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Psyc 474 > Sept 5 > Flashcards

Sept 5 Flashcards

1
Q

why talk about research methods?

A
  1. foster critical thinking & media literacy

headlines in media often sensationalize research findings, distorting nuanced insights and obscuring study limitations

many opinions about relationships online are presented as facts, but lack scientific backing

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2
Q

confirmation bias

A

tendency to seek out, pay attention to, and believe evidence that supports our pre-existing beliefs

we aren’t objective observers of our relationship interactions - interpretations of events are biased by our expectations and emotions

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3
Q

4 points on how our perspective is unique and limited

A
  1. experience has no control group (no way to limit confounders)
  2. your experience are just a small sample of all relationships
  3. often unaware of many forces on behaviours (ie. underestimate the power of the situation)
  4. too quick to see causal relationship where there may be none
    - just because two things co-occur, doesn’t mean one causes the other
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4
Q

our lay theories, from our experience, are…

A

not always correct

because of our unique and limited perspectives

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5
Q

relationship scientists examine questions in what manner?

A

systematically

by collecting data and testing their hypotheses

while taking steps to:
1. reduce bias
2. reduce subjectivity
3. rule out alternate explanations

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6
Q

can love be studied? quote and perspectives

A

“no one - not even the National Science Foundation - can argue that falling in love is a science” - US Senator William Proxmire, 1975

studying love isn’t impossible, but it is challenging

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7
Q

why is love challenging to study?

A

it’s abstract

so are its components: commitment, satisfaction, trust, attraction

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8
Q

what is key to studying love?

A

how we OPERATIONALIZE these psychological constructs

need to carefully consider what we’re really measuring and what we think we’re measuring

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9
Q

operationalizing our constructs

A

can’t measure psych constructs directly, only their operationalizations

ie. for attraction, could look at…
1. behavioural indicators (smiling, phone number exchange)
2. self-reported ratings of attraction
3. physiological measures (heart rate, brain activity)

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10
Q

measurement validity

A

extent to which operationalization adequately captures the psychological construct of interest

“are you measuring what you think you’re measuring?”

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11
Q

measurement validity: your measure should…

A
  1. make sense “on its face”, intuitively
  2. be well grounded in existing theoretical conceptions of the construct
  3. relate to other measures of construct
  4. predict future outcomes
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12
Q

4 diff types of measures

A
  1. self-report
  2. behavioural observations
  3. indirect measures
  4. physiological measures
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13
Q

self report

A

ask participants to describe their thoughts, feelings, behaviours

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14
Q

2 types of self report questionnaires

A
  1. fixed-response questionnaires
  2. open-ended questionnaires
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15
Q

fixed-response questionnaires

A

specific set of questions and possible responses predetermined by the researchers

ie. The Love Scale (Rubin)

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16
Q

The Love Scale (Rubin) is what kind of measure?

A

fixed response questionnaire

1-9 rating system

1 = not at all true, disagree completely
9 = definitely true, agree completely

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17
Q

examples of questions on The Love Scale

A

rate on scale from 1-9 (true to not true)

if my partner were feeling badly, my first duty would be to cheer them up

I feel that I can confide in my partner about virtually everything

I find it easy to ignore my partner’s faults

I would do almost anything for my partner

When I am with my partner, I spend a good deal of time just looking at them

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18
Q

comments on The Love Scale

A

takes love (abstract) and makes it quantifiable through specific statements

questions focus on care and affection aspects of love, but misses other things like commitment and passion

culturally biased - would this be appropriate all over the world?

but this scale is logical and makes sense

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19
Q

qualitative research

A

methodological approach relying primarily on open ended questions

examine the broader themes that emerge from participants’ responses

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20
Q

content analysis

A

examining the broader themes that emerge from participants’ responses

part of qualitative research

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21
Q

open ended questions

A

participant gives any answer that comes to mind

helpful when studying something we don’t know much about yet

way of gathering info to generate more specific questions later on

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22
Q

open ended questions are useful when…

A

we are studying something we don’t know much about yet

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23
Q

pros of self-report

A

cheap

easy to administer

no special equipment required

means we can recruit more participants = more powerful, reliable findings

allows us to “get inside people’s heads”

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24
Q

cons of self-report

A

difficulties with self-awareness and recall

social desirability bias

participants may not interpret questions in the way you intended

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25
Q

social desirability bias

A

desire to be seen in a positive light

relationship researchers deal with many sensitive topics

ie. higher reported rates of infidelity in online surveys vs face to face interviews

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26
Q

people’s definition of sex varies

A

asked people what constituted sex for them

13.9% = “you touch each other’s genitals”

39.9% = “oral contact with other’s genitals”

81% = “penile-anal intercourse”

95.5% = “penile-vaginal intercourse”

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27
Q

sentiment override

A

global beliefs about the partner/relationship may colour perception and memory of specific interactions

ie. “how many times did your partner kiss you yesterday?”

