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.

• Klíčová slova
• Accelerometer, Adherence, Estimand framework, Fitbit, GGIR, Just-in-time adaptive intervention (JITAI), Pragmatic trial, Primary care, Text messages, Wearables,
• MeSH
• akcelerometrie MeSH
• cvičení * MeSH
• diabetes mellitus 2. typu * terapie   psychologie   diagnóza   MeSH
• fitness náramky MeSH
• lidé MeSH
• multicentrické studie jako téma MeSH
• nositelná elektronika MeSH
• pragmatické klinické studie jako téma MeSH
• praktické lékařství * metody   MeSH
• prediabetes * terapie   psychologie   diagnóza   MeSH
• sedavý životní styl * MeSH
• telemedicína * statistika a číselné údaje   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• protokol klinické studie MeSH

BACKGROUND: The escalating global prevalence of type 2 diabetes and prediabetes presents a major public health challenge. Physical activity plays a critical role in managing (pre)diabetes; however, adherence to physical activity recommendations remains low. The ENERGISED trial was designed to address these challenges by integrating mHealth tools into the routine practice of general practitioners, aiming for a significant, scalable impact in (pre)diabetes patient care through increased physical activity and reduced sedentary behaviour. METHODS: The mHealth intervention for the ENERGISED trial was developed according to the mHealth development and evaluation framework, which includes the active participation of (pre)diabetes patients. This iterative process encompasses four sequential phases: (a) conceptualisation to identify key aspects of the intervention; (b) formative research including two focus groups with (pre)diabetes patients (n = 14) to tailor the intervention to the needs and preferences of the target population; (c) pre-testing using think-aloud patient interviews (n = 7) to optimise the intervention components; and (d) piloting (n = 10) to refine the intervention to its final form. RESULTS: The final intervention comprises six types of text messages, each embodying different behaviour change techniques. Some of the messages, such as those providing interim reviews of the patients' weekly step goal or feedback on their weekly performance, are delivered at fixed times of the week. Others are triggered just in time by specific physical behaviour events as detected by the Fitbit activity tracker: for example, prompts to increase walking pace are triggered after 5 min of continuous walking; and prompts to interrupt sitting following 30 min of uninterrupted sitting. For patients without a smartphone or reliable internet connection, the intervention is adapted to ensure inclusivity. Patients receive on average three to six messages per week for 12 months. During the first six months, the text messaging is supplemented with monthly phone counselling to enable personalisation of the intervention, assistance with technical issues, and enhancement of adherence. CONCLUSIONS: The participatory development of the ENERGISED mHealth intervention, incorporating just-in-time prompts, has the potential to significantly enhance the capacity of general practitioners for personalised behavioural counselling on physical activity in (pre)diabetes patients, with implications for broader applications in primary care.

• Klíčová slova
• Behaviour change techniques, Fitbit, Just-in-time adaptive intervention (JITAI), Participatory development, Phone counselling, Primary care, Self-regulation theory, Text messages, Walking, Wearables,
• MeSH
• cvičení MeSH
• diabetes mellitus 2. typu * prevence a kontrola   epidemiologie   MeSH
• lidé MeSH
• mobilní telefon * MeSH
• praktické lékařství * MeSH
• prediabetes * terapie   MeSH
• sedavý životní styl MeSH
• telemedicína * metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: The growing number of patients with type 2 diabetes and prediabetes is a major public health concern. Physical activity is a cornerstone of diabetes management and may prevent its onset in prediabetes patients. Despite this, many patients with (pre)diabetes remain physically inactive. Primary care physicians are well-situated to deliver interventions to increase their patients' physical activity levels. However, effective and sustainable physical activity interventions for (pre)diabetes patients that can be translated into routine primary care are lacking. METHODS: We describe the rationale and protocol for a 12-month pragmatic, multicentre, randomised, controlled trial assessing the effectiveness of an mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED). Twenty-one general practices will recruit 340 patients with (pre)diabetes during routine health check-ups. Patients allocated to the active control arm will receive a Fitbit activity tracker to self-monitor their daily steps and try to achieve the recommended step goal. Patients allocated to the intervention arm will additionally receive the mHealth intervention, including the delivery of several text messages per week, with some of them delivered just in time, based on data continuously collected by the Fitbit tracker. The trial consists of two phases, each lasting six months: the lead-in phase, when the mHealth intervention will be supported with human phone counselling, and the maintenance phase, when the intervention will be fully automated. The primary outcome, average ambulatory activity (steps/day) measured by a wrist-worn accelerometer, will be assessed at the end of the maintenance phase at 12 months. DISCUSSION: The trial has several strengths, such as the choice of active control to isolate the net effect of the intervention beyond simple self-monitoring with an activity tracker, broad eligibility criteria allowing for the inclusion of patients without a smartphone, procedures to minimise selection bias, and involvement of a relatively large number of general practices. These design choices contribute to the trial's pragmatic character and ensure that the intervention, if effective, can be translated into routine primary care practice, allowing important public health benefits. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05351359, 28/04/2022).

