Cited by 344Diabetes Management and EducationMobile Health and mHealth ApplicationsDigital Mental Health Interventions

Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus

Open access
Pal, Kingshuk, Eastwood, Sophie V, Michie, Susan, Farmer, Andrew J, Barnard, Maria L, Peacock, Richard, Wood, Bindie, Inniss, Joni D +1 more·2013·Cochrane Database of Systematic Reviews

Abstract

BACKGROUND: Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient education programmes reduce the risk of diabetes-related complications four-fold. Internet-based self-management programmes have been shown to be effective for a number of long-term conditions, but it is unclear what are the essential or effective components of such programmes. If computer-based self-management interventions improve outcomes in type 2 diabetes, they could potentially provide a cost-effective option for reducing the burdens placed on patients and healthcare systems by this long-term condition. OBJECTIVES: To assess the effects on health status and health-related quality of life of computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. SEARCH METHODS: We searched six electronic bibliographic databases for published articles and conference proceedings and three online databases for theses (all up to November 2011). Reference lists of relevant reports and reviews were also screened. SELECTION CRITERIA: Randomised controlled trials of computer-based self-management interventions for adults with type 2 diabetes, i.e. computer-based software applications that respond to user input and aim to generate tailored content to improve one or more self-management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the abstracts and extracted data. A taxonomy for behaviour change techniques was used to describe the active ingredients of the intervention. MAIN RESULTS: We identified 16 randomised controlled trials with 3578 participants that fitted our inclusion criteria. These studies included a wide spectrum of interventions covering clinic-based brief interventions, Internet-based interventions that could be used from home and mobile phone-based interventions. The mean age of participants was between 46 to 67 years old and mean time since diagnosis was 6 to 13 years. The duration of the interventions varied between 1 to 12 months. There were three reported deaths out of 3578 participants.Computer-based diabetes self-management interventions currently have limited effectiveness. They appear to have small benefits on glycaemic control (pooled effect on glycosylated haemoglobin A1c (HbA1c): -2.3 mmol/mol or -0.2% (95% confidence interval (CI) -0.4 to -0.1; P = 0.009; 2637 participants; 11 trials). The effect size on HbA1c was larger in the mobile phone subgroup (subgroup analysis: mean difference in HbA1c -5.5 mmol/mol or -0.5% (95% CI -0.7 to -0.3); P < 0.00001; 280 participants; three trials). Current interventions do not show adequate evidence for improving depression, health-related quality of life or weight. Four (out of 10) interventions showed beneficial effects on lipid profile.One participant withdrew because of anxiety but there were no other documented adverse effects. Two studies provided limited cost-effectiveness data - with one study suggesting costs per patient of less than $140 (in 1997) or 105 EURO and another study showed no change in health behaviour and resource utilisation. AUTHORS' CONCLUSIONS: Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control and the effect was larger in the mobile phone subgroup. There is no evidence to show benefits in other biological outcomes or any cognitive, behavioural or emotional outcomes.

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Crossref · 10.1002/14651858.cd008776.pub2

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  • Previous controlled studies have demonstrated the effectiveness of digital interventions in metabolic health.

    “our findings build upon previous controlled studies demonstrating the effectiveness of digital interventions in metabolic health18.”

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Authors
Pal, K., Eastwood, S. V., Michie, S., Farmer, A. J., Barnard, M. L., Peacock, R., Wood, B., Inniss, J. D., & Murray, E.
Affiliations
  • The Royal Free Hospital (GB)
  • University of Oxford; Department of Primary Care Health Sciences; Radcliffe Observatory Quarter, Walton Street Oxford UK OX2 6GG
  • Whittington Hospital (GB)
  • Archway Healthcare Library; Holborn Union Building Archway Campus, Highgate Hill London UK N19 5LW
Venue
Cochrane Database of Systematic Reviews
Publisher
Wiley
Published
2013-03-28
Volume
2013
Issue
3
Pages
CD008776-CD008776
ISSN
  • 1361-6137 (ISSN-L)
  • 1465-1858
OpenAlex
W2031205218
Cited by
344
References
167
Citations by year
2026: 10 · 2025: 9 · 2024: 21 · 2023: 23 · 2022: 27 · 2021: 14 · 2020: 29 · 2019: 31 · 2018: 39 · 2017: 35 · 2016: 38 · 2015: 25 · 2014: 25 · 2013: 14 · 2012: 2
FWCI
5.02
Type
journal article
Language
en
Open access
Locations
  • Cochrane Database of Systematic Reviews (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
National Institute for Health and Care Research (RP-PG-0609-10135)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
type 2 diabetes, diabetes self-management, computer-based intervention, online intervention, mobile phone intervention, glycemic control, HbA1c, health-related quality of life, behaviour change techniques, patient education, patient decision support, goal setting, tailored advice, feedback and reinforcement, cost-effectiveness, chronic disease, diabetes complications
MeSH terms
Adult, Aged, Diabetes Mellitus, Type 2, Health Status, Glycated Hemoglobin, Humans, Middle Aged, Quality of Life, Self Care, Therapy, Computer-Assisted, Randomized Controlled Trials as Topic, Internet

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