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New Advances in Measurement. Ronald D. Rogge. TOPICS. RELATIONSHIP QUALITY T1 : IRT Optimization Study 1 T2 : Responsiveness to Change Studies 2-5 T3 : Bi-Dimensional View Studies 6-7 T4 : Implicit Measures Studies 8-11 ATTENTION T5 : Screening for Error Variance Studies 12-16.

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topics
TOPICS
  • RELATIONSHIP QUALITY
    • T1: IRT Optimization
      • Study 1
    • T2: Responsiveness to Change
      • Studies 2-5
    • T3: Bi-Dimensional View
      • Studies 6-7
    • T4: Implicit Measures
      • Studies 8-11
  • ATTENTION
    • T5: Screening for Error Variance
      • Studies 12-16
acknowledgements
Acknowledgements
  • Couples Satisfaction Index
      • Janette Funk, Mike Maniaci, Maria Saavedra, Soonhee Lee
  • Positive-Negative Relationship Quality
      • Frank Fincham, Richard Mattson, Matt Johnson
  • C.A.R.E. Program
      • Tom Bradbury, Rebecca Cobb, Matt Johnson, Erika Lawrence, Lisa Story, Lexi Rothman
  • Implicit Assessment
      • Soonhee Lee, Harry Reis
  • Attention / Effort
      • Mike Maniaci, Janette Funk, Soonhee Lee, Maria Saavedra
relationship quality
Relationship Quality
  • Relationship satisfaction
      • Self-report scales (DAS, MAT, QMI)
      • 30-50 years of research (over 4K studies)
      • Excellent correlational validity
      • Level of noise?
      • Responsive to change over time?
      • Are these the “best” items?
topic 1 irt optimization
TOPIC 1: IRT Optimization
  • Large sample method
      • N at least 1,000 in smallest group
  • Large item pool
      • Unidimensional
      • Non-redundant
  • Used by ETS
      • SAT, GRE, MCAT, LSAT
  • Quality of each item
      • Information
      • Noise
  • Advantages
      • Over correlations
      • Over small sample methods
irt approach
IRT Approach
  • Latent scores (q) for each subject
      • Like GRE scores
      • Assessing relationship satisfaction
  • Parameters for each item
      • Response curves
      • Higher q’s  higher responses?
  • Item Responsiveness
      • How informative?
      • Where informative?
  • Creates information profiles
      • For individual items
      • For sets of items
study 1 measures
Study 1 - Measures
  • 141 satisfaction items:
      • DAS, MAT, RAS, KMS, QMI, SMD
      • 71 additional items
  • 7 anchor scales:
      • Neuroticism (EPQ-N)
      • Conflict / Communication (MCI, CPQ, IAI)
      • Stress (PSS)
      • Sexual Chemistry (Eros)
      • Instability (MSI)
  • 2 validity scales:
      • Inconsistency (PAI)
      • Infrequency (PAI)
study 1 sample
Study 1 - Sample
  • 5,315 online respondents
      • After removing:
        • Incomplete or invalid responses
        • Multivariate outliers
      • 26yo (10yrs)
      • 83% Female
      • 76% Caucasian
      • 26% High school ed. or lower
      • $27K average income
      • 24% married, 16% engaged, 60% dating
evaluating previous scales
Evaluating Previous Scales
  • IRT results
      • Simultaneous analysis
      • 66 items of existing scales
      • Some very informative items
      • Many poor items
das 31 degree of happiness all things considered of your relationship
DAS-31(Degree of happiness, all things considered, of your relationship)

Response Curves

Information Curve

das mat 5 agreement on friends
DAS/MAT 5Agreement on: FRIENDS

Response Curves

Information Curve

mat 12 in leisure time do you and does your mate prefer to be on the go or to stay at home
MAT 12In leisure time, do you (and does your mate) prefer to be “on the go” or to stay at home?

Response Curves

Information Curve

from items to scales
From Items to Scales
  • A scale’s information

= sum of information from each item

  • How informative

Across different levels of happiness

analysis of existing measures
Analysis of Existing Measures
  • Many uninformative items
      • Particularly for DAS and MAT

 noise / error

  • Modest test information
      • For all scales
      • Notably poor for MAT and DAS
  • Room for improvement
creating the csi
Creating the CSI
  • 141 item pool
      • Screen for contaminating items
      • Screen for redundant items
      • IRT on remaining 66 items
      • Select 32 most effective
what have we gained
What have we gained?
  • Identical correlational results
      • Strong convergent validity
      • Strong discriminant validity
      • Strong construct validity

