Examining Subjective Understanding of Participants and Outside Observers’ in Adolescent Romantic Couples’ Interactions

Joseph W. Dickson1

Melinda S. Harper2

Deborah P. Welsh1

1 University of Tennessee 2 Queens University of Charlotte

Purpose

To simultaneously assess the unique contributions of adolescent dating couple members’ and trained coders’ subjective understanding of an interaction to the prediction of individual and relational functioning at Time 1 and Time 2.

Hypotheses

1. Couple members are expected to perceive their interactions more similarly when compared to trained coders. This difference in subjective understanding is expected to be more divergent for the subjective understanding of couple members’ feelings compared to the subjective understanding of couple members’ behaviors.

2. Couple members’ subjective understanding will predict couple members’ relationship quality at time 1 above and beyond trained coders’ subjective understanding while controlling for other factors impacting couple members’ subjective understanding (i.e. depression and attachment).

Hypotheses (cont.)

3 Couple members’ and trained coders’ subjective understanding at Time 1 will predict relationship satisfaction at Time 2, while controlling for couple members’ relationship satisfaction at Time 1 and other factors impacting subjective understanding (i.e. depression at time of follow-up).

4 Couples’ break-up at Time 2 will be predicted by couple members’ subjective understanding at Time 1 over and beyond trained coders’ subjective understanding.

Participants

The Study of Tennessee Adolescent Romantic Relationships (STARR)

209 adolescent dating couples1

Couples dating a minimum of 4 weeks (range: 4 weeks – 5 years; median: 11 months)

Two assessments approximately 1 year apart (M = 14.8 months, SD = 4.6)

1Couples recruited from a previous study of 2201 high school students from 17 different high schools representing geographic (rural, urban, suburban) and economic diversity

Interaction Procedure Videotape couple having 2 interaction tasks

First Task: Conflictual Issue (as selected by one couple member) (8 min 40 sec)

Second Task: Conflictual Issue (as selected by the other couple member) (8 min 40 sec)

Video-Recall Procedure (Welsh & Dickson, 2005) Conversations viewed twice

Couples Rate own behavior in first viewing Rate partner’s behavior in second viewing

Trained Coders (counterbalanced) Rate one partner in first viewing Rate the other partner in second viewing

40 twenty-second segments rated 7 codes rated for each segment: connection,

conflict, trying to persuade, conceding, discomfort, and frustration

Measures

Time 1:

Relationship Quality – (Levesque, 1993); 5-item scale to assess satisfaction in adolescents’ romantic relationships (α = .85)

Depression – (CES-D; Radloff, 1977); 20-item scale to assess depressive symptomatology during the past week using a four point scale (α = .84)

Attachment – (IPPA; Armsden & Greenberg, 1987); 28-item scale to assess parent attachment (α = .95)

Time 2:

Depression – (CES-D; Radloff, 1977); 20-item scale to assess depressive symptomatology during the past week using a four point scale (α = .90)

Dating Status - Dating status was assessed at Time 2 by asking each participant if they were still dating their original STARR partner (the original partner’s name was supplied for them to reduce confusion)

Results - Descriptive Findings

Due to the high correlations between self and partners’ ratings as well as non-significant paired-samples t-tests (see Table 1), self perceptions and perceptions of their partners were averaged for the variables except conceding.

The correlations examining the similarity of coders’ perceptions highlight that couple members and trained coders have some similarity in their perspectives. (see Table 2)

Using Relationship Quality to assess the construct validity of the six constructs of couples’ communication process revealed good convergent validity except for discomfort and conceding. (see Table 3)

Table 1: Correlations of couples’ communication process and trained coders’ rating of couples’ communication process

Same coder rating behavior and feelings for each couple member Connect Discomfort Frustration Conflict

Trying to Persuade Concede

Boyfriends rating self - Boyfriends rating girlfriends .88** .80** .85** .87** .83** .73**

Girlfriends rating self - Girlfriends rating boyfriends .91** .73** .82** .85** .84** .75**

Coders rating boyfriends - Coders rating girlfriends .86** .56** .73** .83** .73** .12

Table 2: Correlations of couples’ and trained coders’ communication process

Similarity of coders’ perceptions Connect Discomfort Frustration ConflictTrying to Persuade Concede

