Health Research Exam 1

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Pseudoscience

the use of seemingly scientific terms and demonstrations to substantiate claims that are not based on scientific research. The claim may be that a product or procedure will enhance your memory, relieve depression etc. The fact that these are are worthy outcomes makes us very susceptible to believe pseudoscience claims and forgetting to ask whether there is a valid scientific basis for the claims.

Empiricism

 the idea that knowledge comes from systematic observations, which are observations that are made intentionally, purposefully anf consistently.

Falsifiability

Falsifiability (testable hypotheses)is  Good scientific ideas are testable which means they can either be supported or falsified by data –The latter concept is called falsifiability. If an idea is falsified when it is tested, science advances because this result can spur the development of new and better ideas

Peer Review

the process of judging the scientific merit of research through review by other scientists with the expertise to evaluate the research

Skepticism

an approach to claims about the world that rejects unquestioning acceptance. Instead claims are met with an insistence on examining and evaluating evidence given to support the claims.

Replication -

other researchers will replicate the research done by other scientists to evaluate the significance of results. There are different types of replication. Exact replication is where they use the EXACT same procedures used in the original research. Ff results are significant you conclude that they would be obtained over and over again if the study were repeated. Conceptual replication uses diferent procedures to manipulate and measure the same variables.

Cause-effect and types of causal inference:

Cause-effect: determining cause and explaining behavior are particularly closely related because it is difficult ever to know the true cause or all the causes of any behavior (temporal precedence: part of causal inference; the cause occurs before the effect, covariation of cause & effect - part of causal inference; observing that a change in one variable is accompanied by a change in a second variable; alternative explanation: part of a causal inference; a potential alternative cause of an observed relationship between variables)

Goals: describe, predict, determine cause and effect, explain -

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Basic Research vs Applied research vs program evaluation

Basic Research: tries to answer fundamental questions about the nature of behavior. Applied Research: is conducted to address issues in which there are practical problems and potential solutions. (e.g., program evaluation: a major area of applied research is called program evaluation which assesses reforms and innovations in government, education, the criminal justice system, health care etc.)

• Hypothesis & Hypotheses (Predictions); Theory

• = Hypothesis: the hypothesis is a formal statement that specifies how the variables being studies are related.  & Hypotheses (Predictions: a statement of the expected outcome of a research investigation ); Theory - A broad, comprehensive, and well-substantiated explanation for a wide range of natural phenomena. Developed after a family of hypotheses and observations have been repeatedly tested, evaluated, and confirmed by the scientific community over time. It integrates a vast body of evidence, laws, and facts to explain why something happens (for example, the Theory of Evolution or General Relativity).

Participants (subjects)

- In research, a subject (also called an experimental unit, respondent, or participant) is the core individual, animal, object, or entity that is being studied or experimented upon to collect data.

PsychArticles; Google Scholar; Keywords

PsychArticles; Google Scholar; Keywords: using AND means forces both conditions to be true for an article to be included. The parentheses are used to separate different parts of your search specification and are useful when your searches become increasingly complicated. OR Is used to expand a search that is too narrowSuppose you want to find articles that discuss romantic relationships on the internet.A search for internet AND Romance. NOT Is an important tool because it will exclude sources based on the Criterion you specify. This is used to get rid of irrelevant abstracts for example searching “internet AND romance NOT predators.”

Empirical Research Article; Literature Review; meta-analysis

Empirical Research: Research that uses observation, measurement, or collected data to investigate a question and produce findings.

Example: Researchers recruit 100 college students and measure their stress levels and sleep quality to investigate whether stress is associated with poor sleep.

Remember: Researchers conduct an original investigation and analyze data. - - - - - Literature Review: Literature reviews provide summaries of previous research on a particular topic. Traditionally literature reviews were narrative descriptions of individual research investigations along with conclusions controversies and directions for future research. Example: Researchers read 20 previously published studies about stress and sleep, then summarize what those studies found.

Remember: Researchers examine and discuss what other studies have found rather than conduct a new study with participants. - - - - -   meta-analysis: A more quantitative review method for comparing large number of studies in a specific research area is called meta-analysis. With meta-analysis researchers attempt to determine if a research finding is the same across multiple studies. Example: Researchers gather 20 studies investigating the relationship between stress and sleep. They statistically combine the results to estimate how strongly stress and sleep are related overall.

