Table 10 Logistic regression model for the presence of demand for digital health technologies

B

S.E.

Wald

df

Sig.

Exp(B)

95% C.I.for

Lower

Upper

Sex (1 = male; 2 = female)

-0.429

0.274

2.440

1

0.118

0.651

0.380

1.115

Educational level (reference: elementary school)

18.183

3

0.000

Educational level = vocational school, skilled worker

0.514

0.436

1.393

1

0.238

1.672

0.712

3.929

Educational level = high school

1.129

0.353

10.253

1

0.001

3.093

1.550

6.175

Educational level = higher education

2.106

0.632

11.116

1

0.001

8.214

2.382

28.326

Type of residence (reference = village)

12.207

3

0.007

Type of residence = other city

0.410

0.404

1.030

1

0.310

1.507

0.683

3.325

Type of residence = county capital, larger city

-0.596

0.358

2.766

1

0.096

0.551

0.273

1.112

Type of residence = capital

0.561

0.299

3.520

1

0.061

1.753

0.975

3.152

Do you have chronic disease (0 = no; 1 = yes)

0.461

0.277

2.780

1

0.095

1.586

0.922

2.729

What do you think are the possible positive consequences of digital healthcare solutions for society?

0.191

0.035

30.502

1

0.000

1.210

1.131

1.295

What do you think are the possible negative consequences of digital healthcare solutions for society?

0.002

0.044

0.003

1

0.955

1.002

0.920

1.092

Constant

-0.660

0.659

1.002

1

0.317

0.517