Predictive Modelling of Employee Job Satisfaction from Transformational Leadership and Work Motivation in Primary Healthcare
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Job satisfaction among primary healthcare staff is shaped by leadership style and workforce motivation, yet most evidence on transformational leadership in healthcare comes from hospitals rather than primary care, and few studies quantify how much of its association with satisfaction is carried through motivation. Objective: this cross-sectional study modelled the associations among transformational leadership, work motivation and employee job satisfaction at a single Indonesian primary healthcare centre, and tested work motivation as a mediating pathway. Methods: all 42 staff at Gunung Kembang Public Health Centre, Bengkulu Province, completed adapted Multifactor Leadership Questionnaire, Manifest Needs Questionnaire and Job Satisfaction Survey instruments in March 2026. Partial least squares path modelling was used, with bootstrapping (5,000 subsamples) for significance testing and a post hoc power analysis. Results: transformational leadership was positively associated with work motivation (β = 0.811, p < .001) and, to a smaller extent, directly with job satisfaction (β = 0.440, p = .003); work motivation was positively associated with job satisfaction (β = 0.475, p = .001). The indirect association through motivation (β = 0.385, p = .003) accounted for an estimated 47 per cent of the total association, consistent with partial mediation. The model explained 65.7 per cent of the variance in motivation and 75.8 per cent in satisfaction. A full-collinearity check yielded variance inflation factors of 3.5 to 4.0, indicating common method variance cannot be ruled out. Conclusion: In this small, single-centre sample, transformational leadership and work motivation were strongly and positively associated with job satisfaction, with motivation carrying a substantial share of the leadership association. Findings are associational, not causal, and require replication in larger, multi-centre and longitudinal samples before informing workforce policy
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