Remember: Researchers combine the statistical results of multiple studies to reach a broader conclusion

Sections of an article (abstract, introduction, method, results, discussion) - ??

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• Belmont Report (beneficence, autonomy, justice)

• - after the highly unethical Tuskegee study and other unethical studies, a committee was formed that eventually produced the Belmont Report. This was the third critical document in the development of ethical standards in Behavioral Science. This report defined the principles and applications that have guided more detailed regulations developed by the American Psychological Association and other professional societies. >>>> The three basic ethical principles of the Belmont Report are: 1. Principle of beneficence - Research should confer benefits and risks must be minimal. The associated application is the necessity to conduct a risk benefit analysis. 2. Principle of respect for persons (Autonomy): Participants are treated as autonomous. They are capable of making deliberate decisions about whether to participate in research. The associated application is informed consent— Potential participants in a research project should be provided with all information that might influence their decision on whether to participate. 3. Principle of Justice - There must be fairness in receiving the benefits of research as well as bearing the burdens of accepting risksThis principle is applied in the selection of subjects for research.

 Informed Consent; active and passive consent; assent

- Informed Consent: Potential participants in a research project should be provided with all information that might influence their active decision of whether or not to participate in a study. active and passive consent: Passive consent is when someone’s agreement or permission is assumed because they do not actively object or refuse. Example: In a research study, parents receive a letter explaining that their child will participate unless they return a form saying they do not want their child involved. assent: Assent is when someone who cannot legally provide informed consent, such as a child, expresses their willingness to participate in something, such as a research study. Example: A researcher obtains parental consent for a 10-year-old child to participate in a study. The researcher also asks the child whether they want to participate. If the child agrees, they have given assent.

Populations requiring special protection

-Groups of people who may be more vulnerable to harm, coercion, or exploitation in research, or who may have difficulty providing informed consent. Researchers must take additional precautions to protect their rights and well-being. Examples: Children, prisoners, pregnant women, people with impaired decision-making abilities, and economically disadvantaged individuals.

• Anonymity, Confidentiality, Coercion

• - - Anonymity: When a participant's identity is completely unknown and cannot be connected to their research responses, even by the researcher. Example: Participants complete a survey without providing their names or any identifying information. Confidentiality: When researchers may know participants' identities but protect their personal information from being shared without permission.

Example: A researcher interviews patients about their mental health but stores their names and responses securely and does not reveal their identities.

- Coercion: When someone uses threats or pressure to force another person to participate in research against their wishes. Example: A professor threatens to lower students' grades if they refuse to participate in a research study.

IRB (exempt research, expedited research, full review research) -

IRB (Institutional Review Board) - IRB = A committee that reviews research involving human participants to ensure that it is ethical, minimizes risks, and protects participants' rights and safety. There are three main levels of IRB review: 1. Exempt research: Research that falls into specific low-risk categories and is exempt from certain ongoing IRB review requirements. It must still be determined to qualify for exemption. Example: An anonymous survey asking adults about their study habits. Expedited research: Research involving no more than minimal risk that qualifies for review by an IRB chairperson or designated reviewer rather than the entire committee. Example: Collecting small blood samples from healthy adult volunteers under qualifying conditions. Full board review: Research that requires review by the entire IRB committee, typically because it involves greater than minimal risk or does not qualify for the other categories. Example: Testing an experimental medical treatment that could cause significant side effects.

Plagiarizing -

misrepresenting another’s work as your own

Fraud -

Intentionally deceiving others by fabricating (making up) or falsifying (manipulating) research data, methods, or results.

variable

Variable: any characteristic, number, quality, or condition that varies—that is has at least two values

Constant -

A constant variable, sometimes known as a control variable, is something you keep the same during an experiment.

Type of Variables - e.g., Mediating, Moderating

= Mediating variable (mediator): A variable that explains how or why one variable influences another. Example: Researchers find that exercising improves mood. Improved sleep quality may be a mediating variable because exercise improves sleep, which then improves mood. Moderating variable (moderator): A variable that changes the strength or direction of the relationship between two other variables. Example: Researchers examine whether studying improves test scores. Test difficulty may be a moderating variable because the relationship between studying and test performance may differ depending on how difficult the test is. - - - - - Mediator = WHY or HOW? It explains the mechanism connecting two variables.

