An e-Coaching Intervention for Family Carers to Enhance Well-Being and Resilience Through Self-Help Strategies: Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
Background: Family carers of older adults often experience significant mental health challenges, including anxiety and depression. Although online coaching interventions have been found to reduce anxiety and depressive symptoms in carers, only a few studies have examined the broader impact of applying online self-help interventions for enhancing resilience and overall well-being in carers. This study evaluates the effectiveness of a self-directed e-coaching intervention for family carers of older adults aimed at reducing anxiety and depressive symptoms, while also assessing its impact on enhancing their resilience and overall well-being, particularly for those with mild levels of carer needs. Objective: This study aims to evaluate the effectiveness of a self-directed e-coaching intervention in reducing symptoms of anxiety and depression among carers of older adults using the 7-Item Generalized Anxiety Disorder Scale (GAD-7) and 9-Item Patient Health Questionnaire (PHQ-9), respectively, and also to examine secondary outcomes to determine its broader impact, including improvement in the level of carer needs, quality of life, caregiving burden, self-care efficacy, and resilience. Methods: This is a 3-arm randomized controlled trial that involves family carers of older adults living in Hong Kong, who will be randomly assigned to one of the e-coaching intervention groups or the control group through an online platform. The e-coaching intervention will consist of structured modules for self-directed learning on lifestyle intervention, family relationships, and emotion regulation. Participants in the intervention groups will either receive full content or partial content tailored to their caregiving needs. A total of 240 participants will complete the GAD-7 and PHQ-9 assessments at baseline, postintervention, and at a 3-month follow-up to evaluate changes in anxiety and depression scores. Secondary outcome measures will include standardized measurements assessing the level of carer needs, quality of life, caregiving burden, self-care efficacy, and resilience. It is hypothesized that participants in both e-coaching intervention groups will demonstrate a statistically significant reduction in anxiety and depressive symptoms at both postintervention and 3-month follow-ups compared to the control group, in terms of reductions in GAD-7 and PHQ-9 scores. Results: This randomized trial was funded for an original project period from January 2023 to January 2028. The enrollment commenced in April 2025 and is ongoing, with the expectation of closing enrollment in May 2026. We anticipate that data analyses will be completed by September 2026. Conclusions: The anticipated findings from this study could provide valuable insights into the potential of e-coaching as an accessible self-help intervention for improving mental health outcomes among carers of older adults, particularly those classified with mild levels of carer needs. If successful, this self-directed approach may offer a scalable solution to alleviate psychological distress and enhance overall well-being and resilience in this vulnerable population. The results will inform future mental health strategies and interventions tailored for carers, ultimately fostering a healthier caregiving environment.
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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 | 0,025 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,012 | 0,007 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,096 | 0,012 |
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 ».