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Predicting Psychopathology in Jewish Ultra-Orthodox IPV Survivors: A Machine Learning Approach
Aiala Szyfer Lipinsky
,
Limor Goldner
, Dana Hadar
School of Creative Arts Therapies
Research output
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Contribution to journal
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Article
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peer-review
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Dive into the research topics of 'Predicting Psychopathology in Jewish Ultra-Orthodox IPV Survivors: A Machine Learning Approach'. Together they form a unique fingerprint.
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Keyphrases
Well-being
100%
Ultra-Orthodox Jews
100%
Machine Learning Approach
100%
Survivors
100%
PTSD Symptoms
71%
Self-stigma
42%
Recovery Action
28%
Ultra-orthodox Community
28%
Posttraumatic Cognitions
28%
Israeli
14%
Self-perception
14%
Help-seeking
14%
Posttraumatic Stress
14%
Cultural Values
14%
Strong Predictor
14%
Disengagement
14%
Religious Norms
14%
Cultural Norms
14%
Religious Values
14%
Regression Tree
14%
Random Forest Machine Learning
14%
Active Engagement
14%
Collectivist Society
14%
Violence Attitude
14%
Higher Self
14%
Psychology
Intimate Partner Violence
100%
Post Traumatic Stress Disorder
100%
Psychopathology
100%
Learning Algorithm
16%
Predictor of Psychopathology
16%
Coping Behavior
16%