>PONE-D-24-31136>>Prevalence of Symptom Exaggeration Among North American Independent Medical Evaluation Examinees: A systematic review of observational studies>>PLOS ONE

Dear Dr. Busse,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Thank you for your submission. I read it with enthusiasm, as it shows notable merits. Nevertheless, I noticed some concerns that I'd like the authors to address. As follows:

1) Please double-check grammar (e.g. punctuation and verb tense)

2) Please double-check refs (e.g. keep the requested style, Vancouver, and also correct formatting, punctuation and remove repetitives)

3) The Abstract is well-structured, but could benefit from conciseness. The inclusion of multiple phrases, such as "symptom exaggeration" and "observational studies," makes it somewhat repetitive. I'd suggest reducing redundant terms to improve readability;

- The logical transitions between the background, methods, and results are somewhat abrupt. For instance, it's unclear how the analysis of "symptom exaggeration" directly links to "inter-rater reliability" or whether the gender-specific findings are derived from a subset analysis or the primary outcomes. Please provide a clearer link between the methodological approach and the primary research question;

- The stats parameters (e.g. p-values, effect sizes, CIs) are provided, but more detail on the significance of these values will enhance the depth of the findings. For example, how do these rates of symptom exaggeration in IMEs impact policy, clinical practice, or future research directions? Offering these insights would broaden the reliability;

- Sample size details are provided, but the inclusion of additional information, such as variations across cohorts or specific diagnostic categories, would be useful. For instance, were patients with traumatic brain injuries or chronic pain assessed differently? This would offer a clearer understanding of subgroup analysis and generalisation;

- A brief explanation of whether the studies had high or low certainty is important;

- The abstract briefly touches on gender differences, but would benefit from elaborating on why women show higher rates of symptom exaggeration in these studies. Consider a brief sentence;

- The findings could be expanded to include more specific quantitative details, such as the range of exaggeration percentages across the cohorts or any significant moderators or predictors found in the meta-analysis;

- The conclusion is concise but could be expanded to include a brief part on how symptom exaggeration influences clinical decision-making during IMEs. Additionally, mentioning how these findings could influence future research or policy changes is essential;

- The abstract would be improved by providing the main strengths, such as prevalence rates for symptom exaggeration or differences in exaggeration across different conditions;

- The term "symptom exaggeration" is mentioned without any clear definition. Please elaborate;

4) The transition between the background on disabilities and the introduction of IMEs feels somewhat confusing. Providing a smoother transition into how symptom exaggeration affects IMEs will improve your argument;

- There are relevant stats about disabilities in North America, which effectively establishes the context. However, there is a need for a more explicit link between this background information and the objective. For example, while the IME process is mentioned, the transition to the issue of symptom exaggeration is quite abrupt

5) The Introduction touches on symptom exaggeration as a factor affecting IME outcomes. Nevertheless, there is the need to state how the authors would measure it or what variables will be examined (e.g. mental health, pain severity).

6) Explicitly state how your study addresses gaps or contradictions found in previous studies. For example, why past standardisation efforts failed. More emphasis on the relevance and novelty of the study is essential;

7) While the IME concept and symptom exaggeration are introduced, there is little detail about the methodology or variables that will be assessed;

- Please articulate your hypotheses with the rationale;

- To improve flow, consider adding a sentence explaining why IMEs are prone to variability, and how symptom exaggeration may influence;

- Summarise the objectives and hypotheses clearly in one sentence;

8) Overall, there are some worrying aspects in Introduction:

- The Introduction needs a clearer flow. Consider providing the background and context of IMEs, then move into the issue of symptom exaggeration. After that, it's important to debate what previous studies have found and highlight their gaps. You can then explain how this study will ease those. Concluding with the rationale, objectives, and hypotheses will give the Introduction a strong structure. Consider to mention why the study is important since it'll make more engaging and relevant for a broader audience;

