[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"depressed-mood\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:depressed-mood":30},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,43,76,119,173],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":18,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":23,"briefSummary":25,"conditions":26,"keywords":31,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":38,"leadSponsor":40,"locationsCount":4},"100645046","digital-insomnia-and-circadian-therapy-for-reducing-depression-symptoms-in-college-students-100645046",false,"NCT07677930","Digital Insomnia and Circadian Therapy for Reducing Depression Symptoms in College Students","Prevent Worsening of Depressive Symptoms Using Digital Cognitive Behavioral Therapy for Insomnia and Circadian Intervention in College Students","Inclusion Criteria:\n\n* Youths aged between 18-24 years old.\n* Insomnia disorders as determined by DSM-5 criteria with a predominant complaint of difficulty initiating sleep.\n* Presence of an evening chronotype according to the score on the Horne-Östberg Morning-Eveningness Questionnaire (MEQ) and having a late bedtime of 12:00 am\u002Fmidnight or later for at least 3 nights per week in the last 3 months.\n* Presented with at least subclinical depressive symptoms as determined by Patient Health Questionnaire-9 ≥ 10.\n* Accessibility to a smartphone.\n\nExclusion Criteria:\n\n* Having a diagnosed sleep disorder that may potentially contribute to the disruption of sleep quantity and quality other than insomnia and delayed sleep phase syndrome, as ascertained by Structured Diagnostic Interview for Sleep patterns and Disorders (DISP), such as restless leg syndrome and OSA, and narcolepsy.\n* Diagnosed with neuropsychiatric disorders such as major depressive disorder, anxiety disorders, bipolar affective disorders, schizophrenia, moderate or above suicidality.\n* Concurrent, regular use of medications known to affect sleep continuity and quality, including both Western medications (e.g. hypnotics, steroids, antidepressants, antihistamines) and over-the-counter medications (e.g. melatonin).\n* Participate in other psychotherapy (e.g., CBT, mindfulness) currently or in the past three months.","ALL","18 Years","24 Years",{"count":20,"type":21},195,"ESTIMATED","INTERVENTIONAL",[24],"NA","Depression is a leading cause of global disease burden, poor quality of life, disability and suicide, and commonly occurs in adolescence and early adulthood. Insomnia and circadian factors were regarded as potential targets for preventing worsening of depressive symptoms. Additionally, digital insomnia treatment reduces depressive symptoms but is insufficient for individuals with an evening chronotype. Circadian intervention is an adjunctive treatment for sleep disturbance and depression, but is often overlooked. In this study, we aim to evaluate the effect of guided digital insomnia and circadian intervention (dCBT-I + dCI) in reducing depressive symptoms in college students with insomnia and an evening chronotype compared with digital insomnia intervention alone (dCBT-I) and a health education group (dHE). We also aim to develop and evaluate multimodal prediction models to identify individuals who are more or less likely to respond to the interventions, using clinical, behavioral, circadian, and digital engagement data.",[27,28,29,30],"Eveningness","Insomnia","Circadian Rhythm","Depressed Mood",[27,28,30,29],"NOT_YET_RECRUITING","2026-06-29",{"date":35,"type":36},"2026-07-01","ACTUAL",{"date":35,"type":21},{"date":39,"type":21},"2029-06-30",{"name":41,"class":42},"Chinese University of Hong Kong","OTHER",{"id":44,"slug":45,"hasResults":11,"nctId":46,"briefTitle":47,"officialTitle":47,"acronym":48,"eligibilityCriteria":49,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":50,"targetDuration":52,"studyType":53,"phases":4,"briefSummary":54,"conditions":55,"keywords":56,"overallStatus":65,"whyStopped":4,"lastUpdateSubmitDate":66,"lastUpdatePostDateStruct":67,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":75},"100633540","atlas-1-advanced-trial-for-longitudinal-assessment-in-salma-1-100633540","NCT07528014","ATLAS-1: Advanced Trial for Longitudinal Assessment in Salma 1","ATLAS-1","Inclusion Criteria:\n\n* Adults (≥18 years) of any gender identity presenting for care with a depressed mood.\n* Prescribed treatment with esketamine, conventional TMS, or SAINT as part of standard clinical care.\n* Able to provide informed consent and comply with all study requirements.