Promoting Engagement With Smartphone Apps for Suicidal Ideation in Young People: Development of an Adjunctive Strategy Using a Lived Experience Participatory Design Approach
Notice bibliographique
Résumé
BACKGROUND: Suicide among young people is a worrying public health concern. Despite this, there is a lack of suitable interventions aligned with the needs of this priority population. Emerging evidence supports the effectiveness of digital interventions in alleviating the severity of suicidal thoughts. However, their efficacy may be undermined by poor engagement. Technology-supported strategies (eg, electronic prompts and reminders) have been deployed alongside digital interventions to increase engagement with the latter. However, evidence of their efficacy is inconclusive. User-centered design approaches may be key to developing feasible and effective engagement strategies. Currently, no study has been published on how such an approach might be expressly applied toward developing strategies for promoting engagement with digital interventions. OBJECTIVE: This study aimed to detail the processes and activities involved in developing an adjunctive strategy for promoting engagement with LifeBuoy-a smartphone app that helps young people manage suicidal thoughts. METHODS: Development of the engagement strategy took place in 2 phases. The discovery phase aimed to create an initial prototype by synthesizing earlier findings-from 2 systematic reviews and a cross-sectional survey of the broader mental health app user population-with qualitative insights from LifeBuoy users. A total of 16 web-based interviews were conducted with young people who participated in the LifeBuoy trial. Following the discovery phase, 3 interviewees were invited by the research team to take part in the workshops in the design phase, which sought to create a final prototype by making iterative improvements to the initial prototype. These improvements were conducted over 2 workshops. Thematic analysis was used to analyze the qualitative data obtained from the interviews and workshops. RESULTS: Main themes from the interviews centered around the characteristics of the strategy, timing of notifications, and suitability of social media platforms. Subsequently, themes that emerged from the design workshops emphasized having a wider variety of content, greater visual consistency with LifeBuoy, and a component with more detailed information to cater to users with greater informational needs. Thus, refinements to the prototype were focused on (1) improving the succinctness, variety, and practical value of Instagram content, (2) creating a blog containing articles contributed by mental health professionals and young people with lived experience of suicide, and (3) standardizing the use of marine-themed color palettes across the Instagram and blog components. CONCLUSIONS: This is the first study to describe the development of a technology-supported adjunctive strategy for promoting engagement with a digital intervention. It was developed by integrating perspectives from end users with lived experience of suicide with evidence from the existing literature. The development process documented in this study may be useful for guiding similar projects aimed at supporting the use of digital interventions for suicide prevention or mental health.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».