Exploring Counselor Practices and Risk Assessment in a Proactive Digital Intervention Through Instagram in Young People: Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: Suicide is one of the leading causes of preventable death in young people, and the way young people are communicating suicidality has evolved to include web-based disclosures and help-seeking. To date, mental health intervention services, both on the web and in person, have been conceived in the traditional model, whereby support is provided if a young person (or their family) actively seeks out that support when distressed. On the other hand, proactive outreach is an innovative approach to intervention that has been shown to be effective in other areas of health care. Live for Tomorrow chat was delivered on Instagram and comprised of counselors who reach out to provide brief person-centered intervention to young people who post content indicating distress or suicidality. OBJECTIVE: Our aim was to explore how counselors engaged young people in a proactive digital intervention and how risk assessment was conducted in this context. METHODS: We analyzed 35 transcripts of conversations between counselors and young people aged 13-25 years using the 6-step approach of Braun and Clarke's reflexive thematic analysis. These transcripts included a counseling intervention and a follow-up chat that was aimed at collecting feedback about the counseling intervention. RESULTS: A total of 7 themes emerged: using microskills to facilitate conversations, building confidence and capacity to cope with change, seeking permission when approaching conversations about suicidality or self-harm, conversations about suicidality following a structured approach, providing assurances of confidentiality, validation of the experience of suicidality, and using conversations about suicidality to identify interventions. Counselors were able to translate counseling microskills and structured questioning regarding suicidality into a digital context. In particular, in the digital context, counselors would use the young person's post and emojis to further conversations and build rapport. CONCLUSIONS: The findings highlight the importance of the counselor's role to listen, empathize, validate, and empower young people and that all these skills can be transferred to a digital text counseling intervention. Counselors used a structured approach to understanding suicidality in a permission-seeking, validating, and confidential manner to identify interventions with the young person. These practices allowed the conversation to move beyond traditional risk assessment practices to meaningful conversations about suicidality. Moving beyond traditional risk assessment practices and into conversations about suicidality allowed for the validation of the young person's experience and exploration of interventions and support that made sense and were seen to be helpful to the young person. This study highlighted the benefits of a proactive digital chat-based intervention, which is a novel approach to engaging with young people experiencing psychological distress and suicidality. Furthermore, this research demonstrates the feasibility and benefit of moving mental health intervention and support to a medium where young people are currently disclosing distress and intervening proactively.
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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 | 0,010 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».