Evidence map›Paper›PMID 36939680›Full record

ArticleJMIR diabetes2023

Improving the Well-being of Adolescents With Type 1 Diabetes During the COVID-19 Pandemic: Qualitative Study Exploring Acceptability and Clinical Usability of a Self-compassion Chatbot.

Anna Boggiss, Nathan Consedine, Sarah Hopkins, Connor Silvester, Craig Jefferies, Paul Hofman, Anna Serlachius

Open access · goldAbstract read
In one paragraph

Article in JMIR diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
5.1field-weighted citation impact, top 4% 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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
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  7. The usability and feasibility of a self-compassion chatbot (COMPASS) for youth living with type 1 diabetes.Diabetic medicine : a journal of the British Diabetic Association · 2025
    Article
  8. Article
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  11. Chatbots and COVID-19: Taking Stock of the Lessons Learned.Journal of medical Internet research · 2024
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  13. Review
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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

7 authors at 3 institutions in 1 country.

Anna BoggissDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7336-955X
Nathan ConsedineDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-7691-0938
Sarah HopkinsDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-4705-5362
Connor SilvesterDepartment of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-8958-350X
Craig JefferiesStarship Children's Health, Auckland City Hospital, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-0541-6094
Paul HofmanLiggins Institute, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-8995-8711
Anna SerlachiusDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-4797-8351
University of Auckland · NZAuckland City Hospital · NZAuckland University of Technology · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBefore the COVID-19 pandemic, adolescents with type 1 diabetes (T1D) had already experienced far greater rates of psychological distress than their peers. With the pandemic further challenging mental health and increasing the barriers to maintaining optimal diabetes self-management, it is vital that this population has access to remotely deliverable, evidence-based interventions to improve psychological and diabetes outcomes. Chatbots, defined as digital conversational agents, offer these unique advantages, as well as the ability to engage in empathetic and personalized conversations 24-7. Building on previous work developing a self-compassion program for adolescents with T1D, a self-compassion chatbot (COMPASS) was developed for adolescents with T1D to address these concerns. However, the acceptability and potential clinical usability of a chatbot to deliver self-compassion coping tools to adolescents with T1D remained unknown.

objectiveThis qualitative study was designed to evaluate the acceptability and potential clinical utility of COMPASS among adolescents aged 12 to 16 years with T1D and diabetes health care professionals.

methodsPotential adolescent participants were recruited from previous participant lists, and on the web and in-clinic study flyers, whereas health care professionals were recruited via clinic emails and from diabetes research special interest groups. Qualitative Zoom (Zoom Video Communications, Inc) interviews exploring views on COMPASS were conducted with 19 adolescents (in 4 focus groups) and 11 diabetes health care professionals (in 2 focus groups and 6 individual interviews) from March 2022 to April 2022. Transcripts were analyzed using directed content analysis to examine the features and content of greatest importance to both groups.

resultsAdolescents were broadly representative of the youth population living with T1D in Aotearoa (11/19, 58% female; 13/19, 68% Aotearoa New Zealand European; and 2/19, 11% Māori). Health care professionals represented a range of disciplines, including diabetes nurse specialists (3/11, 27%), health psychologists (3/11, 27%), dieticians (3/11, 27%), and endocrinologists (2/11, 18%). The findings offer insight into what adolescents with T1D and their health care professionals see as the shared advantages of COMPASS and desired future additions, such as personalization (mentioned by all 19 adolescents), self-management support (mentioned by 13/19, 68% of adolescents), clinical utility (mentioned by all 11 health care professionals), and breadth and flexibility of tools (mentioned by 10/11, 91% of health care professionals).

conclusionsEarly data suggest that COMPASS is acceptable, is relevant to common difficulties, and has clinical utility during the COVID-19 pandemic. However, shared desired features among both groups, including problem-solving and integration with diabetes technology to support self-management; creating a safe peer-to-peer sense of community; and broadening the representation of cultures, lived experience stories, and diabetes challenges, could further improve the potential of the chatbot. On the basis of these findings, COMPASS is currently being improved to be tested in a feasibility study.

Indexed as

adolescenceartificial intelligencechatbotconversational agentCOVID-19digital healthmental healthmobile phonepsychosocial interventionsself-compassiontype 1 diabetes

Identifiers

PMID36939680
PMCPMC10166132
OpenAlexW4318598114

What OpenQuestion 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 OpenQuestion graph.