- The text shifts abruptly between topics, like disability stats and symptom exaggeration, without clearly connecting them or stating the rationale. Brief mentioning the methods used to measure symptom exaggeration is really important;

- The authors could provide more context to strengthen their argument. IMEs often focus too narrowly on the biomedical model, overlooking psychosocial factors and work-related conditions, which influences the fairness and consistency of evaluations. The lack of standardisation and unified guidelines contributes to these issues. Additionally, biases in IME practices, such as favouring employer-provided information over patient accounts, lead to underdiagnosis and lower disability ratings compared to treating physicians. This bias fosters distrust and adds to the inconsistencies in the IME process. For more details, see 10.1097/PEC.0000000000000487 and 10.1007/978-3-319-71906-1;

- Another aspect contributing to IME variability is the difference in approaches, prognoses, and standards among evaluators. Studies show that diagnostic discordance rates can exceed 80%, with higher discordance linked to increased mortality (OR ≈ 1.2), underscoring the need for standardised protocols. Inconsistent assessments can lead to delayed treatment, denied disability benefits, and declining patient quality of life. Standardisation would improve accuracy and consistency, reducing patient burden and enhancing trust in IMEs. Furthermore, the focus on the biomedical model overlooks the role of psychological and social factors, suggesting that adopting a biopsychosocial approach could yield more accurate evaluations;

- The Introduction mentions IMEs and symptom exaggeration, but it fails to clearly state the objectives or what the study aims to explore. Providing specific objectives and hypotheses would make it easier for readers to understand the focus of the research;

- Explain how the variability in IME outcomes could be influenced by symptom exaggeration, tying it to the broader context of disability assessments;

- Strengthen the rationale by incorporating previous findings on symptom exaggeration in IMEs;

- The study focuses on symptom exaggeration as a source of variability in IMEs, an underexplored area. While past findings checked the reliability of IMEs, this work could provide important insights on how symptom exaggeration influences assessments of disability. Please consider providing a clearer explanation of why this is relevant;

- Providing more context on how symptom exaggeration might vary by condition is important; for example, variations in symptom exaggeration between conditions like traumatic brain injury and chronic pain will make the argument more cohese;

- Please clarify the relevance of the European results - what are the similarities or differences between IME in continents? And expand this part. Consider that healthcare systems are different, especially due to different geographical frameworks;

- I'd highly suggest to to introduce the concept of symptom exaggeration within the context of the study;

The Introduction is brief and lacks depth to establish a clear framework. Without the mentioned components, the Introduction feels underdeveloped and won't effectively set ground for the study. This can make the interpretation challenging without a solid rationale of the study;

9) Overall comments on Methods:

- The details about PRISMA and MOOSE are not provided. For example, the authors didn't report the refs for each checklist, and also didn't specify what workflow (e.g. screening, extraction, etc.) was followed. Including detailed information from both checklists, such as principal items, would enhance the presentation. The overall impression is, "How did the authors follow these guidelines?" Finally, why wasn't the systematic review registered on PROSPERO, the widely recommended registry for such studies?;

- The search strategy, while reported in the Sup. file, could be included in the main text to enhance clarity and robustness;

- Why include studies in other languages? Are the terms and interpretations the same across different contexts?;

- Please refine the verb tense for consistency;

- Several aspects of the design require clarification, particularly concerning the definitions, variable selection, and operationalisation. There is also a lack of explanation for the focus on specific countries. The justification for study exclusions, and the criteria for classifying symptom exaggeration could be detailed. Additionally, the handling of population overlap needs to be explained. Furthermore, if six authors conducted the screening, how was inter-rater reliability assessed? Failing to address these concerns risks making the study appear biased and unreliable;

- The eligibility criteria lack a clear rationale for including certain types of studies while excluding others. For instance, the inclusion of studies that "assessed the prevalence of symptom exaggeration using a known group design or multi-modal determination method" seems arbitrary without explaining these specific designs (c.f. 10.1212/CPJ.0000000000000092; and why they are superior or necessary for the systematic review. Please elaborate on why these aspects were chosen;

