| Health post-injury |
---|
Model 1 | Model 2 |
---|
Independent variable | OR | CI | Â |
p
| AOR | CI | Â |
p
|
---|
Fairness claims process | 2.78 | 1.45, | 5.33 | .002 | 2.83 | 1.40, | 5.71 | .004 |
Age | Â | Â | Â | Â | 1.01 | 0.99, | 1.04 | .23 |
Gender | Â | Â | Â | Â | 0.91 | 0.45, | 1.83 | .78 |
Country of birth | Â | Â | Â | Â | 1.00 | 0.48, | 2.12 | .99 |
Socio-economic status | Â | Â | Â | Â | 1.12 | 0.57, | 2.20 | .74 |
Education | Â | Â | Â | Â | 0.88 | 0.42, | 1.88 | .75 |
Marital status | Â | Â | Â | Â | 0.90 | 0.46, | 1.79 | .77 |
Injury | Â | Â | Â | Â | 1.35 | 0.57, | 3.16 | .49 |
Hospital admission | Â | Â | Â | Â | 2.04 | 0.97, | 4.26 | .06 |
Time after injury | Â | Â | Â | Â | 0.62 | 0.32, | 1.20 | .16 |
Health pre-injury | Â | Â | Â | Â | 6.15 | 1.09, | 34.61 | .04 |
- Note: Model 1 Nagelkerke R2 = 0.08; Model 2 Nagelkerke R2 = 0.16
- Multiple logistic regression analysis, modelling the probability of good or excellent health (versus fair or poor health). Model 1 explores the unadjusted association between the overall fairness perception and health. Model 2 adjusts for demographic, injury variables, and pre-injury health. There was no multicollinearity
- Coding: Overall fairness claims process (0 = disagree/neutral; 1 = agree); Gender (0 = Male; 1 = Female); Country of birth (0 = Other; 1 = Australia); Socio-economic status (0 = Lower; 1 = Higher); Education (0 = Low/Medium; 1 = High); Marital status (0 = Single/Divorced; 1 = Married); Injury (0 = Other; 1 = Whiplash/soft tissue injury); Hospital admission (0 = No; 1 = Yes); Time after injury (0 = 12 months; 1 = 24 months); Health pre-injury (0 = Poor; 1 = Good); Health post-injury (0 = poor/fair, 1 = good/excellent). Reference category = 0