Research tool kit/Epidemiology

Course Objective

All the steps needed to write a (clinically) relevant, high-quality, and successful research proposal will be covered in this course, through lectures and work groups, resulting in a written research proposal to be presented in a video pitch.

After completing this course

1. The student can conduct comprehensive literature searches using academic databases, critically evaluate existing research, and synthesise findings to identify knowledge gaps and articulate both scientific and societal relevance.
2. The student can recognise the importance of open-science practices, including proper data management, to ensure transparency, reproducibility, and credibility in psychological research
3. The student can formulate focused, coherent, and theoretically grounded research questions and hypotheses based on a thorough literature review, ensuring meaningful contributions to the field of psychology.
4. The student can describe and differentiate between major psychological research designs, including cross-sectional, longitudinal, experimental (lab-based), and randomised controlled trial designs.
5. The student can analyse the strengths and limitations of various research designs and assess their suitability for addressing specific research questions and hypotheses
6. The student can identify potential confounding variables and select appropriate statistical tests to address the research question, including strategies to control or adjust for confounds.
7. The student can apply ethical principles in research design, including informed consent, debriefing, confidentiality, and protection of participants.
8. The student can critically evaluate published research articles based on methodological rigour, statistical validity, and ethical considerations.
9. The student can integrate knowledge of research designs, statistics, and ethics into coherent written research proposals and clear, well-structured oral presentations.

Course Content

Through various lectures, you will learn about the purpose, scope, and limitations of different research methods and designs, such as clinical trials, longitudinal studies, and cross-sectional studies from the perspective of clinical, developmental, and neuropsychology. Additionally, you will get acquainted with the practical and ethical aspects of conducting research in psychology and the writing of a data-analysis plan. Your acquired knowledge will be tested in weekly canvas quizzes that count towards your final grade.

There will be weekly homework assignments, which will prepare you for the weekly workgroups. In the workgroup sessions, you will work on different aspects of the research proposal, through individual and group assignments. You will practice with making informed and substantiated decisions regarding your research, and critically looking at the scientific literature. The first five workgroups will be synchronous (mandatory), and the last two workgroups will be asynchronous (mandatory). A large part of the workgroups is based on peer feedback because evaluating researcher and researcher proposals critically is one of the course's learning goals. You will, of course, be supervised in this and all students will receive individual feedback as well.

Additional Information Teaching Methods

Method of Assessment

Sufficient tutorial attendance (Pass/Fail)

Attending and participating in tutorials is mandatory. You are allowed to miss one tutorial, but must complete an additional assignment in order to compensate for this absence. The compensatory assignment must be submitted via Canvas by the deadline indicated and must be passed at a sufficient level (≥5.5). Being more than 15 minutes late and/or not being well prepared may also be considered an absence. “Well prepared” means that the student has completed the preparatory assignment(s) for that tutorial. These preparatory assignments must be submitted via Canvas before 09:00 on the morning of the tutorial. Failure to submit the preparatory assignment(s) on time will be marked as an absence. If you miss two or more tutorial meetings and/or do not complete the compensatory assignment by the deadline, you will fail the tutorial attendance requirement. In that case, a numerical final grade cannot be registered, and you will receive NS or NVD on VUweb.

Homework assignments (10%)

During the course, there will be five preparational homework assignments, each due at 09:00 on the day of the workgroups. On-time and complete submissions receive full credit (10 points). Late or incomplete submissions receive no credit (1 point). Failed homework assignments can be resubmitted before the next tutoral session. However, failure to submit the preparatory assignment(s) on time will be marked as an absence.

Midterm exam (30%)

A midterm exam will take place in week 6 and will cover the content of the first five lectures and tutorials. There will be an opportunity for a resit exam. In accordance with the FGB Teaching and Examination Regulations, this resit is allowed for both passed and failed exams, and the most recent mark (i.e., not the highest mark) will apply in the event of a resit. Both the final exam and the resit exam will be administered digitally at the VU with in-person proctoring.

Video Pitch (10%)

• You will prepare a 4-minute video pitch of your research that will be assessed using a published rubric. Students who submit an insufficient pitch at the final deadline are eligible for a resit, with a maximum achievable grade of 6.0 on the resubmission. This also applies when academic misconduct has been identified in the original submission, provided a resit is granted. Students who do not submit any assignment by the final deadline may be eligible for a resit without a grade cap, subject to the applicable Rules and Guidelines of the Examination Board and course regulations.

Research Proposal (50%)

The final product of the course is a short research proposal, graded by your tutor according to a published rubric. Students who submit an insufficient proposalat the final deadline are eligible for a resit, with a maximum achievable grade of 6.0 on the resubmission. This also applies when academic misconduct has been identified in the original submission, provided a resit is granted. Students who do not submit any assignment by the final deadline may be eligible for a resit without a grade cap, subject to the applicable Rules and Guidelines of the Examination Board and course regulations.

Entry Requirements

Succesful completion of Statistical and Methodology courses (Research Methods 1 and 2).

Literature

All learning materials will be published on canvas using scientific articles and lectures

Additional Information

Academic misconduct is defined as any act or omission by a student that partially or entirely precludes making an accurate assessment of their knowledge, understanding and skills, or those of another student. Use of generative AI (e.g., ChatGPT) is not allowed, and its use in this course is a form of academic misconduct. Plagiarism is the literal adoption of someone else’s work or parts thereof without citation of sources and presenting it as one’s own work. Paraphrasing or summarizing other people’s work may also constitute plagiarism if insufficient reference is made to the source. Plagiarism is a form of academic misconduct, and the term fraud refers to both academic misconduct and plagiarism. If fraud is found or suspected, the FGB Examination Board will be notified as soon as possible, and they will then make a decision on the fraud case. For further details regarding the rules, regulations, and penalties for fraud, see Rules and Guidelines of the FGB Examination Board and the VU Manual for Quality Assurance of Teaching and Learning.

Explanation Canvas

All study materials, deadlines, examples of the proposal will be published on canvas. Deadlines and instructions on canvas are leading.

Recommended background knowledge

You have already gained knowledge and skills on most of the topics in this course through previous methodology courses such as Research Methods 1 and Research Methods 2. Besides this, the knowledge obtained in previous Statistics courses is relevant for this course. This course will build upon and integrate this pre-existing knowledge by following all the steps of the empirical cycle. This course will also give you the tools for writing your bachelor’s thesis