- If there is no reliable and valid standard for assessing symptoms, it's somewhat concerning to understand the reliability of the categorisation of the quality of the included studies. Actually, some studies report strategies for a reliable assessment of symptom exaggeration. Consider mentioning symptom validity tests. I think providing a detailed assessment criterion or more than one tool would be important (c.f. 10.1002/nur.10092). Consider using the Cochrane risk of bias or other tools (c.f. 10.1136/bmj.d5928; 10.1016/j.acn.2005.02.002). Also, explain how the authors ensured the reliability of the findings and what kind of psychometric assessments were performed (c.f. 10.1007/s12207-021-09436-8; 10.1016/j.acn.2005.02.002);

- The preference for including studies with larger sample size when population overlap exists introduces a potential for selection bias. Larger sample sizes do not always equate to better quality for meta-analysis. It'd be interesting to refer to relevant literature on this matter (e.g. 10.1002/sim.1186; 10.1136/bmj.d7762). I'd highly suggeest conducting robust sensitivity analyses to assess the influence of including or not certain studies (c.f. 10.1016/j.jclinepi.2004.01.<wbr style="color: rgb(34, 34, 34); font-family: Arial, Helvetica, sans-serif; font-size: small;" />018; 10.1111/rssc.12440);

10) Overall comments on Results:

- The authors could consider some approaches: a. run both fixed- and random-effects and scrutinise if there are substantial differences in the effects (i.e. if found, heterogeneity would be a really worrying aspect), b. identify studies with a high risk of bias, or small sample, remove them, and conduct sensitivity analysis (e.g. using l-o-o or cumulative sensitivity analysis). Then check the results, specifically evaluating the existence of differences in effects, CIs overlap, and changes in I² values. This would also be important when analysing subgroups;

- While beyond-chance scores are rare, they can still provide valuable insights into clinical findings (c.f. 10.1016/j.spinee.2004.11.016; 10.1186/s12874-016-0108-4). For instance, some studies have employed complementary approaches to assess symptom exaggeration (c.f. 10.1097/00001199-200004000-<wbr style="color: rgb(34, 34, 34); font-family: Arial, Helvetica, sans-serif; font-size: small;" />00006; 10.1007/BF01874896); Please elaborate;

- In studies where symptom exaggeration is being evaluated, the lack of blinding could significantly influence the results. Therefore, I would highly encourage the authors to expand this part;

- The databases used in the search are comprehensive. However, expanding the search to include other databases, such as Scopus, could ensure that no additional relevant refs are missed. Could the authors clarify why Scopus or similar databases were not included in the search strategy?;

- Additionally, more details regarding the filters applied during the search would be essential. For instance, were specific study designs or types prioritised during the screening process, and if so, which ones?;

- As recommended by Cochrane, systematic reviews should be updated to maintain their relevance and accuracy. Could the authors provide an approximate timeline for when they plan to refresh the search;

- How were duplicates handled during the search process?

- The search strategy is well-constructed and covers several important terms across databases. However, there are some concerning aspects. The use of broad terms such as 'validity' and 'disability' may result in many extraneous results, diminishing the relevance of the retrieved studies and also increasing the overall screening effort. Additionally, applying filters (e.g. specific diagnostic criteria or populations) could help enhance the reliability and focus on more relevant studies. Please clarify the rationale for not using such refinements;

- Please clarify the relevance of the transformation using F-T arcsine in your study. This is really important based on your design. The concern is to provide an explanation of parameters and the rational, enhancing clarity for readers outside the field;

- The trim-and-fill method could provide a more accurate adjustment for potential bias. Overall, after assessing any asymmetry in the funnel plot, this trims and fills missing data points to 'reach' symmetry, recalculating the overall effect size. Could the authors consider applying this approach and debating the influence on their analysis?;

