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Psychometric properties of the Bangla version of the Kessler Psychological Distress Scale (K6)

Asaduzzaman Khan

Asaduzzaman Khan

  • School of Health & Rehabilitation Sciences, The University of QueenslandBrisbane, Australia
  • Active Healthy Kids BangladeshDhaka, Bangladesh
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Khan, Asaduzzaman
, 
Riaz Uddin

Riaz Uddin

  • School of Health & Rehabilitation Sciences, The University of QueenslandBrisbane, Australia
  • Active Healthy Kids BangladeshDhaka, Bangladesh
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Uddin, Riaz
, 
Naznin Alam

Naznin Alam

Department of Business Administration, Stamford University BangladeshDhaka, Bangladesh
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Alam, Naznin
, 
Shuhana Sultana

Shuhana Sultana

Department of Health Promotion & Health Education, Bangladesh University of Health SciencesDhaka, Bangladesh
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Sultana, Shuhana
, 
Mahbub-Ul Alam

Mahbub-Ul Alam

Environmental Interventions Unit, Infectious Disease Division, icddr,bDhaka, Bangladesh
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Alam, Mahbub-Ul
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Rushdiá Ahmed

Rushdiá Ahmed

  • Health Systems and Population Studies Division, icddr,bDhaka, Bangladesh
  • BRAC James P Grant School of Public Health, BRAC UniversityDhaka, Bangladesh
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Ahmed, Rushdiá
  
04 set 2019
Psychometric properties of the Bangla version of the Kessler Psychological Distress Scale (K6)'s Cover Image
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Pubblicato online: 04 set 2019
Pagine: 183 - 194
Ricevuto: 24 giu 2019
Accettato: 30 lug 2019
DOI: https://doi.org/10.2478/gp-2019-0016
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© 2019 Asaduzzaman Khan et al.. published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1

The best fitted model, with standardized estimates, based on the results of confirmatory factor analysis of the items of Bangla K6 at time 1 (n = 718)Note: Oval represents the latent construct or factor; rectangle represents the items; and small circle represents the relevant error terms. Item loadings are interpreted as correlation between the items and the construct, and ranged from 0.53 (item 6) to 0.68 (item 4).Goodness-of-fit indices of CFA on the Bangla K6 items at time 1 were:- Chi-square test: Chi-sq (7) = 7.92, p = 0.34 suggests a good fit;- Tucker Lewis Index (TLI) = 0.997 > 0.95 suggests an excellent fit;- Comparative Fit Index (CFI) = 0.996 > 0.95 suggests an excellent fit;- Root Mean Square Error of Approximation (RMSEA) = 0.014 < 0.05 suggests an excellent fit;- Standardized Root Mean Square Residual (SRMR) = 0.012 < 0.05 suggests a good fit.
The best fitted model, with standardized estimates, based on the results of confirmatory factor analysis of the items of Bangla K6 at time 1 (n = 718)Note: Oval represents the latent construct or factor; rectangle represents the items; and small circle represents the relevant error terms. Item loadings are interpreted as correlation between the items and the construct, and ranged from 0.53 (item 6) to 0.68 (item 4).Goodness-of-fit indices of CFA on the Bangla K6 items at time 1 were:- Chi-square test: Chi-sq (7) = 7.92, p = 0.34 suggests a good fit;- Tucker Lewis Index (TLI) = 0.997 > 0.95 suggests an excellent fit;- Comparative Fit Index (CFI) = 0.996 > 0.95 suggests an excellent fit;- Root Mean Square Error of Approximation (RMSEA) = 0.014 < 0.05 suggests an excellent fit;- Standardized Root Mean Square Residual (SRMR) = 0.012 < 0.05 suggests a good fit.

Figure 2

The best fitted model, with standardized estimates, based on the results of confirmatory factor analysis of the items of Bangla K6 at time 2 (n = 715)Note: Oval represents the latent construct or factor; rectangle represents the items; and small circle represents the relevant error terms. Item loadings are interpreted as correlation between the items and the construct, and ranged from 0.57 (item 6) to 0.70 (item 4).Goodness-of-fit indices of CFA on the Bangla K6 items at time 2 were:- Chi-square test: Chi-sq (7) = 9.97, p = 0.13 suggests a good fit;- Tucker Lewis Index (TLI) = 0.992 > 0.95 suggests an excellent fit;- Comparative Fit Index (CFI) = 0.997 > 0.95 suggests an excellent fit;- Root Mean Square Error of Approximation (RMSEA) = 0.03 < 0.05 suggests an excellent fit;- Standardized Root Mean Square Residual (SRMR) = 0.014 < 0.05 suggests a good fit.
The best fitted model, with standardized estimates, based on the results of confirmatory factor analysis of the items of Bangla K6 at time 2 (n = 715)Note: Oval represents the latent construct or factor; rectangle represents the items; and small circle represents the relevant error terms. Item loadings are interpreted as correlation between the items and the construct, and ranged from 0.57 (item 6) to 0.70 (item 4).Goodness-of-fit indices of CFA on the Bangla K6 items at time 2 were:- Chi-square test: Chi-sq (7) = 9.97, p = 0.13 suggests a good fit;- Tucker Lewis Index (TLI) = 0.992 > 0.95 suggests an excellent fit;- Comparative Fit Index (CFI) = 0.997 > 0.95 suggests an excellent fit;- Root Mean Square Error of Approximation (RMSEA) = 0.03 < 0.05 suggests an excellent fit;- Standardized Root Mean Square Residual (SRMR) = 0.014 < 0.05 suggests a good fit.

