Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study

Lara J. Mentink; Jana Thomas; René J. F. Melis; Marcel G. M. Olde Rikkert; Sebastiaan Overeem; Jurgen A. H. R. Claassen

doi:10.1371/journal.pone.0237622

Peer Review History

Original SubmissionJuly 27, 2020
15 Sep 2020 Decision Letter - Henrik Oster, Editor PONE-D-20-23329 Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study PLOS ONE Dear Dr. Mentink, 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. - Provide more details on sleep architecture (SWA, delta power etc.). - Figure legends and methods need more details. - Provide a power analysis calculation to justify the small sample size. Please submit your revised manuscript by Oct 30 2020 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: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Henrik Oster, Ph.D. Academic Editor PLOS ONE Additional Editor Comments: n/a 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 provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information. If you are reporting a retrospective study of medical records or archived samples, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical records used in research, please include this information. Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”). For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research. 3. Thank you for stating in your Funding Statement: "This study was funded in parts by the ISAO grant (Internationale Stichting Alzheimer Onderzoek, grant number: 15040). Philips kindly provided the home-EEG devices that were used in this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." Please provide an amended statement that declares all the funding or sources of support (whether external or internal to your organization) received during this study, as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now. Please also include the statement “There was no additional external funding received for this study.” in your updated Funding Statement. Please include your amended Funding Statement within your cover letter. We will change the online submission form on your behalf. 4. Thank you for stating the following in the Financial Disclosure section: "This study was funded in parts by the ISAO grant (Internationale Stichting Alzheimer Onderzoek, grant number: 15040). Philips kindly provided the home-EEG devices that were used in this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." We note that you received funding from a commercial source: Philips Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc. Within this Competing Interests Statement, please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared. Please include your amended Competing Interests Statement within your cover letter. We will change the online submission form on your behalf. Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests 5. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. [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: Partly Reviewer #2: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: 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 ****** 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 ****** 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: Alzheimer’s disease is characterized by an accumulation of amyloid-ß in the brain. It is supposed that clearance of amyloid-ß by the glymphatic system occurs during sleep. It has been shown that disruption of deep sleep led to an increase in amyloid-ß concentration in cerebrospinal fluid. Sleep disruption has been associated with an increased risk for developing Alzheimer’s disease. Earlier studies showed that long-time shift-working pilots with sleep disruption did not show evidence of early Alzheimer’s disease. To explain this finding, the authors hypothesized two mechanisms (1) pilots had increased efficiency in generating deep sleep (DST) during workweek (model 1) and (2) pilots experienced high rebound sleep during rest week (model 2). The authors analyzed data from the SCHIP study dataset from 10 pilots (age 51.6 +/- 2.4 years) with an employment time of 18.4 +/- 3.9 years. The authors applied the Pittsburgh Sleep Quality Index (PSQI) to determine subjective sleep quality of pilots in both workweeks and rest weeks. Objective sleep characteristics were measured by home-EEG devices used by the pilots on 10 workdays and 10 rest days. Results showed that pilots had poorer subjective sleep quality in workweeks than in rest weeks (8.2 vs. 3.9 scores, p<0.001). Average DST per day was shorter in workweeks than in rest weeks (58.3 min vs. 65.9 min, p = 0.19). Average DST% per day was longer in workweeks compared to rest weeks (21.9 vs. 18.4, p = 0.08). Multilevel model analysis, testing model 1 and model 2, indicates that increased efficiency in generating deep sleep during workweeks seems more likely a compensatory mechanism than rebound sleep in rest weeks. This is an interesting study, but there are some concerns to be addressed. The main concern refers to the small size of participants (N = 10). Thus, the large difference in “DST per day” between workweeks (58.3 min) and rest weeks (65.9 min) was not statistically significant. Effect size