• Klíčová slova
• Active control, Ecological Momentary Assessment (EMA), Fitbit, Just-in-time adaptive intervention (JITAI), Micro-randomisation, Phone counselling, Text messages, Primary care, Self-monitoring, Step-count,
• MeSH
• cvičení MeSH
• diabetes mellitus 2. typu * prevence a kontrola   MeSH
• lidé MeSH
• multicentrické studie jako téma MeSH
• pragmatické klinické studie jako téma MeSH
• praktické lékařství * MeSH
• prediabetes * terapie   MeSH
• randomizované kontrolované studie jako téma MeSH
• sedavý životní styl MeSH
• telemedicína * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• protokol klinické studie MeSH

OBJECTIVE: To determine the net effect of different physical activity intervention components on step counts in addition to self-monitoring. DESIGN: A systematic review with meta-analysis and meta-regression. DATA SOURCES: Five databases (PubMed, Scopus, Web of Science, ProQuest and Discus) were searched from inception to May 2022. The database search was complemented with backward and forward citation searches and search of the references from relevant systematic reviews. ELIGIBILITY CRITERIA: Randomised controlled trials comparing an intervention using self-monitoring (active control arm) with an intervention comprising the same treatment PLUS any additional component (intervention arm). DATA EXTRACTION AND SYNTHESIS: The effect measures were mean differences in daily step count. Meta-analyses were performed using random-effects models, and effect moderators were explored using univariate and multivariate meta-regression models. RESULTS: Eighty-five studies with 12 057 participants were identified, with 75 studies included in the meta-analysis at postintervention and 24 at follow-up. At postintervention, the mean difference between the intervention and active control arms was 926 steps/day (95% CI 651 to 1201). At a follow-up, the mean difference was 413 steps/day (95% CI 210 to 615). Interventions with a prescribed goal and involving human counselling, particularly via phone/video calls, were associated with a greater mean difference in the daily step count than interventions with added print materials, websites, smartphone apps or incentives. CONCLUSION: Physical activity interventions that combine self-monitoring with other components provide an additional modest yet sustained increase in step count compared with self-monitoring alone. Some forms of counselling, particularly remote phone/video counselling, outperformed other intervention components, such as websites and smartphone apps. PROSPERO REGISTERED NUMBER: CRD42020199482.

• Klíčová slova
• Behaviour, Health promotion, Meta-analysis, Physical activity, Walking,
• MeSH
• cvičení * MeSH
• data management MeSH
• lidé MeSH
• mobilní aplikace * MeSH
• motivace MeSH
• telefon MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH
• systematický přehled MeSH

