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Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study
BACKGROUND: The Depression Anxiety Stress Scale 21 (DASS-21) is a mental health screening tool with conflicting studies regarding its factor structure. No studies have yet attempted to develop a computer adaptive test (CAT) version of it. OBJECTIVE: This study calibrated items for, and simulated, a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337454/ https://www.ncbi.nlm.nih.gov/pubmed/37347530 http://dx.doi.org/10.2196/45334 |
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author | Kraska, Jake Bell, Karen Costello, Shane |
author_facet | Kraska, Jake Bell, Karen Costello, Shane |
author_sort | Kraska, Jake |
collection | PubMed |
description | BACKGROUND: The Depression Anxiety Stress Scale 21 (DASS-21) is a mental health screening tool with conflicting studies regarding its factor structure. No studies have yet attempted to develop a computer adaptive test (CAT) version of it. OBJECTIVE: This study calibrated items for, and simulated, a DASS-21 CAT using a nonclinical sample. METHODS: An evaluation sample (n=580) was used to evaluate the DASS-21 scales via confirmatory factor analysis, Mokken analysis, and graded response modeling. A CAT was simulated with a validation sample (n=248) and a simulated sample (n=10,000) to confirm the generalizability of the model developed. RESULTS: A bifactor model, also known as the “quadripartite” model (1 general factor with 3 specific factors) in the context of the DASS-21, displayed good fit. All scales displayed acceptable fit with the graded response model. Simulation of 3 unidimensional (depression, anxiety, and stress) CATs resulted in an average 17% to 48% reduction in items administered when a reliability of 0.80 was acceptable. CONCLUSIONS: This study clarifies previous conflicting findings regarding the DASS-21 factor structure and suggests that the quadripartite model for the DASS-21 items fits best. Item response theory modeling suggests that the items measure their respective constructs best between 0θ and 3θ (mild to moderate severity). |
format | Online Article Text |
id | pubmed-10337454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-103374542023-07-13 Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study Kraska, Jake Bell, Karen Costello, Shane J Med Internet Res Original Paper BACKGROUND: The Depression Anxiety Stress Scale 21 (DASS-21) is a mental health screening tool with conflicting studies regarding its factor structure. No studies have yet attempted to develop a computer adaptive test (CAT) version of it. OBJECTIVE: This study calibrated items for, and simulated, a DASS-21 CAT using a nonclinical sample. METHODS: An evaluation sample (n=580) was used to evaluate the DASS-21 scales via confirmatory factor analysis, Mokken analysis, and graded response modeling. A CAT was simulated with a validation sample (n=248) and a simulated sample (n=10,000) to confirm the generalizability of the model developed. RESULTS: A bifactor model, also known as the “quadripartite” model (1 general factor with 3 specific factors) in the context of the DASS-21, displayed good fit. All scales displayed acceptable fit with the graded response model. Simulation of 3 unidimensional (depression, anxiety, and stress) CATs resulted in an average 17% to 48% reduction in items administered when a reliability of 0.80 was acceptable. CONCLUSIONS: This study clarifies previous conflicting findings regarding the DASS-21 factor structure and suggests that the quadripartite model for the DASS-21 items fits best. Item response theory modeling suggests that the items measure their respective constructs best between 0θ and 3θ (mild to moderate severity). JMIR Publications 2023-06-22 /pmc/articles/PMC10337454/ /pubmed/37347530 http://dx.doi.org/10.2196/45334 Text en ©Jake Kraska, Karen Bell, Shane Costello. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.06.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Kraska, Jake Bell, Karen Costello, Shane Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title | Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title_full | Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title_fullStr | Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title_full_unstemmed | Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title_short | Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study |
title_sort | graded response model analysis and computer adaptive test simulation of the depression anxiety stress scale 21: evaluation and validation study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337454/ https://www.ncbi.nlm.nih.gov/pubmed/37347530 http://dx.doi.org/10.2196/45334 |
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