and statistical power should be given. Shiftwork: It would be helpful if the authors could give more information on the shift work times of the 10 pilots for the 10 days of EEG data collection. Also, it would be interesting to know whether the shiftwork of the 10 pilots was primarily characterized by sleep deprivation or by sleep disruption. This might be of interest for the discussion of the findings. Measurement of sleep quality: Page 5, lines 116-117: The authors wrote that the PSQI was completed on a workweek and on a rest week. It would be fine to inform whether the PSQI was completed at the end of the workweek and the rest week. Normally, the PSQI refers to a time period of four weeks. Home-EEG measurements: - Page 6, lines 122-123: The authors wrote that some pilots wore the EEG-device during two periods of work days and rest days. Please clarify the number of these pilots. Did the authors compare the results of both periods? - Table 1: “Employment time” means years of shift work? Please clarify. - Page 8, lines 175-177: The authors found that pilots had poorer subjective sleep quality (PSQI score) in workweeks than in rest weeks. It would be of interest to know whether the difference in PSQI score was due to differences in sleep onset latency and/or sleep duration between workweeks and rest weeks. Table 2 shows the PSQI score, but does not include sleep duration and sleep-onset latency. The TST in Table 2 refers to EEG measurements, if I correctly understand. Reviewer #2: The current manuscripts reports findings from a study that sought to test whether long-time shift workers (maritime pilots) compensated for shift related sleep loss by increasing the efficiency of deep sleep during work week sleep sessions or by rebound sleep during the rest week. The results suggest that the pilots have a small increase (that only reached an alpha level of 0.08) in the percent of deep sleep totals (%DST) during the workweek compared to the rest week. However, the pilots acquired significantly less total sleep time and deep sleep time during the work week compared to the rest week. When the data are compared via two computational models to test which may represent a compensatory mechanism for sleep loss (the work vs rest week sleep), the authors concluded that increased efficiency in deep sleep during the work week is more likely represents the compensatory mechanisms. While the findings are interesting in that they support the classic model that the amount of sleep/sleep efficiency is directly proportional to the time spent awake in prior to sleep, there are some concerns with the study and data presentation. 1. The authors use a novel home EEG monitoring system. It is unclear how well this system can detect Slow Wave Activity (a measure of deep sleep efficiency i.e. delta power) compared to traditional polysomnographic recordings. It would be very useful to the reader if they provided more detailed information concerning delta power and/or a spectral analysis of sleep under the two conditions. 2. The figure legends would benefit from more detail. What are the -days the workweek? are these consecutive? how does the model handle missing days? it appears that several participants do not have a values after day 2, 3, or 4. 3. While the authors acknowledge that the sample size is small (n=10). There is no mention of a power analysis calculation that would provide the reader information about the sample size actually required to reach a power of at least .8 ****** 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: No Reviewer #2: 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.0237622.r001
Revision 1
14 Oct 2020 Author Response We thank the reviewers for their time to review our manuscript and for their useful suggestions. Please find our point-by-point response to the reviewer comments below. Reviewer #1: Alzheimer’s disease is characterized by an accumulation of amyloid-ß in the brain. It is supposed that clearance of amyloid-ß by the glymphatic system occurs during sleep. It has been shown that disruption of deep sleep led to an increase in amyloid-ß concentration in cerebrospinal fluid. Sleep disruption has been associated with an increased risk for developing Alzheimer’s disease. Earlier studies showed that long-time shift-working pilots with sleep disruption did not show evidence of early Alzheimer’s disease. To explain this finding, the authors hypothesized two mechanisms (1) pilots had increased efficiency in generating deep sleep (DST) during workweek (model 1) and (2) pilots experienced high rebound sleep during rest week (model 2). The authors analysed data from the SCHIP study dataset from 10 pilots (age 51.6 +/- 2.4 years) with an employment time of 18.4 +/- 3.9 years. The authors applied the Pittsburgh Sleep Quality Index (PSQI) to determine subjective sleep quality of pilots in both workweeks and rest weeks. Objective sleep characteristics were measured by home-EEG devices used by the pilots on 10 workdays and 10 rest days. Results showed that pilots had poorer subjective sleep quality in workweeks than in rest weeks (8.2 vs. 3.9 scores, p<0.001). Average DST per day was shorter in workweeks than in rest weeks (58.3 