Chapter 4 Research Methods in Clinical Psychology Introduction to Clinical Psychology 2e hunsley & lee PREPARED BY DR. cathy chovaz, king’s college, Uwo

Ways of Generating Research Hypotheses Everyday Experience and Observation Professional Experience and Observation Addressing Applied Problems and Needs Previous Research Theory

Topics Relationship Between Variables Ethics in Research Important Concepts to Clinical Research Clinical Research Designs Selecting the Participants Selecting the Measures Psychometric Properties of the Measures

Relationships Between Variables Correlation – the variables are associated in some way Moderation – one variable influences the direction or size of another Mediation - one variable explains the relationship between two others

Ethics in Research (some principles) Institutional approval Informed consent Inducements for participation Deception in research Debriefing Humane care for animals Reporting results

Important Concepts to Clinical Research Internal validity – controlling for biases External validity – how representative and applicable the study is Statistical conclusion validity – whether the study was designed in a way to adequately test hypotheses through statistical methods

Clinical Research Designs 1. Case Study – detailed description of a case, which can allow for a great deal of hypothesis generating Down side: many threats to internal validity making it difficult to generalize 2. Single case designs A-B (two measures of symptoms pre- and post-treatment A-B (designs with a number of clients) A-B-A (designs with one person at different time points)

Clinical Research Designs 3. Correlational designs – association among variables (most commonly used design) Does not imply causality ‘Median splits’ on a particular variable - dichotomizing Factor analysis – the underlying structure of a variable Mediator vs. Moderator designs Structural equation modeling

Clinical Research Designs 4. Quasi-experimental designs - comparing groups when random assignment is not available or ethical 5. Experimental Designs (the ‘gold standard’ in clinical research) – random assignment and experimental manipulation Randomized controlled trials (RCT)

Clinical Research Designs 6. Meta-analysis – summarizing several similar studies through a statistical analysis Effect size – a statistical measure of how strong the experimental effect is (i.e., statistical significance does not say how strong the effect is, only that it is unlikely to have randomly occurred)

Selecting the Participants Importance of selecting a representative sample (age, gender, SES, ethnicity, etc.) Sampling strategy – how participants are chosen/recruited Probability sampling – requesting participants from say, every 10th person in a neighborhood Non-probability sampling – recruiting through a method that will reach as many people as possible

Selecting the Participants Setting the sample size – making sure there are enough participants to detect differences in groups Low power Sufficient sample size Statistical significance Clinical significance

Selecting the Measures Self-Report Measures – participant report Informant-Report Measures – report by someone who knows the participant Rater Evaluations – research assistant rates the participant Performance Measures – how a participant does on a task (e.g., reaction time or behavioural measure)

Selecting the Measures Projective Measures – participant responses to ambiguous stimuli, which may reflect the internal state of the participant Observation of Behaviour - coding systems used to summarize complicated behaviour Psychophysiological Measures – a range of measures reflecting biological markers (e.g., heart rate, blood pressure, neural activity) Archival Data – Data stored for some other purpose used for research (e.g., police records, health care utilization records, and academic records)

Psychometric Properties of the Measures Reliability: Internal Consistency: Homogeneity of test items Test-Retest Reliability: Stability of scores on a measure over time Inter-Rater Reliability: The consistency of scores on a measure across different raters or observers.

Psychometric Properties of the Measures Validity: Content Validity: How fully and accurately the measure represents the construct being assessed Face Validity: How much the measure overtly appears to be measuring the construct of interest. Criterion Validity: The association of a measure with a related criterion Concurrent Validity: The association of a measure with other relevant data measured at the same point in time.

Psychometric Properties of the Measures Validity (cont.): Predictive Validity: The association of a measure with other relevant data measured at some future point in time. Convergent Validity: The association between a measure and either other measures of the same construct or conceptually related constructs Discriminant Validity: The association between measures that, conceptually, should not be related Incremental Validity: The extent to which a measure adds to the prediction of a criterion beyond what can be predicted with other measurement data

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