Tailoring implementation strategies for the healthy actions and lifestyles to Avoid Dementia or Hispanos y el ALTo a la Demencia Program: Lessons learned from a survey study
Notice bibliographique
Résumé
BACKGROUND: Healthy Actions and Lifestyles to Avoid Dementia Program (HALT-AD) or Hispanos y el ALTo a la Demencia is a recently-developed online educational platform to help individuals identify and modify their own dementia modifiable risk factors (MRF). In light of known challenges in recruiting and retaining diverse participants in research studies, there is a need to identify data-informed strategies that will contribute to effective outreach and tailored implementation of HALT-AD among its intended users of Hispanic and non-Hispanic midlife and older adults in the US. OBJECTIVES: To identify factors (i.e, demographic, medical, psychosocial and environmental) that may facilitate or impede effective program enrollment and participation. DESIGN: Cross-sectional study SETTING: Data from an online and self-administered survey conducted between January and April 2023 PARTICIPANTS: Residents of California, predominately San Diego, who were 50 to 85 years old, with no dementia or Alzheimer's disease, proficient in English or Spanish and with enough technical ability to complete the survey electronically (n=157; 43% Hispanic). INTERVENTION (IF ANY): none MEASUREMENTS: RedCap was used to capture answers to closed and open-ended survey questions. Mixed-methods analysis was used: For quantitative data, descriptive statistics, comparisons by group (Hispanic/non-Hispanic), and exploratory factor analysis were conducted in SPSS. Thematic analysis with open coding in Excel was used for qualitative responses. RESULTS: Independent of ethnicity, participants' most preferred method of reach for recruitment was through a conversation with their doctor or with a family member or friend. Their least preferred method was receiving a Facebook advertisement especially among non-Hispanics. Interest in program participation did not differ by sociodemographic characteristics or self-rated satisfaction with individualized MRFs. Instead, having higher confidence in one's ability to commit to behavior change was significantly associated with higher interest in program participation. While a common theme to motivate both groups to participate was the potential to decrease dementia risk, non-Hispanics were motivated by the premise of supporting research and having a positive user experience. For program implementation, Hispanics were more likely to be interested in participating if live sessions, either online or in-person, were provided to offer support with making lifestyle changes as adjunct to completing online courses independently. In both groups, participation may be further facilitated by offering wearable devices which provide participants with feedback on lifestyle change progress. CONCLUSIONS: A "one-size-fits-all" approach to recruitment and implementation of HALT-AD may not be effective in enrolling and retaining participants in future studies or for clinical use. Instead, a tailored approach that accounts for personal and ethnically-dependent preferences may be more beneficial.
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 | 0,038 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».