Chapter 4: Research Methods Notes

Introduction

• Research funding is a highly competitive and challenging endeavor, sought from various sources such as advocacy groups, large pharmaceutical manufacturers, and government agencies like the National Institutes of Health (NIH). The rigorous evaluation process ensures that only the most promising and ethically sound research projects receive support.

Chapter Objectives

• 04.01 Describe the goals of research as they relate to psychopathology, including description, causation, and treatment efficacy.

• 04.02 Compare the uses, strengths, and limitations of case studies, correlational research, and experimental research as methods used by psychologists to understand mental disorders and their underlying mechanisms.

• 04.03 Distinguish between cross-sectional and longitudinal designs as temporal strategies that examine psychopathology across different age groups or over extended periods.

• 04.04 List how ethical considerations, such as informed consent, beneficence, and justice, are identified and addressed in modern psychological research involving human participants.

Basic Components of Research

• Three main topics for psychopathology research, guiding the focus and specific questions asked:

  • The nature of the problems people report

  • The causes (etiology) of psychopathology

  • Treatment evaluation

• All scientific research starts with a hypothesis, which is an educated guess or a testable prediction about the relationship between two or more variables.

• Hypotheses in science are formulated to be specific, clear, and empirically testable, meaning they can be supported or refuted through observation and experimentation.

• The research design provides a structured method to systematically test these hypotheses, typically by examining the relationship between independent and dependent variables through controlled observation or manipulation.

• Notation (conceptual): the independent variable (IV) is the variable that is manipulated or changed by the researcher, while the dependent variable (DV) is the variable that is measured and is expected to change as a result of the IV manipulation.

Considerations in Research Design

• Internal validity vs. external validity:

  • Internal validity: This refers to the extent to which the observed effects in a study are truly due to the independent variable and not to other extraneous factors or confounds.

  • External validity: This refers to the extent to which the results of a study can be generalized to other populations, settings, times, or conditions outside of the specific study.

• Ways to increase internal validity by minimizing confounds:

  • Use of control groups: These groups do not receive the experimental treatment or manipulation and serve as a baseline for comparison, helping to rule out alternative explanations for observed effects.

  • Use of randomization procedures: Randomly assigning participants to different study groups (e.g., treatment vs. control) helps ensure that the groups are comparable at the outset, distributing potential confounds evenly and reducing systematic biases.

  • Use of analogue models: While not always ideal for external validity, using models that approximate real-world phenomena under highly controlled laboratory conditions can significantly enhance internal validity by isolating specific variables.

• Key reference concepts:

  • Internal validity: Crucial for making accurate causal inferences within the specific parameters of the study.

  • External validity: Essential for determining the practical utility and applicability of research findings to real-world clinical practice and diverse populations.

Statistical vs Clinical Significance

• Statistical methods help protect against inherent biases in evaluating data by providing objective criteria for determining if observed effects are likely due to chance or a real phenomenon.

• Statistical significance: This quantifies the probability that observed results are unlikely due to random chance.

• Clinical significance: This addresses whether the results are meaningful and practically important in real-world clinical practice, leading to tangible improvements for individuals.

• Balancing statistical vs. clinical significance:

  • Evaluate effect size: This is a quantitative measure of the strength of a phenomenon, providing a more informative metric than p-values alone. Larger effect sizes indicate more substantial and potentially clinically meaningful impacts.

  • Social validity: Assessing whether the changes observed are noticeable and valued by patients, their families, and other relevant stakeholders. This can involve qualitative feedback and measures of quality of life.

• Patient uniformity myth: This critique highlights the common research pitfall where researchers sometimes treat all participants within a diagnostic category as a homogeneous group, ignoring crucial individual differences that can impact treatment response or symptom presentation.

• Important formulas and concepts:

  • Correlation coefficient, r, which ranges from -1 to 1: This is a statistical measure that expresses the extent to which two variables are linearly related.

  • Mathematical relation: $r = \frac{\mathrm{cov}(X,Y)}{\sigma<em>X \sigma</em>Y}$

  • Where $\mathrm{cov}(X,Y)$ is the covariance between variables X and Y, and $\sigma<em>X$ and $\sigma</em>Y$ are the standard deviations of X and Y, respectively.