• Moderator = WHEN, FOR WHOM, or HOW MUCH? It changes the relationship between two variables.

operational definition

definition of a concept that specifies the method used to measure or manipulate the concept. Example: A researcher studying anxiety defines it as participants' scores on a standardized anxiety questionnaire.

Correlation - positive, negative; linear, curvilinear

= Correlation refers to a statistical relationship between two variables. It describes how variables change in relation to one another, but does not establish that one causes the other. Positive correlation: When two variables move in the same direction. As one increases, the other tends to increase (or both decrease). Example: The more hours students study, the higher their test scores tend to be. Negative correlation: When two variables move in opposite directions. As one increases, the other tends to decrease. Example: The more hours someone spends exercising, the lower their reported stress levels may be. Linear correlation: A relationship between two variables that follows an approximately straight-line pattern. It can be positive or negative. Example: As the number of hours studied increases, test scores consistently tend to increase. Curvilinear correlation (nonlinear relationship): A relationship between two variables that follows a curved pattern rather than a straight line. The direction or strength of the relationship changes at different levels. Example: Moderate anxiety might be associated with better test performance than either very low or very high anxiety, creating an inverted U-shaped relationship.

Correlational Design; causation and the Third Variable Problem

Correlational design: A research method that examines relationships between variables without the researcher manipulating them. Example: Researchers measure how many hours students sleep and their academic performance to see whether the two are related. Causation: When a change in one variable directly produces a change in another variable. Example: In a well-controlled experiment, researchers demonstrate that a particular teaching method causes students to perform better on a test. Third-variable problem: When two variables appear related, but an additional, unaccounted-for variable may actually explain their relationship. Example: Researchers find that children with larger shoe sizes have better reading skills. However, age is a third variable: older children generally have larger feet and more developed reading skills. ***Important: Correlation does not prove causation because researchers cannot automatically determine whether A causes B, B causes A, or another variable influences both. This includes the directionality problem, where it is unclear which variable influences the other.

Confounding Variable(s)

- A confounding variable is an additional variable that changes systematically with the independent variable and could influence the dependent variable, making it difficult to determine what actually caused the results.

• Experiment; (Manipulated Variables) Independent Variables; Dependent Variables = Experiment:

• A research method in which researchers deliberately manipulate an independent variable, measure its effect on a dependent variable, and control other factors to test cause-and-effect relationships. Independent variable (IV): The variable that researchers deliberately change or manipulate to see whether it affects another variable. Dependent variable (DV): The variable that researchers measure to determine the effect of the independent variable. It is the outcome or participant response being studied. Example: Researchers want to determine whether sleep deprivation affects memory.

- IV: Hours of sleep (researchers assign participants different sleep durations). >>> DV: Memory performance (measured through test scores). The researchers manipulate sleep duration and measure how participants perform on a memory test. Remember: Independent variable = what researchers change. Dependent variable = what researchers measure.

Field vs. Laboratory

- Field research: Research conducted in a natural, real-world environment where participants typically behave as they would in everyday life. - Laboratory research: Research conducted in a controlled environment where researchers can more easily regulate conditions and eliminate outside influences.

Validity of a study:  construct, internal, external

Validity of a study:  construct, internal, external = Validity refers to how accurately and appropriately a study measures what it intends to measure and supports the conclusions researchers draw. Construct validity: Are we measuring what we think we are measuring? Internal validity: Can we confidently establish cause and effect? External validity: Do the findings apply beyond this study?