- Please consider expanding the analyses by assessing Tau² (i.e. between-study variance), which could provide better insights into heterogeneity (c.f. 10.1136/bmj.327.7414.557);

- When conducting stats analyses (e.g. meta-regression, subgroup analyses), it’s essential to be cautious of small-study effects, which can influence the robustness of your findings;

- The Results are intriguing. However, the observed high variability and low certainty, as well as the association between women and higher symptom exaggeration, raise concerns about potential confounding factors. Differences in populations, diagnostic tools, and study designs likely contribute to this variability. The authors are encouraged to explore these issues more thoroughly, perhaps expanding the meta-regression to include more DVs for multivariate analysis. Consider additional approaches like structural equation modeling to reduce the number of variables, along with PCA and clustering. This would enhance the depth of your analyses, results, and overall presentation;

- Please specify test parameters (e.g. effect sizes, confidence intervals) alongside p-values for a more comprehensive understanding of the results;

- Ensure consistency in decimal places throughout the results section;

- The CIs for symptom exaggeration in women should be carefully examined, as overlapping CIs could indicate heterogeneity or residual variance;

- Given these shortcomings, I suggest the authors: a) Check for studies with small samples or wide CIs and identify possible outliers, b) Carefully consider the influence of outliers and residuals, c) Reporting I² and Tau² stats to assess heterogeneity. If heterogeneity is high, outliers could be driving the variation between studies;

11) The Discussion is well-structured but lacks conciseness, particularly in the “Relation to Other Studies” and “Implications for Future Research” sections. Streamlining these parts would enhance clarity and flow;

- While the study finds low-certainty evidence of symptom exaggeration in IMEs, the authors didn't provide sufficient arguments about what drives this low certainty. The sources of uncertainty (e.g., inconsistency, bias, imprecision) could be more clearly outlined. Also, consider debating the influence of heterogeneity;

- Some examples of how different studies operationalised symptom exaggeration differently and how this could be 'solved' seem a very interesting approach;

- Suggest practical steps for developing and validating new assessment tools for IMEs;

- Additionally, scrutinise CIs more carefully for potential overlap, as this could indicate heterogeneity;

- There is a concerning aspect regarding the connection to other findings.The arguments lack depth and focus mainly on 'correlation' with somatic symptoms, which may not fully align with IMEs or the study's objectives. Clarify the main differences between studies, focussing on the authors. The link between gender and symptom exaggeration could be simplified, and the data more sharply refined;

- Please provide a detailed explanation of how the multimethod approaches varied across studies and how the differences may have influenced the outcomes of the meta-analysis;

- The limitations are mentioned, but other biases, such as cultural or healthcare factors, could be potential confounders. Also, the lack of standardization and the absence of reliable assessments should be addressed;

- The link between Results and the Discussion could be clearer. Highlighting specific findings from the results, such as effect sizes or CIs, would enhance the reliability and make the conclusions more solid;

- The terminology distinguishing symptom exaggeration from malingering is unclear. Please clarify this distinction;

12) Tables and illustrations:

- The search strategy appears to include terms that may retrieve numerous irrelevant studies. The authors could consider refining the search by removing broad terms and avoiding overuse of wildcards. This can reduce the retrieval of unnecessary results and save future researchers from conducting an excessively lengthy and unfocused search. For example, terms like "independent" and linked terms such as "MMPI" and "work capacity" could be refined or excluded to enhance specificity. In using the current strategy, I encountered studies from adjacent fields, such as business or diagnostics for conditions unrelated to the focus of the review;

- The risk of bias Table lacks clarity and cohesion, as the studies are not organized alphabetically or by any discernible pattern, making it hard to follow. The use of consecutive sampling raises concerns about potential selection bias, which could influence the outcomes and, consequently, generalisation. Additionally, the 5% cutoff for missing data, though comprehensive, should be supported by relevant evidence to justify. While age and education are important demographics, it's unclear why other variables, such as gender, were not included. Expanding the demographic could provide a more comprehensive understanding of their influence on the findings;

