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Exploring the Relationship Between Hurtful Messages and Partner Attachment
Unformatted Document Text:  Hurt and Attachment 15 dimensions of attachment. Other variables potentially influencing frequency and degree of hurt (such as gender, length of relationship, and commitment to the relationship) were also assessed as controls. In all models, only the intercept was allowed to vary randomly. All predictor variables were fixed due to the low sample size in addition to no theoretical basis to expect that the slopes of the predictor variables would vary among couples. As previously mentioned, depending on their answer to the question regarding a specific incident during the conflict, they completed the degree of hurt portion in terms of the one incident or in terms of the entire 10-minute interaction. Interestingly, the majority of participants indicated that they were not hurt by a specific message during the interaction (84%) even though they were re-enacting a conflict. Due to the small number of those indicating a specific incident of hurt, only those indicating no hurt during the interaction were included in the analyses (N=86). Additionally, because the partner attachment questionnaire was the last portion of a lengthy set of questionnaires, one partner in 12 couples did not complete this questionnaire reducing the number of cases to 74 (37 couples). Thus, this analysis should be considered exploratory and results should be interpreted cautiously. Results Bivariate correlations (i.e., not accounting for the hierarchical nature of the data) among all predictor and outcome variables are included in Table 1. Table 2 shows the results of the models predicting frequency of HMs. The first model (i.e., the null model) shows that there is significant variance around the intercept between the couples. Additionally, the intra-cluster correlation (ICC = .45), or in other words, the variance between partners in relation to the total variance, indicates that there is substantial similarity between partners’ reports. These both suggest that multi-level analyses are necessary. The null model also serves as a basis for which

Authors: Dailey, Rene. and Le Poire, Beth.
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Hurt and Attachment 15
dimensions of attachment. Other variables potentially influencing frequency and degree of hurt
(such as gender, length of relationship, and commitment to the relationship) were also assessed
as controls. In all models, only the intercept was allowed to vary randomly. All predictor
variables were fixed due to the low sample size in addition to no theoretical basis to expect that
the slopes of the predictor variables would vary among couples.
As previously mentioned, depending on their answer to the question regarding a specific
incident during the conflict, they completed the degree of hurt portion in terms of the one
incident or in terms of the entire 10-minute interaction. Interestingly, the majority of participants
indicated that they were not hurt by a specific message during the interaction (84%) even though
they were re-enacting a conflict. Due to the small number of those indicating a specific incident
of hurt, only those indicating no hurt during the interaction were included in the analyses
(N=86). Additionally, because the partner attachment questionnaire was the last portion of a
lengthy set of questionnaires, one partner in 12 couples did not complete this questionnaire
reducing the number of cases to 74 (37 couples). Thus, this analysis should be considered
exploratory and results should be interpreted cautiously.
Results
Bivariate correlations (i.e., not accounting for the hierarchical nature of the data) among
all predictor and outcome variables are included in Table 1. Table 2 shows the results of the
models predicting frequency of HMs. The first model (i.e., the null model) shows that there is
significant variance around the intercept between the couples. Additionally, the intra-cluster
correlation (ICC = .45), or in other words, the variance between partners in relation to the total
variance, indicates that there is substantial similarity between partners’ reports. These both
suggest that multi-level analyses are necessary.
The null model also serves as a basis for which


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