Evidence map›Paper›PMID 40040613›Full record

ArticleJournal of advanced nursing2025

Understanding Self-Care Patterns in Adults With Type 1 Diabetes: Insights From a Mixed Methods Study.

Austin M Matus, Lea Ann Matura, Peter F Cronholm, Michael R Rickels, Barbara Riegel

Abstract read
In one paragraph

Article in Journal of advanced nursing, 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
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0citing papers in PubMed
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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

5 authors.

Austin M MatusDivision of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-7564-2524
Lea Ann MaturaUniversity of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.
Peter F CronholmDepartment of Family Medicine and Community Health and Center for Public Health, Leonard Davis Institute of Health Economics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Michael R RickelsDivision of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Barbara RiegelUniversity of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-0970-136X

Funding

Diabetes, Endocrine, and MetabolismT32DK007314 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI DORIS A STOFFERS, Patrick Seale · 1986 to 2026
$9.0M
Restoring awareness of hypoglycemia in type 1 diabetesU01DK135120 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI Michael R Rickels · 2022 to 2026
$2.5M
A Mixed Methods Investigation of Attitudes and Self-Care in Individuals with Type-1 Diabetes Mellitus with Intact and Impaired Awareness of HypoglycemiaF31NR020137 · NINR · UNIVERSITY OF PENNSYLVANIA · PI MATUS, AUSTIN M · 2022 to 2023
$53k
NIDDK NIH HHS T32 DK007314NIDDK NIH HHS T32DK007314NIDDK NIH HHS U01 DK135120NIDDK NIH HHS U01DK135120NINR NIH HHS F31 NR020137NINR NIH HHS F31NR020137
6 · The paper itself

Abstract

aimThe aim of this study was to explore self-care among adults with type 1 diabetes (T1D) to (1) characterise possible self-care profiles in adults with T1D; (2) explain self-care maintenance, monitoring and management within the self-care profiles; and (3) develop a typology of self-care in adults with T1D.

designMixed-methods study with explanatory sequential design.

methodsParticipants (n = 200) completed a validated self-care survey. Cluster analysis of survey data was performed to identify self-care profiles. Then, semi-structured individual interviews were performed with a nested sample (n = 20) stratified by these profiles. Directed content analysis was applied to transcript data to describe self-care within profiles. Findings were integrated via joint display to develop a typology of self-care in adults with T1D. DATA SOURCES: A total of 200 adults with T1D were recruited from a diabetes centre in a large, urban US city from 6/2022 to 11/2022 (quantitative phase) and a nested sample (n = 20) from 12/2022 to 4/2023 (qualitative phase).

resultsWe identified three self-care profiles: Expert, Inconsistent and Novice. Expert self-care was characterised by a steadfast and holistic approach to maintaining health, the use of internal and external cues to monitor for health changes and informed management decision-making when health changes were detected. Inconsistent self-care was characterised by the capability to maintain health, often limited by low health prioritisation, a lack of perceived need for greater effort and compulsive management decision-making. Novice self-care was characterised by difficulty maintaining health and limited skill development in more advanced self-care processes, including monitoring for and managing health changes.

conclusionsThis study identified an Expert-Inconsistent-Novice typology of self-care in adults with T1D, aligning with previous research and suggesting a stable typology across conditions. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Characterising self-care among adults with T1D may facilitate aligning support with individual needs. IMPACT: Progression towards Expert self-care may offer clinically meaningful improvements in glycaemic control and reduced risk for diabetes complications. REPORTING

methodGood Reporting of A Mixed Methods Study (GRAMMS) Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Indexed as

Diabetes Mellitus, Type 1Self CareAdultAgedFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultcluster analysisself‐caretype 1 diabetes mellitus

Identifiers

PMID40040613
PMCPMC12231084

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.