Summary Introduction Biomedical Sciences (Empirical cycle, Variables & Descriptive statistics, Study design, Ethics, Probability rules, Biases)

Introduction to Biomedical Sciences (IBMS)
Year 1

Lecture 1; The Empirical cycle

Empirical research = research based on observation and measurement of phenomena,
as directly experienced by the researcher
- an example of scientific research
1. Evidence based data
2. Compare to theory
3. Quantitative and qualitative

Empirical evidence = Objective evidence that appears the same, regardless of the observer

Empirical cycle =
1. Identifying problem
- Observation
- noticing relationship
- Unexpected event
- Previous research
2. Reviewing literature
- what is already known
- gaps in literature?
3. Setting RQs, objectives, hypothesis
- what do you want to find out
4. Choose study design
- research strategy
- what variables, tools, measurements
- ethical considerations
5. Decide sample design
- sample of persons / events → represent population?
6. Collecting data
7. Processing and analyzing data
- what statistical methods need to be applied to data in order to accept
hypothesis
- evaluation data → interpretation of results → hypothesis proven?
8. Writing report evaluation study
→ for: scientist collect evidence in order to test their hypothesis



WG 1; Not study

RQ =
- open ended

, - running sentence
- specific + unambiguous
- not too broad
- follow PICO (population, intervention, control, outcome)

PICO : Effects of cannabinoids on glioblastomas
P→ European glioblastoma patients
I → Effect of cannabinoids
C → Glioblastoma patients on other therapies
O → Decrease tumor size

Hourglass structure




CPR1;

Review articles = Summarizes + evaluated preexisting knowledge
- abstract, introduction, BODY, discussion, references
Research articles = Provides new knowledge by showing novel empirical data
- abstract, introduction, METHODS, RESULTS, discussion, references

Referencing
- to avoid plagiarism
When?
- Insights/ideas/work from others
- not needed for common knowledge

Paraphrasing
- copy pasting directly
- Paraphrasing without crediting the author
- Patchwriting → paraphrasing by only changing few
words (even with citations)

Annotated Bibliography = bibliography that includes paragraph about each source

, - good to keep track of all sources wanting to be used
- informs about relevance
- includes: Reference, Context, Outcome, Evaluation



Lecture 2; not on test

Scientific Literature




Primary Literature = Original research articles, surveys, case report, case studies, editorial
Secondary Literature = Narrative reviews, Systematic reviews, Meta analysis, Book
reviews, Guidelines, Commentary

Scientific article
- Very dense
Read:
- Zapping → pick an article relevant to research
● (scanning of: titles, abstracts, intro, conclusions + title keywords, type of lit,
journal, date )
- Skim reading → grasp the papers content (not detailed)
● understand approach → first + last part of discussion → check figures tables
(quick)
● Quick scan throughout article → relevant methods, relevant results, whole
discussion, relevant fig tables)
- Structured focused reading → understand paper in depth
● key points
● figured out whether article is relevant for you and if outcomes are helpful




Lecture 3; Variables & Descriptive statistics

Science = The process of collecting data through observation (to better understand how the
world works)
Methodology = Study of the methods used to collect data, make those observations,
address RQs
Statistics = Set of mathematical tools that help us draw conclusions about our data

Individual = objects described by a set of data