Article

Identifying Preliminary Risk Profiles for Dissociation in 16to 25-Year-Olds Using Machine Learning

2025-02-20

Abstract excerpt

<p>Introduction: Dissociation is associated with clinical severity, increased risk of suicide and self-harm, and disproportionately affects adolescents and young adults. Whilst evidence indicates multiple factors contribute to dissociative experiences, a multifactorial explanation of increased risk for dissociation has yet to be achieved. <h4>Methods:</h4> We used multiple regression to investigate the relative in...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: eba997d4-90ce-5ae3-a2e8-d64ff106ee2e
DOI: 10.31234/osf.io/j54v3_v2

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Identifying Preliminary Risk Profiles for Dissociation in 16to 25-Year-Olds Using Machine LearningDOI 10.31234/osf.io/j54v3_v2Read

Identifying risk profiles for dissociation in 16- to 25-year-olds using machine learning.Semantic proximity Read

Identifying risk profiles for dissociation in 16- to 25-year-olds using machine learning.Semantic proximity Read

Predicting identity dissociation using childhood maltreatment and genetic variation in the stress-response gene FKBP5: a machine learning analysis.Semantic proximity Read

Transdiagnostic Profiles of Socio-Affective Functioning in Adolescents At-Risk of Poor Mental HealthSemantic proximity Read

Multidimensional apathy: A simple and inclusive clinical marker of youth mental health—A longitudinal studySemantic proximity Read

Traumatic childhood experiences and levels of personality functioning: Effect of body connection in a cross-sectional German and Chilean sampleSemantic proximity Read

Early Life Trauma Predicts Affective Phenomenology and the Effects are Partly Mediated by Staging Coupled with Lowered Lipid-Associated Antioxidant DefencesSemantic proximity Read

Context Matters: Bridging severity, frequency, duration, and timing of childhood maltreatment experiences through similarity representationsSemantic proximity Read

The quest for a biological phenotype of adolescent non-suicidal self-injury: a machine-learning approach.Semantic proximity Read

Epistemic Trust, Mistrust and Credulity Questionnaire (ETMCQ) validation in French language: Investigating association with lonelinessSemantic proximity Read

Adverse Childhood Experiences, School Bullying Retrospection, and the Impact on Resilience in AdulthoodSemantic proximity Read

Construction and Initial Psychometric Validation of the Morana Scale – A Multidimensional Projective Diagnostic Tool for Assessing the Risk of Destructiveness in a Sample of Individuals Engaged in Mental Health Discourse, Developed Using Artificial IntelligenceSemantic proximity Read