A Brief Form of the Child Abuse Potential Inventory: Development and Validation

Abstract

A brief version of the Child Abuse Potential Inventory (CAP) was developed using a development sample of N = 1,470, and cross-validated using an additional sample of N = 713. Items were selected to maximize (a) CAP variance accounted for; (b) prediction of future child protective services reports; (c) item invariance across gender, age, and ethnicity; (d) factor stability; and (e) readability and acceptability. On cross-validation, scores from the resulting 24-item risk scale demonstrated an internal consistency estimate of .89, a stable 7-factor structure, and substantial correlations with the CAP Abuse Risk score (r = .96). The CAP risk cutoff was predicted with 93% sensitivity and 93% specificity (area under the receiver operating characteristics curve = .98), and the Brief Child Abuse Potential Inventory (BCAP) and CAP demonstrated similar patterns of external correlates. The BCAP may be useful as a time-efficient screener for abuse risk.

Predictors of Parenting and Infant Outcomes for Impoverished Adolescent Parents

“…The Brief Child Abuse Potential Inventory (BCAP; Ondersma, Chaffin, Simpson, & LeBreton, 2005) is a 34-item questionnaire that attempts to identify individuals at-risk of engaging in child abuse and is a brief version of the widely used Child Abuse Potential Inventory (Milner, 1986). The BCAP has shown high internal consistency (.89).…”

Predicting child maltreatment: A meta-analysis of the predictive validity of risk assessment instruments

“…Because these reviews lack meta-analysis of quantitative data, it is not yet known how these instruments perform on average. Furthermore, some primary studies report very low predictive accuracies (see, for instance, Barber et al, 2008;Ondersma, Chaffin, Mullins, & LeBreton, 2005), whereas others report far better predictive accuracies (see, for instance, Loman & Siegel, 2004;De Ruiter, Hildebrand, & Van der Hoorn, 2012). Given this rather wide range, synthesizing data in a quantitative manner is essential to get insight in the overall predictive accuracy of risk assessment instruments.…”

The role of organizational insiders' developmental feedback and proactive personality on newcomers' performance: An interactionist perspective.

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