Evidence map›Paper›PMID 41306078›Full record

SynthesisJournal of medical Internet research2025

Functions, Features, and Psychological Well-Being Impacts of Type 1 Diabetes Self-Management Mobile and Web Apps: Systematic Review.

Titouan Cloarec, Katie Cunneen, David Nickson, Simon Leigh, Petra Hanson, Carla Toro

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Titouan CloarecWarwick Applied Health, Warwick Medical School, University of Warwick, Gibbet Hill Campus, Coventry, CV4 7AL, United Kingdom, 44 07491330344.ORCID http://orcid.org/0009-0009-6808-8874
Katie CunneenDepartment of Psychology, University of Warwick, Coventry, United Kingdom.ORCID http://orcid.org/0000-0002-0666-1622
David NicksonWarwick Applied Health, Warwick Medical School, University of Warwick, Gibbet Hill Campus, Coventry, CV4 7AL, United Kingdom, 44 07491330344.ORCID http://orcid.org/0000-0003-1995-224X
Simon LeighWarwick Applied Health, Warwick Medical School, University of Warwick, Gibbet Hill Campus, Coventry, CV4 7AL, United Kingdom, 44 07491330344.ORCID http://orcid.org/0000-0002-6843-6447
Petra HansonWarwick Applied Health, Warwick Medical School, University of Warwick, Gibbet Hill Campus, Coventry, CV4 7AL, United Kingdom, 44 07491330344.ORCID http://orcid.org/0000-0002-6845-1049
Carla ToroWarwick Applied Health, Warwick Medical School, University of Warwick, Gibbet Hill Campus, Coventry, CV4 7AL, United Kingdom, 44 07491330344.ORCID http://orcid.org/0000-0001-6351-1340

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People living with type 1 diabetes must adhere to an intense self-care regimen, which may impact their psychological well-being and contribute to poor self-management behaviors. Despite their potential, most mobile health and web-based apps for diabetes management prioritize glycemic control and often overlook psychological well-being. As a result, evidence on the effectiveness of these interventions in improving psychological well-being remains limited, and there is still uncertainty about which functions and features are the most effective. Objective: The objective of this review was to assess changes in the psychological well-being of people with type 1 diabetes and identify the functions and features of mobile and web-based interventions that may enhance their psychological well-being. Methods: Relevant studies were identified through PubMed, Web of Knowledge, Embase, Scopus, APA PsycInfo, and the Cochrane Central Register of Controlled Trials, with the search conducted at the end of November 2024. Studies were included if they quantitatively assessed the impact of mobile health or web-based apps on psychological well-being in people with type 1 diabetes using validated screening tools. A conventional content analysis approach was used to categorize the functions and features of the included interventions. Results: In total, 8 of the 2142 articles identified met the inclusion criteria and were included in the review. Six categories of functions were identified, each incorporating different sets of features: (1) therapy, (2) education, (3) self-management, (4) peer support, (5) health care professional-patient support, and (6) parental support. Only 2 of the 8 studies reported improved psychological well-being. One of these 2 studies included therapy-based interventions, while the other combined self-management, education, and peer support functions. However, the limited number of studies and variability in study design and participant characteristics limited the ability to attribute the effectiveness in improving psychological well-being to specific functions and features or their combinations. Conclusions: This review highlights the limited effectiveness of currently available mobile health and web-based interventions in improving the psychological well-being of people living with type 1 diabetes. While some interventions showed promise, the findings highlight the need for targeted, theory-based approaches; stakeholder involvement in intervention design and development; and combination of functions and features to improve support and long-term outcomes.

Indexed as

Diabetes Mellitus, Type 1InternetMobile ApplicationsSelf CareSelf-ManagementHumansPsychological Well-BeingTelemedicinemobile healthPRISMApsychological well-beingtype 1 diabetesweb-based interventions

Identifiers

PMID41306078
PMCPMC12658348

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.