Introduction to science, 5

1. Introduction to science, 5 Module 4: Core research steps; The hour glass model. • This is a PowerPoint Show • Click through it by pressing any key. • If this does not open as a show go to “slide show” to start it. • Focus & think about each point; do not just passively click. Dr. David J. McKirnan, University of Illinois at Chicago, Psychology; mckirnanuic@gmail.com

2. The overall “flow” of research Phenomenon - Larger question the research addresses Theory - Explanatory processes & how they are related • Hypothesis • Concrete variables • Specific prediction Section Overview • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise analysis of outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

3. Research Flow Phenomenon - Larger question the research addresses What needs explaining? Why is it important? Theory - Explanatory processes & how they are related How / why do I think it works? • Hypothesis • Concrete variables • Specific prediction What is my specific prediction? • Methods / Data • Operational definitions • Study procedures What concrete evidence or data will I collect? Results - Hypothesis-wise analysis of outcomes What was the outcome? Hypothesis supported? What do the results mean for the theory? What is unanswered? • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

4. Research Flow Phenomenon - Larger question the research addresses The research flow begins with broad, abstract questions Theory - Explanatory processes & how they are related • Hypothesis • Concrete variables • Specific prediction Gets more specific & concrete • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise analysis of outcomes Then back to a more general discussion. • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

5. Core features of research: Theory. Phenomenon - Larger question the research addresses Theory - Explanatory processes & how they are related • Hypothesis • Concrete variables • Specific prediction Theory: • Abstract statement of how basic processes relate to each other… • Answers howor whythe phenomenon“works.” • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise analysis of outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

6. Core features of research: Theory. These are basic physical or behavioral processes. They are the building blocks of theories. • Economic uncertainty • Cognitive style • Stress • Gravity • Learning…

7. Core features of research: Theory. • They are abstract: • We cannot actually “see” gravity. • We just see what it does (stuff falls). • Economic uncertainty • Cognitive style • Stress • Gravity • Learning…

8. Core features of research: Theory. • Gravity is a Hypothetical Construct: • Central to our understanding of nature • We measure and understand it by observing its effects on the world. • Economic uncertainty • Cognitive style • Stress • Gravity • Learning…

9. Core features of research: Theory. • A theory is a statement about how these hypothetical constructs are related • to each other • to some concrete event

10. How do we use theory in research? • Test a theory: Do women who feel strong stereotype threat about math actually do worse? • Compare theories: Which best explains women’s statistics performance: stereotype threat or social role learning? • Extend an established theory: Can stereotype threat help us explain athletic as well as academic performance? • Apply a theory: Can I create instructions that relieve stereotype threat for women during statistics?

11. Core features of research: Hypotheses. Phenomenon - Larger question the research addresses Theory - Basic Ψprocesses we think explain the phenomenon • Hypothesis • Concrete variables that express the Ψ processes • Specific prediction • Methods / Data • Operational definitions • Study procedures Hypothesis: • A prediction • That is potentially falsifiable. Results - Hypothesis-wise statistical analysis of study outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

12. 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. • …that is potentially falsifiable(see text for discussion) • Can be conceivably / logically shown to be untrue • Specific enough to be tested

13. Basics of research: hypothesis Hypotheses in Measurement v. Experimental studies.. • In experiments we manipulate the Independent Variable. • So hypotheses are expressed in control terms: • IFI make people relaxed thentheir fear and loathing of statistics will decrease. • Measurement studiesdo not manipulate anything. • Hypotheses are expressed as a relation. • People who are (already) relaxed will tend to fear statistics less.

14. Core features of research: Methods. Phenomenon - Larger question the research addresses Methods: • Measurement or experimental procedures • Rely on Operational Definitions Theory - Basic Ψprocesses we think explain the phenomenon • Hypothesis • Concrete variables that express the Ψ processes • Specific prediction • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise statistical analysis of study outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

15. 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 • Turn our hypotheses into concrete variables • That we examine via specific procedures

16. Basics of research: methods Methods • We turn our hypotheses into variables via an operation definition. What is “depression”? What operations could assess it? Verbal behavior “vegetative”; sleep, eating Depression Appearance Suicide, drug use, work… Survey / questionnaire answers…

17. Basics of research: methods Methods • OurOperation definitiondetermines what a variable “means” in our study. • What is “economic uncertainty”? • The unemployment rate? • Subjective attitude ratings? • What is “Stress”? • Heart rate & cortisol levels? • Speech patterns?

18. Basics of research: methods Methods • We have two forms of operational definitions: In Experiments we specify a manipulationthat defines the variable In Observational or descriptive research we define our variables by their measurement. • These reflect two main branches of research: Measurement v. Experimental.

