PSY9401A ¨C Mental health and wellbeing

Course content

This course is a seminar for Ph.d. students in the fields of mental health and wellbeing, with meetings on a regular basis throughout the semester. The course focuses on research on causal processes in mental health and wellbeing, social inequality in mental health and wellbeing, and intervention, prevention, and mental health promotion. The course is designed to promote an interdisciplinary approach to mental health and wellbeing research, integrating psychological, epidemiological, genetic, neurocognitive, and sociological perspectives.

Topics will include:

• Interdisciplinary approaches to mental health including, but not limited to, psychological, genetic, neurodevelopmental, epidemiological, and sociological perspectives.
• The structure and nature of mental health problems and wellbeing.
• Developmental processes.
• Genetic and environmental factors.
• Neurocognitive perspectives.
• Social inequality and gradients in mental health/wellbeing.
• Interventions, prevention, and mental health promotion.
• Epidemiological approaches, modelling strategies, research designs and state-of-the art methodology.

The course is organized by the PROMENTA Research Center.

Learning outcome

Knowledge

Participants will:

• Increase their theoretical and empirical knowledge on mental health and wellbeing and the causal processes involved from an interdisciplinary perspective.
• Increase their knowledge about relevant approaches to understand mental health problems and wellbeing, including perspectives covering psychology, genetics, neurodevelopmental development, social gradients, and family and neighborhoods.

Skills

Participants will:

• Improve skills concerning presentation of research in the mental health field.
• Improve skills in publishing strategies.
• Improve their methodological skills in domains such as epidemiological methods, longitudinal modelling, neurodevelopmental methods, genetically informative designs, structural equation modelling, multilevel modelling, and machine learning techniques.

General competence

Participants will:

• Improve their competence in critically evaluating research and interventions in the mental health and wellbeing field, and in critical reflection on ethical and methodological challenges of doing research and interventions in this field.
• Develop a general understanding of the nature, advantages, and challenges of interdisciplinary research.

Admission to the course

The course is open for Ph.d. candidates, postdocs and senior faculty. New participants are admitted each semester. For Ph.d. candidates, the seminar serves as a mandatory course within the Ph.d program and requires attendance over two semesters. Participation of Ph.d. candidates together with postdocs and senior faculty will provide synergy effects and a unique learning environment.

You need to register for the course in Studentweb. You need to register for PSY9401A in the first semester. If you have completed the first semester you need to register for PSY9401B.

Please contact the administration if you have problems to sign up in Studentweb.?

Overlapping courses

• 1 credits overlap with PSY9500A ¨C PhD Research seminar I.
• 1 credits overlap with PSY9500B ¨C PhD Research seminar II.
• 1 credits overlap with PSY9500C ¨C PhD Research seminar III.

Teaching

Teaching consists of five seminars, each two hours in duration, per semester. The course will include a combination of presentations by participants, discussion of projects, lectures on methods, and review of state-of-the-art research.

The seminar may also be used for mid-way evaluations of the attending Ph.d. candidates.

Examination

Examination

Requirement for Ph.d. candidates: Active participation, including project presentation, and attendance over two semesters at minimum.

ECTS-credits: 5 credits after two semesters (3+2 ECTS)

A (semester 1): active participation and project presentation.

B (semester 2): active participation.

Language of examination

English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about?the grading system.

More about examinations at UiO

• Use of sources and citations
• How to use AI as a student
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.