Work-Life Balance and Psychological Well-Being Among Nursing Officers during the Covid-19 Pandemic: A Cross-Sectional Study in a Tertiary Care Hospital in Bhatinda

Background: The COVID-19 pandemic placed unprecedented psychological and occupational stress on healthcare workers, particularly nursing officers who served on the frontlines. Prolonged exposure to high-risk environments, increased workloads, and emotional fatigue have raised concerns about their mental health and overall well-being. Objective: This study aimed to examine the relationship between work-life balance and psychological well-being among nursing officers during the COVID-19 pandemic in a tertiary care hospital in Bathinda, India. Methods: A descriptive cross-sectional survey was conducted among 43 nursing officers who had direct involvement in COVID19 patient care. Standardized tools were used: Hayman’s Work-Life Balance Scale to assess balance across time, involvement, and satisfaction domains, and Ryff’s Psychological Wellbeing Scale to evaluate six dimensions of well-being. Data were analyzed using descriptive statistics and Pearson’s correlation. Results: The mean psychological well-being score was 157.37 ± 14.25, and the mean work-life balance score was 53.30 ± 9.73. A weak positive correlation (r = 0.175, p = 0.131) was observed between psychological well-being and work-life balance, suggesting a modest association.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-09-23
DOI
https://doi.org/10.22214/ijraset.2025.74279
Primary Topic
COVID-19 Pandemic Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Work-Life Balance and Psychological Well-Being Among Nursing Officers during the Covid-19 Pandemic: A Cross-Sectional Study in a Tertiary Care Hospital in Bhatinda

Lt Col Neelam Chand
International Journal for Research in Applied Science and Engineering Technology
COVID-19 Pandemic Impacts
article

Work-Life Balance and Psychological Well-Being Among Nursing Officers during the Covid-19 Pandemic: A Cross-Sectional Study in a Tertiary Care Hospital in Bhatinda

Lt Col Neelam Chand
article en

Abstract

Background: The COVID-19 pandemic placed unprecedented psychological and occupational stress on healthcare workers, particularly nursing officers who served on the frontlines. Prolonged exposure to high-risk environments, increased workloads, and emotional fatigue have raised concerns about their mental health and overall well-being. Objective: This study aimed to examine the relationship between work-life balance and psychological well-being among nursing officers during the COVID-19 pandemic in a tertiary care hospital in Bathinda, India. Methods: A descriptive cross-sectional survey was conducted among 43 nursing officers who had direct involvement in COVID19 patient care. Standardized tools were used: Hayman’s Work-Life Balance Scale to assess balance across time, involvement, and satisfaction domains, and Ryff’s Psychological Wellbeing Scale to evaluate six dimensions of well-being. Data were analyzed using descriptive statistics and Pearson’s correlation. Results: The mean psychological well-being score was 157.37 ± 14.25, and the mean work-life balance score was 53.30 ± 9.73. A weak positive correlation (r = 0.175, p = 0.131) was observed between psychological well-being and work-life balance, suggesting a modest association.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(9)
Openalex Percentile: Top 66%
COVID-19 Pandemic Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.