Bringing Functional Family Probation Services to the Community: A Qualitative Case Study

Austin, Denise Lynmarie

doi:10.15760/etd.1435

Cited by 1 publication

(1 citation statement)

References 83 publications

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“…The incidence of chronic diseases such as cardiovascular and cerebrovascular diseases, tumors, and other chronic diseases has increased, the disease spectrum has changed, medical costs have increased rapidly, and the burden on the family has increased relatively, which to a large extent has limited the medical needs of the population and the rational use of health resources [1][2]. To comply with the transformation of the medical model, it is an inevitable trend of medical development to move from the hospital to the community to provide direct, continuous, comprehensive, convenient, fast, economical, and high-quality services for individuals, families, and society [3].…”

Section: Introductionmentioning

confidence: 99%

Exploration of a deep learning-based mechanism for predicting the work competence of community caregivers

Huang,

Li,

Zhang

et al. 2024

Applied Mathematics and Nonlinear Sciences

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To predict the workability of community nursing staff and provide corresponding training strategies based on the results. In this study, a nursing staff workability prediction model based on R-GCN-GRU was constructed. In the process of community nursing staff workability feature extraction, the attention mechanism is introduced, combined with the degree of association between the captured nodes of the R-GCN network and the long-term memory capacity of the GRU network, and the model optimization is carried out using the cross-entropy loss function. Finally, the workability of community caregivers in a city in Guangdong Province was predicted to verify the accuracy of the model from multiple perspectives. The results showed that clinical handling ability, keen observation ability, and communication ability were more valued by most caregivers, and their selection rates all reached 98.4%. On the other hand, clinical research, organizational management, and innovation abilities were relatively low. In the ability prediction of individual characteristics, the highest income personnel’s working ability was second only to the lowest salary personnel reaching 44.61±6.03. The working ability of older age and higher-position nursing staff, and nursing staff with more than 25 years of service reached 45.62±6.14, 48.30±5.22, and 45.86±5.52, respectively.

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Section: Introductionmentioning

confidence: 99%