using atlas ti for literature review

Literature Review and Referencing

• First Online: 27 January 2024

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• Ajay Gupta 2  

Part of the book series: Springer Texts in Social Sciences ((STSS))

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ATLAS.ti supports literature review and referencing. It helps researchers coding articles, organize references, extract in-text citations, and identify patterns in published studies on the topic of interest from which the researcher can draw inferences and present their insights. One can perform a literature search and review of multiple documents in chronological or any logical order. Literature review in ATLAS.ti involves three stages: data preparation, import, and conversion. Reference Manager tools are used to generate the files of articles, which are then imported to ATLAS.ti for literature review and referencing. Using the export and import functions, ATLAS.ti imports all the information associated with the data. It then automatically generates document groups and references in the comment sections, which aids data analysis and concept discovery, coding, followed by review, analysis, and reporting. The discussions in this chapter use an example of qualitative content analysis to explain the literature review process in ATLAS.ti, and the steps for reporting references in text, network, and Excel formats.

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Recommended Readings

Phelps, R., Fisher, K., & Ellis, A. (2007). Organizing and managing your research: A practical guide for postgraduates . Sage.

Google Scholar  

Ragin, C. C. (1994). Qualitative comparative analysis. The comparative political economy of the welfare state, 320.

Silverman, D. (2010). Doing qualitative research. Doing qualitative research , 1–100.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: grounded theory procedures and techniques . Newbury Park: Sage Publications.

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Gupta, A. (2023). Literature Review and Referencing. In: Qualitative Methods and Data Analysis Using ATLAS.ti. Springer Texts in Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-49650-9_15

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Published : 27 January 2024

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Master Your Research Projects with the Power of AI

ATLAS.ti bridges human expertise with AI efficiency to provide fast and accurate insights. Communicate directly with your documents and have them automatically coded based on your intentions, providing customized results. Only ATLAS.ti offers complete insight and verifiability of your AI analysis results at all times. This enables you to unpack the black box of AI in your research and uniquely make it your own.

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If you're considering ATLAS.ti for qualitative data analysis, you're making a wise choice. Our top-rated QDA software is perfect for students, researchers, academic institutions, and commercial enterprises – offering a wide array of AI-driven analysis tools to help you succeed. Here are just a few reasons to choose ATLAS.ti:

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Transforming text-based data into valuable insights can be time-consuming. With ATLAS.ti, you can import data from any source and gain deeper insights using AI. In addition, our qualitative data analysis software offers tools to automatically create coded segments in your data and quickly identify themes.

ATLAS.ti's qualitative data analysis tools enable you to organize all your text data (i.e., from customer interviews or focus groups) in one place. This way, you can analyze qualitative data faster than ever. Plus, you can utilize a code hierarchy with a tree structure for better code management.

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Whether you rely on transcripts from focus groups , observation notes, survey responses , or even audio and video files – you can analyze it all with ATLAS.ti. Unlike quantitative data tools, our software supports all major forms of data so that you can conduct qualitative data analysis on any research project, even customer feedback, textual data, pictures, and video recordings.

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• Program agenda

How To Review your Literatures by using ATLAS.ti In 5 Easy Steps

Most projects require a number of steps plus a good dose of perseverance. Even the simplest project requires preparation, know-how and perseverance through several steps for a certain period of time. Setting out to review your literatures for any academic exercise – be it by using the traditional pens-and-papers method, or by using a computer software – is no exception. This article will show you how to use ATLAS.ti software program to review your literatures in a mere five easy steps.

Step 1: Preparation of essentials This will include: (1) Atlas.ti software readily installed on your PC, (2) A number of literatures to be reviewed, and (3) A conducive ‘internal’ and ‘external’ surroundings so that you can concentrate on your review, e.g. a positive mind-setting, a comfy chair, a cup of coffee or a glass of juice etc.

When all the essentials are ready, you can be rest assured that you can begin the review process straightaway.

Step 2: Assign the literature files as ‘Primary Documents’ or ‘P-Docs’ within the Atlas.ti program

Just follow these simple steps: (1) Open ‘P-Docs Manager’ window within the Atlas.ti program, (2) Click on ‘Assign primary documents’ icon and a textbox will appear, (3) Select the literature files that you wish to review, and (4) Click ‘OK’. The textbox will disappear, and the list of literatures will appear in the ‘P-Docs Manager’ window.

By ‘assigning’ literature files into the Atlas.ti program, you simply create ‘links/bridges’ between the literatures and the Atlas.ti program rather than ‘uploading’ the files into Atlas.ti. Uploading causes the Atlas.ti file to be ‘heavy’ and ‘burdensome’ to ‘carry around’, or to be saved into other removable disks.

Perhaps, another important reason for using the ‘assigning’ method is to make it easy for your future use, because, upon assigning the literatures as P-Docs, you will be able to view, review and output the literatures from within the Atlas.ti program itself, without having to open each of the literature files! Wouldn’t that be cool?

Step 3: Think of a number of themes for your review

This can be achieved by thinking what you wish to obtain from the literatures. It can be anything related to your research. For instance, if you’re doing a write-up on ‘Scrapbooking’, the possible themes could be: ‘history’, ‘how to’, ‘resources’, ‘advantages’, ‘disadvantages’, ‘where to publish’ etc. and the list can go as long as you wish. Once you have identified the themes, list each theme (in Atlas.ti, the themes are known as ‘Codes’) in the ‘Code Manager’ … This can be a very critical step. It demands concentration as well as your full attention. Enabling yourself to reach this stage is really a boost to your feeling. Go for it!

Here are more tips to help you with this Step: (1) Open ‘Code Manager’ window within the Atlas.ti program, (2) Click on ‘Create a new item’ icon and a textbox will appear, (3) List all the possible themes/codes, each is separated by the symbol “|”,or alternatively, you can repeat step (1) and (2) (4) Click ‘OK’. The textbox will disappear, and the list of themes/codes will appear in the ‘Code Manager’ window. Congratulations! You did it!

