Psychology 242, Dr. McKirnan

1. Psychology 242, Dr. McKirnan Right click for “full Screen” or “end show”. Left click to proceed, 1/6/10 Lectures 2: Core features of a research study. General types of research designs.

2. Introductory lectures 2: The Role and Structure of Science • What does science do? • The core features of a research study. • Overall Research approaches.

3. Introduction to science, 4 • What does science do? • The core features of a research study. • Overall Research approaches. 

4. What does science do? • Describe the world • Initial approach to scientific study: “what is it” • Leads to hypotheses • Predict events • Core feature of a hypothesis: if “X” then “Y”. • Often still descriptive rather than experimental. • Test theories • Cause and effect questions involving hypothetical constructs. • Often controlled experiments or complex correlation designs. • Test applications of theories • Using theory to model change • Testing interventions or policy

5. Science: A. Describing the world • Taxonomies or behavioral categories Major personality "types"? Categories of mental illnesses "Types" of drug users. • Epidemiology rate of behavior or status x a population Distribution of HIV/AIDS: sifts by time, place, demographics Uniform crime rates Distribution of drug use types across ages… • Direct behavioral description typically qualitative Consumer decision making processes. Actual mechanics of drug acquisition & use...

6. Descriptive research Paleontology attempts to accurately describe the predecessors of humans to understand evolution Carefully describing specimens and the conditions where they are found produce insights into environmental change and evolution. E X A M P L E

7. Science: B. Prediction of events solve a practical problem  test a theory • Simple prediction What test score or personal attribute predicts college success? How can I predict which employees will develop a drug problem? • “Method of similarity” (Correlation) What child rearing style correlates with extroversion? What personality types correlate with drug use? • “Method of differences" (Experiment) Test efficacy of a heroin agonist v. placebo in treating drug addicts 1. Two groups differ in one attribute (Independent variable) -- an existing condition / behavior -- an imposed treatment 2. Do they also differ in a second attribute? (Dependent var.)

8. Predictions and theory development Correlating certain anatomical features of “proto-humans” with physical environments can test or develop theories about natural selection pressures. Scientists can than predict the types of fossils that should appear in different places. E X A M P L E

9. Science: C. Testing theories • Direct cause & effect questions What causes individual differences in academic ability? How does personality create vulnerability to drug use? • Identifying basic psychological processes How is language consolidated in the brain? What brain & behavioral changes underlie drug tolerance? • Showing how processes are related Mediation:Do drugs lead to risk by making people more impulsive? Moderation:Do drugs lead to risk primarily among men who are depressed? (Does depression create vulnerability to drug-related risk…?)

10. Predictions and theory development New data have led us to completely reframe the basic process of evolution from a simple progression to a widening “bush” of parallel species. E X A M P L E

11. Testing theory: Mediating effects Simple empirical effect: Drug use Risky behavior Mediating (theory testing) hypothesis: • How does an effect “work”? Why or How does drug use lead to risk? • Where / how might we change it? Drug use Impulsivity Risky behavior

12. Testing theory: “Moderating” effects Moderating (theory limiting) hypothesis: • When or among whom does an effect “work”? • Where / how might we change it in differentgroups? Drug use Risk Depressed men Non-depressed men Drug use Risk

13. Science: D. Testing applications of theories • Using theory to design an intervention Using basic learning theory to “teach” people to no longer have phobias. Designing alternatives to drug use for people with high “sensation seeking” disposition… • Using an intervention study to actually test a theory Comparing drug treatment to cognitive-behavioral treatment for depression. Testing social network approaches to drug prevention among college students.

14. What does science do: Summary? • Descriptive studies • “who what where…” • Predict events • Correlational studies • Experiments / Hypothesis tests • Test theories • How or why it works • Testing applications of theories

15. Introduction to science, 5 • What does science do? • The core features of a research study. • Overall Research approaches. 

