Senior management leadership, social support, job design and stressor-to-strain relationships in hospital practice

摘要

Purpose: The purpose of this paper is to examine the effect of the quality of senior management leadership on social support and job design, whose main effects on strains, and moderating effects on work stressors-to-strains relationships were assessed. Design/methodology/approach: A survey involving distribution of questionnaires was carried out on a random sample of health care employees in acute hospital practice in the UK. The sample comprised 65,142 respondents. The work stressors tested were quantitative overload and hostile environment, whereas strains were measured through job satisfaction and turnover intentions. Structural equation modelling and moderated regression analyses were used in the analysis. Findings: Quality of senior management leadership explained 75 per cent and 94 per cent of the variance of social support and job design respectively, whereas work stressors explained 51 per cent of the variance of strains. Social support and job design predicted job satisfaction and turnover intentions, as well as moderated significantly the relationships between quantitative workload/hostility and job satisfaction/turnover intentions. Research limitations/implications: The findings are useful to management and to health employees working in acute/specialist hospitals. Further research could be done in other counties to take into account cultural differences and variations in health systems. The limitations included self-reported data and percept-percept bias due to same source data collection. Practical implications: The quality of senior management leaders in hospitals has an impact on the social environment, the support given to health employees, their job design, as well as work stressors and strains perceived. Originality/value: The study argues in favour of effective senior management leadership of hospitals, as well as ensuring adequate support structures and job design. The findings may be useful to health policy makers and human resources managers.