AIMS: Accelerometers are becoming increasingly commonplace for assessing physical activity; however, their use in patients with cardiovascular diseases is relatively substandard. We aimed to systematically review the methods used for collecting and processing accelerometer data in cardiology, using the example of heart failure, and to provide practical recommendations on how to improve objective physical activity assessment in patients with cardiovascular diseases by using accelerometers. METHODS AND RESULTS: Four electronic databases were searched up to September 2019 for observational, interventional, and validation studies using accelerometers to assess physical activity in patients with heart failure. Study and population characteristics, details of accelerometry data collection and processing, and description of physical activity metrics were extracted from the eligible studies and synthesized. To assess the quality and completeness of accelerometer reporting, the studies were scored using 12 items on data collection and processing, such as the placement of accelerometer, days of data collected, and criteria for non-wear of the accelerometer. In 60 eligible studies with 3500 patients (of those, 536 were heart failure with preserved ejection fraction patients), a wide variety of accelerometer brands (n = 27) and models (n = 46) were used, with Actigraph being the most frequent (n = 12), followed by Fitbit (n = 5). The accelerometer was usually worn on the hip (n = 32), and the most prevalent wear period was 7 days (n = 22). The median wear time required for a valid day was 600 min, and between two and five valid days was required for a patient to be included in the analysis. The most common measures of physical activity were steps (n = 20), activity counts (n = 15), and time spent in moderate-to-vigorous physical activity (n = 14). Only three studies validated accelerometers in a heart failure population, showing that their accuracy deteriorates at slower speeds. Studies failed to report between one and six (median 4) of the 12 scored items, with non-wear time criteria and valid day definition being the most underreported items. CONCLUSIONS: The use of accelerometers in cardiology lacks consistency and reporting on data collection, and processing methods need to be improved. Furthermore, calculating metrics based on raw acceleration and machine learning techniques is lacking, opening the opportunity for future exploration. Therefore, we encourage researchers and clinicians to improve the quality and transparency of data collection and processing by following our proposed practical recommendations for using accelerometers in patients with cardiovascular diseases, which are outlined in the article.

• Klíčová slova
• Counts, Cut points, Heart failure, Physical activity, Raw acceleration, Steps,
• MeSH
• akcelerometrie MeSH
• cvičení MeSH
• kardiovaskulární nemoci * MeSH
• lidé MeSH
• srdeční selhání * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• systematický přehled MeSH

INTRODUCTION: Although numerous activity trackers have been validated in healthy populations, validation is lacking in chronic heart failure patients who normally walk at a slower pace, making it difficult for researchers and clinicians to implement activity monitors during physical activity interventions. METHODS: Six consumer-level activity monitors were validated in a 3-day field study in patients with chronic heart failure and healthy individuals under free living conditions. Furthermore, the same devices were evaluated in a lab-based study during treadmill walking at speeds of 2.4, 3.0, 3.6, and 4.2 km·h-1. Concordance correlation coefficients (CCC) were used to evaluate the agreement between the activity monitors and the criterion, and mean absolute percentage errors (MAPE) were calculated to assess differences between each device and the criterion (MAPE <10% was considered as a threshold for validity). RESULTS: In the field study of healthy individuals, all but one of the activity monitors showed a substantial correlation (CCC ≥0.95) with the criterion device and MAPE <10%. In patients with heart failure, the correlation of only two activity monitors (Garmin vívofit 3 and Withings Go) was classified as at least moderate (CCC ≥0.90) and none of the devices had MAPE <10%. In the lab-based study at speeds 4.2 and 3.6 km·h-1, all activity monitors showed substantial to almost perfect correlations (CCC ≥0.95) with the criterion and MAPE in the range 1%-3%. However, at slower speeds of 3.0 and 2.4 km·h-1, the accuracy of all devices substantially deteriorated: their correlation with the criterion decreased below 90% and their MAPE increased to 4-8% and 10-45%, respectively. CONCLUSIONS: Even though none of the tested activity monitors fall within arbitrary thresholds for validity, most of them perform reasonably well enough to be useful tools that clinicians can use to simply motivate chronic heart failure patients to walk more.

• MeSH
• akcelerometrie přístrojové vybavení   metody   MeSH
• ambulantní monitorování přístrojové vybavení   metody   MeSH
• chronická nemoc MeSH
• chůze fyziologie   MeSH
• cvičení fyziologie   MeSH
• dospělí MeSH
• fitness náramky MeSH
• lidé MeSH
• reprodukovatelnost výsledků MeSH
• senioři MeSH
• srdeční selhání patofyziologie   MeSH
• zátěžový test přístrojové vybavení   metody   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH