Evidence mapPaperPMID 37511644Full record

ReviewJournal of personalized medicine2023

Measures of Patient-Reported Expectations, Acceptance, and Satisfaction Using Automated Insulin Delivery Systems: A Review.

Marco Marigliano, Enza Mozzillo, Valentina Mancioppi, Francesca Di Candia, Francesco Maria Rosanio, Annalisa Antonelli, Ilaria Nichelatti, Claudio Maffeis, Stefano Tumini, Roberto Franceschi

Open access · goldAbstract readReview
In one paragraph

Review in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Marco MariglianoDepartment of Surgery, Dentistry, Pediatrics and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera Universitaria Integrata of Verona, 37126 Verona, Italy.ORCID 0000-0002-3232-8807
Enza MozzilloDepartment of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, 80138 Naples, Italy.ORCID 0000-0002-8437-8494
Valentina MancioppiDepartment of Surgery, Dentistry, Pediatrics and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera Universitaria Integrata of Verona, 37126 Verona, Italy.ORCID 0000-0002-4241-0118
Francesca Di CandiaDepartment of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, 80138 Naples, Italy.
Francesco Maria RosanioDepartment of Translational Medical Science, Section of Pediatrics, Regional Center of Pediatric Diabetes, Federico II University of Naples, 80138 Naples, Italy.
Annalisa AntonelliDepartment of Maternal and Child Health, UOSD Regional Center of Pediatric Diabetology, Chieti Hospital, 66100 Chieti, Italy.
Ilaria NichelattiPediatric Diabetology Unit, Pediatric Department, S.Chiara General Hospital of Trento, Azienda Provinciale per i Servizi Sanitari, 38122 Trento, Italy.
Claudio MaffeisDepartment of Surgery, Dentistry, Pediatrics and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera Universitaria Integrata of Verona, 37126 Verona, Italy.ORCID 0000-0002-3563-4404
Stefano TuminiDepartment of Maternal and Child Health, UOSD Regional Center of Pediatric Diabetology, Chieti Hospital, 66100 Chieti, Italy.ORCID 0000-0002-3135-2637
Roberto FranceschiPediatric Diabetology Unit, Pediatric Department, S.Chiara General Hospital of Trento, Azienda Provinciale per i Servizi Sanitari, 38122 Trento, Italy.ORCID 0000-0002-2230-7148
Azienda Ospedaliera Universitaria Integrata Verona · ITUniversity of Chieti-Pescara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

acceptanceAIDexpectationsatisfaction

Identifiers

PMID37511644
PMCPMC10382040
OpenAlexW4381742395

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.