Pattern and perception of wellbeing, quality of work life and quality of care of health professionals in Southwest Nigeria

Table 2 Factors that best differentiate poor from good quality of life (WHO-QoL)

Predictors	Regression Coefficients (B)	Odds ratio (β)	Wald	P-value
Age (years)
20 – 29 (reference)			9.507	0.050*
30 – 39	0.362	1.436	3.658	0.056
40 – 49	0.673	1.961	7.263	0.007*
50 – 59	0.877	2.403	8.706	0.003*
60 – 69	1.249	3.486	1.436	0.231
Gender (reference = female)
Male	0.279	1.322	3.740	0.053
Years of practice
0–2 (reference)			12.788	0.005*
3–5	0.181	1.199	1.009	0.315
6–10	-0.268	0.765	1.586	0.208
≥ 11	-0.645	0.525	6.827	0.009*
Designation
Nurse (reference)			32.411	< 0.001*
Medical practitioner	-0.763	0.466	20.401	< 0.001*
Pharmacist	-0.298	0.743	1.826	0.177
Physiotherapist	0.159	1.172	0.452	0.501
Radiographer	-0.226	0.798	0.053	0.819
Medical lab. Scientist	0.070	1.072	0.080	0.777
Occupational therapist	-0.560	0.571	0.597	0.440
Others	0.557	1.745	0.542	0.461
Personal Wellbeing	1.199	3.318	99.098	< 0.001*
Quality of Work Life	0.671	1.957	29.812	< 0.001*
Constant	-1.136	0.321	41.371	< 0.001*

Approach: Forward Wald binary logistic regression
Model summary: χ² (17, N = 1567) = 256.12, p < 0.001. Nagelkerke R² = 21.3%. Overall prediction success was also modest at 69.8%, with 60.0% of people with good QoL correctly classified and 77.3% of poor QoL classified
^* = statistic is significant at p < 0.05

ISSN: 1472-6963