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Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review
In people with type 1 diabetes, Automated Insulin Delivery (AID) systems adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that determines insulin delivery. To date, all the available AID systems...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382040/ https://www.ncbi.nlm.nih.gov/pubmed/37511644 http://dx.doi.org/10.3390/jpm13071031 |
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author | Marigliano, Marco Mozzillo, Enza Mancioppi, Valentina Di Candia, Francesca Rosanio, Francesco Maria Antonelli, Annalisa Nichelatti, Ilaria Maffeis, Claudio Tumini, Stefano Franceschi, Roberto |
author_facet | Marigliano, Marco Mozzillo, Enza Mancioppi, Valentina Di Candia, Francesca Rosanio, Francesco Maria Antonelli, Annalisa Nichelatti, Ilaria Maffeis, Claudio Tumini, Stefano Franceschi, Roberto |
author_sort | Marigliano, Marco |
collection | PubMed |
description | In people with type 1 diabetes, Automated Insulin Delivery (AID) systems adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that determines insulin delivery. To date, all the available AID systems require users to announce carbohydrate intake and deliver meal boluses, as well as respond to system alarms. The use of AID devices both initially and over time may be influenced by a variety of psychological factors. Analysis of patient-related outcomes should be taken into account, while recruiting applicants for the systems who are motivated and have realistic expectations in order to prevent AID dropout. We report an up-to-date summary of the available measures and semi-structured interview content to assess AID expectations, acceptance, and satisfaction using the AID systems. In conclusion, we suggest, before and after starting using AID systems, performing a specific evaluation of the related psychological implications, using validated measures and semi-structured interviews, that allows diabetes care providers to tailor their education approach to the factors that concern the patient at that time; they can teach problem-solving skills and other behavioral strategies to support sustained use of the AID system. |
format | Online Article Text |
id | pubmed-10382040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103820402023-07-29 Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review Marigliano, Marco Mozzillo, Enza Mancioppi, Valentina Di Candia, Francesca Rosanio, Francesco Maria Antonelli, Annalisa Nichelatti, Ilaria Maffeis, Claudio Tumini, Stefano Franceschi, Roberto J Pers Med Review In people with type 1 diabetes, Automated Insulin Delivery (AID) systems adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that determines insulin delivery. To date, all the available AID systems require users to announce carbohydrate intake and deliver meal boluses, as well as respond to system alarms. The use of AID devices both initially and over time may be influenced by a variety of psychological factors. Analysis of patient-related outcomes should be taken into account, while recruiting applicants for the systems who are motivated and have realistic expectations in order to prevent AID dropout. We report an up-to-date summary of the available measures and semi-structured interview content to assess AID expectations, acceptance, and satisfaction using the AID systems. In conclusion, we suggest, before and after starting using AID systems, performing a specific evaluation of the related psychological implications, using validated measures and semi-structured interviews, that allows diabetes care providers to tailor their education approach to the factors that concern the patient at that time; they can teach problem-solving skills and other behavioral strategies to support sustained use of the AID system. MDPI 2023-06-22 /pmc/articles/PMC10382040/ /pubmed/37511644 http://dx.doi.org/10.3390/jpm13071031 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Marigliano, Marco Mozzillo, Enza Mancioppi, Valentina Di Candia, Francesca Rosanio, Francesco Maria Antonelli, Annalisa Nichelatti, Ilaria Maffeis, Claudio Tumini, Stefano Franceschi, Roberto Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title | Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title_full | Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title_fullStr | Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title_full_unstemmed | Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title_short | Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review |
title_sort | measures of patient-reported expectations, acceptance, and satisfaction using automated insulin delivery systems: a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382040/ https://www.ncbi.nlm.nih.gov/pubmed/37511644 http://dx.doi.org/10.3390/jpm13071031 |
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