Table 4.
The impact of AI on the mental health of manufacturing workers: a robustness tests.
| Variables | Psychological depression | Overall work environment | Mental health |
|---|---|---|---|
| Model 7 | Model 8 | Model 9 | |
| AI | −0.531* (0.282) | 0.536* (0.278) | −1.527** (0.766) |
| Work overtime | −1.033*** (0.2) | 0.381 (0.818) | |
| Overall work environment | −0.442*** (0.142) | ||
| Gender | −0.261 (0.232) | −0.411* (0.239) | −1.605** (0.761) |
| Age | −0.016 (0.014) | 0.010 (0.015) | −0.056 (0.043) |
| Marital status | −0.540 (0.355) | 0.417 (0.403) | −1.704 (1.399) |
| Hukou status | 0.193 (0.273) | 0.476 (0.306) | 0.443 (0.889) |
| Years of education | −0.016 (0.040) | 0.033 (0.043) | −0.052 (0.139) |
| Physical health | −0.466*** (0.142) | 0.833*** (0.158) | −2.173*** (0.475) |
| Employer type | −0.348 (0.442) | −0.815* (0.449) | −0.193 (1.278) |
| Annual income | −0.007 (0.038) | −0.039 (0.049) | −0.050 (0.151) |
| Labor union | 0.206 (0.270) | 0.256 (0.274) | 0.733 (0.881) |
| The number of acquaintances | −0.491** (0.241) | 0.193 (0.251) | −1.210 (0.758) |
| Neighborhood support | 0.137 (0.119) | 0.073 (0.133) | 0.073 (0.398) |
| Regional characteristics | 0.063 (0.288) | 0.504 (0.319) | −0.525 (1.005) |
| Constant | 2.286** (1.022) | 12.111*** (1.180) | 31.139*** (4.959) |
| Observations | 547 | 547 | 547 |
*
p < 0.1,
**
p < 0.05,
***
p < 0.01.