- The Table on psychometric data raises concerns as it presents tests used in completely different settings, likely increasing heterogeneity. The variability in sample sizes, demographics, and the use of unreliable tools diminishes the potential for generalisation of the findings. Additionally, there are several outdated refs that should be updated to reflect current practices. Lastly, please double-check the grammar, as there are issues with punctuation and formatting that need correction;

- It's essential to note that the funnel plot is asymmetric, indicating heterogeneity. This reinforces the importance of using the trim-and-fill method to ensure robustness. The authors could also check carefully the sensitivity analysis and assess how the funnel looks after refinement. At a glance, there seem to be small-study effects, given the number of studies on left side;

- The graph on meta-regression exhibits dispersion and variability that isn't related to demographics (i.e. as indicated by the regression line). Please implement additional metrics like CIs or residuals for clarity and include important stats like the p-values, I², and other important metrics;

- The Table on study characteristics is missing important variables, like the ratio or percentage of women, including incorrect reporting (e.g. sampling being 'unclear'), and utilises confusing criteria for assessing symptom exaggeration. Please consider restructuring the Table to enhance clarity;

Overall, this is a well-conducted study, and I commend the endeavour. The findings presented are of notable importance. While this might sound lengthy, it is provided with the best intentions, aiming to align with the high standards expected in scientific communication.

While I found this study to be promising and well-conceived, I believe its current state may require extensive rounds, which could complicate the review process. To help streamline, I’ve provided some suggestions for the authors to consider. I encourage the authors to consider or check these and choose how they wish to proceed. Should they choose to resubmit after corrections, I'd be happy to read the ms again. I apologise if this isn’t the most positive news, but I see great potential in this work.

==============================

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Thiago P. Fernandes, PhD

Academic Editor

PLOS ONE

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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>PONE-D-24-31136R1>>Prevalence of Symptom Exaggeration Among North American Independent Medical Evaluation Examinees: A systematic review of observational studies>>PLOS ONE

Dear Dr. Busse,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Thank you for your valuable submission.

That said, there are two main concerns in this round.

Before all, I’d like to mention that I read with enthusiasm and think the study has merits to reach a broad audience. This is the main - and most important - aspect to consider in this lengthy round. As noticed while re-reading (and as pointed out by the reviewer), many of the previously raised concerns remain unaddressed.

It appears that certain important adjustments were not fully considered. The reviewer's comments highlight the need for a more detailed rebuttal, particularly clarifying and addressing all the raised concerns. Although lengthy rounds are not common at this point, I trust that with continued effort, the ms has potential and can be refined to meet the required standards.

I understand this is not the best news, but in its current form, the ms cannot proceed. The concerns raised require considerable adjustments and further work. If the authors are willing to address these issues, I would be happy to reassess the ms after the necessary changes are made.

==============================

Please submit your revised manuscript by Apr 05 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Thiago P. Fernandes, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

>Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.>

Reviewer #2: (No Response)

Reviewer #3: (No Response)

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>2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. >

Reviewer #2: Partly

Reviewer #3: Yes

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>3. Has the statistical analysis been performed appropriately and rigorously? >

Reviewer #2: Yes

Reviewer #3: Yes

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>4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.>

Reviewer #2: No

Reviewer #3: Yes

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>5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #2: Yes

Reviewer #3: Yes

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>6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)>

Reviewer #2: The current manuscript is a revision about the prevalence of symptom exaggeration among IME examinees. I did not review the initial version of this manuscript, but reviewed the revision. I have checked my comments with the initial review comments, please see below.

