Enhancing Regional Elderly Care Through Vocational Nursing: A Strategic PEST-SWOT Analysis and Formation Logic

This study examines the development of higher vocational nursing professional groups (HVNPGS) in promoting regional elderly care through a PEST-SWOT analysis framework. The objective is to identify the internal and external factors influencing the sustainability and effectiveness of vocational nursing programs. Using a mixed-methods approach, the study combines qualitative data from interviews and focus groups with quantitative data from structured surveys conducted across various vocational nursing institutions. The PEST-SWOT analysis model was employed to evaluate the political, economic, social, and technological dimensions impacting the growth of HVNPGs. The findings reveal that political support, particularly government policies and financial subsidies, plays a critical role in the success of vocational nursing programs. Economic sustainability remains a challenge, especially in rural areas, while societal attitudes toward elderly care and nursing professions continue to affect program attractiveness. Technological integration offers opportunities for enhancing nursing education, though disparities in access present ongoing challenges. The study concludes that a comprehensive strategy addressing political, economic, societal, and technological factors is essential for the growth of HVNPGs. The implications suggest that policymakers and educators must prioritise funding, societal engagement, and technological infrastructure to ensure vocational nursing programs that can meet the increasing demands of elderly care.

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Publication Details

Journal
Journal of Advances in Humanities Research
Published
2024-12-25
DOI
https://doi.org/10.56868/jadhur.v3i4.228
Primary Topic
Strategic Planning and Analysis
Type
article
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article

Enhancing Regional Elderly Care Through Vocational Nursing: A Strategic PEST-SWOT Analysis and Formation Logic

Zhou Yong
Journal of Advances in Humanities Research
Strategic Planning and Analysis
article

Enhancing Regional Elderly Care Through Vocational Nursing: A Strategic PEST-SWOT Analysis and Formation Logic

Zhou Yong
article en

Abstract

This study examines the development of higher vocational nursing professional groups (HVNPGS) in promoting regional elderly care through a PEST-SWOT analysis framework. The objective is to identify the internal and external factors influencing the sustainability and effectiveness of vocational nursing programs. Using a mixed-methods approach, the study combines qualitative data from interviews and focus groups with quantitative data from structured surveys conducted across various vocational nursing institutions. The PEST-SWOT analysis model was employed to evaluate the political, economic, social, and technological dimensions impacting the growth of HVNPGs. The findings reveal that political support, particularly government policies and financial subsidies, plays a critical role in the success of vocational nursing programs. Economic sustainability remains a challenge, especially in rural areas, while societal attitudes toward elderly care and nursing professions continue to affect program attractiveness. Technological integration offers opportunities for enhancing nursing education, though disparities in access present ongoing challenges. The study concludes that a comprehensive strategy addressing political, economic, societal, and technological factors is essential for the growth of HVNPGs. The implications suggest that policymakers and educators must prioritise funding, societal engagement, and technological infrastructure to ensure vocational nursing programs that can meet the increasing demands of elderly care.

Journal of Advances in Humanities ResearchVol. 3(4)
Guiyang University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 56%
Strategic Planning and Analysis
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Enhancing Regional Elderly Care Through Vocational Nursing: A Strategic PEST-SWOT Analysis and Formation Logic — Zhou Yong · Journal of Advances in Humanities Research (2024) | TGRS Research Map | TGRS