Preferences for Electronic Modes of Communication Among Older Primary Care Patients: Cross-sectional Survey
Notice bibliographique
Résumé
BACKGROUND: Health information delivered via daily modes of communication such as email, text, or telephone reportedly supports improved health behavior and outcomes. While different modes of communication beyond clinical visits have proven successful for patient outcomes, preferences for communication modes have not been comprehensively studied among older primary care patients. We addressed this gap by assessing patient preferences for receiving cancer screening and other information from their doctors' offices. OBJECTIVE: We explored stated preferences by communication modes through the lens of social determinants of health (SDOH) to gauge acceptability and equity implications for future interventions. METHODS: A cross-sectional survey was mailed to primary care patients aged 45-75 years, in 2020-2021, which assessed respondents' use of telephones, computers, or tablets in daily life and their preferred modes of communication for different types of health information, including educational materials about cancer screening, tips for taking prescription medication, and protection from respiratory diseases from their doctors' offices. Respondents indicated their willingness to receive messages from their doctors' offices via each of the provided modes of communication, including telephone, text, email, patient portals, websites, and social media, on a 5-point Likert scale ranging from "unwilling" to "willing." We present the percentage of respondents who indicated that they were "willing" to receive information via specific electronic mode. Chi-square tests were used to compare participants' willingness by social characteristics. RESULTS: In total, 133 people completed the survey (response rate 27%). The average respondent age was 64 years, 82 (63%) respondents were female, 106 (83%) were White, 20 (16%) were Black, and 1 (1%) was Asian. In total, 75 (58%) respondents had a bachelor's degree or higher; 26 (20%) resided in rural areas, 37 (29%) in suburban areas, 50 (39%) in a town, and 15 (12%) in a city. The majority, 73 (57%), reported being comfortable with their income. Preferences of respondents for electronic communication about cancer screening were distributed as follows: 100 (75%) respondents were willing to receive information from their doctor's office via their patient portal, 98 (74%) via email, 75 (56%) via text, 60 (45%) via the hospital website, 50 (38%) via telephone, and 14 (11%) via social media. About 6 (5%) respondents were unwilling to receive any communication via electronic modes. Preferences were distributed similarly for other types of information. Respondents reporting lesser income and education consistently preferred receiving telephone calls relative to other communication modes. CONCLUSIONS: To optimize health communication and reach a socioeconomically diverse population, telephone calls should be added to electronic communication, especially for people with less income and education. Further research needs to identify the underlying reasons for the observed differences and how best to ensure that socioeconomically diverse groups of older adults can access reliable health information and health care services.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».