Impact of an Online Discussion Forum on Self-Guided Internet-Delivered Cognitive Behavioral Therapy for Public Safety Personnel: Randomized Trial
Notice bibliographique
Résumé
BACKGROUND: Internet-delivered cognitive behavioral therapy (ICBT) is an effective and accessible treatment for various mental health concerns. ICBT has shown promising treatment outcomes among public safety personnel (PSP), who experience high rates of mental health problems and face barriers to accessing other mental health services. Client engagement and clinical outcomes are better in ICBT with therapist guidance, but ICBT is easier to implement on a large scale when it is self-guided. Therefore, it is important to identify strategies to improve outcomes and engagement in self-guided ICBT and other self-guided digital mental health interventions. One such strategy is the use of online discussion forums to provide ICBT clients with opportunities for mutual social support. Self-guided interventions accompanied by online discussion forums have shown excellent treatment outcomes, but there is a need for research experimentally testing the impact of online discussion forums in ICBT. OBJECTIVE: We aimed to evaluate a transdiagnostic, self-guided ICBT intervention tailored specifically for PSP (which had not previously been assessed), assess the impact of adding a therapist-moderated online discussion forum on outcomes, and analyze participants' feedback to inform future research and implementation efforts. METHODS: In this randomized trial, we randomly assigned participating PSP (N=107) to access an 8-week transdiagnostic, self-guided ICBT course with or without a built-in online discussion forum. Enrollment and participation were entirely web-based. We assessed changes in depression, anxiety, and posttraumatic stress as well as several secondary outcome measures (eg, treatment engagement and satisfaction) using questionnaires at the pre-enrollment, 8-week postenrollment, and 20-week postenrollment time points. Mixed methods analyses included multilevel modeling and qualitative content analysis. RESULTS: Participants engaged minimally with the forum, creating 9 posts. There were no differences in treatment outcomes between participants who were randomly assigned to access the forum (56/107, 52.3%) and those who were not (51/107, 47.7%). Across conditions, participants who reported clinically significant symptoms during enrollment showed large and statistically significant reductions in symptoms (P<.05 and d>0.97 in all cases). Participants also showed good treatment engagement and satisfaction, with 43% (46/107) of participants fully completing the intervention during the course of the study and 96% (79/82) indicating that the intervention was worth their time. CONCLUSIONS: Previous research has shown excellent clinical outcomes for self-guided ICBT accompanied by discussion forums and good engagement with those forums. Although clinical outcomes in our study were excellent across conditions, engagement with the forum was poor, in contrast to previous research. We discuss several possible interpretations of this finding (eg, related to the population under study or the design of the forum). Our findings highlight a need for more research evaluating the impact of online discussion forums and other strategies for improving outcomes and engagement in self-guided ICBT and other digital mental health interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05145582; https://clinicaltrials.gov/study/NCT05145582.
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 | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,002 |
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 ».