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 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..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:13 |
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| Enthalten in: |
Journal of Personalized Medicine - 13(2023), 7, p 1031 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Marco Marigliano [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
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| doi: |
10.3390/jpm13071031 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ09387751X |
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