Development of a scale for the evaluation of the quality of the shared decision process in multiple sclerosis patients

Elena Álvarez-Rodríguez; César Manuel Sánchez-Franco; María José Pérez-Haro; Laura Bello-Otero; Marta Aguado-Valcarcel; Inés González-Suárez

doi:10.1371/journal.pone.0268125

Peer Review History

Original SubmissionDecember 15, 2021
25 Jan 2022 Decision Letter - Fatih Özden, Editor PONE-D-21-39578Development of a scale for the evaluation of the quality of the shared decision process in multiple sclerosis patients.PLOS ONE Dear Dr. Suárez, 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. Please submit your revised manuscript by Mar 10 2022 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. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. 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, Fatih Özden, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf. 2. Please amend your current ethics statement to address the following concerns: a) Did participants provide their written or verbal informed consent to participate in this study? b) If consent was verbal, please explain i) why written consent was not obtained, ii) how you documented participant consent, and iii) whether the ethics committees/IRB approved this consent procedure. 3. We note you have included a table to which you do not refer in the text of your manuscript. Please ensure that you refer to Table 1 in your text; if accepted, production will need this reference to link the reader to the Table. 4. Please upload a copy of Supporting Information S1 File. XLS file. which you refer to in your text on page 6. 5. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments: Dear Authors, The reviewers now completed their reviews. Both three reviewers has indicated their good comments on the manuscript, however two of them requested minor revisions. Please carefully fulfill these comment, then submit it again. Please also provide a response to their comments with a separate form. King Regards [Note: HTML markup is below. Please do not edit.] 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 Reviewer #3: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ****** 3. 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 #1: Yes Reviewer #2: Yes Reviewer #3: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ****** 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: I have read your article and it is fantastic!. I have just minor or may be technical errors you need to address. Otherwise the article is good to go for me. 1) You mentioned that you used PCA to select the factor structure. Are there other clustering methods you could have used to achieve thesame/similar results? 2) You mentioned you used Leave-One Item out Cross-validation (i.e. you deleted one item out, and re-examine their alpha value), which may be biased as the model was trained/built using the entire data. To avoid this kind of bias, one will have to do a Leave-one-out cross-validation (Leave one person out of the model) and refit the model with that person included, and check whether or not the alpha value changes. If the change in the alpha value with and without this person is too drastic, then the model is unstable with respect to the selected items. In that case, one will need to redefine the factor structure or use limited factors. This is what I call model validation. Therefore, in addition to the leave-one item out approach, that evluates the consistency of the factor structure, I will like the authors to do leave-one out validation (leave-one person out of the model) and refit their model with the 4 identified scales. You can then plot the observed alpha versus the predicted alpha to see how well the model agrees. This will guarantee that an already validated scale is applicable to Spanish cohort. Unless otherwise, please provide concrete details why this sort of analysis cannot be done. I am statisfied with the current results, and the achieve value of alpha =0.88. Reviewer #2: A sound manuscript with a very thorough methodological context on a very particular and extremely important subject. In addition it provides extremely detailed data on the aspects that were investigated and consequently a solid indication of the patient's perspective on matters that may influence his/her reality Reviewer #3: In the manuscript, the authors validate a decision-making scale in the Spanish language. New therapeutic options available for the treatment of MS –even if more effective and easier to administer– may pose increased risks of severe side effects. Taking this into account, involvement of PwMS in the treatment decision-making process becomes even more imperative. The work seems very solid to me, although the number of patients recruited is small. Only in the discussion, I think it is necessary to mention other decision-making scales validated in Spanish, such as the Control Preference Scale, and explain the advantages of using the scale evaluated in this manuscript. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Valery Fuh-Ngwa Reviewer #2: Yes:** Dimitrios Kitsos Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0268125.r001
Revision 1