Although this step is significant and should not be missed out, do not worry if you only have one Code in the beginning. You can always add on other Codes along the coding process. Likewise, do not worry, too, if you have too many Codes in the beginning, because along the coding process, you can always delete unnecessary Codes, or merge similar Codes together.

Step 4: Begin the coding process

Coding means: going through the text of the literatures, and identifying which points fall under which Code. When you have identified the points, highlight it by using your cursor, and simply drag the Code from within the ‘Code Manager’ and drop it onto the P-Docs view. Once you have done that, a mark will appear at the right- hand side of the P-Docs view. In Atlas.ti ‘language’, the highlighted portion of the P-Docs is called ‘Quotation’. Bravo! You did it again!

An important point to clarify; Atlas.ti software program does not replace the reading and understanding process. It simply helps to replace the traditional way of highlighting using a highlighter/pen with the computer-clicking. Further, it also replaces the pens-and-papers management of data by making the process computerised. Now you are ready for the next Step.

Step 5: Output the quotation for the Codes

When you are done with coding/reviewing a number of literatures and you feel like you have gathered enough information on a particular theme/Code; then you’re getting ready for your write-up. You can retrieve all the quotations which have been coded earlier into a single text document. This process is called ‘Getting the Output’; which is quite simple really – just about anybody can do it.

This is how it goes: (1) You highlight the code which you wish to output within the ‘Code Manager’, (2) You click at the ‘Output’ and a drop down menu will appear, (3) Simply select ‘Quotations for the Selected Code(s)’, (4) You will be prompted with a textbox, which requires you to choose from: ‘Editor’, ‘Printer’, ‘File’, or ‘File & Run’.

I guess you must be thinking: “Which one should I choose?”

Well, if you wish to edit the output before printing, you may choose ‘Editor’. If you wish to print it straightaway, you may choose ‘Printer’. You may choose ‘File’ if you wish to save the output, or ‘File & Run’ if you wish to save the output and thereafter open the view for the reference of your write-up.

At the end, when you have done the above mentioned Steps, you can relax and enjoy the benefits of your success. You deserve to be pleased with yourself! You set out to attain your goal (that is coding) and you have succeeded! Bravo! You have “climbed the Mountain”! Now you know that you can review your literatures by using the Atlas.ti software program and save all the hassles of the traditional pens-and-papers methods. I am sure you are looking forward to code even more articles.

**** For further information on Atlas.ti, queries or training invitations, please contact us by e-mail at animunirah [at] gmail.com at anytime or phone +60195555084 (Malaysian time is GMT +8).

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22 responses to how to review your literatures by using atlas.ti in 5 easy steps.

hi there.. i accidentally found your blog! it was so crucial that i have to learn the atlas.ti and nvivo by myself and i’ve downloaded the tutorials from atlas.ti webpage..

thanks for the tips!

Dear corrynelson, good for you. In fact, you can download the trial version of Atlas.ti version 6.1.1 from the webpage, and try to navigate around. The tutorials are very useful. Good luck!

Im a newbie…. without any atlas.ti experience. I have attended the Nvivo workshop but I notice that atlas.ti is much easier. I missed Ani Munirah’s workshop so I have to learn how to operate atlas.ti on my own…. so far so gud! Tqvm to Ani Munirah who introduced to me the software last year…

Dr. Othman, I always stress upon the simplicity of ATLAS.ti and try my best to show the simple steps of working with it to my workshop participants 🙂 In fact, I trust you can start working on your own by only referring to the Quick Tour which can be downloaded from the official website. My research partner and I are now translating the same into Malay languagae, which will soon be available. I trust this would benefit most of our Malaysian users.

Gud…. hoping to be the first who get the book. Pls include lots of workout and real life examples…. especially for simple data with interview transcripts, pdfs, docs, movies and sounds…..

First of all, congrats for your winning article!. I wonder if you have some ideas of how to keep track of you reference or bibliographic material of the codes you are using when writing up?? Thanks.

Hi Julio, other people might have their own style of keeping records. As for myself, I manage my references by using the EndNote version X3. I learned from my lecturer Dr. Nadiyah Elias when saving documents, try to keep the file name as {Author, year} in a specific folder. When referring to the very same reference, I just sort in the EndNote according to the author, and I’ll be able to track it.

As for the codes, I learned this tip from my mentor Dr. Susanne Friese to name the codes in the Code Manager of ATLAS.ti according to groups, alternatively to use the Code Family. Please e-mail me personally and I’ll be able to explain more in detail. Thanks.

May I suggest using Mendeley instead of Endnote. The real nice feature of Mendeley is that if you allow it, it can sort all your files into any structure you want. For instance, it can automatically name your files based on an author-year format, which then can be used within Atlas.ti.

Just thought I would mention this excellent feature :).

Dear Dr. Hariri,

Thank you for sharing the information. I do have colleagues using Mendeley, but since I’ve started using EndNote for quite some time and have built quite a decent references database on my area, I would prefer to stick to one reference manager only.

Anyhow, in deciding on which software to use, it is always advisable to look around and choose one which fits most for the particular purpose of the research.

Hello Julio; congratulations! I have two questions. Do you assign the docs as the original files (like maybe they are stored in EndNote) or do you create copies and place them in a single folder?

Dear David, I’m not sure if this question is intended for me, or for Julio. Never mind. I’ll just share my thoughts. I personally create copies of the files and store them in a special folder intended for analysis using ATLAS.ti, the same folder in which I’ll store my HU later. The simple reason for this is because, once the file is assigned as primary document, the ‘link/bridge’ will be facilitated by the files and the HU in the same folder.. In addition, it will be easier for storage and backup purposes.

Thanks for this post.

Please, is Atlas.it useful for engineering literature review ? I just know about it.

Thanks again and have a nice day.

Dear Nabeel, sure. I don’t see any reason why it cannot be used for engineering field.

Many thanks this, I am starting a literature review for my PhD and your post is very helpful. From previous ATLAS.ti experience, I found the software to slow down with image intensive networks, and I am a bit concerned the same may occur when my literature review grows.

Have you implemented or come across any extensive literature reviews in ATLAS.ti i.e. 300 pdf or more?