19. Operational Definitions • This is the independent variable • To test the hypothesis that stress impairs memory I may createstress in the lab via… • Shock. • Requiring a difficult performance in front of others. Are • shock (a physical threat) • and • performance (a social threat) • Equivalent ‘Stressors”?

20. Experiments: operational definitions through manipulations • I may measure stress levels in this class via: • A questionnaire scale • Heart rate • Anxious behavior, sleep loss, appetite change… Are • Equivalent measures of Stress? • heart rate • and • sleep loss

21. Operationalizing “Stress” Does stress lead to illness? Measure the dependent variable • Infection post-exposure • Observed respiratory infections Manipulate the independent variable • Threatening information. • Shock. • Require difficult public performance. E X A M P L E Measure the predictor • Questionnaire scale on life events • Assess cardio-vascular reactivity Measure the outcome variable • Self-reported respiratory infections • Morbidity & mortality

22. Operationalizing “Stress” Does stereotype threat lower academic performance? Measure the dependent variable • Performance under highlighted & public vs. control conditions Manipulate the independent variable • Highlight group difficulties • Make the performance public E X A M P L E Measure the outcome variable • Performance over a course Measure the predictor • Questionnaire scale: • Anticipated group performance • Self-consciousness

23. Why use operational definitions? • Any theory must be operationalized to be heuristically useful • Operational definitions orient us toward real world rather than vague abstractions I think stress makes people less healthy • What does “stress” mean? • Long v. short term? • Subjective v. life events? • How will you measure it? • Overt behavior? • Physiological? • Psychological? • What does “health” mean? • Long v. short term? • Positive v. symptoms? • How will you measure it? • Overt behavior? • Physical? • Psychological?

24. The limits of “operationism” • Some variables are easy to operationalize; e.g., the effect of a drug dose on hypertension. • IV = drug dose1 v. drug dose 2 v. Placebo… • DV = blood pressure. • Some constructs can only be roughly operationalized. • “Pro-social attitude”, “self-concept”… • Some constructs have diverging operational definitions. • How do you operationally define “stress”? • …learning? • Some domains may not be operationalizable. • String theory… • “Spirituality”? “Happiness”? Behavior? Self-perception? Physiological?

25. When am I dead? How do we define death? Click the image for an excellent piece from WNYC Radiolab. E X A M P L E

26. When am I dead? • 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 some “vegetative” patients • Physical death • Your body is consigned to the grave • Someone speaks your name the last time E X A M P L E

27. Core features of research: Results. Phenomenon - Larger question the research addresses Theory - Basic Ψprocesses we think explain the phenomenon Results: • Qualitative • Quantitative; statistical reasoning • Hypothesis • Concrete variables that express the Ψ processes • Specific prediction • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise statistical analysis of study outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

28. Results Results • Two major streams of research results: Qualitativeresearch relies on rich description, using text, images, video and other media. Quantitative research uses numerical scales and statistical reasoning

29. Results Results • In depth description of animal behavior; field notes and behavioral markers Qualitative research. • Observation of class exercises plus collection and categorizing of written notes

30. Results Results Qualitative research. • “Found Text”.

31. Results Results • Descriptive or measurement studies • Simple “empirical question”… • What % of adolescents use X or Y drugs? • an exploratory account of a question… • What are the correlates of college success? • Experiments 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? Quantitative research.

32. Results Results • Numerical representation of reality • Descriptive statistics • Simple characterization: “who / what / when?” • Inferential statistics • Generalize to a larger population. • “Statistical reasoning”: Quantitative research. • Probability judgmentsusing the Normal distribution.

33. Core features of research: Results. Phenomenon - Larger question the research addresses Theory - Basic Ψprocesses we think explain the phenomenon • Hypothesis • Concrete variables that express the Ψ processes • Specific prediction Discussion & Conclusions: • What do we know now about our theory? • Study limitations? • Where do we go now? • Methods / Data • Operational definitions • Study procedures Results - Hypothesis-wise statistical analysis of study outcomes • Discussion & Conclusion • Relate results back to theory • Study limitations & Future studies

34. Results Discussion • What are the implications of the results for our theory (or empirical question)? • What does it mean that the hypothesis was (was not) supported? • Has our theory been supported? • Are there other possible interpretations of these findings? • What other hypotheses might these data support? • What applications might there be of these results? Study implications.

35. Results Discussion • 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 Study limitations. How representativewas…

36. What does science do? • Hypothetical constructs • In important relationship Phenomenon & Theory • Specific variables • Falsifiable prediction Hypothesis • Operational definition • Internal & external validity Methods Section Overview • Qualitative / Quantitative • Descriptive question or exploration • Hypothesis test Results • Meaning of results for the theory • Alternate interpretations • Study Limitations. Discussion

37. Basic Elements of a Research Project Phenomenon Big picture /question Begin with the “big question” Theory Hypothetical Constructs Causal explanation … articulate a clear theory Hypothesis Operational definition Specific prediction …and derive concrete hypotheses. Methods Measurement v. experimental Then specific methods, the core of a scientific study. • Data / Results • Descriptive data • Test hypothesis Then actual data & results… Discussion Implications for theory … implications for the theory Conclusions Future research? …and larger issues.