  • Therefore $r \in [-1, 1]$ where $r = +1$ indicates a perfect positive linear relationship, $r = -1$ indicates a perfect negative linear relationship, and $r = 0$ indicates no linear relationship.

Studying Individual Cases

• Case study method:

  • Involves extensive, in-depth observation and detailed description of a single client, often over an extended period.

  • Historically, case studies formed the foundation of early developments in understanding and classifying psychopathology, providing rich qualitative data and insights into rare conditions or complex presentations.

• Limitations:

  • Lacks scientific rigor and suitable controls, making it difficult to establish cause-and-effect relationships or rule out alternative explanations.

  • Internal validity is typically weak due to the absence of comparison groups and the inability to manipulate variables systematically.

  • Often entails numerous confounds, as many variables interact in a single individual's life, making it challenging to isolate the specific factors contributing to observed outcomes. Results are also difficult to generalize.

Correlational Research

• Assess the degree to which levels of certain variables are systematically linked to levels of other variables. This method is used when direct manipulation of variables is unethical or impractical.

• The nature of correlation:

  • Describes a statistical relation, or co-occurrence, between two or more variables without the researcher manipulating any of them.

  • It measures the strength and direction of a linear relationship between variables.

• Range: $-1.0 \le r \le +1.0$ (negative to positive correlation).

  • A correlation close to $+1.0$ indicates a strong positive relationship (as one variable increases, the other tends to increase).

  • A correlation close to $-1.0$ indicates a strong negative relationship (as one variable increases, the other tends to decrease).

  • A correlation close to $0$ indicates a weak or no linear relationship.

• Negative correlation vs. positive correlation: For example, a negative correlation might be observed between stress levels and immune function (as stress increases, immune function decreases), while a positive correlation might exist between hours studied and exam scores.

• Necessary in situations where you can’t ethically or practically manipulate variables, such as studying the relationship between early childhood trauma and adult psychopathology.

• Limitations:

  • Causation and directionality cannot be inferred from correlation alone. This is often summarized as "correlation does not imply causation" due to the third-variable problem (an unmeasured variable could be causing both observed variables) and the directionality problem (it's unclear which variable influences the other).

Epidemiological Research

• A specialized type of correlational research focused on large populations.

• Often involves extensive surveys of large groups within a defined population or community to create a comprehensive picture of a problem's presence and characteristics.

• Studies the incidence (new cases in a period), distribution (pattern of cases across demographics, geography), and consequences of a particular problem or set of mental health problems in one or more populations. This data helps identify risk factors and inform public health interventions.

Group Experimental Research

• Nature: Involves the deliberate manipulation of one or more independent variables by the researcher and then observing the effects of this manipulation on the dependent variable(s).

• Aims to determine robust causal relationships by controlling for other factors, making it the gold standard for establishing causality.

• Places a high premium on internal validity, ensuring that any observed changes in the dependent variable are indeed attributable to the manipulated independent variable.

• A clinical trial is a specific type of experiment rigorously designed to evaluate the effectiveness, safety, and optimal dosage of a new treatment or intervention in a controlled setting.

Clinical Trials

• Control group: This group is critical for comparison, as it does not receive the experimental treatment or receives a standard-of-care or placebo, allowing researchers to isolate the effects of the active intervention.

• Often matched to demographics of the experimental group (e.g., age, gender, severity of symptoms) to ensure comparability and minimize confounds.

• Placebo control group: Some participants receive an inactive or inert treatment (e.g., a sugar pill or saline injection) that is indistinguishable from the active treatment. Participants are typically unaware of which treatment they are receiving.

• Double-blind procedure: A research design where neither the participants nor the researchers (or assessors) who are interacting with participants or collecting data are aware of which treatment condition individual participants are assigned to. This minimizes bias from participant expectations and researcher influence.

• Placebo effect: A psychological phenomenon where a change or improvement occurs simply because the participant expects improvement, even when taking an inactive treatment. It highlights the power of belief and expectation in treatment outcomes.

