A Spiritual Self-Care Mobile App (Skylight) for Mental Health, Sleep, and Spiritual Well-Being Among Generation Z and Young Millennials: Cross-Sectional Survey
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».