Promoting Social Participation and Recovery Using Virtual Reality–Based Interventions Among People With Mental Health and Substance Use Disorders: Qualitative Study
Notice bibliographique
Résumé
BACKGROUND: People with mental health disorders (MHDs) and substance use disorders (SUDs) are a highly vulnerable group, particularly affected by social exclusion, marginalization, and disconnectedness. Virtual reality technology holds a potential for simulating social environments and interactions to mitigate the social barriers and marginalization faced by people recovering from MHDs and SUDs. However, it is still unclear how we can harness the greater ecological validity of virtual reality-based interventions targeting social and functional impairments in individuals with MHDs and SUDs. OBJECTIVE: The aim of this paper was to explore how service providers in community-based MHD and SUD health care services perceive the barriers to social participation among adults recovering from MHDs and SUDs to provide a broader understanding of how learning experiences can be modeled to promote social participation in virtual reality environments. METHODS: Two semistructured, open-ended, and dual-moderator focus group interviews were conducted with participants representing different community-based MHD and SUD health care services. Service providers were recruited from their MHD and SUD services in our collaborating municipality in Eastern Norway. We recruited the first participant group at a municipal MHD and SUD assisted living facility for service users with ongoing excessive substance use and severe social dysfunctionality. We recruited the second participant group at a community-based follow-up care service aimed at clients with a broad range of MHDs and SUDs and various levels of social functioning. The qualitative data extracted in the interviews were analyzed, using reflexive thematic analysis. RESULTS: The analysis of the service providers' perceptions of the barriers to social participation among clients with MHDs and SUDs revealed the following five main themes: challenging or lacking social connections, impaired cognitive functions, negative self-perception, impaired personal functioning, and insufficient social security. The barriers identified are interrelated in a cluster of cognitive, socioemotional, and functional impairments, leading to a severe and diverse complex of barriers to social participation. CONCLUSIONS: Social participation relies on people's capability to use their present social opportunities. Promoting basic human functioning is key to promoting social participation among people with MHDs and SUDs. The findings in this study indicate a need to address cognitive functioning, socioemotional learning, instrumental skills, and complex social functions to meet the complexity and diversity of the identified barriers to social functioning in our target group. Virtual reality-based interventions for promoting social participation should be sequenced into distinct scenarios dedicated to specific learning goals to build complex learning in a step-by-step process based on successively more complex levels of human and social functioning.
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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 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,006 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 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 ».