Abstract
Background: Family violence, especially child maltreatment and intimate partner violence, in early childhood has a strong impact on negative developmental outcomes. There is evidence of child, parental, and family risk factors. Less is known about paternal than maternal risk factors. Objective: To identify maternal and paternal predictors of family violence and predictive constellations of risk factors. Participants and setting: According to psychosocial adversity in a larger study, families were stratified into low-, medium- and high-risk groups. Both, mothers and fathers (n = 197/191), were investigated longitudinally across seven months using self-report questionnaires and ratings of the IFEEL Pictures. Methods: chi(2)-tests, logistic regression models, and prediction configural frequency analysis (P-CFA) were employed. Results: Univariate predictors (p < .05) were anxiety and stress in mothers, and insensitivity in recognizing negative child emotions in fathers. Within high-risk levels, paternal adverse childhood experiences (ACE) were a predictor (z = 2.92, p > .01), proven by P-CFA. Logistic regression models including family violence at baseline, sociodemographic variables, univariate predictors, and ACE of both parents revealed maternal anxiety (OR = 1.22, p < .05) and low paternal recognition of negative IFEEL Pictures (OR = 6.00, p < .05) as predictors. P-CFA identified socioemotional problems in children and low paternal recognition of negative child emotions as a predictive risk constellation (z = 2.58, p > .01). Conclusion: Analysis of both caregivers in small population samples with oversampled at-risk families leads to a systemic perspective of family violence. The identified risk constellation is highly relevant for early childhood intervention.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Psychologie und Pädagogik > Department Pädagogik und Rehabilitation |
Themengebiete: | 100 Philosophie und Psychologie > 150 Psychologie |
ISSN: | 0145-2134 |
Sprache: | Englisch |
Dokumenten ID: | 100114 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:33 |
Letzte Änderungen: | 05. Jun. 2023, 15:33 |