Abstract Introduction Self-efficacy scales are useful predictors of behavioral outcomes. In sleep, Lacks proposed a first self-efficacy scale in 1987 which has been widely studied. Recognizing the need for an updated instrument to address modern lifestyle and technology constraints, we developed the Sleep Efficacy for Sleep Health (SE4SH), a novel 24-item questionnaire assessing perceived confidence in controlling sleep-related factors and behaviors (e.g., caffeine intake, exercise timing). Methods Users of Fitbit wearables were invited to participate in an IRB-approved, 4-week-long assessment of sleep under normal free-living conditions in early 2025. At the onset of the trial, users were asked to complete the SE4SH questionnaire as implemented within the Fitbit mobile app. Basic demographic information was recorded, as well as wearable reported sleep parameters over the duration of the study. Psychometric assessment was based on a set of hypothesized five underlying factors (F1–F5) - (F1) diet and substance intake, (F2) exercise and light exposure, (F3) schedule and routine control, (F4) knowledge in dealing with sleep problems, and (F5) technology/environment control. Psychometric performance was assessed with Cronbach’s α, and convergent and discriminant validity of the identified factors. Results 3453 unique users completed the surveys and reported valid demographic data (F=2468/M=981/Other=3, age=50.3±13.7, BMI 28.8±6.2). The average raw score reported on the SE4SH questionnaire was 75.9 (on a 24-120 scale). Men reported a higher raw score than women (78.3 vs 74.9, p 0.05, Cohen’s d = 0.2). Raw scores were highest on efficacy around alcohol/caffeine choices, with lowest scores on knowing how to address difficulty staying asleep. The overall survey had Cronbach’s α of 0.945 (individual component αs: 0.65-0.93). Discriminant validity was also good, with inter-group correlations ranging from 0.42-0.78, illustrating that the groupings reflected distinct aspects of self-efficacy. Conclusion The Sleep Efficacy for Sleep Health (SE4SH) is a promising novel 24-item survey that captures aspects of a person’s beliefs about their confidence in controlling sleep-related factors and behaviors, and has been demonstrated to have appropriate psychometric properties in an initial deployment with users. Support (if any) This research was supported by Google.
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Heneghan et al. (Fri,) studied this question.
synapsesocial.com/papers/6a002191c8f74e3340f9c8a3 — DOI: https://doi.org/10.1093/sleep/zsag091.0190
Conor Heneghan
Cross-Cutting Cardiology
Logan Schneider
Google (United States)
Hamsa Subramaniam
Google (United States)
SLEEP
Google (United States)
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