Intimate Partner Violence Risk Assessment in Community Health Facilities: A Multisite Longitudinal Study
Karin Arbach and Antonella Bobbio
Universidad Nacional de Córdoba, ArgentinaReceived 25 October 2017, Accepted 12 March 2018
The remarkable development of tools for the structured assessment of violent reoffending of intimate partner aggressors coexists with a relative scarcity of tools adapted for the diversity of community facilities for women who suffer intimate partner violence (IPV). This situation prompted the development of the RVD-Bcn in Catalonia (Spain). The present multisite prospective study is the first to test the predictive validity of this tool for IPV risk assessment in a sample different to the original. Trained assessors interviewed 321 women in five community health facilities in Córdoba (Argentina); 230 of them completed a follow-up that ranged from 47 to 311 days. Incidents of physical IPV, including serious threats and forced sex, were recorded prospectively. Rates of IPV in the low, moderate and high-risk groups were 10, 57, and 33 percent, respectively. The summary risk ratings were significantly associated with the occurrence of violence during follow-up, as were RVD scores (ROC-AUCs = .88 and .89, respectively). Low-risk participants not only suffered fewer IPV events than participants in the moderate and high-risk group, but also suffered them later in time. The most accurate predictive model of IPV included total scores and a dichotomised variable of low vs. moderate-high summary risk rating. Findings contribute to the emerging practice of including structured violence risk assessment in Latin American professional contexts and institutions.
El notable desarrollo de herramientas para la evaluación estructurada de la reincidencia violenta de los agresores de pareja coexiste con una relativa escasez de herramientas adaptadas a la diversidad de las instalaciones comunitarias para las mujeres que sufren violencia de género (IPV). Esta situación impulsó el desarrollo del RVD-Bcn en Cataluña (España). El presente estudio prospectivo multicéntrico es el primero en probar la validez predictiva de esta herramienta para la evaluación del riesgo de la IPV en una muestra diferente de la original. Asesores capacitados entrevistaron a 321 mujeres en cinco centros de salud comunitaria en Córdoba (Argentina); 230 de ellos completaron un seguimiento que varió de 47 a 311 días. Se registraron prospectivamente incidentes de IPV física, incluyendo amenazas graves y relaciones sexuales no consentidas. Las tasas de IPV en los grupos de bajo, moderado y alto riesgo fueron de 10, 57 y 33%, respectivamente. El resumen de calificaciones de riesgo se asoció significativamente con episodios de violencia durante el seguimiento, al igual que las puntuaciones de RVD (ROC-AUC =. 88 y. 89, respectivamente). Los participantes de bajo riesgo no sólo sufrieron menos episodios de IPV que los participantes en el grupo de riesgo moderado y alto, sino que también tardaron más tiempo en padecerlos. El modelo predictivo más preciso de IPV incluyó puntuaciones totales y una variable dicotómica de calificación de riesgo resumen bajo frente a moderado-alto. Los hallazgos contribuyen a la práctica emergente de incluir la valoración estructurada del riesgo de violencia en contextos profesionales e instituciones en Latinoamérica.
Intimate partner violence, Structured risk assessment, Community health facilities, Prospective.
Violencia de pareja, Evaluación del riesgo estructurado, Instalaciones sanitarias comunitarias, Prospectivo.
Violence against women is a public health problem that cuts across all societies, education and socioeconomic levels, and ethnic and cultural groups (Heise & García-Moreno, 2002). Intimate partner violence (IPV) is one expression of violence against women. In low and middle-income countries of the Americas, IPV prevalence among ever-partnered women is around 30% (2013), and in some countries it reaches 50% (Bott, Guedes, Goodwin, & Mendoza, 2012). In this paper, IPV is defined as any actual, attempted, or threatened physical harm perpetrated by a man against a woman with whom he has, or has had, an intimate, sexual relationship (Kropp & Gibas, 2010).