 Measuring same thing

  • Higher information…
  •  Should have
      • Lower Noise
      • Higher Precision
      • Greater Power
satisfaction groups
Satisfaction Groups
  • IRT satisfaction estimates
      • For each subject
      • Based on MAT, DAS, & CSI items
      • (equivalent of GRE scores)
  • Created satisfaction groups
      • N = 265
      • HIGHLY similar SAT within each group
  • MAT, DAS & CSI scores also similar?
effect size
Effect Size
  • Ability to detect difference
      • Between groups
      • Pre – Post
  • Effect Size = M1 – M2.

pooled SD

  • Difference in SD units
  • Power for detecting D’s in SAT groups
study 1 conclusions
STUDY 1 - Conclusions
  • CROSS-SECTIONALLY
      • CSI assess same construct
      • Higher precision
      • Higher power
  • NEXT STEP
      • Longitudinal analysis
      • Responsiveness to change over time
topic 2 responsiveness
TOPIC 2: Responsiveness
  • Detecting change
      • Assumption
      • Longitudinal
  • External Criteria
      • Treatment effect
      • Clinician
      • Interviewer
      • Global report
  • SERM (Sdiff)
      • Noise over time
      • Estimating
  • Two main applications
      • Individual change
      • Clinically distinct groups
studies 2 through 4
Studies 2 through 4
  • Study 2
    • 267 online respondents
      • 1 & 2wk follow ups
      • 468 change scores
  • Study 3
    • 156 online respondents
      • 1, 2, 3, 4, 6 & 12mo follow ups
      • 455 change scores
  • Study 4
    • 545 online respondents
      • 1, 2, 3, 4, 6, 9 & 12mo follow ups
      • 1,552 change scores
studies 2 4 measures
Studies 2-4: Measures
  • Relationship satisfaction scales:
      • DAS-32
      • MAT-15
      • CSI-32
      • CSI-16*
      • CSI-4*
  • 3 global relationship change items
      • Change since last assessment
individual change
Individual Change
  • How many points of change needed?

(to show significant change)

    • SERM in “No Change”
      • RCI (Jacobson & Truax, 1991)
      • MDC95 (Stratford et al., 1996)
      • MDC95 (SD units) = 1.96*SERM.

SD

    • PRESENTING
      • Meta-Analytic Summary
      • Standardized Units
detecting change
Detecting Change
  • Individual Change
      • IRT optimization
      • Longer scales
  • Distinct Groups
    • Can scales distinguish?
      • Mild deterioration
      • No change
      • Mild improvement
perceived change
Perceived Change
  • How much have these changed?
      • Overall happiness in the relationship
      • Feeling close and connected
      • Stability of the relationship
perceived change1
Perceived Change
  • Averaged responses
      • Alpha = .92
  • Created change groups
quantifying group level responsiveness
Quantifying Group-Level Responsiveness
  • MCID

(Guyatt, Walter & Norman, 1987)

      • Noise over time (SERM)
      • Effect Sizes:

(Avg Change)IMPROVE – (Avg Change)NO CHANGE

SERM

(Avg Change)DETERIORATE – (Avg Change)NO CHANGE

SERM

analytic strategy
Analytic Strategy
  • Improving method
      • Multi-wave data
      • Global change continuous
      • Moderation
  • HLM
      • PV: Global change score
      • Moderators:
        • Gender
        • T0 Satisfaction
      • DV: Change scores on scales (n = 2475)

