Lecture Notes: Research Designs, Variables, Ethics, and Foundations of Psychological Research

Lab & Course Logistics

• Lab 1 and Lab 2 are open; Lab 1 covers material from chapter 2 (psychological research) and Lab 2 covers content starting today (chapter 3).
• Quizzes:
  • You have up to three attempts; you don’t have to use all attempts if you achieve 100%.
  • The quiz counts toward your lab grade.
• SmartBook: Chapter 3 is open and due this Sunday before the exam.
• Packback:
  • We are in the Packback era; sign up if you haven’t yet. If issues arise, email the instructor or Waverly.
  • Introduction post is now open and not graded; it gives you a chance to explore the platform.
  • Posts must be in the form of a question (e.g., "Welcome to Site 101. Who are you?"). Packback requires questions to foster curiosity and peer feedback.
  • If you encounter issues, contact the instructor.
• Alternative assignments: if you needed an alternative assignment over the weekend, please inform us by today. Later this week, Waverly will invite eligible students into a special portal for these alternatives.
• Thursday’s class format (flipped classroom) announced: two short videos to watch before class; in-class time devoted to activities and extensions on the brain, rather than long lectures.
• Today’s focus: finish Thursday’s discussion on study design, then introduce neuroscience and behavior.
• Review from last week: the big three primary research designs are descriptive, correlational, and experimental; today’s content begins with the third design (experimentation) and includes a history of ethics.
• There will be a brief recap of the distinction between research designs and research methods; emphasis on how correlations relate to causation and why experiments are needed to establish causal claims.
• Announcement: Thursday’s class will feature neuroscience content (neurons and brain) in a flipped format.

Correlation, Illusory Correlations, and Regression Toward the Mean

• Correlational designs have a strong place in psychological research; many contemporary studies are correlational (surveys, interviews, etc.).
• Illusory correlations: seeing a relationship between two variables that is not truly causal; examples include misattributing cause-and-effect from coincidental associations.
  • Simpson’s paradox example (fictional Springfield bears): an observed association may disappear or reverse when data are grouped differently.
  • A cartoon about Harris’s lucky socks: sales spikes on days with a particular employee wearing lucky socks may be due to other factors, not the socks.
• Regression toward the mean: extreme observations tend to move toward the average on subsequent measurements; this can create the illusion of a causal relationship when one did not exist.
  • Dallas Cowboys example: a player posts unusually high yards in one game; the next game is more likely closer to the average, not continuing the extreme performance.
• The phrase “correlation does not imply causation.”
  • Strong correlations do not prove that one variable causes changes in another.
  • To establish causation, we need experimentation where we manipulate an independent variable and observe effects on a dependent variable.
• Transition to experimentation: experiments allow us to test causal relationships beyond what correlational data can show.

Research Designs: Descriptive, Correlational, Experimental

• Descriptive designs
  • Describe characteristics or phenomena without examining relationships between variables.
• Correlational designs
  • Examine associations between variables (e.g., survey data), quantify strength via correlation coefficient, but cannot establish causation.
• Experimental designs
  • Manipulate one or more independent variables (IVs) and measure the effect on one or more dependent variables (DVs).
  • Aim to establish causal relationships by controlling for confounding variables.
• Key takeaway: Descriptive → describes, Correlational → associates, Experimental → tests causality.

Key Variables in Experiments

• Independent Variable (IV): the factor(s) that the researcher deliberately manipulates; can be multiple or a single variable.
• Dependent Variable (DV): the outcome measured to see the effect of the IV.
• Example 1: Reading intervention
  • IV: presence or absence of a reading intervention (or multiple levels of the intervention).
  • DV: student GPA or reading achievement.
• Example 2: Free snacks in a park
  • IV: whether snacks are offered (and possibly type of snack).
  • DV: park attendance.
• Confounding variables (confounders): other variables that influence the DV and are not intentionally manipulated.
  • Example: Weather (rain) could influence park attendance regardless of snacks.
  • Type of treat could also confound if some treats attract more people due to allergies or preferences.
• Multiple IVs: it’s possible to manipulate more than one independent variable (e.g., snack presence and snack type) and observe interaction effects.

Experimental Design Essentials: Random Sampling, Random Assignment, Blinding, Placebo, and Deception

• Random Sampling: every member of the population of interest has an equal chance of being surveyed/selected; goal is generalizability of findings.
• Random Assignment: randomly assign participants to experimental or control conditions; goal is causal inference by equalizing groups on potential confounds.
• Blind procedures
  • Single-blind: participants do not know which condition they are in; the experimenter may or may not know.
  • Double-blind: neither participants nor the researchers interacting with participants know which condition participants are in; reduces bias.
• Placebo effect
  • The expectation of receiving a treatment can produce perceived or actual improvements, even if the treatment is inert.
  • Distinction: true drug effect vs placebo effect; debriefing helps distinguish between the two.
• Deception in research
  • Deception may be permitted if IRB/ethics review deems it necessary and risk is minimal.
  • Debriefing is required after deception to explain the true purpose and methods of the study.
• Informed consent and risks
  • Participants must be informed about the general purpose, procedures, and risks/benefits; consent is voluntary.
  • For research involving medications, potential side effects and procedures must be disclosed; plans for stopping the study and resources (e.g., counseling) should be provided.

