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Int J Intercult Relat
Psychiatry Investig


Type D Personality

 

 

Denollet’s Distressed Personality Trait (Type D)

 

 

อุทิศ แด่ ศ.ดร. โจฮัน โดเนลเล็ต แห่ง มหาวิทยาทิลเบอร์ก ประเทศเนเธอร์แลนด์ ผู้ได้สร้างคุณูปการแก่วงการจิตวิทยาและจิตเวชศาสตร์ ซึ่งได้จากไปในเดือน ตุลาคม ๒๕๖๒

Dedicated to Prof. Dr. Johan Donellet of Tilburg University, The Netherlands who has made contributions to the field of psychology and psychiatry. Prof.Dr. passed away in October 2019.


In Memoriam Johan Denollet (1957-2019) | Tilburg University

Johan Denollet 

DS14

Prof.Dr. Donellet created the DS14 to measure the distressed type of personality trait. It has been tested in numerous populations and translated into many languages. We were gratefully granted the permission to translate the DS14(+3) into Thai version by Prof.Dr. Denollet in June 2012.  We are highly appreciated and congratulate Prof. Dr. Denollet on what he has been accomplished and dedicated to people in this world.

เราได้อุทิศบุญกุศลที่ได้ทำมาตังแต่อดีต นับภพชาติไม่ถ้วน  แด่ Prof. Denollet ขอผลบุญทั้งหลาย นำท่านไปสู่สัมปรายภพ ที่ที่มีแต่ความสุข สืบไป :  ศ.นพ. ทินกร - ศ.พญ. ณหทัย วงศ์ปการันย์

 

Description:

The DS14 is a brief, psychometrically sound measure of negative affectivity and social inhibition that could readily be incorporated in epidemiologic and clinical research.

 

Measurement:


Thai Version of Type D personality trait (DS14+3)

Type D Thai.pdf

Scoring: 

DS17

Negative Affectivity =DS2 + DS4 + DS5 + DS7 + DS9 + DS12 + DS13 + DS16

Social Inhibition=DS1(Reversed) + DS3(Reversed) + DS6 + DS8 + DS10 + DS11 +  DS14 + DS15 + DS17

DS14 (no item 15-16-17)

Negative Affectivity =DS2 + DS4 + DS5 + DS7 + DS9 + DS12 + DS13 

Social Inhibition=DS1(Reversed) + DS3(Reversed) + DS6 + DS8 + DS10 + DS11 +  DS14 

 

Psychometric property of Thai DS 

DS17 has been tested in 1600 participants.

Reliability 

Reliability Analysis

 

Scale Reliability Statistics
  Cronbach's α McDonald's ω
scale   0.897   0.902  
Note. item 'ds3' correlates negatively with the total scale and probably should be reversed
 

 

  Factor analysis results of Thai version DS17
 

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.923

Bartlett's Test of Sphericity

Approx. Chi-Square

13432.625

df

136

Sig.

.000

 

Communalities

 

Initial

Extraction

reversed

1.000

.678

ds2

1.000

.532

reversed

1.000

.614

ds4

1.000

.688

ds5

1.000

.728

ds6

1.000

.378

ds7

1.000

.584

ds8

1.000

.583

ds9

1.000

.665

ds10

1.000

.611

ds11

1.000

.594

ds12

1.000

.575

ds13

1.000

.674

ds14

1.000

.594

ds15

1.000

.580

ds16

1.000

.580

ds17

1.000

.603

Extraction Method: Principal Component Analysis.

 

 


Total Variance Explained

Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

6.975

41.030

41.030

6.975

41.030

41.030

4.470

26.294

26.294

2

1.949

11.464

52.494

1.949

11.464

52.494

4.267

25.101

51.396

3

1.336

7.859

60.352

1.336

7.859

60.352

1.523

8.957

60.352

4

.853

5.020

65.372

 

 

 

 

 

 

5

.759

4.467

69.839

 

 

 

 

 

 

6

.657

3.862

73.702

 

 

 

 

 

 

7

.584

3.438

77.139

 

 

 

 

 

 

8

.555

3.266

80.406

 

 

 

 

 

 

9

.533

3.136

83.542

 

 

 

 

 

 

10

.468

2.751

86.293

 

 

 

 

 

 

11

.426

2.508

88.801

 

 

 

 

 

 

12

.400

2.354

91.155

 

 

 

 

 

 

13

.381

2.240

93.394

 

 

 

 

 

 

14

.334

1.965

95.360

 

 

 

 

 

 

15

.308

1.813

97.172

 

 

 

 

 

 

16

.251

1.475

98.647

 

 

 

 

 

 

17

.230

1.353

100.000

 

 

 

 

 

 

Extraction Method: Principal Component Analysis.

