Internet-Based Dementia Prevention Intervention (DementiaRisk): Protocol for a Randomized Controlled Trial and Knowledge Translation
Notice bibliographique
Résumé
BACKGROUND: Research has shown that engaging in a range of healthy lifestyles or behavioral factors can help reduce the risk of developing dementia. Improved knowledge of modifiable risk factors for dementia may help engage people to reduce their risk, with beneficial impacts on individual and public health. Moreover, many guidelines emphasize the importance of providing education and web-based resources for dementia prevention. Internet-based interventions may be effective, but few have been studied rigorously or widely disseminated. We created DementiaRisk, an award-winning, web- and email-based education platform for the public focused on modifiable risk factors, featuring multimedia e-learning and email "microlearning" content, to help raise awareness and improve knowledge of actions to reduce dementia risk. OBJECTIVE: This protocol describes a randomized controlled trial to (1) evaluate whether exposure to DementiaRisk changes knowledge of dementia risk factors, intention to engage in risk reduction activities, and health behaviors related to dementia risk reduction and to (2) explore qualitative aspects including participants' engagement and satisfaction with the intervention and barriers and facilitators to use. METHODS: Using a sequential explanatory mixed methods design, this study conducts a quantitative analysis followed by a qualitative inquiry to evaluate outcomes and feasibility. In total, 485 participants will be recruited on the web and randomly assigned to 2 groups: one accessing DementiaRisk and the other receiving alternative e-learning on mild cognitive impairment. Assessments will be delivered on the web at baseline (T1), at 4 weeks (T2), and at 2 months after the intervention (T3). Knowledge will be assessed using items from the Dementia Knowledge Assessment Scale, intentions to engage in risk reduction activities will be assessed using items in line with current evidence, and health behaviors related to dementia risk reduction will be assessed using items from the Godin-Shephard Leisure Time Physical Activity Questionnaire along with additional questions related to a range of health status domains. Outcomes and feasibility will be assessed using the Information Assessment Method for patients and consumers. A linear mixed effects model will be used to examine the relationship between each outcome score by group and time point. RESULTS: This study was approved by the Hamilton Integrated Research Ethics Board on August 24, 2022 (project ID 14886) and received funding in February 2023. Recruitment took place from March 28, 2023, to April 28, 2023, with the final participants completing the intervention by August 18, 2023. Analyses and interpretation of data are ongoing. CONCLUSIONS: DementiaRisk is a readily scalable, technology-enhanced solution for dementia prevention education. It has been designed using evidence-based principles of multimedia learning. It has the potential to scale and spread widely using the open internet, so it may be able to reach a wider audience than traditional in-person educational interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05383118; https://clinicaltrials.gov/study/NCT05383118. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64718.
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 | 0,059 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,005 |
| Méta-épidémiologie (sens large) | 0,014 | 0,006 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,010 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,135 | 0,025 |
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 ».