Psychology Lecture Notes: Scientific Culture, Pseudoscience & Research Methods - PDF

LECTURE NOTES SCIENTIFIC CULTURE Principles of good science Materialism -​ Everything in the universe has a physical basis -​ Can be measured physically / objectively -​ Everything follows principles of cause and affect -​ Love, your thoughts, your emotions, etc… has a physical basis - is...

LECTURE NOTES SCIENTIFIC CULTURE Principles of good science Materialism -​ Everything in the universe has a physical basis -​ Can be measured physically / objectively -​ Everything follows principles of cause and affect -​ Love, your thoughts, your emotions, etc… has a physical basis - isn’t always easy to access though. -​ If some aspect of us was immaterial, there would be no point in studying psychology! -​ We follow the same laws as everything else in the universe. -​ Neuroscientests today can agree that all aspects of humans have a physical basis. Universalism -​ We make systematic observations that are measured objectively -​ Try to agree upon standardized, empirical measurement strategies -​ Everyone has the same measuring tools, everyone can support or refute each others observations, engage in scientific dialogue. Communality -​ Data should be open and accessible -​ Scientists should be open about their methods that yielded results so that other members of the scientific community can replicate it -​ Researchers shold engage in consistent dialogue with each other. -​ Ensures that science is for the greater good and not just for profit. Disinterestedness -​ Science should not be interested in the outcome / tailor the experiments for a particular outcome. -​ Often, companies rush / exaggerate scientific process to begin profiting from outcome. -​ Leads to questionable data, questionable science, and questionable results. Organized skepticism -​ Evaluating things based on scientific merit -​ Not on the prestigiousness of the journal publishing them. Developing a theory “Theory” -​ A way to organize and explain a variety of facts/descriptions/observations -​ Explains larger phenomena causing things to happen. -​ We can always put theories to the test = falsifiable -​ Important way of generating new knowledge -​ Parsimonious Pseudoscience -​ Often relies on authority -​ Emphasis on scientific-sounding jargon -​ E.G. = COLD F.X. - extracted polysaccharides of the gingko tree = literally sugar! -​ Emphasis on jargon to make product sound more science-based than it is -​ E.g., increased vitality; increased precision; how do we measure this? -​ Products are not peer review -​ Poor to no methodology used in production -​ Ignores or conflicts with known / existing scientific evidence -​ E.G. - eat dark, leafy greens to oxygenate your blood (?) - complete BS -​ E.G. how pheremones work - the smell of mens sweat bypasses “rational” brain of women and they respond with attraction (BS) -​ Consistently vague claims -​ Often reinforces existing status quo or a particular worldview (misconceptions) -​ Does not facilitate further research / engage with existing scientific research. Goals of psychological research -​ Describe behaviour -​ Predict behaviour -​ Determine causes and mechanisms of behaviour Once we can accomplish these three things, we can now attempt to influence / control this behaviour -​ E.G. - Facebook experiment -​ “Massive scale emotional contagion through social networks” - people with negative timelines reported more negative feelings on average -​ Whether or not you believe in science, the social media you consume is curated by dedicated psychology teams at companies -​ Designed to curate what you see and how you feel = more engagement  -​ EXAMPLE 2: Marshmallow test -​ Children are given a marshmallow and challenged to resist eating it, with the promise that if they wait a certain amount of time, they will be rewarded with a second marshmallow -​ 1/3 children exhibit self control and wait -​ 2/3 eat the marshmallow as soon as the psychologist leaves the room -​ Some children reported feeling angry having to wait for the marshmallow -​ Speaks to broader trends in psychology. Types of research -​ Basic research -​ Applied research Research design basics -​ What is a variable? -​ A thing that varies (haha) -​ Some people are tall, some people are short - height is a variable -​ The temperature in a room is a variable -​ In psychology , we are interested in conceptual variables -​ Memory is a conceptual variable -​ Emotion is a conceptual variable -​ Attention is a conceptual variable. Operationalization = turning a conceptual variable to a measured variable -​ E.g., we can’t directly measure love, but we can measure behaviours like numbers of hugs, kisses, etc… -​ Operational variable is a stand-in for an abstract concept that we can’t measure by itself (in this instance, hugs and kisses are operational variables). -​ Most of the time, one operational variable isn’t enough -​ For love, we could measure heartbeat, kisses, hugs, eye patterns, etc… Four general categories of variables -​ Independant variable  -​ Dependant variable -​ -​ Situational variable -​ Temperature in room at time of experiment -​ Quality of computers being used for a testing experiment, etc… -​ Aim to control, standardize as much as possible. -​ -​ Participant Variables -​ Gender identity -​ Language of origin -​ Socioeconomic background -​ Personal experience -​ Takeaway: high sample size, ensuring diverse sample groups. -​ Equally spread out amongst all levels of the dependant variable. Relationships Between Variables Non-Experimental Method: Correlation Research Positive correlation = two variables generally moving in a positive linear direction (e.g., attitude change and speech rate are a positive correlation) Negative correlation = two variables generally moving in a negative linear direction (e.g., amount of noise and group size go down) Curvilinear correlation = positive at first, but eventually reaches a point of diminisning returns (e.g., caffeine and performance). Relationships Between Variables Experimental Method -​ Independant variable affects change in the Dependant variable -​ This allows us to understand cause and effect. Causality -​ Covariation of cause and effect  -​ If the cause happens = the effect happens -​ If the cause doesn’t happen = the effect doesn’t happen -​ For instance = drug use: what came first? The economic challenges leading to drug use, or the drug use leading to economic challenges? Temporal precedence -​ We have to see the cause before the effect. -​ Cause comes first, effect comes after. -​ No more plausible alternative explanation -​ Best way to collect “true” information is by controlling an independant variable, and watching the behaviour of a dependant variable. Confounding variable DEFINITION -​ Variable that varies along with the independent variable. -​ Your variable that isn’t supposed to be changing (independant variable) is changing alongside the dependant variable and screwing up the experiment -​ E.G. = injecting rats with alcohol. -​ Independent variable = alcohol -​ Dependant variable = amount of alcohol -​ Confounding variable = the amount of fluid the animal is being filled with; could be influencing results. -​ FIX = all animals receive the same volume of fluid, with the alcohol content being higher or lower. -​ E.G. - rat drug experiment -​ Rats were given the choice to administer drugs, which many chose to do and became addicted. -​ Confounding variable = social isolation lead rats to administer the drug out of boredom and inactivity where otherwise they might not have. -​ This correlates to humans = social isolation is often a predictor of drug use. EXAMPLE = clinical drug studies -​ In a drug study, we usually have a controlled environment where nothing occurs -​ Placebo is a method of control -​ Exception: if treatment already exists -​ Placebo is contrasted with research-backed product  -​ -​ Treatment arms -​ Some participants get higher dose, some get lower dose, some get placebo. -​ Confounding variable = people behave accordingly with what they expect to happen -​ People will act more “drunk” if they are told they consumed alcohol - even if they hadn’t -​ We often want to “perform” for researchers in a study -​ Social animals = want to do what’s expected of us SOLUTION: Blinded procedures -​ Single blind = participant doesn’t know what they’re getting -​ Double blind = participant AND researcher both don’t know what the participant is getting. -​ Open label Animal Models for Research -​ Animals are used for research -​ Understand basic mechanisms, genetics, etc… -​ Because there are no viable alternatives -​ Because they have high predictive value -​ Ethical considerations are always made -​ Have a number of protections in place (e.g., CCAC, ACC). Human Research -​ Ethical considerations must also be made -​ Federally mandated committees review human research proposals -​ Informed consent. Mean, median, mode -​ Important for understanding and splitting up your data -​ Histogram diagrams. Standard deviation and standard error Standard deviation on curve graph = tells you how wide the normal curve is, e.e., how much variance there is in your data. What is p value? -​ Is our information between groups really that different, or is it the product of noise? -​ Tells you how likely it is that your data could have occurred under the null hypothesis. -​ Typically, significance level is p