 

 

Component Matrixa

 

Component

1

2

3

reversed

.179

.467

.654

ds2

.588

-.431

 

reversed

 

.552

.556

ds4

.757

-.294

.170

ds5

.709

-.433

.196

ds6

.435

 

-.430

ds7

.711

-.215

.177

ds8

.693

.322

 

ds9

.686

-.382

.220

ds10

.736

.237

-.114

ds11

.677

.300

-.215

ds12

.749

-.117

 

ds13

.760

-.255

.180

ds14

.686

.332

-.112

ds15

.553

.372

-.369

ds16

.736

.194

 

ds17

.648

.396

-.162

Extraction Method: Principal Component Analysis.

a. 3 components extracted.

 

 

Rotated Component Matrixa

 

Component

1

2

3

reversed

 

.134

.807

ds2

.690

.139

-.191

reversed

-.138

 

.766

ds4

.780

.281

 

ds5

.837

.155

 

ds6

.195

.439

-.384

ds7

.703

.294

 

ds8

.310

.669

.199

ds9

.800

.160

 

ds10

.348

.698

 

ds11

.232

.735

 

ds12

.599

.460

 

ds13

.763

.303

 

ds14

.257

.719

.106

ds15

 

.755

 

ds16

.419

.622

.134

ds17

.173

.750

 

Extraction Method: Principal Component Analysis.

 Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 5 iterations.

 Velicer's Minimum Average Partial (MAP) Test:

 

Eigenvalues

       4.6729

       1.7710

        .4810

        .4214

        .2332

        .1867

        .1373

        .0965

 

Average Partial Correlations

                       squared         power4

          .0000          .3125          .1551

         1.0000          .2451          .0736

         2.0000          .0664          .0119

         3.0000          .1276          .0519

         4.0000          .2042          .1160

         5.0000          .2718          .1526

         6.0000          .4346          .3312

         7.0000         1.0000         1.0000

 

The smallest average squared partial correlation is

        .0664

 

The smallest average 4rth power partial correlation is        .0119 

The Number of Components According to the Original (1976) MAP Test is  2 

The Number of Components According to the Revised (2000) MAP Test is  2 

 

PARALLEL ANALYSIS:

 

Principal Components & Random Normal Data Generation

 

Specifications for this Run:

Ncases    1620

Nvars       17

Ndatsets  1000

Percent     95

 

Raw Data Eigenvalues, & Mean & Percentile Random Data Eigenvalues

         Root     Raw Data        Means     Prcntyle

     1.000000     6.975089     1.179706     1.212279

     2.000000     1.948846     1.144121     1.168726

     3.000000     1.335986     1.116807     1.138866

     4.000000      .853328     1.093737     1.112620

     5.000000      .759430     1.072547     1.090665

     6.000000      .656618     1.052942     1.068730

     7.000000      .584400     1.034032     1.049977

     8.000000      .555293     1.015480     1.030355

     9.000000      .533157      .997270     1.012661

    10.000000      .467733      .979135      .993500

    11.000000      .426316      .961127      .976057

    12.000000      .400104      .943167      .957735

    13.000000      .380734      .924380      .940230

    14.000000      .334103      .905326      .921923

    15.000000      .308171      .885159      .902756

    16.000000      .250724      .862285      .881163

    17.000000      .229968      .832779      .856370

 

 

Model Description

Model Name

MOD_3

Series or Sequence

1

rawdata

2

means

3

percntyl

Transformation

None

Non-Seasonal Differencing

0

Seasonal Differencing

0

Length of Seasonal Period

No periodicity

Horizontal Axis Labels

root

Intervention Onsets

None

For Each Observation

Values not joined

Applying the model specifications from MOD_3

  

Case Processing Summary

 

rawdata

means

percntyl

Series or Sequence Length

17

17

17

Number of Missing Values in the Plot

User-Missing

0

0

0

System-Missing

0

0

0

  

In summary, factor analyses suggested the Thai version DS17 demonstrated a two-factor solution, which were negative emotion and social inhibition dimesions, as proposed by the original version(Denollet, 2005)

 

 

 

References: 

 

 

Denollet, J. (2005). DS14: standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosom Med, 67(1), 89-97. doi:10.1097/01.psy.0000149256.81953.49

 







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