“I don’t remember, but he loves me and we have a good relationship, so it must’ve been a lot”

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28
Q

behavioural observation

A

gather data about relationship events without having to ask people who are experiencing those events directly

ie. how do people in happy and distressed relationships differ in the way they behave towards each other?

train observers to WATCH & CODE recordings of participant behaviour

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29
Q

behavioural observation: can observe people…

A
  1. in the lab
  2. at home
  3. anywhere! (speed dating events, airports)
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30
Q

behavioural observation: coders must agree about…

A

what constitutes incidents of a given behaviour category

need INTER-RATER RELIABILITY

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31
Q

inter-rater reliability

A

extent to which coders agree on whether a specific behaviour has or hasn’t occurred

important in behavioural observation

lots of behaviours require INTERPRETATION

ie. lighthearted joke vs hostile sarcasm

may be easier to agree on a SUPER CONCRETE behaviour, but lose the broader meaning of the behaviour (“can’t see the forest through the trees”)
- ie. may agree that a SMILE has occurred, but each smile carries different meaning

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32
Q

coders require ________ _________ to ensure ________-_________ __________

A

extensive training

inter-rater reliability

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33
Q

pros of behavioural observation

A
  1. directly assess behaviours of interest
  2. don’t have to rely on faulty memories
  3. avoid social desirability bias
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34
Q

cons of behavioural observation

A
  1. expensive, time and labour intensive
  2. reactivity: change in behaviour caused by knowledge one is being observed
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35
Q

reactivity

A

possible con of behavioural observation

a change in behaviour caused by the knowledge one is being observed

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36
Q

indirect measures are designed to avoid…

A
  1. reactivity
  2. social desirability
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37
Q

reaction time is an example of what kind of measure?

A

indirect

used to assess IMPLICIT ATTITUDES: the automatic tendency to associate a given stimulus with positive or negative feelings

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38
Q

the newlywed game study setup

A

bring in newlyweds

assess their EXPLICIT and IMPLICIT attitudes towards partner

sit in front of computer, briefly see picture of partner

then see a cross

then shown a word (either positive or negative)

INSTRUCTIONS: indicate valence of word as quickly as possible

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39
Q

the newlywed game underlying premise

A

some concepts are more tightly linked in our minds on the basis of experience

index of automatic attitudes = negative word RT - positive word RT

higher score = more positive attitude

positive feelings for partner facilitates identification of positive words

40
Q

in the newlywed game, a higher score means…

A

more positive attitude towards your partner

negative word RT - positive word RT

because negative word RT should be longer than positive word RT

41
Q

the newlywed game results

A
  1. conscious/explicit attitudes NOT CORRELATED with implicit attitudes
  • suggests Ps aren’t aware of implicit attitudes
  1. IMPLICIT but not explicit attitudes associated with newlyweds’ CHANGES IN SATISFACTION over time (4 years)
  2. IMPLICIT attitudes predict NONVERBAL BEHAVIOUR in couple discussions
  • nonverbal behaviours linked to satisfaction with conversation and relationship satisfaction over following week
  • explicit attitudes didn’t predict either verbal or nonverbal behaviour
42
Q

newlyweds game: what did implicit attitudes predict?

