Table 3:
Relationship between TA visits (time), independent variables, and the interaction of provider professional category with the slope of the TA visit time trajectory with the number of correct PP messages delivered1
| Model 1 | ||||
|---|---|---|---|---|
| Variable | β | SE | t | p-value |
| Technical Assistance visits (time) | 1.084 | 0.037 | 29.04 | <0.001 |
| Intercept | 1.973 | 0.140 | 14.09 | <0.001 |
| Model 2 | ||||
| Variable | β | SE | t | p-value |
| Technical Assistance visits (time) | 0.920 | 0.063 | 14.57 | <0.001 |
| Provider is clinician | −0.907 | 0.478 | −1.90 | 0.058 |
| Time x provider category interaction | 0.230 | 0.079 | 2.91 | 0.004 |
| Sex of provider - female | −0.076 | 0.215 | −0.36 | 0.722 |
| Sector in health center | ||||
| Psycho-social support | −0.677 | 0.444 | −1.52 | 0.128 |
| Integrated Consultation | −0.558 | 0.274 | −2.04 | 0.041 |
| TB Clinic | −1.240 | 0.361 | −3.43 | 0.001 |
| Adult and adolescent counseling and testing | −0.824 | 0.537 | −1.54 | 0.125 |
| Client sex | 0.176 | 0.132 | 1.34 | 0.180 |
| Client ART status | 0.136 | 0.138 | 0.98 | 0.325 |
| Intercept | 2.793 | 0.598 | 4.67 | <0.001 |
The intraclass correlation (ICC) for the null model was 0.092. An ICC of 0.092 means that 9% of the variation in PP message provision can be attributed to a healthcare provider effect.