Dissertationen

gloria.glessner@charlotte-fresenius-uni.de

Background: The experience of loneliness has been studied as an important transdiagnostic variable in different adverse mental health conditions. Since the COVID-19 pandemia at the latest, however, it has become clear that the experience of loneliness is not only common in the clinical but also the general population. Loneliness can also be considered a risk factor of psychological disorders. However, a distinction between state and trait loneliness is still lacking and the distinction between loneliness experienced in everyday life and the associated factors has not yet been sufficiently investigated. Therefore, the aim of our study was to examine loneliness from both a state and a trait perspective by using smartphone data from everyday life.

Methods: In this study, data (N= ∽360) from a smartphone study within the Coping with Corona (CoCo) project was used to investigate loneliness. Trait loneliness was collected, followed by a four-week survey period using the Experience Sampling Method (ESM), during which state levels of loneliness and affect were assessed daily at four random times via smartphone. At the same time, individual app-usage was continuously recorded via passive sensing. After 30 days of ESM and sensing, trait characteristics were measured again. We plan to investigate whether mean state loneliness over time is associated with surveyed trait loneliness, whether loneliness during the week predicts loneliness on weekends and to what extent state and trait loneliness are related to positive or negative affect and the use of certain apps. We plan to investigate our research questions using a multilevel vector autoregression approach.

Result: to be published

Discussion: Our study may provide more detailed insights regarding the interaction and experience of trait and state loneliness and associated factors. Using this as a basis, digital prevention and intervention approaches could be developed to reduce loneliness early on.

Keywords: loneliness, trait loneliness, state loneliness, smart sensing, experience sampling method

Institution: Ludwig-Maximilians-Universität München

Erstbetreuer: Prof. Dr. Markus Bühner, LMU München

Zweitbetreuerin: Prof. Dr. Nina Sarubin, Charlotte Fresenius Hochschule

patricia.garatva@charlotte-fresenius-uni.de

Previous research has demonstrated that emerging technologies, especially machine learning, can support in the diagnosis of mental disorders. However, a deeper understanding of these systems is crucial for improving their diagnostic performance and reliability. Consequently, the first part of this dissertation aims to provide a comprehensive and systematic overview of machine learning algorithms used in the diagnosis of depressive disorders, highlighting the machine learning characteristics and its diagnostic performance. Building on this, the second part of the dissertation involves training machine learning algorithms to predict depression, with a particular focus on the costs associated with misdiagnosis and the potential added value of integrating passive sensing data from devices such as smartphones and wearables. The final section of the dissertation will explore the acceptance of these diagnostic systems among healthcare professionals, assessing their practical applicability and potential integration into clinical practice.

Institution: Universität Ulm

Erstbetreuer: Prof. Dr. Harald Baumeister, Universität Ulm, Abt. Klinische Psychologie und Psychotherapie

Zweitbetreuerin: Prof. Dr. Nina Sarubin, Charlotte Fresenius Hochschule

milena.marx@charlotte-fresenius-uni.de

Erwachsene, die mit Kindern sprechen, tun dies auf eine spezifische Art und Weise. Die kindegerechte Sprache (IDS) ist gekennzeichnet durch eine höhere Stimmlage, eine höhere Variation in der Tonhöhe, linguistisch einfacherer Sprache und weitere Charakteristika (Cox et al., 2023). Säuglinge präferieren IDS nicht nur gegenüber der typischerweise an Erwachsene gerichteten Sprache, sie profitieren auch von ihrer Benutzung (ManyBabies Consortium, 2020). Besonders mit Blick auf die frühe Sprachenwicklung konnten bereits positive Assoziationen festgestellt werden.

Doch inwieweit wirkt sich IDS auch auf breitere kognitive Fähigkeiten und deren neuronale Korrelate aus? An bisherige Arbeiten anschließend sollen offene Fragestellungen in multimethodischen Studien beantwortet werden.

Studie 1 untersucht mithilfe von Eyetracking die Blickmuster und den Lernerfolg von Säuglingen und Kleinkindern für neue Gegenstände, die in IDS vorgestellt werden.

