A short story about an interesting or funny event or occurrence
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Tradition
Skills and knowledge handed down over time \n – Advantage: Each subsequent generation starts with \n a more advanced state of knowledge \n - Greater component of training than ongoing \n education
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Authority
Specialist in the area \n Licensed psychologist, accountant. \n Will have more detailed knowledge within \n their realm. \n BUT: \n Only advantageous if specialist is well-informed on \n current best evidence
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Trial and Error
Altering practice based on trying something \n new.... \n BUT: \n - Not systematic, haphazard approach. \n - Difficult to determine why or why not a solution \n has worked
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Deductive & Inductive Reasoning
Application of logical reasoning to come up with a solution.
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Deductive reasoning
General observation → specific conclusion
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Inductive reasoning
Specific observation → general conclusion
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The Scientific Method
Incorporating inductive and deductive reasoning \n Systematic and controlled process \n Involves a sequence of events
\- Make an observation \n - Formulate a question & hypothesis \n - Design an experiment..... \n - Execute the experiment
\- Analyze the results...... \n - Draw conclusion
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Key elements of scientific method
Skepticism \n Open-mindedness \n Objectivity
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Quantitative research
Measurement of outcomes using numerical data under \n standardized conditions
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Qualitative research
\- Deriving conclusions from open-ended questionnaires, surveys, interviews and observations. \n - Not applying numerical descriptions to observations.
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Basic research
\- Pure or fundamental research \n - Direct practical applications? \n - Investigates underlying psychological, anatomical, or \n physiological mechanisms
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Applied research
\- Research that has direct practical application \n – Based on a general premise (assumption) that is not directly tested in the study
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Translational research
Application of basic scientific findings to clinically relevant issues, and simultaneously, the generation of scientific questions based on clinical dilemmas.
Describing a group of individuals on a set of variables to document their characteristics.
Example: Describing personality traits among in-residence first-year university students.
\- Case study
\- Normative study (Establishing baseline statistics for specific groups of people)
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Exploratory research
Examining the interaction of various factors on people’s behaviour/characteristics.
\- Epidemiology
\- Cohort study (Following a group of people over time)
\- Case-control study (Selecting groups of individuals based on the presence of the condition investigated)
\- Correlational-predictive research (Examining relationships between variables)
\- Methodological (Evaluating/demonstrating the reliability, validity, and/or validity of measurement instruments and/or procedures)
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Correlational study
Identify the dependent variable (this is the variable that we are trying to predict)...... \n Identify the independent variable (i.e., the x-axis variable)...... \n Make a scatterplot of the data
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Experimental research
Designed to compare groups to establish a cause-and-effect \n relationship
\- RCT – Randomized Controlled Trial (Controlling factors that can affects of the results of a research study)
\- Quasi-experimental designs (Same as experimental designs, but with less control)
\- Pre-experimental designs
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Developing a research question
\-Introspection
\-Find the exception to the rule
\-Matter of degree
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Hypothesis
Educated “guess”, sometimes truly a guess
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Research hypothesis
Based on knowledge
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Statistical hypothesis
Probability of occurrence
Null vs alternative hypothesis (type 1 and 2 error probability)
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Scientific law
A statement based on repeated experimental observation
“Newton law of motion”
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Scientific theory
Psychology relies much more on theories than laws
Well substantiated explanation of an event
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Key concepts of hypothesis
\-Variables: Elements in a study that can vary of assume different values
\-Qualitative or quantitative (numerical)
Constant: Factor that does not change. Can be used for experimental control: Eliminating confounding items
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Conceptual definition
General definition of a variable
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Operational definition
Definition of the same variable (conceptual) in context
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Personality
Conceptual definition: Characteristic thoughts, emotional responses, and behaviours that are relatively stable in an individual over time across circumstances.