 Change scores ≈ 1pt global change

 MCID effect sizes

  • Meta-Analytic Summary
responsiveness conclusions
Responsiveness Conclusions
  • Can be quantified
      • Scale selection
      • Power estimates
  • Responsive scales
      • Greater power
        • Individual
        • Group
  • Cross-sectional  Longitudinal
      • Precision & Power translate
  • NEXT STEP  Treatment Effects
topic 3 bi dimensional view
Topic 3: Bi-Dimensional View
  • Uni-Dimensional view
      • Positive feelings opposite negative feelings
  • Bi-Dimensional view
      • Pos/Neg independent
      • Moderately “dissatisfied”
        • Ambivalent
        • Indifferent
      • Uni-Dimensional obscuring?
background
Background
  • Fincham & Linfield (1997)
    • PN-QIMS
      • Two 3-item scales
        • Qualities of spouse
        • Feelings toward spouse
        • Feelings about marriage
      • Considering only (pos/neg)
      • Separated in survey
    • CFA in 123 couples
    • Unique information
study 5
Study 5
  • Mattson et al. (under review)
  • New pos-neg scale
    • 7 SMD items of CSI
    • Pos / neg separately
  • Large online sample
    • Ambivalent
    • Indifferent
study 5 sample
Study 5 - Sample
  • 1656 online respondents
    • Demographics
      • 28yo (7yrs)
      • 94% Female
      • 87% Caucasian
      • 30k income
      • 5% ≤ high school
    • Romantic relationships
      • 38% married (6.5yrs)
      • 19% engaged (3.6yrs)
      • 41% dating – exclusive (2.4yrs)
study 6
Study 6
  • IRT Optimized Positive & Negative Scales
    • Item Pools
      • 20 positive items
      • 20 negative items
    • Large sample
      • UG respondents
    • Analyses
      • EFA
      • Redundancy
      • IRT
  • Precision / Power / Validity
study 6 sample
Study 6 - Sample
  • 1,814 undergrad respondents
    • Demographics
      • 19yo (2yrs)
      • 77% Female
      • 72% Caucasian
      • Together 2.6yrs
      • 26% dissatisfied
    • Close relationships
      • 54% romantic partners
      • 38% friends
      • 5% family members
      • 3% roommates
    • Romantic relationships
      • 76% dating – exclusive
      • 21% dating – non-exclusive
positive negative relationship qualities
Positive-Negative Relationship Qualities
  • New PN-RQ scales
    • Best 4 & 8 items by IRT
pn rq
PN-RQ
  • Power from Optimization
      • More precise
  • Unique Information
      • Ambivalent vs. Indifferent
  • NEXT: Responsiveness
study 7
Study 7
  • PREP
      • Psycho-educational workshop
      • Speaker-Listener Technique
  • CARE
      • Psycho-educational workshop
      • Acceptance based techniques (IBCT)
  • Awareness
      • Self-guided
      • Semi-strutured
  • No Treatment
study 71
Study 7
  • 173 Newlywed couples
      • Engaged or married <6mo
      • Screened for severe discord (MAT below 85)
  • Demographics
      • AGE 29
      • Caucasian H: 58% W: 54%
      • Latino/a H: 17% W: 23%
      • Asian Am H: 9% W: 11%
      • African Am H: 5% W: 5%
  • Assessed
      • MAT, PN-QIMS
      • 6 points over 3yrs
slope intercept hlm results
Slope-Intercept HLM Results
  • MAT
      • Drops over time for Men
  • Negative Qualities
      • ns
  • Positive Qualities
      • Drops only in No Treatment*
      • TX: Sig better slopes in Men
bi dimensional view
Bi-Dimensional View
  • Distinct individuals
  • Distinct treatment effects
  • Enhance
      • Theories
      • Clinical work
topic 4 implicit assessment
Topic 4: Implicit Assessment
  • Limitations of Self-Report
      • Insight
      • Biases
  • Limitations of Observational Coding
      • Costly
      • Evaluation apprehension
      • Not all constructs observable
  • Implicit assessment
      • Indirect
      • Inexpensive
      • Unique insights
previous work
Previous Work
  • Me/Not-Me task

Aron, Aron, Tudor, & Nelson (1991), Aron & Fraley (1999), Slotter & Gardner (2009)

  • Rxn Time on Evaluations

Fincham, Garnier, Gano-Phillips, & Osborne (1995)

  • Partner-focused IAT

Zayas & Shoda (2005)

Banse & Kowalick (2007)

Scinta & Gable (2007)

  • Self-focused IAT

Dewitt, de Houwer, & Buysse (2008)

  • Sequential priming task

Scinta & Gable (2007)

go no go association task
Go/No-Go Association Task
  • Partner-GNAT
      • Sort three types of words
        • Good
        • Bad
        • Partner
      • Presented
        • One at a time
        • In random order
      • Spacebar for targets
gnat stimuli
GNAT Stimuli
  • Partner words
      • First name
      • Nick name
      • Pet name / Distinguishing characteristic
gnat procedure
GNAT Procedure
  • Procedure
      • Obtain partner stimuli
      • Sorting task
        • 16 practice trials: good as target
        • 16 practice trials: bad as target
        • 70 trials: partner + good as targets
        • 70 trials: partner + bad as targets
      • Complete counterbalancing

CriticalTrials

slide70
GNAT
  • Fast task (600msec)
      • Accuracy
      • D’ index
  • Proposed
      • High performance on P-good

