Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,809
- 试验地点
- 3
- 主要终点
- Incidence of affective disorders from baseline to follow-up (per structured diagnostic interview)
研究概览
简要总结
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.
详细描述
People with diabetes (PWD) have a higher risk of mental disorders: a systematic review showed the odds of 15 different mental disorders is significantly increased (1). A review indicated that mental health disorders can drive the incidence of diabetes and lead to a negative prognosis (2). Common mental health problems in diabetes include diabetes distress, depression, anxiety, and disordered eating (1,3).
The ADA/EASD's precision medicine consensus statement highlights mental health as "highly relevant" (4). Moreover, mental health data should be "combined with other data … to improve the precision of clinical decision making." A review by the investigators supports that precision mental health in diabetes can be achieved by combining glucose data with behavioral and mental data (5).
A precision medicine approach to mental health requires an in-depth exploration of mental health subgroups. This involves identifying distinct patterns and subgroups who show different courses of mental outcomes as well as understanding the contribution of glucose in relation to physio- and psychological factors. The interplay between mental health, CGM metrics, and behavioral factors is crucial for elucidating mental health trajectories and advancing personalised treatment strategies (5-7).
With the previous DIA-LINK and PRO-MENTAL studies, the investigators set the basis for a precision mental health approach. By combining CGM with ecological momentary assessment (EMA), a methodology allowing repeated daily assessments of mental variables, an innovative approach for precision mental health was established (7). In a recent study, this approach was used to identify individual drivers of diabetes distress using n-of-1 analyses (8). The study supports specific subgroups in which distress is differentially influenced either by the mental perceptions of glucose or the actual glucose values. It was also demonstrated that glycemic control and psychosocial well-being at follow-up were differentially influenced depending on the individual drivers of distress.
Digital twins are a valuable tool for identifying relevant subgroups of PWD who share similar courses of glucose and mental health. A digital twin represents a virtual model of an individual, integrating data from various sources, including CGM, electronic health records, EMA, behaviors, and sensors. A digital twin is ideal to study highly dynamic networks between metabolic, behavioral, and psychological factors (9-11). However, a recent systematic review highlights that although psychosocial factors play a role in glucose control, none of the reviewed digital twins incorporated such factors. The authors conclude that "addressing this deficiency opens new perspectives and opportunities for improving the holistic management of T1D through more comprehensive and inclusive modeling approaches" (9).
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •18 to 80 years of age
- •Diagnosis of type 1 diabetes or type 2 diabetes or other specific type of diabetes
- •Diabetes duration ≥ 1 year
- •Sufficient German language skills
- •Informed consent
排除标准
- •Inability to consent
- •Significant cognitive impairment (e.g. dementia)
- •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/psychotic disorder)
- •Terminal illness
- •Being bedridden
结局指标
主要结局
Incidence of affective disorders from baseline to follow-up (per structured diagnostic interview)
时间窗: Baseline, 2-year Follow-up
Diagnoses of affective disorders were assessed at baseline (as part of the PRO-MENTAL study) using the corresponding section of the Brief Diagnostic Interview for Mental Disorders (Mini-DIPS OA, improved version). The PRO-MENTAL cohort is followed up in the TwinPeaks study including a re-assessment of affective disorders using the Mini-DIPS OA at 2-year follow-up. Primary outcome is the 2-year incidence of affective disorders as per structured diagnostic interview.
Incidence of anxiety disorders from baseline to follow-up (per structured diagnostic interview)
时间窗: Baseline, 2-year Follow-up
Diagnoses of anxiety disorders were assessed at baseline (as part of the PRO-MENTAL study) using the corresponding section of the Brief Diagnostic Interview for Mental Disorders (Mini-DIPS OA, improved version). The PRO-MENTAL cohort is followed up in the TwinPeaks study including a re-assessment of anxiety disorders using the Mini-DIPS OA at 2-year follow-up. Primary outcome is the 2-year incidence of anxiety disorders as per structured diagnostic interview.
Incidence of eating disorders at from baseline to follow-up (per structured diagnostic interview)
时间窗: Baseline, 2-year Follow-up
Diagnoses of eating disorders were assessed at baseline (as part of the PRO-MENTAL study) using the corresponding section of the Brief Diagnostic Interview for Mental Disorders (Mini-DIPS OA, improved version). The PRO-MENTAL cohort is followed up in the TwinPeaks study including a re-assessment of eating disorders using the Mini-DIPS OA at 2-year follow-up. Primary outcome is the 2-year incidence of eating disorders as per structured diagnostic interview.
Depressive symptoms: Incidence at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Depressive symptoms are assessed with the Patient Health Questionnaire-9 (PHQ-9) at baseline, 12 months, and 24 months. PHQ-9 sum score range: 0 - 27; higher scores indicate higher depressive symptoms; scores of 10 and above are considered as elevated depressive symptoms. The incidence of depressive symptoms at 2-year follow-up compared to baseline (for persons without depressive symptoms at baseline) is a secondary outcome.
