Facilitating Weight Loss and Reversing Type 2 Diabetes (T2D) by Means of a Collaborative eHealth Lifestyle Coaching Intervention in Primary Care - A 2-year Randomised Controlled Trial

1. Introduction With diseases such as Type 2 diabetes (T2D), adiposity and cardiovascular diseases rapidly increasing, cost effective management is needed (World Health Organization, 2017). Lifestyle improvements such as weight loss, diet and exercise managed in a primary care setting has shown significant impact on reduced risk of cardiovascular disease and reversing T2D for 46-56% of patients with T2D (Lean et al., 2017, Johansen et al., 2017). Based on these findings, weight loss among overweight patients with T2D and patients at risk of developing T2D has important clinical and societal effects.

Traditional lifestyle interventions are mostly ineffective and expensive long-term. Internet and mobile technology-based interventions aiming at promoting healthy lifestyles have shown potential for scalability, accessibility, and cost effective use in primary care settings both for overweight patients and T2D patients (Brandt et al, 2011, Haste et al., 2017, Komkova et al 2018). However, there is only sparse knowledge about whether the beneficial effects are long-term (Afshin et al., 2016, Levine et al., 2015).

Qualitative research studies comprising patients, general practitioners and the healthcare professionals' perspectives suggest that the establishment of an empathic relationship is key to long-term lifestyle change (Brandt et al., 2018a, 2018b and 2018c). An observational study among 103 diabetes patients using the collaborative eHealth tool (LIVA) demonstrated a clinically significant self-reported weight loss of 4.7 kg among users who had been on the platform for 90+ days (Komkova et al., 2018). Modelling the association between weight reduction and decreased health care costs, the same study estimated that the program will save 2,667€ annually for every patient and be cost effective from a municipal perspective even with only 1 year of implementation data for T2D patients (Mukherjee et al., 2016, Nichols et al., 2016, Bell et al., 2014).

In the present study, the model to be tested is a lifestyle intervention using a cost-effective eHealth coaching tool (LIVA) model: following an initial meeting, frequent digital communication is established between health coach and patient, supplemented by machine learning. Machine learning is performed using data automatically gathered from patients' relevant daily lifestyle registrations such as activity level, step count, diet goals fulfilment, sleep, etc. Data will be analysed to predict attrition and outcome. The developed algorithms and models will then be used to increase outcome and decrease dropout by supporting the health coaches with information and guidance how to deliver better coaching directly and indirectly. This intervention will be compared with standard lifestyle interventions in a municipality setting. 2. Study objectives and hypothesis The aim of this study is to evaluate the clinical efficacy of the LIVA intervention for overweight patients at risk of developing a chronic disease and overweight type 2 diabetes patients in a primary care setting. We hypothesize that the LIVA intervention will lead to significant weight loss, reduced HbA1C, and reduced need for medication compared to usual care. 3. Methods and analysis Study design and setting The study is a randomized controlled trial with one year of intervention and one year of subsequent maintenance, with continued collection of clinical and questionnaire data, where the primary endpoint is weight loss and the secondary endpoint is HbA1c. The intervention is conducted in a real life setting; all data management will be at the Research Unit for General Practice, Department of Public Health, Primary trial sponsor, J.B. Winsløwsvej 9A, 5000 Odense C, Denmark. Recruitment of patients to the study is in 8-10 municipalities within the Region of Southern Denmark and the Capitol Region of Denmark. The study has been registered at https://register.clinicaltrials.gov. On-boarding of patients began in March 2018 and the results are expected to be accessible during 2021.

Study population and inclusion criteria Flow of patients is described in figure 1. In each municipality, advertising through social media will be used to recruit eligible patients for municipal preventive offers, fulfilling the inclusion criteria in the study (Table 1). These patients will be contacted by phone and/ or email, and informed about the study and asked to register if they accept the offer to participate.