 Strong positive implicit attitude

      • High performance on P-bad

 Strong negative implicit attitude

studies 8 9 samples
Studies 8 & 9: Samples
  • Study 8
    • 122 online respondents
      • 39% married (for 3.3yrs)
      • 13% engaged (together for 2.7yrs)
      • 58% dating (for 2.4yrs)
    • 79% Caucasian
    • 87% Female
    • 43% provided follow-up data
    • 8 ended their relationships
  • Study 9
    • 100 online respondents
      • 10% married (for 3.6yrs)
      • 12% engaged (together for 3.2yrs)
      • 77% dating (for 1.8yrs)
    • 77% Caucasian
    • 86% Female
    • 63% provided follow-up data
    • 11 ended their relationships
method variance
Method Variance
  • P-good and P-bad
    • r = .45
    • Shared method variance
      • Ability
      • Effort
      • Attention
      • Comfort with computers
  • Enter as pairs
      • Simultaneous PVs
      • Partial correlations
      • Shared variance dropped
  • Examine interaction
      • Pos & Neg attitudes might interact
studies 8 9 analytic strategy

LEVEL 2:

p0 = b00

p1 = b10+ b11(relationship satisfaction)

+ b12 (hostile conflict)

+ b13 (neuroticism)

+ b14 (partner-good)

+ b15 (partner-bad)

+ b16 (partner-good X partner-bad)

+ r1

Self-Report Controls

Partner-GNAT

Performance

Studies 8 & 9: Analytic Strategy
  • Discrete-time hazard modeling in HGLM

LEVEL 1:

Prob(Breakup) = P

log[ P/(1-P) ] = p0 + p1(time) + e

study 8 prediction of relationship breakup over 1 year
Study 8: Prediction of Relationship Breakup over 1 year

NOTE: B = unstandardized beta; SE = standard error. † p < .10; * p < .05

study 9 prediction of relationship breakup over 1 year
Study 9: Prediction of Relationship Breakup over 1 year

NOTE: B = unstandardized beta; SE = standard error. † p < .10; * p < .05

studies 8 9 summary
Studies 8 & 9: Summary
  • Partner-GNAT
    • Predicts Breakup over 1yr
      • After controlling for SR scales
      • Possible interaction
  • Suggests
    • Partner-GNAT provides unique information
      • P’s unable to report
      • P’s unwilling to report
  • Next Step: Mechanism of action
study 10
Study 10
  • Partner-GNAT
    • Generic good or bad words
      • Good stimuli: freedom, pleasure, gift
      • Bad stimuli: death, accident, poverty
  • Behavioral coding
    • Two 10-minute Problem discussions
    • Two 10-minute Social Support discussions
    • Two teams of naïve coders
  • Self-report data
coding process
Coding Process
  • Two separate teams (5 and 7 coders)
      • Weekly meetings
  • Spouses coded in separate passes
      • 30sec intervals
      • Global codes
  • Counterbalancing
      • Order of couples
      • Order of spouses (within each interaction)
      • Order of topics (H vs. W)
  • Rated 15-18 dimensions
  • All coders coded all tapes
      • Codes averaged within coders & interactions
      • Codes averaged across coders
      • Created composite codes
composite codes
Composite Codes
  • Support Behavior/Affect
      • Emotional Support
      • Negative Behavior
  • Conflict Behavior/Affect
      • Empathic Listening
      • Affection
      • Negative Behavior
study 10 sample
Study 10: Sample
  • 57 couples
      • 48% engaged to be married (in 4.8mo)
      • 52% married (for 3.7mo)
  • Relationships
      • Together 3.3yrs
      • Highly satisfied (avg. CSI = 141)
      • 81% premarital cohabitation
      • 93% living together at T0
      • 14% had children at T0
  • Demographics
      • Age 28yo
      • 91% Caucasian
      • 53k joint income
      • 9% ≤ HS education
study 10 analytic strategy
Study 10: Analytic Strategy
  • Actor-Partner Interdependence Modeling in HLM
  • Modeling trajectories over time
      • Two level model
        • Level 1 – Individual differences
          • GNAT indices
          • Coded behavior
          • Initial self-report
        • Level 2 – Dyadic variables
          • Relationship length
          • Number of children
study 10 summary
Study 10: Summary
  • Partner-GNAT
      • Linked to own behavior
      • Linked to partner’s behavior
      • Across domains

 Might shape each other

  • Tailoring GNAT
      • Implicit assessment of attachment?
self report attachment scales
Self Report Attachment Scales
  • ECR-R
      • Attachment Anxiety

“I worry a lot about my relationship”

      • Attachment Avoidance

“I find it difficult to allow myself to depend on romantic partners”

