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Table 5 Factors that best classify health practitioners with good and poor quality of care

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

Predictors

Regression Coefficients (B)

Odds ratio (β)

Wald

P-value

Age (years)

 20 – 29 (reference)

  

8.240

0.083

 30 – 39

-0.209

0.811

1.668

0.196

 40 – 49

0.142

1.153

0.643

0.423

 50 – 59

-0.183

0.833

0.773

0.379

 60 – 69

1.033

2.809

1.210

0.271

Gender (reference = female)

 Male

-0.333

0.717

5.571

0.018*

Designation

 Nurse (reference)

  

24.921

0.001*

 Medical practitioner

-0.486

0.615

8.520

0.004*

 Pharmacist

-0.751

0.472

11.030

0.001*

 Physiotherapist

0.080

1.083

0.124

0.725

 Radiographer

-0.868

0.420

0.582

0.446

 Medical lab. scientist

0.039

1.039

0.027

0.870

 Occupational therapist

1.237

3.446

2.940

0.086

 Others

-0.687

0.503

0.912

0.340

Nature of appointment

 Full time (reference)

  

7.232

.027*

 Part time

-0.466

0.628

5.527

.019*

 Casual

0.818

2.266

1.367

0.242

Work volume per week

 < 20 (reference)

  

12.918

0.005*

 20–40

0.103

1.109

0.122

0.727

 41–60

0.498

1.646

2.994

0.084

 > 60

0.637

1.891

4.242

0.039*

Personal Wellbeing

0.355

1.427

8.833

0.003*

Quality of Work Life

0.726

2.066

34.932

 < 0.001*

Constant

-0.820

0.441

6.844

0.009*

  1. Approach: Forward Wald binary logistic regression
  2. Model summary: χ2 (19, N = 1580) = 149.198, p < 0.001. Nagelkerke R2 = 13.0%. Overall prediction success was modest at 65.4%, with 39.0% of people providing good quality of care correctly classified and 82.5% of people classified as providing poor quality of care
  3. * = statistic is significant at p < 0.05