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. 2022 Mar 23;6(3):e28750. doi: 10.2196/28750

Table 6.

Results of seemingly unrelated hierarchical regression analyses with self-threat and resistance to change as dependent variables (full model 4).


Coefficient (SE; 95% CI) Z value P value
Model 4a with dependent variable self-threat

Stage 1 (controls)


Age –0.034 (0.009; –0.052 to –0.016) –3.650 <.001


Gender –0.134 (0.134; –0.396 to 0.129) –1.000 .39


Familiarity –0.086 (0.072; –0.226 to 0.054) –1.210 .25


Group (experienced and novice) 0.317 (0.218; –0.109 to 0.744) 1.460 .15

Step 2 (identity threats)


ProReca 0.503 (0.070; 0.366 to 0.641) 7.170 <.001


ProCapb 0.372 (0.080; 0.215 to 0.529) 4.650 <.001

Step 3 (Temporal distance of AIc, interactions)


Temporal distance 0.137 (0.077; –0.014 to 0.289) 1.780 .08


Temporal distance x ProRec 0.291 (0.078; 0.138 to 0.443) 3.730 <.001


Temporal distance x ProCap –0.203 (0.086; –0.372 to –0.034) –2.350 .02

Intercept 1.071 (0.276; 0.531 to 1.611) 3.880 <.001
Model 4b with dependent variable resistance

Stage 1 (controls)


Age –0.001 (0.009; –0.018 to 0.016) –0.130 .90


Gender –0.134 (0.127; –0.382 to 0.114) –1.060 .29


Familiarity –0.066 (0.068; –0.198 to 0.067) –0.970 .33


Group (experienced and novice) –0.061 (0.206; –0.465 to 0.343) –0.300 .77

Step 2 (identity threats)


ProRec 0.055 (0.066; –0.076 to 0.185) 0.820 .41


ProCap 0.400 (0.076; 0.251 to 0.548) 5.270 <.001

Step 3 (Temporal distance of AI, interactions)


Temporal distance 0.149 (0.073; 0.005 to 0.292) 2.030 .04


Temporal distance x ProRec 0.087 (0.074; –0.057 to 0.232) 1.190 .24


Temporal distance x ProCap –0.165 (0.082; –0.325 to –0.005) –2.020 .04

Intercept 0.237 (0.261; –0.274 to 0.748) 0.910 .36

aProRec: threats to professional recognition.

bProCap: threats to professional capabilities.

cAI: artificial intelligence.