Psychology 242, Dr. McKirnan - PowerPoint PPT Presentation

Right click for “full Screen” or “end show”. Left click to proceed,

1/6/10

Lectures 2:

Core features of a research study.

General types of research designs.

• What does science do?
• The core features of a research study.
• Overall Research approaches.

• What does science do?
• The core features of a research study.
• Overall Research approaches.



• Describe the world

• Initial approach to scientific study: “what is it”
• Leads to hypotheses

• Predict events

• Core feature of a hypothesis: if “X” then “Y”.
• Often still descriptive rather than experimental.

• Test theories

• Cause and effect questions involving hypothetical constructs.
• Often controlled experiments or complex correlation designs.

• Test applications of theories

• Using theory to model change
• Testing interventions or policy

• Taxonomies or behavioral categories

Major personality "types"?

Categories of mental illnesses

"Types" of drug users.

• Epidemiology rate of behavior or status x a population

Distribution of HIV/AIDS: sifts by time, place, demographics

Uniform crime rates

Distribution of drug use types across ages…

• Direct behavioral description typically qualitative

Consumer decision making processes.

Actual mechanics of drug acquisition & use...

Paleontology attempts to accurately describe the predecessors of humans to understand evolution

Carefully describing specimens and the conditions where they are found produce insights into environmental change and evolution.

E X A M P L E

solve a practical problem

 test a theory

• Simple prediction

What test score or personal attribute predicts college success?

How can I predict which employees will develop a drug problem?

• “Method of similarity” (Correlation)

What child rearing style correlates with extroversion?

What personality types correlate with drug use?

• “Method of differences" (Experiment)

Test efficacy of a heroin agonist v. placebo in treating drug addicts

1. Two groups differ in one attribute (Independent variable)

-- an existing condition / behavior

-- an imposed treatment

2. Do they also differ in a second attribute? (Dependent var.)

Correlating certain anatomical features of “proto-humans” with physical environments can test or develop theories about natural selection pressures.

Scientists can than predict the types of fossils that should appear in different places.

E X A M P L E

• Direct cause & effect questions

What causes individual differences in academic ability?

How does personality create vulnerability to drug use?

• Identifying basic psychological processes

How is language consolidated in the brain?

What brain & behavioral changes underlie drug tolerance?

• Showing how processes are related

Mediation:Do drugs lead to risk by making people more impulsive?

Moderation:Do drugs lead to risk primarily among men who are depressed? (Does depression create vulnerability to drug-related risk…?)

New data have led us to completely reframe the basic process of evolution from a simple progression to a widening “bush” of parallel species.

E X A M P L E

Simple empirical effect:

Drug use

Risky

behavior

Mediating (theory testing) hypothesis:

• How does an effect “work”? Why or How does drug use lead to risk?
• Where / how might we change it?

Drug use

Impulsivity

Risky

behavior

Moderating (theory limiting) hypothesis:

• When or among whom does an effect “work”?
• Where / how might we change it in differentgroups?

Drug use

Risk

Depressed men

Non-depressed men

Drug use

Risk

• Using theory to design an intervention

Using basic learning theory to “teach” people to no longer have phobias.

Designing alternatives to drug use for people with high “sensation seeking” disposition…

• Using an intervention study to actually test a theory

Comparing drug treatment to cognitive-behavioral treatment for depression.

Testing social network approaches to drug prevention among college students.

• Descriptive studies
• “who what where…”

• Predict events
• Correlational studies
• Experiments / Hypothesis tests

• Test theories
• How or why it works

• Testing applications of theories

• What does science do?
• The core features of a research study.
• Overall Research approaches.



Abstract statement of how two processes relate to each other…

Answers why or how the phenomenon “works.”

Theory:

• Hypothetical Constructs
• Abstract statements of psychological processes…

“stress”, “depression”, “learning”, “attraction”…

• …that cannot be directly observed: we observe their effects only.

