Exploring Mental Health Professionals’ Perspectives of Text-Based Online Counseling Effectiveness With Young People: Mixed Methods Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Population-based studies show that the risk of mental ill health is highest among young people aged 10 to 24 years, who are also the least likely to seek professional treatment because of a number of barriers. Electronic mental (e-mental) health services have been advocated as a method for decreasing these barriers for young people, among which text-based online counseling (TBOC) is a primary intervention used at many youth-oriented services. Although TBOC has shown promising results, its outcome variance is greater in comparison with other electronic interventions and adult user groups. OBJECTIVE: This pilot study aimed to explore and confirm e-mental health professional's perspectives about various domains and themes related to young service users' (YSUs) motivations for accessing TBOC services and factors related to higher and lower effectiveness on these modalities. METHODS: Participants were 9 e-mental health professionals who were interviewed individually and in focus groups using a semistructured interview. Thematic analysis of qualitative themes from interview transcripts was examined across the areas of YSU motivations for access and factors that increase and decrease TBOC effectiveness. RESULTS: A total of 4 domains and various subthemes were confirmed and identified to be related to YSUs' characteristics, motivations for accessing TBOC, and moderators of service effectiveness: user characteristics (ie, prior negative help-seeking experience, mental health syndrome, limited social support, and perceived social difficulties), selection factors (ie, safety, avoidance motivation, accessibility, and expectation), and factors perceived to increase effectiveness (ie, general therapeutic benefits, positive service-modality factors, and persisting with counseling despite substantial benefit) and decrease effectiveness (ie, negative service-modality factors). CONCLUSIONS: Participants perceived YSUs to have polarized expectations of TBOC effectiveness and be motivated by service accessibility and safety, in response to several help-seeking concerns. Factors increasing TBOC effectiveness were using text-based communication, the online counselor's interpersonal skills and use of self-management and crisis-support strategies, and working with less complex presenting problems or facilitating access to more intensive support. Factors decreasing TBOC effectiveness were working with more complex problems owing to challenges with assessment, the slow pace of text communication, lack of nonverbal conversational cues, and environmental and connectivity issues. Other factors were using ineffective techniques (eg, poor goal setting, focusing, and postcounseling direction) that produced only short-term outcomes, poor timeliness in responding to service requests, rupture in rapport from managing service boundaries, and low YSU readiness and motivation.
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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 | 0,016 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| 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 ».