Table 3.

Estimated average marginal effect on the probability of high job satisfaction and good work–life balance from using digital health technology

Model	Estimated average marginal effect on the probability (95% CI)
Job satisfaction
Unadjusted analysis	0.174 (0.102 to 0.246)
Adjusted analysis	0.162 (0.112 to 0.212)
General practitioners only	0.246 (0.180 to 0.313)
Specialists only	0.107 (0.021 to 0.193)
Physician in training only	0.080 (−0.038 to 0.198)
Adjusted IV analysis	0.142 (−0.013 to 0.297)
Work–life balance
Unadjusted analysis	0.283 (0.198 to 0.367)
Adjusted analysis	0.232 (0.176 to 0.287)
General practitioner only	0.213 (0.125 to 0.301)
Specialist only	0.176 (0.086 to 0.2767)
Physician in training only	0.194 (0.075 to 0.312)
Adjusted IV analysis	0.203 (0.024 to 0.381)

This table presents the estimated average marginal change in the probability of high job satisfaction and good work–life balance from using digital health technology. Each estimate is from a separate probit regression model that includes a full set of covariates from table 1. All the adjusted estimates include the state the practice is located and the physicians’ personality traits. The estimates for the specialists are adjusted for their specialties. The study sample includes 7043 physicians who answered questions on the use of digital health technology, and all the variables used in the analysis. All the estimates are also adjusted for the cross-sectional survey weights. The 95% CIs presented in parentheses are based on SEs clustered at the postcode level. Detailed estimates are shown in online supplemental tables 2 and 3.

P value of Wald test of exogeneity <0.001.

IV, instrumental variable.