Night Shift Worker Sleep Habits and Demand for Fatigue Management Features in a Mobile Application

Night Shift Worker Sleep Habits and Demand for Fatigue Management Features in a Mobile Application | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Night Shift Worker Sleep Habits and Demand for Fatigue Management Features in a Mobile Application Jaime K Devine, Amha Tekalign, Kyle Edward Chamberlin, Chantel Jewel Cooper, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7464384/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Digital health interventions like a sleep hygiene mobile application (app) designed specifically for night shift workers, can help improve health and on-the-job safety. Successful app development should consider user experience and economic demand in addition to sleep biology. This study reports the results of a market survey which aims to assess interest in a hypothetical sleep hygiene app designed for night shift workers. Methods N = 97 night shift workers, predominantly from the healthcare industry (n = 52), completed an anonymous online survey about their sleep habits, fatigue, technology use, perceived importance of app features, preferred pricing models, and level of comfort sharing data with employers. Results Respondents reported sleeping less than 7 hours on average with frequent sleep and fatigue issues in relation to their working schedules. Respondents ranked the ability of a sleep hygiene app to sync with their work schedule as the most important app feature. Slightly under half of respondents (n = 48) preferred a “free with ads” pricing model to one-time or recurring fees. n = 84 respondents were interested in using a fatigue management app; n = 93 would either be as interested or more interested if the app was paid for by their employer. The majority of respondents (n = 78) were either neutral or comfortable with sharing sleep data with their employers. Conclusions Night shift workers experience sleep problems and fatigue at work. Night shift workers would prefer a sleep hygiene app that takes their schedules into account and would be more likely to use an app that is either free with ads or paid for by their employer. shift work sleep hygiene mHealth app consumer sleep technology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Short sleep duration, defined as regularly getting less than 7 hours of sleep per day, is a common problem for night shift workers [ 1 , 2 ]. Schedules that require workers to be awake and on-shift during the night mean that sleep must accordingly occur during the day [ 3 ]. Workers are likely to have more difficulty sleeping during the day not only because the circadian clock promotes wakefulness at this time, but also because of social zeitgebers like noise, meal timing, or family obligations [ 3 ]. While the causes of short sleep duration may be myriad, there is an undeniable negative impact on the worker [ 1 – 6 ]. Night workers have worse health outcomes, decreased job performance, and an increased risk of making an error or having an accident in the workplace [ 2 , 7 , 8 ]. There is an immediate need for interventions that aim to increase sleep duration in night shift workers [ 1 , 4 ]. Educating workers about healthy sleep habits, also known as sleep hygiene, is just one technique that workplaces can implement to increase sleep duration in night workers [ 4 , 9 , 10 ]. Mobile health (mHealth) technologies like sleep hygiene applications (apps) allow for the delivery of personalized feedback that can be tailored specifically to the needs of night shift workers [ 11 ]. Sleep hygiene apps can use self-report sleep diary or utilize data from consumer sleep technologies (CSTs), known colloquially as sleep trackers or wearables. Many of these CSTs (though not all) have been tested and shown to track sleep as accurately as research-grade methods like polysomnography or actigraphy [ 12 – 14 ]. The global sleep app market is estimated to grow at a compound annual growth rate between 13–15% between 2025 and 2032 [ 15 , 16 ]. Market growth is expected to be driven by an increasing prevalence of sleep disturbances as well as consumer interest in personal wellness [ 15 , 16 ]. However, data privacy concerns and high costs are expected to hamper the market’s growth [ 15 , 17 , 18 ]. These concerns are particularly relevant for apps designed to help improve sleep for working populations. Namely, who should be expected to pay the costs associated with the app and who should have access to the data? On the one hand, apps are traditionally designed to provide personalized feedback directly to the individual consumer. An app should be tailored to the end user’s issues so that it can inspire behavioral change over time. Improvements to sleep hygiene have the potential to benefit individual health and well-being. These arguments support the idea that apps should be developed for personal use and paid for by the individual consumer. On the other hand, however, it is unfair to expect individual workers to bear full responsibility for sleep disturbances that can be attributed to their working conditions. A recent review of evidence for behavioral management of sleep disorders in shift workers concluded that individual-focused interventions are unlikely to be effective without strong support at the organizational level [ 19 ]. Improving sleep hygiene should be considered a shared responsibility between individual workers and their organization. Therefore, it follows that an app that aims to improve sleep behavior that is specifically disrupted by the work schedule should be designed with both the needs of the individual and the organization in mind. If the organization bears the expense of paying for an app, however, they will likely want access to users’ data in return. There is also the pragmatic issue of pricing—how much money an individual user or the organization is willing to pay for a sleep hygiene app versus how much money is needed to continually support the app’s features. The future success of sleep mHealth technologies for shift workers depends on a market strategy that bridges the divide between the organization and the individual. App development may benefit from taking multiple research perspectives, including marketing, sleep and circadian biology, user experience (UX), and behavioral economics, into account. For example, a sleep hygiene app that has been extensively tested in a laboratory setting may fail to increase sleep duration in a real-world setting if the end user does not find the app engaging. Collaboration between software developers, scientists, and business professionals may be necessary in order to develop financially sustainable apps that actually improve sleep health outcomes for shift workers. The fatigue science team at the Institutes for Behavior Resources (IBR) has been conducting a series of surveys about the desirability of CSTs as scientifically relevant sleep tracking tools. Previous surveys in this project have focused on the opinions of sleep researchers, general consumers, and aviation professionals [ 17 , 20 , 21 ]. The current study was done in collaboration with the University of Maryland Robert H. Smith School of Business Master of Business Administration (MBA) Technology Management Graduate Program Capstone Project, a program that connects student teams with real-world business challenges. The goal of this survey was to establish an estimate of night shift workers’ current issues with sleep in the context of work, their preferences for sleep-tracking features and brands, and their willingness to share sleep data with their organization. The survey furthermore assessed night workers’ economic demand for a hypothetical app based on pricing models (free with ads, one-time fee, or subscription). Finally, the survey evaluated how night workers’ interest in the hypothetical app changed based on whether it was purchased individually versus paid for by their company. The findings of this survey build on a growing body of research that aims to bridge the knowledge gap between sleep science and the development of successful digital health interventions. Methods Subjects and Procedure The Technology Management Graduate Program Capstone student team developed a novel survey for the purposes of this study. The full survey is included in the Supplementary Material. The survey was hosted by the Technology Management Graduate Program Capstone student team on the online tool Qualtrics ( www.qualtrics.com ) throughout the month of June 2025. Potential respondents were recruited through social media, email, and word of mouth. The voluntary anonymous survey was composed of seventeen questions that focused on 1) the respondent’s professional background and shift work experience; 2) the respondent’s sleep behavior and workplace fatigue, and; 3) the respondent’s preferences and interest in app features, pricing models, brands of sleep trackers, and data sharing in the context of work. Data was shared with the IRB research team after the conclusion of the Industry Capstone project. This study was approved with exempt status by the Salus Institutional Review Board (Protocol Number UMD2025) and these analyses were conducted in accordance with the Declaration of Helsinki. Statistical Analysis All data were exported from Qualtrics as an Excel file and subsequently analyzed