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Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

3 clinical studies listed.

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Depression and Anxiety Symptom

Tundra lists 3 Depression and Anxiety Symptom 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

NCT07415850

The Effect of a Four-Week Hatha Yoga Intervention to Improve Quality of Life, Anxiety, and Depressive Symptoms in Individuals Undergoing Assisted Reproductive Technology (ART) Treatment

The goal of this clinical trial is to learn if a four-week yoga program works to improve quality of life in people undergoing IVF (In Vitro Fertilization). It will also learn if a four-week yoga program decreases anxiety and depression symptoms in people undergoing IVF. The main questions it aims to answer are: * Does a four-week yoga program effect quality of life, anxiety, and depression symptoms in people undergoing IVF? * Do the effects vary by individual characteristics of the people in the study? Researchers will compare the yoga intervention group to routine care as usual. Participants will: * Participate in a weekly virtual yoga class for four weeks (total of four yoga classes), or follow routine care as usual while undergoing IVF. * Take three online surveys every 4 weeks. * Be involved in the study for 8 weeks.

Gender: FEMALE

Ages: 18 Years - Any

Updated: 2026-02-17

1 state

IVF
In Vitro Fertilization
Quality of Life (QOL)
+5
RECRUITING

NCT07391540

ICBT for Psychological Symptoms Related to Economy

This study aims to investigate the effects of guided internet-based cogitive behavioral therapy (ICBT) on psychological symptoms related to economy. In this pilot study, the investigators investigate participants' psychological symptoms before and after, and one and two years after, they have received eight weeks of therapist guided ICBT.

Gender: All

Ages: 18 Years - Any

Updated: 2026-02-06

1 state

Depression and Anxiety Symptom
RECRUITING

NCT06350201

Machine Learning-based Classification of Symptom Clusters and Online CBT

To breakthrough the bottleneck identified, we will conduct a cross-sectional study to develop a symptom clustering model for depression and anxiety. A wide range of statistical methods as well as machine learning approaches were explored, and a cohesive hierarchical clustering algorithm will be used. After developing the model, a symptom-matched intervention program based on problem solving therapy will be formulated. We are supposed to examine whether its use for personalizing symptom-matched psychological treatment can lead to improved patient outcomes, compared with usual care. This project is expected to provide a new and precise method for the emotion management, which will provide a standardized intervention pathway combining screening with treatment for the management of depression symptom and anxiety symptom. A preciser intervention matched to individual symptoms may provide important insight in improving patient outcome as well as a standardized mood management pathway targeting to the early detection and intervention for community residents.

Gender: All

Ages: 18 Years - 64 Years

Updated: 2026-01-08

Depression and Anxiety Symptom