Ethics and Responsible Research: Belmont Report, IRB, and Oversight

• Belmont Report (1979) core principles:
  • Respect for Persons: treat individuals as autonomous agents; obtain informed consent; protect those with diminished autonomy; ensure privacy and confidentiality.
  • Beneficence: minimize risk and maximize benefits; assess risk/benefit balance.
  • Justice: ensure fair subject selection; protections for vulnerable populations; ensure equitable distribution of research benefits and burdens.
• Informed consent
  • Participants sign to indicate they understand the study and agree to participate; they can withdraw at any time.
  • For minors, parental consent is required; some participants may require assent from the minor.
  • Debriefing and confidentiality are explained in advance and maintained unless disclosure is legally required.
• Privacy and confidentiality
  • Data storage, handling, and access controls to protect participant privacy.
• Risk and benefit assessment
  • IRB approval hinges on whether the potential benefits justify the risks.
  • In drug trials, disclosures about possible side effects and trial stopping rules are mandatory.
• Deception and deception management
  • When deception is used, debriefing explains the true study purpose and resolves potential harm.
• Justice in subject selection
  • Special protections for vulnerable groups (e.g., children, prisoners, pregnant individuals, the elderly, people with disabilities, certain racial/ethnic groups).
  • If an effective treatment exists, researchers may need to offer it to participants in the control group after the study.
• Oversight bodies and acts
  • Institutional Review Board (IRB) for human subjects research; evaluates risk/benefit, consent processes, and whether deception is warranted.
  • Institutional Animal Care and Use Committee (IACUC) for animal research; ensures humane treatment and ethical considerations.
  • Animal Welfare Act governs animal research practices.
• Real-world ethical pitfalls highlighted
  • Tuskegee Syphilis Study: withholding treatment; exploited vulnerable populations.
  • Nazi experiments and the Nuremberg Code: foundational emphasis on voluntary consent and minimization of harm.
  • Milgram, Stanford Prison, Harlow, Little Albert, Pavlov: historical cases illustrating ethical concerns and the evolution of guidelines.
• Contemporary example from 2010: falsified data linking vaccines to autism; underscores the importance of integrity and ethics in research and public communication.

Historical Case Studies and Ethical Lessons

• Pavlov’s classical conditioning (dogs): demonstrated learning via association; raised questions about animal welfare and humane treatment.
• Little Albert (John B. Watson and Rosalie Rayner): conditioned fear in a child using a white rat; raised concerns about consent and psychological harm.
• Milgram’s obedience experiments: shocking learners under instructions; highlighted obedience to authority vs ethics of psychological harm.
• Stanford Prison Experiment (Zimbardo): role assignment leading to harm; emphasized safeguards and ethics in social roles and manipulation.
• Harlow’s monkeys: attachment deprivation with cloth vs wire surrogate mothers; significant animal welfare concerns.
• Tuskegee Syphilis Study: long-term withholding of treatment; led to strengthened protections in human subjects research.
• Nazi medical experiments: extreme violations; contributed to the development of the Nuremberg Code and modern ethical standards.
• Contemporary ethics discussions: ensure informed consent, risk minimization, voluntary participation, and equitable treatment.
• These cases inform today’s practice, emphasizing the need for IRB oversight, debriefing, consent, and balancing risk/benefit.

Guidelines for Conducting Ethical Research on Humans and Animals

• Human subjects:
  • Obtain IRB approval before starting; ensure alignment with Belmont principles.
  • Ensure informed consent, voluntariness, and the right to withdraw.
  • Protect privacy and confidentiality; disclose potential risks and benefits.
  • Use deception only when necessary and with debriefing after the study.
  • Minimize risk; provide resources if participation causes distress; offer post-study benefits when appropriate.
  • Ensure fair and just subject selection; consider vulnerable populations carefully.
• Animal subjects:
  • Follow IACUC guidelines and the Animal Welfare Act.
  • Justify animal use and ensure humane treatment; minimize suffering and number of animals used when possible.
• Data integrity and reporting:
  • Avoid falsification, fabrication, or manipulation of data.
  • Transparently report methods and results to support replication and verification.

Practical Takeaways and Real-World Relevance

• The most important element in research is ethics and the alignment of values with scientific methods; grounding research in an ethic of care.
• When planning studies, consider:
  • The purpose of random sampling vs random assignment: generalizability vs causality.
  • How blinding and placebo controls help separate true effects from expectations.
  • The potential confounds and how they will be controlled (e.g., random assignment, standardization of procedures).
  • How to handle deception ethically (IRB approval, debriefing).
• The upcoming session will shift toward neuroscience and behavior, including neurons and brain structures; preparation by reviewing today’s material on design and ethics will help with understanding brain-behavior relationships.

Key Formulas and Concepts (quick reference)

• Correlation coefficient (conceptual): a measure of the strength and direction of the linear relationship between two variables; does not imply causation.
• Formal relation for correlation (for interested students):
  $r = \frac{\text{cov}(X,Y)}{\sigma<em>X \sigma</em>Y}$
• Independent variable (IV) and dependent variable (DV) definitions:
  • IV: the factor intentionally manipulated by the researcher.
  • DV: the outcome measured to assess the effect of the IV.
• Belmont Report principles (summarized):
  • Respect for Persons: autonomy, consent, privacy.
  • Beneficence: minimize risk, maximize benefits.
  • Justice: fair participant selection and access to benefits.

Connections to Previous Lectures and Real-World Relevance

• Built on last week’s distinction between descriptive, correlational, and experimental designs; today’s focus deepens the understanding of experimental control and causality.
• Emphasizes why most published psychology findings rely on care in design, analysis, and ethical conduct to ensure valid, generalizable, and humane science.
• Real-world relevance includes how ethical guidelines govern clinical trials, educational research, and any study involving human or animal subjects, and why hospitals, universities, and research organizations maintain rigorous oversight.

Preview: Neuroscience and Behavior (Thursday)

• Thursday’s class will be flipped: two short videos to watch before class; in-class activities will extend learning about particular brain areas and their roles in behavior.
• Instructor will post announcements after class today with access to the pre-class videos.
• Expect to engage in hands-on activities to apply concepts from today’s lecture to neural mechanisms and behavior.