Title: Observational epidemiology: Cross-sectional, cohort and case-control studies
Keywords: Research method
Quantitative methods
Country: Norway
Institution: Norway - Centre for International Health, Universitetet i Bergen
Course coordinator: Bernt Lindtjørn
Date start: 2018-02-05
Date end: 2018-02-23
About duration and dates: 3 weeks
Classification: advanced optional
Mode of delivery: Face to face
Course location: Centre for International Health, Bergen
ECTS credit points: 5 ECTS credits
SIT: 135 hours (45 hours per week): Lectures 40 hours, individual assignments or group assignments with supervision and discussions 40 hours and individual reading and lab exercises 51 hours, 4 hours exam.
Language: English
At the end of the course the students should be able to:
• Discuss the main principles of epidemiological research
• Differentiate between the principles of cross-sectional studies, case-control studies and cohort studies - and compare these designs and the design of randomized controlled trials
• Estimate sample sizes for different epidemiological studies (cross-sectional, case-control, cohort)
• Compare alternative sampling methods
• Differentiate between the different types of cohort studies, i.e. prospective, retrospective and double cohorts
• Differentiate between different types of case-control studies
• Plan the epidemiological design of a study
• Evaluate selection bias in epidemiological studies
• Evaluate information bias in epidemiological studies
Assessment Procedures:
4-hour written exam consisting of short questions and problem-solving questions and calculation. The part with short questions counts 50% for the grade given, and the problem-solving questions count 50%. If the student fails to pass the exam, he/she will be allowed for a resit in the same semester.
• Sampling methods and design effects
• Sample size and statistical power
• Measures of disease occurrence and of exposure-disease association
• Bias, confounding, effect modification
• Surveys and surveillance
• Cross-sectional study
• Cohort study
• Case-control study
• Points to remember in the planning and evaluation of the different study designs
Reading the selected literature provides necessary background information to follow the course. Each day has a mixture of lectures and practical sessions, with group work or individual work on specific assignments and the use of the computer laboratory for data analysis under supervision. The lectures are interactive, and course participants are encouraged to ask questions and discuss during all sessions. The reference literature will be made available on the first day of the course through internet (“Mitt UiB”). Scientific papers will be handed out for reading, group work and presentations/discussions in plenary together with the course facilitators/lecturers.
About 40% of the course is lectures, 40% individual assignments or group assignments with supervision and work/discussions and 20% individual reading and lab exercises.
Students admitted to a Master’s degree Programme may join this course (e.g. TropEd Europe network).
Good working knowledge of English (TOEFL score of at least 550 points paper-based or 213 points computer-based, or an equivalent approved test).
Compulsory 80% attendance in group work and laboratory exercises.
Max no. of students: 30, max. no of TropEd students: 15.
Min. no of students: 5.
70 EUR to cover parts of the teaching materials and other administrative costs.
Scholarships: None
Major changes since initial accreditation:
There are no major changes in this course since it first started. However, based on student and teacher’s evaluations and natural changes, the course has become much more interactive with an increase in the use of exercises.
Student evaluation:
1. Statistical packages. Students thought it would be beneficial is they could have a short introduction session on Stata/SPSS at the start or end of Day 1 (if not possible before that). However, they were able to work their way through STATA by end of Day 1 and SPSS was fairly intuitive. Suggestion: Distribute pre-reading on introduction to SPSS/STATA, including how to import datasets from different packages (e.g. excel format). Also state in course description that although familiarity with basics of statistical software is an advantage, it is not essential; students may view the pre-reading and the program before the course. During the course a formal session on introduction to the software will not be covered.
2. They were pleased to have two sessions on sampling- this should NOT be changed. The session on causal inference should be retained. Suggestion was to introduce case-control on the last Friday of week 2 (? afternoon) so that we could have some additional time for this component.
3. During the exercises a strong emphasis on interpretation is requested rather than only focus on analysis.
4. The amount of time spent on 'recap' of basic concepts could be reduced by referring students to appropriate pre- readings prior to the course. Perhaps also recommend specific sections of the textbook to preview.

• Teaching and assessment methods: Even more hands-on would be good
• Curriculum: Good, see comments from students above
• Information and documentation – would be good if students were better prepared before course, as there were very large differences between students’ pre-course level
• Grade distribution – 19 pass 1 fail - acceptable
• Localities/equipment – auditorium with computers difficult with long distance from back to see screen up front, sound a bit difficult

• Distribute pre-reading on introduction to SPSS/STATA, including how to import datasets from different packages (e.g. excel format). State in course description that familiarity with basics of statistical software is an advantage.
• Give more specific advice as to pre-reading, to reduce somewhat potential large differences in pre-course knowledge
• Change in course description that there will be given grades, not only pass/fail (some students need grades).
Lessons learned:
The main lesson learnt is that theoretical teaching combined with exercise provides a better method for student learning. During the last years, we have also set aside time for the students to present their own data, and this has been a successful exercise.

The main lesson learned is that some students from TropEd did not have sufficient background in the use of computers and statistics. Most of the comments in the evaluations is because of their weak background in basic epidemiology and statistics. We have therefore put these as pre-requisites for attending future courses.

Also, the knowledge retained by the students on assessing cause and effect varies, and we will increase the number of home assignments to improve this learning outcome.
tropEd accreditation:
Accredited in May 2006, re-accredited in October 2011 and January 2017. This accreditation is valid until January 2022.
Remarks: To Application Form
Email Address: linda.forshaw@igs.uib.no
Date Of Record Creation: 2012-01-13 01:41:59 (W3C-DTF)
Date Of Record Release: 2012-01-13 07:55:34 (W3C-DTF)
Date Record Checked: 2017-09-12 (W3C-DTF)
Date Last Modified: 2017-10-10 04:45:03 (W3C-DTF)

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