using Excel 2013. Summary statistics were calculated for each question. The Excel Rank function was used to calculate weighted mean rank order. In-depth statistical testing was not appropriate for these analyses due to the qualitative nature of the survey. Results A total of 169 respondents completed the online survey. Seventy-two (72) participants indicated that they only worked day shifts and were excluded from further analysis. The distribution of respondents by industry and shift type is summarized in Table 1 . All included respondents (N = 97) completed 100% of the survey. As shown in Table 1 , shift workers from the healthcare industry made up 54% of all survey responses (n = 52). All other industries comprised a response rate of less than 10% of total responses. Sixty-eight percent (68%) of respondents across all industries indicated working a mixture of day and night shifts (n = 66) while 32% of respondents indicated working regular night shifts. Figure 1 depicts respondents normal hours of sleep and their concerns about fatigue in relation to their job performance by number of total responses. Ninety-eight percent of respondents (n = 95) indicated that they regularly slept seven hours or less when working night shifts (Fig. 1 A). Only two respondents indicated that they regularly slept eight or more hours when working nights. As shown in Fig. 1 B and 1 C respectively, eighty percent of respondents (n = 78) either somewhat agreed with or strongly agreed with the statement ‘I struggle with sleep and feeling rested when I work at night’ and 66% of respondents agreed with the statement ‘I worry that fatigue affects my performance at work on a regular basis’. Thirty-six percent of respondents (n = 35) had reported a fatigue-related incident at work (Fig. 1 D). Of the respondents who had reported a fatigue-related incident at work, n = 13 worked in healthcare, n = 5 working in aviation, n = 4 in construction/industrial, n = 6 in manufacturing, n = 2 from Information Technology (IT) and n = 1 each from the fields of security, transportation, retail/commerce, research, and finance. These responses represent, respectively, 25% of the total reporting respondents from the healthcare industry, 55% of respondents from aviation, 50% of respondents from construction/industrial, 75% of respondents from manufacturing, 33% of respondents from IT, 33% of respondents from security, and 50% of respondents from transportation, and 100% of respondents from retail/commerce, research, and finance. Table 1 Respondent Demographics by Industry and Shift Schedule Industry Total Number of Respondents Regular Night Shift Day and Night Shifts Healthcare 52 19 33 Aviation 9 0 9 Construction/Industrial 8 2 6 Manufacturing 8 3 5 Information Technology 5 3 2 Security 3 1 2 Retail/Commerce 3 0 3 Hospitality 3 1 2 Scientific 2 1 1 Transportation 2 1 1 Finance 1 0 1 Media 1 0 1 Total 97 31 66 Respondents next answered a series of questions related to fatigue management in the context of work. Figure 2A depicts respondents’ fatigue-related challenges by rank order. Respondents were able to select all items that applied from a list of common fatigue issues, provide their own write-in response, or indicate that they did not experience any fatigue-related challenges. ‘Feeling fatigued during long shifts’ was the most commonly-reported fatigue-related challenge (Fig. 2A, n = 71). ‘Trouble sleeping on days off’, ‘insomnia’, ‘children’, and ‘mood swings’ were included as write-in responses. All respondents indicated that they experienced at least one fatigue-related challenge. Figure 2B shows strategies to manage fatigue. Caffeine was the most frequently-reported strategy to manage fatigue (n = 76). ‘Marijuana’, ‘CPAP machine’, ‘melatonin’, ‘herbal supplements’, ‘Adderall’ and ‘other medication’ were included as write-in responses. Three respondents indicated that they did not use any strategies or tools to manage fatigue. Figure 3 shows responses for current use of sleep trackers (Fig. 3 A), whether sleep trackers are allowed in the workplace (Fig. 3 B) and respondents’ level of comfort sharing sleep data with their employers (Fig. 3 C). Apple was the most popular brand of sleep tracker reported by night shift workers (Fig. 3 A). Twenty-one respondents (22%) reported using no consumer sleep trackers at all. Sleep trackers were largely permitted in the workplace (Fig. 3 B). Only four respondents indicated that sleep trackers were not allowed; two respondents were unsure of their workplace policies about sleep trackers. Figure 3 C shows that 80% (n = 78) of respondents were either neutral or comfortable to some degree with sharing sleep data with their employers. The remaining 20% (n = 19) respondents were not comfortable with the idea of sharing sleep data with their employers. Respondents were next asked to rate features within a hypothetical app designed to manage sleep and fatigue in shift workers by order of importance (high importance, medium importance, or low importance). Figure 4 depicts respondents’ perceived importance of sleep tracking features (Fig. 4A) and preferred pricing model (Fig. 3 B) for a hypothetical app designed for shift workers. The highest proportion of night shift workers (n = 82, 84% of total population) ranked the ability of the app to sync with their work schedule as ‘highly important’, followed by ‘sleep quality history’ (n = 81, 83%). ‘Alertness forecasting’ (n = 60, 60%) and ‘prospective sleep planner’ (n = 53, 55%) were rated as highly important by the fewest respondents. As shown in Fig. 4B, nearly half of respondents (n = 48, 49%) preferred a ‘free with ads’ pricing model. A $ 10 one-time fee was preferred by approximately one-third of respondents (n = 35, 36%) and $ 2 monthly subscription fee was preferred by fourteen percent (n = 14) of respondents. Lastly, respondents indicated their overall interest in a sleep hygiene app designed for shift workers, and whether their level of interest would change if their employer paid for the app relative to personal cost, as shown in Fig. 5 . Figure 5 A shows that 86% of respondents (n = 84) were interested in using an app to manage fatigue on a regular basis. Figure 5 A shows that 96% of respondents (n = 93) would either be as interested or more interested in using a fatigue management app if it was paid for by their employer rather than personal cost. Five (n = 5) of the respondents from the “Neither interested nor disinterested”, n = 3 respondents from the “Not very interested”, and both (n = 2) respondents from the “Not at all interested” categories shown in Fig. 5 A indicated that they would either be “A little more interested” or “Much more interested” if their employer paid for the app (Fig. 5 B). Within the n = 3 respondents who indicated in Fig. 5 B that they would be “A little less interested” in the app if it was paid for by their employer, n = 1 respondent each originally indicated that they were “Not very interested”, “Somewhat interested”, or “Very interested” in a fatigue management app (Fig. 5 A). The singular “Much less interested” respondent from Fig. 5 B indicated that they were “Neither interested nor disinterested” in a fatigue management app (Fig. 5 A). Discussion This report is the latest in a multi-survey project designed to establish consumer demand for sleep technologies on the basis of their scientific or operational relevancy [ 17 , 20 – 22 ]. Previous surveys in this series focused on demand for sleep technologies from the perspective of general consumers [ 20 ], sleep researchers [ 21 ], or aviation professionals [ 17 ]. The current survey focused on individuals who reported working regular night shifts or mixed day and night shifts. In contrast to the previous studies in this series, the current survey focused primarily on demand for a digital technology (a sleep hygiene mobile app) rather than a hardware device like a wearable sleep tracker [ 17 , 20 , 21 ]. Additionally, the current survey represents a collaboration between laboratories focusing on fatigue science, behavioral economics, data science, and information systems. The findings from this market survey support an interdisciplinary approach to understanding what constitutes a successful digital sleep health intervention. Unsurprisingly, night shift workers in this survey reported fatigue and sleep issues in relation to their work. This supports findings from previous studies and reflects a well-known safety concern with regards to working nights [ 1 , 7 , 8 , 23 ]. Over half of the respondents reported working a mixture of day and night shifts (68%; n = 66). Rotating shift work is associated with worse sleep health outcomes and a higher safety risk than regular night shifts because of the ongoing need to adapt to a new schedule [ 8 , 23 ]. It is likely that full-time night workers and rotating or irregular night shift workers may have different sleep hygiene needs. The sample size of this dataset is insufficient to explore differences between regular night shift workers and irregular night shift workers but should be considered for future research. Very few of the respondents reported sleeping for seven or more hours when working nights (Fig. 1 A), placing them at risk for issues related to short sleep duration. Eighty percent (80%; n = 78) of respondents agreed that they struggled with sleep (Fig. 1 B) and every respondent