Major:

Symptom overreporting may have multiple causes (see Merckelbach et al., 2019). Symptom exaggeration due to external incentives is related to malingering. Your reply to point 64 states: "We noticed that most studies use the terms interchangeably and often label their criteria as criteria to assess malingering. However, when using the term malingering one presumes intent. Thus we felt it was an important suggestion to note in our discussion that considering how ‘clinicians are, understandably and appropriately, hesitant to assign a label of malingering…. (45)’ the term symptom exaggeration may be a more appropriate replacement." Indeed, malingering equals symptom overreporting, but symptom overreporting does not necessarily mean malingering. In the context of IME, malingering might be more obvious to use for the manuscript, though in clinical practice one should not always assume but rather take malingering into account.

Both the introduction and discussion are very short, relating to the point 29 raised in the previous round. In my opinion, these comments are not sufficiently dealt with. Also the transitions between different topics within the Introduction and Discussion could be improved.

It is stated that French and Spanish studies were included to reduce language bias, but what about culture bias? You state this later on, but this is something that could be taken into account at an earlier level.

Risk of bias assessment: also relating to point 36> why were no tools used to assess risk of bias? E.g., Cochrane's? Also, what was the measure of agreement (e.g., Kappa)? The selection seems very subjective.

Table 2: what do the levels of inconsistency mean, especially 'serious inconsistency'? How does this relate to your conclusions?

It is concluded that the review found no evidence for differences in the prevalence of symptom exaggeration based on clinical condition, but most patients among studies eligible for our review presented with either mild TBI or chronic pain'. This was not a (preregistered) research question, and how to conclude this based on only two clinical conditions? Other clinical diagnoses might have symptom exaggeration, but are not included in the current review.

Minor:

Some reasoning errors in conclusions; if women report higher rates of symptom exaggeration, then it is logically that studies that included more women show higher raters.

There are still some punctuation errors (extra comma use, delete space) throughout the manuscript. At times the phrasing (e.g., p.23 line 72 ('Such concerns...) could be improved.

For research transparency, what were the exact key words? I know they are stated in supplemental materials and that the apparently take 3 pages to explain, but I do believe these could be stated clearly in the manuscript.

Reviewer #3: Dear authors of the article, I want to thank you for a well-prepared article.

The undoubted advantages of the article are:

The text of the article is logically structured and understandable to the reader. The language meets the level and requirements of the scientific language. The article uses modern data analysis, adequate to the purpose of the study. The research is of high importance for science and practice. The authors openly and adequately note in the article limitations, implications for future research and practice.

I certainly recommend this article for publication in the journal, but I have some questions and recommendations for improvement.:

1. why were only these databases CINAHL, EMBASE, MEDLINE and PsycINFO used for analysis?

2. In the discussion section, it is necessary to go beyond America and compare scientific data with other countries and continents

3. At the end of the paragraph "Eligible studies", clarify what does "large sample size" mean (what is the sample size in numbers)?

4. In the paragraph "We rated confidence in the reference standard as either..." describe in more detail (if possible, give examples) what ‘weak’, ‘moderate’ or ‘strong’ mean?

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Reviewer #2: Yes:  Sanne Houben

Reviewer #3: Yes:  Olga Terekhina

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Prevalence of Symptom Exaggeration Among North American Independent Medical Evaluation Examinees: A systematic review of observational studies

PONE-D-24-31136R2

Dear Dr. Busse,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Reviewers' comments:

Reviewer's Responses to Questions

>Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.>

Reviewer #3: All comments have been addressed

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. >

Reviewer #3: Yes

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>3. Has the statistical analysis been performed appropriately and rigorously? >

Reviewer #3: Yes

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.>

Reviewer #3: Yes

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Reviewer #3: Yes

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Reviewer #3: The authors correctly and competently provided answers to all questions and comments, specifying in detail the corrections that were made to the text. The authors have done a lot of work in the process of preparing the article. The article turned out to be interesting for the professional community and has theoretical and practical significance.The authors openly and adequately note in the article limitations, implications for future research and practice. I certainly recommend this article for publication in the journal

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Reviewer #3: Yes:  Olga Terekhina

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