. 2016 Jun 22;7(2):573–586. doi: 10.4338/ACI-2015-12-RA-0180

Table 4.

Construct Correlations

Construct^a	Mean	±SD^b	CA^c	ICR^d	AVE^e	Age	ATT	JF	RA
Age	62.46	7.53	SIC	SIC	SIC	SIC^f
ATT	4.31	0.77	0.50	0.800	0.666	-0.123	0.816^*
JF	4.49	0.58	0.836	0.887	0.668	-0.007	0.526^g	0.817^*
RA	4.51	0.63	0.710	0.872	0.773	0.004	0.514^g	0.756^g	0.879^*

^a Constructs: Attitude (ATT), Job Fit (JF), Relative Advantage (RA), and age of patients.

^b SD: Standard deviation

^c CA: Cronbach alpha

^d ICR: Internal composite reliability

^e AVE: Average Variance Extracted

^f SIC: Single item construct

^g Latent variable correlations (Inter-construct correlations)

*The bold values are the square root of AVE. To meet the Fornell-Larcker criterion for discriminant validity, these values should be greater than latent variable correlations.