Interventions Addressing Stress in Healthcare: Traditional and Technological Approaches-evaluation Using the Mcdm Technique
Year: 2025
Type: article
Abstract: Workplace stress in the healthcare sector is a multifaceted issue that significantly affects employee well-being and performance and was exacerbated by the COVID-19 pandemic. Key stressors include excessive workloads, long hours, high demands, emotional obligations, and inadequate support, all which lead to mental, physical, and emotional health issues, reduced productivity, and increased absenteeism. Effective stress management interventions include technology-enhanced mindfulness, cognitive-behavioral therapies, and physical and expressive arts interventions. Technology-enhanced interventions show promise but face challenges like gender inequality and data security concerns. Traditional interventions improve mindfulness and well-being but have inconclusive impacts on burnout and resilience. Expressive arts and physical interventions reduce occupational stress, though larger studies are needed. Managing stress requires a comprehensive approach, combining traditional and technological methods. The Analytic Hierarchy Process (AHP) was conducted with 20 medical officers in an Indian hospital and identified Workload and Time Constraints (WTC) and Organizational Constraints (OC) as primary stressors. A sensitivity analysis was conducted to determine how variations in the prioritized variables would impact various alternatives. This study was conducted with doctors working as medical officers in a private hospital with the assumption that a decision on traditional or technical interventions would help decrease stress. Furthermore, this study is aligned with the United Nation Sustainable Development Goal, SDG-3 (good health and well-being).
Authors: Akankhya Panda, Sowdamini Thatta, Saurabh Pradhan
Institution: GITAM University
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409162472