Depressive symptoms: Remission at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Depressive symptoms are assessed with the Patient Health Questionnaire-9 (PHQ-9) at baseline, 12 months, and 24 months. PHQ-9 sum score range: 0 - 27; higher scores indicate higher depressive symptoms; scores of 10 and above are considered as elevated depressive symptoms. The remission of depressive symptoms at 2-year follow-up compared to baseline (for persons with elevated depressive symptoms at baseline) is a secondary outcome.
Anxiety symptoms: Incidence at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Anxiety symptoms are assessed with the Generalized Anxiety Disorders-7 (GAD-7) Questionnaire at baseline, 12 months, and 24 months. GAD-7 sum score range: 0 - 21; higher scores indicate higher anxiety symptoms; scores of 10 and above are considered as elevated anxiety symptoms. The incidence of anxiety symptoms at 2-year follow-up compared to baseline (for persons without anxiety symptoms at baseline) is a secondary outcome.
Anxiety symptoms: Remission at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Anxiety symptoms are assessed with the Generalized Anxiety Disorders-7 (GAD-7) Questionnaire at baseline, 12 months, and 24 months. GAD-7 sum score range: 0 - 21; higher scores indicate higher anxiety symptoms; scores of 10 and above are considered as elevated anxiety symptoms. The remission of anxiety symptoms at 2-year follow-up compared to baseline (for persons with elevated anxiety symptoms at baseline) is a secondary outcome.
Disordered eating behaviour: Incidence at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Disordered eating behaviours are assessed with the Diabetes Eating Problems Survey-Revised (DEPS-R/DEPS-10) at baseline, 12 months, and 24 months. DEPS-R sum score range: 0 - 80; higher scores indicate more diabetes-related eating problems; scores of 20 and above are considered to indicate disordered eating. The incidence of disordered eating behaviours at 2-year follow-up compared to baseline (for persons without disordered eating at baseline) is a secondary outcome.
Disordered eating behaviour: Remission at 2-year Follow-up
时间窗: Baseline, 2-year Follow-up
Disordered eating behaviours are assessed with the Diabetes Eating Problems Survey-Revised (DEPS-R/DEPS-10) at baseline, 12 months, and 24 months. DEPS-R sum score range: 0 - 80; higher scores indicate more diabetes-related eating problems; scores of 20 and above are considered to indicate disordered eating. The remission of disordered eating behaviours at 2-year follow-up compared to baseline (for persons with disordered eating at baseline) is a secondary outcome.
General diabetes distress over time
时间窗: Baseline, 2-year Follow-Up
General diabetes distress is assessed with the Problem Areas in Diabetes Scale (PAID) at baseline, 6-month FU, 12-month FU, 18-month FU, and 24-month FU to detect changes in diabetes distress from baseline to 2-year FU. PAID total score range: 0 - 100; higher scores indicate higher diabetes distress; scores of 40 and above are considered to indicate elevated diabetes distress.
Daily diabetes distress over time
时间窗: Baseline, 2-year Follow-Up
Daily diabetes distress is assessed at baseline, 6-month FU, 12-month FU, 18-month FU, and 24-month FU over each 14 consecutive days using smartphone-based ecological momentary assessment with selected items from the Problem Areas in Diabetes Scale (PAID) adapted for daily assessment (rated on an 11-point scale from 0 - 10; higher values indicate higher mental burden) to detect changes in daily burdens from baseline to 24-month FU. A 10-item sum score ranges from 0 - 100 with higher values indicating higher daily distress.
Glycated hemoglobin (HbA1c) over time
时间窗: Baseline, 2-year Follow-up
HbA1c (glycated hemoglobin), a laboratory measure of average blood glucose over the past 8 to 12 weeks, is estimated/collected at baseline, 6-month FU, 12-month FU, 18-month FU, and 24-month FU from the participants to detect changes for glycated hemoglobin from baseline to 2-year FU.
Glycemic levels (CGM glucose) over time
时间窗: Baseline, 2-year Follow-Up
Automatically recorded daily glucose values are obtained from participants where continuous glucose monitoring (CGM) devices are used. Available glucose data are extracted at baseline, 6-month FU, 12-month FU, 18-month FU, and 24-month FU for each over 14 consecutive days of CGM measurement - parallel to the daily EMA - to detect changes in glucose levels from baseline to 2-year FU.
次要结局
- Wellbeing over time(Baseline, 2-year Follow-up)
- Subjective health state over time(Baseline, 2-year Follow-up)
- General sleep quality over time(Baseline, 2-year Follow-up)
- Daily sleep quality over time(Baseline, 2-year Follow-up)
- Fear of diabetes complications over time(Baseline, 2-year Follow-up)
- Diabetes self-management over time(Baseline, 2-year Follow-up)
研究者
Norbert Hermanns
Prof. Dr. / PhD
Forschungsinstitut der Diabetes Akademie Mergentheim