Factors Associated with Evidence-Based Decision-Making Among Specialized Nurses Working in Selected Health Facilities in Nairobi, Kenya

Background: Evidence-Based Decision-Making (EBDM) is central to quality nursing practice, yet many nurses continue to rely on intuition when making clinical decisions. In low-resource settings such as Kenya, limited access to information, knowledge-sharing barriers, and institutional constraints further hinder EBDM. Understanding the factors that influence EBDM among specialized nurses is vital for improving patient care and health system outcomes. Methods: This study employed a concurrent nested mixed-methods design guided by the ACE Star Model. The quantitative arm utilized a cross-sectional census of 51 maternal and child health nurses from four public hospitals in Nairobi, while the qualitative arm involved two in-depth interviews with supervisors. Data were collected using a structured questionnaire and interview guide. Quantitative analysis was conducted using SPSS with logistic regression to identify factors associated with EBDM, while qualitative data were analyzed thematically. Married nurses and those with higher academic qualifications demonstrated marginally lower odds of low EBDM utilisation. Institutional factors and barriers such as limited internet access, staffing constraints, and time shortages were reported but not statistically significant. Qualitative insights highlighted reliance on tacit knowledge, bounded autonomy, and workload pressures as major influences on decision-making. Conclusion: Specialized nurses in Nairobi largely rely on tacit knowledge and intuition, with individual capacities playing a critical role in shaping EBDM. Strengthening research skills, integrating EBDM training early into nursing curricula, and creating institutional support systems are essential for enhancing evidence use in clinical practice. Strategies for capturing and translating tacit knowledge into actionable evidence should be prioritized to improve patient outcomes. Further large-scale, multidisciplinary studies are recommended to validate these findings.