Mapping bridges between movie preferences, normal-range, and pathological personality traits through network analysis
Abstract
The present study aimed to understand the relationship between cinematic preferences and both normal-range and pathological personality traits. To this end, an Exploratory Graph Analysis (EGA) and a network analysis were performed on a sample of 1482 Brazilian participants aged 18 to 73 years (M = 29.83, SD = 9.45). The sample was composed mainly of women (73.88%), undergraduate students (32.87%), and individuals who self-identified as White (71.19%). Normal-range traits were measured using the Big Five Inventory-2 Short Form (BFI-2-S), pathological traits were assessed with the Personality Inventory for DSM-5 – Brief Form (PID-5-BF+), and film preferences were captured by the Measuring Onscreen Viewing Interests and Entertainment Styles (MOVIES) scale. First, an Exploratory Graph Analysis (EGA) was employed to identify the latent structure of film preferences, yielding four latent clusters of film genres: Intense, Realistic, Fictitious, and Light. Subsequently, a network analysis mapped the associations between these clusters and personality traits, highlighting relationships with Openness, Conscientiousness, Negative Affect, and Psychoticism. These findings illustrate how cultural film preferences and personality traits interrelate, highlighting the potential of using such preferences as an indirect tool for assessing an individual's personality profile for therapeutic purposes. • Openness emerged as a consistent bridge node linking adaptive and pathological traits. • Pornography displayed unexpected community drift, linking to Horror, Comedy, and Antagonism. • Conscientiousness, Negative Affect, and Detachment showed the strongest bridge influence across clusters.
Fields of Study & Subjects
Mental Health Research Topics
Personality Traits and Psychology
Personality Disorders and Psychopathology
Publication details
- Journal / source
- Personality and Individual Differences
- Volume
- 253
- Pages
- 113644–113644
- Publication date
- 10 January 2026
- Language
- EN