      • Difficult to disentangle
        • Attachment
        • Preoccupied / Dismissive Behaviors
      • Requires insight / honesty
study 11
Study 11
  • Standard Battery of SR scales
  • Implicit Attachment
      • Partner-GNAT*
      • Self-GNAT*
      • *New Valence Categories
        • Relationally Worthy
        • Relationally Worthless
      • Hypotheses
        • Partner-GNAT*  internal working model of others
        • Self-GNAT*  internal working model of self
gnat stimuli1
Partner words

First name

Nick name

Pet name / characteristic

Self words

First name

Last name

Nick name / characteristic

GNAT Stimuli
study 11 sample
Study 11: Sample
  • Recruitment underway
  • First 48 couples
      • 79% committed dating relationships (1.6yrs)
      • 4% engaged (2.9yrs)
      • 17% married (4.5yrs)
  • Relationships
      • Quite satisfied (CSI-16 = 70)
      • Dissatisfied
        • 6% of married
        • 9% of dating
  • Demographics
      • Age 24yo
      • 76% Caucasian
      • 37k joint income
      • 9% ≤ HS education
future directions
Future Directions
  • Unique information
      • Beyond SR
      • Clinically useful?
  • Shapes behavior
      • Longitudinal mediation?
      • Change over time?
  • Can be Tailored
      • Attachment?
  • Alternate Targets
      • Family
      • Friends
      • Behaviors
  • Moderators
      • Mindfulness
      • Assimilation of Partner into Self-Concept
        • IOS
        • RISC
topic 5 attention effort
Topic 5: Attention / Effort
  • Inattention
      • Adds error / noise
      • Reduces power
  • Quantifying
      • Large Clinical Inventories (e.g., PAI)
        • Infrequency
        • Inconsistency
      • Experimental Research
        • Instruction reading (IMC; Oppenheimer, 2009)
      • Survey Research
        • Unknown
study 12
Study 12
  • Quantifying Inattention
      • Behavioral Measures
        • 7 directed responses
        • 20 pronoun task
        • 2min video
      • Self-Report
        • Inattentive
        • Patterned
        • Rushed
        • Instruction skipping
study 12 sample
Study 12 - Sample
  • 575 online respondents
      • 54% Mturk.com
      • 13% online forums
      • 33% UG psychology students
  • Demographics
      • 29yo (12yrs)
      • 70% Female
      • 77% Caucasian
      • 21% ≤ High School
      • 30% ≤ $30k / year
screening for inattention
Screening for Inattention
  • Developing ARS
      • Item pool
        • Infrequent items
        • Inconsistent pairs
      • 3 large online samples
      • Ability to discriminate
        • P responses
        • Random data
        • Random responders
studies 13 through 15
Studies 13 through 15
  • Study 13
    • 1195 online respondents
      • 85% female
      • 77% Caucasian
      • 26yo (SD = 8.4)
  • Study 14
    • 1878 online respondents
      • 91% female
      • 85% Caucasian
      • 28yo (SD = 7.1)
  • Study 15
    • 547 online respondents
      • 74% female
      • 72% Caucasian
      • 20yo (SD = 1.3)
final ars scales
Final ARS scales
  • Two scales
      • 11 infrequency items
        • I enjoy the music of Marlene Sandersfield
        • I look forward to my time off
      • 11 inconsistency item pairs
        • I am an active person
        • I have an active lifestyle
  • Agreement with PAI
      • Study 14
        • Continuous: r’s = .64 and .83
        • Categorical: kappa = .72
convergent validity
Convergent Validity
  • Study 12 indices
  • ARS inattentive respondents
    • Higher on inattention indices?
      • Behavioral Markers
      • Self-Report
    • Comparable regression results?
ars inattentive p s1
ARS Inattentive P’s
  • Robins et al. (2001)
      • Big 5  Self Esteem
      • R2 = .34**
      • 3 sig coeffs
  • Attentive P’s
      • N = 621
      • R2 = .41**
      • 3 sig coeffs
  • Inattentive P’s
      • N = 55
      • R2 = .08 ns
      • no sig coeffs

ns

ars convergent validity
ARS Convergent Validity
  • ARS inattentive respondents
    • Higher inattention
      • Behavioral Markers
      • Self-Report
    • Adding noise
      • Lowering power
study 16
Study 16
  • Reading instructions?
  • ARS vs. IMC
    • Oppenheimer (2009)
    • IMC: Instructional Manipulation Check
      • Single paragraph / item
      • Eliminates 20-40% of P’s
      • Enhances power
        • Paragraph manipulations
          • Sports ticket
          • Can of pop
slide114

Sports Participation

Most modern theories of decision making recognize the fact that decisions do not take place in a vacuum. Individual preferences and knowledge, along with situational variables can greatly impact the decision process. In order to facilitate our research on decision making we are interested in knowing certain factors about you, the decision maker. Specifically, we are interested in whether you actually take the time to read the directions; if not, then some of our manipulations that rely on changes in the instructions will be ineffective. So, in order to demonstrate that you have read the instructions, please ignore the sports items below, as well as the continue button. Instead, simply click on the title at the top of this screen (i.e., “Sports Participation”) to proceed to the next screen. Thank you very much.

