The StopDia study is based on the convincing scientific evidence that type 2 diabetes (T2D) and its comorbidities can be prevented by a healthy lifestyle. The need for additional research is based on the fact that the attempts to translate scientific evidence into actions in the real-world health care have not led to permanent and cost-effective models to prevent T2D. The specific aims of the StopDia study following the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework are to 1) improve the Reach of individuals at increased risk, 2) evaluate the Effectiveness and cost-effectiveness of the digital lifestyle intervention and the digital and face-to-face group lifestyle intervention in comparison to routine care in a randomized controlled trial (RCT), and 3) evaluate the Adoption and Implementation of the StopDia model by the participants and the health care organizations at society level. Finally, we will address the Maintenance of the lifestyle changes at participant level and that of the program at organisatory level after the RCT. The StopDia study is carried out in the primary health care system as part of the routine actions of three provinces in Finland, including Northern Savo, Southern Carelia, and Päijät-Häme. We estimate that one fifth of adults aged 18–70 years living in these areas are at increased risk of T2D. We recruit the participants using the StopDia Digital Screening Tool, including questions from the Finnish Diabetes Risk Score (FINDRISC). About 3000 individuals at increased risk of T2D (FINDRISC ≥12 or a history of gestational diabetes, impaired fasting glucose, or impaired glucose tolerance) participate in the one-year randomized controlled trial. We monitor lifestyle factors using the StopDia Digital Questionnaire and metabolism using laboratory tests performed as part of routine actions in the health care system. Sustainable and scalable models are needed to reach and identify individuals at increased risk of T2D and to deliver personalized and effective lifestyle interventions. With the StopDia study we aim to answer these challenges in a scientific project that is fully digitally integrated into the routine health care. ClinicalTials.gov . Identifier: NCT03156478 . Date of registration 17.5.2017.

Background: Digital health interventions may offer a scalable way to prevent type 2 diabetes (T2D) with minimal burden on health care systems by providing early support for healthy behaviors among adults at increased risk for T2D. However, ensuring continued engagement with digital solutions is a challenge impacting the expected effectiveness. Objective: We aimed to investigate the longitudinal usage patterns of a digital healthy habit formation intervention, BitHabit, and the associations with changes in T2D risk factors. Methods: This is a secondary analysis of the StopDia (Stop Diabetes) study, an unblinded parallel 1-year randomized controlled trial evaluating the effectiveness of the BitHabit app alone or together with face-to-face group coaching in comparison with routine care in Finland in 2017-2019 among community-dwelling adults (aged 18 to 74 years) at an increased risk of T2D. We used longitudinal data on usage from 1926 participants randomized to the digital intervention arms. Latent class growth models were applied to identify user engagement trajectories with the app during the study. Predictors for trajectory membership were examined with multinomial logistic regression models. Analysis of covariance was used to investigate the association between trajectories and 12-month changes in T2D risk factors. Results: More than half (1022/1926, 53.1%) of the participants continued to use the app throughout the 12-month intervention. The following 4 user engagement trajectories were identified: terminated usage (904/1926, 46.9%), weekly usage (731/1926, 38.0%), twice weekly usage (208/1926, 10.8%), and daily usage (83/1926, 4.3%). Active app use during the first month, higher net promoter score after the first 1 to 2 months of use, older age, and better quality of diet at baseline increased the odds of belonging to the continued usage trajectories. Compared with other trajectories, daily usage was associated with a higher increase in diet quality and a more pronounced decrease in BMI and waist circumference at 12 months. Conclusions: Distinct long-term usage trajectories of the BitHabit app were identified, and individual predictors for belonging to different trajectory groups were found. These findings highlight the need for being able to identify individuals likely to disengage from interventions early on, and could be used to inform the development of future adaptive interventions. Trial Registration: ClinicalTrials.gov NCT03156478; https://clinicaltrials.gov/ct2/show/NCT03156478 International Registered Report Identifier (IRRID): RR2-10.1186/s12889-019-6574-y

Lack of tools to evaluate the quality of diet impedes dietary counselling in healthcare. We constructed a scoring for a validated food intake questionnaire, to measure the adherence to a healthy diet that prevents type 2 diabetes (T2D). The Healthy Diet Index (HDI) consists of seven weighted domains (meal pattern, grains, fruit and vegetables, fats, fish and meat, dairy, snacks and treats). We studied the correlations of the HDI with nutrient intakes calculated from 7-day food records among 52 men and 25 women, and associations of HDI with biomarkers and anthropometrics among 645 men and 2455 women. The HDI correlated inversely with total fat (Pearson’s r = −0.37), saturated fat (r = −0.37), monounsaturated fat (r = −0.37), and the glycaemic index of diet (r = −0.32) and positively with carbohydrates (r = 0.23), protein (r = 0.25), fibre (r = 0.66), magnesium (r = 0.26), iron (r = 0.25), and vitamin D (r = 0.27), (p < 0.05 for all). In the linear regression model adjusted for BMI and age, HDI is associated inversely with waist circumference, concentrations of fasting and 2-h glucose and triglycerides in men and women, total and LDL cholesterol in women, and fasting insulin in men (p < 0.05 for all). The HDI proved to be a valid tool to measure adherence to a health-promoting diet and to support individualised dietary counselling.

