Journal Article Epublish
PubMed: 40013071 DOI: 10.1177/20552076251319662
Preferences of community-dwelling older adults with multimorbidity for digital empowerment interventions: Protocol for a discrete choice experiment study.
Digit Health 11:20552076251319662
Authors: Yawen Ren, Li Yang, Wenguang Wang, Runtian Lv, Xiuqing Fang, Yueling Wang, Jiayi Zhong
Affiliations
- School of Nursing, Qingdao University, Qingdao, Shandong, China.
- School of Nursing, Qingdao University, Qingdao, Shandong, China. Qingdao Municipal Key Laboratory for Smart Healthcare and Chronic Disease Management, Qingdao University, Qingdao, Shandong, China.
Abstract
Introduction
The development of digital health technologies has had a positive impact on the management of comorbidity in the elderly. At the same time, it also sets certain requirements for the digital health literacy of older adults. To effectively implement interventions that improve digital health literacy among older adults with multimorbidity, it is essential to involve patients in decision-making processes and to develop interventions that align with their preferences.
Methods and analysis
This study will use Discrete choice experiment to investigate the needs and preferences of older adults with multimorbidity for digital health literacy intervention. Attributes were identified through a literature review, in-depth interviews, and expert consultation. The attributes are intervention provider, content, type, frequency, material, learning mode, supplementary services, and cost. According to the identified attributes and levels, the choice set questionnaires were generated using Stata software. Furthermore, the study will assess the impact of demographic factors, social support, self-efficacy, levels of digital health literacy, and technology anxiety on the selection of preferences. A mixed logic model will analyze respondents'preferences for different intervention attributes and levels. A latent class model will identify heterogeneous group preferences.
Results
We anticipate a minimum of 300 older adults with multimorbidity in community enrolling and completing data collection. Study results will be published in peer-reviewed scientiļ¬c journals.
Conclusions
The collection and analysis of patient preference information will greatly improve the accuracy and effectiveness of digital health literacy interventions in the development, adoption, and economic evaluation.
MeSH
Patient Preference, Multimorbidity, Health Literacy, Empowerment, Literacy, Digital Health