Thanks from a spring day in Cape Town! Byron

Hi Byron, I have come across a research with more than 300 pdf before. The software should be able to handle it. Further, we are expecting improvements to the version 7 which is due to be released anytime now. If you still experience the problem, can you please contact the support team at http://www.atlasti.com/contacts.html ? hopefully they can help you.

Thanks Ani, I will look into this. Keep well, Byron

Salam Dr Ani, can I know besides it is very useful managing our LR, what else ATLAS.ti could be implemented in doing PhD. Tqvm

Dear aysha, ATLAS.ti is a CAQDA – computer aided qualitative data analysis software, meaning it helps with your analysis of qualitative data – unstructured or structured. It includes primary data (interviews, unstructured survey, observation, field notes, video, audio, etc.) or secondary data (books, journal articles, newspapers, reports, etc.

Simply put, the software helps u to make sense of your data – from the raw data to the reportable format 🙂

Q1: What is the latest atlas software.. is the software free ? Version of ATLAS.ti 7 is free and works without time limit. other atlas software is a trial version. which one is better? Q2: the software helps u to make sense of your data – from the raw data to the reportable format ..can you give example in literiture review case .tq

Q1: The latest ATLAS.ti version is 7. The latest update for the version (as of today) is 7.0.85. It is not a freeware, it is a shareware, you can find the pricing information on the official website http://www.atlasti.com . But you may download the trial @ demo version, which is free and works without time limit. It only limits the number of documents you can analyse, code and quotes you can create, as well as memos and network view you can come up with. Apologies, I am not sure how to respond to “which one is better?”. Comparing between which and which?

Q2: If you follow the steps mentioned in the above blog post, and up until step 5, choosing the Editor will reveal to you the Output of the ‘segments of the literatures’ which you think are relevant for a particular code. Our problem nowadays is that there are too many literatures @ past research to go through. To make it worse, the relevant segment in the literatures is only small e.g. one sentence or one paragraph. The coding and Output features of ATLAS.ti can help us to ‘capture’ these small segments in each of the literatures and send for Output in the format of .Rtf or .Doc. Hope the above assists.

i downloaded and started using it..but only 30 documents can be saved ..perhaps i have to chunck my theme.. piece by piece (not to excide 30 docs) example : 1 File for history , another for advantages etc….what do you think? did you do the same too?

** exceed (typo)

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ATLAS.ti  is a computer program used mostly, but not exclusively, in qualitative research or qualitative data analysis.

The purpose of ATLAS.ti is to help researchers uncover and systematically analyze complex phenomena hidden in unstructured data (text, multimedia, geospatial). The program provides tools that let the user locate, code, and annotate findings in primary data material, to weigh and evaluate their importance, and to visualize the often complex relations between them.

ATLAS.ti is used by researchers and practitioners in a wide variety of fields including anthropology, arts, architecture, communication, criminology, economics, educational sciences, engineering, ethnological studies, management studies, market research, quality management, psychology and sociology.

ATLAS.ti consolidates large volumes of documents and keeps track of all notes, annotations, codes and memos in all fields that require close study and analysis of primary material consisting of text, images, audio, video, and geodata.

In addition, it provides analytical and visualization tools designed to open new interpretative views on the material.

To support multi-method multi-user projects across space and time (longitudinal studies), project data export using XML is available. With XML, the proprietary nature of most software systems can be mitigated. This is indeed a mandatory requirement in scientific settings.

ATLAS.ti’s XML schema ( http://downloads.atlasti.com/atlasti_hu_2.2.xsd ) influenced the development of the QuDEX language ( http://dext.data-archive.ac.uk/schema/schema.asp ) at University of Essex.

In this webinar, you will learn:

• Common problems faced in doing Literature Review
• How ATLAS.ti can address the problems…
• 3 steps of doing Literature Review using ATLAS.ti…
• Q&As on doing Literature Review using ATLAS.ti

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Analysing near-miss incidents in construction: a systematic literature review.

1. Introduction

• Q 1 —Are near-miss events in construction industry the subject of scientific research?
• Q 2 —What methods have been employed thus far to obtain information on near misses and systems for recording incidents in construction companies?
• Q 3 —What methods have been used to analyse the information and figures obtained?
• Q 4 —What are the key aspects of near misses in the construction industry that have been of interest to the researchers?

2. Definition of Near-Miss Events

3. research methodology, 4.1. a statistical analysis of publications, 4.2. methods used to obtain information about near misses, 4.2.1. traditional methods.

• Traditional registration forms
• Computerized systems for the recording of events
• Surveys and interviews

4.2.2. Real-Time Monitoring Systems

• Employee-tracking systems
• Video surveillance systems
• Wearable technology
• Motion sensors

4.3. Methods Used to Analyse the Information and Figures That Have Been Obtained

4.3.1. quantitative and qualitative statistical methods, 4.3.2. analysis using artificial intelligence (ai), 4.3.3. building information modelling, 4.4. key aspects of near-miss investigations in the construction industry, 4.4.1. occupational risk assessment, 4.4.2. causes of hazards in construction, 4.4.3. time series of near misses, 4.4.4. material factors of construction processes, 4.5. a comprehensive overview of the research questions and references on near misses in the construction industry, 5. discussion, 5.1. interest of researchers in near misses in construction (question 1), 5.2. methods used to obtain near-miss information (question 2), 5.3. methods used to analyse the information and data sets (question 3), 5.4. key aspects of near-miss investigations in the construction industry (question 4), 6. conclusions.

