Evidence map›Paper›PMID 32673214›Full record

ArticleJMIR diabetes2020

Web-Based and mHealth Technologies to Support Self-Management in People Living With Type 2 Diabetes: Validation of the Diabetes Self-Management and Technology Questionnaire (DSMT-Q).

Laura Kelly, Crispin Jenkinson, David Morley

Abstract read
In one paragraph

Article in JMIR diabetes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Laura KellyHealth Services Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0003-1454-9240
Crispin JenkinsonHealth Services Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-3692-0779
David MorleyHealth Services Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0003-1911-5855

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA growing number of web-based and mobile health (mHealth) technologies have been developed to support type 2 diabetes self-management. Little is known about individuals' experiences with these technologies and how they support self-management. Appropriate tools are needed to understand how web-based and mHealth interventions may impact self-management.

objectiveThis study aimed to develop an instrument, the Diabetes Self-Management and Technology Questionnaire (DSMT-Q), to assess self-management among people living with type 2 diabetes who use web-based and mHealth technologies.

methodsA total of 36 candidate questionnaire items, drafted previously, were refined using cognitive debriefing interviews (n=8), expert consultation, and public patient involvement feedback. Item reduction steps were performed on survey data (n=250), and tests of validity and reliability were subsequently performed.

resultsFollowing amendments, patients and experts found 21 items relevant and acceptable for inclusion in the instrument. Survey participants included 104 (41.6%) women and 146 (58.4%) men. Two subscales with high construct validity, internal consistency, and test-retest reliability were identified: "Understanding individual health and making informed decisions" and "Confidence to reach and sustain goals."

conclusionsAnalyses confirmed good psychometric properties in the DSMT-Q scales. This tool will facilitate the measurement of self-management in people living with type 2 diabetes who use web-based or mHealth technologies.

Indexed as

mHealthquestionnaireself-careself-monitoringtype 2 diabetes

Identifiers

PMID32673214
PMCPMC7380900

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.