Reliability - test-retest; internal consistency (e.g., Cronbach’s alpha); interrater -

Reliability - test-retest; internal consistency (e.g., Cronbach’s alpha); interrater - the degree to which a measure is consistent. - Test-retest reliability: The extent to which a measure produces consistent results when administered to the same individuals at different times, assuming the characteristic being measured has not changed. Example: A student takes an intelligence test twice, one week apart, and receives very similar scores both times. Internal consistency: The degree to which different questions or items on the same test consistently measure the same underlying concept. Example: A questionnaire measuring anxiety contains 10 questions. If all 10 questions measure anxiety effectively, participants' responses should generally be consistent across the items. Cronbach's alpha (α): A statistic commonly used to assess the internal consistency of a questionnaire or test. It measures how closely related the items are as a group. Example: Researchers create a 15-question depression questionnaire and calculate Cronbach's alpha to determine whether the questions consistently measure the same underlying construct. Important: A high Cronbach's alpha does not automatically mean a test is valid or that it measures only one construct. - Interrater reliability: The degree to which two or more observers or researchers agree in their observations, judgments, or ratings. Example: Two psychologists independently observe the same child and record the number of aggressive behaviors displayed. If their observations are similar, the study has high interrater reliability.

Validity - face, content, predictive, concurrent, convergent, discriminant - Face

Validity refers to how accurately a test or measurement tool measures what it is supposed to measure.

The six types can be confusing because they all assess validity in slightly different ways. I'm going to use the same example—a researcher creating a new anxiety questionnaire—to help you see the differences.

1. Face Validity

Definition: The extent to which a test appears to measure what it is supposed to measure.

Example: A researcher creates an anxiety questionnaire with questions like "Do you frequently feel nervous?" and "Do you worry excessively?"

These questions seem relevant to anxiety, so the questionnaire has good face validity.

Remember: Does the test LOOK like it measures the right thing?

2. Content Validity

Definition: The extent to which a test adequately covers all important aspects of the concept being measured.

Example: A researcher creates an anxiety questionnaire that measures excessive worrying, physical symptoms (like a racing heart), and difficulty relaxing.

Because it covers multiple important aspects of anxiety rather than just one, it has better content validity.

Remember: Does the test cover EVERYTHING important about the concept?

3. Predictive Validity

Definition: The extent to which a test accurately predicts a relevant future outcome.

Example: Researchers give students an anxiety questionnaire at the beginning of the semester. Students who score higher tend to experience greater anxiety-related difficulties later in the semester.

This provides evidence of predictive validity because the questionnaire predicts a future outcome.

Remember: Can the test predict something that happens in the FUTURE?

4. Concurrent Validity

Definition: The extent to which a test's results agree with a relevant established measure or criterion assessed at approximately the same time.

Example: Researchers give participants a new anxiety questionnaire and also have a psychologist evaluate their current anxiety levels on the same day.

If the questionnaire scores agree closely with the psychologist's assessments, this supports concurrent validity.

Remember: Does the test agree with another relevant assessment conducted at the SAME TIME?

5. Convergent Validity

Definition: The extent to which a test produces results that are strongly related to other measures of the same or closely related concepts.

Example: Researchers compare their new anxiety questionnaire with a different, well-established anxiety questionnaire.

If people who score high on one also tend to score high on the other, this supports convergent validity.

Remember: Do tests measuring SIMILAR things produce similar results?

6. Discriminant Validity

Definition: The extent to which a test is not strongly related to measures of different, theoretically unrelated concepts.

Example: Researchers compare scores on their anxiety questionnaire with participants' height.

Because height and anxiety are theoretically unrelated, researchers would not expect a strong relationship between the two.

If the questionnaires' scores are not strongly associated with height, this is consistent with discriminant validity.

Remember: Does the test distinguish between DIFFERENT, unrelated concepts?Important distinction: Reliability is about consistency, while validity is about accuracy. A test can be reliable without being valid.

Measures – reactive (nonreactive); nominal, ordinal, interval, ratio.

Measures – reactive (nonreactive); nominal, ordinal, interval, ratio. - nominal being the least precise and informative and interval/ratio variable being most precise and informative. Ratio — True zero, all maths (e.g. height, weight, age) - Interval — Equal gaps, no true zero (e.g. °C, IQ, years) - Ordinal — Ordered, unequal gaps (e.g. Likert, grades)- - Nominal — Labels only (e.g. gender, blood type)

Naturalistic observation; systematic observation

= Naturalistic observation = observing behavior in its natural setting. Systematic observation = observing behavior using predetermined rules and specific behavioral categories.

