Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

Table 5 Stepwise regression models predicting openness, concern, and benefit

Predictor	Model 1: Openness			Model 2: Concern			Model 3: Benefit
Predictor	B	95% CI	β	B	95% CI	β	B	95% CI	β
Age	− 0.01	[− 0.01, 0.00]	− 0.07*	0.00	[0.00, 0.00]	0.00	0.00	[− 0.01, 0.00]	− 0.03
Sex	0.08	[− 0.02, 0.18]	0.05	− 0.22	[− 0.32, − 0.12]	− 0.13***	− 0.07	[− 0.15, 0.02]	− 0.04
Race	− 0.01	[− 0.14, 0.11]	− 0.01	− 0.00	[− 0.12, 0.12]	− 0.00	− 0.12	[− 0.22, − 0.01]	− 0.06*
Ethnicity	0.05	[− 0.14, 0.23]	0.01	− 0.15	[− 0.33, 0.03]	− 0.05	− 0.11	[− 0.26, 0.05]	− 0.04
Employment status	0.27	[0.16, 0.37]	0.14***	− 0.24	[− 0.35, − 0.13]	− 0.14***
Health status				− 0.23	[− 0.36, − 0.09]	− 0.11**
Health system trust	0.04	[0.02, 0.06]	0.12***	− 0.06	[− 0.08, − 0.04]	− 0.20***
Trust in technology	0.17	[0.12, 0.21]	0.25***	− 0.10	[− 0.14, − 0.06]	− 0.16***	0.12	[0.08, 0.16]	0.22***
Faith in technology	0.22	[0.15, 0.29]	0.21***				0.30	[0.24, 0.37]	0.34***
Conscientiousness	− 0.06	[− 0.10, − 0.02]	− 0.09**	0.12	[0.08, 0.16]	0.18***
Agreeableness				0.10	[0.06, 0.14]	0.15***
Extraversion				− 0.04	[− 0.07, − 0.01]	− 0.08**
Social conservatism				0.00	[0.00, 0.00]	− 0.07*
Economic conservatism	0.00	[− 0.01, 0.00]	− 0.07*
R²	.26***			.21***			.25***

N = 916. Age, sex, race, and ethnicity entered in a first step as control variables. Age is continuous. Variables are coded as follows: Sex (1 male; 0 female), race (1 White; 0 non-White), and ethnicity (1 Latino; 0 not-Latino). Employment status (1 full-time; 0 other); health status (1 good/very good/excellent; 0 poor/fair)
*p < .05; **p < .01; ***p < .001

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