• A quantitative analysis of the Q 1 question has revealed a positive trend, namely that there is a growing interest among researchers in studying near misses in construction. The greatest interest in NM topics is observed in the United States of America, China, the United Kingdom, Australia, Hong Kong, and Germany. Additionally, there has been a recent emergence of interest in Poland. The majority of articles are mainly published in journals such as Safety Science (10), Journal of Construction Engineering and Management (8), and Automation in Construction (5);
• The analysis of question Q 2 illustrates that traditional paper-based event registration systems are currently being superseded by advanced IT systems. However, both traditional and advanced systems are subject to the disadvantage of relying on employee-reported data, which introduces a significant degree of uncertainty regarding in the quality of the information provided. A substantial proportion of the data and findings presented in the studies was obtained through surveys and interviews. The implementation of real-time monitoring systems is becoming increasingly prevalent in construction sites. The objective of such systems is to provide immediate alerts in the event of potential hazards, thereby preventing a significant number of near misses. Real-time monitoring systems employ a range of technologies, including ultrasonic technology, radio frequency identification (RFID), inertial measurement units (IMUs), real-time location systems (RTLSs), industrial cameras, wearable technology, motion sensors, and advanced IT technologies, among others;
• The analysis of acquired near-miss data is primarily conducted through the utilisation of quantitative and qualitative statistical methods, as evidenced by the examination of the Q 3 question. In recent years, research utilising artificial intelligence (AI) has made significant advances. The most commonly employed artificial intelligence techniques include text mining, machine learning, and artificial neural networks. The growing deployment of Building Information Modelling (BIM) technology has precipitated a profound transformation in the safety management of construction sites, with the advent of sophisticated tools for the identification and management of hazardous occurrences;
• In response to question Q 4 , the study of near misses in the construction industry has identified several key aspects that have attracted the attention of researchers. These include the utilisation of both quantitative and qualitative methodologies for risk assessment, the analysis of the causes of hazards, the identification of accident precursors through the creation of time series, and the examination of material factors pertaining to construction processes. Researchers are focusing on the utilisation of both databases and advanced technologies, such as real-time location tracking, for the assessment and analysis of occupational risks. Techniques such as Analytic Hierarchy Process (AHP) and clustering facilitate a comprehensive assessment and categorisation of incidents, thereby enabling the identification of patterns and susceptibility to specific types of accidents. Moreover, the impact of a company’s safety climate and organisational culture on the frequency and characteristics of near misses represents a pivotal area of investigation. The findings of this research indicate that effective safety management requires a holistic approach that integrates technology, risk management and safety culture, with the objective of reducing accidents and enhancing overall working conditions on construction sites.

7. Gaps and Future Research Directions, Limitations

• Given the diversity and variability of construction sites and the changing conditions and circumstances of work, it is essential to create homogeneous clusters of near misses and to analyse the phenomena within these clusters. The formation of such clusters may be contingent upon the direct causes of the events in question;
• Given the inherently dynamic nature of construction, it is essential to analyse time series of events that indicate trends in development and safety levels. The numerical characteristics of these trends may be used to construct predictive models for future accidents and near misses;
• The authors have identified potential avenues for future research, which could involve the development of mathematical models using techniques such as linear regression, artificial intelligence, and machine learning. The objective of these models is to predict the probable timing of occupational accidents within defined incident categories, utilising data from near misses. Moreover, efforts are being made to gain access to the hazardous incident recording systems of different construction companies, with a view to facilitating comparison of the resulting data;
• One significant limitation of near-miss research is the lack of an integrated database that encompasses a diverse range of construction sites and construction work. A data resource of this nature would be of immense value for the purpose of conducting comprehensive analyses and formulating effective risk management strategies. This issue can be attributed to two factors: firstly, the reluctance of company managers to share their databases with researchers specialising in risk assessment, and secondly, the reluctance of employees to report near-miss incidents. Such actions may result in adverse consequences for employees, including disciplinary action or negative perceptions from managers. This consequently results in the recording of only a subset of incidents, thereby distorting the true picture of safety on the site.

Author Contributions

Institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Woźniak, Z.; Hoła, B. Analysing Near-Miss Incidents in Construction: A Systematic Literature Review. Appl. Sci. 2024 , 14 , 7260. https://doi.org/10.3390/app14167260

Woźniak Z, Hoła B. Analysing Near-Miss Incidents in Construction: A Systematic Literature Review. Applied Sciences . 2024; 14(16):7260. https://doi.org/10.3390/app14167260

Woźniak, Zuzanna, and Bożena Hoła. 2024. "Analysing Near-Miss Incidents in Construction: A Systematic Literature Review" Applied Sciences 14, no. 16: 7260. https://doi.org/10.3390/app14167260

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• Introduction
• Conclusions
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LMIC indicates low- and- middle-income country; SR, systematic review.

a This review included distinct conclusions about separate conditions and comparators, and so it appears in this map more than once.

eAppendix 1. Search Strategies

eAppendix 2. Excluded Studies

eAppendix 3. Evidence Table

eAppendix 4. Conditions in Previously Published Map in 2018 and Current Map

eReferences.

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Mak S , Allen J , Begashaw M, et al. Use of Massage Therapy for Pain, 2018-2023 : A Systematic Review . JAMA Netw Open. 2024;7(7):e2422259. doi:10.1001/jamanetworkopen.2024.22259

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Use of Massage Therapy for Pain, 2018-2023 : A Systematic Review

• 1 Veterans Health Administration, Greater Los Angeles Healthcare System, Los Angeles, California
• 2 UCLA Fielding School of Public Health, University of California, Los Angeles
• 3 RAND Corporation, Santa Monica, California

Question   What is the certainty or quality of evidence in recent systematic reviews for use of massage therapy for painful adult health conditions?

Findings   This systematic review identified 129 systematic reviews in a search of the literature published since 2018; of these, 41 assessed the certainty or quality of evidence of their conclusions. Overall, 17 systematic reviews regarding 13 health conditions were mapped, and most reviews concluded that the certainty of evidence was low or very low.

Meaning   This study found that despite massage therapy having been the subject of hundreds of randomized clinical trials and dozens of systematic reviews about adult health conditions since 2018, there were few conclusions that had greater than low certainty of evidence.

Importance   Massage therapy is a popular treatment that has been advocated for dozens of painful adult health conditions and has a large evidence base.

Objective   To map systematic reviews, conclusions, and certainty or quality of evidence for outcomes of massage therapy for painful adult health conditions.

