Does a diabetes phone app lower blood sugar over a year?
A year of using a diabetes self-management phone app, with or without a short course of nurse phone counselling, did not lower long-term blood sugar more than usual care.
Source
A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH
Study at a glance
- Design
- RCT — 3-arm open-label RCT (1:1:1 block randomisation): app only, app plus 4 months of phone health counselling, or usual care; 1-year follow-up
- N
- N=151 · 151 randomised (51 app, 50 app plus counselling, 50 control); HbA1c available for 120 at 1 year
- Population
- Adults in Norway with type 2 diabetes and HbA1c at or above 7.1%, recruited mainly via general practitioners
- Outcome
- Primary: change in HbA1c at 1 year; secondary: self-management (heiQ), quality of life (SF-36), depressive symptoms (CES-D), weight, diet and physical activity
Structured fields used in claim comparison tables when every cited study has a complete layer.
What they did
Adults with poorly controlled type 2 diabetes were randomised to usual care, a phone app linked by Bluetooth to a glucose meter (with diet, activity and goal-setting diaries), or the same app plus five monthly motivational-interviewing phone calls from a diabetes nurse during the first 4 months. Everyone kept seeing their GP as normal. Outcomes were measured at baseline, 4 months and 12 months, analysed by intention-to-treat and adjusted for age, gender and education.
What they found
HbA1c fell in all three groups, but the change did not differ between either app group and usual care after 1 year. There were no between-group differences in weight, quality of life, depressive symptoms, diet or physical activity. The only positive secondary result was a small gain in the 'skill and technique acquisition' self-management domain in the app-plus-counselling group (B = 0.21). Only about a third of app users used it substantially, and, unexpectedly, participants aged 63 or over were more likely to be heavy users (OR 2.7).
The limits
What it doesn't show
The trial was small and powered only for HbA1c, and 21% dropped out, so modest effects on secondary outcomes could be missed. Low use of the app, partly because the phones became outdated during the trial, means it tested offering the app rather than using it consistently. Participants could not be blinded, the control group happened to have more depressive symptoms at baseline, and volunteers motivated to join an mHealth study may not represent typical patients. The authors also question whether HbA1c is the right outcome for a self-management intervention.
Key terms
- HbA1c (glycated haemoglobin)
- A blood measure reflecting average blood glucose over the previous few months; the standard marker of diabetes control.
- mHealth
- Health care or self-care delivered through mobile devices such as phones and apps.
- Motivational interviewing
- A client-centred counselling style that helps people explore and resolve ambivalence about changing behaviour.
- Intention-to-treat analysis
- Analysing participants in the groups they were randomised to, regardless of how much of the intervention they actually used.
- Transtheoretical model (stages of change)
- A model describing readiness to change behaviour in stages, used to tailor counselling to where a person is.
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Quiz yourself
What was the main result for HbA1c at 1 year?
Common questions
If HbA1c dropped in every group, why is this a null result?
An RCT compares groups, and all three improved by similar amounts, so the improvement cannot be credited to the app; it may reflect regression to the mean, study participation or usual GP care.
Does this mean diabetes apps don't work?
Not in general. It shows this low-intensity app and short counselling booster didn't beat usual care in this trial, where most people used the app only lightly.
Why is the finding about older users interesting?
It contradicts the common assumption that older patients avoid technology; here people aged 63 or over were more likely to be substantial app users.
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