1. 1 Research Methods in Psychology Behavioral Medicine Psy 314 William P. Wattles, Ph.D.. Francis Marion University

2. 2 Empirical 4 a. Relying on or derived from observation or experiment: empirical results that supported the hypothesis. 4 b. Verifiable or provable by means of observation or experiment: empirical laws.

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4. 4 Faith Healing gone bad 4 NYT 8/29 8-year old died at prayer service intended to save him.

5. 5 Good science versus bad science 4 Alternative explanations.

6. 6 Seven Signs of Voodoo Science 4 1. The discoverer pitches the claim directly to the media. 4 2. The discoverer says a powerful establishment is suppressing his work. 4 3. The effect is at the very limit of detection. 4 4. Evidence for the discovery is anecdotal.

7. 7 Seven Signs of Voodoo Science 4 5. The discoverer says a belief is credible because it has endured for centuries. 4 6. The discoverer has worked in isolation. 4 7. New laws of nature are proposed to explain the observation.

8. 8 The Case Study A.Widely used, easy to implement. B.Allows for a thorough analysis of the subject. Useful when phenomena is rare or new C.Provides a description D.May disconfirm uniform assumptions E.Useful for hypothesis generation.

9. 9 Disadvantages of case study a.Can confuse the individual and the disorder. b. Cannot generalize from this idiographic (individual) data or to nomothetic ( general)

10. 10 Idiographic vs. Nomothetic data 4 Idiographic refers to the individual. 4 Nomothetic - Of or relating to the study or discovery of general scientific laws. 4 When we use nomothetic data we gain and. We lose specificity to the individual but we gain in that we can now generalize to others.

11. Survey 4 A questionnaire asking self-reported attitude or behavior. 11

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13. Class Survey 2013 13

14. 14 Correlation 4 Observation only 4 Relationship one tends to follow the other 4 text: correlation indicates how similar the scores are. 4 In general when one increases the other increases and vice versa.

15. 15 Correlation 4 The relationship between two variables X and Y. 4 In general, are changes in X associated with Changes in Y? 4 If so we say that X and Y covary. 4 We can observe correlation by looking at a scatter plot.

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17. 17 Type of correlation 4 Positive correlation. The two change in a similar direction. Individuals below average on X tend to be below average on Y and vice versa. 4 Negative correlation the two change in the opposite direction. Individuals who are above average on X tend to be below average on Y and vice versa.

18. 18 Examples 4 Positive correlations: Hours spent studying and g.p.a.; height and weight, exam 1 score and exam 2 score, Obesity and type2 diabetes, hypertension, asthma 4 Negative correlations; temperature and heating bills; hours spent watching TV and g.p.a.; SAT median and % taking the test.

19. 19 Correlation Coefficient 4 One number that tells us about the strength and direction of the relationship between X and Y. 4 Has a value from -1.0 (perfect negative correlation) to +1.0 (perfect positive correlation) 4 Perfect correlations do not occur in nature

20. 20 Strength of Correlation 4 Weak.10,.20,.30 4 Moderate.40,.50,.60 4 Strong.70,.80,.90 4 No correlation 0.0

21. 21 Advantages of Correlation 4 Relatively simple to do. 4 Involves observation not manipulation

22. 22 Disadvantages of Correlation CORRELATION DOES NOT IMPLY CAUSATION

23. Causation 4 Sadly, there is no sufficient way to prove that an association between a factor and a disease is a causal relationship. 4 http://www.med.uottawa.ca/sim/dat a/Causation_e.htm http://www.med.uottawa.ca/sim/dat a/Causation_e.htm 4 Strength 4 Consistency 4 Specificity 4 Temporality 4 Dose response (biological gradiant) 4 Plausibility 4 Coherence 23

24. 24 Correlation 4 Measures of health for nations correlate with the number of televisions.

25. 25 4 Obesity increased with popularity of low-fat diet. –More Driving –Less walking –Larger portions –More computers

26. 26 EXPERIMENT 4 Experimenter Control (manipulation) –Independent variable –Dependent variable 4 Two or more groups –experimental group –control group 4 Random assignment

27. 27 Independent Variable 4 Under control of the experimenter 4 Used to explain changes in the dependent variable 4 Example: Type of instruction –Should include a control group

28. 28 Dependent Variable 4 Not under control by the experimenter 4 Presumed to be caused or affected by the independent variable 4 Example: grade on final exam

29. 29 Random Assignment 4 Essential aspect of experiment 4 Allows us to control for all potential confounds 4 Each subject has an equal chance of being in each group. 4 Intact groups not random 4 Replication to deal with chance variation

30. 30 EXPERIMENT 4 Double-blind –to avoid social expectations –to avoid demand characteristics 4 External validity-extent to which we can generalize 4 Analogue-animals, cold water immersion as stress

31. Overdiagnosed, Welch, Schwartz & Woloshin 31

32. Overdiagnosed, Welch, Schwartz & Woloshin 32

33. Example of Experiment 4 New York Times 9/1/2009 4 The Claim: Chamomile Can Soothe a Colicky Baby. The Claim: Chamomile Can Soothe a Colicky Baby. 33

34. Randomized Clinical Trial 4 Independent Variable –Treatment group Chamomile tea –Control Group Other tea 4 Dependent Variable –Presence of colic 34

35. Randomized Clinical Trial 4 Results –Treatment group 57 percent better –Control group 26 percent better 35

36. 36 Advantage of Experiment 4 Can talk about one variable causing another.