Interview data, behavioral symptoms, questionnaire…

• That are linked as a proposition.
• Specifies how one construct is related to another…

stress + genetics  depression

• …and Generally specifies what causes an outcome

A theory has two core ingredients…

• Test a theory: does stereotype threat actually exist and govern performance?
• Compare theories: Which best explains women’s statistics performance: stereotype threat or social role learning
• Extend an established theoryto a new outcome or phenomenon: can stereotype threat help us explain athletic as well as academic performance?
• Apply a theoryto change behavior: can I create instructions that relieve stereotype threat for women during statistics.

Hypothesis

• An hypothesis is a Prediction
• It links variables derived from the theory.
• It implicitly specifies your idea of cause and effect.
• Hypotheses are expressed in control terms for experiments.
• If X then Y:if I make people relaxed their fear and loathing of statistics will decrease…
• …and as a simple relation for measurement studies.
• People who are (already) relaxed will tend to fear statistics less
• …that is potentially falsifiable(see text for discussion)
• Can be conceivably / logically shown to be untrue
• Specific enough to be tested

A concrete statement of how processes relate to each other..

about variables derived from your theory.

Methods

• Core element of scientific approach
• Objective; designed to separate data from person
• Public: Copernican Revolution / Galileo
• Replicable: others can repeat or expand the study
• Test variables via operation definition
• Specify operations that express construct
• Define / understand variable in terms of operations

Turn variables into research procedures.

Verbal behavior

“vegetative”; sleep, eating

Depression

Appearance

Suicide, drug use, work…

Survey / questionnaire answers…

1. Specify a manipulation that creates the variable.

• Typical of the independent variable in experiments
• To relate stress to memory I may create “stress” in the lab via…
• Threatening information.
• Shock.
• Requiring a difficult performance in front of others.

2. Specify a measurement to capture a variable

• For measurement studies and the dependent variable in experiments.
• Measurement-based operational definitions of stress may be:
• A questionnaire scale
• Heart rate
• Anxious behavior, sleep loss, appetite change…

• Middle ages: the soul departs the body – weighs 21 grams
• The name:
• 17th Century: Cordelia’s daughter in King Lear shows no breath on a mirror held to her nose
• 19th Century: Development of the stethoscope and “heart death”.
• Mid-20th Century: Development of respirators / life support and “brain death”.
• Occasions major religious, personal conflicts
• Terri Schiavo case (2005): definition of “death” becomes major political controversy.
• 21st Century: fMRI images show responsiveness even in “vegetative” patients

• Physical death
• Your body is consigned to the grave
• Someone speaks your name the last time

• Any theory must be operationalized to be heuristically useful
• Generate concrete & testable hypotheses
• Test or eliminates jargon, pop psych, new age constructs
• Many ψconcepts are abstract, so their real meaning critically depends on an operational definition.
• Attitudes
• “ Cognitive load”
• Operational definitions orient us toward real world in theory development.

• “Stress”
• I.Q.

• Science consists of theories & explanations, not just measures.
• Measures that do not have the goal of explaining a ψ process are vacuous.
• Science wants general laws, not measure-specific findings.
• A concept pertains to a class of measures (e.g., diverse measures of depression, motivation, etc.), not one specific measure.
• Ultimately, science does not care about the measures or the numbers

• Some variables are easy to operationalize; e.g., the effect of a drug dose on hypertension.
• IV = drug1 v. drug dose2 v. placebo
• DV = blood pressure, serum measure, etc.
• Some constructs can only be roughly operationalized.
• Variables such as “future orientation”, “identity integration”…
• Some constructs have diverging operational definitions.
• How do you operationally define “stress”?
• …motivation?
• Some domains may not be operationalizable.
• String theory…
• Relativity v. quantum mechanics views of gravity; indirect derivations can be tested, but not the core construct
• “Spirituality”? “Happiness”?

Behavior?

Self-perception?

Physiological?

