Status quo on knowledge of Alzheimer's disease among community-dwelling elderly:a latent profile analysis
Objective:To explore the categories of Alzheimer's disease knowledge among community-dwelling older adults and to analyze its influencing factors of different categories.Methods:From May to August in 2023,stratified random sampling was used to select the older adults in three main urban areas of Chongqing(Jiulongpo District,Shapingba District and Yubei District),and the general data questionnaire and Chinese version of Alzheimer's Disease Knowledge Scale(ADKS)were used as investigation tools.According to the scores of each dimension of ADKS,the potential profiles of Alzheimer's disease knowledge categories of the older adults in the community were analyzed,and the disordered multi-classification Logistic regression analysis was used to explore the influencing factors of Alzheimer's disease knowledge categories of the older adults in the community.Results:A total of 558 older adults in the community were included.Three profiles were identified,which were"high scores group"(10% ),"moderate scores group"(44% ),and"poor scores group"(46% ).The results of disordered multiple Logistic regression analysis showed that age,education level,household registration,dementia contact history and dementia education history were the influencing factors of category of Alzheimer's disease knowledge among the older adults in the community(P<0.05).Conclusions:There is obvious heterogeneity in the knowledge of Alzheimer's disease among the older adults in the community.We should strengthen the health education of the older adults in the"moderate scores group"and"poor scores group",especially pay more attention to the older adults who are older,rural,and having no history of dementia contact or dementia education,so as to start precise intervention as soon as possible to prevent the occurrence of Alzheimer's disease.
Alzheimer's diseasecommunitythe older adultspotential profile analysisinfluencing factorsinvestigation and research
国家科技期刊平台
NSTL
万方数据