Single-Case Experimental Designs

• Nature: Involves rigorous, systematic study of single individuals, but unlike traditional case studies, it applies experimental manipulations to determine cause-and-effect relationships within that individual.

• Researchers manipulate the timing and nature of experimental conditions for a single participant, often through repeated introduction and withdrawal of an intervention.

• Frequent repeated measurement of outcomes is critical to establish a stable baseline, observe changes during intervention, and demonstrate experimental control.

• Types of designs:

  • Withdrawal design (also known as ABAB design): Involves establishing a baseline (A), introducing an intervention (B), withdrawing it (A), and then reintroducing it (B). If the behavior changes systematically with the introduction and withdrawal of the intervention, causality is suggested.

  • Multiple baseline design: This design does not require withdrawing treatment and is used when a treatment cannot or should not be reversed.

• See page reference for a more elaborate discussion of the Multiple Baseline Design.

Multiple Baseline Design

• An example design type used in single-case research to demonstrate experimental control by showing that changes occur only when the intervention is introduced, and not before. It applies the intervention sequentially across different behaviors in the same individual, the same behavior in different settings, or the same behavior in different individuals without the need to withdraw treatment, thus avoiding ethical issues or loss of therapeutic gains associated with withdrawal.

Discussion Topics (Types of Research Participation)

• Scenarios evaluating willingness to participate in different research contexts, highlighting the varied demands and ethical considerations involved:
  1) Epidemiologic study on mood-disorder prevalence: Typically involves surveys or interviews to gather data on a large scale, less invasive.
  2) Intensive evaluation for a rare disorder: May involve extensive diagnostic testing, biological samples, and detailed historical data collection, more demanding for the individual.
  3) Exposure to a mild stressor with brain monitoring: Involves controlled experimental conditions, often with physiological measurements like fMRI or EEG, raising questions about discomfort and privacy.
  4) Clinical trial comparing a new treatment to standard treatment and placebo: Involves random assignment to different treatment arms, potential for receiving an inactive treatment, and regular follow-ups.

Studying Genetics (1 of 4)

• Behavioral genetics: A field that investigates the interplay and complex interactions of genes, experience, and environmental factors in shaping behavior, personality, and psychopathology.

• Key terms:

  • Genotype: Refers to an individual's complete set of inheritable genetic material or a specific gene variant.

  • Phenotype: Refers to the observable characteristics or traits of an individual, which result from the interaction of their genotype with the environment. Examples include eye color.

  • Endophenotype: These are measurable components (e.g., neurophysiological, biochemical, endocrinological, neuroanatomical, cognitive) that are intermediate between the distal genes and the observable proximal phenotype.

• Family studies:

  • Proband: The individual in a family who first comes to the attention of a geneticist with a particular genetic trait or disorder of interest (e.g., schizophrenia, mood disorder).

  • If a genetic influence exists for a particular trait or disorder, one would expect the trait to be significantly more common in first-degree relatives (parents, siblings, children, who share approximately 50% of genes) than in second-degree relatives (aunts, uncles, grandparents, who share approximately 25% of genes) or the general population.

  • Familial aggregation: This term describes the tendency of a disorder or trait to run in families, suggesting a potential genetic component, though it can also be due to shared environmental factors.

  • Shared environment: The fact that family members often grow up and live together means they share similar environmental influences (e.g., parenting styles, socioeconomic status, exposure to stressors). This can confound genetic inferences in family studies, as similarities could be due to either genes or environment.

Studying Genetics (3 of 4)

• Adoption studies:

  • These studies are particularly valuable because they help separate environmental effects (rearing environment) from genetic effects (biological parentage) by examining individuals who were adopted early in life.

  • Sibling pairs separated at birth: Researchers might compare identical or fraternal twins adopted into different families, or non-twin siblings raised apart. The key question is: do they show similarities in traits or disorders despite being raised in different environments?

  • Do adopted children resemble their birth parents (indicating genetic influence) or their adoptive parents (indicating environmental influence, or the influence of the rearing environment)? If adopted children are more similar to their birth parents on a particular trait, it strengthens the argument for genetic factors.