Evidence Review   In this systematic review, a computerized search was conducted of PubMed, the Allied and Complementary Medicine Database, the Cumulated Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and Web of Science from 2018 to 2023. Included studies were systematic reviews of massage therapy for pain in adult health conditions that formally rated the certainty, quality, or strength of evidence for conclusions. Studies of sports massage therapy, osteopathy, dry cupping or dry needling, and internal massage therapy (eg, for pelvic floor pain) were ineligible, as were self-administered massage therapy techniques, such as foam rolling. Reviews were categorized as those with at least 1 conclusion rated as high-certainty evidence, at least 1 conclusion rated as moderate-certainty evidence, and all conclusions rated as low- or very low–certainty evidence; a full list of conclusions and certainty of evidence was collected.

Findings   A total of 129 systematic reviews of massage therapy for painful adult health conditions were found; of these, 41 reviews used a formal method to rate certainty or quality of evidence of their conclusions and 17 reviews were mapped, covering 13 health conditions. Across these reviews, no conclusions were rated as high certainty of evidence. There were 7 conclusions that were rated as moderate-certainty evidence; all remaining conclusions were rated as low- or very low–certainty evidence. All conclusions rated as moderate certainty were that massage therapy had a beneficial associations with pain.

Conclusions and Relevance   This study found that despite a large number of randomized clinical trials, systematic reviews of massage therapy for painful adult health conditions rated a minority of conclusions as moderate-certainty evidence and that conclusions with moderate- or high-certainty evidence that massage therapy was superior to other active therapies were rare.

Massage therapy is a popular and widely accepted complementary and integrative health modality for individuals seeking relief from pain. 1 This therapy is the practice of manual assessment and manipulation of the superficial soft tissues of skin, muscle, tendon, ligament, and fascia and the structures that lie within the superficial tissues for therapeutic purpose. 2 Individuals may seek massage therapy to address pain where conventional treatments may not always provide complete relief or may come with potential adverse effects. Massage therapy encompasses a range of techniques, styles, and durations and is intended to be delivered by uniquely trained and credentialed therapists. 3 Original research studies have reported on massage therapy delivered by a wide variety of health care professionals, such as physical therapists, physiotherapists, and nurses. 4 , 5 Despite massage therapy’s popularity and long history in practice, evidence of beneficial outcomes associated with massage therapy remains limited.

The Department of Veterans Affairs (VA) previously produced an evidence map of massage therapy for pain, which included systematic reviews published through 2018. 6 An evidence map is a form of systemic review that assesses a broad field to identify the state of the evidence, gaps in knowledge, and future research needs and that presents results in a user-friendly format, often a visual figure or graph. 7 To categorize this evidence base for use in decision-making by policymakers and practitioners, VA policymakers requested a new evidence map of reviews published since 2018 to answer the question “What is the certainty of evidence in systematic reviews of massage therapy for pain?”

This systematic review is an extension of a study commissioned by the VA. While not a full systematic review, this study nevertheless reports methods and results using the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA ) reporting guideline where applicable and filed the a priori protocol with the VA Evidence Synthesis Program Coordinating Center. Requirements for review and informed consent were waived because the study was designated as not human participants research.

Literature searches were based on searches used for the evidence map of massage therapy completed in 2018. 8 We searched 5 databases for relevant records published from July 2018 to April 2023 using the search terms “massage,” “acupressure,” “shiatsu,” “myofascial release therapy,” “systematic*,” “metaanaly*,” and similar terms. The databases were PubMed, the Allied and Complementary Medicine Database, the Cumulated Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and Web of Science. See eAppendix 1 in Supplement 1 for full search strategies.

Each title was screened independently by 2 authors for relevance (S.M., J.A., and P.G.S.). Abstracts were then reviewed in duplicate, with any discrepancies resolved by group discussion. To be included, abstracts or titles needed to be about efficacy or effectiveness of massage therapy for a painful adult health condition and be a systematic review with more than 1 study about massage therapy. A systematic review was defined as a review that had a documented systematic method for identifying and critically appraising evidence. In general, any therapist-delivered modality described as massage therapy by review authors was considered eligible (eg, tuina, acupressure, auricular acupressure, reflexology, and myofascial release). Sports massage therapy, osteopathy, dry cupping or dry needling, and internal massage therapy (eg, for pelvic floor pain) were ineligible, as were self-administered massage therapy techniques, like foam rolling. Reviews had to be about a painful condition for adults, and we excluded publications in low- and middle-income countries because of differences in resources for usual care or other active treatments for included conditions. Publications were required to compare massage therapy with sham or placebo massage, usual care, or other active therapies. Systematic reviews that covered other interventions were eligible if results for massage therapy were reported separately.

We next restricted eligibility to reviews that used formal methods to assess the certainty (sometimes called strength or quality) of the evidence for conclusions. In general, this meant using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). 9 However, other formal methods were also included, such as the approach used by the US Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) program. To be included, a review had to state or cite the method used and report the certainty (or strength or quality) of evidence for each conclusion. After we applied this restriction, most health conditions had only 1 systematic review meeting the eligibility criteria, and we used this review for the map. Among conditions for which we identified more than 1 review meeting the eligibility criteria, we first assessed whether reviews differed in some other feature used to classify reviews on our map (eg, different comparators or type of massage therapy), which we would label with the appropriate designation (such as vs usual care or reflexology ). If there were multiple reviews about the same condition and they did not differ in some other feature, we selected the systematic review we judged as being most informative for readers. In general, this was the most recent review or the review with the greatest number of included studies.

Data on study condition, number of articles in a review, intervention characteristics, comparators, conclusions, and certainty, quality, or strength of evidence were extracted by 1 reviewer and then verified by a second reviewer (S.M., J.A., and P.G.S.). Our evidence mapping process produced a visual depiction of the evidence for massage therapy, as well as an accompanying narrative with an ancillary figure and table.

The visual depiction or evidence map uses a bubble plot format to display information on 4 dimensions: bubble size, bubble label, x-axis, and y-axis. This allowed us to provide the following types of information about each included systematic review:

Number of articles in systematic review (bubble size): The size of each bubble corresponds to the number of relevant primary research studies included in a systematic review.

Condition (bubble label): Each bubble is labeled with the condition discussed by that systematic review.