Eating competence is an attitudinal and behavioral concept, based on The Satter Eating Competence Model. In adults, it has been shown to be associated with a higher quality of diet. Eating competence or its association with the quality of diet has not been studied in adolescents. The aim of the current study was to explore the utility of using a preliminary Finnish translation of the ecSI 2.0 for evaluating presumed eating competence and its association with food selection, meal patterns and related psychobehavioral factors in 10–17 year old adolescents. Altogether 976 10–17 years old Finnish adolescents filled in the study questionnaire. When exploring the construct validity of ecSI 2.0, the confirmatory factor analysis (CFA) indicated acceptable model fit and all four components of the ecSI 2.0 (eating attitudes, food acceptance, internal regulation of food intake, management of eating context) correlated with each other and were internally consistent. Over half (58%) of the adolescents scored 32 or higher and were thus classified as presumably eating competent (pEC). Eating competence was associated with greater meal frequency, more frequent consumption of vegetables and fruits, and more health-promoting family eating patterns. In addition the pEC, adolescents more often perceived their body size as appropriate, had less often tried to lose weight and had a higher self-esteem and a stronger sense of coherence than the not pEC ones. Family eating patterns and self-esteem were the main underlying factors of eating competence. In conclusion, this preliminary study suggests eating competence could be a useful concept to characterize eating patterns and related behaviors and attitudes in adolescents. However, these preliminary findings need to be confirmed in further studies with an instrument fully validated for this age group.

Background: Type 2 diabetes can be prevented through lifestyle changes, but sustainable and scalable lifestyle interventions are still lacking. Habit-based approaches offer an opportunity to induce long-term behavior changes. Objective: The purposes of this study were to describe an internet-based lifestyle intervention for people at risk for type 2 diabetes targeted to support formation of healthy habits and explore its user engagement during the first 6 months of a randomized controlled trial (RCT). Methods: The app provides an online store that offers more than 400 simple and contextualized habit-forming behavioral suggestions triggered by daily life activities. Users can browse, inspect, and select them; report their performances; and reflect on their own activities. Users can also get reminders, information on other users’ activities, and information on the prevention of type 2 diabetes. An unblended parallel RCT was carried out to evaluate the effectiveness of the app in comparison with routine care. User engagement is reported for the first 6 months of the trial based on the use log data of the participants, who were 18- to 70-year-old community-dwelling adults at an increased risk of type 2 diabetes. Results: Of 3271 participants recruited online, 2909 were eligible to participate in the RCT. Participants were randomized using a computerized randomization system to the control group (n=971), internet-based intervention (digital, n=967), and internet-based intervention with face-to-face group coaching (F2F+digital, n=971). Mean age of control group participants was 55.0 years, digital group 55.2 years, and F2F+digital 55.2 years. The majority of participants were female, 81.1% (787/971) in the control group, 78.3% (757/967) in the digital group, and 80.7% (784/971) in the F2F+digital group. Of the participants allocated to the digital and F2F+digital groups, 99.53% (1929/1938) logged in to the app at least once, 98.55% (1901/1938) selected at least one habit, and 95.13% (1835/1938) reported at least one habit performance. The app was mostly used on a weekly basis. During the first 6 months, the number of active users on a weekly level varied from 93.05% (1795/1929) on week 1 to 51.79% (999/1929) on week 26. The daily use activity was not as high. The digital and F2F+digital groups used the app on a median of 23.0 and 24.5 days and for 79.4 and 85.1 minutes total duration, respectively. A total of 1,089,555 habit performances were reported during the first 6 months. There were no significant differences in the use metrics between the groups with regard to cumulative use metrics. Conclusions: Results demonstrate that internet-based lifestyle interventions can be delivered to large groups including community-dwelling middle-aged and older adults, many with limited experience in digital app use, without additional user training. This intermediate analysis of use behavior showed relatively good engagement, with the percentage of active weekly users remaining over 50% at 6 months. However, we do not yet know if the weekly engagement was enough to change the lifestyles of the participants. Trial Registration: ClinicalTrials.gov NCT03156478; https://clinicaltrials.gov/ct2/show/NCT03156478

Redesigning choice environments appears a promising approach to encourage healthier eating and physical activity, but little evidence exists of the feasibility of this approach in real-world settings. The aim of this paper is to portray the implementation and feasibility assessment of a 12-month mixed-methods intervention study, StopDia at Work, targeting the environment of 53 diverse worksites. The intervention was conducted within a type 2 diabetes prevention study, StopDia. We assessed feasibility through the fidelity, facilitators and barriers, and maintenance of implementation, building on implementer interviews (n = 61 informants) and observations of the worksites at six (t1) and twelve months (t2). We analysed quantitative data with Kruskall–Wallis and Mann–Whitney U tests and qualitative data with content analysis. Intervention sites altogether implemented 23 various choice architectural strategies (median 3, range 0–14 strategies/site), employing 21 behaviour change mechanisms. Quantitative analysis found implementation was successful in 66%, imperfect in 25%, and failed in 9% of evaluated cases. These ratings were independent of the ease of implementation of applied strategies and reminders that implementers received. Researchers’ assistance in intervention launch (p = 0.02) and direct contact to intervention sites (p < 0.001) predicted higher fidelity at t1, but not at t2. Qualitative content analysis identified facilitators and barriers related to the organisation, intervention, worksite environment, implementer, and user. Contributors of successful implementation included apt implementers, sufficient implementer training, careful planning, integration into worksite values and activities, and management support. After the study, 49% of the worksites intended to maintain the implementation in some form. Overall, the choice architecture approach seems suitable for workplace health promotion, but a range of practicalities warrant consideration while designing real-world implementation.