Background Although disclosing the predictors of different behavioral and psychological symptoms of dementia (BPSD) is the first step in developing person-centered interventions, current understanding is limited, as it considers BPSD as a homogenous construct. This fails to account for their heterogeneity and hinders development of interventions that address the underlying causes of the target BPSD subsyndromes. Moreover, understanding the influence of proximal factors—circadian rhythm–related factors (ie, sleep and activity levels) and physical and psychosocial unmet needs states—on BPSD subsyndromes is limited, due to the challenges of obtaining objective and/or continuous time-varying measures. Objective The aim of this study was to explore factors associated with BPSD subsyndromes among community-dwelling older adults with dementia, considering sets of background and proximal factors (ie, actigraphy-measured sleep and physical activity levels and diary-based caregiver-perceived symptom triggers), guided by the need-driven dementia-compromised behavior model. Methods A prospective observational study design was employed. Study participants included 145 older adults with dementia living at home. The mean age at baseline was 81.2 (SD 6.01) years and the sample consisted of 86 (59.3%) women. BPSD were measured with a BPSD diary kept by caregivers and were categorized into seven subsyndromes. Independent variables consisted of background characteristics and proximal factors (ie, sleep and physical activity levels measured using actigraphy and caregiver-reported contributing factors assessed using a BPSD diary). Generalized linear mixed models (GLMMs) were used to examine the factors that predicted the occurrence of BPSD subsyndromes. We compared the models based on the Akaike information criterion, the Bayesian information criterion, and likelihood ratio testing. Results Compared to the GLMMs with only background factors, the addition of actigraphy and diary-based data improved model fit for every BPSD subsyndrome. The number of hours of nighttime sleep was a predictor of the next day’s sleep and nighttime behaviors (odds ratio [OR] 0.9, 95% CI 0.8-1.0; P=.005), and the amount of energy expenditure was a predictor for euphoria or elation (OR 0.02, 95% CI 0.0-0.5; P=.02). All subsyndromes, except for euphoria or elation, were significantly associated with hunger or thirst and urination or bowel movements, and all BPSD subsyndromes showed an association with environmental change. Age, marital status, premorbid personality, and taking sedatives were predictors of specific BPSD subsyndromes. Conclusions BPSD are clinically heterogeneous, and their occurrence can be predicted by different contributing factors. Our results for various BPSD suggest a critical window for timely intervention and care planning. Findings from this study will help devise symptom-targeted and individualized interventions to prevent and manage BPSD and facilitate personalized dementia care.

Background Health-related quality of life (HRQOL) is an important concept to consider both individuals' ability to manage their daily lives and health status across the lifespan. Despite this variable's importance, there is a lack of clarification on the factors associated with HRQOL, especially for military women. The aim of this study was to examine factors associated with HRQOL of military women in the Republic of Korea (ROK) Army. Methods This cross-sectional study included 196 participants who were currently within their 5-year service period. HRQOL was measured by the Korean version of the Short-Form 36 Health Survey Questionnaire version 2.0 (SF-36v2), and depression was assessed using the Korean version of the Patient Health Questionnaire-9 (PHQ-9). Differences in HRQOL according to general and occupational factors were analyzed using the independent t-test and analysis of variance (ANOVA). Multiple linear regression analysis was performed to identify factors associated with the HRQOL of women serving as military junior officers. Results The mean score for the physical component summary (PCS) of SF-36v2 was 56.0 ± 5.8, and that for the mental component summary (MCS) of SF-36v2 was 47.2 ± 10.0. For depression, the mean score was 5.4 ± 5.2, whereas 19.4% of the participants scored more than 10 out of 27 points, which means moderate to severe. No variables showed statistically significant relationships with the PCS. However, military women showed a lower score for MCS when they were officers (adjusted β = − 3.52; 95% CI = − 5.47, − 1.58), had higher perceived stress (adjusted β = − 0.62, 95% CI = − 0.83, − 0.41), and a higher score for depression (adjusted β = − 0.86, 95% CI = − 1.10, − 0.63). Conclusions Although depression levels were not severe, it was a significant factor of HRQOL. Stress and depression were found to be significant factors associated with the MCS in military women. Therefore, to improve their HRQOL, the ROK Army should provide early screening, intervention, and management program for high-risk military women. In addition, an appropriate organizational atmosphere within the military must be created to promote such programs.

The behavioral and psychological symptoms of dementia (BPSD) are challenging aspects of dementia care. This study used machine learning models to predict the occurrence of BPSD among community-dwelling older adults with dementia. We included 187 older adults with dementia for model training and 35 older adults with dementia for external validation. Demographic and health data and premorbid personality traits were examined at the baseline, and actigraphy was utilized to monitor sleep and activity levels. A symptom diary tracked caregiver-perceived symptom triggers and the daily occurrence of 12 BPSD classified into seven subsyndromes. Several prediction models were also employed, including logistic regression, random forest, gradient boosting machine, and support vector machine. The random forest models revealed the highest area under the receiver operating characteristic curve (AUC) values for hyperactivity, euphoria/elation, and appetite and eating disorders; the gradient boosting machine models for psychotic and affective symptoms; and the support vector machine model showed the highest AUC. The gradient boosting machine model achieved the best performance in terms of average AUC scores across the seven subsyndromes. Caregiver-perceived triggers demonstrated higher feature importance values across the seven subsyndromes than other features. Our findings demonstrate the possibility of predicting BPSD using a machine learning approach.

Demented older adults experience many internal and external stress inducers that are thought to be a source of behavioral and psychological symptoms of dementia(BPSD). The purpose of this study was to compare the stress index among older adults through salivary cortisol levels and physical stress index. This study was cross-sectional design, including 139 participants who recruited until May of this year(104 demented older adults who visited hospital outpatient neurology and 35 non-demented older adults as control group). The physical stress index was measured by heart rate variability and salivary cortisol levels(4 samples/day, 1 days). Salivary cortisol levels were measured at four times after wake up, after breakfast, before dinner and after dinner. The data were analyzed using independent t-test and generalized estimating equations. In salivary cortisol levels measured after wake up, the demented older adults reported about 1.5 times higher than non-demented older adults(p=.042). And the salivary cortisol levels measured after breakfast were about 2.3 times higher in the demented older adults than in control groups(p=.002). Accordingly, the results can be concluded that demented older adults have higher stress levels than control groups in the morning. Also the physical stress index through heart rate variability(HRV) in the demented older adults(6.30±0.65) had higher than control groups(6.00±0.55, t=2.45, p=.016). There are significant differences in salivary cortisol levels and physical stress index between demented older adults and control groups. As stress inducers affects BPSD for the demented older adults, nursing intervention should be tailored to proper way based on their stress inducers.