Understanding and assessing mental health through behavior observation
Key methods for gathering data include self-reports and observational studies.
Describe behavior: assess how frequent a condition like depression is.
Example: How prevalent is depression in certain populations?
Predict behavior: explore relationships between variables.
Example: Is there an association between spending time alone and experiencing depression?
Explain behavior: analyze causal relationships.
Example: Does social isolation lead to increased levels of depression?
Programs can utilize the three goals of research: description, prediction, and explanation, to provide a comprehensive understanding of mental health issues.
Different methodologies include:
Self-reports
Observational studies
Case studies
Archival data
Directly asking individuals about their experiences and feelings.
Important considerations:
Will the data be collected via surveys or interviews?
What types of questions will be posed?
Open-ended questions:
Allows for detailed qualitative data (e.g., describe your personality).
Example response: "My personality is fairly reserved..."
Forced-choice questions:
Respondents choose between options (e.g., NPI statements).
Likert scales:
Measures level of agreement (e.g., self-esteem statements on a scale).
Wording Issues:
Double-barreled questions should be simplified to avoid confusion.
Order Effects:
Randomize question order to reduce bias.
Acquiescence:
Responding positively to all items can be problematic. Solutions include reverse-wording items.
Fence-sitting:
Avoid middle-ground responses by limiting scale options.
Socially Desirable Responding:
Encourage neutral wording to reduce bias.
Brainstorm a range of questions with input from experts.
Determine the response type.
Pilot test to evaluate reliability and validity.
Use factor analysis to determine if measures capture intended constructs (e.g., Big Five traits).
Test-retest reliability: consistent scores over time.
Internal reliability: consistency of scores across items (use Cronbach’s alpha, threshold = 0.70).
Subjective Validity:
Face validity and content validity assess alignment with constructs.
Criterion Validity:
Predictive and concurrent validity determine correlation with outcomes.
Offer detailed assessments, useful for diagnosing mental disorders.
Can capture non-verbal cues but are also influenced by interviewer biases.
Types of interviews:
Structured, semi-structured, and unstructured formats allow flexibility in gathering information.
Focus on variables without manipulation - Example: moral transgressions.
Types include:
Naturalistic Observation
Participant Observation
Structured Observation
Observer Bias and Effects: Expectation-based influence on interpretation and participant behavior.
Reactivity: Individuals may act differently when aware of being observed.
Interrater Reliability: consistency across different observers, can utilize Cohen’s kappa and ICC for ratings.
In-depth examination of individuals or small groups providing rich data.
Notable case studies include Genie (language acquisition) and Phineas Gage (personality changes from brain injury).
Using pre-existing datasets to answer new research questions, such as tracking trends in narcissism over time.
Design a correlational study based on earlier assignments; emphasize non-manipulative variables, sampling, and measurement reliability/validity.
Suggested activity to assess a personality test, focusing on question types and validity threats.
Instructions for engaging in practice questions using provided tools and codes.