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Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research

This is a commentary on methodological challenges and analytical requirements in designing an evaluation of the knowledge, motivation, attitude, preventive practice-outcome (KMAP-O) model for selfcare management of diabetes. Critical issues pertaining to an investigation of the dose-response relatio...

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Autor principal: Wan, Thomas T.H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202301/
https://www.ncbi.nlm.nih.gov/pubmed/34179297
http://dx.doi.org/10.1177/23333928211023220
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author Wan, Thomas T.H.
author_facet Wan, Thomas T.H.
author_sort Wan, Thomas T.H.
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description This is a commentary on methodological challenges and analytical requirements in designing an evaluation of the knowledge, motivation, attitude, preventive practice-outcome (KMAP-O) model for selfcare management of diabetes. Critical issues pertaining to an investigation of the dose-response relationship between the intervention program and outcomes, the comparative effectiveness evaluation, and the lengths of observation were noted. Although numerous publications on factors influencing diabetes care and control were systematically reviewed and documented in the literature, scientific results on artificial intelligence research remain to be uncovered. To optimizing the knowledge and clinical practice in selfcare management, specific methodological approaches to predictive analytics are suggested for future clinical studies, using a comprehensive behavioral system such as the KMAP-O model.
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spelling pubmed-82023012021-06-24 Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research Wan, Thomas T.H. Health Serv Res Manag Epidemiol Commentary This is a commentary on methodological challenges and analytical requirements in designing an evaluation of the knowledge, motivation, attitude, preventive practice-outcome (KMAP-O) model for selfcare management of diabetes. Critical issues pertaining to an investigation of the dose-response relationship between the intervention program and outcomes, the comparative effectiveness evaluation, and the lengths of observation were noted. Although numerous publications on factors influencing diabetes care and control were systematically reviewed and documented in the literature, scientific results on artificial intelligence research remain to be uncovered. To optimizing the knowledge and clinical practice in selfcare management, specific methodological approaches to predictive analytics are suggested for future clinical studies, using a comprehensive behavioral system such as the KMAP-O model. SAGE Publications 2021-06-10 /pmc/articles/PMC8202301/ /pubmed/34179297 http://dx.doi.org/10.1177/23333928211023220 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Commentary
Wan, Thomas T.H.
Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title_full Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title_fullStr Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title_full_unstemmed Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title_short Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
title_sort predictive analytics for the kmap-o model in design and evaluation of diabetes care management research
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202301/
https://www.ncbi.nlm.nih.gov/pubmed/34179297
http://dx.doi.org/10.1177/23333928211023220
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