Digitally supported program for type 2 diabetes risk identification and risk reduction in real-world setting: Protocol for the StopDia model and randomized controlled trial

Jussi Pihlajamäki (Corresponding Author), Reija Männikkö, Tanja Tilles-Tirkkonen, Leila Karhunen, Marjukka Kolehmainen, Ursula Schwab, Niina Lintu, Jussi Paananen, Riia Järvenpää, Marja Harjumaa, Janne Martikainen, Johanna Kohl, Kaisa Poutanen, Miikka Ermes, Pilvikki Absetz, Jaana Lindström, Timo A. Lakka

    Research output: Contribution to journalArticleScientificpeer-review

    22 Citations (Scopus)


    Background: 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. Methods: 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. Discussion: 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. Trial registration: Identifier: NCT03156478. Date of registration 17.5.2017.

    Original languageEnglish
    Article number255
    Number of pages13
    JournalBMC Public Health
    Publication statusPublished - 1 Mar 2019
    MoE publication typeA1 Journal article-refereed


    STOP DIABETES - from knowledge to solutions project is funded by the Strategic Research Council at the Academy of Finland ( about-us/SRC/) in 2016–2019 (303537).


    • Digital health behavior change intervention
    • Effectiveness
    • Lifestyle intervention
    • Prevention
    • Randomized controlled trial
    • Scalability
    • Type 2 diabetes
    • Humans
    • Middle Aged
    • Male
    • Diabetes Mellitus, Type 2/economics
    • Young Adult
    • Healthy Lifestyle
    • Adult
    • Female
    • Surveys and Questionnaires
    • Health Promotion/economics
    • Risk Reduction Behavior
    • Mass Screening/economics
    • Primary Health Care/economics
    • Risk Assessment/economics
    • Randomized Controlled Trials as Topic
    • Cost-Benefit Analysis
    • Adolescent
    • Finland
    • Aged


    Dive into the research topics of 'Digitally supported program for type 2 diabetes risk identification and risk reduction in real-world setting: Protocol for the StopDia model and randomized controlled trial'. Together they form a unique fingerprint.

    Cite this