Association between community environment and dependency among the elderly people from a service provision perspective

Pan, YiYang; Chen, Yuan; Cui, PingYu; Waili, Nuremaguli; Li, Ying

doi:10.1186/s12877-022-03687-z

Cited by 3 publications

(3 citation statements)

References 45 publications

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“…Stroke patients in rural areas may be insensitive to disease perception due to financial constraints or lack of stroke-related knowledge, leading to delay in seeking medical treatment and missing the optimal period of treatment and rehabilitation ( 72 ). The study points out that the health care resources and facilities of the environment in which older adults live are significantly associated with care dependency ( 73 ). In addition to the resource needs of the elderly, a point that cannot be ignored is that the current social changes and demographic changes are changing the family structure and the size of the elderly population, and that a portion of the rural elderly are separated from their adult children for long periods of time and lack other ways of emotional support, which may be one of the reasons influencing the low level of social support and the lower independence of the patients who reside in rural areas for a long period of time after the onset of the disease ( 74 ).…”

Section: Discussionmentioning

confidence: 99%

Developmental trajectory of care dependency in older stroke patients

Lin,

Dong,

Huang

et al. 2024

Front. Neurol.

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BackgroundStroke is the leading cause of death in China. Older stroke survivors often have other chronic conditions, not only musculoskeletal deterioration due to age, but also changes in body image that can be brought on by stroke and other diseases, making them unable to take good care of themselves and dependent on others. The degree of dependency affects the rehabilitation progress of stroke survivors and shows dynamic changes that need to be recognized.ObjectivesThis study investigates the trajectory of dependency changes in older stroke patients with comorbidities and analyze the influencing factors.MethodsGrounded in the Chronic Illness Trajectory Framework (CITF), a longitudinal study was conducted from February 2023 to October 2023, tracking 312 older stroke patients with comorbidities admitted to two tertiary hospitals in Guangzhou. Care dependency levels were assessed using Care Dependency Scale on admission day 5 (T0), at discharge (T1), 1 month post-discharge (T2), and 3 months post-discharge (T3). Growth Mixture Model were utilized to identify trajectory categories, and both univariate analysis and multivariate logistic regression methods were employed to explore factors associated with different developmental trajectories.ResultsA total of four developmental trajectories were fitted, C1 (high independence-slow increased group, 52.0%), C2 (moderate independence-rapid increased group, 13.0%), C3 (moderate independence-slow increased group, 25.0%), and C4 (low independence-increased and decreased group, 10.0%). Length of hospital stay, place of residence, level of social support, residual functional impairments, NIHSS score, and BI index independently influence the trajectory categories.ConclusionThere is heterogeneity in care dependency among older stroke patients with comorbidities. Most patients gradually reduce their dependency and become more independent, but others remain dependent for an extended period of time. It is recommended to focus on patients who live in rural areas, have low social support, have high admission NIHSS scores and have residual functional impairment, and provide them with personalized continuity of care and rehabilitation services in order to reduce care dependency and the burden of care, and to improve patients’ quality of life.

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Section: Discussionmentioning

confidence: 99%

Developmental trajectory of care dependency in older stroke patients

Lin,

Dong,

Huang

et al. 2024

Front. Neurol.

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“…The Grey Model, first proposed by a professor at Huazhong University of Science and Technology in 1982 22 , has attracted considerable attention from scholars and researchers worldwide and has been widely applied in various domains. A Grey System is defined as a system in which, in a data, some information is known, while other information is unknown 23 .…”

Section: Ai To Promote Social Elderly Care Servicesmentioning

confidence: 99%

Opportunities and challenges of integrating artificial intelligence in China's elderly care services

Zhao,

2024

Sci Rep

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The challenge of elderly care presents a formidable task, demanding the collective attention of governmental bodies and diverse sectors of society. The integration of Artificial Intelligence (AI) into the research and development of Social Elderly Care Service (ECS) has emerged as a dominant trend, holding substantial importance in the establishment of an efficient ECS system. This study aims to serve as a comprehensive reference for the advancement of China's ECS system, achieved through the harmonious integration of a social ECS system with AI capabilities. This paper introduces the fundamental theory of AI, delving into the intricacies of the greyscale model of AI. Furthermore, it provides an overview of the current landscape of elderly care and elder care institutions, offering scientific data and insights to propel further research on AI development and system construction. Through an analysis of the existing research status, the study identifies prevalent issues within the AI-ECS integration, emphasizing pivotal factors influencing the construction of a robust social ECS system. To address these concerns, the study puts forth specific and viable policy recommendations. Notably, the questionnaire's statistics underscore that 83% of the elderly populace would opt for AI-driven solutions in selecting intelligent products, thereby underscoring the pivotal role of AI within the social ECS system. The challenges facing elderly care systems, including demographic shifts, resource constraints, and evolving societal norms, demand innovative solutions for providing efficient and effective care. This study addresses these challenges by exploring the integration of Artificial Intelligence (AI) into Social Elderly Care Services (ECS) in China. By delving into the theory of AI and assessing the existing research status, the study identifies key issues in AI-ECS integration and proposes viable policy recommendations. Insights from stakeholder surveys further highlight the importance of AI-driven solutions in meeting the needs of the elderly population.

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“…Family environments for older adults people can sometimes be associated with negative experiences such as isolation and loneliness ( 7 ). There is a significant correlation between the dependency of older adults people and the availability of environmental resources within the community ( 19 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Does the community service environment affect the willingness of older adults people to socialize for older adults care?

Huang,

Feng,

Shi

2024

Front. Public Health

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Population ageing is a significant trend in social development and will remain a fundamental national condition in China for the foreseeable future. Socialized older adults care has become a crucial strategy for China to address population ageing. However, the current levels of acceptance and willingness to seek socialized older adults care among older adults are relatively low. This study focuses on examining how the community environment and services influence older adults people’s willingness to engage in social activities related to older adults care. Using data from the China Longitudinal Ageing Social Survey (CLASS) (N = 9,657), this study investigated the impact of the community service environment on older adults people’s willingness to participate in social activities related to older adults care through a logit model. The study revealed that 9.15% of older adults (N = 9,657) in China are willing to engage in social activities related to older adults care. Furthermore, the individual characteristics and family support of older adults play a significant role in shaping their willingness to engage in older adults care. The provision of medical services, daily care services, and entertainment venues by the community positively influence older adults people’s willingness to participate in social activities related to older adults care (p < 0.01), whereas psychological counselling services have a negative impact (p < 0.01). The impact of community services on older adults people’s willingness to engage in social activities related to older adults care varies due to factors such as smoking and chronic diseases. These findings provide valuable insights for improving older adults’ social engagement in China.

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Association between community environment and dependency among the elderly people from a service provision perspective

Cited by 3 publications

References 45 publications

Developmental trajectory of care dependency in older stroke patients

Developmental trajectory of care dependency in older stroke patients

Opportunities and challenges of integrating artificial intelligence in China's elderly care services

Does the community service environment affect the willingness of older adults people to socialize for older adults care?

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