mHealth intervention delivered in general practice to increase physical activity and reduce sedentary behaviour of patients with prediabetes and type 2 diabetes (ENERGISED): rationale and study protocol for a pragmatic randomised controlled trial

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

Participatory development 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)

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

Teorie cisel v matematicke olympiade a ve vyuce gymnazii

Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi

Predictions of Alzheimer's disease treatment and care costs in European countries.

BACKGROUND:Given the increasing lifespan of the elderly and the higher proportion of older people in the global population, the incidence rate of neurodegenerative diseases is increasing. The aim of this study is to evaluate, by means of computer simulations, developments in the costs of treating and caring for people suffering from Alzheimer's disease (AD) in the EU 28 by 2080, while assuming the introduction of drug administrations at various disease stages. METHODS:Impact analysis leverages a mathematical model that compares five different population development scenarios when introducing different types of drugs to the scenarios but without changing the treatment. Changes in the economic burden are considered as of 2023, when new drugs are expected to enter the market. FINDINGS:The results of the simulations show that by prolonging the length of a person's 'stay' in the Mild, Moderate, or Severe stage, the total cost of care for all persons with AD will increase by 2080. For individual scenarios, the percentage of patients and costs increased as follows: Mild by one year, by 10.61%; Mild by two years, by 17.73%; Moderate by one year, by 16.79%; Moderate by two years, by 34.88%; and Severe by one year, by 23.79%. The change in cost development when prolonging the stay in the Mild cognitive impairment stage (by lowering the incidence by 10%, 30%, or 50%) reduced the cost (by 4.88%, 16.78% and 32.48%, respectively). INTERPRETATION:The results unambiguously show that any intervention prolonging a patient's stay in any stage will incur additional care costs and an increase in the number of persons with AD. Therefore, extending lifespan is important in terms of improving the quality of life of patients, and the introduction of new drugs must consider the additional costs imposed upon society

Feasibility of Real-time Behavior Monitoring Via Mobile Technology in Czech Adults Aged 50 Years and Above: 12-Week Study With Ecological Momentary Assessment

BackgroundCzech older adults have lower rates of physical activity than the average population and lag behind in the use of digital technologies, compared with their peers from other European countries. ObjectiveThis study aims to assess the feasibility of intensive behavior monitoring through technology in Czech adults aged ≥50 years. MethodsParticipants (N=30; mean age 61.2 years, SD 6.8 years, range 50-74 years; 16/30, 53% male; 7/30, 23% retired) were monitored for 12 weeks while wearing a Fitbit Charge 2 monitor and completed three 8-day bursts of intensive data collection through surveys presented on a custom-made mobile app. Web-based surveys were also completed before and at the end of the 12-week period (along with poststudy focus groups) to evaluate participants’ perceptions of their experience in the study. ResultsAll 30 participants completed the study. Across the three 8-day bursts, participants completed 1454 out of 1744 (83% compliance rate) surveys administered 3 times per day on a pseudorandom schedule, 451 out of 559 (81% compliance rate) end-of-day surveys, and 736 episodes of self-reported planned physical activity (with 29/736, 3.9% of the reports initiated but returned without data). The overall rating of using the mobile app and Fitbit was above average (74.5 out of 100 on the System Usability Scale). The majority reported that the Fitbit (27/30, 90%) and mobile app (25/30, 83%) were easy to use and rated their experience positively (25/30, 83%). Focus groups revealed that some surveys were missed owing to notifications not being noticed or that participants needed a longer time window for survey completion. Some found wearing the monitor in hot weather or at night uncomfortable, but overall, participants were highly motivated to complete the surveys and be compliant with the study procedures. ConclusionsThe use of a mobile survey app coupled with a wearable device appears feasible for use among Czech older adults. Participants in this study tolerated the intensive assessment schedule well, but lower compliance may be expected in studies of more diverse groups of older adults. Some difficulties were noted with the pairing and synchronization of devices on some types of smartphones, posing challenges for large-scale studies