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Psychologisches Institut Professur "Prävention und Mental Health"

Themen für Masterarbeiten

  • Informationen zur Masterarbeit
    Master's Thesis at the Chair
    In supervising master's theses, we place great importance on close and effective collaboration with students. Mutual commitment, reliability, and dedication are essential for satisfactory and effective supervision. Dedicated and reliable students can expect close and constructive support.
    If you are interested in one of the topics listed below, please contact the relevant person. In addition to a brief CV, please include a one-page letter of motivation with your application for a master's thesis, explaining why you are applying for the research project.

    Masterarbeit am Lehrstuhl
    In der Betreuung von Masterarbeiten ist uns eine gute und enge Zusammenarbeit mit den Studierenden sehr wichtig. Voraussetzung für eine befriedigende und effektive Betreuung ist wechselseitige Verbindlichkeit, Verlässlichkeit und Engagement. Engagierte und zuverlässige Studierende können mit einer engen und konstruktiven Betreuung rechnen. Bei Interesse an einem der unten aufgeführten Themen wenden Sie sich bitte an die entsprechende Kontaktperson. Bitte fügen Sie Ihrer Bewerbung für eine Masterarbeit neben einem kurzen Lebenslauf auch ein ca. einseitiges Motivationsschreiben bei, in welchem Sie erklären, warum Sie sich für das Forschungsprojekt bewerben
    Betreuungsperson der Masterarbeit: Prof. Dr. Jennifer Belus

Übersicht der Masterarbeitsthemen dieser Professur

Durch Klick auf die einzelnen Themen werden die Detail-Informationen angezeigt.

 

offen:

  • Who responds to treatment interventions for harmful alcohol use in Lesotho?

    Beschreibung: Brief psychological interventions for harmful alcohol use show promise in low- and middle-income countries (LMICs), yet relatively little is known about which individuals benefit most from different delivery modalities. The World Health Organization?s (WHO) Mental Health Gap Action Program (mhGAP) for substance use disorder is a widely-validated and brief psychological intervention developed for use by lay providers in LMICs. Using data from a randomized clinical trial in Lesotho comparing in-person mhGAP delivery and text message-based delivery, this study will examine sociodemographic predictors of treatment response and non-response within each experimental condition.
    - Proficiency in quantitative data analysis using R
    - Familiarity with clinical trial data structures and intent-to-treat frameworks
    - Experience with or willingness to learn regression modeling
    - Interest in global mental health and implementation science in low-resource settings

    Kontakt: Dr. Arran James Davis, E-Mail

    Status: offen (erfasst / geändert: 22.06.2026)

  • Is loneliness increasing in Europe?

    Beschreibung: Loneliness is a major predictor of poor mental health outcomes, with politicians and academics describing a recent ?epidemic of loneliness?. Using the European Social Survey dataset, this study will explore temporal trends in loneliness and social connection in Europe over the past 25 years. Analyses will shed light on whether loneliness is indeed increasing in Europe, with a focus on how trends may be driven by specific sub-groups, such as young people or the socioeconomically disadvantaged.
    - Proficiency in quantitative data analysis using R
    - Familiarity large-scale longitudinal survey methodology
    - Experience with or willingness to learn multilevel regression modelling
    - Interest in epidemiological approaches to mental health research

    Kontakt: Dr. Arran James Davis, E-Mail

    Status: offen (erfasst / geändert: 10.06.2026)

  • How do social connection and loneliness relate to mental health and wellbeing among young people across cultural contexts?

    Beschreibung: Social connection is a fundamental determinant of mental health, yet most research on youth social connection has been conducted in high-income, Western contexts. Using an existing cross-national or multi-site dataset (e.g., the WHO World Mental Health Surveys, or multi-country adolescent wellbeing datasets such as the Health Behaviour in School-aged Children study), this research will examine how indicators of social connection and loneliness relate to mental health and wellbeing outcomes among young people, and whether these associations vary across cultural and socioeconomic contexts.
    - Proficiency in quantitative data analysis using R
    - Familiarity with cross-national survey data and issues of measurement equivalence
    - Experience with or willingness to learn multilevel regression modelling
    - Interest in youth mental health, social determinants of wellbeing, and cross-cultural research

    Kontakt: Dr. Arran James Davis, E-Mail

    Status: offen (erfasst / geändert: 10.06.2026)

 

vergeben:

  • What predicts participant retention and loss to follow-up in a randomized controlled trial of mental health intervention in Lesotho?

    Beschreibung: Participant retention is a is a critical methodological and equity challenge in clinical trials conducted in low- and middle-income countries (LMICs), yet the factors that predict dropout and loss to follow-up remain poorly understood in these contexts. This research will work with process outcome data from the Leseli research program, including interventionist notes documenting contact attempts, missed visits, and reasons for non-participation. The researcher will first clean and code these data to distinguish between voluntary dropout and loss to follow-up, before examining the sociodemographic predictors of each. A mixed-methods approach may be adopted. This would include brief, descriptive quantitative accounts of the sociodemographic factors associated with retention outcomes. It would also include qualitative analysis of process notes will illuminate the contextual factors ? including labor migration, cross-border work, housing instability, and limited mobile phone access ? that shape participants' ability to remain engaged over time. - Some experience in quantitative data analysis using R (desirable, but not necessary) - Comfort with data cleaning and working with messy, real-world process data - Familiarity with or willingness to learn basic qualitative coding and thematic analysis - Interest in implementation science, trial methodology, and the structural determinants of research participation in low-resource setting
    Anzahl Arbeiten für dieses Thema: 1
    Zeitrahmen: ab sofort
    Eingabedatum: 10.06.2026
    Kontakt: Dr. Arran James Davis, E-Mail

    Status: vergeben (erfasst / geändert: 22.06.2026)