Heterogeneity in the level of dementia literacy among community doctors in China: A latent profile analysis.

Abstract

Background: This study aimed to explore the heterogeneity of community doctors based on their knowledge of dementia and the potential factors associated with their dementia literacy.

Methods: A total of 1288 community doctors completed the Alzheimer disease knowledge scale (ADKS) in a cross-sectional study conducted between December 2021 and January 2022. We used latent class analysis (LCA) to explore potential clusters based on responses to the ADKS. Multivariate multinomial logistic regression analysis was performed to evaluate the associations between potential risk factors and the knowledge of community doctors.

Results: Community doctors were divided into four clusters according to their knowledge structure (Akaike information criterion (AIC) = 35672.83, Bayesian information criterion (BIC) = 36307.63, adjusted BIC (aBIC) = 35916.91, entropy = 0.814): the severity-focused subgroup (n = 269), the physical issues-focused group (n = 370), the knowledge uncertainty group (n = 191), and the general-focused group (n = 458). Age, education level, type of practice, and professional title were associated with the knowledge structure of Alzheimer's disease (AD). In addition, the perception that patients seek care in community health centres for physical reasons and community doctors' failure to manage patients with recently identified cognitive impairment were associated with the structures of the ADKS among community doctors (P < 0.05).

Conclusions: There is heterogeneity in the level of AD knowledge among community doctors and their demographic characteristics, perceptions, and practices. Further efforts are needed to optimise the knowledge structure of dementia among community health care professionals.