Evidence map›Paper›PMID 29773539›Full record

Trial reportBMJ (Clinical research ed.)2018

Effectiveness of text message based, diabetes self management support programme (SMS4BG): two arm, parallel randomised controlled trial.

Rosie Dobson, Robyn Whittaker, Yannan Jiang, Ralph Maddison, Matthew Shepherd, Catherine McNamara, Richard Cutfield, Manish Khanolkar, Rinki Murphy

2 registry-linked trialsOpen access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMJ (Clinical research ed.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 84 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 8 pooled it
13.3field-weighted citation impact, top 1% 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.

NCT06118671 naunknown statusnot on this mapstarted 2023, after this paper: background citation

Application and Effectiveness Evaluation of Artificial Intelligence in Lifestyle Management of Diabetic Patients of Community

TypeinterventionalSponsorChongqing Medical UniversityRan2023 to 2024Enrolled460ConditionsDiabetesArmspersonalized lifestyle intervention by AI
NCT06957093 narecruitingnot on this mapstarted 2025, after this paper: background citation

Evaluation of the Therapeutic Efficacy and Safety of Artificial Intelligence-based Decision-making Technology in the Integrated Management of Diabetes Mellitus: a Longitudinal, Open-labeled, Randomized Controlled Trial

TypeinterventionalSponsorThe First Hospital of Jilin UniversityRan2025 to 2026Enrolled400ConditionsDiabetes Mellitus Type 2 (T2DM), Artificial Intelligence (AI)Armsartificial intelligence, Routine diagnosis and treatment group for diabetes
3 · Its place in the literature

Who cites it

84 citing papers in PubMed, 8 syntheses or guidelines pooled it, 169 citations in OpenAlex.

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  6. Informational support for depression and quality of life improvements in older patients with cancer: a systematic review and meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
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  11. The effect of a community-based health behaviour intervention on health-related quality of life in people with Type 2 diabetes in Nepal: a Cluster Randomized Controlled Trial.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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24 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Rosie DobsonNational Institute for Health Innovation, School of Population Health, University of Auckland, Auckland 1142, New Zealand r.dobson@auckland.ac.nz.
Robyn WhittakerNational Institute for Health Innovation, School of Population Health, University of Auckland, Auckland 1142, New Zealand.
Yannan JiangNational Institute for Health Innovation, School of Population Health, University of Auckland, Auckland 1142, New Zealand.
Ralph MaddisonInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Burwood VIC, Australia.
Matthew ShepherdSchool of Counselling, Human Services and Social Work, University of Auckland, Auckland, New Zealand.
Catherine McNamaraDiabetes Service, North Shore Hospital, Takapuna, Auckland, New Zealand.
Richard CutfieldDiabetes Service, North Shore Hospital, Takapuna, Auckland, New Zealand.
Manish KhanolkarAuckland Diabetes Centre, Greenlane Clinical Centre, Auckland, New Zealand.
Rinki MurphyAuckland Diabetes Centre, Greenlane Clinical Centre, Auckland, New Zealand.
University of Auckland · NZNorth Shore Hospital · NZDeakin University · AUGreenlane Clinical Centre · NZWaitemata District Health Board · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine the effectiveness of a theoretically based and individually tailored, text message based, diabetes self management support intervention (SMS4BG) in adults with poorly controlled diabetes.

designNine month, two arm, parallel randomised controlled trial.

settingPrimary and secondary healthcare services in New Zealand.

participants366 participants aged 16 years and over with poorly controlled type 1 or type 2 diabetes (HbA1c ≥65 mmol/mol or 8%) randomised between June 2015 and November 2016 (n=183 intervention, n=183 control).

interventionsThe intervention group received a tailored package of text messages for up to nine months in addition to usual care. Text messages provided information, support, motivation, and reminders related to diabetes self management and lifestyle behaviours. The control group received usual care. Messages were delivered by a specifically designed automated content management system.

main outcome measuresPrimary outcome measure was change in glycaemic control (HbA1c) from baseline to nine months. Secondary outcomes included change in HbA1c at three and six months, and self efficacy, diabetes self care behaviours, diabetes distress, perceptions and beliefs about diabetes, health related quality of life, perceived support for diabetes management, and intervention engagement and satisfaction at nine months. Regression models adjusted for baseline outcome, health district category, diabetes type, and ethnicity.

resultsThe reduction in HbA1c at nine months was significantly greater in the intervention group (mean -8.85 mmol/mol (standard deviation 14.84)) than in the control group (-3.96 mmol/mol (17.02); adjusted mean difference -4.23 (95% confidence interval -7.30 to -1.15), P=0.007). Of 21 secondary outcomes, only four showed statistically significant improvements in favour of the intervention group at nine months. Significant improvements were seen for foot care behaviour (adjusted mean difference 0.85 (95% confidence interval 0.40 to 1.29), P<0.001), overall diabetes support (0.26 (0.03 to 0.50), P=0.03), health status on the EQ-5D visual analogue scale (4.38 (0.44 to 8.33), P=0.03), and perceptions of illness identity (-0.54 (-1.04 to -0.03), P=0.04). High levels of satisfaction with SMS4BG were found, with 161 (95%) of 169 participants reporting it to be useful, and 164 (97%) willing to recommend the programme to other people with diabetes.

conclusionA tailored, text message based, self management support programme resulted in modest improvements in glycaemic control in adults with poorly controlled diabetes. Although the clinical significance of these results is unclear, the findings support further investigation into the use of SMS4BG and other text message based support for this patient population.

trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12614001232628.

Indexed as

Text MessagingAdolescentAdultDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2FemaleGlycated HemoglobinHealth PromotionHumansMaleMiddle AgedNew ZealandProgram EvaluationQuality of LifeSelf-ManagementYoung AdultGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID29773539
PMCPMC5957049
OpenAlexW2803239462

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.