Boyfriends rating self - Girlfriends rating boyfriends .38** .28** .41** .44** .40** .18**

Girlfriends rating self - Boyfriends rating girlfriends .36** .17* .43** .39** .40** .12

Boyfriends rating self - Coders rating boyfriends .36** .25** .31** .44** .33** .11

Girlfriends rating self - Coders rating girlfriends .43** .18* .48** .41** .40** .20*

* p < .05; ** p < .01

Results – Hypothesis 1 Using analysis of variance, significant differences

were found between the perceptions of trained coders and couple members. The divergent appears to be more clear when rating feelings. (Tables 4 & 5)

Table 4: Means and homogeneous subsets for raters’ subjective understanding of feelings

Rater Connection Rater Discomfort Rater Frustrated

Subset1 2

Subset1 2

Subset1 2

Observers' ratingsof Girlfriend 1.31 Girlfriends' ratings 0.75

Girlfriends' ratings 0.86

Observers' ratings

of Boyfriend 1.34 Boyfriends' ratings 0.93 0.93Observers' ratings

of Boyfriend 0.93

Boyfriends' ratings 2.80

Observers' ratingsof Girlfriend 1.07

Boyfriends' ratings 0.95

Girlfriends' ratings 2.84

Observers' ratingsof Boyfriend 1.12

Observers' ratingsof Girlfriend 1.25

Table 5: Means and homogeneous subsets for raters’ subjective understanding of behaviors

Rater Conflict Rater Persuade Rater Conceding

Subset1

Subset1 2

Subset1 2 3

Girlfriends' ratings 1.30 Girlfriends' ratings 1.22 Observers' ratings

of Girlfriend 0.55

Observers' ratings of Boyfriend 1.37 Boyfriends' ratings 1.29

Observers' ratingsof Boyfriend 0.57

Boyfriends' ratings 1.43Observers' ratings

of Boyfriend 1.51Girlfriends' ratings

of Self 0.60 0.60

Observers' ratingsof Girlfriend 1.49

Observers' ratingsof Girlfriend 1.61

Girlfriends' ratings of Partner 0.69 0.69 0.69

Boyfriends' ratings of Self 0.75 0.75

Boyfriends' ratings of Partner 0.84

Results – Hypothesis 2 Predictive Findings1

Model – 2: Couple members perceived by trained coders as being more connected reported higher relationship satisfaction t(393) = -2.18, p<.01.

Model – 3: Couple members who perceived less conflict (t(392) = -2.01, p<.05), less conceding by their partner (t(392) = -1.99, p<.05), more connection (t(392) = 2.15, p<.05), and feeling less frustrated (t(392) = -3.61, p< .001) during their conversation reported higher relationship quality.

Model – 4: While controlling for trained coders’ subjective understanding, couple members’ who reported feeling less frustrated during the interaction reported better relationship quality, t(386) = -2.78, p<.01. (see Table 6).

1Length of relationship, attachment, and depression were entered into the model as covariates

Results – Hypothesis 3 Model – 2: Couple members who were viewed by trained

coders as conceding more at Time 1 reported significantly lower relationship quality at Time 2, t(132) = -2.08, p < .05.

Model – 3: Couples who were depressed at Time 2 reported significantly lower relationship quality at Time 2, t(131) = -2.07, p < .05.

Model – 4: Couple members who were viewed by trained coders as conceding more at Time 1, reported poorer relationship quality at Time 2. Couples report of connection at Time 1 as well as their report of depression at Time 2 approached significance.

Results – Hypothesis 4 Couple members’ perception of their connection and the

trained coders’ ratings of couple members’ conceding during the interaction significantly predicted breakup at follow-up. The more connection coded by couples gives a higher probability of them still being together at Time 2. The more conceding observed by trained coders during the interaction the higher the probability of them still being together at Time 2. (With the low mean for the variable it may show flexibility)

Conclusions

As found in previous studies, couple members’ subjective understanding of the interaction is more favorable than trained coders’ perceptions.

Trained coders and couple members have different understandings of the

interactions with more divergence in their perceptions of participants feelings.

This study demonstrates participants’ subjective understanding of the

interaction as well as trained coders’ perceptions contribute unique aspects to the prediction of relational and individual functioning over time.

Couple members who were viewed by trained coders as conceding more at Time 1, reported poorer relationship quality at Time 2.

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