Vetrovsky, T;
Kral, N;
Pfeiferova, M;
Seifert, B;
Capek, V;
Jurkova, K;
Steffl, M;
Cimler, R;
Kuhnova, J;
Harris, T;
et al.
Vetrovsky, T; Kral, N; Pfeiferova, M; Seifert, B; Capek, V; Jurkova, K; Steffl, M; Cimler, R; Kuhnova, J; Harris, T; Ussher, M; Wahlich, C; Malisova, K; Pelclova, J; Dygryn, J; Elavsky, S; Maes, I; Van Dyck, D; Rowlands, A; Yates, T
(2025)
mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): statistical analysis plan.
TRIALS, 26 (1).
p. 166.
ISSN 1745-6215
https://doi.org/10.1186/s13063-025-08865-z
SGUL Authors: Ussher, Michael Henry
![]() |
PDF
Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) |
![]() |
Microsoft Word (.docx) (Additional file 1: Statistical analysis plan checklist)
Supporting information
Download (22kB) |
Abstract
Background Type 2 diabetes and prediabetes represent significant global health challenges, with physical activity (PA) being essential for disease management and prevention. Despite the well-documented benefits, many individuals with (pre)diabetes remain insufficiently active. General practitioners (GP) provide an accessible platform for delivering interventions; however, integrating PA interventions into routine care is hindered by resource constraints. Objectives The ENERGISED trial aims to address these barriers through an innovative GP-initiated mHealth intervention combining wearable technology and just-in-time adaptive interventions. Methods The ENERGISED trial is a pragmatic, 12-month, multicentre, randomised controlled trial, assessing a GP-initiated mHealth intervention to increase PA and reduce sedentary behaviour in patients with type 2 diabetes and prediabetes. The primary outcome is daily step count, assessed via wrist-worn accelerometry. The primary analysis follows the intention-to-treat principle, using mixed models for repeated measures. Missing data will be handled under the missing-at-random assumption, with sensitivity analyses exploring robustness through reference-based multiple imputation. The trial incorporates the estimand framework to provide transparent and structured treatment effect estimation. Discussion This statistical analysis plan outlines a robust approach to addressing participant non-adherence, protocol violations, and missing data. By adopting the estimand framework and pre-specified sensitivity analyses, the plan ensures methodological rigour while enhancing the interpretability and applicability of results. Conclusions The ENERGISED trial leverages innovative mHealth strategies within primary care to promote PA in individuals with (pre)diabetes. The pre-specified statistical framework provides a comprehensive guide for analysing trial data and contributes to advancing best practices in behavioural intervention trials for public health. Trial registration ClinicalTrials.gov NCT05351359. Registered on April 28, 2022.
Item Type: | Article | ||||||
---|---|---|---|---|---|---|---|
Additional Information: | © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ | ||||||
Keywords: | Wearables, Just-in-time adaptive intervention (JITAI), Fitbit, GGIR, Pragmatic trial, Estimand framework, Accelerometer, Text messages, Primary care, Adherence | ||||||
SGUL Research Institute / Research Centre: | Academic Structure > Population Health Research Institute (INPH) | ||||||
Journal or Publication Title: | TRIALS | ||||||
ISSN: | 1745-6215 | ||||||
Language: | en | ||||||
Publisher License: | Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0 | ||||||
Projects: |
|
||||||
URI: | https://openaccess.sgul.ac.uk/id/eprint/117537 | ||||||
Publisher's version: | https://doi.org/10.1186/s13063-025-08865-z |
Statistics
Actions (login required)
![]() |
Edit Item |