Which of these activities do you engage in regularly?

(click all that apply)

skiing

soccer

snowboarding

running

hockey

football

swimming

basketball

tennis

cycling

Continue

slide115

Sports Participation

Most modern theories of decision making recognize the fact that decisions do not take place in a vacuum. Individual preferences and knowledge, along with situational variables can greatly impact the decision process. In order to facilitate our research on decision making we are interested in knowing certain factors about you, the decision maker. Specifically, we are interested in whether you actually take the time to read the directions; if not, then some of our manipulations that rely on changes in the instructions will be ineffective. So, in order to demonstrate that you have read the instructions, please ignore the sports items below, as well as the continue button. Instead, simply click on the title at the top of this screen (i.e., “Sports Participation”) to proceed to the next screen. Thank you very much.

Which of these activities do you engage in regularly?

(click all that apply)

skiing

soccer

snowboarding

running

hockey

football

swimming

basketball

tennis

cycling

Continue

study 16 sample
Study 16 - Sample
  • 652 online respondents
      • 60% Mturk.com
      • 40% UG psychology students
  • Demographics
      • 28yo (11.5yrs)
      • 70% Female
      • 74% Caucasian
      • 27% ≤ High School
      • 30% ≤ $30k / year
sunk cost task thaler 1985
Sunk Cost Task (Thaler, 1985)

Imagine that your favorite football team is playing an important game that you

[have paid handsomely for.]

[have received from a friend.]

However, on the day of the game, it happens to be freezing cold. What do you do?

ns

soda pricing task thaler 1985
Soda Pricing Task (Thaler, 1985)

You are on the beach on a hot day. For the last hour you have been thinking about how much you would enjoy an ice cold can of soda. Your companion needs to make a phone call and offers to bring back a soda from the only nearby place where drinks are sold, which happens to be a

[run-down grocery store.] [fancy resort.]

Your companion asks how much you are willing to pay for the soda and will only buy it if it is below the price you state. How much are you willing to pay?

ns

ns

inattention summary
Inattention Summary
  • Inattention
    • Skipping instructions
      • As high as 20-40%
    • Skimming items
      • 5-10%
    • ARS effectively screens
      • Enhances power
summary
Summary
  • RELATIONSHIP QUALITY
    • T1: IRT Optimization
      • Study 1
    • T2: Responsiveness to Change
      • Studies 2-5
    • T3: Bi-Dimensional View
      • Studies 6-7
    • T4: Implicit Measures
      • Studies 8-10
  • ATTENTION
    • T5: Screening for Error Variance
      • Studies 11-15
limitations
Limitations
  • Online samples
  • Largely female
  • Largely Caucasian
  • Lacking behavioral criteria
criterion validity
Criterion Validity
  • DAS Distress groups
    • Current gold-standard
    • DAS score < 97.5
    • 1027 DAS distressed P’s
    • ROC’s to identify CSI cut scores
    • Identified CSI distressed P’s
    • 91% agreement w/ DAS
studies 2 4 demographics
Studies 2-4: Demographics
  • SAMPLE
    • N = 2,056 initial respondents
    • N = 968 (47%) respondents with longitudinal data
  • AGE
    • M = 27.7yo (9.3yrs)
  • GENDER
    • 71% Female
    • 29% Male
  • RACE
    • 83% Caucasian
    • 5% Asian
    • 4% African American
    • 4% Latino
  • SES
    • 10% High school diploma or less
    • 25K avg yearly income
studies 2 4 relationships
Studies 2-4: Relationships
  • Relationship Types
      • 37% Married: 7.9 yrs (7.9 yrs)
      • 13% Engaged: 3.2 yrs (2.4 yrs)
      • 50% Dating: 1.8 yrs (1.9 yrs)
  • Relationship Satisfaction (MAT)
      • Married: 108 (32)
      • Engaged: 122 (24)
      • Dating: 116 (24)
  • Dissatisfied Respondents
      • 24% (n = 487)
study 2 sample
Study 2 - Sample
  • N=596 initial respondents
      • 27yo (SD = 10yrs)
      • 77% Female
      • 84% Caucasian
      • 8% ≤ High school
      • 22K income
      • 30% married, 14% engaged, 55% dating
      • 16% dissatisfied
  • 372 provided email (62%)
  • 267 completed follow ups (71%)
  • NS differences on
      • Length of relationship Relationship satisfaction
      • Age Education
      • Gender
study 3 sample
Study 3 - Sample
  • N=398 initial respondents
      • 26yo (SD = 8yrs)
      • 86% Female
      • 80% Caucasian
      • 9% ≤ High school
      • 20K income
      • 30% married, 12% engaged, 58% dating
      • 24% dissatisfied
  • 252 provided email (63%)
  • 156 completed follow ups (62%)
  • NS differences on
      • Length of relationship Relationship satisfaction
      • Gender Ethnicity
study 4 sample
Study 4 - Sample
  • N=1062 initial respondents
      • 29yo (SD = 9yrs)
      • 79% Female
      • 83% Caucasian
      • 11% ≤ High school
      • 29K income
      • 44% married, 13% engaged, 43% dating
      • 28% dissatisfied
  • 746 provided email (70%)
  • 545 completed follow ups (73%)
  • NS differences on
      • Length of relationship
      • Age Ethnicity
rci and mdc 95 equations
RCI and MDC95 Equations
  • RCI
      • SERM = √2*SD2(1 – rxx)
      • SERM = √2*MSE
      • RCI = (x2 – x1) / SERM
      • If RCI > 1.96

