The Usability, Feasibility, Acceptability, and Efficacy of Digital Mental Health Services in the COVID-19 Pandemic: Scoping Review, Systematic Review, and Meta-analysis
Notice bibliographique
Résumé
BACKGROUND: After the rapid spread of the novel SARS-CoV-2, the short-term and long-term mental health impacts of the pandemic on the public, in particular on susceptible individuals, have been reported worldwide. Although digital mental health services expand accessibility while removing many barriers to in-person therapy, their usability, feasibility, acceptability, and efficacy require continued monitoring during the initial phase of the pandemic and its aftermath. OBJECTIVE: In this study, we aimed to understand what mental health services are offered, whether they are practical or acceptable, and to what extent digital mental health services are effective in response to the COVID-19 pandemic across high-income and low- and middle-income countries. METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline. We implemented searches in PubMed (MEDLINE), Embase, PsycINFO, and Cochrane databases for studies that were published between December 2019 and November 2021 and that involved the use of digital mental health services. Two review authors screened, assessed, and extracted studies independently. The protocol was registered on the International Prospective Register of Systematic Reviews. RESULTS: This review identified 7506 articles through database searching. In total, 65 (0.9%) studies from 18 countries with 67,884 participants were eligible for the scoping review. Of the 65 studies, 16 (24.6%) were included in the meta-analysis. A total of 15 (23.1%) studies measured the usability; 31 (47.7%) studies evaluated the feasibility; 29 (44.6%) studies assessed the acceptability; and 51 (78.5%) studies assessed the efficacy. Web-based programs (21/65, 32.3%), videoconferencing platforms (16/65, 24.6%), smartphone apps (14/65, 21.5%), and SMS text messaging (5/65, 7.7%) were the main techniques. Psychotherapy (44/65, 67.7%) followed by psychoeducation (6/65, 9.2%) and psychological support (5/65, 7.7%) were commonly used. The results of the meta-analysis showed that digital mental health interventions were associated with a small reduction in depressive symptoms (standardized mean difference=-0.49; 95% CI -0.74 to -0.24; P<.001) and a moderate reduction in anxiety symptoms (standardized mean difference=-0.66; 95% CI -1.23 to -1.0; P=.02) significantly. CONCLUSIONS: The findings suggest that digital mental health interventions may be practical and helpful for the general population, at-risk individuals, and patients with preexisting mental disorders across high-income and middle-income countries. An expanded research agenda is needed to apply different strategies for addressing diverse psychological needs and develop integrated mental health services in the post-COVID-19 era. TRIAL REGISTRATION: PROSPERO CRD42022307695; https://tinyurl.com/2jcuwjym.
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 | 0,058 | 0,182 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,024 | 0,032 |
| Bibliométrie | 0,014 | 0,016 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».