Skip to main content

Table 6 Latent construct correlations (upper off-diagonal values), square root of AVE (bold, diagonal) and scale intercorrelations (lower off-diagonal values)

From: Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach

Nr

Factors

1

2

3

4

5

6

7

8

9

1

Physician–patient relationship

.73

-.42e a

-.29e

-.42e

-.34e

-.39e

-.18c

-.25e

-.24d

2

Insecurity

-.36d b

.89

.37e

.50e

.35e

.44e

.13

.13

.19c

3

Falsified patient information

-.32d

.36d

.89

.39e

.27e

.35e

.35e

.33e

.15c

4

Reservations

-.37d

.44d

.31d

.75

.67e

.34e

.15

.08

.39e

5

Fear of side effects

-.28d

.29d

.25d

.50d

.82

.27d

.10

.02

.22d

6

Individual decisions

-.30d

.35d

.34d

.26d

.21c

.74

.51e

.29e

.29e

7

Avoidance of drug side effects

-.14c

.04

.35d

.13

.08

.36d

.79

.18c

.17c

8

Carelessness

-.19d

.10

.29d

.07

-.01

.20d

.12

.79

.12

9

Drug intake in public

-.22d

.16c

.11

.32d

.15c

.18d

.13

.07

.81

  1. aFornell-Larcker-criterion of discriminant validity: each latent correlation must be lower than both the corresponding row and column value (square root of AVE of each construct)
  2. bInterpretation according to product-moment correlation: > .1 weak effect; > .3 moderate effect; > .5 strong effect
  3. cCorrelations are significant at the level of .05 (2-tailed)
  4. dCorrelations are significant at the level of .01 (2-tailed)
  5. eCorrelations are significant at the level of .001 (2-tailed)