e-Learning and Web-Based Tools for Psychosocial Interventions Addressing Neuropsychiatric Symptoms of Dementia During the COVID-19 Pandemic in Tokyo, Japan: Quasi-Experimental Study
Notice bibliographique
Résumé
Background Concern has been raised that the COVID-19 pandemic and consequent social distancing measures may increase neuropsychiatric symptoms in people with dementia. Thus, we developed and delivered an e-learning training course to professional caregivers on using a web-based tool for psychosocial interventions for people with dementia. Objective The aim of our study was to evaluate the feasibility and efficacy of an e-learning course in combination with a web-based tool in addressing neuropsychiatric symptoms of dementia. Methods A quasi-experimental design was used in Tokyo, Japan. The e-learning course was delivered three times to professional caregivers between July and December 2020. Caregivers who completed the course assessed the level of neuropsychiatric symptoms in people with dementia using the total score from the Neuropsychiatric Inventory (NPI) via a web-based tool. The primary outcome measures were the number of caregivers who implemented follow-up NPI evaluations by March 2021 and the change in NPI scores from baseline to their most recent follow-up evaluations. As a control group, information was also obtained from professional caregivers who completed a face-to-face training course using the same web-based tool between July 2019 and March 2020. Results A total of 268 caregivers completed the e-learning course in 2020. Of the 268 caregivers, 56 (20.9%) underwent follow-up evaluations with 63 persons with dementia. The average NPI score was significantly reduced from baseline (mean 20.4, SD 16.2) to the most recent follow-up evaluations (mean 14.3, SD 13.4). The effect size was assumed to be medium (Cohen drm [repeated measures]=0.40). The control group consisted of 252 caregivers who completed a face-to-face training course. Of the 252 caregivers, 114 (45.2%) underwent follow-up evaluations. Compared to the control group, caregivers who completed the e-learning course were significantly less likely to implement follow-up evaluations (χ21=52.0, P<.001). The change in NPI scores did not differ according to the type of training course (baseline-adjusted difference=–0.61, P=.69). Conclusions The replacement of face-to-face training with e-learning may have provided professionals with an opportunity to participate in the dementia behavior analysis and support enhancement (DEMBASE) program who may not have participated in the program otherwise. Although the program showed equal efficacy in terms of the two training courses, the feasibility was suboptimal with lower implementation levels for those receiving e-learning training. Thus, further strategies should be developed to improve feasibility by providing motivational triggers for implementation and technical support for care professionals. Using online communities in the program should also be investigated.
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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».