37. Analog Study 4 a type of study in psychology that attempts to replicate or simulate, under controlled conditions, a situation analogous to real life 37

38. Research ExampleExample 38

39. Clinical Course of self-limiting conditions. 39 Improvement Intervention Deterioration asymptomatic symptomatic

40. 40 Dose Response Relationship 4 A direct, consistent association between an independent variable, such as a behavior, and a dependent variable, such as a disease. 4 Supports a causal interpretation.

41. Dose response relationship 4 All available prospective studies that measured fitness and categorized participants based on fitness level similarly show a strong inverse dose- response between fitness and risk of developing metabolic syndrome 4 http://www.health.gov/paguidelines/report/g3_ metabolic.aspx http://www.health.gov/paguidelines/report/g3_ metabolic.aspx 41

42. Dose response 4 A dose response relationship makes it much less likely that a factor to which the risk factor and the disease are related is an explanation of the underlying risk factor- disease relationship. 42

43. 43 Studies over time 4 Cross-sectional studies-conducted during only one point in time. 4 Longitudinal studies follow participants over an extend time period.

44. 44 Reliability 4 Does the test measure consistently? 4 text: The degree to which test scores are free from errors of measurement 4 Reliability is necessary but not sufficient

45. 45 Measurement Error 4 Measurement error is always present 4 Anything affecting the test score that does not relate to the issue of interest. –response tendency –social desirability 4 text: Variation in scores not due to changes in the targeted characteristic.

46. 46 Validity 4 Does the test measure what it is supposed to measure?

47. 47 Concurrent Validity 4 A type of criterion validity 4 Concurrent means at the same time 4 Correlate results of one measure with another variable – measured at the same time. –expected to be related 4 Example stress profile correlated to medical history.

48. 48 Predictive Validity 4 Another type of Criterion validity 4 Can the test predict something it should be able to predict? 4 Example, stress profile did not predict symptoms, physician visits or self- perceptions of health

49. 49 Epidemiology 4 Branch of medicine that investigates the frequency and distribution of disease and related factors. 4 Important in SARS epidemic

50. 50 Epidemiology 4 Prevalence-the proportion of the population that has a particular disease at a specific time. 4 Incidence-measures the frequency of new cases of the disease.

51. 51 Epidemiology 4 Determine the etiology or origins of a specific disease. To develop and test hypotheses. 4 Discovering who is more likely to have a disease is useful in determining its cause. SARS as an example 4 Discovering risk factors such as dirty water or smoking.

52. 52 Epidemiology 4 Mortality- Death rate 4 Morbidity-The rate of incidence of a disease.

53. 53 Epidemiology 4 A risk factor is any characteristic or condition that occurs with greater frequency in people with a disease than it does in people free from the disease.

54. 54 Epidemiology 4 Presence of a risk factor increases the likelihood of developing the illness. 4 Suggests primary prevention

55. 55 Epidemiology  Relative versus absolute risk. Relative: Considered in comparison with something else 4 Relative risk the ratio of incidence or prevalence in the exposed group to that of the unexposed group 4 Absolute risk-The persons chances of developing a disease.

56. 4 Test A 4 If around 1,000 people have this test every 2 years, 1 person will be saved from dying from this cancer every 10 years. 4 4 Test B 4 If you have this test every 2 years, it will reduce your chance of dying from this cancer from around 3 in 1, 000 to 2 in 1,000 over the next 10 years. 4 4 Test C 4 If you have this test every 2 years, it will reduce your chance of dying from this cancer by around one third over the next 10 years. 56

57. Relative Risk 4 If you have this test every 2 years, it will reduce your chance of dying from this cancer by around one third over the next 10 years. 57

58. Absolute risk 4 If you have this test every 2 years, it will reduce your chance of dying from this cancer from around 3 in 1, 000 to 2 in 1,000 over the next 10 years. 58

59. Number needed to treat 4 If around 1,000 people have this test every 2 years, 1 person will be saved from dying from this cancer every 10 years. 4 Clinical vs. Statistical significancesignificance 59

60. Absolute Risk vs. Relative Risk 60 4 Example New York Times Nov. 08 Example New York Times Nov. 08

61. 61 Relative Risk 4/8=50% Absolute risk 8% reduced to 4% A decrease of 4 % points or 4 people per hundred

62. 62 Quality of care data 4 NYT 9/3/04 4 More than 98 percent of hospitals in the United States are reporting quality-of-care data for treating heart attack, heart failure and pneumonia, the Centers for Medicare and Medicaid Services said yesterday.

63. 63 Clinton heart bypass 4 During Heart bypass surgery blood vessels are taken from elsewhere in the body, often the leg, and sewn in to create detours around coronary artery blockages 4 516,000 were performed in 2001

64. 64 Quality of care data 4 Clinton hospital 3.93 deaths per hundred versus 2.18 for coronary bypass overall in NY. 4 Correlational data but they control for 45 risk factors.

65. 65 The End