\n\nExclusion Criteria:\n\n* Any condition deemed by the investigator to preclude safe participation in study assessments.",{"count":51,"type":21},5000,"12 Months","OBSERVATIONAL","This study will evaluate the feasibility and clinical utility of developing predictive models of treatment response for patients with depressed mood using multimodal clinical data collected in real-world clinical settings. The study will examine outcomes among patients treated with interventions including esketamine, conventional transcranial magnetic stimulation (TMS), or Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT). Retrospective clinical and research data from existing databases may also be incorporated, when available and authorized, to support model development and validation. The goal is to assess whether integrated clinical datasets can be used to support the development of predictive tools that may inform personalized treatment selection in depression.",[30],[57,58,59,60,61,62,63,64],"Depression","transcranial magnetic stimulation (TMS)","accelerated TMS","SAINT","Spravato","esketamine","Treatment-resistant depression (TRD)","Major depressive disorder (MDD)","RECRUITING","2026-04-07",{"date":68,"type":36},"2026-04-14",{"date":70,"type":36},"2026-03-25",{"date":72,"type":21},"2037-03",{"name":74,"class":42},"Salma Health, Inc.",2,{"id":77,"slug":78,"hasResults":11,"nctId":79,"briefTitle":80,"officialTitle":81,"acronym":82,"eligibilityCriteria":83,"healthyVolunteers":84,"sex":16,"minAge":85,"maxAge":4,"enrollmentInfo":86,"targetDuration":4,"studyType":22,"phases":88,"briefSummary":89,"conditions":90,"keywords":101,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":109,"lastUpdatePostDateStruct":110,"startDateStruct":112,"completionDateStruct":114,"leadSponsor":116,"locationsCount":118},"100617156","impact-of-lifestyle-on-health-maintenance-a-randomized-controlled-trial-100617156","NCT07314957","Impact of Lifestyle on Health Maintenance: A Randomized Controlled Trial","The Role of Lifestyle in Maintaining Health: Biological, Psychological and Social Responses of the Organism to Lifestyle","LifeHealth-RCT","Inclusion Criteria:\n\n* adults aged 20 years and older\n* overweight or obesity (BMI ≥25 kg\u002Fm²),\n* stable body weight over the past 6 months\n* physically inactive.\n\nExclusion Criteria:\n\n* HbA1c \\>12%\n* insulin therapy\n* severe psychiatry and severe chronic illnesses of parents\n* diseases of the hypothalamus and pituitary and adrenal gland\n* mobility restriction\n* tetraplegia\n* use of obesity pharmacotherapy\n* malignant disease and chemotherapy\n* pregnancy",true,"20 Years",{"count":87,"type":21},120,[24],"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.",[91,92,93,94,95,96,97,98,99,30,100],"Metabolic Syndrome","Inactivity\u002FLow Levels of Exercise","Unhealthy Diet","Unhealthy Alcohol Use","Smoking Behaviors","Stress","Sleep Disorder","Obesity & Overweight","Anxiety","Emotional Eating Behaviour",[102,103,104,105,96,106,107,108],"Habits","Lifestlye","Nutrition","Phisical activity","Metabolic syndrome","Mental health","Sleep","2026-02-09",{"date":111,"type":36},"2026-02-12",{"date":113,"type":21},"2026-09-01",{"date":115,"type":21},"2027-12-31",{"name":117,"class":42},"University of Zadar",1,{"id":120,"slug":121,"hasResults":11,"nctId":122,"briefTitle":123,"officialTitle":123,"acronym":124,"eligibilityCriteria":125,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":126,"enrollmentInfo":127,"targetDuration":4,"studyType":53,"phases":4,"briefSummary":129,"conditions":130,"keywords":150,"overallStatus":65,"whyStopped":4,"lastUpdateSubmitDate":164,"lastUpdatePostDateStruct":165,"startDateStruct":167,"completionDateStruct":169,"leadSponsor":170,"locationsCount":172},"100609246","precision-subclassification-of-mental-health-in-diabetes-digital-twins-for-precision-mental-health-to-track-subgroups-100609246","NCT07212075","Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups","TwinPeaks","Inclusion Criteria:\n\n* 18 to 80 years of age\n* Diagnosis of type 1 diabetes or type 2 diabetes or other specific type of diabetes\n* Diabetes duration ≥ 1 year\n* Sufficient German language skills\n* Informed consent\n\nExclusion Criteria:\n\n* Inability to consent\n* Significant cognitive impairment (e.g. dementia)\n* Severe disorder or condition impacting the person's ability to participate in the study or likely to confound results (e.g. treated cancer, heart disease ≥ NYHA III, schizophrenia\u002Fpsychotic disorder)\n* Terminal illness\n* Being bedridden","80 Years",{"count":128,"type":21},1809,"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.