Assessing the Usability of Web-Based Alcohol Education for Older Adults: A Feasibility Study
Notice bibliographique
Résumé
BACKGROUND: Older adults can experience unfavorable health effects from drinking at relatively low consumption levels because of age-related physiological changes and alcohol's potentially adverse interactions with declining health, increased medication-use and diminishing functional status. At the same time, alcohol use in older adults may be protective against heart disease, stroke, and other disorders associated with aging. We developed "A Toast to Health in Later Life! Wise Drinking as We Age," a web-based educational intervention to teach older adults to balance drinking risks and benefits. OBJECTIVE: To examine the intervention's feasibility in a sample of community-dwelling current drinkers ≥55 years of age and examine its effects on their quantity and frequency of alcohol use, adherence to standard drinking guidelines, and alcohol-related risks. METHODS: Participants were recruited in person, by mail and by telephone between September and October 2014 from a community-based social services organization serving Los Angeles County. Once enrolled, participants were randomly assigned to the intervention or to a control group. The conceptual frameworks for the intervention were the Health Belief Model, models of adult learning, and the US Department of Health and Human Services guidelines for designing easy-to-use websites. The intervention's content focuses on the relationship between drinking and its effects on older adults' medical conditions, use of medications, and ability to perform daily activities. It also addresses quantity and frequency of alcohol use, drinking and driving and binge drinking. The control group did not receive any special intervention. Data on alcohol use and risks for both groups came from the online version of the Alcohol-Related Problems Survey and were collected at baseline and four weeks later. Data on usability were collected online from the intervention group immediately after it completed its review of the website. RESULTS: The 49 intervention and 47 control participants did not differ at baseline in age, ethnicity, medication use, medical conditions, or alcohol use and both groups were mostly female, college-educated, and in good health. Of the intervention participants, 94% (46/49) had little or no difficulty using the website, with 67% (33/49) reporting that they will change the way they think about drinking because of their exposure to the education. At the 4-week follow-up, the intervention group reported drinking less (P=.02). No changes between groups were found in quantity and frequency, adherence to recommended guidelines, or risk status. CONCLUSIONS: Community-dwelling older adults are receptive to online alcohol education. To be most effective, the education should be included as a component of a larger effort consisting of screening and counseling preferably in a health care setting.
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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 | 0,014 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».