Layperson-Facilitated Internet-Delivered Cognitive Behavioral Therapy for Homebound Older Adults With Depression: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Depression in older adults has serious biological, psychological, and social consequences. Homebound older adults experience a high burden of depression and significant barriers to accessing mental health treatments. Few interventions to address their specific needs have been developed. Existing treatment modalities can be challenging to scale up, are not tailored to unique population concerns, and require significant staffing support. Technology-assisted, layperson-facilitated psychotherapy has the potential to overcome these challenges. OBJECTIVE: The aim of this study is to assess the efficacy of a layperson-facilitated internet-delivered cognitive behavioral therapy program tailored for homebound older adults. The novel intervention, Empower@Home, was developed based on user-centered design principles and partnerships between researchers, social service agencies, care recipients, and other stakeholders serving low-income homebound older adults. METHODS: This 2-arm, 20-week pilot randomized controlled trial (RCT) with a waitlist control crossover design aims to enroll 70 community-dwelling older adults with elevated depressive symptoms. The treatment group will receive the 10-week intervention immediately, whereas the waitlist control group will cross over and receive the intervention after 10 weeks. This pilot is part of a multiphase project involving a single-group feasibility study (completed in December 2022). This project consists of a pilot RCT (described in this protocol) and an implementation feasibility study running in parallel with the pilot RCT. The primary clinical outcome of the pilot is the change in depressive symptoms after the intervention and at the 20-week postrandomization follow-up. Additional outcomes include acceptability, adherence, and changes in anxiety, social isolation, and quality of life. RESULTS: Institutional review board approval was obtained for the proposed trial in April 2022. Recruitment for the pilot RCT began in January 2023 and is anticipated to end in September 2023. On completion of the pilot trial, we will examine the preliminary efficacy of the intervention on depression symptoms and other secondary clinical outcomes in an intention-to-treat analysis. CONCLUSIONS: Although web-based cognitive behavioral therapy programs are available, most programs have low adherence and very few are tailored for older adults. Our intervention addresses this gap. Older adults, particularly those with mobility difficulties and multiple chronic health conditions, could benefit from internet-based psychotherapy. This approach can serve a pressing need in society while being cost-effective, scalable, and convenient. This pilot RCT builds on a completed single-group feasibility study by determining the preliminary effects of the intervention compared with a control condition. The findings will provide a foundation for a future fully-powered randomized controlled efficacy trial. If our intervention is found to be effective, implications extend to other digital mental health interventions and populations with physical disabilities and access restrictions who face persistent disparities in mental health. TRIAL REGISTRATION: ClinicalTrials.gov NCT05593276; https://clinicaltrials.gov/ct2/show/NCT05593276. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/44210.
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 | 0,035 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,004 |
| Méta-épidémiologie (sens large) | 0,013 | 0,007 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,094 | 0,014 |
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 ».