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Identifying subgroups of individuals based on their epistemic stance, attachment dimensions and childhood trauma: A
H Delamain1, R Saunders1, M Tanzer2
1CORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), Research Department of Clinical, Educational, and Health Psychology, University College London, London, United Kingdom; Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom.
Background:
The present study examines the interplay between epistemic stance, attachment dimensions, and childhood trauma in relation to specific demographic factors and mental health outcomes. This study aims to understand how these factors form distinct profiles among individuals, to identify those at risk of mental health concerns.
Method:
Latent Profile Analysis (LPA) was employed on a dataset from the general population (n = 500) to identify subgroups of individuals based on their epistemic stance (mistrust and credulity), attachment dimensions, and childhood trauma. Group comparison tests examined differences in sociodemographic variables across the profiles, whilst linear regression analyses investigated between-profile variations in mental health and wellbeing measures.
Results:
The LPA revealed a four-profile solution as the most suitable fit for the data. The latent profiles were characterised as follows: LP1 (14% of the sample; high levels of mistrust and low scores on all other measures), LP2 (62% of the sample; average scores on all measures), LP3 (15% of the sample; highest scores on all measures), and LP4 (9% of the sample; lowest scores on all measures). Between-profile significant differences were found for relationship status and education levels. Linear regression analyses demonstrated variations across the profiles for mental health symptoms and wellbeing measures.
Conclusions:
This study identified four distinct profiles with specific combinations of epistemic stance, attachment dimensions, and childhood trauma. These profiles were associated with differing levels of mental health symptom severity and wellbeing, suggesting their potential utility in informing preventive strategies targeting individuals at highest risk of negative outcomes.
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