min vs. 65.9 min, p = 0.19). Average DST% per day was longer in workweeks compared to rest weeks (21.9 vs. 18.4, p = 0.08). Multilevel model analysis, testing model 1 and model 2, indicates that increased efficiency in generating deep sleep during workweeks seems more likely a compensatory mechanism than rebound sleep in rest weeks. This is an interesting study, but there are some concerns to be addressed. Major comments: 1. The main concern refers to the small size of participants (N = 10). Thus, the large difference in “DST per day” between workweeks (58.3 min) and rest weeks (65.9 min) was not statistically significant. Effect size and statistical power should be given. Response: We would like to thank the reviewer for the positive remarks. For the SCHIP study, we included a unique cohort of maritime pilots with prolonged and consistent sleep disruption due to their work, making this a highly valuable population that allowed us to explore sleep as an isolated variable in relation to Alzheimer’s Disease. This research is a secondary analysis of the SCHIP study, where we were limited to the maritime pilot group in the Netherlands who agreed to participate in that extensive study. As a consequence, the sample size for the current study was fixed. We agree that the present study is limited by the small sample size and that the true power of the study – would we have been able to calculate it in advance for this specific purpose – would have been likely low. However, post-hoc observed power is not informative about the true power and post-hoc power calculations should therefore be refrained from (see http://daniellakens.blogspot.com/2014/12/observed-power-and-what-to-do-if-your.html). As our finding was non-significant, the observed power of the study will also have been low, because “reporting post-hoc power is nothing more than reporting the p-value in a different way” (see blog post from Daniel Lakens: http://daniellakens.blogspot.com/2014/12/observed-power-and-what-to-do-if-your.html). As for the reporting of the effect size of DST per day, we calculated a point estimate of 0.41 (z-score/√n; 1.31/√10), which qualifies as moderate. However, taking into consideration the standard error of the point estimation, the true effect may be considerably bigger or smaller. Future studies are needed, which can use the current effect size and other considerations to design a study that can provide more definitive answers about the hypothesis that our findings suggest. In our study, we were cautious in presenting our results, based on the small sample size, throughout the whole manuscript. We have now extended our limitation section regarding the small sample size on page 14, lines 276-279, or see section below: The study is limited by the small sample size (n=10), which has impacted the statistical power of our results. However, the sample size was fixed, as this report pertains to a secondary analysis of the SCHIP study, where we were limited to the maritime pilot group in the Netherlands who agreed to participate in that extensive study [21]. 2. Shiftwork: It would be helpful if the authors could give more information on the shift work times of the 10 pilots for the 10 days of EEG data collection. Also, it would be interesting to know whether the shiftwork of the 10 pilots was primarily characterized by sleep deprivation or by sleep disruption. This might be of interest for the discussion of the findings. Response: We agree it would be interesting to have that information. Unfortunately, we do not have specific information about the individual shift work times. The shifts of maritime pilots are highly dependent on the amount and kind of ships that arrive. During the workweek, maritime pilots work on a rotating schedule, i.e., once the maritime pilots are called to work and finished a trip/shift, they end up on the bottom of the list. They will be called to duty again determined by the rotating schedule, however, it is also dependent on the timing and the kind of ships that arrive. Therefore, the shifts are very random and exact shift work times cannot be predicted or received afterwards. However, all pilots follow this work scheme, thus shift work hours are consistent within the group. The shift work of the maritime pilots is furthermore characterized by a combination of sleep deprivation (missing a full night of sleep due to work), sleep restriction (a shorter night of sleep), and sleep fragmentation (short sleep periods interrupted by calls to work). We agreed to use the umbrella term ‘sleep disruption’ throughout the whole manuscript to refer to their unique sleep schedules. The sleep disruption of the maritime pilots therefore, cannot be broken down into specific disturbances like sleep loss or deprivation, but is rather a mixture of different aspects. We have now further clarified this in the methods section on page 5, lines 105-109, or see section below. Working these shifts mostly results in fragmented sleep divided over multiple sleep sessions per day (24 hours). Sleep disruption in this cohort is defined as a combination of sleep deprivation (missing a full night of sleep due to work), sleep restriction (a shorter night of sleep), and sleep fragmentation (short sleep periods interrupted by calls to work). Detailed information about the maritime pilots and in-/exclusion criteria can be found in the SCHIP methods paper [21]. 