Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Nursing

Supervisor

Kerr, Michael S.

Abstract

In Canada, a close look at the nursing workforce shows a decline due to limited supply and increasing demand resulting in a looming shortage in the near future. Retaining nurses’ is a key strategy to overcome the shortage by limiting nurses’ turnover. Nurses’ job dissatisfaction is the most significant predictor of turnover intention and is associated with undesired outcomes such as nurses’ absenteeism, burnout, low service quality, and patient dissatisfaction. The differences in factors affecting job satisfaction between rural and urban nurses have not been fully studied. This study aimed to identify the differences and similarities in the extrinsic and intrinsic factors that influence job satisfaction among nurses in urban and rural southern Ontario; to determine the impact of job satisfaction on nurses’ turnover intention among nurses working in rural and urban settings, and to develop an instrument to measure job satisfaction for nurses working in acute care settings. A non-experimental, cross-sectional correlational design was used. Data were collected between May 2019 and July 2019 in southern Ontario. A non-proportional stratified sampling technique was used for recruiting the sample and participants were given the option to respond either online or by mailed survey. A total of 349 participants completed the study survey which included the newly developed Acute Care Nurses Job Satisfaction Scale and the Anticipated Turnover Scale. The results showed no significant difference between rural and urban nurses in either overall job satisfaction or turnover intention. Peer support/work conditions, quality of supervision, and achievement/job interest/responsibility were significant overall predictors of job satisfaction in rural and urban settings. There was a significant difference between rural and urban nurses in terms of satisfaction from benefits and job security. Moreover, the nurses’ job satisfaction levels in both settings correlated negatively with their turnover intention. The Acute Care Nurses Job Satisfaction Scale demonstrated acceptable psychometric properties. This study confirmed that several extrinsic and intrinsic factors are associated with nurses’ job satisfaction in rural and urban settings. Developing strategies that improve satisfaction by modulating these specific factors may improve nurses’ job satisfaction, reduce turnover and ultimately positively impact patient care.

Summary for Lay Audience

In Canada, the predicted nursing shortage is a potentially significant problem that could negatively impact safe patient care. Nurses’ retention is one of the key strategies to overcome this shortage by limiting the loss of nurses due to job turnover. Low job satisfaction is associated with high nurses’ turnover. It is also associated with lower patient satisfaction and poorer quality health services. Working in rural hospitals can be different than working in urban hospitals in terms of availability of resources, type of patients, workload and service provided, hence nurses in these two settings may be expected to have different factors determining their job satisfaction. In this study, surveys were mailed to a sample of nurses working in hospitals located in southern Ontario, aiming to collect data about their job satisfaction and turnover intention. After data analysis, no differences in job satisfaction and turnover intention were found between nurses working in rural and urban areas. However, peer support/work conditions, quality of supervision, and achievement/job interest/responsibility were all found to be related to nurses’ job satisfaction. Also, rural nurses were more satisfied with benefits and job security compared to urban nurses. Finally, higher nurses’ job satisfaction was related to lower turnover intention. The findings of this study can help in tailoring plans for improving nurses’ job satisfaction and reducing turnover intention based on the working context.

Available for download on Saturday, December 31, 2022

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