3 Mar 2022 Author Response You mentioned that you used PCA to select the factor structure. Are there other clustering methods you could have used to achieve the same/similar results? Yes, indeed. We could have used non metric multidimensional scaling and cluster analysis for ordinal data, for instance. Non metric multidimensional scaling is a statistical methodology used to visualize high dimen- sional and complicated data sets in few dimensions (preferably in two). The goodness of the fit is made through the stress parameter. Stress could be described as a value showing the difference between the distance in the reduced dimension in comparison to the complete dimensional space. Stress values greater than 20 are considered as a poor dimension selection, values between 10 and 20, reasonable, between 5 and 10, good, between 2.5 and 5, excellent and between 0 and 2.5, perfect. The principal goal of cluster analysis for ordinal data is to classify the observations in groups, in the way that, the categorical observations in one group are most similar to each other and the differences between the groups are the most different as possible. This technique can be used as dimensional reduction as it is able to describe the hidden structure of the objects. Nevertheless, to perform principal components analysis was for us a priority because this statis- tical tool is able to rank the dimensions/components based on the amount of variance explained by the data and we want to explain the maximum amount of information by the new selected dimensions. V ar(P C1) > V ar(P C2) > ... > V ar(P CN ) Where N are the number of original variables and PC are the principal components. 2. You mentioned you used Leave-One Item out Cross-validation (i.e. you deleted one item out, and re-examine their alpha value), which may be biased as the model was trained/built using the entire data. To avoid this kind of bias, one will have to do a Leave-one-out cross-validation (Leave one person out of the model) and refit the model with that person included, and check whether or not the alpha value changes. If the change in the alpha value with and without this person is too drastic, then the model is unstable with respect to the selected items. In that case, one will need to redefine the factor structure or use limited factors. This is what I call model validation. Therefore, in addition to the leave-one item out approach, that evluates the consistency of the factor structure, I will like the authors to do leave-one out validation (leave-one person out of the model) and refit their model with the 4 identified scales. You can then plot the observed alpha versus the predicted alpha to see how well the model agrees. This will guarantee that an already validated scale is applicable to Spanish cohort. Unless otherwise, please provide concrete details why this sort of analysis cannot be done. I am statisfied with the current results, and the achieve value of alpha =0.88. Cronbach’s alpha coefficients using the whole sample N = 203 are presented in the table 1. Where raw alpha is the alpha that we would obtain if we deleted the item itself. (Leave-One Item out Cross-validation). The global value of raw alpha is 0.88. And for each factor, using the whole sample: • SatisfactionSDM The overall Cronbach’s alpha is 0.874. • AdverseEffectsDMT The overall Cronbach’s alpha is 0.925. InfoReliability The overall Cronbach’s alpha is 0.873. DMTConvenience The overall Cronbach’s alpha is 0.625. If we perform leave one (person) out cross validation, the resulted alpha’s for each subset (N-1) are plotted in figure 1. Where the solid lines are the expected alpha values and the dotted lines the observed for each dimension, as well as for the overall alpha, when all the items are included. As we can see the observed alpha values are quite stable and they are in agreement with the expected values. Reviewer #3 The work seems very solid to me, although the number of patients recruited is small. Only in the discussion, I think it is necessary to mention other decision-making scales validated in Spanish, such as the Control Preference Scale, and explain the advantages of using the scale evaluated in this manuscript. Other scales are now mentioned and the main differences with prior scales have been highlighted. Our scale is unique in evaluating satisfaction with the information obtained during the process itself and offers an improvement opportunity for physicians and in their relationship with patients. Attachments Attachment Submitted filename: Respuestas.pdf https://doi.org/10.1371/journal.pone.0268125.r002
25 Apr 2022 Decision Letter - Fatih Özden, Editor Development of a scale for the evaluation of the quality of the shared decision process in multiple sclerosis patients. PONE-D-21-39578R1 Dear Dr. Suárez, 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. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Fatih Özden, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): 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 #1: All comments have been addressed Reviewer #4: All comments have been addressed ******** 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 #1: Yes Reviewer #4: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #4: Yes ****** 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 #1: Yes Reviewer #4: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #4: Yes ****** 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 #1: Excellent work! I am very statisfied with the current results following the Leave-one-person Out cross-validation. Both the observed and expected alpha seems very reasonable to me. Great job there! Reviewer #4: Authors well answered to all comments. Statistical analyses wer well performed and the paper was clear and well written. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes:** Valery Fuh-Ngwa Reviewer #4: No https://doi.org/10.1371/journal.pone.0268125.r003
Formally Accepted
6 May 2022 Acceptance Letter - Fatih Özden, Editor PONE-D-21-39578R1 Development of a scale for the evaluation of the quality of the shared decision process in multiple sclerosis patients. Dear Dr. Suárez: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Fatih Özden Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0268125.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .