PSC 150
A. The Need to Belong(Baumeister & Leary, 1995)
“The need is for frequent, nonaversive interactions within an ongoing relational bond” (video)
If this need is not fulfilled, mental and physical health suffer
B. Social network structure and health
Stronger social networks predict good health outcomes
1. The Alameda County study (Berkman & Syme, 1979)
9-year prospective study of ~5000 people
Measure of social network structure
1. Marriage
2. Close friends/relatives
3. Church membership
4. Informal group membership
Results: Social isolation predicts higher mortality
Controlling for health at baseline, SES, smoking, alcohol consumption, physical activity, obesity, race, life satisfaction,and use of preventive health services
2. The Pittsburgh Cold Study
(Cohen et al., 1997)
Ps were administered nasal drops containing cold viruses and were examined to investigate:
→ Whether or not they developed colds
→ The degree to which they produced mucus
Beforehand, Ps reported on the diversity of their social roles (e.g., spouse, parent, friend, coworker)
Results: Ps with 1-3 network roles were 4.2 times (!) more likely to develop a cold than were those with 6+ network roles
C. Relationship quality and health
It’s not just the existence of relationships
Marital quality study
A meta-analysis: Combining 123 articles and 72,000 people
Results: Having a low-quality marriage predicts poorer health and elevated mortality rates
People that have worse quality relationships had higher cardiovascular (high blood pressure), Subjectve (self-rated poor health), Objective (mortality)
D. Social rejection and “hurt feelings”
We have the need to belong (in a group or someone) in order to thrive in life
People say they experience “pain” and hurt” from social rejection
Can we interpret this claim literally?
The Cyberball study
Does social rejection cause activation in regions of the brain known to activate following physical pain?
Rejection manipulation: Cyberball
Inclusion condition
Getting the ball a third of the time in a group of 3 people
Rejection Condition
You don’t get the ball thrown
People feel terrible when they’re being pushed to the side and not being acknowledged in this condition
Results: brain activation parallels the pattern that occurs following physical pain.
The need to feel like you’re a part of something is a part of the core of human beings.
We hate feeling rejected so much that even if you feel pushed aside by people you dont like, you still feel bad and rejected.
Psychology, Science, and Truth
A.The goal of science: To discover truth
Truth: That which corresponds to reality
Some methods of discovering truth
Intuition - it just feels true
Metaphysics - religion, mythology, etc.
Logic - basic assumption, if-then reasoning ,etc.
Science - based on observation and evidence ← Psychologists
Intuition vs. Science:
If an expert believes something to be true, should we also believe it? (Testing Therapeutic Touch clip)
Experts often have terrific insights, but scientists view these insights as testable hypotheses rather than as facts.
B.The hindsight bias
The tendency to believe you “knew it all along” after learning that an event happened because it “just made sense”
Ex: the winner of the Bachelor, Supreme Court Justices
“Common sense” wisdom is contradictory
“Out of sight, out of mind” vs “Absence makes the heart grow fonder”
“Opposites attract” vs, “Birds of a feather flock together”
Or our example: Are we attracted to people who like us or to people who play hard to get?
Common sense does not state when the behavior will occur
There are conditions where we like people who like us and conditions where we like people who play “hard to get”.
We can only draw conclusions on these topics with evidence
C.Ethics of research
Very sensitive questions - more so than in many other areas of psychology
Participants may…
→ learn something they wish they didn’t know
→ learn they don’t know something they wish they did
Science’s ethical imperative
Some Basics
Theories, hypotheses and operationalizations
Theory: A hypothetical explanation of a natural phenomenon
→ “carcinogens harm human health”
Hypothesis: A testable, falsifiable prediction made by a theory
→ Can support or disprove, but never prove, a theory
→ “Carcinogen exposure causes cancer”
Operational Definitions: Description of an abstract property in concrete, measurable terms
→ Abstract property: Carcinogen exposure
→ Operational definition: # of cigarettes smoked per day
Reliability and Validity
Reliability: The tendency for a measure to produce the same result whenever it is used to measure the same thing
→ Think: Consistent
→ A ruler, a scale, a self-report measure of happiness, etc
Validity: The extent to which a measurement and a topic are conceptually related
→ Think: Accurate
→ Is the measure sensibly related to the underlying construct?
Frequency distributions: Graphical representations of the measure of a sample
A mean difference does not mean all people in one group differ from all people in the other!
Central tendency
Mean: The average of the measurements
Median: The middle measurement; half below, half above
Mode: The most frequent measurement
Experimental & Correlational Studies
Experiments (very powerful – allow for causal conclusions)
Independent and dependent variables
→ The independent variable (IV) is deliberately manipulated
Ex: Assign people to smoke 10 vs 0 cigarettes per day
Experimental condition vs. the control condition
→ The dependent variable (DV) is measured to see if the IV affects it
Ex: Likelihood of lung cancer 20 years later
Random assignment
Each participant (P) has an equal chance of being assigned to any condition of the IV (e.g., new therapy vs. standard therapy)
→ Condition is determined by chance, not by self-selection
Participants in the two groups should be the same on average except for the manipulated variable
B. Correlation Studies
Correlation: The association between two variables
Useful when one cannot manipulate the IV
Ethical or practical limitations
Ex: Is parental divorce associated with behavior problems?
Two problems with drawing causal conclusions from correlational research
First: reverse-causality problem
→ Perhaps behavior problems cause divorce
Second: The third-variable problem
→ Perhaps genes underlying risk-taking tendencies cause both divorce and behavior problems in one’s child
The correlation coefficient ®
Varies from -1 to +1
Sign indicates the directions of association
Magnitude (in absolute value) indicates strength of association
Correlations are high/strong when knowing the score on one variable gives you confidence about the score on the other
C. Developmental Designs
Retrospective design: Ask people about their past experiences
→ Compared Jennifer L’s past relationship with Ben to Jennifer G’s past relationship with Ben
→ Problem: Memories can be biased by recent events
Longitudinal design: Follow people over time (best design when possible)
Problem: Participant attrition
Still NOT experimental, so you cannot draw causal conclusions
Data Collection Methods
Self-reports: Asking people about thoughts/feelings
Retrospective vs. Current
Global vs. specific
→ “How active is your sex life?” vs. “How many times did you have sexual intercourse in the past week?”
Subjective vs. objective
→ “How satisfying is your relationship?” vs. “Did your partner give you a present for your birthday?”
Self-reports always entail some subjectivity
Observational studies: Coding over behaviors
Couples interact in a laboratory and are videorecorded.
Experience-sampling procedures can capture everyday interaction (e.g., the iEAR)
“Introverts have a horror of small talk, but enjoy deep discussions”
→ “Deep’ conversations boost introverts' feelings of connectedness
Physiological measures: Levels of hormones in blood/saliva, heart rate, muscle tension, fMRI brain scans
Comparing participants who have recently fallen in love with long-term married and in-love individuals.
Archival materials: Photographs, diaries, public media (Facebook, Reddit)
Using yearbook photos to predict later marital status
Language changed preceding/following breakup