A Mobile App–Based Intervention Program for Nonprofessional Caregivers to Promote Positive Mental Health: Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: While nonprofessional caregivers often experience a sense of fulfillment when they provide care, there is also a significant risk of emotional and physical burnout. Consequently, this can negatively affect both the caregiver and the person being cared for. Intervention programs can help empower nonprofessional caregivers of people with chronic diseases and develop solutions to decrease the physical and psychological consequences resulting from caregiving. However, most clinically tested intervention programs for nonprofessional caregivers require face-to-face training, and many caregivers encounter obstacles that hinder their participation in such programs. Consequently, it is necessary to design internet-based intervention programs for nonprofessional caregivers that address their needs and test the efficacy of the programs. OBJECTIVE: The aim of this study was to evaluate the effectiveness of a smartphone app-based intervention program to increase positive mental health for nonprofessional caregivers. METHODS: This study was a randomized controlled trial of 3 months' duration. A total of 152 caregivers over 18 years of age with a minimum of 4 months' experience as nonprofessional caregivers were recruited from primary health care institutions. Nonprofessional caregivers were randomized into two groups. In the intervention group, each caregiver installed a smartphone app and used it for 28 days. This app offered them daily activities that were based on 10 recommendations to promote positive mental health. The level of positive mental health, measured using the Positive Mental Health Questionnaire (PMHQ), and caregiver burden, measured using the 7-item short-form version of the Zarit Caregiver Burden Interview (ZBI-7), were the primary outcomes. Users' satisfaction was also measured. RESULTS: In all, 113 caregivers completed the study. After the first month of the intervention, only one factor of the PMHQ, F1-Personal satisfaction, showed a significant difference between the groups, but it was not clinically relevant (0.96; P=.03). However, the intervention group obtained a higher mean change for the overall PMHQ score (mean change between groups: 1.40; P=.24). The results after the third month of the intervention showed an increment of PMHQ scores. The mean difference of change in the PMHQ score showed a significant difference between the groups (11.43; P<.001; d=0.82). Significant changes were reported in 5 of the 6 factors, especially F5-Problem solving and self-actualization (5.69; P<.001; d=0.71), F2-Prosocial attitude (2.47; P<.001; d=1.18), and F3-Self-control (0.76; P=.03; d=0.50). The results of the ZBI-7 showed a decrease in caregiver burden in the intervention group, although the results were inconclusive. Approximately 93.9% (46/49) of the app users indicated that they would recommend the app to other caregivers and 56.3% (27/49) agreed that an extension of the program's duration would be beneficial. CONCLUSIONS: The app-based intervention program analyzed in this study was effective in promoting positive mental health and decreasing the burden of caregivers and achieved a high range of user satisfaction. This study provides evidence that mobile phone app-based intervention programs may be useful tools for increasing nonprofessional caregivers' well-being. The assessment of the effectiveness of intervention programs through clinical trials should be a focus to promote internet-based programs in health policies. TRIAL REGISTRATION: ISRCTN Registry ISRCTN14818443; http://www.isrctn.com/ISRCTN14818443. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-019-7264-5.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».