in this survey reported experiencing as least one fatigue-related challenge (Fig. 2A), with “feeling fatigued during long shifts” being the most commonly reported challenge. Two-thirds of respondents (n = 64) indicated a concern for their ability to perform (Fig. 1 C), and approximately one-third of respondents had already reported a fatigue-related incident at work (Fig. 1 D). It is worth noting that “reporting a fatigue-related incident” could be loosely interpreted by respondents from something as official as filing a written report to something as casual as making a verbal complaint to management. Respondents were not prompted with a definition about what constituted a fatigue report and were not asked to provide specifics about their personal experience with reporting a fatigue-related incident. This constitutes a limitation to the interpretation of the data. Most of the night shift workers in this survey engaged in a number of tools or strategies to manage fatigue. These strategies can largely be classified as either pharmacological or behavioral. Caffeine was the most frequently-reported strategy for counteracting fatigue (Fig. 2B). Other pharmacological strategies included sleep aids, Adderall, marijuana, unspecified “medication”, and melatonin. Napping, sleep tracking, and meditation were common behavioral countermeasures. Recent reviews of both pharmacological interventions [ 24 ] or non-pharmacological interventions [ 19 , 25 ] to improve sleep or reduce sleepiness in shift workers have shown mixed evidence for the ability of any of these strategies to improve individual shift worker sleep. Sleep tracking was the third most common strategy reported by night shift workers as a way to manage fatigue (Fig. 2B). Respondents were not asked to specify their sleep tracking method, so responses may have included analogue tracking methods like keeping a sleep diary as well as the use of CSTs or apps. Relatedly, when asked what brand of sleep trackers they use in Fig. 3 A, 22% (n = 21) of respondents reported not using a CST at all, which was the second highest proportion of responses after those who reported using the Apple watch (Fig. 3 A; n = 48). Sleep trackers were largely permitted in the workplace (Fig. 3 B) and the majority of night shift workers were comfortable with sharing data with their employers (Fig. 3 C). Night shift workers also prioritized the ability of a sleep app to sync with their work schedule over other features (Fig. 4A). Taken together, these findings suggest an organizational-level opportunity to fill a gap in night shift workers’ needs for sleep management with already available technology. Cost seemed to be a driver for night shift workers’ interest in a sleep hygiene app. Respondents preferred a pricing model where a hypothetical app would be free compared to a one-time fee or recurring subscription (Fig. 4B) and expressed increased interest in the app if it was paid for by their employer (Fig. 5 B). These findings are in keeping with market reports that identify high cost as a barrier to economic growth for sleep technology [ 15 , 16 ] and results from our previous surveys examining demand for CSTs [ 17 , 20 , 21 ]. In our previous survey of aviation professionals, cost was listed as a common reason for not using CSTs and even respondents who already used a CST still indicated a preference for using a device purchased by the organization over a personally-owned device for fatigue risk management purposes [ 17 ]. A limitation to the current study is that respondents were only provided with three pricing options rather than given a purchase task survey designed to establish a demand curve representing likelihood of purchase across a series of increasing prices [ 20 , 21 , 26 ]. The three pricing models included in this survey (free with ads, $ 10 one-time fee, and $ 2 monthly fee) were informed by our previous behavioral economics surveys as well as by estimated market costs for continually hosting a sleep health app. However, a purchase task may have been able to pinpoint a more granular price point at which night shift workers would be most willing to use a sleep health app. When it comes to the use of digital health technologies to improve sleep in shift workers, there is decidedly room for improvement. There is underwhelming evidence that sleep hygiene apps or other individual strategies to manage fatigue in the workplace can be effective [ 9 , 19 , 24 , 25 ]. This may be because interventions are rarely tested using a high-quality research design like a clinical trial, making it difficult to observe improvements [ 19 , 25 , 27 , 28 ]. Another suggestion made by Arroyo et al. 2022 is that making a successful behavioral change for sleep is more complex than changing diet or exercise patterns [ 28 ]. Sleep health apps may require a different design strategy than other mHealth apps [ 28 ]. One strategy that may help successfully develop sleep health technologies specifically for shift workers is to develop an app that bridges the divide between the individual worker and their organization. It is possible that workers will be more likely to make behavioral changes if that behavior is linked to their ability to perform their job safely and is supported by their employer. Additionally, organizations may be more willing to support initiatives that can deliver objective measures of behavior, such as through the analysis of sleep data shared through the app. Developing sleep hygiene apps for organizational use may have the added benefit of reducing concerns about privacy and data-sharing. In this survey and our previous survey of aviation professionals, respondents indicated a greater willingness to share anonymous data with their employers if the technology used to collect the data was paid for by the company [ 17 ]. Conclusion There is a need to develop effective mHealth interventions to improve sleep hygiene in night shift workers, the majority of whom report sleep and fatigue issues in relation to work. Night shift workers in the current survey indicated a preference for organizational-level technological solutions, including rating the ability of an app to sync with their work schedule data as highly important relative to other app features, being comfortable with sharing data with their employer, and expressing more interest in using an app based on whether it was paid for by their employer or not. The findings from this survey builds upon a growing body of research aimed to incorporate behavioral economics and user preference into the conversation about how to best develop scientifically-sound technologies to improve sleep health outcomes in working populations [ 17 , 21 , 22 ]. Declarations Acknowledgements. The authors would like to acknowledge the professors and administrators of the University of Maryland Robert H. Smith School of Business Master of Business Administration (MBA) Technology Management Graduate Program Capstone Project for their support, mentorship, collaboration, and hard work. Data availability . The dataset generated during the current study is available from the corresponding author on reasonable request. Author Contributions AT, KEC, CJC, JC, and DB performed the research described in this paper. JKD performed the secondary data analysis and drafted the initial version of the manuscript under the supervision of SRH. All authors contributed to the editing and proofreading of the final draft. Ethics approval and consent to participate All participants provided informed consent prior to their participation in the original study. Secondary use of de-identified data for research purposes was deemed non-human subjects research by the Salus Institutional Review Board, an independent, appropriately constituted and fully accredited institutional review board based in Austin, Texas, USA. This study was approved with exempt status by the Salus Institutional Review Board (Protocol Number UMD2025). These analyses were conducted in accordance with the Declaration of Helsinki. Consent for publication Not applicable. Competing interests Author JKD is a guest editor for the BMC Digital Health “The future of circadian and sleep health in the digital era” special collection. Funding information There was no funding associated with this project. 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Supplementary Files SupplementaryMaterialSurvey.