A Relationship between Depression and Wandering in Community-Dwelling Elders with Dementia

The Prevalence of Missing Incidents and Their Antecedents Among Older Adult MedicAlert Subscribers: Retrospective Descriptive Study

BACKGROUND

With the population aging, the number of people living with dementia is expected to rise, which, in turn, is expected to lead to an increase in the prevalence of missing incidents due to critical wandering. However, the estimated prevalence of missing incidents due to dementia is inconclusive in some jurisdictions and overlooked in others.

OBJECTIVE

The aims of the study were to examine (1) the demographic, psychopathological, and environmental antecedents to missing incidents due to critical wandering among older adult MedicAlert Foundation Canada (hereinafter MedicAlert) subscribers; and (2) the characteristics and outcomes of the missing incidents.

METHODS

This study used a retrospective descriptive design. The sample included 434 older adult MedicAlert subscribers involved in 560 missing incidents between January 2015 and July 2021.

RESULTS

The sample was overrepresented by White older adults (329/425, 77.4%). MedicAlert subscribers reported missing were mostly female older adults (230/431, 53.4%), living in urban areas with at least 1 family member (277/433, 63.8%). Most of the MedicAlert subscribers (345/434, 79.5%) self-reported living with dementia. MedicAlert subscribers went missing most frequently from their private homes in the community (96/143, 67.1%), traveling on foot (248/270, 91.9%) and public transport (12/270, 4.4%), during the afternoon (262/560, 46.8%) and evening (174/560, 31.1%). Most were located by first responders (232/486, 47.7%) or Good Samaritans (224/486, 46.1%). Of the 560 missing incidents, 126 (22.5%) were repeated missing incidents. The mean time between missing incidents was 11 (SD 10.8) months. Finally, the majority of MedicAlert subscribers were returned home safely (453/500, 90.6%); and reports of harm, injuries (46/500, 9.2%), and death (1/500, 0.2%) were very low.

CONCLUSIONS

This study provides the prevalence of missing incidents from 1 database source. The low frequency of missing incidents may not represent populations that are not White. Despite the low number of missing incidents, the 0.2% (1/500) of cases resulting in injuries or death are devastating experiences that may be mitigated through prevention strategies.

Modeling and mobile home monitoring of behavioral and psychological symptoms of dementia (BPSD)

With the increasing global aging population, dementia care has rapidly become a major social problem. Current diagnosis of Behavior and Psychological Symptoms of Dementia (BPSD) relies on clinical interviews, and behavioral rating scales based on a period of behavior observation, but these methods are not suitable for identification of occurrence of BPSD in the daily living, which is necessary for providing appropriate interventions for dementia, though, has been studied by few research groups in the literature. To address these issues, in this study developed a BPSD monitoring system consisting of a Psycho-Cognitive (PsyCo) BPSD model, a Behavior-Physio-Environment (BePhyEn) BPSD model, and an implementation platform. The PsyCo BPSD model provides BPSD assessment support to caregivers and care providers, while the BePhyEn BPSD model provides instantaneous alerts for BPSD enabled by a 24-hour home monitoring platform for early intervention, and thereby alleviation of burden to patients and caregivers. Data for acquiring the models were generated through extensive literature review and regularity determined. A mobile robot was utilized as the implementation platform for improving sensitivity of sensors for home monitoring, and elderly individual following algorithms were investigated. Experiments in a virtual home environment showed that, a virtual BPSD elderly individual can be followed safely by the robot, and BPSD occurrence could be identified accurately, demonstrating the possibility of modeling and identification of BPSD in home environment.

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

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.