Authors’ responses (AR)

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AR: A de-identified data set can be shared against a reasonable request and research plan. Correspondence can be addressed to the first author.

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AR: Please see the above response.

Please update your Data Availability statement in the submission form accordingly.

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

AR: Changed as requested.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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 #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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

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Reviewer #1: Yes

Reviewer #2: Yes

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

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Reviewer #1: Yes

Reviewer #2: Yes

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5. 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 #1: Summary

This manuscript investigates the association between patient-reported outcome measures (PROMs) and objectively measured upper-extremity activity using triaxial accelerometry in older adults following proximal humeral fracture. The study is based on a secondary analysis of data from two randomized controlled trials and addresses an important methodological question regarding outcome assessment in musculoskeletal research.

The manuscript is clearly written, the methods are largely transparent, and the analyses are appropriately cautious in reporting uncertainty. The finding of weak and imprecise associations between PROMs and accelerometer-based activity is consistent with prior literature in other orthopedic populations and is of interest from a measurement and outcomes-research perspective.

AR: We thank you for the positive comments.

However, several methodological issues—particularly regarding selection bias, construct validity of accelerometer thresholds, heterogeneity of the study population, and statistical power—need to be more explicitly addressed. Given PLOS One’s emphasis on scientific validity rather than perceived impact, the manuscript would benefit from improved transparency and more conservative interpretation of results.

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Major Comments

1. Selection Bias and Data Availability

o Accelerometer data were collected at only two participating centers, although the parent trials were multicenter.

o The manuscript does not provide a comparison between patients included in this secondary analysis and those without accelerometer data.

Recommendation:

Provide a comparison of baseline characteristics between included and non-included patients or clearly discuss the potential for selection bias and its implications for generalizability.

AR: We thank you for your very insightful comment. In the supplementary data, we now assess which variables are associated with a study's inclusion using logistic regression. We also compared baseline variables between included and non-included patients.

2. Clinical and Methodological Heterogeneity

o The cohort includes multiple fracture types (2-, 3-, and 4-part), different treatment strategies (nonoperative, plate fixation, hemiarthroplasty), and participants from two trials with distinct interventions.

o While multivariable adjustment was performed, the modest sample size (n = 96) limits the robustness of these models.

Recommendation:

Explicitly discuss the implications of heterogeneity and limited statistical power. Consider clarifying that the analyses are exploratory in nature.

AR: First paragraph in the discussion is edited as follows: “Based on our analyses, PROMs have, at best, a weak and uncertain association with objectively measured upper extremity activity. Given the heterogeneity of recovery patterns and the limited statistical power for detecting modest associations, these analyses should be interpreted as exploratory.”

3. Validity of Accelerometer Thresholds

o No validated cut-offs exist for categorizing upper-arm accelerometer data in patients with shoulder pathology.

o The applied thresholds were derived from wrist-worn accelerometers in populations that differ from the present cohort.

Recommendation:

Emphasize this limitation more clearly and avoid framing accelerometer-based activity as a definitive measure of functional recovery.

AR: We have rewritten the conclusion and it includes a statement as follows: “Accelerometer-based activity measurement does not appear to provide a turnkey solution for assessing recovery, but rather offers one additional dimension that requires careful interpretation. Its role should be clarified through studies that incorporate longitudinal measurements, define clinically meaningful thresholds, and link objective activity to patient-centered outcomes.”

4. Interpretation of Accelerometer-Based Activity

o Accelerometers measure movement quantity rather than task-specific function, movement quality, or shoulder-specific performance.

o Compensatory movements and passive arm swing cannot be distinguished from purposeful shoulder use.

Recommendation:

Clarify that accelerometer-based measurements represent one dimension of recovery and should be interpreted as complementary to PROMs rather than as a replacement.

AR: We have combined this with the above-mentioned aspects and also added: “Although PROMs are based on specific questions, their weak correlation with objectively measured activity levels suggests that additional instruments may complement PROMs when evaluating different dimensions of recovery”.

5. Timing and Duration of Measurements

o Activity was measured only at a single time point (12 months) and over a short period (four days).

o This limits insight into longitudinal recovery patterns and may be influenced by behavioral modification during monitoring.

Recommendation:

Explicitly acknowledge these limitations and restrict conclusions to the measured time frame.

AR: In the limitations we added: “Activity was measured at a single time point (12 months) over a short monitoring period of four days, which limits the ability to capture longitudinal recovery patterns or habitual activity over longer periods. The present findings are restricted to the association between PROMs and objectively measured activity at 12 months and should not be extrapolated to earlier phases of recovery or to long-term activity patterns”

6. Framing of Conclusions

o The conclusion suggests that PROMs may not reflect “actual functional activity.”

o Given the limitations of both PROMs and accelerometry, this statement may be too strong.