3. Measurement of sleep quality: Page 5, lines 116-117: The authors wrote that the PSQI was completed on a workweek and on a rest week. It would be fine to inform whether the PSQI was completed at the end of the workweek and the rest week. Normally, the PSQI refers to a time period of four weeks. Response: This is indeed a good point. The PSQI was not completed at a certain time point in a workweek or rest week. Rather, participants received the instruction to fill out the PSQI twice at the same time, once with regard to their estimated scores over the workweeks in the past month and once with regard to their estimated scores over their rest weeks during the past month. We adjusted the section about the PSQI in the manuscript on page 6, lines 119-121, or see section below: Participants received the instruction to fill out the PSQI twice, once with regard to their estimated scores over the workweeks in the past month and once with regard to their estimated scores over their rest weeks during the past month. 4. Home-EEG measurements: Page 6, lines 122-123: The authors wrote that some pilots wore the EEG-device during two periods of work days and rest days. Please clarify the number of these pilots. Did the authors compare the results of both periods? Response: In total, 10 participants wore the EEG-device, of whom 7 participants wore the device for two periods and 1 participant for three periods of a workweek following a rest week. We did not compare the results of these periods within a participant, because this comparison was not informative to our research question. Our multilevel models however took this fact of multiple measurement periods per participant into account through the implementation of a three- rather than a two level hierarchical model. We clarified the number of pilots who wore the EEG-device during multiple periods of a workweek following a rest week in the manuscript on page 6, lines 126-128, or see below: In total, ten participants wore the home-EEG device. Seven participants wore the device during two periods and one participant during three periods of a workweek following a rest week. 5. Table 1: “Employment time” means years of shift work? Please clarify. Response: Yes, that is correct, the employment time means the years of shift work. We have clarified this in Table 1. 6. Page 8, lines 175-177: The authors found that pilots had poorer subjective sleep quality (PSQI score) in workweeks than in rest weeks. It would be of interest to know whether the difference in PSQI score was due to differences in sleep onset latency and/or sleep duration between workweeks and rest weeks. Table 2 shows the PSQI score, but does not include sleep duration and sleep-onset latency. The TST in Table 2 refers to EEG measurements, if I correctly understand. Response: Indeed, the TST in table 2 refers to the home-EEG measurements, we altered Table 2 to clarify this. Concerning the PSQI subcomponents, this is a very interesting remark. We looked at the subcomponents of the PSQI and found that the difference between the PSQI scores concerning workweeks and rest weeks was due to most factors and not just the difference in sleep onset latency and/or sleep duration. We saw significant differences concerning sleep quality (p=0.001), sleep onset latency (p=0.025), sleep duration (p=0.001), sleep efficiency (p<0.001) and daily dysfunction (p=0.025). We added the subcomponents of the PSQI to Table 2 (page 10) and adjusted the section about the PSQI in the manuscript on page 9, lines 185-186, or see section below: The difference resulted from multiple subcomponents of the PSQI (Table 2). Reviewer #2: The current manuscripts reports findings from a study that sought to test whether long-time shift workers (maritime pilots) compensated for shift related sleep loss by increasing the efficiency of deep sleep during work week sleep sessions or by rebound sleep during the rest week. The results suggest that the pilots have a small increase (that only reached an alpha level of 0.08) in the percent of deep sleep totals (%DST) during the workweek compared to the rest week. However, the pilots acquired significantly less total sleep time and deep sleep time during the work week compared to the rest week. When the data are compared via two computational models to test which may represent a compensatory mechanism for sleep loss (the work vs rest week sleep), the authors concluded that increased efficiency in deep sleep during the work week is more likely represents the compensatory mechanisms. While the findings are interesting in that they support the classic model that the amount of sleep/sleep efficiency is directly proportional to the time spent awake in prior to sleep, there are some concerns with the study and data presentation. Major comments: 1. The authors use a novel home EEG monitoring system. It is unclear how well this system can detect Slow Wave Activity (a measure of deep sleep efficiency i.e. delta power) compared to traditional polysomnographic