1. Developing a Tool to Measure Health Worker Motivation in District Hospitals in Kenya Patrick Mbindyo, Duane Blaauw, Lucy Gilson, Mike English

2. Background Interventions to improve worker practice may fail if HWs are poorly motivated – Worker motivation strongly linked to worker performance Tool development (SAQ) – to characterize average motivation in hospitals – Simple to apply & can quantitatively describe hospitals Nested in larger intervention study seeking to improve worker practices in DH

3. Methods To measure motivation, use subjective or objective methods? Literature review done to source possible constructs for inclusion 17 constructs used- 10 determinants; 7 outcomes Result in SAQ with 71 questions: 5 point Likert scale – strongly agree to strongly disagree Response bias - randomly assorted & 40% negatively worded Piloted to explore its performance – reduced questions to 66 Outcomes – 23 questions

4. Sampling & Data Collection Convenience sample of 90 staff from each hospital (30% of hosp staff) Random sample constraints -staff leave, breaks, shift Total sample size estimate of 720 Data collected by identically trained survey teams on- site (2 weeks per site) Preferentially targeted staff in paediatric areas & other areas with regular contact with sick children Intervention was aimed at improving paediatric care.

5. Data Analysis Data analysed using STATA 9.2. Scoring of Likert scale responses: – 1-5 (where strongly agree is 5 for positively worded qns). – 1-5 (reverse coding for negatively worded qns- strongly disagree is 5) I am confident about my ability to do my job (+ve) I cannot be relied upon by my colleagues at work (-ve) Simple stats used to explore performance of SAQ - frequency distributions, mean and median scores Further analysis done – – Correlation (0.5 and above good); – Cronbach’s alpha; – Factor analysis – data reduction + simplified index

6. Results Respondent Characteristics Hospitals Total (%) X2X2 P value H1H2H3H4H5H6H7H8 Gender (female - %) 49.372.461.058.459.851.869.147.958.917.60.014 Paediatrics (%) 45.069.648.854.839.532.550.060.349.630.4<0.001 Table 1: Respondent Characteristics for the 8 Study Hospitals

7. Results…1 Variable Factor 1 Organizational Commitment Factor 2 Job Satisfaction Factor 3 Conscientiousness 1. No Motivation 0.4478 2. Very satisfied with job 0.5928 3. Satisfied with opportunity to use my abilities in my job 0.5348 4. Job makes me feel good about myself 0.4199 5. Proud to be working for this hospital 0.5420 6. Glad to work for this facility than others in the country 0.5701 7. Hospital inspires me to do my very best on the job 0.4837 8. I always complete my tasks efficiently and effectively 0.5224 9. I am a hard worker 0.5322 10. I am punctual about coming to work 0.4812 Table2: Factor Analysis of the 10-Item Motivation Index (Rotated Factor Loadings and unique variances)

8. Results…2 23-Item Score (Factor loadings) 10-Item Score (Factor loadings) 10-Item Score (Equally weighted) 23-Item Score (Factor loadings) 1.0000 10-Item Score (Factor loadings) 0.9798 (p<0.001) 1.0000 10-Item Score (Equally weighted) 0.9608 (p<0.001) 0.9821 (p<0.001) 1.0000 Table 3: Correlation between different Motivation Scores.

9. Results…3 Hospital Mean 10 Item Motivation Score Standard Deviation H2 39.314.83 H337.935.33 H437.095.29 H836.624.87 H536.465.43 H736.295.63 H136.046.27 H635.915.88 Total36.945.54 Table 4: Mean 10 Item Motivation Scores by Hospital, from highest to lowest. Differences in mean motivation scores statistically significant between H2 &H6 (ANOVA, p<0.001) Not explained by gender, working in paediatrics, or being a clinician

10. Discussion Index able to differentiate study hospitals according to their workers’ reported motivational levels Qualitative data suggests simplified index appropriately indicates variable levels of motivation between hospitals – e.g. differences in management between high and low scored hospitals Questions comprising the 10-item tool approximated issues relevant to staff motivation in district hospitals

11. Conclusion 10-item tool appears to capture motivation quantitatively – output supported by qualitative work Understanding of the context of implementation and doing concurrent qualitative work to triangulate results emphasized Its value will be known with more testing – However, it is potentially useful for wider use