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Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale
INTRODUCTION: The Alzheimer’s Disease Knowledge Scale (ADKS) is one of the most popular instruments for assessing a person’s knowledge regarding Alzheimer’s disease (AD). The objective of this study was to explore ADKS item characteristics with item response theory (IRT) procedures. METHODS: A nonin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Healthcare
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139996/ https://www.ncbi.nlm.nih.gov/pubmed/33512697 http://dx.doi.org/10.1007/s40120-021-00230-x |
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author | Garcia-Ribas, Guillermo García-Arcelay, Elena Montoya, Alonso Maurino, Jorge Ballesteros, Javier |
author_facet | Garcia-Ribas, Guillermo García-Arcelay, Elena Montoya, Alonso Maurino, Jorge Ballesteros, Javier |
author_sort | Garcia-Ribas, Guillermo |
collection | PubMed |
description | INTRODUCTION: The Alzheimer’s Disease Knowledge Scale (ADKS) is one of the most popular instruments for assessing a person’s knowledge regarding Alzheimer’s disease (AD). The objective of this study was to explore ADKS item characteristics with item response theory (IRT) procedures. METHODS: A noninterventional web-based study was conducted. A nonparametric IRT procedure, Mokken analysis, was used to explore the underlying latent structure of the ADKS and ADKS item characteristics regarding scalability and violations of the monotone homogeneity (MH) model. A random-effects meta-analysis was implemented that combined ADKS scores from independent studies. RESULTS: A total of 447 employees of a pharmaceutical company participated in the study. The mean ADKS score was 21.2 (SD 2.8). Mokken analysis showed that most ADKS items (22 of 30) do not fit to any scale and can be considered to be scale independent. Two items (#1: particularly prone to depression; #20: depression can be mistaken for AD) fit to a domain relating to depression, another two items (#2: mental exercise can prevent AD development; #8: benefit of psychotherapy) can be related to potential prevention and improvement, and four items (#12: poor nutrition can make the symptoms worse; #18: high cholesterol may increase the risk of AD; #26: high blood pressure may increase the risk of AD; #27: genes can only partially account for AD development) fit to a risk factor domain. As expected from those results, neither the overall scale (H = 0.033) nor its items showed appropriate scalability index values, suggesting that ADKS does not fit to a MH model. Eleven items showed violations of the assumptions of the MH model. The meta-analytical average score was 21.78 (95% CI 20.67–22.90), with healthcare professionals and caregivers showing the highest levels of AD knowledge. CONCLUSION: Although the ADKS does not present a unidimensional structure, its independent items together provide a comprehensive spectrum of information regarding AD knowledge. |
format | Online Article Text |
id | pubmed-8139996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-81399962021-06-03 Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale Garcia-Ribas, Guillermo García-Arcelay, Elena Montoya, Alonso Maurino, Jorge Ballesteros, Javier Neurol Ther Original Research INTRODUCTION: The Alzheimer’s Disease Knowledge Scale (ADKS) is one of the most popular instruments for assessing a person’s knowledge regarding Alzheimer’s disease (AD). The objective of this study was to explore ADKS item characteristics with item response theory (IRT) procedures. METHODS: A noninterventional web-based study was conducted. A nonparametric IRT procedure, Mokken analysis, was used to explore the underlying latent structure of the ADKS and ADKS item characteristics regarding scalability and violations of the monotone homogeneity (MH) model. A random-effects meta-analysis was implemented that combined ADKS scores from independent studies. RESULTS: A total of 447 employees of a pharmaceutical company participated in the study. The mean ADKS score was 21.2 (SD 2.8). Mokken analysis showed that most ADKS items (22 of 30) do not fit to any scale and can be considered to be scale independent. Two items (#1: particularly prone to depression; #20: depression can be mistaken for AD) fit to a domain relating to depression, another two items (#2: mental exercise can prevent AD development; #8: benefit of psychotherapy) can be related to potential prevention and improvement, and four items (#12: poor nutrition can make the symptoms worse; #18: high cholesterol may increase the risk of AD; #26: high blood pressure may increase the risk of AD; #27: genes can only partially account for AD development) fit to a risk factor domain. As expected from those results, neither the overall scale (H = 0.033) nor its items showed appropriate scalability index values, suggesting that ADKS does not fit to a MH model. Eleven items showed violations of the assumptions of the MH model. The meta-analytical average score was 21.78 (95% CI 20.67–22.90), with healthcare professionals and caregivers showing the highest levels of AD knowledge. CONCLUSION: Although the ADKS does not present a unidimensional structure, its independent items together provide a comprehensive spectrum of information regarding AD knowledge. Springer Healthcare 2021-01-29 /pmc/articles/PMC8139996/ /pubmed/33512697 http://dx.doi.org/10.1007/s40120-021-00230-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Garcia-Ribas, Guillermo García-Arcelay, Elena Montoya, Alonso Maurino, Jorge Ballesteros, Javier Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title | Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title_full | Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title_fullStr | Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title_full_unstemmed | Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title_short | Quantifying Knowledge of Alzheimer’s Disease: An Analysis of the Psychometric Properties of the Alzheimer’s Disease Knowledge Scale |
title_sort | quantifying knowledge of alzheimer’s disease: an analysis of the psychometric properties of the alzheimer’s disease knowledge scale |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139996/ https://www.ncbi.nlm.nih.gov/pubmed/33512697 http://dx.doi.org/10.1007/s40120-021-00230-x |
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