Associations between DSM-IV mental disorders and diabetes mellitus: a role for impulse control disorders and depression.
Peter de Jonge, Jordi Alonso, Dan J Stein...
https://pubmed.ncbi.nlm.nih.gov/24488082Actively Recruiting
Age: 18Years - 80Years
All Genders
ID07212075
Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups
Led by Forschungsinstitut der Diabetes Akademie Mergentheim · Updated on 2025-12-04
1809
Participants Needed
3
Research Sites
17 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are investigating mental health conditions such as distress, depression, anxiety, and eating disorders in people with diabetes. This study aims to use a personalized approach called precision mental health to identify subgroups of people with diabetes who share common patterns in the relationships between glucose levels and psychosocial factors. The goal is to develop a digital twin, a virtual model that can simulate and predict the course of mental health and blood sugar control to help guide more tailored diabetes care. Participants include over 1,800 people with type 1, type 2, or other specific types of diabetes. They continuously complete ecological momentary assessments (EMA), which involve daily surveys about stress, mood, and diabetes distress, along with questionnaires every six months. Glucose levels are measured using continuous glucose monitoring (CGM) devices, and clinical interviews diagnose mental health disorders. Data on medication, complications, diet, physical activity, and metabolic measures like HbA1c are also collected to build comprehensive profiles. During the study, participants undergo repeated assessments every six months over a two-year period, including EMA, questionnaires, CGM data collection, and diagnostic interviews in a subset. Researchers analyze the complex interactions between metabolic, behavioral, and psychological data using machine learning to identify subgroups and validate the digital twin's predictions. The main outcomes measured include the incidence and remission of mental disorders, diabetes distress, and glycemic control. This observational study will provide insights to support personalized mental health care in diabetes.
CONDITIONS
Brief Title
Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups
Who Can Participate
Age: 18Years - 80Years
All Genders
Eligibility Criteria
You may qualify if you...
- 18 to 80 years of age
- Diagnosis of type 1 diabetes, type 2 diabetes, or another specific type of diabetes
- Diabetes duration of at least 1 year
- Sufficient German language skills
- Ability to provide informed consent
You will not qualify if you...
- Inability to provide consent
- Significant cognitive impairment such as dementia
- Severe medical conditions impacting participation or confounding results, including treated cancer, advanced heart disease (NYHA III or higher), schizophrenia, or other psychotic disorders
- Terminal illness
- Being bedridden
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person or online)
Monitoring
Duration - Up to 5 years
Participants undergo repeated assessments of mental health and metabolic data including clinical interviews, continuous glucose monitoring (CGM), ecological momentary assessment (EMA), and online surveys every 6 months.
Every 6 months for clinical interviews and online surveys; 14-day EMA periods every 6 months; continuous glucose monitoring data collected every 6 months
Long-term Monitoring
Duration - Up to 5 years
Participants are observed over the long term to track the progression and incidence of mental health disorders and diabetes-related outcomes, contributing data for the development and validation of a digital twin model.
Follow-up assessments every 6 months including clinical interviews in a subsample, EMA, CGM, and questionnaires
Trial Site Locations
Total: 3 locations
1
Diabetes Clinic Mergentheim (DCM)
Bad Mergentheim, Baden-Wurttemberg, Germany, 97980
Actively Recruiting
2
MVZ Diabetespraxis Mergentheim
Bad Mergentheim, Baden-Wurttemberg, Germany, 97980
Completed
3
MVZ DiaMedicum Würzburg
Würzburg, Baden-Wurttemberg, Germany, 97072
Completed
Loading map...
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
1
Similar Trials
Frequently Asked Questions
Have more questions? Get in touch with our team for quick support
Not the Right Trial for You?
Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.
Already have an account? Log in here
Published Research Related To This Trial
The role of mental disorders in precision medicine for diabetes: a narrative review.
Sanne H M Kremers, Sarah H Wild, Petra J M Elders...
https://pubmed.ncbi.nlm.nih.gov/35729420Constructs of depression and distress in diabetes: time for an appraisal.
Frank J Snoek, Marijke A Bremmer, Norbert Hermanns
https://pubmed.ncbi.nlm.nih.gov/25995123Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).
Wendy K Chung, Karel Erion, Jose C Florez...
https://pubmed.ncbi.nlm.nih.gov/32556613Coordination of glucose monitoring, self-care behaviour and mental health: achieving precision monitoring in diabetes.
Norbert Hermanns, Dominic Ehrmann, Amit Shapira...
https://pubmed.ncbi.nlm.nih.gov/35380233Associations of Time in Range and Other Continuous Glucose Monitoring-Derived Metrics With Well-Being and Patient-Reported Outcomes: Overview and Trends.
Dominic Ehrmann, Lilli Priesterroth, Andreas Schmitt...
https://pubmed.ncbi.nlm.nih.gov/34149255Time With Diabetes Distress and Glycemia-Specific Distress: New Patient-Reported Outcome Measures for the Psychosocial Burden of Diabetes Using Ecological Momentary Assessment in an Observational Study.
Dominic Ehrmann, Andreas Schmitt, Lilli Priesterroth...
https://pubmed.ncbi.nlm.nih.gov/35613338Perceived glucose levels matter more than CGM-based data in predicting diabetes distress in type 1 or type 2 diabetes: a precision mental health approach using n-of-1 analyses.
Dominic Ehrmann, Norbert Hermanns, Andreas Schmitt...
https://pubmed.ncbi.nlm.nih.gov/39078490Digital Twins in Type 1 Diabetes: A Systematic Review.
Giacomo Cappon, Andrea Facchinetti
https://pubmed.ncbi.nlm.nih.gov/38887022Digital twins and artificial intelligence in metabolic disease research.
Clara Mosquera-Lopez, Peter G Jacobs
https://pubmed.ncbi.nlm.nih.gov/38744606