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

Cheng-Chen Chang, 1, 2,* Wen-Fu Wang, 3, 4,* Yi-Ying Li, 5,* Yu-An Chen, 1 Yen-Jen Chen, 1 Yi-Cheng Liao, 1 Kai-Ming Jhang, 3 Hsin-Hung Wu 5– 7 1Department of Psychiatry, Changhua Christian Hospital, Changhua, Taiwan; 2School of Medicine, Chung Shan Medical University, Taichung City, Tai...

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Main Authors: Chang CC, Wang WF, Li YY, Chen YA, Chen YJ, Liao YC, Jhang KM, Wu HH
Format: Article
Language:English
Published: Dove Medical Press 2021-07-01
Series:Risk Management and Healthcare Policy
Subjects:
Online Access:https://www.dovepress.com/using-the-apriori-algorithm-to-explore-caregivers-depression-by-the-co-peer-reviewed-fulltext-article-RMHP
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spelling doaj-5fa2684ba23d4f2bbcfa9abfa96015d82021-07-14T19:53:23ZengDove Medical PressRisk Management and Healthcare Policy1179-15942021-07-01Volume 142953296366864Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their CaregiversChang CCWang WFLi YYChen YAChen YJLiao YCJhang KMWu HHCheng-Chen Chang, 1, 2,* Wen-Fu Wang, 3, 4,* Yi-Ying Li, 5,* Yu-An Chen, 1 Yen-Jen Chen, 1 Yi-Cheng Liao, 1 Kai-Ming Jhang, 3 Hsin-Hung Wu 5– 7 1Department of Psychiatry, Changhua Christian Hospital, Changhua, Taiwan; 2School of Medicine, Chung Shan Medical University, Taichung City, Taiwan; 3Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan; 4Department of Holistic Wellness, Ming Dao University, Changhua, Taiwan; 5Department of Business Administration, National Changhua University of Education, Changhua, Taiwan; 6Department of M-Commerce and Multimedia Applications, Asia University, Taichung City, Taiwan; 7Faculty of Education, State University of Malang, Malang, East Java, Indonesia*These authors contributed equally to this workCorrespondence: Hsin-Hung Wu Email hhwu@cc.ncue.edu.twPurpose: 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.Keywords: patient with dementia, Alzheimer’s disease, behavioral and psychological symptoms of dementia, caregiver, caregiver’s mood, depressive symptomatology, Center for Epidemiologic Studies Depression Scale, caring scenario, Apriori algorithmhttps://www.dovepress.com/using-the-apriori-algorithm-to-explore-caregivers-depression-by-the-co-peer-reviewed-fulltext-article-RMHPpatient with dementiaalzheimer's diseasebehavioral and psychological symptoms of dementiacaregivercaregiver’s mooddepressive symptomatologycenter for epidemiologic studies depression scalecaring scenarioapriori algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Chang CC
Wang WF
Li YY
Chen YA
Chen YJ
Liao YC
Jhang KM
Wu HH
spellingShingle Chang CC
Wang WF
Li YY
Chen YA
Chen YJ
Liao YC
Jhang KM
Wu HH
Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
Risk Management and Healthcare Policy
patient with dementia
alzheimer's disease
behavioral and psychological symptoms of dementia
caregiver
caregiver’s mood
depressive symptomatology
center for epidemiologic studies depression scale
caring scenario
apriori algorithm
author_facet Chang CC
Wang WF
Li YY
Chen YA
Chen YJ
Liao YC
Jhang KM
Wu HH
author_sort Chang CC
title Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
title_short Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
title_full Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
title_fullStr Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
title_full_unstemmed Using the Apriori Algorithm to Explore Caregivers’ Depression by the Combination of the Patients with Dementia and Their Caregivers
title_sort using the apriori algorithm to explore caregivers’ depression by the combination of the patients with dementia and their caregivers
publisher Dove Medical Press
series Risk Management and Healthcare Policy
issn 1179-1594
publishDate 2021-07-01
description Cheng-Chen Chang, 1, 2,* Wen-Fu Wang, 3, 4,* Yi-Ying Li, 5,* Yu-An Chen, 1 Yen-Jen Chen, 1 Yi-Cheng Liao, 1 Kai-Ming Jhang, 3 Hsin-Hung Wu 5– 7 1Department of Psychiatry, Changhua Christian Hospital, Changhua, Taiwan; 2School of Medicine, Chung Shan Medical University, Taichung City, Taiwan; 3Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan; 4Department of Holistic Wellness, Ming Dao University, Changhua, Taiwan; 5Department of Business Administration, National Changhua University of Education, Changhua, Taiwan; 6Department of M-Commerce and Multimedia Applications, Asia University, Taichung City, Taiwan; 7Faculty of Education, State University of Malang, Malang, East Java, Indonesia*These authors contributed equally to this workCorrespondence: Hsin-Hung Wu Email hhwu@cc.ncue.edu.twPurpose: 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.Keywords: patient with dementia, Alzheimer’s disease, behavioral and psychological symptoms of dementia, caregiver, caregiver’s mood, depressive symptomatology, Center for Epidemiologic Studies Depression Scale, caring scenario, Apriori algorithm
topic patient with dementia
alzheimer's disease
behavioral and psychological symptoms of dementia
caregiver
caregiver’s mood
depressive symptomatology
center for epidemiologic studies depression scale
caring scenario
apriori algorithm
url https://www.dovepress.com/using-the-apriori-algorithm-to-explore-caregivers-depression-by-the-co-peer-reviewed-fulltext-article-RMHP
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