Figure 3

Bland-Altman plot of the Bangla K6 between test and retest sessionsNote: Differences between test and retest sessions were plotted against the average of the two sessions for each participant. It plots average measures of the two test sessions (x-axis) against difference between test and retest measures (y-axis). The centre line represents mean of differences, while the upper and lower lines indicate 95% limits of agreement (LOA).- Narrow LOAs suggest that the test-retest measures essentially equivalent, while wide LOAs suggest that the measures are ambiguous.- If the variability in measurements is consistent across the plot without any particular pattern or trend, then it is an indication of homoscedasticity. If the difference gets larger as the average gets larger, it suggests the presence of heteroscedasticity.
Bland-Altman plot of the Bangla K6 between test and retest sessionsNote: Differences between test and retest sessions were plotted against the average of the two sessions for each participant. It plots average measures of the two test sessions (x-axis) against difference between test and retest measures (y-axis). The centre line represents mean of differences, while the upper and lower lines indicate 95% limits of agreement (LOA).- Narrow LOAs suggest that the test-retest measures essentially equivalent, while wide LOAs suggest that the measures are ambiguous.- If the variability in measurements is consistent across the plot without any particular pattern or trend, then it is an indication of homoscedasticity. If the difference gets larger as the average gets larger, it suggests the presence of heteroscedasticity.

Figure 4

ROC-curves for the Bangla K6 predicting depressive symptoms for students of schools (#1) and universities (#2) at time 1 (CES-D-10 as the reference criterion)Note: The area under the ROC curve (AUC) shows how well a test can distinguish between two diagnostic groups (positive/negative).- The closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test.- An AUC of 0.50 suggests that the Bangla K6 is no better than chance at predicting depressive symptoms, whereas an AUC of 1.0 would indicate that the Bangla K6 predicts depressive symptoms perfectly.- AUC = 0.82 for school students and AUC = 0.80 for university students represent good prediction of depressive symptoms at time 1.
ROC-curves for the Bangla K6 predicting depressive symptoms for students of schools (#1) and universities (#2) at time 1 (CES-D-10 as the reference criterion)Note: The area under the ROC curve (AUC) shows how well a test can distinguish between two diagnostic groups (positive/negative).- The closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test.- An AUC of 0.50 suggests that the Bangla K6 is no better than chance at predicting depressive symptoms, whereas an AUC of 1.0 would indicate that the Bangla K6 predicts depressive symptoms perfectly.- AUC = 0.82 for school students and AUC = 0.80 for university students represent good prediction of depressive symptoms at time 1.

Figure 5

ROC-curves for the Bangla K6 predicting depressive symptoms for students of schools (#1) and universities (#2) at time 2 (CES-D-10 as the reference criterion)Note: The area under the ROC curve (AUC) shows how well a test can distinguish between two diagnostic groups (positive/negative).- The closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test.- An AUC of 0.50 suggests that the Bangla K6 is no better than chance at predicting depressive symptoms, whereas an AUC of 1.0 would indicate that the Bangla K6 predicts depressive symptoms perfectly.- AUC = 0.85 for school students and AUC = 0.80 for university students represent good prediction of depressive symptoms at time 2.
ROC-curves for the Bangla K6 predicting depressive symptoms for students of schools (#1) and universities (#2) at time 2 (CES-D-10 as the reference criterion)Note: The area under the ROC curve (AUC) shows how well a test can distinguish between two diagnostic groups (positive/negative).- The closer the curve follows the left-hand border and then the top border of the ROC space, the more accurate the test.- An AUC of 0.50 suggests that the Bangla K6 is no better than chance at predicting depressive symptoms, whereas an AUC of 1.0 would indicate that the Bangla K6 predicts depressive symptoms perfectly.- AUC = 0.85 for school students and AUC = 0.80 for university students represent good prediction of depressive symptoms at time 2.

j_gp-2019-0016_tab_001_w2aab3b8c16b1b7b1ab2b3ab4Aa

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