A
  1. associated with newlyweds’ changes in satisfaction over time
  2. predict nonverbal behaviour in couple discussion
43
Q

newlyweds game: explicit attitudes didn’t predict…

A

verbal behaviour

nonverbal behaviour

44
Q

pros of indirect measures

A
  1. avoid social desirability & reactivity problems

could be particularly useful for sensitive topics

45
Q

cons of indirect measures

A
  1. big gap between construct of interest and operationalization

can we be sure that we’re studying what we think we’re studying

46
Q

physiological responses

A

body’s reaction to various experiences/stimuli

  1. ANS activity (heart race, BP)
  2. hormone changes (cortisol, sex hormones)
  3. immune system changes
  4. brain activity
47
Q

challenges collecting & interpreting fMRI data

A
  1. very confined & noisy environment
  • makes it hard to create powerful psychological experience for participants
  1. don’t see brain “activation” per se - infer activation by subtracting response on control from trial of interest
  • need to think carefully about task design
48
Q

pros of physiological response measures

A
  1. interesting in their own right (understanding link between relationships and health)
  2. outside participants’ control (not susceptible to social desirability bias, etc)
49
Q

cons of physiological response measures

A
  1. very expensive > leads to smaller size
  2. ambiguity in interpretation
  3. could be more invasive (depending on the measure)
50
Q

archival data

A

draw on publicly available documents & data

ie. marriage licenses, yearbooks, Facebook, personal ads

data collected by someone else, often for an unrelated purpose

51
Q

example of archival data

A

more positive facial expressions in yearbook photos predict likelihood of being happily married 30 years later

51
Q

pros of archival data

A
  1. typically economical
  2. can examine historical trends
52
Q

cons of archival data

A

limited by type and quality of og data

also limited access to this data

52
Q

measurement: takeaway

A

no single approach is perfect

all have limitations

ideally, want to adopt a multi-method approach - using combo of methods to triangulate on an answer

53
Q

correlational design

A

examine NATURALLY OCCURRING associations between variables (the things we’re measuring)

ie. do people tend to be attracted to those more similar to themselves?

strength of association captured by the CORRELATION COEFFICIENT (r) which ranges from -1 to +1

  • sign tells us direction
  • magnitude tells us strength of association
54
Q

pros of correlational design

A

sometimes the only option available

some variables can’t be manipulated by researchers

ie. gender, culture, age, marriage status, chronic illness, having an affair

55
Q

cons of correlational design

A

can’t draw conclusions about CAUSATION (conclusion about cause and effect)

56
Q

correlational design: does marriage cause happiness?

A

evidence to suggest that marriage & happiness are associated

plausible that marriage may increase happiness

BUT could also be true that happier people are more likely to get married

OR optimistic people may be more likely to get married AND more likely to be happy

57
Q

3 criteria must be met to conclude causation

A
  1. two variables must be correlated
  2. one variable must precede the other
  3. there must be no reasonable alternative explanations for the pattern of correlation (no confounders)
58
Q

cross sectional data

A

collected at single point in time

59
Q

longitudinal data

A

collected from the same participants, about the same variables, on multiple occasions

allows us to examine CHANGE OVER TIME

ie. how does satisfaction change over course of relationship?

ie. do communication patterns early in relationship predict whether the couple will stay together or break up later?

60
Q

longitudinal research: 2 challenges & considerations

A
  1. choosing the right interval (how long to follow them for, how frequently to assess them)
  2. attrition: sample you start with may not be the sample you end with
61
Q

longitudinal research: choosing the right interval

A

for certain questions, may need to follow couples for a long time (months, years, decades)

sometimes, may be interested in more frequent assessments over shorter time period

62
Q

daily diary study

A

type of longitudinal approach

where Ps provide data everyday AT ABOUT THE SAME TIME

63
Q

experience sampling

A

type of longitudinal approach

where data is gathered THROUGHOUT THE DAY, thereby capturing behaviours, thoughts & feelings as they occur

64
Q

attrition bias

A

participants may drop out

those who drop out may SYSTEMATICALLY DIFFER from those remaining in the study

65
Q

example of attrition bias

A

researchers have often observed u-shaped pattern of MARRIAGE SATISFACTION

satisfaction is high, then drops slowly until low, then increases slowly until high again

could be an ARTIFACT OF UNSATISFIED COUPLES DROPPING OUT OF STUDY

66
Q

the U shaped pattern of marriage satisfaction could be…

A

an example of attrition bias

an artifact of unsatisfied couples dropping out of the study

67
Q

cons of longitudinal research

A
  1. expensive in terms of time and labour
  2. attrition bias
  3. correlational: getting 1 step closer to making causal claims, but still not there
68
Q

statistically controlling for alternative explanations

A

you measure an alternative variable that might explain your effect, and you INCLUDE IT in your analyses

if your effect is just a proxy for something the control variable is doing, your EFFECT WOULD BE WIPED OUT

ie. when children eat more ice cream, they’re more likely to drown
- have you tried controlling for whether it’s summertime?
- oh hey, the effect is gone. wild.

