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. 2022 Nov 23;5(4):e39890. doi: 10.2196/39890

Table 4.

Results of 20 multiple imputed cross-validated regression.


Willingness to adopt technology Quality of life from technology Perceived value of technology Confidence using technology

Ma β M β M β M β
Intercept 20 −.11 20 3.19 20 4.55 20 6.34
Tech readiness optimism b 20 .11 20 .11 20 .02
Tech readiness innovativeness 15 .01
Tech readiness insecurity 14 .00 2 .00
Positive tech readiness 18 .01 19 .01 7 .00
General tech experience 20 .06 20 .06
Gender (women) 8 −.06 0
Education 20 .03
General health 11 −.04
Self-assessed comprehension 19 .01
Self-assessed learning ability 11 .00
Self-assessed applying new knowledge 20 .03
Self-assessed problem-solving or reasoning 20 .02
Self-assessed detection 19 .02
Cognitive abilities: fluid 1 −.02
Cognitive abilities: crystalized 18 −.08 7 −.02 20 .14
Perceptions of aging: gains 12 .01 1 .00
Openness to experience 13 .01
Help with technology 20 −.03 20 −.20
Confidence using technology 20 .15 N/Ac N/A N/A N/A N/A N/A
Concern with privacy of technology 1 .00
Perceived effort of technology 20 .11 20 .04
Perceived value of technology 20 .54 N/A N/A N/A N/A N/A N/A
Quality of life from technology 20 .24 N/A N/A N/A N/A N/A N/A
Discounting parameterd 15 −.27

aM: number of models in which the parameter was included.

b—: variable was not selected as predictive in any data record for this dependent variable.

cN/A: not applicable.

dTech readiness discomfort, negative tech readiness, age, self-assessed vocabulary, self-assessed numeric, self-assessed, memory, self-assessed grasping, and perceptions of aging losses were included in the model; however, they are not presented because they were not predictive in any model computed.