16. The core features of a research study

17. Basics of research: what is a theory? Abstract statement of how two processes relate to each other… Answers why or how the phenomenon “works.” Theory: • Hypothetical Constructs • Abstract statements of psychological processes… “stress”, “depression”, “learning”, “attraction”… • …that cannot be directly observed: we observe their effects only. Interview data, behavioral symptoms, questionnaire… • That are linked as a proposition. • Specifies how one construct is related to another… stress + genetics  depression • …and Generally specifies what causes an outcome A theory has two core ingredients…

18. How do we use theory in research? • Test a theory: does stereotype threat actually exist and govern performance? • Compare theories: Which best explains women’s statistics performance: stereotype threat or social role learning • Extend an established theoryto a new outcome or phenomenon: can stereotype threat help us explain athletic as well as academic performance? • Apply a theoryto change behavior: can I create instructions that relieve stereotype threat for women during statistics.

19. The core features of a research study

20. Basics of research: hypothesis Hypothesis • An hypothesis is a Prediction • It links variables derived from the theory. • It implicitly specifies your idea of cause and effect. • Hypotheses are expressed in control terms for experiments. • If X then Y:if I make people relaxed their fear and loathing of statistics will decrease… • …and as a simple relation for measurement studies. • People who are (already) relaxed will tend to fear statistics less • …that is potentially falsifiable(see text for discussion) • Can be conceivably / logically shown to be untrue • Specific enough to be tested A concrete statement of how processes relate to each other.. about variables derived from your theory.

21. The core features of a research study

22. Basics of research: methods Methods • Core element of scientific approach • Objective; designed to separate data from person • Public: Copernican Revolution / Galileo • Replicable: others can repeat or expand the study • Test variables via operation definition • Specify operations that express construct • Define / understand variable in terms of operations Turn variables into research procedures. Verbal behavior “vegetative”; sleep, eating Depression Appearance Suicide, drug use, work… Survey / questionnaire answers…

23. What does it mean to operationalize a variable? 1. Specify a manipulation that creates the variable. • Typical of the independent variable in experiments • To relate stress to memory I may create “stress” in the lab via… • Threatening information. • Shock. • Requiring a difficult performance in front of others. 2. Specify a measurement to capture a variable • For measurement studies and the dependent variable in experiments. • Measurement-based operational definitions of stress may be: • A questionnaire scale • Heart rate • Anxious behavior, sleep loss, appetite change…

24. How would you operationalize death? • Middle ages: the soul departs the body – weighs 21 grams • The name: • 17th Century: Cordelia’s daughter in King Lear shows no breath on a mirror held to her nose • 19th Century: Development of the stethoscope and “heart death”. • Mid-20th Century: Development of respirators / life support and “brain death”. • Occasions major religious, personal conflicts • Terri Schiavo case (2005): definition of “death” becomes major political controversy. • 21st Century: fMRI images show responsiveness even in “vegetative” patients • Physical death • Your body is consigned to the grave • Someone speaks your name the last time

25. Why use operational definitions? • Any theory must be operationalized to be heuristically useful • Generate concrete & testable hypotheses • Test or eliminates jargon, pop psych, new age constructs • Many ψconcepts are abstract, so their real meaning critically depends on an operational definition. • Attitudes • “ Cognitive load” • Operational definitions orient us toward real world in theory development. • “Stress” • I.Q.

26. The limits of “operationism” • Science consists of theories & explanations, not just measures. • Measures that do not have the goal of explaining a ψ process are vacuous. • Science wants general laws, not measure-specific findings. • A concept pertains to a class of measures (e.g., diverse measures of depression, motivation, etc.), not one specific measure. • Ultimately, science does not care about the measures or the numbers

27. Methods of operationally defining variables • Some variables are easy to operationalize; e.g., the effect of a drug dose on hypertension. • IV = drug1 v. drug dose2 v. placebo • DV = blood pressure, serum measure, etc. • Some constructs can only be roughly operationalized. • Variables such as “future orientation”, “identity integration”… • Some constructs have diverging operational definitions. • How do you operationally define “stress”? • …motivation? • Some domains may not be operationalizable. • String theory… • Relativity v. quantum mechanics views of gravity; indirect derivations can be tested, but not the core construct • “Spirituality”? “Happiness”? Behavior? Self-perception? Physiological?

