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Table 5 Logistic Regression Models on second breast screening uptake against different variables and different constructs

From: Predicting reattendance to the second round of the Maltese national breast screening programme: an analytical descriptive study

 

B

SE

Wald

P-value

OR

95% CI

Model Accuracy YES

Model Accuracy NO

Model 1: Demographics

      

100%

0%

 Age

-0.154

0.084

3.329

0.068

0.858

0.727, 1.011

  

 Constant

7.926

4.905

2.611

0.106

2769.527

   

Model 2: Health Status

      

100%

0%

 Breast condition

-1.093

0.526

4.315

0.038

0.335

0.119, 0.940

  

 Constant

0.893

0.940

0.902

0.342

2.441

   

Model 3: Health Beliefs

      

93.2%

30.8%

 No possibility of getting breast cancer

1.064

0.474

5.030

0.025

2.897

1.144, 7.338

  

 Fear of unknown procedurea

0.563

0.388

2.102

0.147

1.755

0.820, 3.756

  

 GP advice

-1.145

0.562

4.158

0.041

0.318

0.106, 0.956

  

 Constant

0.480

2.717

0.031

0.860

1.617

   

Model 4: Illness Perceptions

      

89.2%

69.2%

 Breast swelling, dimpling, redness or soreness of the skin

-1.796

0.720

6.215

0.013

0.166

0.040, 0.681

  

 Diet

-1.029

0.312

10.873

0.001

0.357

0.194, 0.659

  

 Altered immunity

1.462

0.568

6.610

0.010

4.313

1.415, 3.141

  

 Whole life would change

-1.334

0.533

6.257

0.012

0.263

0.093, 0.749

  

 Constant

9.082

3.931

5.337

0.021

8796.855

   

Model 5: Health Beliefs and Illness Perceptions

      

89.2%

69.2%

 Breast swelling, dimpling, redness or soreness of the skin

-1.796

0.720

6.215

0.013

0.166

0.040, 0.681

  

 Diet

-1.029

0.312

10.873

0.001

0.357

0.194, 0.659

  

 Altered immunity

1.462

0.568

6.610

0.010

4.313

1.415, 3.141

  

 Whole life would change

-1.334

0.533

6.257

0.012

0.263

0.093, 0.749

  

 Constant

9.082

3.931

5.337

0.021

8796.855

   

Model 6: Health Beliefs and Illness Perceptions

      

95.9%

84.6%

 Early detection

5.699

2.097

7.390

0.007

298.646

4.904, 18,187.040

  

 If early detection, treatment not as badb

12.267

7.293

2.830

0.093

2.126 × 105

0.132, 3.427 × 1011

  

 Having mammography decreases chances of dyingb

-8.890

6.724

1.748

0.186

0.000

0.000, 72.821

  

 Fear of unknown procedure

5.210

1.842

8.003

0.005

183.103

4.955, 6765.914

  

 Unnecessary radiation

4.471

1.655

7.301

0.007

87.419

3.414, 2238.732

  

 Breast swelling, dimpling, redness or soreness of the skin

-8.961

3.119

8.252

0.004

0.000

0.000, 0.058

  

 Personality

-5.566

2.295

5.885

0.015

0.004

0.000, 0.343

  

 Diet

-5.558

1.946

8.160

0.004

0.004

0.000, 0.175

  

 Germ or virus

-5.721

2.168

6.967

0.008

0.003

0.000, 0.229

  

 Altered immunity

8.217

2.860

8.254

0.004

3705.048

13.620, 1.008 × 106

  

 Breast cancer last short time

-2.623

1.042

6.340

0.012

0.073

0.009, 0.559

  

 Affects the way others see you

3.105

1.286

5.831

0.016

22.305

1.795, 277.210

  

 Whole life would change

-9.738

3.266

8.888

0.003

0.000

0.000, 0.036

  

 You get worried if breast cancer occurs

2.444

1.199

4.159

0.041

11.521

1.100, 120.694

  

 Constant

14.947

26.502

0.318

0.573

3.102 × 106

   

Model 7: The 14 constructs

      

94.6%

30.0%

 Perceived barriers

0.155

0.054

8.305

0.004

0.167

1.051, 1.296

  

 Breast cancer identity

-0.231

0.120

3.691

0.055

0.794

0.627, 1.005

  

 Causes of breast cancerc

-0.070

0.040

3.022

0.082

0.932

0.861, 1.009

  

 Consequencesc

-0.204

0.116

3.082

0.079

0.815

0.649, 1.024

  

 Constant

11.286

4.983

5.129

0.024

79,721.454

   
  1. B Unstandardized coefficients, SE Standard error, OR Odds ratio, CI Confidence interval
  2. a‘Fear of unknown procedure’ was retained due to better accuracy in the logistic regression model. Without this variable, the accuracy would decrease from 30.8 to 19.2%
  3. b‘If early detection, treatment not bad’ and ‘Having mammography decreases death’ were retained due to better accuracy in the logistic regression model. Without these variables, the accuracy would decrease from 84.6 to 76.9%
  4. c‘Causes of breast cancer’ and ‘Consequences’ were retained due to better accuracy in the logistic regression model. Without these variables, the accuracy would decrease from 30.0 to 15.4%