\n\nBelonging 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.\n\nOver 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.\n\nThe 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.\n\nTo 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.\n\nThe 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.",[131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,30,147,148,149],"Diabetes (DM)","Diabete Mellitus","Diabete Type 1","Diabete Type 2","Diabetes Distress","Diabetes Complications","Depression - Major Depressive Disorder","Depression Anxiety Disorder","Depression Bipolar","Depression Disorders","Anxiety Disorder (Panic Disorder or GAD)","Anxiety Disorder NOS","Eating Disorder Binge","Anorexia Nervosa","Bulimia Nervosa","Eating Disorder Not Otherwise Specified","Anxiety Symptoms","Disordered Eating Behaviors","Fear of Hypoglycemia",[151,152,153,154,155,156,157,158,159,160,161,162,57,99,163,135,124],"Digital Twin","Precision Medicine","Precision Mental Health","Subclassification","Trajectories","Subtypes","Person-reported Outcomes (PRO)","Ecological Momentary Assessment (EMA)","Continuous Glucose Monitoring (CGM)","People with Diabetes (PWD)","Diabetes Mellitus","HbA1c","Eating disorder","2025-11-27",{"date":166,"type":36},"2025-12-04",{"date":168,"type":36},"2025-01-01",{"date":115,"type":21},{"name":171,"class":42},"Forschungsinstitut der Diabetes Akademie Mergentheim",3,{"id":174,"slug":175,"hasResults":11,"nctId":176,"briefTitle":177,"officialTitle":178,"acronym":179,"eligibilityCriteria":180,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":181,"enrollmentInfo":182,"targetDuration":4,"studyType":22,"phases":184,"briefSummary":185,"conditions":186,"keywords":191,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":198,"lastUpdatePostDateStruct":199,"startDateStruct":201,"completionDateStruct":203,"leadSponsor":205,"locationsCount":118},"100609240","evaluation-of-dalia-solution-for-depressed-patient-100609240","NCT07211984","Evaluation of Dalia Solution For Depressed Patient","Evaluation of the Clinical and Organizational Impact of the Digital Medical Device Dalia in the Management of Depression","DaliaMonitorin","Inclusion Criteria:\n\n* Age ≥ 18 years\n* Patient with a diagnosis of depressive episode, as defined by ICD-11, and with a PHQ-9 score ≥ 15 confirmed by a psychiatrist or general practitioner\n* Patient receiving a first antidepressant treatment (treatment-naïve) OR having had a modification of antidepressant treatment in the two weeks prior to inclusion\n* Patient equipped with a smartphone or a computer or a tablet with internet access\n* Patient affiliated to a health insurance scheme\n* Patient able to read and understand French\n* Patient having signed informed consent\n\nExclusion Criteria:\n\n* Patient under non-cardioselective beta-blocker (carvedilol, labetalol, propranolol, pindolol) and beta-mimetic (salbutamol, terbutaline)\n* Patient with a pacemaker or with a known cardiac arrhythmia\n* Patient with major neurocognitive disorder (e.g., dementia) or psychotic disorders likely to compromise participation in the study\n* Patient hospitalized at the time of inclusion whose discharge is not planned within the next two weeks\n* Patient treated with esketamine\n* Patient with excessive consumption of psychoactive substances (alcohol or drugs), which may interfere with the course or follow-up of the study\n* Patient unable to wear the bracelet during the study due to dermatological conditions\n* Patient under guardianship, curatorship, or legal protection, or any other administrative or judicial measure depriving rights and freedom\n* Patient considered non-autonomous by the investigator\n* Patient already included in another interventional research study\n* Vulnerable persons referred to in Articles L.1121-5 to 8 and L.1122-1-2 of the French Public Health Code are excluded from the study","76 Years",{"count":183,"type":21},644,[24],"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\u002FOR a PHQ-9 score lower than 15. The threshold of 5 points is the Minimal Clinically Important Difference (MCID) of the PHQ-9 scale",[187,188,30,189,190],"Depression Chronic","Depressed","Depression and Quality of Life","Depression Diagnosis",[57,192,193,194,195,196,197],"PHQ-9","MADRS","Depressive episode","Anxiety disorder","Antidepressant prescriptions","Smartwatch","2025-10-01",{"date":200,"type":36},"2025-10-08",{"date":202,"type":21},"2025-10-10",{"date":204,"type":21},"2026-03-31",{"name":206,"class":207},"Dalia Care","INDUSTRY"]