Date

7-22-2025

Department

School of Health Sciences

Degree

Doctor of Philosophy in Health Sciences (PhD)

Chair

Matthew Ingle

Keywords

Statistical Modeling, Nurse, Nursing

Disciplines

Health and Physical Education

Abstract

This study aims to investigate if statistical modeling can help to improve the nurse’s work environment by identifying and solving basic workplace stresses. The major problem addressed is the stressful situation of burnout and high turnover levels for nurses, which affects the patient and the quality of care. Therefore, this research is important since it can enhance nurse job satisfaction and retention which subsequently can result in better healthcare outcomes, lower operational costs, and better patient safety. The central research questions guiding this study are: (1) How can statistical modeling aid in the discovery and correction of underlying factors that influence unfavorable working conditions for nurses? (2) What workplace interventions could be implemented based on statistical insights to enhance nurses' quality of work life and job satisfaction? Quantitative interviews, survey analysis using SPSS, and workplace observations constitute three ways of collecting data for this study. Through the interview findings, major themes were found which included excessive workload, leadership problems, and insufficient resources. This was supported by statistical analysis of such correlations as job satisfaction and the availability of resources and leadership support. These findings informed five key recommendations: decreasing nurse-to-patient ratios, strengthening leadership training, executing wellness and mental health programs, supplying more opportunities for professional development, and optimizing resource allocation. The intervention aims at improving workplace conditions, supporting nurse wellbeing and as such improving patient care.

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