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Nov, 2025 Reviews received at journal 18 Nov, 2025 Reviews received at journal 29 Oct, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 14 Sep, 2025 Editor assigned by journal 08 Sep, 2025 Submission checks completed at journal 04 Sep, 2025 First submitted to journal 04 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7464384","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":516985226,"identity":"a3165914-e8ff-4d6e-b266-0dbcda3d066b","order_by":0,"name":"Jaime K 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Chamberlin","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Kyle","middleName":"Edward","lastName":"Chamberlin","suffix":""},{"id":516985233,"identity":"fc0100ac-fce5-41df-8a28-0cf29dbe181f","order_by":3,"name":"Chantel Jewel Cooper","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Chantel","middleName":"Jewel","lastName":"Cooper","suffix":""},{"id":516985235,"identity":"6216a46c-f46e-416d-a235-72f256fbc397","order_by":4,"name":"Joel Camacho","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Joel","middleName":"","lastName":"Camacho","suffix":""},{"id":516985236,"identity":"562cfd80-8449-4192-9d24-b900bbba8920","order_by":5,"name":"Daniel Bonsu","email":"","orcid":"","institution":"University of Maryland","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Bonsu","suffix":""},{"id":516985237,"identity":"80833e67-2789-41eb-8080-b3c1087d75df","order_by":6,"name":"Steven R Hursh","email":"","orcid":"","institution":"The Johns Hopkins University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"R","lastName":"Hursh","suffix":""}],"badges":[],"createdAt":"2025-08-26 15:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7464384/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7464384/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91919596,"identity":"68129e4e-d756-43dc-8d9f-0033cfe5cc59","added_by":"auto","created_at":"2025-09-23 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01:11:44","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89824,"visible":true,"origin":"","legend":"","description":"","filename":"65eb208884f4477fa9b2c9a459a82dfd1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/ee62b8cfb75889baf3aa631a.xml"},{"id":91919605,"identity":"d5b3fcd8-c4f8-4424-b0b5-e14648a1d940","added_by":"auto","created_at":"2025-09-23 01:11:37","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":99172,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/6cb6e716ccc197ec0e1d11e1.html"},{"id":91919603,"identity":"3057c8e2-4ed0-4dec-bfda-a1679dfc149c","added_by":"auto","created_at":"2025-09-23 01:11:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106938,"visible":true,"origin":"","legend":"\u003cp\u003ePie charts depicting, by total response count: A) night shift workers’ normal sleep duration in hours; B-C) rate of agreement with statements about fatigue at work; D) whether or not respondents had reported a fatigue-related incident at work.\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/e5993f73160a6021925e4c23.jpg"},{"id":91919613,"identity":"ab8a9a40-609f-437c-bd7a-35af8969c92f","added_by":"auto","created_at":"2025-09-23 01:11:43","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90498,"visible":true,"origin":"","legend":"\u003cp\u003eMean rank order of responses regarding A) fatigue-related challenges and B) strategies or tools used by respondents to personally manage their fatigue. Items are listed on the y-axis by weighted rank, with items at the top of the chart corresponding to higher ranking. Bars depict the total number of responses for each item. Respondents were able to select multiple items.\u003c/p\u003e","description":"","filename":"image2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/d6e1ffe778de207679e80dcd.jpg"},{"id":91919595,"identity":"1b61805f-ab01-49ce-a543-fab642edb219","added_by":"auto","created_at":"2025-09-23 01:11:34","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80015,"visible":true,"origin":"","legend":"\u003cp\u003eA) Brands of consumer sleep trackers currently used by night shift workers. Brands are ranked from most frequently reported (top) to least frequently reported (bottom). Number of responses are represented by black bars and data labels. B) Pie chart depicting response rate for whether sleep trackers are allowed in the workplace. Each slice of the pie chart represents a different option with the number of responses directly beneath. C) Pie chart depicting level of comfort sharing data with employers. Each slice of the pie chart represents a different comfort level with the number of responses directly beneath.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/00540f6c2837b71fad14dd42.jpeg"},{"id":91919604,"identity":"112ea807-ce8b-425a-a8ac-47ef23f465bb","added_by":"auto","created_at":"2025-09-23 01:11:37","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94316,"visible":true,"origin":"","legend":"\u003cp\u003eA) Perceived importance of sleep hygiene features in a hypothetical app designed for shift workers. Items are listed on the y-axis by weighted rank, with number 1 corresponding to higher importance ranking. Bars depict the number of responses by level of importance (high importance is in light grey; medium importance is in medium grey; and low importance is in dark grey) for each item. B) Pie chart depicting preferences for app pricing model. Each slice of the pie chart represents a different pricing model option with the number of responses directly beneath.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/69564b47f4a07505d013220b.jpeg"},{"id":91919638,"identity":"a576f9b6-0944-4dc5-8475-03b42729f509","added_by":"auto","created_at":"2025-09-23 01:11:45","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":81312,"visible":true,"origin":"","legend":"\u003cp\u003ePie chart depicting A) night shift workers’ level of interest in using a fatigue management app, and B) Relative level of interest depending on the app was paid for by their employer. Each slice of the pie chart represents a different option with the number of responses directly beneath.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/769715807dc773909017dca8.jpeg"},{"id":91919792,"identity":"59e7c495-22a5-4258-8469-364e77bd6c34","added_by":"auto","created_at":"2025-09-23 01:19:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1007595,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/046ce15d-a7b3-4d5b-9437-05e9d1708062.pdf"},{"id":91919608,"identity":"f9cff953-4129-46ff-a90b-b753c2b61374","added_by":"auto","created_at":"2025-09-23 01:11:37","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17652,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialSurvey.docx","url":"https://assets-eu.researchsquare.com/files/rs-7464384/v1/3b2124a3426f5f55d2a7eceb.docx"}],"financialInterests":"Competing interest reported. Author JKD is a guest editor for the BMC Digital Health “The future of circadian and sleep health in the digital era” special collection.","formattedTitle":"Night Shift Worker Sleep Habits and Demand for Fatigue Management Features in a Mobile Application","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eShort sleep duration, defined as regularly getting less than 7 hours of sleep per day, is a common problem for night shift workers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Schedules that require workers to be awake and on-shift during the night mean that sleep must accordingly occur during the day [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Workers are likely to have more difficulty sleeping during the day not only because the circadian clock promotes wakefulness at this time, but also because of social zeitgebers like noise, meal timing, or family obligations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. While the causes of short sleep duration may be myriad, there is an undeniable negative impact on the worker [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Night workers have worse health outcomes, decreased job performance, and an increased risk of making an error or having an accident in the workplace [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere is an immediate need for interventions that aim to increase sleep duration in night shift workers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Educating workers about healthy sleep habits, also known as sleep hygiene, is just one technique that workplaces can implement to increase sleep duration in night workers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Mobile health (mHealth) technologies like sleep hygiene applications (apps) allow for the delivery of personalized feedback that can be tailored specifically to the needs of night shift workers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Sleep hygiene apps can use self-report sleep diary or utilize data from consumer sleep technologies (CSTs), known colloquially as sleep trackers or wearables. Many of these CSTs (though not all) have been tested and shown to track sleep as accurately as research-grade methods like polysomnography or actigraphy [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe global sleep app market is estimated to grow at a compound annual growth rate between 13\u0026ndash;15% between 2025 and 2032 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Market growth is expected to be driven by an increasing prevalence of sleep disturbances as well as consumer interest in personal wellness [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, data privacy concerns and high costs are expected to hamper the market\u0026rsquo;s growth [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These concerns are particularly relevant for apps designed to help improve sleep for working populations. Namely, who should be expected to pay the costs associated with the app and who should have access to the data?\u003c/p\u003e\u003cp\u003eOn the one hand, apps are traditionally designed to provide personalized feedback directly to the individual consumer. An app should be tailored to the end user\u0026rsquo;s issues so that it can inspire behavioral change over time. Improvements to sleep hygiene have the potential to benefit individual health and well-being. These arguments support the idea that apps should be developed for personal use and paid for by the individual consumer. On the other hand, however, it is unfair to expect individual workers to bear full responsibility for sleep disturbances that can be attributed to their working conditions.