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KIN 104 > Module 1 - Kinesiology and Science > Flashcards

Module 1 - Kinesiology and Science Flashcards

1
Q

What are the 3 departments in the Faculty of Health?

A

The School of Public Health Sciences, Dept. of Kinesiology + Health Sciences, Dept. of Recreation + Leisure Studies

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2
Q

What are the 5 programs offered by the Faculty of Health?

A

Health Sciences, Public Health, Kinesiology, Recreation + Sport Business, Therapeutic Recreation, Recreation + Leisure Studies

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3
Q

Kinesiology

A

The study of human movement

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4
Q

Kinematics

A

The study of motion

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5
Q

Kinetics

A

The study of forces that cause motion

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6
Q

Kinesthesia

A

Sense of movement

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7
Q

What is the difference between the discipline and the profession?

A
  • 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)
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8
Q

Minors + specializations offered by Dept. of Kinesiology + Health Sciences (3A, 3B, 4A, 4B)

A
  • Neuroscience minor (Sept. 1, 2024)
  • Ergonomics + injury prevention minor
  • Human nutrition minor
  • Medical physiology minor
  • Rehabilitation sciences specialization
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9
Q

How do you know what is “true”?

A
  • 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
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10
Q

The Scientific Process

A
  • 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
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11
Q

What if results of your research do not support your hypothesis?

A
  • 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
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12
Q

Confirmation bias

A
  • 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
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13
Q

Importance of evidence

A
  • 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
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14
Q

Peer-reviewed scientific publications

A
  • Quality control
  • Valid, high quality, original
  • Also called scholarly, academic, refereed
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15
Q

Primary article (empirical study)

A
  • Aims to gain new knowledge through direct/indirect observation + research
  • Quantitative/qualitative data + analysis
  • Often include sections –> intro, methods, results, discussion (IMRaD)
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16
Q

Review article

A
  • Summary of existing research in a field/topic area
  • Several types: narrative reviews, scoping reviews, systematic reviews
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17
Q

Narrative reviews

A
  • Summarizes some of existing evidence
  • Overviews, describes, + synthesizes topic
  • Can be more biased
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18
Q

Scoping reviews

A
  • Broad reviews, aim to gather as much evidence as possible + map evidence into themes
  • Describe methodology, what do search + how (to remove biases)
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19
Q

Systematic reviews

A
  • Highly structured reviews that utilize pre-planned methods to include/exclude articles
  • Describe methodology, what do search + how (to remove biases)
20
Q

Meta-analysis journal articles

A
  • 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
21
Q

Case studies

A
  • 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
22
Q

RADAR Framework

A
  • 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
23
Q

Steps to reading a paper

A

Skim, first (second…) detailed read, review data, summarize

24
Q

Structure of a paper

A

Title, abstract, intro, methods, results, discussion, references

25
Q

Statistics

A
  • Field of mathematics that relates to presentation, analysis, + interpretation of data
  • Important to recognize trends + patterns, describe relationships between 2 variables, statistical differences
26
Q

Score:

A

Value associated w/ a variable of interest (usually has units)

27
Q

Frequency

A

A count based on a criteria, most common, “how much?”, “how often does something occur?”

28
Q

Mean

A
  • An average, mathematical centre of ALL scores
  • Symbol: X̅
    (central tendency)
29
Q

Median

A
  • The score that divides a data set in 2 equal halves (e.g. 50th percentile)
    (central tendency)
30
Q

Mode

A
  • The score that occurs the most (e.g. the score w/ the highest frequency)
    (central tendency)
31
Q

Data set

A

Collection of scores

32
Q

Standard deviation

A
  • Indicates how closely individual data points cluster around the mean
  • Low –> similar, low variability
  • High –> different, high variability
  • Symbol: s
    (variability), most common
33
Q

Standard error

A
  • Same info as standard deviation, different value
    (variability), most common
34
Q

Range

A
  • Max - min values
    (variability)
35
Q

Normal curve

A
  • Bell curve
  • Frequency distribution
  • Allows percentile calculations
  • Relative
  • Curve is symmetrical –> mode, median, and mean are the same value
36
Q

Histogram

A

Frequency count vs data

37
Q

Box plot (whisker plot)

A
  • Range (lower extreme - upper extreme)
  • Lower quartile (25th percentile), upper quartile (75th percentile)
38
Q

Scatter plot

A
  • Represents relationship between 2 variables
  • Correlation regression (lines): statistical analysis that measures the strength of the relationships between 2 variables
39
Q

Time series plot

A
  • Similar to scatterplot
  • x-axis is time
40
Q

Statistical significance

A
  • Likelihood (probability) that a relationship between two+ variables is due to something (usually and intervention) other than random chance
  • Objective
41
Q

Biological (clinical) significance

A
  • 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
42
Q

Minimally clinically important difference (MCID)

A
  • Outcomes that reflect the smallest benefit/change that is meaningful to the person/patient
  • More intrinsic
  • Subjective
43
Q

Probability

A

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)

44
Q

Null hypothesis

A
  • 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
45
Q

P-value

A
  • 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
46
Q

Statistical difference

A
  • 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)

KIN 104 (4 decks)

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