Automated Virtual Reality Cognitive Therapy for People With Psychosis: Protocol for a Qualitative Investigation Using Peer Research Methods
Notice bibliographique
Résumé
BACKGROUND: Many people with psychosis experience difficulties in everyday social situations. Anxiety can make life challenging, leading to withdrawal. Cognitive therapy, using active in vivo learning, enables people to overcome fears. These treatments are not readily available to people with psychosis. Automated virtual reality (VR) therapy is a potential route to increase accessibility. The gameChange automated VR cognitive therapy is designed to help people overcome anxious avoidance and build confidence in everyday social situations. A virtual coach guides the person through the treatment. Understanding user experience is key to facilitating future implementation. Peer research methods, in which people with lived experience of the issues being studied are involved in collecting and analyzing data, may be useful in developing this understanding. This encourages researchers to draw on their lived experience to explore participant perspectives and co-create knowledge. OBJECTIVE: The primary objective is to use a peer research approach to explore the participant experience of a novel automated VR therapy for anxious social avoidance. This includes understanding (1) the experience of anxious social avoidance in people with psychosis, (2) the experience of the gameChange automated VR cognitive therapy, and (3) any potential impact of the therapy in people's lives. This will inform future implementation strategies. The secondary objective is to explore how peer research can be used to co-create knowledge. METHODS: Semistructured interviews will be conducted with approximately 25 people with psychosis participating in the gameChange trial (ISRCTN17308399). Participants will be recruited from the five trial centers based in National Health Service mental health trusts across England. Interviews will be conducted by two researchers. One is a peer researcher with similar lived experience to the trial participants. The other has lived experiences of mental health issues that do not directly overlap with those of the trial participants. Interview questions will focus on an individual's experience of anxious social avoidance, experiences of participating in the gameChange VR therapy, and any changes or impact following therapy. The interview schedule was developed in collaboration with the gameChange Lived Experience Advisory Panel (LEAP), comprising 10 project advisors with lived experience of psychosis. Interpretative phenomenological analysis and template analysis will be used to explore individual accounts. The LEAP will contribute to the analysis. RESULTS: Data collection will be conducted from April to September 2021, and analysis will be conducted from June to October 2021. As of September 28, 2021, 20 participants had been interviewed, and coding is underway. CONCLUSIONS: The study, employing a peer research approach, may provide a unique insight into the experiences of anxious social avoidance in people with psychosis and its treatment using automated VR therapy. This will inform potential future implementation of VR automated therapies in mental health services. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31742.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,076 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,006 | 0,006 |
| Intégrité de la recherche | 0,005 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,056 | 0,009 |
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 ».