\u003c/p\u003e\u003cp\u003eA recent review of evidence for behavioral management of sleep disorders in shift workers concluded that individual-focused interventions are unlikely to be effective without strong support at the organizational level [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Improving sleep hygiene should be considered a shared responsibility between individual workers and their organization. Therefore, it follows that an app that aims to improve sleep behavior that is specifically disrupted by the work schedule should be designed with both the needs of the individual and the organization in mind. If the organization bears the expense of paying for an app, however, they will likely want access to users\u0026rsquo; data in return. There is also the pragmatic issue of pricing\u0026mdash;how much money an individual user or the organization is willing to pay for a sleep hygiene app versus how much money is needed to continually support the app\u0026rsquo;s features.\u003c/p\u003e\u003cp\u003eThe future success of sleep mHealth technologies for shift workers depends on a market strategy that bridges the divide between the organization and the individual. App development may benefit from taking multiple research perspectives, including marketing, sleep and circadian biology, user experience (UX), and behavioral economics, into account. For example, a sleep hygiene app that has been extensively tested in a laboratory setting may fail to increase sleep duration in a real-world setting if the end user does not find the app engaging. Collaboration between software developers, scientists, and business professionals may be necessary in order to develop financially sustainable apps that actually improve sleep health outcomes for shift workers.\u003c/p\u003e\u003cp\u003eThe fatigue science team at the Institutes for Behavior Resources (IBR) has been conducting a series of surveys about the desirability of CSTs as scientifically relevant sleep tracking tools. Previous surveys in this project have focused on the opinions of sleep researchers, general consumers, and aviation professionals [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The current study was done in collaboration with the University of Maryland Robert H. Smith School of Business Master of Business Administration (MBA) Technology Management Graduate Program Capstone Project, a program that connects student teams with real-world business challenges.\u003c/p\u003e\u003cp\u003eThe goal of this survey was to establish an estimate of night shift workers\u0026rsquo; current issues with sleep in the context of work, their preferences for sleep-tracking features and brands, and their willingness to share sleep data with their organization. The survey furthermore assessed night workers\u0026rsquo; economic demand for a hypothetical app based on pricing models (free with ads, one-time fee, or subscription). Finally, the survey evaluated how night workers\u0026rsquo; interest in the hypothetical app changed based on whether it was purchased individually versus paid for by their company. The findings of this survey build on a growing body of research that aims to bridge the knowledge gap between sleep science and the development of successful digital health interventions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eSubjects and Procedure\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe Technology Management Graduate Program Capstone student team developed a novel survey for the purposes of this study. The full survey is included in the Supplementary Material. The survey was hosted by the Technology Management Graduate Program Capstone student team on the online tool Qualtrics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.qualtrics.com\u003c/span\u003e\u003cspan address=\"http://www.qualtrics.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) throughout the month of June 2025. Potential respondents were recruited through social media, email, and word of mouth. The voluntary anonymous survey was composed of seventeen questions that focused on 1) the respondent\u0026rsquo;s professional background and shift work experience; 2) the respondent\u0026rsquo;s sleep behavior and workplace fatigue, and; 3) the respondent\u0026rsquo;s preferences and interest in app features, pricing models, brands of sleep trackers, and data sharing in the context of work. Data was shared with the IRB research team after the conclusion of the Industry Capstone project. This study was approved with exempt status by the Salus Institutional Review Board (Protocol Number UMD2025) and these analyses were conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll data were exported from Qualtrics as an Excel file and subsequently analyzed using Excel 2013. Summary statistics were calculated for each question. The Excel Rank function was used to calculate weighted mean rank order. In-depth statistical testing was not appropriate for these analyses due to the qualitative nature of the survey.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA total of 169 respondents completed the online survey. Seventy-two (72) participants indicated that they only worked day shifts and were excluded from further analysis. The distribution of respondents by industry and shift type is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All included respondents (N\u0026thinsp;=\u0026thinsp;97) completed 100% of the survey. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, shift workers from the healthcare industry made up 54% of all survey responses (n\u0026thinsp;=\u0026thinsp;52). All other industries comprised a response rate of less than 10% of total responses. Sixty-eight percent (68%) of respondents across all industries indicated working a mixture of day and night shifts (n\u0026thinsp;=\u0026thinsp;66) while 32% of respondents indicated working regular night shifts.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts respondents normal hours of sleep and their concerns about fatigue in relation to their job performance by number of total responses. Ninety-eight percent of respondents (n\u0026thinsp;=\u0026thinsp;95) indicated that they regularly slept seven hours or less when working night shifts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Only two respondents indicated that they regularly slept eight or more hours when working nights. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC respectively, eighty percent of respondents (n\u0026thinsp;=\u0026thinsp;78) either somewhat agreed with or strongly agreed with the statement \u0026lsquo;I struggle with sleep and feeling rested when I work at night\u0026rsquo; and 66% of respondents agreed with the statement \u0026lsquo;I worry that fatigue affects my performance at work on a regular basis\u0026rsquo;. Thirty-six percent of respondents (n\u0026thinsp;=\u0026thinsp;35) had reported a fatigue-related incident at work (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Of the respondents who had reported a fatigue-related incident at work, n\u0026thinsp;=\u0026thinsp;13 worked in healthcare, n\u0026thinsp;=\u0026thinsp;5 working in aviation, n\u0026thinsp;=\u0026thinsp;4 in construction/industrial, n\u0026thinsp;=\u0026thinsp;6 in manufacturing, n\u0026thinsp;=\u0026thinsp;2 from Information Technology (IT) and n\u0026thinsp;=\u0026thinsp;1 each from the fields of security, transportation, retail/commerce, research, and finance. These responses represent, respectively, 25% of the total reporting respondents from the healthcare industry, 55% of respondents from aviation, 50% of respondents from construction/industrial, 75% of respondents from manufacturing, 33% of respondents from IT, 33% of respondents from security, and 50% of respondents from transportation, and 100% of respondents from retail/commerce, research, and finance.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRespondent Demographics by Industry and Shift Schedule\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndustry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Number of Respondents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegular Night Shift\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDay and Night Shifts\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthcare\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAviation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstruction/Industrial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eManufacturing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInformation Technology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecurity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRetail/Commerce\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScientific\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransportation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRespondents next answered a series of questions related to fatigue management in the context of work. Figure\u0026nbsp;2A depicts respondents\u0026rsquo; fatigue-related challenges by rank order. Respondents were able to select all items that applied from a list of common fatigue issues, provide their own write-in response, or indicate that they did not experience any fatigue-related challenges. \u0026lsquo;Feeling fatigued during long shifts\u0026rsquo; was the most commonly-reported fatigue-related challenge (Fig.