighted, in particular SDG 13 on climate and SDG 7 on energy, but also SDG 12 on sustainable consumption and production and SDG 17 on partnerships. We conclude with a proposed seven stage approach, for energy modellers who wish to successfully bridge between the research and policy eco-systems, namely (1) undertake scientifically robust research, making methods and results openly and publicly available (2) frame research questions that respond to specific policy needs, (3) translate research results into policy insights (4) improve communications of research findings including through use of infographics (5) engage actively with policy practitioners and policy makers (6) co-produce policy with policy practitioners and (7) build absorptive capacity in the policy system.

Environmental Research Institute, Ellen Hutchins Building, University College Cork, Lee Road, Cork, Ireland T23 XE10 ,

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