Systematic Review
Systematic reviews, often accompanied by metaanalyses or meta-syntheses, are becoming increasingly common in all fields of health science as a way of summarizing data from multiple studies.
The course will provide a step-by-step guide for performing systematic reviews, including developing a protocol for a systematic review, formulating a search strategy, literature search selecting studies, extracting data, critically appraising primary studies, synthesizing data, interpreting findings, and reporting and disseminating systematic reviews.
Knowledge:
- Has advanced knowledge about planning to conduct a systematic review-study, involving both qualitative and quantitative studies in health science and practice.
- Has thorough and specialized insights regarding each step of developing a protocol for performing a systematic review with meta-analysis or meta-synthesis.
- Can effectively identify and analyze academical and clinical challenges that could be solved by a systematic review.
Skills:
- Can utilize and deal critically with various databases to perform a systematic review.
- Can develop research questions suited for systematic review, plan search strategies, screen and select relevant studies, extract data, appraise critically, synthetize, interpret and report the findings.
General Competencies:
- Demonstrates an ability to analyze the strengths and weaknesses of systematic review, concerning the utilization of findings for further innovation within clinical practice.
- Masters the language and terminology of systematic review.
- Can communicate about academic issues, analyses, and conclusions within systematic review.
The course spans over two digital gatherings and includes various learning activities such as lectures, group discussions, along with individual and groups hands-on exercises.
The course includes project- and research-based learning, which helps the students develop practical skills by engaging in hands-on projects and real-world scenarios. Through project-based learning students will have the opportunity to apply theoretical concepts to practical situations, enhancing their understanding of systematic review methodologies as well as their ability to conduct comprehensive literature reviews in the field of health science.
Students also benefit from one-to-one feedback in the seminars. Additionally, students are encouraged to engage in self-study and complete assigned tasks to enhance their understanding and application of course concepts. Following the course, participants have the option to submit their work to the instructor for further feedback.
During the first gathering, which spans three days, students will become acquainted with all the steps involved in conducting a systematic review. In the second gathering, which is a one-day digital session, students will provide preliminary study protocol for performing a systematic review with meta-analysis or meta-synthesis and will discuss in the meeting.
Digital teaching sessions spring 2027:
Week 4: January 25.-27. 2027.
Week 7: February 15. 2027.
(Nord University reserves the right to make changes).
Compound assessment (SV), grading scale: Passed/not passed. All components must be approved in order to receive a combined grade for the course.
Compulsory participation (OD), grading scale: Approved/not approved. An attendance rate of 80% is required, and attendance is recorded hour by hour during the online sessions.
Assessment task 1 (AK), grading scale: Approved/not approved. Must be approved before the written assignment can be assessed.
Assessment task 2 (AK), grading scale: Approved/not approved. Must be approved before the written assignment can be assessed.
Written assignment (OP), grading scale: Passed/not passed.
The exam date can be found in Studentweb (after semester registration with teaching and exam notification for the course has been approved).
The exam answer must always be prepared by the candidate themselves. Generating an answer using ChatGPT or similar artificial intelligence tools and submitting it, in whole or in part, as one's own work is considered cheating.
For more information about ChatGPT or similar AI tools, as well as source referencing, unauthorized collaboration, and plagiarise, see the Guidelines for Exam Candidates at Nord University – Rector’s Decision 16.05.23: www.nord.no/student/eksamen
