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Skip search results from other journals and go to results- 51 JMIR Formative Research
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Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis
The measures and domains assessed in the app include (1) social support, using 3 items from the Schuster Social Support Scale [24]; (2) personal functioning, using 3 items about educational and employment engagement and achievement [25]; (3) psychological distress, using the K6 (Kessler-6) scale for psychological distress [26]; (4) sleep, using 4 sleep items, including feeling refreshed after sleep, trouble falling asleep, and subjective energy [27]; (5) physical activity, 4 items from the International Physical
J Med Internet Res 2025;27:e71305
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These can include vasomotor symptoms (VMS) such as hot flashes (sudden, temporary onset of warmth in the body, flushing, and sweating) and night sweats (episodes of excessive sweating that happen during sleep), as well as depression, anxiety, and sleep disturbances [3]. In the United States, approximately 6000 women transition into menopause each day, many of whom face these challenges for years before and after menopause [4].
JMIR Mhealth Uhealth 2025;13:e58204
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Therefore, CWs can track vital parameters and behaviors, such as heart rate, physical activity (PA), or sleep [1].
The usage of CWs in the population has increased enormously within the last decade. In 2022, around 500 million of these devices were sold worldwide, which means that the sales increased by the factor 16 compared with 2014 [2]. In Germany, 7.2 million CWs were sold in 2022 [3].
JMIR Mhealth Uhealth 2025;13:e59199
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Data were collected on daily activity (number of steps) and sleep.
Fitbit data were obtained via the Fitbit API, which provides preprocessed JSON files reflecting proprietary algorithms for step counting and sleep [50]. For sleep, each participant had one JSON file that spanned the duration of the study, which included a sleep log with timestamps for sleep onset and offset and a breakdown of sleep stages (eg, light, rapid eye movement [REM], deep).
JMIR Form Res 2025;9:e66187
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Poor sleep quality is another common observance among postsecondary students [16], with conditions such as delayed sleep phase syndrome being 50% more prevalent among postsecondary students compared to the general population [17]. A distinctive combination of social, work, and academic pressures renders this population particularly susceptible to poor sleep quality [18,19].
JMIR Form Res 2025;9:e66131
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Calls and screen use were event-based sensor streams, whereas location, heart rate, sleep, and steps were time series sensor streams. We sampled location coordinates at 1 sample per 10 minutes and heart rate, sleep, and steps at 1 sample per minute.
Throughout the study duration, the mobile app alerted and directed participants 3 times a day to complete a brief EMA survey within the app.
J Med Internet Res 2025;27:e70871
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Sleep disturbances such as insomnia, fragmented sleep, daytime sleepiness, and sleep-disordered breathing are common features of Alzheimer disease (AD) and Lewy body disease (LBD) and often appear early in the disease course and before clinical diagnosis [1,2].
JMIR Aging 2025;8:e72824
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To further personalize the experience of Aspire2 B, participants were encouraged to answer more questions covering aspects like sleep quality, physical activity, and dietary intake, although these were not mandatory (refer to Optional Onboarding Questions section). From these responses, subjects were assigned to one of three challenges, that are (1) nutrition, (2) movement, (3) sleep based on set criteria (eg, those reporting poor sleep quality were placed in sleep challenge).
JMIR Form Res 2025;9:e63471
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In this study, poorer SDM was linked to having greater sleep apnea severity for older adults without MCI. In contrast, for those with MCI, poorer performance was associated with decreased sleep spindle duration and smaller hippocampal subfield size. As various age-related sleep changes occur both naturally [7] and with neurodegenerative diseases [8,9], it is crucial to understand how these alterations impact SDM.
JMIR Aging 2025;8:e68147
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Based on this, we hypothesize that internet use may be associated with a reduced risk of sleep problems, including poor sleep quality and abnormal sleep duration, in middle-aged and older adults. To test this hypothesis, we examined both cross-sectional and longitudinal associations between internet use or internet frequency and sleep quality, as well as between internet use or internet frequency and sleep duration.
J Med Internet Res 2025;27:e71030
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