Research Article

Acceptance of 3D Printing by Occupational Therapists: An Exploratory Survey Study

Table 4

Correlations between demographic variables, experience with 3D printing, UTAUT constructs, and general attitude.

VariablesbSD123456789101112131415

Demographic variables
(1) Age11935.6412.69
(2) Gender (female vs. male)117n/an/a-.04
(3) Country classification (developed vs. developing economy)119n/an/a-.21-.37
(4) Technology generation (3D virtual vs. software)113n/an/a.83-.06-.13
(5) Early adopter status (1-5)1032.800.85-.21-.26.37.01

Experience with 3D printing
(6) Years of experience with 3D printing10113.3311.36.94.08-.33.79.04
(7) Number of objects printed312.290.94-.41-.05.02-.09-.14-.45
(8) Self-reported level of experience with 3D printing (1-5)372.541.17-.14-.03.14.05-.05-.02.47
(9) Self-reported skill level regarding 3D printing (1-5)372.541.07-.12-.27.32.06.00-.06.28.69

UTAUT constructs and general attitude
(10) Behavioural intention to use 3D printing in one’s job (BIU) (1-5)1053.550.91.09-.20.42.07.50.01.23-.06-.08
(11) Performance expectancy (PE) (1-5)1173.400.83-.06-.14.47-.19.30-.10.08-.01-.06.62
(12) Effort expectancy (EE) (1-5)1103.490.54-.08.00.09-.10.03-.14.10.00.11.23.19
(13) Social influence (SI) (1-5)1102.760.73.21-.14.28.18.48.18.00-.04-.09.62.60.09
(14) Facilitating conditions (FC) (1-5)1073.210.63.10-.13.23-.06.47.07.00-.05-.05.62.56.15.57
(15) General attitude towards using 3D printing in one’s job (1-7)1005.631.11.17-.27.26.09.34.11.21.27.26.57.61.15.54.52

aGrey cells indicate significant correlations (; ). bThis column shows the number of participants who answered all scale items for the constructs.