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Table 2 ProffNurse SAS (n−357)−Pattern Matrix

From: The Professional Nurse Self-Assessment Scale: Psychometric testing in Norwegian long term and home care contexts

 

Component

Item

1

2

3

4

5

6

24

.731

.067

−.096

−.076

.067

.036

25

.722

.229

−.087

−.114

.137

.119

17

.719

−.037

.053

.205

.010

.002

27

.714

.063

−.019

.058

.004

−.038

18

.673

−.153

.156

.090

−.020

−.022

23

.654

.177

.036

−.005

−.240

−.113

31

.623

.264

.081

.012

−.072

.024

34

.597

−.109

.121

.076

.100

−.148

36

.562

.288

.165

−.151

.129

.017

20

.558

−.261

.222

.146

.004

−.113

35

.545

−.195

.000

.064

.102

−.269

16

.542

−.055

−.109

.261

.109

−.140

30

.534

−.028

.059

.147

−.074

−.300

19

.520

−.324

.275

.184

.042

−.215

28

.495

.279

.157

−.051

−.124

−.162

26

.451

.069

.208

−.014

.079

−.172

38

.432

.183

.318

−.181

.130

.059

29

.430

.408

.158

−.125

−.097

−.102

22

.426

.078

.287

−.028

−.003

−.137

37

.370

.249

.316

−.202

.226

.002

21

.317

.027

.117

.280

−.016

−.258

10

.300

.275

.052

.273

.042

.192

32

.138

.002

.026

.098

−.037

−.047

11

.118

.609

−.002

.206

.135

.099

52

.119

.608

.014

.060

.290

.069

63

−.140

.600

−.002

.085

.252

−.186

50

−.052

.599

−.008

.163

.090

−.285

49

.092

.584

−.016

.072

.007

.057

59

.059

.527

.051

.074

.010

−.208

62

.120

.503

−.031

.086

−.508

−.274

51

.014

.490

.080

.167

.023

−.306

14

.125

.455

−.018

.126

−.027

.061

66

.079

.431

−.105

.122

.265

−.250

70

.179

.412

.096

.106

−.113

−.212

64

−.037

.355

.239

−.027

.092

−.035

58

.020

.321

.237

−.077

.035

−.231

69

.011

.306

.133

−.162

.040

−.077

65

.006

.235

.151

.085

.062

−.104

44

.107

.105

.724

−.074

−.028

.007

43

.255

−.102

.721

−.084

−.013

−.001

42

.235

−.218

.712

.030

.088

−.020

45

.061

.239

.709

−.212

.139

.008

41

.098

−.111

.708

.143

−.129

−.025

40

.041

−.065

.662

.057

.216

−.170

39

.094

−.001

.618

.079

.168

−.119

54

−.073

.183

.553

.205

−.070

.085

46

−.010

−.121

.517

.147

.133

−.218

7

.039

.217

.506

.273

−.282

.058

53

−.160

.229

.441

.179

.138

−.034

48

.107

.154

.385

.110

−.023

−.295

47

−.052

.009

.186

.082

−.001

−.075

3

−.005

−.077

.013

.639

.175

−.011

2

.121

.067

−.048

.610

.183

.044

5

.173

.111

−.074

.605

.233

.133

1

−.091

.008

.171

.538

−.057

−.147

6

−.037

.214

.297

.454

−.224

.004

9

.117

−.030

.252

.441

.157

.040

8

.102

.022

.238

.433

−.082

−.133

15

.078

.257

.215

.388

−.093

.009

4

−.050

.076

.050

.341

−.225

−.079

13

.324

−.189

.082

.338

.098

−.315

74

−.046

.138

.281

.322

.039

−.227

12

.056

.284

.197

.291

.018

−.091

72

−.084

.034

.155

.056

.779

.078

71

−.059

.076

.051

.080

.700

−.024

67

.184

.162

−.172

.229

.374

−.142

55

.216

.173

.191

−.034

.337

−.165

60

−.001

.179

.045

−.120

−.057

−.775

61

−.003

.179

−.019

−.108

−.051

−.726

56

.135

.036

−.085

.125

.219

−.555

33

.288

−.193

.055

.056

−.006

−.521

73

.077

−.109

.300

.128

.086

−.470

57

.061

.027

.188

−.029

.421

−.463

68

.280

.201

.101

.104

−.078

−.368

  1. Extraction method: Principal Component Analysis
  2. Rotation method: Oblimin (oblique) with Kaiser Normalization
  3. Loadings ≥0.4 in bold