Developing a Tool to Measure Health Worker Motivation in

District Hospitals in Kenya

Patrick Mbindyo, Duane Blaauw, Lucy Gilson, Mike English

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

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

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.

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

Results

Respondent

Characteristics

HospitalsTotal

(%)X2

P value

H1 H2 H3 H4 H5 H6 H7 H8

Gender(female - %)

49.3

72.4

61.0 58.459.

851.

869.

147.

958.9

17.6

0.014

Paediatrics (%)

45.0

69.6

48.8 54.839.

532.

550.

060.

349.6

30.4

<0.001

Table 1: Respondent Characteristics for the 8 Study Hospitals

Results…1

Variable

Factor 1Organization

al Commitment

Factor 2Job

Satisfaction

Factor 3Conscientious

ness

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)

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.

Results…3

HospitalMean 10 Item

Motivation Score

Standard Deviation

H2 39.31 4.83H3 37.93 5.33H4 37.09 5.29H8 36.62 4.87H5 36.46 5.43H7 36.29 5.63H1 36.04 6.27H6 35.91 5.88

Total 36.94 5.54

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

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

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