Shapes and colors: Intervention characteristics for each condition are presented in the form of colors (type of intervention) and shapes (comparators). For type of intervention, we included nonspecified massage therapy, tuina, myofascial release, reflexology, acupressure, and auricular acupressure. For comparators, we included mixed comparators with subgroups, mixed comparators with no subgroups, sham or placebo, and active therapy or usual care. A condition can appear more than once if multiple systematic reviews included different type of massage therapy or different comparators.

Strength of findings (rows): Each condition is plotted on the map based on the ratings of certainty of evidence statement as reported in the systematic reviews: high, moderate, low, or very low.

Outcome associated with massage therapy (columns): Each condition is plotted in potential benefit or no benefit as the outcome associated with massage therapy. Columns are not mutually exclusive. A review could have more than 1 conclusion, and conclusions could differ in the benefit associated with massage therapy. Both conclusions are included on the map.

Risk of bias is not part of the method of an evidence map. We assessed the quality of included reviews using criteria developed by the U S Preventive Services Task Force (USPSTF). Certainty of evidence as determined by the original authors of the systematic review was abstracted for each conclusion in each systematic review and tabulated.

The search identified 1164 potentially relevant citations. Among 129 full-text articles screened, 41 publications were retained for further review. Of these, 24 reviews were excluded from the map for the following reasons: only 1 primary study about interventions of interest (11 studies), outcomes associated with massage therapy could not be distinguished from other included interventions (5 studies), not an intervention of interest (3 studies), not a comparison of interest (2 studies), overlap with a more recent or larger review that was already included on the map (2 studies), and self-delivered therapy (1 study). We included 17 publications in this map covering 13 health conditions. 4 , 10 - 25 The literature flowchart ( Figure 1 ) summarizes results of the study selection process, and eAppendix 2 in Supplement 1 presents citations for all excluded reviews at full-text screening.

The total number of primary studies about massage therapy for pain in the included reviews ranged from 2 studies to 23 studies. There were 12 reviews that included fewer than 10 primary studies 4 , 11 - 17 , 20 - 23 and 5 reviews that included 10 to 25 studies about massage therapy for pain. 10 , 18 , 19 , 24 , 25 Of included reviews, 3 reviews were completed by the Cochrane Collaboration 4 , 19 , 23 and 2 reviews were completed by the AHRQ EPC program. 11 , 18

We categorized the included 17 reviews by health condition. These categories were cancer-related pain, 15 , 24 back pain (including chronic back pain, 25 chronic low back pain, 18 , 22 and low back pain 17 ), chronic neck pain, 18 fibromyalgia, 21 labor pain, 4 , 19 mechanical neck pain, 13 myofascial pain, 14 palliative care needs, 10 plantar fasciitis, 12 post–breast cancer surgery pain, 16 postcesarean pain, 23 postpartum pain, 20 and postoperative pain. 11

Of 17 included reviews, 3 reviews included more than 1 type of massage therapy and 14 reviews included 1 type of massage therapy. Reviews by Chou et al 11 and Smith et al 16 included acupressure and nonspecified massage therapy as interventions. The review by Candy et al 7 included reflexology and nonspecified massage therapy as interventions. Of the 14 reviews with 1 type of massage therapy, there were 5 reviews describing nonspecified massage therapy, 10 , 14 , 17 , 20 1 review about tuina, 22 5 reviews about myofascial release, 8 , 9 , 12 , 18 , 19 and 3 reviews about acupressure. 13 , 15 , 21

A variety of comparators were included in reviews. Of 9 reviews that included more than 1 comparator in analyses, 4 , 11 , 13 , 14 , 18 - 22 2 reviews did not conduct separate analyses by comparator (labeled mixed with no subgroups ) 13 , 14 and 3 reviews conducted separate analyses by comparator (labeled mixed with subgroups ). 4 , 21 , 22 The other 4 reviews included a mix of comparators with separate conclusions: sham or placebo and active therapy or usual care, 11 mixed with no subgroups and active therapy or usual care, 18 mixed with subgroups and active therapy or usual care, 20 and mixed with no subgroups, sham, and active therapy or usual care. 19 There were 8 reviews that included 1 comparator only in their analyses, 10 , 12 , 15 - 17 , 23 - 25 with 7 reviews that described interventions compared with active therapy or usual care only, 10 , 12 , 15 , 17 , 23 - 25 while 1 review limited inclusion to primary studies with a sham or placebo comparator. 16

There was substantial variation in the reporting of other details from primary studies in included reviews. Any study that did not specify the mode of delivery was included; studies that explicitly stated that massage therapy was self-delivered were excluded. Of the 17 included reviews, 5 reviews provided details of personnel who administered the therapy, including massage therapist, nurse, aromatherapist, physiotherapist, and reflexologist. 4 , 10 , 19 - 21 A total of 7 reviews presented length of sessions (eg, 5-minute or 90-minute sessions for massage therapy studies and 30-second or 5-minute sessions for acupressure studies). 10 , 16 , 18 , 20 - 23 With the exception of the review by He et al, 15 all reviews reported details about frequency, duration, or both when available. A total of 9 reviews included information about frequency of sessions (eg, 1 session or once every 3 weeks for massage therapy studies and 4 times per day or daily for acupressure studies), 10 , 12 , 16 - 18 , 20 - 23 and 9 reviews reported duration of sessions (eg, single session or 3 months). 10 - 12 , 16 - 18 , 20 , 22 , 23 There were 7 reviews that included details about follow-up (eg, 1 week or 12 months). 10 , 13 , 17 , 18 , 21 , 23 , 25

Using USPSTF criteria to rate the quality of included reviews, 10 reviews were rated good 4 , 10 , 11 , 14 - 16 , 18 , 19 , 21 , 23 and 7 reviews were rated fair. 12 , 13 , 17 , 20 , 22 , 24 , 25 See eAppendix 3 in Supplement 1 for each review’s rating.

