Reminiscence and Digital Storytelling to Improve the Social and Emotional Well-Being of Older Adults With Alzheimer’s Disease and Related Dementias: Protocol for a Mixed Methods Study Design and a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Increasing attention is being given to the growing concerns about social isolation, loneliness, and compromised emotional well-being experienced by young adults and older individuals affected by Alzheimer disease and related dementias (ADRD). Studies suggest that reminiscence strategies combined with an intergenerational approach may yield significant social and mental health benefits for participants. Experts also recommended the production of a digital life story book as part of reminiscence. Reminiscence is typically implemented by trained professionals (eg, social workers and nurses); however, there has been growing interest in using trained volunteers owing to staffing shortages and the costs associated with reminiscence programs. OBJECTIVE: The proposed study will develop and test how reminiscence offered by trained young adult volunteers using a digital storytelling platform may help older adults with ADRD to improve their social and emotional well-being. METHODS: The proposed project will conduct a randomized controlled trial to assess the effects of the intervention. The older and young adult participants will be randomly assigned to the intervention (reminiscence based) or control groups and then be randomly matched within each group. Data will be collected at baseline before the intervention, in the middle of the intervention, at end of the intervention, and at 3 months after the intervention. An explanatory sequential mixed methods design will be used to take advantage of the strengths of both quantitative and qualitative methods. The quantitative data from surveys will be entered into SPSS and analyzed using covariate-adjusted linear mixed models for repeated measures to compare the intervention and control groups over time on the major outcomes of participants. Conventional content analysis of qualitative interviews will be conducted using data analysis software. RESULTS: The project was modified to a telephone-based intervention owing to the COVID-19 pandemic. Data collection started in 2020 and ended in 2022. In total, 103 dyads were matched at the beginning of the intervention. Of the 103 dyads, 90 (87.4%) dyads completed the midtest survey and 64 (62.1%) dyads completed the whole intervention and the posttest survey. Although we are still cleaning and finalizing data analyses, the preliminary results from both quantitative and qualitative data showed promising results of this intergenerational reminiscence approach that benefits both the older adults who have cognitive impairments and the young adult participants. CONCLUSIONS: Intergenerational reminiscence provided by young adult college student offers promising benefits for both the younger and older generations. Future studies may consider scaling up this pilot into a trackable, replicable model that includes more participants with diverse background (eg, public vs private college students and older adults from other agencies) to test the effectiveness of this intervention for older adults with ADRD. TRIAL REGISTRATION: ClinicalTrials.gov NCT05984732; https://classic.clinicaltrials.gov/ct2/show/NCT05984732. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49752.
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 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 | 0,011 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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 ».