Clustering Analysis of the Care Problems of People with Dementia Based on the Minimum Spanning Tree Algorithm: A Cross-Sectional Study

Abstract

Background:

Recognizing the correlations between care problems of people with dementia could help clinicians choose treatment methods because related symptom groups might respond to the same treatment intervention.

Objective:

This study aimed to evaluate the prevalence of various care problems in people with dementia and to explore the core care problems and correlations between care problems of people with dementia.

Methods:

This cross-sectional study recruited family caregivers of people with dementia through memory clinics and WeChat groups. Care problems of people with dementia were measured using a care problems evaluation sheet, which involved three aspects: daily living care problems, behavioral and psychological symptoms, and safety risks. Clustering analysis of the care problems based on Kruskal’s minimum spanning tree (MST) algorithm was performed in the Jupyter Notebook software to explore the core care problems and their correlations.

Results:

A total of 687 carer-patient pairs were included in the analysis. In general, the prevalence of having difficulty in language performance, agitated behavior, and incidence of falls was relatively higher than other care problems in people with dementia, which distressed their family caregivers. Through clustering analysis, the 63 care problems were clustered into 7 clusters and 7 core care problems were identified.

Conclusion:

The prevalence of various care problems of people living with dementia in China was relatively high. The information regarding correlations in clusters among care problems will help practitioners and policymakers to identify the core care problems and optimize more rational treatments for people with dementia.