Participant observer

- A researcher who actively participates in the group or situation being studied while observing the behaviors and interactions of others. -

unobtrusive observer -

A researcher who observes behavior while minimizing their presence or influence so that participants behave as naturally as possible.

Case Study -

Case Study - A descriptive account of the behavior, past history and other relevant factors concerning a specific individual.

Archival Research (historical records, media etc.  e.g., content analysis) =

Archival research: A research method in which researchers analyze existing records, documents, or previously collected data to investigate research questions. Example: Researchers examine hospital records from the past 20 years to investigate changes in rates of diagnosed depression. - Content analysis: A systematic method of examining and categorizing information within written documents, media, recordings, or other materials to identify patterns, themes, or frequencies. Example: Researchers examine magazine advertisements from the 1950s to the present and record how often women are portrayed in traditional household roles. - Remember: Archival research = studying existing information. Content analysis = systematically examining and categorizing the content of information.

Survey vs. interview -

Survey: A research method that collects information from participants through a set of questions about their behaviors, experiences, beliefs, or opinions. Interview: A research method in which a researcher asks participants questions directly, usually through a conversation. Interviews can allow researchers to ask follow-up questions and explore answers in greater detail.

Demographic survey items -

Demographic survey items are questions that collect information about participants' background characteristics to describe the sample or compare different groups. Examples: Age, gender, race or ethnicity, education level, employment status, and household income.

Problems: Loaded questions (social desirability); Double-barreled quest.; Response set

== Loaded question: A question that contains emotionally charged language or assumptions that may pressure participants toward a particular answer. Example: "Don't you agree that the school's ridiculous new attendance policy is unfair?" - - Social desirability bias: When participants provide answers they believe will make them appear more socially acceptable rather than answering completely honestly. Example: A student reports studying five hours every day because they want to appear hardworking, even though they usually study only one hour. Double-barreled question: A question that asks about two or more separate issues but only allows participants to provide one answer. Example: "Are you satisfied with your professors and your academic workload?" A student might like their professors but dislike their workload, making the question difficult to answer accurately. Response set (response style): A tendency to answer survey questions according to a consistent pattern rather than carefully considering the content of each question. Example: A participant repeatedly selects "Strongly Agree" on a questionnaire, regardless of what the statements say.

Positively and negatively keyed questions

== Positively keyed question: An item where agreement indicates a higher level of the characteristic being measured. Example: On a questionnaire measuring self-esteem, the statement "I feel good about myself" is positively keyed because agreeing indicates higher self-esteem. - Negatively keyed question: An item where agreement indicates a lower level of the characteristic being measured. Example: On the same self-esteem questionnaire, the statement "I often feel worthless" is negatively keyed because agreeing indicates lower self-esteem.

Open ended & closed ended -

]- Open-ended questions: Questions that allow participants to answer freely in their own words without being limited to predetermined response options.  - - - Closed-ended questions: Questions that provide participants with a set of predetermined answers from which they must choose.

Likert type items (also in class – reverse coding & scoring of responses)

- Likert-type item: A survey statement that asks participants to indicate their level of agreement, disagreement, or another ordered response. Example 5 point scale from strongly agree to strongly disagree. Reverse coding (reverse scoring): A scoring procedure that reverses the numerical values of certain questionnaire responses so that all items are scored in the same direction. Scoring of responses: The process of assigning numerical values to survey answers and combining or analyzing them according to the questionnaire's scoring instructions. Example: A researcher administers a five-item self-esteem scale. After reverse-coding any necessary items, the researcher adds the five responses to calculate a total self-esteem score.

Pilot procedures (Cronbach’s alpha again relevant) -

Pilot testing = a trial run to identify and correct problems before the main study. Cronbach's alpha =  During pilot testing, researchers may calculate Cronbach's alpha to evaluate whether items intended to measure the same construct demonstrate adequate internal consistency.

Probability sampling (random, stratified random)

= = = Probability sampling is a sampling method in which every member of the population has a known, nonzero chance of being selected. Simple random sampling: A probability sampling method in which every individual in the population has an equal chance of being selected. Stratified Random Sampling: a probability sampling method in which a population is divided into subpopulation groups called strata; individuals are then randomly sampled from each of the strata.