\ Research study: Operational definition (more specific: The big five)
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The big five
Oppenness
Conscientiousness
Extroversion
Agreeableness
Neuroticism
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Deductive hypothesis
Based on a theoretical foundation
Minimal direct observation
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Inductive hypothesis
Based primarily on experimental findings
Examining patterns displayed in research papers, public health data, etc
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Research hypothesis
States what the experimenter thinks will happen
Variables will be different or related to each other OR no differences or relationships… sometimes the same as the null hypothesis
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How to evaluate the hypothesis
\-Does it correspond with reality
\-Is it parsimonious (phenomena behave in the most economic way) (making minimum number of assumptions)
\-How specific is it
\-Barnum effect (tendency of people to believe general descriptions of their personality are highly accurate)
\-Is it falsifiable or refutable?
\-Research study must be able to accept or refute hypothesis
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Experimental design
Independent variable
Dependent variable
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Independent variable (x)
Refers to variable that can be manipulated (ex: Treatment group) with or without
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Dependent variable
The outcome variable
What will be measured
Ex: Number of psychotic episodes per week
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Non-experimental designs
Explanatory (or predictor) variable
Criterion (or response) variable
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Explanatory variable
It is what a researcher manipulates or observes changes in
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Criterion (or response) variable
Outcome variable in non-experimental designs (like dependent)
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How do you get participants?
Volunteer
Must know all relevant information
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Variables
Anything that, when measured, will produce 2 or more different scores
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Qualiative
Research participant information that is NOT measured in “amounts” but classifies the participant based on the measure
Muscle strength example: Strong, moderate, weak
Pain example: Intense, moderate, mild
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Quantitative
A number is assigned to a measure obtained from the research participant (amount)
Muscle strength example: Amount of weight lifted
Pain example: Visual analog scale (0-10 scale)
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Ethics
Application of moral principles concerning what an individual considers right and wrong to help guide one’s decisions and behaviour
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Utilitarian
Greatest good for the greatest number
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Altruistic perspective (ethics)
Involves helping others without personal benefit
Selfless actions
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Egoism
Individuals should act in accordance with their own self-interests
Eric Poehlman did data fabrication and was sent to U.S. federal prison
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Research ethics governed by
\-Federal and institutional policy
\-Research misconduct
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Research misconduct
A serious breach of good research practise that includes but is not limited to falsification, fabrication, and plagiarism committed willfully or through gross negligence when planning, carrying out or reporting on research
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Factors affecting ethical research
\-Scientific competition
\-Societal norms
\-Political influences
\-”Trendy” research
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Scientific competition
Competing with others with similar interests
“Who will find the answer first”
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Societal norms
\-Undefined norms within a discipline or an organization
\-Will foster scientific competition
\-3 P’s: Policy, procedure, practise
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Political influences
\-Ability to obtain external funding for research
\-Research activities are “tailored” around funding hopes
\-Research activities that may “impress” influential people
\-Status, monetary gain, decision making power
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“Trendy” research
\-Blindly “doing what other people are doing”
\-Research questions often go unanswered
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With ethics, the researcher must:
\-Look over previous relevant work (Identify and acknowledge)
\-Identify potential sources of error (limitations)
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Internal responsibility
Researchers
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External responsibility
Personnel not associated with study
ex: Human subjects committee, scientific journal personnel
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Human subjects committee
\-Serves to protect the rights of human participants from physical, psychological, or social harm
\-Non-institutional members of the community
\-Provides approval to being study
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Journal editors and reviewers
\-Determine the quality of submitted work
\-Process prone to ethical violations (Editors found to sometimes violate to gain political favour) (Reviewers may reject without adequate justification due to competitive interests)
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Final responsibility of ethical research
\-Scientific community at large
\-Readership of journals
\-Identifying weaknesses in published work
\-Letter to editor