38. Basic Elements of a Research Project Phenomenon Big picture /question Theory Hypothetical Constructs Causal explanation Hypothesis Operational definition Specific prediction Each element of the project corresponds to a later / earlier issue… Methods Measurement v. experimental • Data / Results • Descriptive data • Test hypothesis Discussion Implications for theory Conclusions Future research?

39. Basic Elements of a Research Project Phenomenon Big picture /question Study results often lead to the next experiment… 2. …then articulate the question or issue clearly Theory Hypothetical Constructs Causal explanation 3. …and try to come up with an explanation Hypothesis Operational definition Specific prediction 4. Our theory helps us develop an hypothesis Methods Measurement v. experimental 5. …that we figure out how to test or measure • Data / Results • Descriptive data • Test hypothesis Data Descriptive data or observation • Data / Results • Test hypothesis 1. We often begin with an observation or a hunch Discussion Implications for theory Then we run the rest of the process Conclusions Future research?

40. Basic Elements of a Research Project Phenomenon Big picture /question Very often research results themselves lead to a new experiment or study. Theory Hypothetical Constructs Causal explanation 1. Our data may not support the hypothesis, or may support an alternate hypothesis Hypothesis Operational definition Specific prediction 2. Negative results: • We may retest our hypothesis with different operational definitions of our variables • Or a whole different study design Methods Measurement v. experimental • Data / Results • Descriptive data • Test hypothesis Data / Results Test new hypothesis Results Was the hypothesis supported? Discussion Implications for theory 3. We then re-run the study. Conclusions Future research?

41. Basic Elements of a Research Project Phenomenon Big picture /question Theory Hypothetical Constructs Causal explanation 1. Of course our data – or someone else’s data – may lead us to rethink our whole theory. Hypothesis Operational definition Specific prediction 2. That would itself lead us to: • Formulate new / different hypotheses • New / different study design & variables • New results Methods Measurement v. experimental • Data / Results • Descriptive data • Test hypothesis Results Our initial findings Results Other findings Data / Results Test new hypothesis Discussion Implications for theory Conclusions Future research?

42. 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.

43. Elements of science, review 2 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.

44. Elements of science, review 3 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.

45. Elements of science, review 3 • In science the numbers are what count most. • Yes, if I have enough of them • Yes, if they have been operationally defined • No, the measures are most important • No, the Theory and hypothesis is most important.

46. Introduction to science, 6 • What does science do? • The core features of a research study. • Overall Research approaches. 

47. Overall research strategies Most basic research distinction: Measurement studies vs. Experiments

48. Overall research strategies We directly assess nature • With more or less structure • Describe behavioral or physical processes • Test hypotheses We exert controlover nature to test specific hypotheses. • Manipulate the independent variable • Control experimental conditions.

49. Overall research strategies • Explorethe process of behavior. • Describebehavioral or social trends. • Relate measured variablesto test hypotheses. • Study natural events; field experiments • Test hypotheses in controlled (“lab”) conditions. • Rich / detailed description: • Direct observation • Interviews • Existing text. • Small, targeted samples • Oral history • Literary criticism • History • Simple counts, by age, gender, ethnicity... • Probability or highly targeted sampling. • Archival data: • Celebrity suicide effect • Economics & crime • Often non-probability / targeted sampling. • Key: standard, reliable & valid measures • Field studies. • Experiments where… • no control over Independent Variable • groups non-equivalent • not blind, • not randomly assigned. • Manipulatethe Independent Variable • Measureeffects on Dependent Variable. • Controlall aspects of experiment • Standardize procedures, • randomly assign participants..

50. Overall research strategies: Drug use Research Question: How does drug use actually occur? Research Question: Who uses drugs, how often, etc.? (epidemiologyof drug use). Research Question: What social or ψ variables are associated with drug use? Research Question: Does one form of drug treatment work better than another? Research Question: What brain centers control “drug craving”? Methods: • Directly observe “shooting galleries” or drug markets, • In-depth interviews with drug users, police, service workers… Methods: • Surveys, interviews, archival data • Cultural & economic analyses Methods: • hypothesis-oriented surveys or interviews • Often targeted samples. • Test cultural, social or ψvariables. • Methods: • Experimental-like design comparing two treatment groups. • Groups are non-equivalent • not blind • not randomly assigned… Methods: • Stimulate specific brain areas (IV). • Measure drug “craving” (DV), • Map brain structure (IV) onto craving / drug-seeking (DVs).