Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers

Abstract

Purpose The purpose of this study was to identify the caring scenarios that result in severe depression in caregivers caring for dementia patients. Patients and Methods A cross-sectional study with 1111 dementia patients and their caregivers in Taiwan from October 2015 to January 2020 was conducted. Gender, age, type of dementia, clinical dementia rating, walking ability, mood symptoms, behavioral symptoms, and psychological symptoms were the variables from the dementia patients. Age, relation to the patient, employment, type of primary care, frequency of care, mood symptoms, and the score from the Center for Epidemiologic Studies Depression Scale were the variables from the caregivers. A comprehensive viewpoint of both dementia patients and their caregivers was evaluated by the Apriori algorithm to find the attributes resulting in different caregiving depressions. Results Forty-seven rules were found with 18 rules of mild depressive symptomatology, 17 rules of moderate depressive symptomatology, and 12 rules of severe depressive symptomatology. A total of 7 general rules were summarized to be the severe depressive symptomatology. The results showed that an unemployed or retired caregiver with the mood symptoms such as helplessness, anger, emotional liability, or anxiety who took care of AD patients or AD patients with a moderate severity would have severe depression. Increased care frequencies (≥6 days per week) and multiple mood problems from caregivers result in severe depression. The composition of adult children, patients’ aggression, and caregivers’ helplessness as well as the combinations of male patients aged 75–84 years with the caregiver’s mood of helplessness or nervousness and hopelessness were highly associated with severe depression. Conclusion For those caring for AD patients, severe depression was associated with the combination of different parameters to constitute each of these seven scenarios. Unlike previous studies which often evaluated one or two variables related to caregiver’s depression, this study provided a more comprehensive viewpoint that enabled the collaborative team to efficiently identify and manage different scenarios by summarizing the rules of caregivers with severe depression from a systematic viewpoint.

Depression among caregivers of patients with dementia: Associative factors and management approaches

“…Previous studies associated caregiver depression with being younger, having White or Hispanic ethnicity (compared to black ethnicity), having a lower educational level, and caring for a patient with ADL dependence[ 40 , 41 ], and behavioral disturbances[ 41 , 42 ]. There is significant evidence that BPSD influence depression in caregivers and may be more influential than the severity of cognitive deficits seen or perceived in the patient[ 43 , 44 ].…”

“…For dementia caregivers, factors associated with depression risk include having a low income, spending more hours caregiving (40 to 79 h/wk compared to less than 40 h/wk)[ 40 ], being female[ 41 ], having a spousal relationship[ 40 , 57 ], living with the patient[ 41 , 44 , 58 ], having poorer health status[ 44 , 58 ], and having a higher caregiver distress sensation[ 44 , 58 , 59 ]. It has been reported that approximately 80% of caregivers have some form of sleep disturbance.…”

Relationship of Psychological Flexibility and Mindfulness to Caregiver Burden, and Depressive and Anxiety Symptoms in Caregivers of People with Dementia

“…Most of the studies explore the relationships between the dementia patient and caregiver sociodemographics, patient illness characteristics, and caregiver burden and depressive and anxiety symptoms. Illness severity and presence of behavioural and psychological symptoms of dementia (BPSD) are known predictors for caregiver burden and depressive and anxiety symptoms [25,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48]. PwD and the caregivers' sociodemographic background have also been studied in Malaysia and in other countries [18,44,49].…”

Applying Apriori algorithm to explore long-term care services usage status—Variables based on the combination of patients with dementia and their caregivers

“…The purpose of this study was to identify which attributes from patients and/or caregivers could result in different usages of the LTC services. The Apriori algorithm has been proven to be very effective in identifying statistical correlations from a multidimensional viewpoint in dementia-related areas by setting up support, confidence, and lift (Jhang et al, 2019 , 2020 ; Chang et al, 2021 ). Thus, the Apriori algorithm was used in this study.…”

“…Thus, the Apriori algorithm was used in this study. The definitions and formulas of support, confidence, and lift are given below (Chang et al, 2021 ; Jhang et al, 2021 ). The support of an association rule A ⇒ B is defined by calculating the percentage of transactions containing both A and B in the database depicted in Equation (1):…”