Environmental Triggers of Specific Subtypes of Agitation in People With Dementia: Observational Study.

Background: Among the most critical behavioral and psychological symptoms of dementia, agitation can lead to decreased quality of life of people with dementia and their caregivers. Monitoring triggers of agitation and its subtypes could enable early detection or prediction of agitated moments, which could be used to guide preventive or mitigating interventions. However, at this point in time, limited research exists on quantifying environmental triggers of agitation or its subtypes. Objective: In this paper, we aim to quantify the relationships between specific environmental factors and agitation as well as specific agitation subtypes, such as motor and verbal agitation. Methods: Using a cross-sectional repeated measures design, 37 people with dementia, admitted to a specialized neuropsychiatric ward for patients with dementia and severe behavioral and psychological problems, were each included for 1 week. During this period, the Pittsburgh Agitation Scale was filled in by the nurses on the ward following an experience sampling methodology to assess a patient's agitation level on a momentary basis. Continuous environmental data (light, sound, and temperature) were collected from fixed sensors mounted on the ward. Generalized linear mixed models were used to quantify relationships between environmental variables and outcome variables (agitation, motor agitation, and verbal agitation). These models accounted for the hierarchical nature of our dataset as well as confounding factors, such as time of day and the room-level location of the patient. The time window for analysis was selected through a comparison of β coefficient estimates across various window lengths. Models were built up sequentially, per outcome variable, using selected features per environmental modality. Results: We found that different environmental factors captured in the window of 33 to 12 minutes before the agitation moment were most informative for different subtypes of agitation: mean light level (β=-0.61, 95% CI -1.12 to -0.10; P=.02) for motor agitation and SD of sound level (β=0.68, 95% CI 0.34-1.02; P<.001) for verbal agitation. Contextual factors such as time of day (β range=0.51-0.94; P<.05 to <.001) and room-level location (β range=0.85-1.08; P<.01 to <.001) were also significant predictors of agitation. Conclusions: Integrating the key differences between predictors of verbal and motor agitation, respectively, the higher SD in sound level and the lower mean light level, in a model predicting the occurrence of subtype-specific agitation, could substantially improve model performance. Overall, these findings can aid in the development of predictive models for agitation based on environmental data and enable subsequent just-in-time interventions, improving the quality of life for both patients and caregivers.