Statistics

• Provide a Numerical representation (or operational definition…) of reality
• Rating scales: ratio, interval, ordinal, categorical
• Statistics can be Descriptive
• Simply characterize a phenomenon: “what is it?”.
• Test a theory: “how does it work?”
• “Statistical reasoning” is central to interpreting research.
• We use thenormal distribution& probability judgementsto determine whether observations are meaningful

or Inferential.

• Descriptive or measurement studies typically address…
• A simple “empirical question”…
• What % of adolescents use X or Y drugs?
• Demographic profile of an “undecided” voter?
• Or an exploratory account of a question…
• What are the correlates of college success?
• Experiments(and some measurement studies) always test a hypothesis:
• How do we know if the hypothesis was supported?
• What statistical criteria did we use?
• Are there alternative explanations for the results?

• Core issue: What are the implications of the results for our theory.
• What does it mean that the hypothesis was (was not) supported?
• What future research does this lead to?
• What other hypotheses might these data support?
• Study limitations: what are the boundaries on what this study can tell us?
• Internal validity:
• How well did we model or represent the hypothetical constructs we were interested in?
• Quality / nature of operationalization & design.
• External validity:
• Our sample?
• Our manipulation or measurement of the independent variable(s)?
• Our assessment of the dependent or outcome variable(s)?
• The research setting itself

How representative was…

Theory

• Hypothetical constructs
• In important relationship

• More specific variables
• Falsifiable prediction

Hypothesis

• Operational definition
• Internal & external validity

Methods

• Numerical representation
• Normal distribution
• Probability

Data & Analysis

Results

• Descriptive: Empirical question or exploration
• Hypothesis: Statistical significance

Discussion

• Meaning of these results for the theory
• Limitations of methods: sample, setting, variables

Each element of the project corresponds to a later / earlier issue…

Phenomenon

Big picture /question

Theory

Hypothetical Constructs

Causal explanation

Move from the “big question” and theory…

Hypothesis

Operational definition

Specific prediction

…to a concrete hypothesis…

Methods

Measurement v.

experimental

To specific methods, the core of a scientific study…

• Data / Results
• Descriptive data
• Test hypothesis

To actual data…

Discussion

Implications for theory

…then back to larger issues.

Conclusions

Future research?

A hypothetical construct is:

A = A concrete description of a variable

B = An abstract statement about a ψ process that cannot be seen directly.

C = An excuse you construct to explain why you are late.

D = An abstract use of statistical theory to test a hypothesis.

A theory is:

A = Wild-eyed speculation about some topic that most people are not interested in.

B = An authoritative statement of how something works: truth.

C = Always tentative or provisional.

D = A statement about how two (or more) hypothetical constructs are related.

An operational definition is:

A = The specific way we manipulate an independent variable.

B = A surgical procedure we use to test a hypothesis.

C = The particular procedures we use to measure a study variable.

D = An abstract statistical statement using probability theory to test hypotheses.

• How do we know something?
• Science, anti-science, pseudoscience.
• Where does our knowledge of the world come from?
• What does science do?
• The core features of a research study.
• Overall Research approaches.



• Rich / detailed description using direct observation, interviews, or existing text.
• Typically small samples that are highly targeted, e.g., specific risk groups.
• Computer analyses can link parts of text.

• Simple counts, “blocked” by, e.g., age, gender, ethnicity.
• Use probability or highly targeted non-probability sampling.
• May use existing archival data as “markers” of psychological processes.

• Manipulate Independent Variable, measure effects on Dependent Variable.
• Control the IV and all observations, randomly assign participants, etc.

• Often uses non-probability / targeted methods to sample specific groups.
• Key: standard, reliable & valid scales (e.g., of attitudes) or behavioral reports (e.g., smoking).

• Experimental design, but…
• no control over Independent Variable
• groups non-equivalent(not blind, not randomly assigned, self-selected…).

Research Question:

Does one form of drug treatment work better than another?

Research Question:

What brain centers control “drug craving”?

