Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches
Abstract
:1. Introduction
- Our study explores elderly care needs in China from the perspective of direct caregivers by extracting texts published by registered users on the topic of elderly care and conducting thematic modelling and sentiment analysis.
- Based on the demand obtained from text mining, this study proposes strategies to improve the quality of aged care services, aiming at offering a multidimensional perspective to improve the construction of elderly care service system in China.
2. Materials and Methods
2.1. Data Acquisition and Pre-Processing
2.2. Emotional Analysis
2.3. Latent Dirichlet Allocation (LDA) Model
- The words in the document obey a Poisson distribution.
- Generate the topic distribution for the mth document by sampling from the Dirichlet distribution
- Generate the topic for the nth word of the mth document by sampling from the polynomial of topics .
- Generate the word distribution corresponding to the topic by sampling from the Dirichlet distribution .
- Finally generate the word by sampling from the polynomial distribution of words.
2.4. Topic Extraction Based on the LDA Topic Model
3. Results and Discussion
3.1. Sentiment Analysis
3.2. Topic Clustering
3.2.1. Mental Health Needs
3.2.2. Information Needs
3.2.3. Intergenerational Demand
- (1)
- The conflict between high property prices and the desire to own a home
- (2)
- The intergenerational conflict between support responsibilities and individual development
- (3)
- The intergenerational conflict regarding marriage and childbearing
4. Conclusions and Recommendations
4.1. Encourage Intergenerational Companionship and Support with a Focus on the Mental Health of the Elderly
4.2. Encouraging Giving Back of Family Members and Safeguarding the Information Acquiring Needs of Older People
4.3. Settling Intergenerational Family Conflicts and Maintaining Harmony among Generations
5. Prospects and Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Topic Categories | Percentage | The 15 Most Frequently Occurring Topic Terms under This Topic |
---|---|---|
1. Family relationships with non-immediate blood relatives and partners | Topic6 7.4% | relatives, red packet, relationship, sister, face, cousin, family, sister, cousin, gift, relationship, friend, child, university, room |
Topic10 4% | mother-in-law, clothes, father-in-law, housework, room, mother-in-law’s house, in-laws, washing machine, kitchen, bedroom, angry, washing dishes, waste, air conditioning, daughter-in-law | |
2. Health and medical coverage | Topic4 11.9% | hospital, doctor, carer, surgery, body, check-up, hospitalisation, sick, brain attack, patient, cancer, discharge, symptoms, having surgery, diabetes |
Topic7 7.3% | work, community, institution, environment, company, industry, companionship, country, services, elderly family members, age, health, self-care, wages, young people | |
Topic8 7% | insurance, medical insurance, medical, accident insurance, products, commercial, sickness insurance, pension insurance, cancer prevention, insurance companies, commercial insurance, major illness, rural, medical insurance, life insurance | |
3. Communication and intergenerational conflict | Topic1 18.2% | children, family, kids, brother, man, male, female, marriage, patriarchy, siblings, girls, childbirth, sister, female, pressure |
Topic2 16.8% | emotions, psychological, relationships, character, influence, children, care, spiritual, communication, temper, world, family, anger, mood, inner | |
Topic3 12.3% | job, graduation, home, university, exam, study, pressure, school, salary, boyfriend, provincial capital, hometown, postgraduate, field, development | |
Topic5 10% | house, buy a house, loan, property, investment, suite, obligation, name, deposit, house price, buy a car, buy a house, salary, law, lawyer | |
Topic9 5.1% | Mobile, video, phone, home, friends, WeChat, playing mahjong, wedding, hair, chat, epidemic, elders, messages, hanging out, photos |
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Wang, Y.; Luo, P. Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches. Sustainability 2022, 14, 11847. https://doi.org/10.3390/su141911847
Wang Y, Luo P. Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches. Sustainability. 2022; 14(19):11847. https://doi.org/10.3390/su141911847
Chicago/Turabian StyleWang, Ying, and Peiwen Luo. 2022. "Exploring the Needs of Elderly Care in China from Family Caregivers’ Perspective via Machine Learning Approaches" Sustainability 14, no. 19: 11847. https://doi.org/10.3390/su141911847