Figure 2 is a visual depiction of the following types of information about each included systematic review: condition, types of comparison treatments (shapes), types of massage therapy (color), number of articles included for each conclusion (bubble size), outcomes associated with massage therapy for pain (columns), and certainty of evidence rating (rows). There were 6 reviews mapped more than once, reflecting primary studies describing more than 1 health condition, 18 more than 1 type of massage therapy, 10 , 20 or outcomes associated with massage therapy compared with different comparators. 11 , 17 - 19 There were 7 conditions from reviews 14 , 16 - 19 , 21 , 22 that reported 1 conclusion rated as moderate-certainty evidence, all of which concluded that massage therapy was associated with beneficial outcomes for pain ( Table 1 ). However, most other conditions had conclusions rated as low- or very low–certainty evidence (12 reviews about 10 conditions 4 , 10 - 13 , 15 , 17 - 20 , 23 - 25 ). This rating means “Our confidence in the effect estimate is limited. The true effect may be substantially different from the estimate of effect,” or “We have very little confidence in the effect estimate.” See eAppendix 3 in Supplement 1 for conclusions in all reviews. This map included 4 conditions that did not appear in the 2018 map, 12 , 16 , 20 , 23 and there were 8 conditions in the 2018 map that did not have new reviews meeting eligibility criteria (mainly a formal grading of the certainty of evidence); 7 health conditions 10 , 11 , 13 - 15 , 17 , 18 , 21 , 22 , 24 , 25 were included in the 2018 map and the new map (see details in eAppendix 4 in Supplement 1 ).

Evidence about adverse events was collected by approximately half of included reviews, and no serious adverse events were reported. While 11 of 17 reviews 10 , 11 , 13 , 15 , 17 - 19 , 22 - 25 described adverse events, 2 reviews 18 , 23 included certainty of evidence conclusions for adverse events for 3 health conditions ( Table 2 ).

There is a large literature of original randomized clinical trials and systematic reviews of randomized clinical trials of massage therapy as a treatment for pain. Our systematic review found that despite this literature, there were only a few conditions for which authors of systematic reviews concluded that there was at least moderate-certainty evidence regarding health outcomes associated with massage therapy and pain. Most reviews reported low- or very low–certainty evidence. Although adverse events associated with massage therapy for pain were rare, the evidence was limited. For reviews that had conclusions about adverse events, authors were uncertain if there was a difference between groups or did not find a difference between groups and rated the evidence low to very low certainty of evidence.

Massage therapy is a broad term that is inclusive of many styles and techniques. We applied exclusion criteria determined a priori to help identify publications for inclusion in the evidence map. Despite that procedure, there was still a lack of clarity in determining what massage therapy is. For instance, acupressure was sometimes considered acupuncture and other times considered massage therapy, depending on author definition. In this case, we reviewed and included only publications that were explicitly labeled acupressure and did not review publications about acupuncture only. This highlights a fundamental issue with examining the evidence base of massage therapy for pain when there is ambiguity in defining what is considered massage therapy.

Unlike a pharmaceutical placebo, sham massage therapy may not be truly inactive. It is conceivable that even the light touch or touch with no clear criterion 26 used in sham massage therapy may be associated with some positive outcomes, meaning that patients who receive the massage therapy intervention and those who receive a sham massage therapy could both demonstrate some degree of symptom improvement. Limitations of sham comparators raise the question of whether sham or placebo treatment is an appropriate comparison group in massage therapy trials. It may be more informative to compare massage therapy with other treatments that are accessible and whose benefits are known so that any added beneficial outcomes associated with massage therapy could be better isolated and understood.

Compared with the 2018 map, our map included 4 new conditions not on the 2018 map, while 8 conditions from the 2018 map had no new reviews meeting eligibility criteria and 7 health conditions appeared in both maps. Despite identifying new conditions and conclusions with higher certainty of evidence in several reviews in our updated search, most included reviews reported low or very low certainty of evidence, suggesting that the most critical research need is for better evidence to increase certainty of evidence for massage therapy for pain. This is a challenge given that massage, like other complementary and integrative health interventions, does not have the historical research infrastructure that most health professions have. 27 Nevertheless, it is only when systematic reviews and meta-analyses are conducted with high-quality primary studies that the association or lack of association of massage therapy with pain will reach higher certainties of evidence. Studies comparing massage therapy with placebo or sham are probably not the priority; rather, the priority should be studies comparing massage therapy with other recommended, accepted, and active therapies for pain. Studies comparing massage therapy with other recommended therapies should also have a sufficiently long follow-up to allow any nonspecific outcomes (eg, those associated with receiving some new treatment) to dissipate. For example, this period has been proposed to be at least 6 months for studies of chronic pain.

There are 2 main limitations to this systematic review’s evidence map. The first, common to all systematic reviews, is that we may not have identified all potentially eligible evidence. If a systematic review was published in a journal not indexed in any of 5 databases we searched and we did not identify it as part of our search of references of included publications, then we would have missed it. Nevertheless, our search strategy identified more than 200 publications about massage therapy for pain published since July 2018, so we did not lack potential reviews to evaluate. The second limitation of evidence maps is that we did not independently evaluate the source evidence; in other words, we took conclusions of authors of the systematic review at face value. That is the nature of an evidence map. Particular to this application of the mapping process, we mapped the review we deemed most informative for the 2 health conditions that had more than 1 eligible review (back pain and labor pain). This necessarily requires judgment, and others could disagree with that judgment. We included the citation for reviews excluded from the map for this overlap reason in supplemental material, and interested readers can review it for additional information. As in all evidence-based products and particularly in 1 such as this covering a large and complex evidence base, it is possible that there are errors of data extraction and compilation. We used dual review to minimize the chance of such errors, but if we are notified of errors, we will correct them.

Although this systematic review found that the number of conclusions about the effectiveness of massage therapy that were judged to have at least moderate certainty of evidence was greater now than in 2018, it was still small relative to the need. More high-quality randomized clinical trials are needed to provide a stronger evidence base to assess the effect of massage therapy on pain. For painful conditions that do not have at least moderate-certainty evidence supporting use of massage therapy, new studies that address limitations of existing research are needed. The field of massage therapy would be best advanced by educating the wider research community with clearer definitions of massage therapy and whether it is appropriate to include multiple modalities in the same systematic review.

Accepted for Publication: May 15, 2024.

Published: July 15, 2024. doi:10.1001/jamanetworkopen.2024.22259

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Mak S et al. JAMA Network Open .