In Studie 2 wird der Effekt von IDS auf visuelle Verarbeitung und Kategorisierung in einem Fast Periodic Visual Stimulation (FPVS) EEG Paradigma untersucht.

Studie 3 nutzt ein weiteres EEG-Paradigma, um den Einfluss von IDS auf die visuelle Aufmerksamkeit zu analysieren.

Institution: Universität Heidelberg

Erstbetreuerin: Prof. Dr. Stefanie Peykarjou, Charlotte Fresenius Hochschule

birgit.probst@charlotte-fresenius-uni.de

While more and more people live in cities, urban life involves exposure to stressors that have been recognized as risk factors for physical and mental health. Research has also indicated positive effects of human-nature interaction on, e.g., psychological restoration, stress reduction, and general wellbeing. However, limited research has investigated links between wellbeing outcomes and greenspace characteristics, such as the biodiversity or structural complexity of a greenspace. Using an interdisciplinary approach at TU Munich, the dissertation investigates measures of greenspace characteristics as predictors for psychological restoration while taking into account potentially influencing variables such as nature perception and nature connectedness. Results could inform both nature-based health interventions and landscape planning in a changing climate, thereby supporting the wellbeing of residents.

Institution: Technische Universität München

Erstbetreuer: Prof. Dr. Michael Suda, Technische Universität München

Zweitbetreuerin: Prof. Dr. Monika Egerer, Technische Universität München

janika.saretzki@charlotte-fresenius-uni.de

Divergent thinking (DT) tests represent the dominant approach in the assessment of individual differences in the human creative cognitive potential. These DT tests (for example, find creative uses for everyday objects) do not have single correct solutions but rather many possible solutions that may differ in their creative quality (novelty and effectiveness). DT test have been used for more than 50 years, but there are still varied approaches on how to implement and score them, as well as persistent concerns regarding their psychometric quality. Therefore, this project will realize a systematic investigation of the optimal test conditions of these standard measures of creativity research. To this end, the project will 1) review the variety and validity evidence of available methods, 2) study specific promising advancements in more detail, and 3) directly compare novel and established methods. In sum, this will allow us to derive evidence-based recommendations for more valid DT assessments, aiming to support a more consistent and effective creativity research.

Institution: Institut für Psychologie der Karl-Franzens-Universität Graz

Erstbetreuer: Assoz. Prof. Mag. Rer. nat. Dr. phil. Mathias Benedek, Institut für Psychologie, Karl-Franzens-Universität Graz

jan-luca.tegethoff@charlotte-fresenius-uni.de

Personen mit chronischen Schmerzen haben ein deutlich erhöhtes Risiko für suizidales Erleben und Verhalten. Um Suizidgedanken frühzeitig zu erkennen und so womöglich den Übergang zu suizidalem Verhalten zu verhindern, müssen wir Suizidalität differenziert und unter Bezugnahme verschiedenster, auch personengruppen-spezifischer Einflussfaktoren verstehen. In Kooperation mit der Universität Duisburg-Essen werden Personen dieser Risikogruppe zweimal im Abstand von vier Wochen zu ihrem suizidalen Erleben und Verhalten, proximalen Risikofaktoren, potenziellen Schutzfaktoren und schmerzspezifischen Faktoren befragt. In einer zweiten Studie werden die als relevant identifizierten Faktoren mittels mehrtägiger Smartphone-basierter Befragungen mehrmals täglich erhoben. Ziel ist es, suizidales Erleben und Verhalten in dieser Risikogruppe alltagsnah und unter Berücksichtigung der individuellen zeitlichen Verläufe zu analysieren und Ansatzpunkte für die klinische Interventionsforschung zu ermitteln.

Institution: Universität Duisburg-Essen

Erstbetreuer: Prof. Dr. Thomas Forkmann, Universität Duisburg-Essen

Zweitbetreuerin: Prof. Dr. Inken Höller, Charlotte Fresenius Hochschule