Evidence map›Paper›PMID 30862052›Full record

Trial reportNutrients2019

A Pilot Randomised Controlled Trial of a Text Messaging Intervention with Customisation Using Linked Data from Wireless Wearable Activity Monitors to Improve Risk Factors Following Gestational Diabetes.

N Wah Cheung, Caron Blumenthal, Ben J Smith, Roslyn Hogan, Aravinda Thiagalingam, Julie Redfern, Tony Barry, Nancy Cinnadaio, Clara K Chow

Open access · goldAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Nutrients, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 13 pooled it
4.8field-weighted citation impact, top 5% 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

33 citing papers in PubMed, 13 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

N Wah CheungDepartment of Diabetes & Endocrinology, Westmead Hospital, Westmead NSW 2145, Australia. wah.cheung@sydney.edu.au.
Caron BlumenthalDivision of Women and Newborn Health, Westmead Hospital, Westmead NSW 2145, Australia. Caron.Blumenthal@health.nsw.gov.au.
Ben J SmithSchool of Public Health, University of Sydney, Sydney NSW 2006, Australia. ben.smith@sydney.edu.au.
Roslyn HoganDepartment of Diabetes & Endocrinology, Westmead Hospital, Westmead NSW 2145, Australia. Roslyn.Hogan@health.nsw.gov.au.
Aravinda ThiagalingamWestmead Clinical School & Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Westmead NSW 2145, Australia. Aravinda.Thiagalingam@health.nsw.gov.au.
Julie RedfernWestmead Clinical School & Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Westmead NSW 2145, Australia. julie.redfern@sydney.edu.au.ORCID 0000-0001-8707-5563
Tony BarryDepartment of Cardiology, Westmead Hospital, Westmead NSW 2145, Australia. tonybarry@mac.com.
Nancy CinnadaioDepartment of Diabetes & Endocrinology, Westmead Hospital, Westmead NSW 2145, Australia. cinnadaio@gmail.com.
Clara K ChowWestmead Clinical School & Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, Westmead NSW 2145, Australia. clara.chow@sydney.edu.au.
The University of Sydney · AUWestmead Hospital · AU

Funding

Australian Diabetes Society xxx
6 · The paper itself

Abstract

Gestational diabetes (GDM) is a highly prevalent disorder of pregnancy which portends a high risk for future type 2 diabetes. Limited evidence indicates lifestyle intervention prevents the development of diabetes, but most previously studied interventions are resource-intensive. Intervention programs that utilise newer technologies may be scalable at lower cost. This 6-month pilot randomized controlled trial tested the delivery of text messages linked to an activity monitor, adaptive physical activity goal setting, and limited face-to-face counseling, as an intervention to improve rates of post-partum glucose tolerance testing and lifestyle behaviours amongst women following a GDM pregnancy. Sixty subjects were randomised 2:1 intervention vs. control. Compared to control subjects, there were trends for intervention subjects to improve diet, increase physical activity, and lose weight. There was no difference between the groups in the rate of glucose tolerance testing. Only 46 (77%) subjects completed some, and 19 subjects completed all the elements of the final evaluation. Feedback regarding the text messages and activity monitor was highly positive. Overall, results suggest that a text message and activity monitor intervention is feasible for a larger study or even as a potentially scalable population health intervention. However, low completion rates necessitate carefully considered modification of the protocol.

Indexed as

ExerciseText MessagingAdultDiabetes, GestationalFemaleHumansPilot ProjectsPregnancyRisk Factorsactivity monitordiabetes preventiongestational diabeteslifestyle programM-healthrandomized controlled trialtext messaging

Identifiers

PMID30862052
PMCPMC6470941
OpenAlexW2921924044

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.