Non-probability sampling (convenience, quota)

= = = Non-probability sampling is a sampling method in which participants are selected without a probability-based random selection process, meaning their probabilities of selection are not all known. Convenience sampling: A non-probability sampling method in which participants are selected because they are easily accessible, available, or willing to participate. Quota sampling: A non-probability sampling method in which researchers establish a predetermined number or proportion of participants from different subgroups, then select individuals nonrandomly until each quota is filled.

Factorial design

Factorial design - A research design that examines two or more independent variables simultaneously, including how they may interact to affect a dependent variable.

Numeric designations of designs (e.g., 2 x 2) -

Numbers that indicate how many independent variables a study has and how many levels each variable contains. A 2 × 2 design has two independent variables, each with two levels, creating four experimental conditions.

Main effect & interaction

=== Main Effect: The overall effect of one independent variable on the dependent variable, averaged across the levels of the other independent variables. Interaction Effect: When the effect of one independent variable on the dependent variable depends on the level of another independent variable.

Program evaluation (needs assessment, implementation, outcomes, summative evaluation)

= =  Program Evaluation: The systematic process of determining whether a program is working, achieving its goals, and how it can be improved. - Needs Assessment: Identifying the problems or needs of a population to determine what services or programs are necessary. - Implementation Evaluation: Examining whether a program is being carried out as planned. - Outcome Evaluation: Measuring whether a program achieved its intended results or goals. - Summative Evaluation: Evaluating a program's overall effectiveness or value, typically after it has been implemented, to help determine whether it should continue, change, or end.

Developmental research - cross-sectional, longitudinal

= = Developmental Research: Research that examines how people grow, develop, and change over time. - Cross-Sectional Design: A research design that compares different age groups at the same point in time. - - Longitudinal Design: A research design that follows the same participants over an extended period to observe changes. - -Remember: Cross-sectional = different people at one time. Longitudinal = same people over time.

Confounds:  history, maturation, testing, statistical regression

== These are common threats to internal validity, meaning they can provide alternative explanations for a study's results.- History: Outside events occurring during a study that may influence the results, independently of the treatment. - Maturation: Natural physical or psychological changes in participants over time that may affect the results. - Testing Effect: When taking a test influences participants' performance on a later test, such as through practice or familiarity. - Statistical Regression (Regression to the Mean): The tendency for unusually high or low scores to become less extreme when measured again, especially when scores contain random variation. Example of statistical regression: Researchers select students who performed exceptionally poorly on a test. When those students take the test again, their scores improve somewhat, even without an effective intervention. This improvement could reflect regression to the mean rather than the treatment.

Single participant, Reversal design (ABA)

Single participant, Reversal design (ABA) = Single-Participant (Single-Subject) Research: A research approach that studies an individual's behavior repeatedly under different conditions to examine the effects of an intervention. These designs can also be used with a small number of individuals. Reversal Design (ABA): A single-subject design that measures behavior during three phases:

• External validity

= The extent to which a study's findings can be applied to other people, settings, situations, or time periods.

Generalization

Generalization - involves making broad or general inferences based on prodesures and findings in a specific study

Exact replication, conceptual replication 

Exact replication, conceptual replication  = = Exact Replication (Direct Replication): Repeating a previous study as closely as possible, using the same methods and procedures, to determine whether similar results can be obtained. Conceptual Replication: Testing the same hypothesis as a previous study but using different methods, procedures, or measurements to determine whether the findings still hold. Remember: Exact replication = repeat the study as closely as possible. Conceptual replication = test the same idea in a different way.

Appendix A all questions

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Classroom discussions all questions

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Manipulated independent variables -

the factor in an experiment that the researcher intentionally changes to test its effect on a dependent variable.

Strong manipulations

of an independent variable  is a deliberate, precise, and substantial change to the independent variable  that produces a clear, measurable effect on the dependent variable , while controlling all other factors to ensure internal validity

Pilot study

A pilot study is a small-scale trial run of a research project’s procedures conducted before the main study to test feasibility, identify design flaws, and refine methods

Manipulation check

- A manipulation check is a measure used in experimental research to verify that the independent variable produced the intended psychological, perceptual, or cognitive effect on participants. Per ex. Checking that participants noticed the independent variable in a study about seeing how people react to the emotion of the person cutting them in line, it's checking that participants notice whether that person is upset or not. Because if they do not the manipulation is not working.