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Research ethics board - Review levels
\-Exempt (Lowest): Research poses less than minimal risk (sometimes not reviewed at all)
\-Expedited (Common): Poses minimal risk typically encountered in daily life
\-Full review: Research poses greater than minimal risk (reviewed by at least five members)
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Nuremberg code
Developed by military tribunals
Established basic ethical principles
\-Participants must be able to make voluntary decision
\-Must not make any positive or negative inducement for participants to enroll in study
\-Participants must provide informed consent
\-Investigator must be compotent
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Declatation of Helsinki
Emphasized review of research protocols by an independent committee not involved with the project
Developed by institutional review board
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Belmont report
Established basic ethical principles in research in the United States
\-Respect for persons (Provide sufficient information, treat people as people)
\-People capable of making their own choices
\-Informed consent (Risks and benefits) (Understand study and procedure) (Free from coercion) (Freedom to withdraw)
\-Benefits must outweigh risks (Cost-benefit analysis)
\-Researchers should do no harm
\-Requires burdens to be distributed fairly, no favour or distain
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Ethical treatment of data
\-Falsification/Fabrication of data (eric poehlman) (Autism and vaccines)
\-Massaging the data (data manipulated to get statistical significance)
\-Dropping participants if outliers
\-Reported only significant results
\-Including some variables but not others
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Role of quantitative methods (stats)
Applying numbers, equations, formulas, math techniques, graphical analyses
\ Research question → research design → Findings/answers → Share/publish findings
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Select design based on research goal
Non-experimental
Quasi-experimental
Experimental
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Determine measures
Keys to effective measurement
Types of measurement error
Reliability and validity of measures
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Recruit research participants
Types of sampling
Sampling issues
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Population
Refers to entire group of individuals to which a law of nature applies
Ex: All uni students in canada, all canadians over 65, all people with cardiovascular disease
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Parameters
Numbers that characterize the population (greek symbols) (u used for mean) (o used for standard deviation) (p used for correlation coefficient)
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Sample
Relatively small subset of a population that is intended to represent that population (ex: All uni students in canada = sample: 50 undergrads from uni of guelph)
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Statistics
Numbers that characterize the sample (english symbols = Sx, r, X (with a line on top))
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Random sample
Individuals that make up the sample are randomly selected from population
\ May not be representative sample
Difficult to randomly select
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Data
Scores on variables, or info expressed as numbers
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Variables
Traits that can change values from case to case
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Cases
Entities from which data are gathered (people, businesses, cities, countries)
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The 2 approaches to statistical applications
Descriptive
Inferential
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Descriptive statistical approach
\-Describing basic characteristics of a person or group
\-Summarize one variable (univariate)
\-Summarize relationship between 2 variables (bivariate)
\-Summarize the relationship between three or more variables (multivariate)
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Inferential statistical approach
\-“Inferring” results of an analysis to a larger population
\-Involves statistical “hypothesis testing”
\-Also involves descriptive statistics
\-Establishes… cause and effect relationship
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Discrete variables
Measured in units that cannot be subdivided (gaps)
Variable classified in whole units
Dichotomous variables (only 2 possible outcomes)
or categorical variables
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Continuous variables
Measured in unit that can be subdivided infinitely
Variable taking on a value along a continuum (no gaps)
Infinite number of fractional components (in theory)
Limited by the precision of the testing instrument (ex: age)
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Dependent variable
Measuring an outcome (ex: results of a federal election)
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Independent variable
A factor influencing an outcome i.e., the dependent variable (Residential location regarding a SARS CoV2 infections (DV))
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Precision measurement
Refers to exactness of measure
Sensitivity of testing instrument
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Measurement scales
\-Nominal
\-Ordinal
\-Interval
\-Ratio
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Nominal scales
Identification scores
Does not measure amount or value
Classifies groups or responses
Ex: Sex at birth, gender, do professional athletes make too much money? (Yes or no)
\ Criteria: Mutually exclusive, exhaustive (category for every score), homogeneous (include cases that are comparable)
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Ordinal scale
\-Scores that indicate rank order
\-Scores only indicate a position between items
\-Ex: Opinion surveys, clinical measurement of muscle strength