28. The core features of a research study

29. Basics of research: Data & Analyses: Statistics • Provide a Numerical representation (or operational definition…) of reality • Rating scales: ratio, interval, ordinal, categorical • Statistics can be Descriptive • Simply characterize a phenomenon: “what is it?”. • Test a theory: “how does it work?” • “Statistical reasoning” is central to interpreting research. • We use thenormal distribution& probability judgementsto determine whether observations are meaningful or Inferential.

30. Basics of research: Results • Descriptive or measurement studies typically address… • A simple “empirical question”… • What % of adolescents use X or Y drugs? • Demographic profile of an “undecided” voter? • Or an exploratory account of a question… • What are the correlates of college success? • Experiments(and some measurement studies) always test a hypothesis: • How do we know if the hypothesis was supported? • What statistical criteria did we use? • Are there alternative explanations for the results?

31. The core features of a research study

32. Basics of research: Discussion • Core issue: What are the implications of the results for our theory. • What does it mean that the hypothesis was (was not) supported? • What future research does this lead to? • What other hypotheses might these data support? • Study limitations: what are the boundaries on what this study can tell us? • Internal validity: • How well did we model or represent the hypothetical constructs we were interested in? • Quality / nature of operationalization & design. • External validity: • Our sample? • Our manipulation or measurement of the independent variable(s)? • Our assessment of the dependent or outcome variable(s)? • The research setting itself How representative was…

33. Core features of a research study: Theory • Hypothetical constructs • In important relationship • More specific variables • Falsifiable prediction Hypothesis • Operational definition • Internal & external validity Methods • Numerical representation • Normal distribution • Probability Data & Analysis Results • Descriptive: Empirical question or exploration • Hypothesis: Statistical significance Discussion • Meaning of these results for the theory • Limitations of methods: sample, setting, variables

34. Basic Elements of a Research Project Each element of the project corresponds to a later / earlier issue… Phenomenon Big picture /question Theory Hypothetical Constructs Causal explanation Move from the “big question” and theory… Hypothesis Operational definition Specific prediction …to a concrete hypothesis… Methods Measurement v. experimental To specific methods, the core of a scientific study… • Data / Results • Descriptive data • Test hypothesis To actual data… Discussion Implications for theory …then back to larger issues. Conclusions Future research?

35. Elements of science, review 1 A hypothetical construct is: A = A concrete description of a variable B = An abstract statement about a ψ process that cannot be seen directly. C = An excuse you construct to explain why you are late. D = An abstract use of statistical theory to test a hypothesis.

36. Elements of science, review 1 A theory is: A = Wild-eyed speculation about some topic that most people are not interested in. B = An authoritative statement of how something works: truth. C = Always tentative or provisional. D = A statement about how two (or more) hypothetical constructs are related.

37. Elements of science, review 1 An operational definition is: A = The specific way we manipulate an independent variable. B = A surgical procedure we use to test a hypothesis. C = The particular procedures we use to measure a study variable. D = An abstract statistical statement using probability theory to test hypotheses.

38. Introduction to science, 6 • How do we know something? • Science, anti-science, pseudoscience. • Where does our knowledge of the world come from? • What does science do? • The core features of a research study. • Overall Research approaches. 

39. Overall research strategies • Rich / detailed description using direct observation, interviews, or existing text. • Typically small samples that are highly targeted, e.g., specific risk groups. • Computer analyses can link parts of text. • Simple counts, “blocked” by, e.g., age, gender, ethnicity. • Use probability or highly targeted non-probability sampling. • May use existing archival data as “markers” of psychological processes. • Manipulate Independent Variable, measure effects on Dependent Variable. • Control the IV and all observations, randomly assign participants, etc. • Often uses non-probability / targeted methods to sample specific groups. • Key: standard, reliable & valid scales (e.g., of attitudes) or behavioral reports (e.g., smoking). • Experimental design, but… • no control over Independent Variable • groups non-equivalent(not blind, not randomly assigned, self-selected…).