 Sig individual change

  • MDC95
      • Solve RCI eq for (x2 – x1)
      • MDC95 = 1.96*SERM
estimating noise reliable individual change
Estimating Noise &Reliable Individual Change

Guyatt, Walter & Norman (1987); Jacobson & Truax (1991)

NOISE

=

SEM(Standard Error of Repeated Measurement)

=

2*MSE(MSE = Mean Squared Error from a Repeated Measures ANOVA on the T0, F1, & F2 scores of ‘No Change’ individuals)

Dx

Signal

RELIABLE CHANGE

=

=

=

1.98

Noise

SEM

Dx = Minimal Detectable Change (MDC95)(smallest change in scores needed in an individual to suggest reliable change)

estimating power for detecting perceived change
Estimating Powerfor Detecting Perceived Change

Guyatt, Walter & Norman (1987)

Sensitivity to Perceived Change(difference in avg change scores between adjacent perceived change groups)

Signal

POWER

(Effect size)

=

=

Noise

SEM(Standard Error ofRepeated Measurement)

responsiveness model
Responsiveness Model
  • Level 1 – repeated assessments

X2 – X1 = p0 + p1*(global change) +

p2*(deterioration) + e

  • Level 2 – individuals

p0 = b00

p1 = b10 + b11*(T0 rel sat) + b12*(male) + r1

p2 = b20 + b21*(T0 rel sat)

differences by gender
Differences by Gender
  • Scales showed slightly smaller effect sizes in men

*

*

*

*

study 51
Study 5
  • Responsiveness to Mild Intervention
    • Reissman, Aron, & Bergen (1993)
      • Pos. activities over 10wks
      • Fun/Exciting  Enhanced satisfaction
    • 158 randomly assigned to:
      • Control
      • Fun / Exciting Activities Feedback
    • 2wk follow up
      • 25 Fun / Exciting behaviors
      • Satisfaction
  • Scales
      • CSI-32 DAS-32 MAT-15 QMI
      • SMD RAS KMS PN-RQ
fun exciting activities feedback
Fun/Exciting Activities Feedback
  • Background

There is a large body of research supporting the importance of fun in relationships.

Unfortunately, many couples slowly forget to make time to do fun things together the longer they are together.

  • Request

As part of this study, we would like you and your partner to make an effort to have more fun with each other over the next 2 weeks.

Specifically, we would like you to try to do some fun activities that get you out of the house and/or out of your normal routines.

