Clinical trials

This study is a single-center micro-randomized trial, aiming to examine the effects of two theory-driven reminder strategies on adherence to repeated, image-based meal logging in adults age 45 and older. Three times daily, participants are automatically randomized to receive one of three reminder messages prior to each habitual mealtime. The main research questions the trial aims to answer are: * Do loss-framed reminders (emphasizing loss of a daily financial reward for not logging) increase meal logging adherence in the two hours following a reminder, compared to a neutral reminder? * Do logging consistency reminders (providing feedback on recent logging streaks) increase meal logging adherence in the two hours following a reminder, compared to a neutral reminder? * Do the effects of loss-framed and logging consistency reminders differ from each other? Primary aim: To estimate the proximal effect of each reminder type on whether a participant logs a meal within two hours of receiving a reminder. Secondary aim: To examine whether within-person physiological patterns (e.g., heart rate variation) moderate response to reminders, with the goal of identifying physiological markers of receptivity to behavioral prompts. The trial aims to enroll 200 adults aged 45 and older. Participants attend a baseline visit for onboarding, consent, and device setup, followed by a 28 day remote intervention period during which they should photograph their meals three times daily (breakfast, lunch, dinner) and wear a smartwatch and smart ring continuously. Prior to each mealtime, they receive an automatically randomized reminder message. Participants earn a daily financial reward contingent on completing meal logging for that day. Note: This trial was registered retrospectively as enrollment began prior to registration. However, registration was completed before data collection was finished and before any data analysis was conducted.

The GLOW UP study is a single-center, prospective, observational case-control study conducted in St. Gallen, Switzerland. The primary aim of the study is to examine to what degree lifestyle data collected from wearable devices and a smartphone app can identify individuals with prediabetes (vs. normoglycemic) in a real-world setting. The study also aims to characterize variability in lifestyle and glycemic patterns and to examine how between- and within-person differences relate to diabetes risk; to identify personalized predictors of early metabolic dysregulation. The study also evaluates new image-based meal tracking algorithms for predicting glycemic control and examines how reminder messages influence adherence to a \~4-week meal logging protocol. The study aims to enroll 200 adults aged 45 years and older with a BMI of at least 25 kg/m² and no known diagnosis of diabetes, including 100 participants with prediabetes and 100 normoglycemic (metabolically healthy) controls. Participants will be classified at the baseline visit using HbA1c and fasting plasma glucose (FPG) tests, with prediabetes defined as HbA1c 5.7-6.4% and/or FPG 5.6-6.9 mmol/L, and normoglycemia defined as HbA1c \<5.7% and FPG \<5.6 mmol/L, following clinical standards. During the \~4-week observational period, participants will be asked to wear a smart ring, a wrist-worn smartwatch, and a blinded continuous glucose monitor (CGM). Participants will be asked to log/take-images of their meals via a study app and to complete brief questionnaires (e.g., tracking mood, stress, and contextual meal annotations) via ecological momentary assessments. FPG and HbA1c samples will be collected at baseline to classify participants as prediabetic or normoglycemic, and again at follow-up (\~4 weeks), which will serve as the primary outcome to evaluate associations between lifestyle and wearable-derived data and diabetes risk status.

The DietCoach study aims to investigate the requirements of a digital dietary counseling platform, and evaluate the dietitian acceptance and usability of the DietCoach platform, which was developed based on the collected requirements. Additionally, the study examines how different levels of patient food purchase data availability affect these factors. The DietCoach platform automatically tracks historic and up-to-date patient food purchase data on loyalty cards and provides nutritional analysis, assisting dietitians in the dietary counseling process. The key research questions (RQ) are: 1. What are the requirements of a digital dietary counseling system based on food purchase data? 2. What is acceptance and usability of the DietCoach platform evaluated by dietitians? 3. How does the availability of patient food purchase data influence the acceptance and perceived usability of the DietCoach platform by dietitians? Dietitians from several cantonal hospitals in the German-speaking area of Switzerland are invited to participate in the study. To answer RQ1, we conduct a workshop and a survey with dietitians to derive key requirements on dietary counseling systems. To answer RQ2 and RQ3, we use a cross-sectional, mixed-methods, between-subjects study design. Researchers will evaluate and compare the acceptance and usability of DietCoach in 3 different conditions (3 patients that had different, i.e., high, medium and low, food purchase data availability). Each participant is assigned to the data of one patient. Participants are required to: 1. use the DietCoach platform to provide at least one dietary recommendation to patient food purchase data in two separate sessions. 2. provide quantitative and qualitative feedback about the acceptance and usability of the DietCoach platform.