Module 1 - Kinesiology and Science Flashcards
What are the 3 departments in the Faculty of Health?
The School of Public Health Sciences, Dept. of Kinesiology + Health Sciences, Dept. of Recreation + Leisure Studies
What are the 5 programs offered by the Faculty of Health?
Health Sciences, Public Health, Kinesiology, Recreation + Sport Business, Therapeutic Recreation, Recreation + Leisure Studies
Kinesiology
The study of human movement
Kinematics
The study of motion
Kinetics
The study of forces that cause motion
Kinesthesia
Sense of movement
What is the difference between the discipline and the profession?
- Discipline: the science of kinesiology itself
- Profession: registered kinesiologist, involves a scope of practice (assessment of human movement + performance, its rehabilitation + management to maintain, rehabilitate, or enhance movement + performance)
Minors + specializations offered by Dept. of Kinesiology + Health Sciences (3A, 3B, 4A, 4B)
- Neuroscience minor (Sept. 1, 2024)
- Ergonomics + injury prevention minor
- Human nutrition minor
- Medical physiology minor
- Rehabilitation sciences specialization
How do you know what is “true”?
- Be aware that some researchers paid to present misleading information
- Studies tracking a larger # of people –> more date + more accurate results
- Look at a variety of sources for a well-rounded understanding
The Scientific Process
- Make observation/review previous research
- Formulate question
- Formulate hypothesis (educated guess based on previous knowledge)
- Design experiment
- Execute experiment
- Analyze results
- Draw conclusion
- Formulate new hypothesis
What if results of your research do not support your hypothesis?
- Confirmation OR refutation of a hypothesis are both valuable outcomes
- Science sets out to determine TRUTH; does not set out to PROVE
- Seek TRUTH not PROOF
Confirmation bias
- Tendency for individuals to search for, select and/or interpret information in a way that serves to confirm their beliefs/hypotheses
- Leads to disregarding information that challenges their beliefs/hypotheses
Importance of evidence
- Accumulation of results from many studies serve to inform what is ‘true’
- Singular studies not enough (multiple studies, locations, researchers coming to the same conclusion –> reinforce ‘truth’)
- Anecdotes are not enough + often influenced by confirmation bias
- Bad science/’pseudo-science’ can be intentionally/unintentionally misleading
- Accumulation of knowledge is important + takes time
Peer-reviewed scientific publications
- Quality control
- Valid, high quality, original
- Also called scholarly, academic, refereed
Primary article (empirical study)
- Aims to gain new knowledge through direct/indirect observation + research
- Quantitative/qualitative data + analysis
- Often include sections –> intro, methods, results, discussion (IMRaD)
Review article
- Summary of existing research in a field/topic area
- Several types: narrative reviews, scoping reviews, systematic reviews
Narrative reviews
- Summarizes some of existing evidence
- Overviews, describes, + synthesizes topic
- Can be more biased
Scoping reviews
- Broad reviews, aim to gather as much evidence as possible + map evidence into themes
- Describe methodology, what do search + how (to remove biases)
Systematic reviews
- Highly structured reviews that utilize pre-planned methods to include/exclude articles
- Describe methodology, what do search + how (to remove biases)
Meta-analysis journal articles
- Secondary analysis
- Combines and/or analyzes data from different primary studies (usually) in new analysis tp strengthen understanding of particular topic
- Taking completed studies + analyzing them together
Case studies
- Report specific instances of interesting phenomena
- Goal: to make other researches aware of possibility that a specific phenomenon might occur
- Often used in medicine to report occurrence of a previously unknown/emerging pathologies
RADAR Framework
- Relevance: support ideas with pertinent info
- Authority: judging credibility of author’s assertions
- Date: currency, info can quickly become obsolete, supporting research with superseded facts weakens your argument
- Appearance + Accuracy: sources are identifiable through appearance + context clues, important b/c errors + untruths distorts line of reasoning, presenting inaccurate info undermines your credibility
- Reason: sources made to serve a purpose (some are frivolous/commercial; provide inaccurate, false, biased info), varied points of view can be valid if based on good reasoning + careful use of evidence
Steps to reading a paper
Skim, first (second…) detailed read, review data, summarize
Structure of a paper
Title, abstract, intro, methods, results, discussion, references
Statistics
- Field of mathematics that relates to presentation, analysis, + interpretation of data
- Important to recognize trends + patterns, describe relationships between 2 variables, statistical differences
Score:
Value associated w/ a variable of interest (usually has units)
Frequency
A count based on a criteria, most common, “how much?”, “how often does something occur?”
Mean
- An average, mathematical centre of ALL scores
- Symbol: X̅
(central tendency)
Median
- The score that divides a data set in 2 equal halves (e.g. 50th percentile)
(central tendency)
Mode
- The score that occurs the most (e.g. the score w/ the highest frequency)
(central tendency)
Data set
Collection of scores
Standard deviation
- Indicates how closely individual data points cluster around the mean
- Low –> similar, low variability
- High –> different, high variability
- Symbol: s
(variability), most common
Standard error
- Same info as standard deviation, different value
(variability), most common
Range
- Max - min values
(variability)
Normal curve
- Bell curve
- Frequency distribution
- Allows percentile calculations
- Relative
- Curve is symmetrical –> mode, median, and mean are the same value
Histogram
Frequency count vs data
Box plot (whisker plot)
- Range (lower extreme - upper extreme)
- Lower quartile (25th percentile), upper quartile (75th percentile)
Scatter plot
- Represents relationship between 2 variables
- Correlation regression (lines): statistical analysis that measures the strength of the relationships between 2 variables
Time series plot
- Similar to scatterplot
- x-axis is time
Statistical significance
- Likelihood (probability) that a relationship between two+ variables is due to something (usually and intervention) other than random chance
- Objective
Biological (clinical) significance
- Effect considered by expert judgement as important and meaningful for human, animal, plant, or environmental health (e.g. stroke victim recovering minimal movement - clinician considers it significant)
- Subjective
Minimally clinically important difference (MCID)
- Outcomes that reflect the smallest benefit/change that is meaningful to the person/patient
- More intrinsic
- Subjective
Probability
Calculate probability that indicates if an event happened simply due to chance (random events) or if there was a reason for said event/difference (some treatment/intervention)
Null hypothesis
- Type of statistical hypothesis that proposes that no statistical difference exists in a set of given observations
- Formulated and then rejected/retained with the help of statistical tests
P-value
- Probability, which is calculated using a statistical test
- Reflects the measure of evidence against null hypothesis
- Small p-values correspond to strong evidence
- P-value below predefined limit (5%, 0.05 or 1%, 0.01) –> results are “statistically different”
- Researcher chooses a “goal post”/”threshold” of either 5% or 1%
- Expressed as percentage
Statistical difference
- Less than/equal to 1% or 5% –> statistical difference (means are NOT the same)
- Greater than 1% or 5% –> NO statistical difference (means are the SAME)
