Multimethod prediction of child abuse risk in an at-risk sample of male intimate partner violence offenders☆
Introduction
Men remain relatively understudied in the physical child maltreatment literature (Behl, Conyngham, & May, 2003) despite widespread recognition that identifying abuse risk factors for men is critical (Guterman & Lee, 2005). Yet father-figures represent at least half of all physical child abuse in the U.S. (Sedlak et al., 2010). The nascent research contrasting mothers and fathers suggests they demonstrate comparable abuse risk profiles (e.g., with community samples, as in Rodriguez, Smith, & Silvia, 2016a; Rodriguez, Smith, & Silvia, 2016b, or Smith Slep & O’Leary, 2007).
Nonetheless, certain groups are particularly likely to demonstrate increased physical child abuse risk, such as those engaged in other family violence like intimate partner violence (IPV). Although male IPV perpetrators appear to be a high risk group for child maltreatment (Herron & Holtzworth-Munroe, 2002; Margolin, Gordis, Medina, & Oliver, 2003; Rumm, Cummings, Krauss, Bell, & Rivara, 2000), remarkably little work has pinpointed the factors that would elevate child abuse risk in such men. Some efforts to classify IPV offenders suggest three subtypes, wherein one Family-Only category would involve violence within the family differing from those who are Borderline-Dysphoric or Antisocial/Generally Violent beyond the family (Holtzworth-Munroe & Stuart, 1994). If we hope to prevent high-risk groups from perpetrating abuse toward children in the first place, we must identify factors that increase their child abuse potential–the likelihood of engaging in parent-child aggression (PCA) that can culminate in physical abuse (Milner, 1994). Consequently, evaluating child abuse risk with theoretically grounded models applicable to at-risk men, like IPV offenders, continues to be an important research direction.
One theory that has been proposed to describe how physical child abuse occurs is known as Social Information Processing (SIP) theory (Milner, 2000). According to SIP theory, before a discipline situation arises, a parent enters that situation with preexisting schemas that will influence their discipline approach. Such preexisting schemas in SIP theory can include cognitive belief structures (e.g., child and discipline specific beliefs) as well as affective schemas that ensue from previous social interactions. In other words, a parent would carry these schemas into a given discipline situation when four stages commence. The parent must first accurately perceive what is occurring in the discipline situation (Stage 1) and interpret the situation (Stage 2). The parent also must integrate all relevant information from the situation to select a discipline strategy (Stage 3). Those who select PCA then experience difficulty monitoring its application in the final cognitive-behavioral stage (Stage 4). The SIP model implies that the preexisting schemas collectively influence each stage, potentially activating the processes in each of the stages (Milner, 2000). In fact, preexisting schemas may exert these influences by actually compromising SIP stage processing, implying potential moderation of the stages by the preexisting schemas.
Thus far, research supports the application of several elements of SIP theory to predicting physical child abuse risk (e.g., with mothers in Spain, as in de Paúl, Asla, Pérez-Albéniz, & de Cádiz, 2006, and Montes, de Paúl, & Milner, 2001; with expectant mothers and fathers in the U.S., Rodriguez et al., 2016a, Rodriguez et al., 2016b; with a community sample of parents in the U.S., Rodriguez & Richardson, 2007). In terms of evidence for preexisting schemas, one cognitive belief structure, approval of parent-child aggression as a discipline strategy, has been connected to child abuse risk (Bower-Russa, Knutson, & Winebarger, 2001; Crouch & Behl, 2001; Rodriguez, Bower-Russa, & Harmon, 2011; Rodriguez, Gracia, & Lila, 2016). In terms of preexisting positive affective schemas, empathy has been proposed in the SIP model to reduce abuse risk (Milner, 2000). Indeed, low empathy has been observed in abusive mothers (Mennen & Trickett, 2011) and in high abuse risk parents (Pérez-Albéniz & de Paúl, 2004). Alternatively, preexisting negative affective states, such as greater dispositional propensity toward expressing anger, has been implicated in child abuse risk (Ammerman, 1990; Hien, Cohen, Caldeira, Flom, & Wasserman, 2010; see also Stith et al., 2009 for review). For SIP Stage 2, negative interpretations regarding children’s behavior has been linked to greater child abuse risk (Rodriguez et al., 2016a, Rodriguez et al., 2016b). Hostile attributions about children are observed in abusive mothers (Haskett, Scott, Willoughby, Ahern, & Nears, 2006) and such negative child attributions in pregnant mothers predict their later harsh parenting and maltreatment (Berlin, Dodge, & Reznick, 2013).
Conversely, minimal work has explored moderators of child abuse risk although, theoretically, affective components could exacerbate SIP cognitions (Milner, 2000). Although not evaluated as part of the SIP model with regard to abuse risk, parents who report more intensely angry negative attributions of children’s hostile intent were more likely to report reacting more strongly in hypothetical discipline situations (Pidgeon & Sanders, 2009). Another study suggests greater anger may complicate perceptual processes in Stage 1 to elevate abuse risk (Rodriguez, 2016). But the extent to which different preexisting schemas interact with and thereby compromise SIP stage cognitive processes is still unclear. Those who have more adverse preexisting schemas (low empathy, higher anger propensity, and more favorable attitudes toward PCA) may be particularly inclined to adopt negative child attributions (Stage 2) that magnifies their child abuse risk.
