A Spiritual Self-Care Mobile App (Skylight) for Mental Health, Sleep, and Spiritual Well-Being Among Generation Z and Young Millennials: Cross-Sectional Survey
Bibliographic record
Abstract
BACKGROUND: Generation Z (Gen Z) and young millennials (GenZennials) (ages 18-35 years) are unique in that they either have no memory of or were born shortly after the internet "explosion." They are constantly on the internet, face significant challenges with their mental health and sleep, and are frequent users of digital wellness apps. GenZennials also uniquely identify with and practice spirituality, which has been linked to better mental health and sleep in adult populations. Research has not examined digital approaches to spiritual self-care and its relationship to mental health and sleep in GenZennials. OBJECTIVE: The purpose of this study was to describe a sample of adult GenZennials who use a spiritual self-care app (ie, Skylight), describe how users engage with and perceive the app, and assess the relationship between frequency of using the app with mental health, sleep, and spiritual well-being. METHODS: Participants were 475 adult Gen Z (ages 18-28 years) and young millennial (ages 29-35 years) Skylight app users who responded to an anonymous survey on the web. The survey asked about demographics, spiritual self-care and practice, and user engagement and perceptions of the app. Outcome measures included 4 validated surveys for mental health (ie, depression, anxiety, and stress) and sleep disturbance, and one validated survey on spiritual well-being. Mean scores were calculated for all measures, and linear regressions were conducted to examine the relationship between the frequency of app use and mental health, sleep, and spiritual well-being outcomes. RESULTS: Participants were predominantly White (324/475, 68.2%) and female (255/475, 53.7%), and approximately half Gen Z (260/475, 54.5%) and half young millennials (215/475, 45.3%). Most users engaged in spiritual self-care (399/475, 84%) and said it was important or very important to them (437/475, 92%). Users downloaded the app for spiritual well-being (130/475, 30%) and overall health (125/475, 26.3%). Users had normal, average depressive symptoms (6.9/21), borderline abnormal anxiety levels (7.7/21), slightly elevated stress (6.7/16), and nonclinically significant sleep disturbance (5.3/28). Frequency of app use was significantly associated with lower anxiety (Moderate use: β=-2.01; P=.02; high use: β=-2.58; P<.001). There were no significant relationships between the frequency of app use and mental health, sleep, and spiritual well-being outcomes except for the personal domain of spiritual well-being. CONCLUSIONS: This is the first study to describe a sample of adult GenZennials who use a spiritual self-care app and examine how the frequency of app use is related to their mental health, sleep, and spiritual well-being. Spiritual self-care apps like Skylight may be useful in addressing anxiety among GenZennials and be a resource to spiritually connect to their personal spiritual well-being. Future research is needed to determine how a spiritual self-care app may benefit mental health, sleep, and spiritual well-being in adult GenZennials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".