recordings. It would be very useful to the reader if they provided more detailed information concerning delta power and/or a spectral analysis of sleep under the two conditions. Response: This is a relevant question. The-EEG device uses one-channel (FpZ-M2) to measure the EEG, which is filtered in three frequency bands: alpha (8-12 Hz), beta (15-30 Hz) and delta (0.5-4 Hz). These three frequency bands are used to detect ‘wake’, ‘light sleep’ and ‘deep sleep’. Deep sleep is detected when the root-mean-square of the delta frequency band exceeds a threshold and when at least six slow waves are detected in a 20 second window. The exact value of the RMS threshold is unknown to us, as it concerns a patented algorithm by the developers. This algorithm has been developed and adjusted using manual sleep scoring of the one-channel EEG by expert sleep technicians (see Garcia-Molina et al, 2018, Closed-loop system to enhance slow-wave activity). The validity of this algorithm has been published, and for example validated as a measure of sleep need dissipation (see Garcia-Molina et al., 2015, Automatic characterization of sleep need dissipation dynamics using a single EEG signal). To inform the readers, we have added the following to the methods section on page 6, lines 130-136, or see below: The home-EEG device was originally developed to acoustically stimulate slow-wave sleep, through automatic EEG-based detection of slow waves in the delta frequency band (0.5-4 Hz). We used the device for measurement purposes only, without auditory stimulation. The (proprietary) SmartSleep algorithm, based on 6 second epochs, differentiates between wakefulness, light sleep, and deep sleep [26, 27]. Deep sleep is detected when the root-mean-square of the delta frequency band exceeds a certain threshold and when at least six slow waves are detected in a 20 second window [27]. 2. The figure legends would benefit from more detail. What are the -days the workweek? are these consecutive? how does the model handle missing days? it appears that several participants do not have a values after day 2, 3, or 4. Response: We agree that the figure legends need some clarification. The days are consecutive, with the rest week starting at day 1. The negative days are the workweek, with day 0 as the last workday. There are participants with missing days, however, these are only present at the start or end of their consecutive days of measurements. We expect these days to be missing completely at random or perhaps missing at random, as not all participants started their consecutive measurements at the first day of the workweek. Mixed models handle missing data of both MCAR and MAR type very well, unlike e.g. a repeated measures ANOVA, participants with missing data on the outcome variable are not excluded from analysis. We clarified the figure legends in the manuscript, page 12, lines 215-220, or see below: Fig 1. Model 1 – efficiency in generating deep sleep. The x-axis indicates consecutive days, with days -4 to 0 representing the workweek and days 1 to 5 representing the rest week. Red line illustrates predicted model values, individual participant data is shown in black. Fig 2. Model 2 – rebound sleep after workweek. The x-axis indicates consecutive days, with days -4 to 0 representing the workweek and days 1 to 5 representing the rest week. Red line illustrates predicted model values, individual participant data is shown in black. 3. While the authors acknowledge that the sample size is small (n=10). There is no mention of a power analysis calculation that would provide the reader information about the sample size actually required to reach a power of at least .8 Response: Thank you for your comment, that resonates with major comment 1 of reviewer 1 and that we have addressed there. Please refer to our answer there. Attachments Attachment Submitted filename: Response_to_reviewers.docx https://doi.org/10.1371/journal.pone.0237622.r002
12 Nov 2020 Decision Letter - Henrik Oster, Editor Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study PONE-D-20-23329R1 Dear Dr. Mentink, 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, Henrik Oster, Ph.D. 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 #2: 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 #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: 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 #2: 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 #2: 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 #2: The authors were highly responsive to the concerns that were raised. All comments were adequately addressed and the manuscript has been greatly improved. There are no further concerns ****** 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 #2: Yes:** Jessica A Mong https://doi.org/10.1371/journal.pone.0237622.r003
Formally Accepted
21 Dec 2020 Acceptance Letter - Henrik Oster, Editor PONE-D-20-23329R1 Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers – The ANCHOR study Dear Dr. Mentink: 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 Prof. Henrik Oster Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0237622.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 .