Alzheimer's disease knowledge of nursing staff in East China: A latent profile analysis - Shufang Zuo; Yueju Wang; Ziyu Wang; Si Chen; Jinghong Liang; Hongyan Meng; Lu Lin (Wiley, 2023)
Abstract Aim The dementia population is expanding fast globally, posing a huge challenge to the healthcare system. Improving the level of Alzheimer's disease knowledge (ADK) in nursing staff is the key to providing quality dementia care and improving the patients' quality of life. This study aimed to investigate and classify the ADK level of nursing staff in East China and to identify the factors influencing the nursing staff's ADK level. Design A cross‐sectional study. Methods A cross‐sectional survey was conducted among 1896 nursing staff in East China from September 2022 to December 2022, using a self‐designed general information questionnaire and the Chinese version of the Alzheimer's Disease Knowledge Scale. Latent profile analysis (LPA) was used to classify the nursing staff according to their ADK level, and multinomial logistic regression was used to identify the factors influencing the nursing staff's ADK level. Results Nursing staff could be classified into four latent profiles according to their ADK level (p < 0.05), namely, the 'Low ADK group', 'Medium ADK group', 'Medium‐high ADK group', and 'High ADK group'. Age, education, experience in AD care and training in ADK were the main factors influencing the classification of the nursing staff's ADK level. Therefore, upgrading education, participating in ADK training, and increasing AD care experience will be conducive to improving the ADK of nursing staff. No Patient or Public Contribution.