Table 2 Measurement model.

From: Exploring the resistance to e-health services in Nigeria: an integrative model based upon the theory of planned behavior and stimulus-organism-response

Construct

Measurement items

Loading

Cronbach’s α

Composite reliability

Average variance extracted

Variance inflation factor

Skewness

CO

CO1: I receive many junk emails concerning health services.

0.86

0.94

0.97

0.79

3.23

−0.34

CO2: I often feel overloaded with information concerning related services.

0.92

4.85

−0.25

CO3: I receive more information than I can process about e-health.

0.92

4.34

−0.173

CO4: I generally get too many notifications of push messages, news feeds.

0.88

3.549

−0.39

CO5: I frequently send a greater number of messages than I initially intended to.

0.86

2.29

−0.05

CHO

CHO1: When considering eHS, there are too many options to choose from.

0.92

0.90

0.91

0.84

2.79

−0.23

CHO2: When considering health-related services online, I need help choosing what would be most suitable for me.

0.91

2.87

−0.32

CHO3: I feel overwhelmed by the variety of health-related choices available through eHS online.

0.93

3.08

−0.32

PR

PR1: Engaging in eHS can lead to errors and damage to one’s health.

0.94

0.93

0.93

0.88

3.77

−0.002

PR2: It is uncertain whether eHS would be as effective as I think.

0.95

4.61

−0.13

PR3: It is probable that eHS would not be worth their cost (e.g., subscriptions to use health apps).

0.93

3.31

−0.08

HL

HL1: It is challenging to determine the reliability of health risk information in the media.

0.88

0.93

0.98

0.82

3.49

−0.46

HL2: It is difficult to determine which everyday behaviors are connected to my overall health.

0.90

3.58

−0.41

HL3: It is challenging to find information on how to handle health problems such as stress or depression effectively.

0.93

 

3.39

−0.26

HL4: Determining how to protect yourself from illness based upon information in the media is not easy.

0.90

 

3.42

−0.46

NA

NA1: It is not necessary to use eHS.

0.94

0.95

0.95

0.91

4.19

0.02

NA2: Using eHS is not a good idea.

0.97

7.24

0.14

NA3: I do not consider eHS a beneficial choice to access healthcare services.

0.96

6.22

0.10

SN

SN1: My doctors think I should not use eHS.

0.89

0.92

0.96

0.80

2.48

0.14

SN2: Most people think that adopting eHS is not good.

0.92

3.93

−0.12

SN3: My family believes that traditional healthcare services (i.e., face to face with a healthcare provider) are preferable to adopting eHS.

0.85

2.67

−0.35

SN4: Most people think that eHS are not necessary.

0.92

3.84

−0.19

PBC

PBC1: Using eHS is easy.

0.81

0.95

1.00

0.81

3.20

−0.45

PBC2: Using eHS is possible.

0.93

4.14

−0.84

PBC3: Using eHS is up to me.

0.92

4.85

−0.79

PBC4: Using eHS is under my control.

0.90

4.74

−0.63

PBC5: I am confident in my ability to effectively use eHS.

0.94

4.65

−0.69

INTU

INTU1: I predict that I will not use eHS in the near future.

0.96

0.95

0.96

0.91

6.56

−0.01

INTU2: I have no plans to use eHS in the near future.

0.97

7.26

−0.02

INTU3: I am not inclined to try out or explore e-health platforms.

0.94

4.00

−0.12

NAB

NAB1: Using eHS is not in my bucket list when it comes to healthcare.

0.93

0.93

0.96

0.88

3.78

−0.92

NAB2: I am assured that I do not need to use eHS even if they are available to me.

0.95

3.70

−0.67

NAB3: I consistently opt for traditional healthcare methods instead of using eHS.

0.93

3.75

−0.88

  1. CO communication overload, CHO choice overload, PR perceived risk, HL health literacy, NA negative attitude, SN subjective norms, PBC perceived behavioral control, INTU intention not to use eHS, NAB non-adoption behavior.