Research Question:

How does drug use actually occur?

Research Question:

Who tends to use drugs, how often, etc.? (epidemiology of drug use).

Research Question:

What social or ψ variables are associated with drug use?

Methods: Experimental design:

• Operationalize drug “craving” in rats (DV),
• Stimulate specific brain areas (IV) to map brain structure onto craving / drug-seeking.

• Methods:
• Experimental-like design comparing two treatment groups.
• Groups are non-equivalent(not blind, not randomly assigned, self-selected…).

Methods:

Direct observation of “shooting galleries” or corner drug markets, in-depth interviews with drug users…

Methods:

• hypothesis-oriented surveys or interviews (potentially with targeted samples: people in rehab., etc.).
• Test ψvariables (motivation, emotions, attitudes…)

Methods:

• Surveys, face-to-face interviews, archival data (e.g., drug arrests, ER visits..)
• Block by demographic variables (age, ethnicity…)

• Many areas not amenable to true experiments,
• e.g., medical, educational, policy studies…
• Readings: Diet & health, mammography, maternal employment
• Key: degree of control over variables

• Core issue: controlled experiments are “gold standard” for testing hypotheses or treatments.

Experiment

High control / ‘lab’ conditions

Determine “cause and effect”: validly interpret data

Internal

validity

Measurement

Less control; ‘research in nature’

Data can generalize to “real world” & capture more complexity

External

validity

External validity Internal validity

Less control:

• Observe / test phenomenon under natural conditions.
• More accurate portrayal of:
• “how it works in nature”
• complexity of phenomenon
• Less able to interpret cause & effect

More control:

• Isolate (or create) the phenomenon in a lab or controlled environment
• Addresses more specific questions or hypotheses
• More ability to interpret cause & effect

Test causality, theory

Exploration & description, epidemiology.

Non-experimental theory test

Naturally occurring events or groups.

Often not, descriptive only

Yes, or complex description

Typically

Always

Behavior, text, status markers

Subjective ratings, behavior

Measured and/or manipulated

Manipulated & measured

Little to moderate

Moderate, via context or stats.

Moderate to high, except sampling

High, via I.V. & exp. procedures

None or simple descriptive

Complex correlations

Analysis of variance

Analyses of variance

Often low to moderate

Moderate, high in some designs

Moderate to High

Very high

High (given sampling)

Moderate to high

Moderate to high

Often low

Overview

How do we know things?

• What does scientific method tell us that other methods (political, religious thought) do not?

What does science do?

• Describe the world
• Taxonomies
• Epidemiology
• Qualitative research
• Predict events
• Simple predictions
• Correlational studies
• Experiments

• Test theories
• Cause & effect
• Identify basic processes
• Show how processes are related
• Test applications of theories
• E.g., behavioral interventions

• Authority / authoritarianism
• Provides stable, core principles or beliefs
• Limits empirical evidence or alternative views
• Intuition / subjective “hunch”
• Important source of novel hypotheses / theories / scientific approaches
• Emotion-based “wishful thinking” or “magical thought” can make us irrational or ignore / distort empirical facts.
• Empiricism
• Grounds knowledge in “real” world, provides important hypothesis-testing perspective
• Our perceptions are subject to cognitive / emotional biases.
• Rationalism / theory
• Central purpose of science: coherent explanation of “why” or “how” nature works.
• When subject to political pressure can limit hypothesis testing or lessen respect for empirical evidence.

Features of research: Key terms

• Theory
• Hypothetical construct
• Hypothesis
• Variable
• Operational definition
• Internal & external validity
• Independent v. Dependent variables
• Measurement v. experimental studies

Phenomenon

Big picture /question

Theory

Hypothetical Constructs

Causal explanation

Hypothesis

Operational definition

Specific prediction

Methods

Measurement v.

experimental

• Data / Results
• Descriptive data
• Test hypothesis

Discussion

Implications for theory

Conclusions

Future research?

External validity Internal validity