Research Methods in Psychology: Foundations, Designs, and Validity

Week 2: Research Methods

Introduction to Research in Psychology

Research methods are essential in psychology for systematically investigating questions about behavior, cognition, and emotion. Scientific research helps to challenge assumptions, solve real-world problems, and understand complex phenomena.

• Facilitated Communication: Example of why rigorous research is needed to test claims and avoid bias.

• Research Questions: Begin with curiosity about common sense assumptions, real-world observations, problem-solving, or understanding mechanisms.

Formulating Research Questions

Developing a research question is the first step in the scientific process. It guides the study's design and methods.

• Sources of Questions:

  • Common sense assumptions

  • Observations in the real world

  • Solving real-world problems

  • Understanding how something works

Sampling and Participants

Populations vs. Samples

Researchers must define who will participate in their studies. The distinction between populations and samples is crucial for generalizability.

• Population: The entire group of interest (e.g., all PSYC1010 students at York).

• Sample: A smaller group drawn from the population (e.g., 20 students who participate in the study).

Random Selection and Generalizability

Random selection ensures that every member of the population has an equal chance of being chosen, which is vital for making findings generalizable.

• Importance:

  • Accurately represents the population

  • Reduces selection bias

  • Essential for experiments seeking generalizability

Operational Definitions

Variables and Operationalization

Operational definitions translate abstract concepts into measurable and observable procedures.

• Variable: Any factor or characteristic that can vary.

• Operational Definition: Specifies how a variable is measured or manipulated in a study.

• Examples:

  • Studying aggression in children: Number of aggressive acts observed during play.

  • Measuring stress levels in university students: Scores on a standardized stress questionnaire.

Overview of Research Designs

The Methods Toolbox

Psychological research employs various methods, each suited to different types of questions.

• Descriptive Methods:

  • Naturalistic observation

  • Case study

  • Self-report measures and surveys

• Correlational Designs: Examine relationships between variables.

• Experimental Designs: Test cause and effect by manipulating variables.

Validity in Research

Internal and External Validity

Validity refers to the accuracy and applicability of research findings.

• Internal Validity: How well a study is conducted; the degree to which it establishes a trustworthy cause-and-effect relationship.

• External Validity: The extent to which findings generalize to real-world settings.

Descriptive Research Methods

Naturalistic Observation

Observing behavior in its natural environment without intervention.

Advantages	Disadvantages
High external validity (generalizable) Rich, detailed information Sometimes the only possible option	Lack of control Time and resource consuming Observer bias Cannot draw cause & effect conclusions

• Example: Observing how often university students use laptops in class for non-class-related reasons.

Case Studies

In-depth analysis of a single person or setting, often used for rare or unusual phenomena.

• Advantages: Rich, detailed descriptions; useful for rare cases.

• Disadvantages: Low external validity; researcher bias.

• Example: Studying individuals with rare brain injuries.

Self-Report/Survey Methods

Collecting data by asking participants to describe their own behaviors, attitudes, or perceptions.

• Issues:

  • Careless or random responding

  • Misunderstanding questions

  • Response bias (e.g., social desirability)

Evaluating Measures: Reliability and Validity

Reliability

Reliability refers to the consistency of a measure.

• Test-Retest Reliability: Consistency across time points. $r = \text{correlation between Time 1 and Time 2 scores}$

• Inter-Rater Reliability: Consistency across different raters. $\kappa = \text{Cohen's kappa, extent of agreement}$

Validity

Validity is the extent to which a measure assesses what it claims to measure.

• High Validity: The measure accurately reflects the intended construct.

• Example: A feline preference scale using a 1-7 Likert scale to measure how much a person likes cats.

Correlational/Non-Experimental Methods

Correlation Coefficient

Correlational studies examine the strength and direction of relationships between variables.

• Correlation Coefficient ($r$): Ranges from -1.0 to +1.0. $-1.0$ = perfect negative, $+1.0$ = perfect positive, $0$ = no relationship.

• Scatter Plots: Visualize relationships between variables.

• Examples: Texting speed & relationship drama; video games & aggression.

Correlation vs. Causation

Correlation does not imply causation. Relationships may be due to third variables or confounds.

• Possible Explanations:

  • A causes B

  • B causes A

  • A and B are both influenced by a third variable

• Third Variable Problem: An outside factor creates a false association.

Pros and Cons of Correlational Designs

Advantages	Disadvantages
Establish trends across large data Describe behavior Predict future behavior Useful when experiments are unethical	Cannot infer causality Third-variable/confounding issues

Experimental Methods

Experimental Design

Experiments test causal relationships by manipulating variables and randomly assigning participants.

• Independent Variable (IV): Manipulated by researcher; has different levels/conditions.

• Dependent Variable (DV): Measured outcome affected by IV.

• Random Assignment: Ensures groups are equivalent at the start.

• Control Condition: Basis for comparison; lacks manipulation.

• Example: Does listening to music improve test performance? IV = music exposure; DV = test scores; control = no music.

Confounding Variables

Confounds are variables other than the IV that may affect the DV, threatening internal validity.

• Example: Mood induction via music and its effect on tipping behavior; confounds could include prior mood, personality, or environment.

Experimental Bias and Expectancy Effects

Biases can arise from researcher expectations or participant awareness of the study's purpose.

• Expectancy Effect: Changes in participant behavior due to researcher expectations.

• Demand Characteristics: Participants guess the study's purpose and alter behavior.

• Solution: Use double-blind designs and conceal study purpose.

Ethical Guidelines in Psychological Research

Ethical Principles

Ethics are fundamental to protect participants and maintain integrity in research.

• Informed Consent: Participants must be informed about the study and consent to participate.

• Protection from Harm: Minimize physical and psychological risks.

• Deception and Debriefing: Deception is allowed only when necessary and must be followed by full debriefing.

• Special Populations: Minors require assent; additional protections may apply.

Historical Example: Tuskegee Syphilis Study

Ethical guidelines have evolved in response to past abuses, such as the Tuskegee Syphilis Study, where participants were not informed of their diagnosis and denied treatment.

• Lesson: Importance of transparency, informed consent, and participant welfare.

Summary Table: Major Research Methods

Method	Main Purpose	Key Features
Naturalistic Observation	Describe behavior in real-world settings	No intervention; high external validity
Case Study	In-depth analysis of individuals/settings	Rich data; low generalizability
Self-Report/Survey	Collect subjective data	Efficient; subject to bias
Correlational Design	Examine relationships	No manipulation; cannot infer causality
Experimental Design	Test cause and effect	Manipulation; random assignment

Additional info: Expanded definitions, examples, and context provided for clarity and completeness.