Studying Genetics (4 of 4)

• Twin studies:

  • These studies are a cornerstone of behavioral genetics, comparing the concordance rates (presence of the same trait in both twins) for a particular trait or disorder between identical (monozygotic or MZ) twins and fraternal (dizygotic or DZ) twins.

  • Identical (monozygotic) twins develop from a single fertilized egg and are genetically identical, sharing 100% of their genes. Fraternal (dizygotic) twins develop from two separate fertilized eggs and, on average, share 50% of their genes, similar to non-twin siblings.

  • If a trait is primarily genetic, one would expect a significantly greater concordance (both twins having the trait) in identical twins (who share the same genetics and often very similar environments) compared to fraternal twins.

  • Can be combined with adoption studies: This powerful design examines identical twins who were adopted apart and raised in different environments. If shared outcomes (e.g., the development of a specific disorder) are observed in these twins, it provides strong evidence that the trait is more attributable to genetic factors, as their environments were divergent while their genetic material was identical.

Locating Specific Genes

• Genetic linkage studies and association studies: These sophisticated molecular genetic techniques are used to pinpoint the specific chromosomal regions or individual genes that may be involved in the etiology of complex disorders.

  • Examine known genetic markers: Researchers use identifiable gene locations or specific DNA sequences (markers) with known chromosomal positions.

  • Compare these markers against the specific trait or disorder of interest: The goal is to see if alleles at the marker locus are co-inherited with the disease or trait within families or populations.

  • If a specific genetic marker (or the region around it) consistently co-occurs with the trait or disorder across affected family members (in linkage studies) or in affected individuals compared to controls (in association studies), it suggests that the trait is likely influenced by a gene located nearby on the same chromosome.

• Distinction between the two:

  • Genetic linkage studies focus on families with a history of the trait or disorder. They look for patterns of co-inheritance of genetic markers and the disorder within these families over generations.

  • Association studies compare allele frequencies of specific genetic markers in groups of individuals with the trait/disorder (cases) versus groups of individuals without the trait/disorder (controls) in the general population. They seek to find specific genetic variants more common in affected individuals.

Discussion: Home Genetics Tests

• Advantages: Accessibility to information regarding ancestry, identification of shared genetic information with relatives, and insight into risk markers for certain disorders (e.g., APOE gene for Alzheimer’s disease, BRCA genes for cancer). These tests can empower individuals with personal health information.

• Risks: Significant concerns regarding privacy (who owns and can access genetic data?), potential misinterpretation of complex genetic risk information by consumers without genetic counseling, psychological impact of receiving distressing news (e.g., high risk for a severe disease), and potential for genetic discrimination in areas like insurance or employment.

• Ethical considerations about knowing genetic risk (e.g., for Huntington’s disease, an incurable neurodegenerative disorder) versus reserving such knowledge. This raises questions about an individual's right not to know, the psychological burden of predictive testing, and the implications for family members.

Studying Behavior Over Time (1 of 2)

• Prevention research: A crucial area in psychopathology aimed at reducing the incidence and prevalence of mental disorders by intervening before or early in the course of a disorder. It is categorized into different levels of focus:

  • Health promotion: A broad strategy focused on increasing healthy behaviors and improving overall well-being in the entire population, regardless of individual risk for a specific disorder. This includes general public health campaigns promoting mental wellness.

  • Universal prevention: Targets specific risk factors and aims to prevent disorders in the entire population or a large unselected group, without identifying specific individuals at high risk. Examples include school-based programs promoting emotional literacy for all students.

  • Selective prevention: Targets specific subgroups of the population who are identified as being at elevated risk for developing a disorder due to certain factors (e.g., children of parents with depression, individuals in high-stress occupations). Interventions are tailored to these at-risk groups.

  • Indicated prevention: Targets individuals who are already showing early signs, symptoms, or prodromal (pre-disorder) indicators of a disorder but do not yet meet full diagnostic criteria. The goal is to prevent the full onset or progression of the disorder.

Studying Behavior Over Time (2 of 2)

• Time-based research strategies: Essential for understanding developmental trajectories, the course of disorders, and the long-term effects of interventions.

  • Cross-sectional designs: Involve taking a