69
Q

while statistically controlling for alternative variables is good…

A
  1. this type of statistical control is still subject to limitations
  2. can be hard to anticipate every relevant variable
70
Q

experimental design

A

manipulate one variable to determine effect on another variable

the ONLY design that (if properly executed) allows us to make causal claims

independent and dependent variables

71
Q

independent variable

A

the MANIPULATED variable in an experiment (possible cause)

72
Q

dependent variable

A

the MEASURED variable in an experiment (possible effect)

73
Q

importance of a good control

A

compare experimental group to control group to determine effect of experimental intervention

want the control condition to match experimental condition AS CLOSELY AS POSSIBLE minus the key ingredient

want to AVOID CONFOUNDS: alternate explanations for relationship between two variables

74
Q

example of a control group to answer Q “are attractive people seen more positively?”

A

have participants rate target profiles on positive & negative personality traits

manipulate attractiveness of photo: attractive or unattractive

must make sure PHOTOS MATCH ON ALL OTHER FACTORS:
- age
- gender
- race
- quality/colour of photo

75
Q

random assignment

A

every participant has equal chance of being assigned to experimental or control group

with large enough sample, two groups should be similar on all these individual traits

helps us rule out alternative explanations

76
Q

why is random assignment important?

A

every participant brings unique set of perspectives, biases etc

potential threat to internal validity

77
Q

internal validity

A

can we rule out alternate explanations in the experiment?

are we sure the effect is being caused by what we think it is?

78
Q

what does internal validity rely on?

A
  1. selection of appropriate controls
  2. random assignment
79
Q

pros of experiments

A

allow us to make causal claims

caveat: as long as there are no threats to internal validity

80
Q

cons of experiments

A
  1. may have lower EXTERNAL VALIDITY
  2. not always feasible
81
Q

external validity

A

extent to which results obtained in a given context generalize to other contexts

82
Q

often make universal claims about relationships, but…

A

don’t study diverse samples

ie. homosexual couples historically underrepresented in relationships research

83
Q

WEIRD participants

A

Western
Education
Industrialized
Rich
Democratic

because convenience samples are much easier and cheaper to get, they’re used more frequently

84
Q

representative sample

A

sample that resembles entire population we want to study on variables of interest

ie. all nationalities, all SES backgrounds

ie. national statistics agencies like StatsCanada

very hard to get

85
Q

even if we do a good job of reaching out to a representative sample…

A

the people who agree to participate may differ from those who don’t

86
Q

volunteer bias

A

people who agree to participate in a study may differ from those who don’t

87
Q

example of volunteer bias

A

mailed invitation to participate in longitudinal study to couples who’d obtained marriage license in LA county between 1993-1994

those who responded to invitation:

  1. higher SES (more education, higher status job)
  2. more likely to have cohabited prior to marriage
88
Q

dyadic data: complicating the sample process

A

often want dyadic data to examine dyadic processes

  1. means both partners need to agree to participate - not all couples do this, excludes lots of couples
  2. are dyadic samples representative of the population or unique?
89
Q

dyadic data: individuals whose partner agreed to participate with them reported…

A
  1. greater relationship satisfaction
  2. greater commitment
  3. more secure attachment
  4. less likelihood to break up over time
90
Q

lecture takeaway

A
  1. relationships researchers generally use a COMBO of convenience and more (though not totally) representative samples
  2. having a non-representative sample doesn’t make the study WRONG - it just limits the extent to which we can generalize our findings
  3. some relationship phenomena more universal than others
  4. NO ONE STUDY IS PERFECT
91
Q

relationship science is an _______ process

A

incremental

no one study is perfect

92
Q

actor-partner interdependence model

A

allows us to examine how individual outcomes are affected by BOTH one’s own characteristics (ACTOR EFFECT) and the partner’s characteristics (PARTNER EFFECT)

because we can recruit both members of couple, we can examine individuals’ outcomes based on their own behaviour/thoughts/characteristics and also those of their partners

93
Q

ethical issues in relationships research

A
  1. asked to deeply think about & confide about issues of highly personal and sensitive nature
  2. may experience negative effects like recognizing relationship problems for the first time
  3. cost-benefit analysis - must be sure the benefits of the research are worth the costs
  4. need to be sensitive in approaching participants, providing effective debriefing and counselling resources

Psyc 474 (23 decks)

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