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Can J Public Health ; 102(6): 427-31, 2011.
Article in English | MEDLINE | ID: mdl-22164552

ABSTRACT

OBJECTIVE: Workforce recruitment and retention challenges are being experienced in public health as in other Canadian health sectors. While there are many nurses working in public health, little research has been done about their job satisfaction. Job satisfaction is linked to recruitment, retention and positive client outcomes. The purpose of this research was to examine the relationships between three modifiable work environment factors (autonomy, control-over-practice, and workload) and Canadian public health nurses' (PHNs) job satisfaction. METHODS: Data were from the 2005 National Survey of the Work and Health of Nurses (response rate, 79.7%; 18,676 nurses). Bivariate and multivariate logistic regression analyses were used for this secondary analysis. Findings were discussed with practicing PHNs, policy-makers and researchers from across Canada at a knowledge translation (KT) 'Think-Tank'. RESULTS: Among the 271 PHNs, 53.5% reported being 'very satisfied' with their jobs. The interaction between autonomy and workload was a significant predictor of PHNs' job satisfaction, (OR 0.97, 95% CI 0.96-0.99, p < 0.01) as was the interaction between age and workload (OR 1.01, 95% CI 1.00-1.01, p < 0.01). Think-Tank participants selected priority areas for application to public health practice, management and research. CONCLUSION: Despite being an important practice factor, this is the first study to reveal the negative influence of PHNs' autonomy when in interaction with an excessive workload. Significant workload findings and the presence of generational differences suggest the need for development of workload measurement tools and public health human resource strategies tailored to a multi-generational workforce.


Subject(s)
Internal-External Control , Job Satisfaction , Professional Autonomy , Public Health Nursing/standards , Workload/psychology , Adult , Age Factors , Attitude of Health Personnel , Canada , Cross-Sectional Studies , Humans , Intergenerational Relations , Logistic Models , Middle Aged , Workforce , Workload/statistics & numerical data
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