Ideally, multiple aspects of such theoretical models are evaluated simultaneously. Adopting a multimethod approach is optimal as this strategy minimizes the reliance on single methods and measures (Eid & Deiner, 2006). Incorporating multiple indicators can balance the weaknesses of a given single indicator, shortcomings that include potential item overlap between measures of predictors and the identified outcome measures. Moreover, our multimethod approach incorporated analog approaches to address concerns regarding the reliance on self-report questionnaires that can be affected by social desirability biases in assessing abuse risk (DeGarmo, Knutson, & Reid, 2006). Implicit assessments assess constructs indirectly, where the intent or scoring is less obvious to the participant, complicating the respondent’s ability to distort their responses (Fazio & Olson, 2003). Indeed, one of the few studies evaluating factors associated with child abuse potential among IPV offenders found few contrasts from a community sample of men which they attributed in part to methodological limitations (Holden, Barker, Appel, & Hazlewood, 2010). Therefore, our multimethod approach includes both multiple indicators as well as analog tasks to strengthen our confidence in analyzing the role of selected constructs in abuse risk.
The present multimethod investigation evaluated elements of the SIP model concurrent with moderators in a high-risk group of male IPV offenders in Spain. SIP preexisting schemas in this study included the acceptability of PCA (a cognitive pre-existing schema) as well as empathy and anger (preexisting dispositional affective schemas); negative child intent attributions were assessed for SIP Stage 2. Specifically, lower empathy, higher anger expression, favorable attitudes toward PCA, and negative child attributions were expected to independently predict men’s physical child abuse risk. In addition, preexisting schemas were hypothesized to exacerbate negative child attributions such that negative child attributions were expected to intensify when men are more anger prone, less empathic, and more inclined to approve of parent-child aggression. These risk factors and interactions have not yet been considered in predicting abuse risk, particularly for men and for an at-risk sample. Evaluating this model with this sample is therefore consistent with past literature pointing to the co-occurrence of IPV and abuse (Margolin et al., 2003).
Section snippets
Participants
The sample included 70 male intimate partner violence perpetrators in Spain who were court-ordered to an intervention program for domestic violence. Offenders had been sentenced to less than two years in prison with no previous criminal record and received a suspended sentence conditional on attendance in a batterer intervention program. Their mean age was 39.08 years (SD = 9.79). Over 75% indicated they had a child, with 30% reporting they were currently married or living with a partner. Nearly
Results
Obtained means and correlations for all outcome measures are presented in Table 1. Compared to other populations, the current sample obtained CAPI scores (M = 24.51; SD = 14.27) only marginally higher (t(69) = 1.70, p = .09 than the general population scores obtained in the Spanish validation of this instrument (M = 21.6; SD = 11.15; de Paúl et al., 1999). These scores are lower compared to CAPI scores for Spanish abusive parents that are around 40 (physical abuse = 45.7; de Paúl et al., 1999). The
Discussion
The current study applied Social Information Processing (SIP) theory to predict physical child abuse potential in a high risk sample of male intimate partner violence offenders in Spain. Findings indicated that low empathy, greater approval of parent-child aggression (PCA), and more negative child intent attributions each significantly increased child abuse risk. Moreover, moderation was demonstrated such that negative child attributions were particularly problematic for those men with lower
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2020, Child Abuse and NeglectCitation Excerpt :This stage includes attentional processes related with the child, such as awareness of children’s behavior, encoding of child-related information, cue detection accuracy, notice of minor changes in children’s behavior, likelihood to observe noncompliant children’ behaviors, ability to distinguish different types of child transgressions, and errors in recognition of the child’s emotional expressions. Specifically, research has been suggesting that high-risk and abusive parents present errors in encoding children’s behavior (e.g., Crouch et al., 2017; Dopke et al., 2003; During & McMahon, 1991; Milner et al., 2011; Miragoli, Balzarotti, Camisasca, & Blasio, 2018) and in recognizing children’s emotions (e.g., Asla, De Paúl, & Pérez-Albéniz, 2011; Francis & Wolfe, 2008; Rodriguez, Gracia, & Lila, 2016), and are more intolerant towards children’s misbehavior (e.g., McElroy & Rodriguez, 2008). Neglectful parents are expected to have more difficulties in perceiving signals indicative of children’s need for attention (Crittenden, 1993).
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2017, European Journal of Psychology Applied to Legal ContextCitation Excerpt :The intervention was developed within the Contexto Program, a psychoeducational and community-based treatment program (mandatory for male abusers) at the Department of Social Psychology, University of Valencia, Spain (see Lila, Oliver, Catalá-Miñana, & Conchell, 2014). The main objective of the program is to reduce risk factors and increase protective factors for IPV, taking into account four levels of analysis: individual, interpersonal, situational, and macrosocial (Catalá-Miñana, Lila, & Oliver, 2013; Gracia, López-Quilez, Marco, Lladosa, & Lila, 2015; Lila, Gracia, & Herrero, 2012; Lila, Gracia, & Murgui, 2013; Rodríguez, Gracia, & Lila, 2016; Romero-Martínez, Lila, & Moya-Albiol, 2016; Vargas, Lila, & Catalá-Miñana, 2015). The sociodemographic characteristics of the sample were as follows: average age was 39.54 years (SD = 11.23); the average annual income was between 6,000 and 12,000 euros.
Revisiting a Multidimensional Model of Intergenerational Transmission of Child Maltreatment
2022, Child Maltreatment: Contemporary Issues in Research and PolicyAcceptability of Family Violence: Underlying Ties Between Intimate Partner Violence and Child Abuse
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Christina Rodriguez was supported by the University of Valencia’s program “VLC-CAMPUS Atracció de Talent” (Grant N° UV-INV-EPC12-67851); Enrique Gracia was supported by the Spanish Ministry of Economy and Competitiveness (PSI2014-54561-P).