Proximate and Distance Heterosexual Dating Relationships: Differences, Similarities, and Dynamic of Factors that Predict Relational Success

A data set of 1286 heterosexual dating individuals, grouped into 643 couples (406 couples in a Proximate relationship; 237 couples in a Distance relationship), were employed to explore Proximate/Distance similarities and differences in the dynamic of factors that predict relational satisfaction between couples. The primary dependent variable, couple relational satisfaction, was measured with eight items from the GWS and three items from the KMS. Primary predictor variables included eight composite variables (relationship satisfaction, emotional engagement, emotional regulation, family & friend support, shared activities, accuracy of perception, positive illusions, identity, and compatibility). A number of individual variables were also employed, including loneliness, separation, permanence, enjoyment of sex, nurturance, disclosure, emotional stability, co-dependence, and others. A crisscross technique (rate self and partner across all variables) facilitated many comparative procedures. Correlations, t-tests, regressions, and structural equation modeling contributed toward the final picture. Results indicate that (a) Distance couples boast a healthier overall personal and couple profile; (b) accuracy of perception plays a much larger role for Distance couples than for Proximate; (c) nurturance follows a similar pattern with a greater impact for Distance couples; (d) family & friend support plays a larger role in Proximate relationships; (e) emotional regulation plays a larger role for Proximate couples; (f) enjoyment of sex is a significant predictor for Proximate couples but not for Distance; and (g) loneliness, highly characteristic of Distance relationships, does not have a negative impact on relational success for Distance couples but significantly diminishes relational satisfaction for Proximate couples. Findings are discussed and avenues for future research explored.

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The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.