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Table 1 Pattern matrix for exploratory factor analysis of the questionnaire

From: Applicability of the theory of planned behavior in explaining the general practitioners eLearning use in continuing medical education

Item

Factor 1 (PBC)

Factor 2 (SN)

Factor (Intention)

Factor 3 (Attitude)

Extraction communality

Q09f: eCME final exam

.792

-.036

-.209

.170

.652

Q18: eCME audiovisual

.700

-.006

.018

-.009

.498

Q09c: eCME scientific quality

.677

.013

.041

.125

.535

Q09b: eCME cost

.630

-.061

.180

-.172

.501

Q03: Improving practice

.561

.160

.306

.168

.560

Q09e: eCME Q&A

.539

-.203

-.058

-.144

.355

Q19: eCME & Internet speed

.486

-.100

-.019

.145

.330

Q08: Independent learning

.410

-.089

.283

.160

.462

Q10: Encouragement by boss

.069

-.857

-.067

.058

.757

Q11: Encouragement by CME office

-.082

-.813

.058

.031

.660

Q12: Encouragement by colleagues

.137

-.768

.080

-.059

.717

Q15: Concentrate with distractors

-.103

-.116

.774

.098

.661

Q06: eCME credit possibility

-.099

-.103

.710

.137

.578

Q20: CME preference

.250

-.011

.708

-.130

.650

Q02: Intention (next 6 month)

.366

.029

.404

-.034

.376

Q04: Traffic time

.066

.125

-.160

.742

.543

Q05: Job leave

-.056

-.107

.133

.620

.454

Q09a: eCME time saving

.227

-.043

.005

.585

.478

Q09d: More eCME credits

-.054

-.057

.108

.529

.315

Q07: Recommending

.388

-.101

.339

.409

.740

Cronbach’s alpha

.81

.8

.56

.78

 

Eigen value

6.4

1.7

1.5

1.2

 
  1. Extraction Method: principal component analysis. Rotation method: Oblimin with Kaiser Normalization. Rotation converged in 12 iterations
  2. Abbreviations: PBC perceived behavioral control, SN subjective norms
  3. Bold numbers emphasize highest loadings in a column