ArticleTrials2024
Effectiveness of a digital health and financial incentive intervention to promote physical activity in patients with type 2 diabetes: study protocol for a randomised controlled trial with a nested qualitative study-ACTIVATE trial.
Article in Trials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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.
Who cites it
2 citing papers in PubMed.
- Effects of Tai Chi on Cognitive Function in Older Adults With Type 2 Diabetes Mellitus: Randomized Controlled Trial Using Wearable Devices in a Mobile Health Model.Journal of medical Internet research · 2025Trial
- Natural remedies proposed for the management of diabetic retinopathy (DR): diabetic complications.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe prevention of type 2 diabetes (T2DM) is recognised as a health care priority in the UK. In people living with T2DM, lifestyle changes (e.g. increasing physical activity) have been shown to slow disease progression and protect from the development of associated comorbidities. The use of digital health technologies provides a strategy to increase physical activity in patients with chronic disease. Furthermore, behaviour economics suggests that financial incentives may be a useful strategy for increasing the maintenance and effectiveness of behaviour change intervention, including physical activity intervention using digital health technologies. The Milton Keynes Activity Rewards Programme (MKARP) is a 24-month intervention which combines the use of a mobile health app, smartwatch (Fitbit or Apple watch) and financial incentives to encourage people living with T2DM to increase physical activity to improve health. Therefore, this randomised controlled trial aims to examine the long-term acceptability, health effects and cost-effectiveness of the MKARP on HbA1c in patients living with T2DM versus a waitlist usual care comparator.
methodsA two-arm, single-centre, randomised controlled trial aiming to recruit 1018 participants with follow-up at 12 and 24 months. The primary outcome is the change in HbA1c at 12 months. Secondary outcomes included changes in markers of metabolic, cardiovascular, anthropometric, and psychological health along with cost-effectiveness. Recruitment will be via annual diabetes review in general practices, retinal screening services and social media. Participants aged 18 or over, with a diagnosis of type 2 diabetes and a valid HbA1c measurement in the last 2 months are invited to take part in the trial. Participants will be individually randomised (1:1 ratio) to receive either the Milton Keynes Activity Rewards Programme or usual care. The intervention will last for 24 months with assessment for outcomes at baseline, 12 and 24 months. DISCUSSION: This study will provide new evidence of the long-term effectiveness of an activity rewards scheme focused on increasing physical activity conducted within routine care in patients living with type 2 diabetes in Milton Keynes, UK. It will also investigate the cost-effectiveness of the intervention.
trial registrationISRCTN 14925701. Registered on 30 October 2023.
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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.