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Research methods in clinical psychology: An introduction for students and practitioners Chris Barker, Nancy Pistrang, and Robert Elliott. CHAPTER 8 Foundations of design. Design: overview. Types of designs Validity analysis Descriptive and correlational designs Correlation and causation
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Research methods in clinical psychology:An introduction for students and practitionersChris Barker, Nancy Pistrang, and Robert Elliott CHAPTER 8 Foundations of design
Design: overview • Types of designs • Validity analysis • Descriptive and correlational designs • Correlation and causation • Quasi-experimental designs • Randomised experimental designs • Control and comparison groups
Classification of designs • Non-experimental designs • Descriptive • Correlational • Experimental designs • Non-randomised (quasi-experimental) • Randomised
Causal relationships Central principle: Correlation does not mean causation Suppose that A and B are correlated: what might be the causal relationship between them? ctd./
Causal relationships 2 Simple causation: B A B A A B Third variable: C ctd./
Causal relationships 3:mediating and moderating variables Mediating variable: A D B Moderating variable: A B E (Baron & Kenny, 1986)
Validity analysis • Statistical conclusion • Internal • Construct • External (from Cook and Campbell, 1979)
Statistical conclusion validity Is the study sensitive enough? • statistical power • design quality Do the variables covary? If so, how strongly?
Internal validity If two variables do covary, is there a causal relationship between them?
Construct validity Do the outcome variables (and also the experimental intervention) represent the underlying constructs that they are supposed to?
External validity Do the results of the study generalise (e.g., across settings or participants)?
Some non-randomised designs(Cook & Campbell, 1979) (Notation: X = intervention; O = observation) One-group posttest-only design X 0 One group pretest-posttest design O1 X O2
Some non-randomised designs (cont.) Nonequivalent groups posttest-only design NR X O NR O Nonequivalent groups pretest-posttest design NR O X O NR O (Y) O
Some threats to internal validity • Endogenous change • Maturational trends • Reactivity of measurement • Secular drift • Interfering events • Regression to the mean • Selection effects
Some threats to the construct validity of the intervention • Confounding variables • “non-specific factors” • Expectancy effects • “placebo effects” • Hawthorne effect
Randomised designs • Essential feature: randomised assignment to experimental groups (conditions) • This controls for the internal validity threat of selection effects, which is a problem with quasi-experimental (non-randomised) designs
RCTs RCT is a common abbreviation for either: Randomised Controlled Trial or Randomised Clinical Trial Efficacy (as opposed to effectiveness) research
Example “Randomised groups pretest-posttest design” R O X O R O (Y) O (see Cook & Campbell, 1979)
Randomised designs: terminology • The dependent variable(s) are the outcome measures • The independent variable(s) are the experimental conditions • The statistical method is analysis of variance (ANOVA)
Factors in randomised designs • Independent variables are arranged as factors • each has two or more levels • multifactorial designs • within-group (repeated measure) factors • between-group factors (experimental conditions) • blocking factors (participant differences)
Some types of control group • No-treatment controls • treatment better than nothing • Wait-list controls • control for expectation of benefit • “Placebo” controls • credible but inert treatment • “double- and triple-blind” • Comparative treatment groups • Alternative treatment • “Treatment as usual” • Dismantling studies
Practical limitations of randomisation • Non-equivalence of groups • Attrition • “intent to treat” analysis • Leakage • Non-cooperation of staff • Costly and time consuming • Can’t study negative events • Ethical issues
Ethical issues in RCTs • No treatment/placebo controls • Wait-list controls • Random assignment v. choice • Specified treatments v. clinical judgements • Decision on patient inclusion • Referrals at termination
Some good experimental design features (1) • Patient homogeneity • Randomised assignment • Groups similar after randomisation • Specific interventions • manualisation • Appropriate control groups • Groups treated equivalently except for intervention ctd./
Good design features (2) • Low attrition • Patients, clinicians and raters blind • Follow-up after termination (e.g., 6 months, one year) • Independent replication