In the last 20 years, identification of the factors that increase (or decrease) the occurrence of this type of violence has become a primary task in the prevention of violence against women (Capaldi, Knoble, Shortt, & Kim, 2012; Krug et al., 2002). Efforts have also been made to generate empirical evidence on structured techniques that assist professionals in this task (Nicholls, Pritchard, Reeves, & Hilterman, 2013). Tools such as the Spousal Assault Risk Assessment guide (SARA; Kropp, Hart, Webster, & Eaves, 1999), the Brief Spousal Assault Form for the Evaluation of Risk (B-SAFER; Kropp, Hart, & Belfrage, 2005), the Ontario Domestic Assault Risk Assessment (ODARA; Hilton et al., 2004), the Domestic Violence Screening Instrument (DVSI; Williams & Houghton, 2004), and the Danger Assessment (DA; Campbell, 1995; Campbell, Webster, & Glass, 2009), are the IPV risk assessment instruments with the highest empirical contrast around the world (Hanson, Helmus, & Bourgon, 2007; Nicholls et al., 2013). The fundamental difference between them is in the criterion to be predicted. For example, while the SARA and the B-SAFER evaluate the risk of a wide range of new physical violence incidents against an intimate partner of any sex, the ODARA evaluates the risk of violent recidivism against a female domestic partner among men with a police record for such violence, and only the DA has been designed to assess the risk for lethal violence (Otto & Douglas, 2010).
The evaluation of risk factors not only enables an estimate to be made of the risk level of a woman under specific conditions to suffer a new violent event from her partner or ex-partner, but also assists professionals to identify the targets to which they must direct the intervention strategies to reduce risk (Belfrage et al., 2012; Kropp, 2008). This is especially relevant in contexts with limited resources, since the most dangerous batterers can receive services first and receive more intensive monitoring (Cattaneo & Goodman, 2005). Furthermore, IPV risk assessment is suitable not only in police, legal, or correctional services where decisions on aggressors and victims are required daily (López-Ossorio, González Álvarez, Buquerín Pascual, García, & Buela-Casal, 2017), but also in the community health context, due to its central role in the process of IPV detection and intervention (Alvarez López, Brito, Arbach, & Andrés-Pueyo, 2010; Colombini, Mayhew, & Watts, 2008; Messing & Thaller, 2015).
Among Spanish-speaking countries, Spain has led the field in structured IPV risk assessment, with extensive developments in correctional (Echeburúa et al., 2013; Echeburúa, Amor, Loinaz, & de Corral, 2010; Lila, Oliver, Galiana, & Gracia, 2013; Lila, Oliver, Lorenzo, & Catalá, 2013; Loinaz, 2014), forensic (Andrés-Pueyo, Lopez-Ferrer, & Alvarez López, 2008), and police (Garrido-Antón, 2012; López-Ossorio et al., 2017; López-Ossorio, González, & Andrés-Pueyo, 2016; Santos Hermoso & Gonzalez Álvarez, 2017) contexts. Researchers and professionals working on a daily basis in these contexts have been very productive in recent years in systematizing empirical research on IPV risk assessment and management, and this, as from the late 1990s, had a relatively rapid impact on professional practice across many official institutions (Arbach & Andrés-Pueyo, 2016; Arce & Fariña, 2010; Echeburúa, Fernández-Montalvo, & de Corral, 2009; Lila, Oliver, Galiana et al., 2013; López-Ossorio et al., 2017; Muñoz Vicente & López-Ossorio, 2016).
The violence risk assessment perspective was also adopted for community health services by the Barcelona Network Against Gender Violence [Circuit Barcelona contra la Violència vers les Dones, or CIRCUIT in Catalan], in the northeast region of Spain. Between 2008 and 2009, the CIRCUIT developed an instrument to improve professional assessment practices and communication between the many different facilities in the network (e.g., health, police, social, legal, and educational services, including non-governmental organisations). The tool is named RVD-BCN (in Catalan, Risc de Violència vers la Dona-Barcelona), referring to the risk of violence against women (Álvarez et al., 2011).
The RVD-BCN is based on the structured professional judgment model for assessing the risk of severe physical violence by intimate partners. It was designed to be completed when the main source of information is the victim report and no interview with the aggressor is available. There are two versions, the preliminary version used in the original study with 19 risk factors and the final version with 16 risk factors, related to the violent, criminal, and clinical history of the man and some victim vulnerability factors. The RVD-BCN was prospectively validated between 2009 and 2010 in a sample of 216 women attending the CIRCUIT facilities. The instrument demonstrated good levels of internal consistency (α = .71) and predictive validity for the most severe forms of physical violence during a six-month follow-up (with Area Under the ROC-Curves around = .72), suggesting that it may be useful in the assessment and short-term management of this type of violence (Arbach & Andrés-Pueyo, 2014).
