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Attachment Styles Predict Personal Network Structure Better Than Big Five Traits.

Elena González Tinoco¹, Srebrenka Letina², Isidro Maya-Jariego³

¹https://ror.org/03265fv13University College Cork, Ireland.

The Spanish Journal of Psychology

|July 13, 2026

Summary

Attachment styles significantly shape personal networks, with secure attachment linked to supportive structures and avoidant styles to fragmented ones. This offers new insights into social network analysis and individual differences.

Keywords:

adult attachment latent class analysis personal network typologies personality social network analysis

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Area of Science:

Psychology
Social Network Analysis
Individual Differences

Background:

Individual differences in social network analysis often focus on personality traits.
Attachment research highlights the impact of attachment styles on interpersonal relationships.

Purpose of the Study:

To investigate the relationship between attachment styles and the structural characteristics of individual personal networks.
To compare the explanatory power of attachment styles versus personality traits (Big Five model) in understanding network configurations.

Main Methods:

Developed a classification of personal networks using structural indicators like cohesion, transitivity, and subgroup configuration.
Utilized density, fragmentation, and centralization as key metrics for network clustering.
Assessed the influence of attachment styles, the Big Five personality traits, and sociodemographic variables on network types.

Main Results:

Attachment styles demonstrated greater explanatory power for relational configurations than the Big Five model.
Secure attachment correlated with dense, noncentralized, and supportive personal networks.
Avoidant attachment and openness to experience were associated with fragmented, modular, and less supportive networks.

Conclusions:

Attachment styles are crucial predictors of personal network structures, offering a deeper understanding than personality traits alone.
Personal network structures vary significantly based on individual attachment styles.
Sociodemographic variables were the strongest predictors of personal network type.