\u0026nbsp;2A, n\u0026thinsp;=\u0026thinsp;71). \u0026lsquo;Trouble sleeping on days off\u0026rsquo;, \u0026lsquo;insomnia\u0026rsquo;, \u0026lsquo;children\u0026rsquo;, and \u0026lsquo;mood swings\u0026rsquo; were included as write-in responses. All respondents indicated that they experienced at least one fatigue-related challenge. Figure\u0026nbsp;2B shows strategies to manage fatigue. Caffeine was the most frequently-reported strategy to manage fatigue (n\u0026thinsp;=\u0026thinsp;76). \u0026lsquo;Marijuana\u0026rsquo;, \u0026lsquo;CPAP machine\u0026rsquo;, \u0026lsquo;melatonin\u0026rsquo;, \u0026lsquo;herbal supplements\u0026rsquo;, \u0026lsquo;Adderall\u0026rsquo; and \u0026lsquo;other medication\u0026rsquo; were included as write-in responses. Three respondents indicated that they did not use any strategies or tools to manage fatigue.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows responses for current use of sleep trackers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), whether sleep trackers are allowed in the workplace (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and respondents\u0026rsquo; level of comfort sharing sleep data with their employers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Apple was the most popular brand of sleep tracker reported by night shift workers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Twenty-one respondents (22%) reported using no consumer sleep trackers at all. Sleep trackers were largely permitted in the workplace (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Only four respondents indicated that sleep trackers were not allowed; two respondents were unsure of their workplace policies about sleep trackers. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC shows that 80% (n\u0026thinsp;=\u0026thinsp;78) of respondents were either neutral or comfortable to some degree with sharing sleep data with their employers. The remaining 20% (n\u0026thinsp;=\u0026thinsp;19) respondents were not comfortable with the idea of sharing sleep data with their employers.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eRespondents were next asked to rate features within a hypothetical app designed to manage sleep and fatigue in shift workers by order of importance (high importance, medium importance, or low importance). Figure\u0026nbsp;4 depicts respondents\u0026rsquo; perceived importance of sleep tracking features (Fig.\u0026nbsp;4A) and preferred pricing model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) for a hypothetical app designed for shift workers. The highest proportion of night shift workers (n\u0026thinsp;=\u0026thinsp;82, 84% of total population) ranked the ability of the app to sync with their work schedule as \u0026lsquo;highly important\u0026rsquo;, followed by \u0026lsquo;sleep quality history\u0026rsquo; (n\u0026thinsp;=\u0026thinsp;81, 83%). \u0026lsquo;Alertness forecasting\u0026rsquo; (n\u0026thinsp;=\u0026thinsp;60, 60%) and \u0026lsquo;prospective sleep planner\u0026rsquo; (n\u0026thinsp;=\u0026thinsp;53, 55%) were rated as highly important by the fewest respondents. As shown in Fig.\u0026nbsp;4B, nearly half of respondents (n\u0026thinsp;=\u0026thinsp;48, 49%) preferred a \u0026lsquo;free with ads\u0026rsquo; pricing model. A \u003cspan\u003e$\u003c/span\u003e10 one-time fee was preferred by approximately one-third of respondents (n\u0026thinsp;=\u0026thinsp;35, 36%) and \u003cspan\u003e$\u003c/span\u003e2 monthly subscription fee was preferred by fourteen percent (n\u0026thinsp;=\u0026thinsp;14) of respondents.\u003c/p\u003e\u003cp\u003eLastly, respondents indicated their overall interest in a sleep hygiene app designed for shift workers, and whether their level of interest would change if their employer paid for the app relative to personal cost, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA shows that 86% of respondents (n\u0026thinsp;=\u0026thinsp;84) were interested in using an app to manage fatigue on a regular basis. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA shows that 96% of respondents (n\u0026thinsp;=\u0026thinsp;93) would either be as interested or more interested in using a fatigue management app if it was paid for by their employer rather than personal cost. Five (n\u0026thinsp;=\u0026thinsp;5) of the respondents from the \u0026ldquo;Neither interested nor disinterested\u0026rdquo;, n\u0026thinsp;=\u0026thinsp;3 respondents from the \u0026ldquo;Not very interested\u0026rdquo;, and both (n\u0026thinsp;=\u0026thinsp;2) respondents from the \u0026ldquo;Not at all interested\u0026rdquo; categories shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA indicated that they would either be \u0026ldquo;A little more interested\u0026rdquo; or \u0026ldquo;Much more interested\u0026rdquo; if their employer paid for the app (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Within the n\u0026thinsp;=\u0026thinsp;3 respondents who indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eB that they would be \u0026ldquo;A little less interested\u0026rdquo; in the app if it was paid for by their employer, n\u0026thinsp;=\u0026thinsp;1 respondent each originally indicated that they were \u0026ldquo;Not very interested\u0026rdquo;, \u0026ldquo;Somewhat interested\u0026rdquo;, or \u0026ldquo;Very interested\u0026rdquo; in a fatigue management app (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The singular \u0026ldquo;Much less interested\u0026rdquo; respondent from Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eB indicated that they were \u0026ldquo;Neither interested nor disinterested\u0026rdquo; in a fatigue management app (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis report is the latest in a multi-survey project designed to establish consumer demand for sleep technologies on the basis of their scientific or operational relevancy [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Previous surveys in this series focused on demand for sleep technologies from the perspective of general consumers [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], sleep researchers [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], or aviation professionals [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The current survey focused on individuals who reported working regular night shifts or mixed day and night shifts. In contrast to the previous studies in this series, the current survey focused primarily on demand for a digital technology (a sleep hygiene mobile app) rather than a hardware device like a wearable sleep tracker [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, the current survey represents a collaboration between laboratories focusing on fatigue science, behavioral economics, data science, and information systems. The findings from this market survey support an interdisciplinary approach to understanding what constitutes a successful digital sleep health intervention.\u003c/p\u003e\u003cp\u003eUnsurprisingly, night shift workers in this survey reported fatigue and sleep issues in relation to their work. This supports findings from previous studies and reflects a well-known safety concern with regards to working nights [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Over half of the respondents reported working a mixture of day and night shifts (68%; n\u0026thinsp;=\u0026thinsp;66). Rotating shift work is associated with worse sleep health outcomes and a higher safety risk than regular night shifts because of the ongoing need to adapt to a new schedule [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It is likely that full-time night workers and rotating or irregular night shift workers may have different sleep hygiene needs. The sample size of this dataset is insufficient to explore differences between regular night shift workers and irregular night shift workers but should be considered for future research.\u003c/p\u003e\u003cp\u003eVery few of the respondents reported sleeping for seven or more hours when working nights (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), placing them at risk for issues related to short sleep duration. Eighty percent (80%; n\u0026thinsp;=\u0026thinsp;78) of respondents agreed that they struggled with sleep (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) and every respondent in this survey reported experiencing as least one fatigue-related challenge (Fig.\u0026nbsp;2A), with \u0026ldquo;feeling fatigued during long shifts\u0026rdquo; being the most commonly reported challenge. Two-thirds of respondents (n\u0026thinsp;=\u0026thinsp;64) indicated a concern for their ability to perform (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), and approximately one-third of respondents had already reported a fatigue-related incident at work (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). It is worth noting that \u0026ldquo;reporting a fatigue-related incident\u0026rdquo; could be loosely interpreted by respondents from something as official as filing a written report to something as casual as making a verbal complaint to management. Respondents were not prompted with a definition about what constituted a fatigue report and were not asked to provide specifics about their personal experience with reporting a fatigue-related incident. This constitutes a limitation to the interpretation of the data.