Sensitivity of dependent variables

how much a dependent variable's value changes in response to variations in one or more independent variables, typically measured through sensitivity analysis.

Demand characteristics;

cues in an experimental setting that hint at the researcher’s hypotheses, leading participants to change their behavior—consciously or unconsciously—to match what they think is expected.

The placebo effect

is the effect where the perception that a treatment works makes it work. For example taking a sugar pill instead of a psychiatric medication will Have the patient experiencing some of the effects. These are related because it is the participants' response to thDemand characteristics that creates the placebo effect.

Experimenter expectancy

a type of experimenter bias where a researcher’s expectations about an outcome are unintentionally communicated to participants, influencing their behavior and the results.

Rosenthal Pygmalion study

an example of Experimenter expectancy - 1968 study Pygmalion in the Classroom. All students in a California elementary school took an IQ test. Teachers were told that about 20% of students  chosen at random were “intellectual bloomers” expected to show exceptional growth that year Teachers were unaware that the selection was random; the label was implanted in their expectations.The “bloomers” showed significantly greater IQ gains than peers, supporting the idea that positive expectations can improve performance 

Double-blind study

• an experiment in which neither the participants nor the researchers know who receives the real treatment or the placebo, reducing bias and improving the validity of results.

Extraneous Variable

Any variable other than the independent variable that could influence the dependent variable - Example: Researchers study how caffeine affects test scores. Participants' sleep quality is an extraneous variable because it could also affect their performance.

Confounding Variable:

A type of extraneous variable that systematically differs between experimental conditions, making it difficult to determine what actually caused the results.

Example: Researchers give caffeine to one group that studies in a quiet room and no caffeine to another group that studies in a noisy room. Noise level is a confounding variable because it differs between groups and could affect test scores. - Key difference: Extraneous variables are potential outside influences, while confounding variables create alternative explanations for the results.

Internal validity:

The extent to which researchers can confidently conclude that the independent variable caused changes in the dependent variable.

- Selection Effect (Selection Bias) and its solution

When experimental groups have preexisting differences that could influence the results, especially when participants are not randomly assigned.

Example: Researchers compare a voluntary exercise group with a non-exercise group. The exercise group may already be healthier or more motivated. Solution: Random assignment to conditions.

Mortality Bias (Attrition): and its solution?

Example: In a study testing a difficult exercise program, many participants who struggle with the exercises drop out. The remaining participants may make the program appear more effective than it actually is.

Solution: Minimize dropout, examine who dropped out, and use appropriate methods to address missing data.

- Testing Effect: and its solution

When completing an initial test influences participants' performance on a later test.

Example: Students perform better on a memory test the second time simply because they remember questions from the first test.

Solution: Use a posttest-only design, appropriate control groups, or alternative versions of the test.

- Order Effect: and its solution

When the order in which participants experience experimental conditions influences their performance or responses.

Example: Participants complete two memory tasks. They perform better on the second task because they have already practiced the first.

Solution: Counterbalancing — vary the order of conditions across participants so that some complete Task A first and others complete Task B first.

Important: Counterbalancing helps control order effects specifically, not all threats to internal validity.

Assignment to Conditions

The process of determining which experimental conditions participants will experience.

Random Assignment:

- Random Assignment: Participants are assigned to experimental conditions by chance to reduce preexisting differences between groups.

Example: Researchers flip a coin to determine whether each participant joins the treatment group or control group.

- Repeated Measures (Within-Subjects Design):

A design in which the same participants experience all experimental conditions.

Example: Researchers measure the memory performance of the same participants after drinking coffee and after drinking water.

- Pretest-Posttest Design

A design in which researchers measure participants before and after an intervention to examine changes.

Example: Researchers measure students' anxiety levels before and after an eight-week mindfulness program.

Matched Pairs Design

A design in which researchers pair participants with similar characteristics and assign each person to a different experimental condition.

Example: Researchers pair students with similar IQ scores, then randomly assign one student from each pair to a new teaching method and the other to a traditional method.