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Table 4 Effect of a social prescription on number of return visits including interactions

From: Once is rarely enough: can social prescribing facilitate adherence to non-clinical community and voluntary sector health services? Empirical evidence from Germany

Dependent variable = Number of return visits (1) (2) (3) (4) (5)
Social prescription (=1) 1.162** (0.086) 0.807 (0.192) 1.149 (0.100) 1.204* (0.114) 1.201*** (0.079)
Male (=1) 0.893 (0.080) 0.891 (0.063) 0.898 (0.063) 0.896 (0.064) 0.893 (0.063)
Age (in years) 0.997 (0.002) 0.995* (0.003) 0.997 (0.002) 0.997 (0.002) 0.997 (0.002)
Distance (in km) 0.978*** (0.009) 0.977*** (0.009) 0.976** (0.011) 0.978*** (0.009) 0.978** (0.009)
Visit due to overweight (=1) 1.257*** (0.082) 1.257*** (0.082) 1.256*** (0.082) 1.292*** (0.107) 1.250*** (0.082)
Visit due to psychological concern (=1) 1.056 (0.183) 1.059 (0.183) 1.055 (0.183) 1.056 (0.184) 1.294 (0.265)
Social prescription × Male 1.013 (0.148)     
Social prescription × Age   1.006 (0.004)    
Social prescription × Distance    1.005 (0.018)   
Social prescription × Visit due to overweight     0.932 (0.118)  
Social prescription × Visit due to psychological concern      0.519** (0.169)
Observations 1734 1734 1734 1734 1734
  1. This table presents mean interaction effects and robust standard errors (in parentheses) of the negative binomial model. The dependent variable is Number of Returns. The main variable of interest is Social Prescription. The incidence rate ratio (IRR) is reported. All the p-values have been replaced by stars and categorised as follows. ***: p < 0.01; **: p < 0.05; *: p < 0.10