GPS-triggered e-diaries, neuroimaging and genetics to unravel urbanicity risks for schizophrenia
Recent evidence suggests that the heightened prevalence of mental disorders in cities is caused by altered neural stress processing. To uncover the specific environmental sources of urban stress, we use innovative GPS-triggered e-diaries. In detail, GPS-triggered e-diaries continuously monitor participants’ locations. Changes are traced in real time on environmental components maps, covering traffic noise, population density etc., and trigger e-diary queries for affect and stress-reactivity. Methodologically, GPS-triggered e-diaries maximize the within-subject variance in real-time. The study is part of an ongoing longitudinal study (PEZ: Psychiatric-epidemiological center) combining GPS-triggered e-diaries with fMRI and biomarkers. PEZ is headed by Prof. Meyer-Lindenberg (CIMH Mannheim, Germany) and supported by the Ministry of Science, Research and the Arts of the State of Baden-Württemberg.
Activity-triggered e-diaries to investigate the mood-brightening effect of physical activity in patients with Depression or Anorexia
|Although empirical studies evidence that structured exercise reduces depressive symptomatology, the underlying mechanisms are poorly understood. We use activity-triggered e-diaries pre and post a ten-week running program to investigate the within-subject dynamics between physical activity and mood in depressed students. In detail, physical activity is assessed and preprocessed on an accelerometer worn on the hip. Via Bluetooth low energy data are transmitted to a smartphone, triggering e-diary assessments if specified thresholds of activity or inactivity are surpassed. Methodologically, activity-triggered e-diaries maximize the within-subject variance in real-time. The study is run in cooperation with the Psychotherapeutic Counselling Centre, Karlsruhe. This methodological approach is also applied to investigate the relation between physical activity and mood in patients suffering from anorexia nervosa, a collaborative project headed by Prof. Zeeck (Medical Center at the University of Freiburg; funded by the Swiss Anorexia Nervosa Foundation).|
Long-term tracking of communication and behaviour to predict new episodes in bipolar disorder
Bipolar disorders are severe chronic illnesses marked by recurrent episodes of depression and (hypo-)mania. Prevention is essential since these episodes are associated with marked impairment in social and occupational functioning. We conduct a randomized, multi-center, observer-blind, parallel group controlled trial with an 18-month intervention phase to investigate whether early warning signs of new depressive or (hypo-)manic episodes and individual threshold-based early interventions will prolong time to a new mood episode. In details, we continuously assess telephone usage (phone calls, text messages and internet usage), movement behavior (steps, movement patterns and activity classes) as well as location (GPS-data) across 18 months. Individual symptom thresholds are defined during 4 consecutive weeks of stabilization. Patients with randomization criteria enter the intervention phase for 18 months. This includes real-time data capturing and data-driven individual symptom-threshold-defined therapeutic interventions in addition to state-of-the-art maintenance treatment.
High-frequency monitoring of affective dynamics to characterize borderline personality disorder and to predict its treatment outcome
|Psychopathology is not simply experiencing weird symptoms or more negative than positive affect. Such a static view would ignore the moment-to-moment ebb and flow of symptoms, which characterizes the disorders. In a current DFG funded study “Developing mixed-latent-state-trait-models to analyse the temporal characteristics of affect and self-esteem in borderline personality disorder” we do hypothesize that the dynamical covariation of affect and self-esteem is specific for BPD. As current statistical models are limited for this kind of analyses, we will expand ordinary mixed-latent-state-trait-models to multigroup-multitrait-mixed-autoregressive-latent-state-trait-growth-curve-models. This project is run in cooperation with Prof Michael Eid (FU Berlin) and Prof. Dr. Martin Bohus (Central Institute of Mental Health, Mannheim).|
Ambulatory Assessment Interventions: Reducing stress and procrastination with a smartphone app
The primary aim of every psychological intervention is to induce some kind of change in the behaviour of the participants. To bring about substantial behavioural change, principles and strategies taught to the participants have to be transferred to their every-day-life. Ambulatory Assessment techniques help to meet that challenge by prompting individuals to apply their skills, when and where they are needed, fostering engagement and adherence, while reducing the required frequency of face-to-face sessions. Therefore, we implemented two IT-based interventions using mobile devices (smartphones). Both of these Ambulatory Assessment Interventions facilitate self-monitoring processes using real-time suggestions and feedback. The first intervention is designed to (1) examine the time-dependent change-processes underlying the emergence of procrastination and (2) to reduce academic procrastination by strengthening students everyday self-regulation (funding: BMBF).
The second intervention is integrated in a stress prevention and -management program, where e-diaries are used to support students in critical situations (funding: Techniker Krankenkasse).
m-Health for monitoring and coaching chronobiology and physical activity in ADHD
To improve motivation for an exercise intervention and a bright light therapy, we developed an m-health system comprising treatment reminders and individualized feedback. In addition, the m-health system includes classical e-diary components, a treatment compliance monitoring and video clips for the exercise module. Technically, acceleration is sampled and processed on a wrist sensor. Using an energy efficient BLE connection, data are transmitted to a smartphone/server, processed in real time. Motivating feedback on performed activity is generated automatically and sent back to the participant´s smartphone. The study is part of the ongoing EU-funded project “Comorbid conditions of attention deficit hyperactive disorders” (CoCa) integrating epidemiological, genetic and experimental studies as well as clinical trials to study the comorbid conditions in ADHD.
For further information please have a look at the ‘MiND the gap’ blog which leads to interesting papers and current debates concerning ADHD, Aggression, Conduct Disorder, and Autism shared by the projects CoCA, Aggressotype and MiND.
An mHealth device to investigate impulsivity and compulsivity in interaction with physical activity and dietary patterns in mental disorders
To modify impulsive and compulsive disorders and behaviours, we investigate whether physical activity interacts with dietary patterns in everyday life. Therefore, we further develop the mHealth device that has been set up for the CoCA-project (see above). Particularly, we engineer an mHealth tool by implementing additional measures on impulsive and compulsive behaviours, food intake, physical activity and circadian rhythms. Furthermore, we combine subjective ratings of impulsivity with neurocognitive measures of impulsivity assessed with cognitive tasks at the smartphone. The study is part of the EU-funded project “Effects of Nutrition and Lifestyle on Impulsive, Compulsive, and Externalizing behaviors” (Eat2beNICE) integrating epidemiological, genetic and experimental studies and clinical trials to investigate the effect of dietary patterns on mental disorders. For further information, see the project’s website.