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Examining the Feasibility of an App-based Sleep Intervention for Shiftworkers Using the RE-AIM Framework.

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Title: Examining the Feasibility of an App-based Sleep Intervention for Shiftworkers Using the RE-AIM Framework.
Authors: Thorne, Hannah (AUTHOR), Sophocleous, Rochelle M (AUTHOR), Sprajcer, Madeline (AUTHOR), Shriane, Alexandra E (AUTHOR), Duncan, Mitch J (AUTHOR), Ferguson, Sally A (AUTHOR), Vandelanotte, Corneel (AUTHOR), Kolbe-Alexander, Tracy (AUTHOR), Gupta, Charlotte C (AUTHOR), Rigney, Gabrielle (AUTHOR), Thomas, Matthew (AUTHOR), Hilditch, Cassie J (AUTHOR), Peterson, Benjamin (AUTHOR), Vincent, Grace E (AUTHOR)
Source: Behavioral Sleep Medicine. May/Jun2025, Vol. 23 Issue 3, p369-384. 16p.
Subjects: Shift systems, Wearable technology, Research protocols, Descriptive statistics, Sleep
Abstract: Objectives: This study assessed the feasibility of Sleepfit, an app-based sleep intervention for shiftworkers, to evaluate participant reach, engagement, and interaction. Methods: The RE-AIM framework guided the feasibility assessment. Participants from various shiftwork industries (e.g. healthcare, mining) completed a 14-day trial of the Sleepfit app, alongside baseline and post-intervention surveys. Descriptive statistics were used to evaluate participant enjoyment and engagement, including daily app usage and the number of activities completed. Results: Among the 110 enrolled shiftworkers, 53 (48%) completed post-intervention assessments, and 34 (30.9%) adhered to the full study protocol. Of those who completed baseline surveys, 85.4% downloaded and used Sleepfit, engaging with an average of 17.3% of available activities, with shiftwork-specific modules like "Coping with Shiftwork" showing the highest engagement. Participants cited lack of time, inconvenience, and losing interest as reasons for discontinuing app use. Conclusions: This study indicates the potential feasibility of app-based interventions like Sleepfit to improve shiftworkers' sleep health through tailored, relevant content. Future studies should consider longer durations and larger samples, incorporating wearable technology to enhance data accuracy and assess sustained effects across varied shift schedules. [ABSTRACT FROM AUTHOR]
Copyright of Behavioral Sleep Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Examining the Feasibility of an App-based Sleep Intervention for Shiftworkers Using the RE-AIM Framework.
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  Data: <searchLink fieldCode="JN" term="%22Behavioral+Sleep+Medicine%22">Behavioral Sleep Medicine</searchLink>. May/Jun2025, Vol. 23 Issue 3, p369-384. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Shift+systems%22">Shift systems</searchLink><br /><searchLink fieldCode="DE" term="%22Wearable+technology%22">Wearable technology</searchLink><br /><searchLink fieldCode="DE" term="%22Research+protocols%22">Research protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Sleep%22">Sleep</searchLink>
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  Data: Objectives: This study assessed the feasibility of Sleepfit, an app-based sleep intervention for shiftworkers, to evaluate participant reach, engagement, and interaction. Methods: The RE-AIM framework guided the feasibility assessment. Participants from various shiftwork industries (e.g. healthcare, mining) completed a 14-day trial of the Sleepfit app, alongside baseline and post-intervention surveys. Descriptive statistics were used to evaluate participant enjoyment and engagement, including daily app usage and the number of activities completed. Results: Among the 110 enrolled shiftworkers, 53 (48%) completed post-intervention assessments, and 34 (30.9%) adhered to the full study protocol. Of those who completed baseline surveys, 85.4% downloaded and used Sleepfit, engaging with an average of 17.3% of available activities, with shiftwork-specific modules like "Coping with Shiftwork" showing the highest engagement. Participants cited lack of time, inconvenience, and losing interest as reasons for discontinuing app use. Conclusions: This study indicates the potential feasibility of app-based interventions like Sleepfit to improve shiftworkers' sleep health through tailored, relevant content. Future studies should consider longer durations and larger samples, incorporating wearable technology to enhance data accuracy and assess sustained effects across varied shift schedules. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behavioral Sleep Medicine is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        Type: general
      – SubjectFull: Wearable technology
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      – SubjectFull: Research protocols
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      – SubjectFull: Descriptive statistics
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              Text: May/Jun2025
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