Transcript PS 03-8_Kundum Developing a Tool to Measure Health Worker

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 onsite (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
Table 1: Respondent Characteristics for the 8 Study Hospitals
Hospitals
Respondent
Characteristics
Total
(%)
H1
H2
H3
Gender
(female - %)
49.3
72.4
61.0
Paediatrics
(%)
45.0
69.6
48.8
H4
X2
P value
H5
H6
H7
H8
58.4
59.8
51.8
69.1
47.9
58.9
17.6
0.014
54.8
39.5
32.5 50.0
60.3
49.6
30.4
<0.001
Results…1
Table2: Factor Analysis of the 10-Item Motivation Index
(Rotated Factor Loadings and unique variances)
Factor 1
Variable
Organizational
Commitment
Factor 2
Job Satisfaction 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
Factor 3
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
Results…2
Table 3: Correlation between different Motivation Scores.
23-Item Score
10-Item Score
10-Item Score
(Factor loadings) (Factor loadings) (Equally weighted)
23-Item Score
(Factor loadings)
10-Item Score
(Factor loadings)
10-Item Score
(Equally
weighted)
1.0000
0.9798
(p<0.001)
1.0000
0.9608
(p<0.001)
0.9821
(p<0.001)
1.0000
Results…3
Table 4: Mean 10 Item Motivation Scores by Hospital, from highest to lowest.
Hospital
H2
H3
H4
H8
H5
H7
H1
H6
Total
Mean 10 Item
Motivation Score
Standard Deviation
39.31
37.93
37.09
36.62
36.46
36.29
36.04
35.91
36.94
4.83
5.33
5.29
4.87
5.43
5.63
6.27
5.88
5.54
• 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