Web-based Therapy Plus Support by a Coach in Depressed Patients Referred to Secondary Mental Health Care: Randomized Controlled Trial
Notice bibliographique
Résumé
Background The evidence for the effectiveness of Web-based therapies comes mainly from nonclinical populations, with a few studies in primary care. There is little evidence from patients referred to secondary mental health care with depression. Adherence to Web-based therapies is often poor. One way to increase this is to create a new health service role of a coach to guide people through the therapy. Objective This study aimed to test in people referred to secondary care with depression if a Web-based therapy (The Journal) supported by a coach plus usual care would be more effective in reducing depression compared with usual care plus an information leaflet about Web-based resources after 12 weeks. Methods We conducted a randomized controlled trial with two parallel arms and a process evaluation that included structured qualitative interviews analyzed using thematic analysis. The coach had a background in occupational therapy. Participants were recruited face-to-face at community mental health centers. Results We recruited 63 people into the trial (intervention 35, control 28). There were no statistically significant differences in the change from baseline in Patient Health Questionnaire-9 (PHQ-9) scores at 12 weeks comparing The Journal with usual care (mean change in PHQ-9 score 9.4 in the intervention group and 7.1 in the control group, t41=1.05, P=.30; mean difference=2.3, 95% CI −2.1 to 6.7). People who were offered The Journal attended on average about one less outpatient appointment compared with usual care, although this difference was not statistically significant (intervention mean number of visits 2.8 (SD 5.5) compared with 4.1 (SD 6.7) in the control group, t45=−0.80, P=.43; mean difference=1.3, 95% CI −4.5 to 2.0). The process evaluation found that the mean number of lessons completed in the intervention group was 2.5 (SD=1.9; range=0-6) and the number of contacts with the coach was a mean of 8.1 (SD=4.4; range=0-17). The qualitative interviews highlighted the problem of engaging clinicians in research and their resistance to recruitment: technical difficulties with The Journal, which prevented people logging in easily; difficulty accessing The Journal as it was not available on mobile devices; participants finding some lessons difficult; and participants saying they were too busy to complete the sessions. Conclusions The study demonstrated that it is feasible to use a coach in this setting, that people found it helpful, and that it did not conflict with other care that participants were receiving. Future trials need to engage clinicians at an early stage to articulate where Web-based therapies fit into existing clinical pathways; Web-based therapies should be available on mobile devices, and logging in should be easy. The role of the coach should be explored in larger trials. Trial Registration Australian New Zealand Clinical Trials Registry (ACTRN): 12613000015741; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=363351&isReview=true (Archived by WebCite at http://www.webcitation.org/6wEyCc6Ss).
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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».