\u003c/p\u003e\u003cp\u003eMost of the night shift workers in this survey engaged in a number of tools or strategies to manage fatigue. These strategies can largely be classified as either pharmacological or behavioral. Caffeine was the most frequently-reported strategy for counteracting fatigue (Fig.\u0026nbsp;2B). Other pharmacological strategies included sleep aids, Adderall, marijuana, unspecified \u0026ldquo;medication\u0026rdquo;, and melatonin. Napping, sleep tracking, and meditation were common behavioral countermeasures. Recent reviews of both pharmacological interventions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] or non-pharmacological interventions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] to improve sleep or reduce sleepiness in shift workers have shown mixed evidence for the ability of any of these strategies to improve individual shift worker sleep.\u003c/p\u003e\u003cp\u003eSleep tracking was the third most common strategy reported by night shift workers as a way to manage fatigue (Fig.\u0026nbsp;2B). Respondents were not asked to specify their sleep tracking method, so responses may have included analogue tracking methods like keeping a sleep diary as well as the use of CSTs or apps. Relatedly, when asked what brand of sleep trackers they use in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, 22% (n\u0026thinsp;=\u0026thinsp;21) of respondents reported not using a CST at all, which was the second highest proportion of responses after those who reported using the Apple watch (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA; n\u0026thinsp;=\u0026thinsp;48). Sleep trackers were largely permitted in the workplace (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and the majority of night shift workers were comfortable with sharing data with their employers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Night shift workers also prioritized the ability of a sleep app to sync with their work schedule over other features (Fig.\u0026nbsp;4A). Taken together, these findings suggest an organizational-level opportunity to fill a gap in night shift workers\u0026rsquo; needs for sleep management with already available technology.\u003c/p\u003e\u003cp\u003eCost seemed to be a driver for night shift workers\u0026rsquo; interest in a sleep hygiene app. Respondents preferred a pricing model where a hypothetical app would be free compared to a one-time fee or recurring subscription (Fig.\u0026nbsp;4B) and expressed increased interest in the app if it was paid for by their employer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). These findings are in keeping with market reports that identify high cost as a barrier to economic growth for sleep technology [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and results from our previous surveys examining demand for CSTs [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In our previous survey of aviation professionals, cost was listed as a common reason for not using CSTs and even respondents who already used a CST still indicated a preference for using a device purchased by the organization over a personally-owned device for fatigue risk management purposes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A limitation to the current study is that respondents were only provided with three pricing options rather than given a purchase task survey designed to establish a demand curve representing likelihood of purchase across a series of increasing prices [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The three pricing models included in this survey (free with ads, \u003cspan\u003e$\u003c/span\u003e10 one-time fee, and \u003cspan\u003e$\u003c/span\u003e2 monthly fee) were informed by our previous behavioral economics surveys as well as by estimated market costs for continually hosting a sleep health app. However, a purchase task may have been able to pinpoint a more granular price point at which night shift workers would be most willing to use a sleep health app.\u003c/p\u003e\u003cp\u003eWhen it comes to the use of digital health technologies to improve sleep in shift workers, there is decidedly room for improvement. There is underwhelming evidence that sleep hygiene apps or other individual strategies to manage fatigue in the workplace can be effective [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This may be because interventions are rarely tested using a high-quality research design like a clinical trial, making it difficult to observe improvements [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Another suggestion made by Arroyo et al. 2022 is that making a successful behavioral change for sleep is more complex than changing diet or exercise patterns [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Sleep health apps may require a different design strategy than other mHealth apps [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOne strategy that may help successfully develop sleep health technologies specifically for shift workers is to develop an app that bridges the divide between the individual worker and their organization. It is possible that workers will be more likely to make behavioral changes if that behavior is linked to their ability to perform their job safely and is supported by their employer. Additionally, organizations may be more willing to support initiatives that can deliver objective measures of behavior, such as through the analysis of sleep data shared through the app. Developing sleep hygiene apps for organizational use may have the added benefit of reducing concerns about privacy and data-sharing. In this survey and our previous survey of aviation professionals, respondents indicated a greater willingness to share anonymous data with their employers if the technology used to collect the data was paid for by the company [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThere is a need to develop effective mHealth interventions to improve sleep hygiene in night shift workers, the majority of whom report sleep and fatigue issues in relation to work. Night shift workers in the current survey indicated a preference for organizational-level technological solutions, including rating the ability of an app to sync with their work schedule data as highly important relative to other app features, being comfortable with sharing data with their employer, and expressing more interest in using an app based on whether it was paid for by their employer or not. The findings from this survey builds upon a growing body of research aimed to incorporate behavioral economics and user preference into the conversation about how to best develop scientifically-sound technologies to improve sleep health outcomes in working populations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the professors and administrators of the University of Maryland Robert H. Smith School of Business Master of Business Administration (MBA) Technology Management Graduate Program Capstone Project for their support, mentorship, collaboration, and hard work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe dataset generated during the current study is available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAT, KEC, CJC, JC, and DB performed the research described in this paper. JKD performed the secondary data analysis and drafted the initial version of the manuscript under the supervision of SRH. All authors contributed to the editing and proofreading of the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent prior to their participation in the original study. Secondary use of de-identified data for research purposes was deemed non-human subjects research by the Salus Institutional Review Board, an independent, appropriately constituted and fully accredited institutional review board based in Austin, Texas, USA. This study was approved with exempt status by the Salus Institutional Review Board (Protocol Number UMD2025). These analyses were conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor JKD is a guest editor for the BMC Digital Health \u0026ldquo;The future of circadian and sleep health in the digital era\u0026rdquo; special collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding associated with this project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYong LC, Li J, Calvert GM (2017) Sleep-related problems in the US working population: prevalence and association with shiftwork status. Occup Environ Med 74(2):93\u0026ndash;104\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOhayon MM, Lemoine P, Arnaud-Briant V, Dreyfus M (2002) Prevalence and consequences of sleep disorders in a shift worker population. J Psychosom Res 53(1):577\u0026ndash;583\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoreno CR, Marqueze EC, Sargent C, Wright KP Jr, Ferguson SA, Tucker P (2019) Working Time Society consensus statements: Evidence-based effects of shift work on physical and mental health. Ind Health 57(2):139\u0026ndash;157\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGurubhagavatula I, Barger LK, Barnes CM, Basner M, Boivin DB, Dawson D, Drake CL, Flynn-Evans EE, Mysliwiec V, Patterson PD et al (2021) Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society. J Clin Sleep Med 17(11):2283\u0026ndash;2306\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArlinghaus A, Bohle P, Iskra-Golec I, Jansen N, Jay S, Rotenberg L (2019) Working Time Society consensus statements: Evidence-based effects of shift work and non-standard working hours on workers, family and community. Ind Health 57(2):184\u0026ndash;200\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWong IS, Dawson D, Van Dongen HP (2019) International consensus statements on non-standard working time arrangements and occupational health and safety. Ind Health 57(2):135\u0026ndash;138\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Cordova PB, Bradford MA, Stone PW (2016) Increased errors and decreased performance at night: A systematic review of the evidence concerning shift work and quality. Work 53(4):825\u0026ndash;834\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChang Q, Zhu Y, Liang H, Cheng J, Li D, Lin F, Zhou X, Pan P, Ma F, Zhang Y Night shift work associates with all-cause and cause-specific mortality: A large prospective cohort study. J Gen Intern Med 2024:1\u0026ndash;11\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRobbins R, Underwood P, Jackson CL, Jean-Louis G, Madhavaram S, Kuriakose S, Vieira D, Buxton OM (2021) A Systematic Review of Workplace-Based Employee Health Interventions and Their Impact on Sleep Duration Among Shift Workers. Workplace Health Saf 69(11):525\u0026ndash;539\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShriane AE, Rigney G, Ferguson SA, Bin YS, Vincent GE (2023) Healthy sleep practices for shift workers: consensus sleep hygiene guidelines using a Delphi methodology. Sleep 46(12)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurray JM, Magee M, Giliberto ES, Booker LA, Tucker AJ, Galaska B, Sibenaller SM, Baer SA, Postnova S, Sondag TA (2023) Mobile app for personalized sleep\u0026ndash;wake management for shift workers: A user testing trial. Digit Health 9:20552076231165972\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChinoy ED, Cuellar JA, Jameson JT, Markwald RR Performance of four commercial wearable sleep-tracking devices tested under unrestricted conditions at home in healthy young adults. Nat Sci Sleep 2022:493\u0026ndash;516\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Zambotti M, Goldstein C, Cook J, Menghini L, Altini M, Cheng P, Robillard R (2024) State of the science and recommendations for using wearable technology in sleep and circadian research. Sleep 47(4):zsad325\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLujan MR, Perez-Pozuelo I, Grandner MA (2021) Past, present, and future of multisensory wearable technology to monitor sleep and circadian rhythms. Front Digit Health 3:721919\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlobal Sleep App (2025) Market Analysis \u0026amp; Forecast: 2025\u0026ndash;2032. In\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatil C: Sleep Tech Market Size, ShareTrends Analysis Report By Product Type (Wearable Devices, Non-Wearable Devices, Sleep Aids), By Application (Sleep Monitoring and Management, Sleep Diagnostics, Therapeutic Use), By Distribution Channel (Online Retail, Offline Retail), By End-User (Residential, Commercial) and By Region(North America, Europe, APAC, Middle East and Africa, LATAM), Forecasts (2025) 2025\u0026ndash;2033. 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Sleep Health 10(2):163\u0026ndash;170\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDevine JK, Schwartz LP, Choynowski J, Hursh SR (2022) Expert Demand for Consumer Sleep Technology Features and Wearable Devices: A Case Study. IoT 3(2):315\u0026ndash;331\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDevine JK, Schwartz LP, Hursh S (2021) What do researchers want in a consumer sleep technology? Sleep 44(5)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWagstaff AS, Lie J-AS Shift and night work and long working hours-a systematic review of safety implications. Scand J Work Environ Health 2011:173\u0026ndash;185\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiira J, Verbeek JH, Costa G, Driscoll TR, Sallinen M, Isotalo LK, Ruotsalainen JH Pharmacological interventions for sleepiness and sleep disturbances caused by shift work. Cochrane Database Syst Reviews 2014(8)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHawkes RE, Sugavanam T, Benton JS, Thurley N, Kyle SD, Ray D, French DP (2025) Which individually-directed non-pharmacological interventions are effective at improving sleep outcomes in shift workers? A systematic review of systematic reviews. Sleep Med Rev :102110\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHursh SR (1980) Economic concepts for the analysis of behavior. J Exp Anal Behav 34(2):219\u0026ndash;238\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLancaster BD, Sweenie R, Noser AE, Roberts CM, Ramsey RR (2023) Sleep mHealth applications and behavior change techniques evaluation. Behav sleep Med 21(6):757\u0026ndash;773\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArroyo AC, Zawadzki MJ (2022) The implementation of behavior change techniques in mHealth apps for sleep: systematic review. JMIR mHealth uHealth 10(4):e33527\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-digital-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Digital Health](https://bmcdigitalhealth.biomedcentral.com/)","snPcode":"44247","submissionUrl":"https://submission.nature.com/new-submission/44247/3","title":"BMC Digital Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"shift work, sleep hygiene, mHealth app, consumer sleep technology","lastPublishedDoi":"10.21203/rs.3.rs-7464384/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7464384/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDigital health interventions like a sleep hygiene mobile application (app) designed specifically for night shift workers, can help improve health and on-the-job safety. Successful app development should consider user experience and economic demand in addition to sleep biology. This study reports the results of a market survey which aims to assess interest in a hypothetical sleep hygiene app designed for night shift workers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;97 night shift workers, predominantly from the healthcare industry (n\u0026thinsp;=\u0026thinsp;52), completed an anonymous online survey about their sleep habits, fatigue, technology use, perceived importance of app features, preferred pricing models, and level of comfort sharing data with employers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eRespondents reported sleeping less than 7 hours on average with frequent sleep and fatigue issues in relation to their working schedules. Respondents ranked the ability of a sleep hygiene app to sync with their work schedule as the most important app feature. Slightly under half of respondents (n\u0026thinsp;=\u0026thinsp;48) preferred a \u0026ldquo;free with ads\u0026rdquo; pricing model to one-time or recurring fees. n\u0026thinsp;=\u0026thinsp;84 respondents were interested in using a fatigue management app; n\u0026thinsp;=\u0026thinsp;93 would either be as interested or more interested if the app was paid for by their employer. The majority of respondents (n\u0026thinsp;=\u0026thinsp;78) were either neutral or comfortable with sharing sleep data with their employers.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eNight shift workers experience sleep problems and fatigue at work. Night shift workers would prefer a sleep hygiene app that takes their schedules into account and would be more likely to use an app that is either free with ads or paid for by their employer.\u003c/p\u003e","manuscriptTitle":"Night Shift Worker Sleep Habits and Demand for Fatigue Management Features in a Mobile Application","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 01:11:01","doi":"10.21203/rs.3.rs-7464384/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-21T10:05:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-18T19:31:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-30T01:37:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"63811550694067180633421986020317000971","date":"2025-09-16T22:47:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184645789014605361631504667858268111883","date":"2025-09-15T20:00:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-14T16:29:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-08T15:33:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-04T14:13:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Digital Health","date":"2025-09-04T13:44:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-digital-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Digital Health](https://bmcdigitalhealth.biomedcentral.com/)","snPcode":"44247","submissionUrl":"https://submission.nature.com/new-submission/44247/3","title":"BMC Digital Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd78154e-1ff2-4a90-a992-e9f9406bb660","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-09T15:53:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 01:11:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7464384","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7464384","identity":"rs-7464384","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}