Projects

We are developing digital platforms for comprehensive mental health assessments in older adults. These tools use both passive and active data collection to evaluate emotional well-being, cognitive function, and behavioral changes, providing a more dynamic and ongoing assessment compared to traditional methods.

This project focuses on incorporating digital biomarkers into routine outcome monitoring systems. By tracking symptoms and responses to treatment in real-time, we aim to optimize therapeutic decisions and personalize treatment plans for older adults. Our biomarkers enable more sensitive detection of changes in emotional states, helping clinicians make timely interventions.

Ambulatory assessment allows for the continuous monitoring of psychological and psychopathological states in real-world environments. This project leverages voice, speech, wearable devices, and mobile applications to collect real-time data on mood, activity, and other symptoms of psychopathology, helping us understand the day-to-day fluctuations in emotional disorders among older adults.

In collaboration with researchers from Prof. Klöppel’s Group, we are investigating digital biomarkers that can detect early signs of cognitive impairments in older adults. These digital biomarkers have the potential to provide early warnings for conditions like mild cognitive impairment (MCI) and Alzheimer’s disease, allowing for timely interventions and potentially delaying the progression of these disorders.

This project investigates a step-wise treatment approach for emotional disorders in older adults by comparing three different intervention models: stand-alone digital interventions, blended care, and treatment as usual (TAU). The goal of this project is to evaluate the effectiveness of providing different treatment strategies based on initial severity.

1. Stand-Alone: Patients with subclinical or mild symptoms receive a low-intensity, self-guided digital intervention focused on CBT and emotional regulation techniques.
2. Blended: Patients with clinical symptoms receive treatment following a blended approach, where the number of inperson sessions is reduced and digital interventions supplement care.
3. Treatment as Usual (TAU): Patients with clinically relevant or severe symptoms receive treatment as usual with regular in-person sessions.

We will measure clinical outcomes such as symptom reduction, quality of life, and engagement levels to determine the most effective and scalable approach for treating emotional disorders in older adults. This project has the potential to optimize the integration of digital tools in clinical practice, offering a more flexible and resource-efficient method for managing mental health in older populations.