      • These activities should be fun and exciting for both of you.
      • These activities should also involve things that you can do together (like going to dinner) rather than more solitary activities (like reading).
fun exciting activities feedback1
Fun/Exciting Activities Feedback

Based on your responses, here is a list of activities you rated as most fun and exciting:

study 5 sample1
Study 5 - Sample
  • 158 initial respondents (first 3 ½ days of recruitment)
      • 30yo (SD = 11yrs)
      • 74% Female
      • 83% Caucasian
      • 18% ≤ High school
      • 53K income
      • 39% married, 10% engaged, 51% dating
      • 18% dissatisfied
  • xxx completed follow ups (73%)
  • NS differences on
      • Length of relationship
      • Age Ethnicity
prep prevention and relationship enhancement program
PREPPrevention and Relationship Enhancement Program
  • 14 hour workshop over 4 sessions
      • One weekend day
      • Three weeknights
  • Communication Skill Focus
      • Speaker-Listener Technique
      • Problem-Solving skills
      • Time Outs
      • Building Positive Behaviors
  • Goals
      • prevent conflict escalation (improve resolution)
      • enhance/protect positive aspects of relationship
care compassionate and accepting relationships through empathy
CARECompassionate and Accepting Relationships through Empathy
  • 14 hour workshop over 4 sessions
      • One weekend day
      • Three weeknights
  • 3 Acceptance based skill modules
      • Support skills
      • Conflict skills
      • Forgiveness skills
  • Goal: increase understanding/acceptance
      • To buffer ‘rough spots’
      • To smooth out conflict discussions
      • To protect positives
awareness condition
Awareness Condition
  • “Movie” Treatment
      • List of relationship-focused movies
      • Watched 5 movies together
      • 40 min guided discussion after each
      • First movie in a group setting (at UCLA)
  • Yoked Control Group
      • Equivalent time together
      • Equivalent time discussing relationship
      • No active psycho-educational component
hypotheses
Hypotheses
  • All treatment conditions would show better marital quality than no tx
  • CARE and PREP would show better marital quality than the minimal tx
  • CARE would demonstrate comparable tx effects to PREP
longitudinal assessments
Longitudinal Assessments
  • T0 – 1-2 months prior to workshop
  • T1 – start of workshop
  • T2 – 6 months after workshop
  • T3 – 1 year
  • T4 – 2 years
  • T5 – 3 years
previous work1
Previous Work
  • Me/Not-Me task
      • Implicit Closeness  3mo shift in SR closeness

Aron, Aron, Tudor, & Nelson (1991), Aron & Fraley (1999), Slotter & Gardner (2009)

  • Rxn Time on Evaluations
      • High Accessibility  Stronger effects among SR scales

Fincham, Garnier, Gano-Phillips, & Osborne (1995)

  • Partner-focused IAT
      • Pos Implicit Atttitude  Secure attachment (& lower attch avoidance)

Zayas & Shoda (2005)

      • Pos Implicit Attitude  Criterion validity (separating groups)

Banse & Kowalick (2007)

      • Pos Implicit Attitude  Current relationship satisfaction

Scinta & Gable (2007)

  • Self-focused IAT
      • Implicit Relational Worthiness  lower attachment anxiety & preoccupation
      • Implicit Relational Anxiety  preoccupied attachment

Dewitt, de Houwer, & Buysse (2008)

  • Sequential priming task
      • Neg Implicit Attitude  3mo shift in SR satisfaction

Scinta & Gable (2007)

composite codes1
Composite Codes
  • Support Behavior/Affect
      • Emotional Support
        • Understanding Reassuring
        • Responsive Relieving blame
      • Negative Behavior
        • Frustration Hostility
        • Disagreeing Blaming
        • Tension
  • Conflict Behavior/Affect
      • Empathic Listening
        • Tuned into P’s feelings Supportive
        • Validating Interested / Curious
      • Affection
        • Warm / Affectionate Humorous / Playful
      • Negative Behavior
        • Hostile Frustrated
        • Angry Blaming
study 10 analytic strategy1
Study 10: Analytic Strategy
  • Actor-Partner modeling in HLM

LEVEL 1:

Relationship Behavior =

+ p1(male X own satisfaction) + p2(male X spouse’s satisfaction)

+ p3(female X own satisfaction) + p4(female X spouse’s satisfaction)

+ similar sets of APIM terms for hostile conflict & neuroticism

+ p13(male X own partner-good) + p14(male X spouse’s partner-good)

+ p15(female X own partner-good) + p16(female X spouse’s partner-good)

+ p17(male X own partner-bad) + p18(male X spouse’s partner-bad)

+ p19(female X own partner-bad) + p20(female X spouse’s partner-bad)

+ APIM terms for interactions between partner-good and partner bad

+ e

Self-Report Controls

Partner-GNAT

Performance

LEVEL 2:

p1 = b10

p2 = b20

p3 = b30 + b31(rel length) + b32(# of kids)+ r3

p4 = b40

(similar equations for remaining lvl2 effects)

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