Corresponding Author: Selene Mak, PhD, MPH, Veterans Health Administration, Greater Los Angeles Healthcare System, 11301 Wilshire Blvd, Los Angeles, CA 90073 ( [email protected] ).

Author Contributions: Drs Mak and Shekelle had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Mak, Miake-Lye, Shekelle.

Acquisition, analysis, or interpretation of data: Mak, Allen, Begashaw, Beroes-Severin, De Vries, Lawson, Shekelle.

Drafting of the manuscript: Mak, Allen, Begashaw, Beroes-Severin, De Vries, Lawson, Shekelle.

Critical review of the manuscript for important intellectual content: Mak, Miake-Lye, Shekelle.

Statistical analysis: Allen.

Obtained funding: Shekelle.

Administrative, technical, or material support: Begashaw, Miake-Lye, Beroes-Severin, De Vries, Lawson.

Supervision: Mak, Shekelle.

Conflict of Interest Disclosures: None reported.

Funding/Support: Funding was provided by the Department of Veterans Affairs Health Services Research and Development.

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

Data Sharing Statement: See Supplement 2 .

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MIT researchers release a repository of AI risks

Which specific risks should a person, company or government consider when using an AI system, or crafting rules to govern its use? It’s not an easy question to answer. If it’s an AI with control over critical infrastructure, there’s the obvious risk to human safety. But what about an AI designed to score exams, sort resumes or verify travel documents at immigration control? Those each carry their own, categorically different risks, albeit risks no less severe.

In crafting laws to regulate AI, like the EU AI Act or California’s SB 1047 , policymakers have struggled to come to a consensus on which risks the laws should cover. To help provide a guidepost for them, as well as for stakeholders across the AI industry and academia, MIT researchers have developed what they’re calling an AI “risk repository” — a sort of database of AI risks.

“This is an attempt to rigorously curate and analyze AI risks into a publicly accessible, comprehensive, extensible and categorized risk database that anyone can copy and use, and that will be kept up to date over time,” Peter Slattery, a researcher at MIT’s FutureTech group and lead on the AI risk repository project, told TechCrunch. “We created it now because we needed it for our project, and had realized that many others needed it, too.”

Slattery says that the AI risk repository, which includes over 700 AI risks grouped by causal factors (e.g. intentionality), domains (e.g. discrimination) and subdomains (e.g. disinformation and cyberattacks), was born out of a desire to understand the overlaps and disconnects in AI safety research. Other risk frameworks exist. But they cover only a fraction of the risks identified in the repository, Slattery says, and these omissions could have major consequences for AI development, usage and policymaking.

“People may assume there is a consensus on AI risks, but our findings suggest otherwise,” Slattery added. “We found that the average frameworks mentioned just 34% of the 23 risk subdomains we identified, and nearly a quarter covered less than 20%. No document or overview mentioned all 23 risk subdomains, and the most comprehensive covered only 70%. When the literature is this fragmented, we shouldn’t assume that we are all on the same page about these risks.”

To build the repository, the MIT researchers worked with colleagues at the University of Queensland, the nonprofit Future of Life Institute, KU Leuven and AI startup Harmony Intelligence to scour academic databases and retrieve thousands of documents relating to AI risk evaluations.

The researchers found that the third-party frameworks they canvassed mentioned certain risks more often than others. For example, over 70% of the frameworks included the privacy and security implications of AI, whereas only 44% covered misinformation. And while over 50% discussed the forms of discrimination and misrepresentation that AI could perpetuate, only 12% talked about “pollution of the information ecosystem” — i.e. the increasing volume of AI-generated spam.

“A takeaway for researchers and policymakers, and anyone working with risks, is that this database could provide a foundation to build on when doing more specific work,” Slattery said. “Before this, people like us had two choices. They could invest significant time to review the scattered literature to develop a comprehensive overview, or they could use a limited number of existing frameworks, which might miss relevant risks. Now they have a more comprehensive database, so our repository will hopefully save time and increase oversight.”

But will anyone use it? It’s true that AI regulation around the world today is at best a hodgepodge: a spectrum of different approaches disunified in their goals. Had an AI risk repository like MIT’s existed before, would it have changed anything? Could it have? That’s tough to say.

Another fair question to ask is whether simply being aligned on the risks that AI poses is enough to spur moves toward competently regulating it. Many safety evaluations for AI systems have significant limitations , and a database of risks won’t necessarily solve that problem.

The MIT researchers plan to try, though. Neil Thompson, head of the FutureTech lab, tells TechCrunch that the group plans in its next phase of research to use the repository to evaluate how well different AI risks are being addressed.

“Our repository will help us in the next step of our research, when we will be evaluating how well different risks are being addressed,” Thompson said. “We plan to use this to identify shortcomings in organizational responses. For instance, if everyone focuses on one type of risk while overlooking others of similar importance, that’s something we should notice and address.

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Investigating experiences of stigma and its impact on substance use recovery among residents of recovery residences in the United States: A scoping review protocol. BSGH020

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The objective of this scoping review is to systematically review the literature on stigma experienced by residents in recovery residences and its impact on substance use recovery outcomes. The review will use the PRISMA-ScR framework to identify studies focused on stigma and recovery in recovery residences published in English within the United States since 2000, including qualitative, quantitative, and mixed-methods studies. Data will be extracted and analyzed thematically to identify gaps in the literature and inform future research and policy development. Preliminary findings suggest that stigma, including labeling and discrimination, significantly hinders recovery by promoting secrecy and withdrawal among residents. Proximity to recovery residences has been shown to reduce community stigma, indicating the potential for better integration and acceptance. This study aims to provide a comprehensive understanding of stigma in recovery residences, its effects on substance use recovery, and recommendations for creating supportive recovery environments. The significance of this study lies in its potential to inform policy, practice, and research, highlighting the need for stigma reduction to improve recovery outcomes in recovery residences. By addressing gaps in the literature, the findings will contribute to developing more effective interventions and supportive environments for individuals recovering from substance use.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

The author(s) received no specific funding for this work.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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No datasets were generated or analyzed during the current study.

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