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Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

3 clinical studies listed.

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Depressed Mood

Tundra lists 3 Depressed Mood clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

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NOT YET RECRUITING

NCT07314957

Impact of Lifestyle on Health Maintenance: A Randomized Controlled Trial

This study aims to evaluate the impact of public health interventions on changes in healthy lifestyle habits over time and their subsequent effects on health outcomes. The investigators hypothesize that exposing at-risk populations to structured physical activity programs, education on healthy nutrition, promotion of the Mediterranean diet, and workshops focused on strengthening psychological resilience will lead to improvements in anthropometric, oxidative, metabolic, and psychological parameters. Anthropometric and laboratory measures will be collected at multiple time points throughout the study. The longitudinal follow-up will span 12 months. It is anticipated that sustained adherence to healthy lifestyle behaviors will result in positive lifestyle changes and enhanced health-related quality of life.

Gender: All

Ages: 20 Years - Any

Updated: 2026-02-12

Metabolic Syndrome
Inactivity/Low Levels of Exercise
Unhealthy Diet
+8
RECRUITING

NCT07212075

Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups

Mental conditions and disorders (e.g. distress, depressive, anxiety, and eating disorders) are more prevalent in people with diabetes (PWD) and associated with reduced quality of life and impaired glycaemic outcomes. Evidence supports a complex network between psychosocial factors and glycaemic control that can be highly variable between persons. It is assumed that subgroups exist that show different trajectories of glycaemia and mental health. Belonging to a particular subgroup may be linked with a higher risk of developing mental health problems compared to others. This suggests that it is possible to treat individuals in different subgroups in a manner that optimizes their treatment and can improve health outcomes. Accurate characterisation can inform more individualized care. This calls for a more personalised approach considering the idiosyncrasies of different subgroups. Over 3 years, the investigators have established the basis of a precision mental health approach for diabetes using n-of-1 analyses. By utilizing combined ecological momentary assessment (EMA: repeated daily sampling of psychosocial factors in everyday life) and continuous glucose monitoring (CGM), intensive longitudinal data per person could be collected. This enables the analysis of individual associations between glycaemic parameters and psychosocial variables and identification of individual sources of diabetes distress in each person. The objective of the present study is to use of the n-of-1 approach to identify subgroups of PWD who share common characteristics in the associations between glucose and psychosocial variables. The identified subgroups shall be used to develop a digital twin for precision mental health in diabetes. The digital twin serves as representation of a real person, allowing to make simulations and predictions of the course of mental health and glycaemia. These predictions can inform diabetes care and lead to more precise, personalised treatment decisions. To achieve this, a longitudinal panel including over 1,400 PWD who continuously complete EMA and questionnaire surveys and measure glucose levels using CGM was developed. Over 1000 clinical interviews to diagnose mental disorders have been conducted to identify major mental health conditions and map mental outcomes. To identify subgroups and develop the digital twin, the sampling will be expanded aiming at a total of 1,809 PWD. Incidence and remission of mental disorders will be determined via repeated interviews. The complex networks between clinical, metabolic, and psychosocial data will be analysed using machine learning, leading to new insights with the potential to shape future guidelines. These results will be used by the digital twin to predict courses of glycaemic control and mental health, translating the individual evidence into direct treatment suggestions.

Gender: All

Ages: 18 Years - 80 Years

Updated: 2025-12-04

1 state

Diabetes (DM)
Diabete Mellitus
Diabete Type 1
+17
NOT YET RECRUITING

NCT07211984

Evaluation of Dalia Solution For Depressed Patient

The goal of this superiority clinical investigation, prospective, multicenter, controlled, randomized, open-label is to evaluate the clinical impact of the Dalia medical telemonitoring device on the management of depressive patients. The main question it aims to answer is: the percentage of patients with clinically significant improvement at 3 months. A clinically significant improvement is defined as a decrease of at least 5 points from the initial PHQ-9 score AND/OR a PHQ-9 score lower than 15. The threshold of 5 points is the Minimal Clinically Important Difference (MCID) of the PHQ-9 scale

Gender: All

Ages: 18 Years - 76 Years

Updated: 2025-10-08

Depression Chronic
Depressed
Depressed Mood
+2