40. Overall research strategies: Drug use Research Question: Does one form of drug treatment work better than another? Research Question: What brain centers control “drug craving”? Research Question: How does drug use actually occur? Research Question: Who tends to use drugs, how often, etc.? (epidemiology of drug use). Research Question: What social or ψ variables are associated with drug use? Methods: Experimental design: • Operationalize drug “craving” in rats (DV), • Stimulate specific brain areas (IV) to map brain structure onto craving / drug-seeking. • Methods: • Experimental-like design comparing two treatment groups. • Groups are non-equivalent(not blind, not randomly assigned, self-selected…). Methods: Direct observation of “shooting galleries” or corner drug markets, in-depth interviews with drug users… Methods: • hypothesis-oriented surveys or interviews (potentially with targeted samples: people in rehab., etc.). • Test ψvariables (motivation, emotions, attitudes…) Methods: • Surveys, face-to-face interviews, archival data (e.g., drug arrests, ER visits..) • Block by demographic variables (age, ethnicity…)

41. Overall Research strategies: measurement v. experiments • Many areas not amenable to true experiments, • e.g., medical, educational, policy studies… • Readings: Diet & health, mammography, maternal employment • Key: degree of control over variables • Core issue: controlled experiments are “gold standard” for testing hypotheses or treatments. Experiment High control / ‘lab’ conditions Determine “cause and effect”: validly interpret data Internal validity Measurement Less control; ‘research in nature’ Data can generalize to “real world” & capture more complexity External validity

42. Overall Research strategies:Validity External validity Internal validity Less control: • Observe / test phenomenon under natural conditions. • More accurate portrayal of: • “how it works in nature” • complexity of phenomenon • Less able to interpret cause & effect More control: • Isolate (or create) the phenomenon in a lab or controlled environment • Addresses more specific questions or hypotheses • More ability to interpret cause & effect

43. Research Strategies: Key issues Test causality, theory Exploration & description, epidemiology. Non-experimental theory test Naturally occurring events or groups. Often not, descriptive only Yes, or complex description Typically Always Behavior, text, status markers Subjective ratings, behavior Measured and/or manipulated Manipulated & measured Little to moderate Moderate, via context or stats. Moderate to high, except sampling High, via I.V. & exp. procedures None or simple descriptive Complex correlations Analysis of variance Analyses of variance Often low to moderate Moderate, high in some designs Moderate to High Very high High (given sampling) Moderate to high Moderate to high Often low

44. overview Overview

45. Core course topics How do we know things? • What does scientific method tell us that other methods (political, religious thought) do not? What does science do? • Describe the world • Taxonomies • Epidemiology • Qualitative research • Predict events • Simple predictions • Correlational studies • Experiments • Test theories • Cause & effect • Identify basic processes • Show how processes are related • Test applications of theories • E.g., behavioral interventions

46. Ways of knowing • Authority / authoritarianism • Provides stable, core principles or beliefs • Limits empirical evidence or alternative views • Intuition / subjective “hunch” • Important source of novel hypotheses / theories / scientific approaches • Emotion-based “wishful thinking” or “magical thought” can make us irrational or ignore / distort empirical facts. • Empiricism • Grounds knowledge in “real” world, provides important hypothesis-testing perspective • Our perceptions are subject to cognitive / emotional biases. • Rationalism / theory • Central purpose of science: coherent explanation of “why” or “how” nature works. • When subject to political pressure can limit hypothesis testing or lessen respect for empirical evidence.

47. key terms Features of research: Key terms • Theory • Hypothetical construct • Hypothesis • Variable • Operational definition • Internal & external validity • Independent v. Dependent variables • Measurement v. experimental studies

48. Basic Elements of a Research Project Phenomenon Big picture /question Theory Hypothetical Constructs Causal explanation Hypothesis Operational definition Specific prediction Methods Measurement v. experimental • Data / Results • Descriptive data • Test hypothesis Discussion Implications for theory Conclusions Future research?

49. Basics of major forms of research. External validity Internal validity