Characteristics Associated With the Use of the Mindfulness Meditation App Headspace in a Large Public Health Deployment: Cross-Sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: Mindfulness-based apps can be an effective and accessible resource for mental health support. However, little is known about their use outside of research settings and what user characteristics relate to app use. OBJECTIVE: This study aimed to examine the characteristics of people who decided to use, not use, or stop using Headspace within the context of a large-scale public deployment, which offered the mindfulness meditation app Headspace as a free mental health resource to community members. METHODS: Nearly 100,000 community members received Headspace. All members (N=92,311) received an email inviting them to complete a voluntary and uncompensated survey. In total, 2725 participants completed the survey. The 20-minute survey asked about the use of Headspace, user experience, mental health problems, mental health stigma, and mental health use. Logistic regression models were used to examine relationships between predictors and nonuse, past use, or current use of Headspace. RESULTS: Participants who were still using Headspace at the time of completing the survey (2076/2725, 76.18%) were more likely to experience mental health challenges and distress and make more use of other digital mental health resources (ie, online tools and connecting with people online) than people who were not using Headspace. In addition, current users of Headspace rated the app higher on user experience compared with past users. The most common reasons for abandoning Headspace were that people were already using other strategies to support their mental health (198/570, 34.7%), no longer needed Headspace (73/570, 12.8%), or did not think Headspace was useful (46/570, 8.1%). CONCLUSIONS: Results indicate that a person's mental health challenges, a perceived need for support, and familiarity with digital resources were associated with continued use of Headspace. While the most common reason for not using Headspace was that people were already using other resources, it is important to consider the continuity of mental health support beyond these free programs for those who may not have easy access to other resources. We discuss potential implications of our findings for offering and using apps such as Headspace as a mental health resource, along with factors that influence engagement with this app.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».