Recommendation:

Reframe conclusions to emphasize weak association and conceptual differences between measurement modalities, consistent with PLOS One’s emphasis on methodological validity rather than clinical inference.

AR: We have now rewritten the conclusion paragraph avoiding too strong statements.

Minor Comments

1. Statistical Reporting

o Clarify whether regression assumptions were formally assessed.

AR: We investigated QQ-plots for our analyses and these are now provided in the Supplement.

o Consider reporting standardized regression coefficients to facilitate interpretation.

AR: We initially considered ordinal and linear regression for the main analyses and preferred the latter due to the interpretability of the regression coefficients. Hence, we prefer the current reporting as they are coefficients with units.

2. Terminology

o Use consistent terminology to distinguish between physical activity, functional capacity, and functional performance.

AR: We thank you for this comment. We have now, e.g., omitted the term “functional activity” and used “physical activity” instead. Function is now related to PROMs.

3. Figures and Tables

o Scatterplots or correlation plots could improve transparency by visualizing the data underlying regression analyses.

AR: Crude values for the activity and outcome variable are now shown in the plots.

o Table captions could more clearly explain the clinical meaning of reported β values.

AR: Other reviewer also commented on this, and the table legends have been edited.

4. Language and Style

o Minor editing would improve readability by reducing repetition and sentence length in the Discussion.

AR: We have made several changes to the discussion, and hopefully, it has improved readability.

Reviewer #2: Thank you for letting me review this article that explores the association between direct functional activity measured with an accelerometer and PROMs.

Below are my remarks on the manuscript:

- Table 1 missing. I would appreciate a casual table that displays the patient characteristics. I know that you wrote some demographics in the text but it is important to really see the demographics of the investigated patient cohort.

AR: Yes of course, to enhance transparency. Table 1 is now provided

- A Flowchart displaying the patient inclusion would be helpful. You explain it in the text but it is more helpful to see it displayed in a figure, how many patients were included from both original studies and how many are i.e. lost for follow up.

AR: Flowchart has been added

- Please standardize the numbers in the tables to a defined amount of decimal numbers (i.e. 2-3.). Especially in Table 3 this would be very helpful.

AR: Corrected as suggested

- You mention Figure 2 but further explanation, what 2A and 2B represents, is missing. Overall, I prefer bar-charts over pie-charts... this could also display the standard deviation. I leave it up to you, if you would like to change the style of presentation, but I would suggest it...

AR: Pie chart is replaced with bar plot.

-Why was smoking status included in the univariate analysis? Does it affect the activity of the arm in any way? I mean, we are not talking about wound healing problems but functionality, therefore i dont really understand the reason.

AR: This was actually an error which we apologize. Smoking was not included in the model

- I do not really understand the Tables well enough. I understand that you did a univariate analysis on the association of the activity of the injured arm with different PROMs and two different cutoff definitions. But I cant really wrap my head around the (un)adjusted beta which that displays the change in DASH when the activity level is increased by 100 minutes. So each patient has a certain amount of time in different activity levels and then check if the DASH is better if more time is spent in higher activity? And what specifically is the adjusted beta for activity? I think this requires a little more explanation for the reader to understand properly.

AR: We have now thoroughly revised the Table legends.

- I think, another limitation might be that the patients might be especially careful with the injured arm if a sensor is attached to it which will later be analyzed by a doctor. I can imagine that they are especially careful, so the doctor does not think, they are doing "too much"...

AR: We thank you for the comment. This is a probable source of bias, similar to Hawthorne effect. We have added many changes to the discussion and decided to leave this undiscussed.

- Generally, one of the main problems is that thresholds are not validated for the upper extremity. But I like your approach with taking both/all of the known one and comparing them.

AR: This is indeed a problem, which is, of course, a problem very hard to mitigate.

- I would appreciate 1-2 sentences discussing the objective vs. subjective outcomes/outcome measures for the patient. I personally think that it is important for the patient to be happy and have a good feeling about the overall outcome because he/she has to live with it. Objective outcome parameter are also necessary but should they overrule the subjective feeling of the patient?

AR: This is a very important aspect. We added a sentence to the fourth discussion paragraph. “While objective measures are essential for standardised assessment, treatment decisions must ultimately reflect patient-perceived recovery and quality of life, as these determine the lived impact of the outcome.”

Thank you very much for your work.

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6. PL

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