In addition to the empirical evidence of its validity, two other features of the instrument make it eligible for being adapted to other contexts. First, both the user manual and the scale itself have been registered under a Creative Commons license, so its free use is permitted (). Second, acceptable levels of satisfaction have been reported by users of the instrument (Andrés Pueyo, Arbach, Lopez-Ferrer, & Nguyen-Vo, 2011, p. 215). Nonetheless, there are no studies testing the predictive validity of the tool in other samples.
In Argentina, studies about violence risk assessment have been carried out by specific research groups, which have been prolific in adapting and validating the tools most used around the world for the South American region (Folino, 2015), including those specific for IPV risk assessment (Kropp, Hart, Webster, & Eaves, 2004). However, local institutions have not generalised this technology into their usual professional practice (Arbach, Bondaruk, Carubelli, Palma, & Singh, 2017; Goldstein, Houck, & Folino, 2015; Singh, Condemarín, & Folino, 2013). For example, the national program for IPV prevention and assistance, which has an annual budget of 10 million dollars, makes no mention of structured IPV risk assessment (Consejo Nacional de las Mujeres, 2016). Moreover, despite figures of violence against women that reach 400 femicides and 86,700 reports per year (Instituto Nacional de Estadística y Censos, 2018), and the resulting strength that feminist movements have gained in Argentina in recent years (Goñi, 2016), no research has been found in PsycINFO, Scopus, ISI Web of Science, Google Scholar, or Latindex reporting data on the validation of techniques for structured intimate partner violence risk assessment in this country. Therefore, the main objective of this study was to analyse the predictive validity of the RVD-BCN for IPV in a sample of female users of community health facilities in Cordoba, a city in the central region of the country with 492,000 adult female inhabitants.Method
The sample was composed of 321 women who attended five public community health facilities: one general hospital (n = 108), one teaching maternity hospital (n = 73), one state maternity hospital (n = 59), the Provincial Council for Women service (n = 53), and one primary health care centre (n = 28). Average age for the total sample at assessment was 37.14 years old (SD = 13.54, range 18-81). The selection criteria were: being more than 18 years old and having had at least one male partner in their lives. Most participants had a male partner at the time of assessment (73.5%) and reported data about him. The rest of the women reported data on their former partner; 63.5% had at least one child, 58.8% had secondary or higher educational level and 52.7% had a paid job. There were differences in the frequency distribution of these characteristics across institutions (see Table 1).
Significant differences were found in mean age, F(4, 302) = 14.20, p < .001. Post hoc comparisons using the Bonferroni test indicated that the mean age for the Provincial Council for Women service (M = 46.85, SD = 1.30) was significantly higher than the rest of the institutions. In addition, significant differences between institutions were found in women having a partner, χ2(4, N = 317) = 30.89, p < .001; child in charge, χ2(4, N = 315) = 58.00, p < .001; educational level, χ2(4, N = 316) = 48.97, p < .001; and having a paid job, χ2(4, N = 306) = 29.17, p < .001 (Table 1).
We used the original research version of the RVD-BCN [in Catalan, Risc de Violència vers la Dona-Barcelona] (Álvarez et al., 2011), which collected information on 19 dynamic and static risk factors, coded dichotomously (0 = absence, 1 = presence) to reach a total score which could range between 0 and 19. After the risk factor information is processed, a final summary risk judgment is required to be made by the assessor that reflects his/her overall professional opinion of IPV risk on a three-point scale (low, moderate, or high) (Andrés Pueyo et al., 2011). This is one of the main characteristics of other instruments based on the structured professional judgment model, such as the Spousal Assault Risk Assessment (Kropp & Gibas, 2010). The predictive validity of this variable was not explored in the original validation study, but a significant correlation was reported with the risk categories established from the ROC curve analysis (r = .56) (Andrés Pueyo et al., 2011, p. 167).
In the original validation study, the mean score of the 16-item version was 7.1 (SD = 2.8) and total scores, which could range between 0 and 16, were significantly correlated with physical violence at three (r = .19) and six (r = .22) months. Furthermore, cut-off scores were established for low (0 to 7, 53% of the sample), medium (8 to 9, 29%) and high (> 10, 18%) IPV risk levels. This categorisation was a good predictor of physical violence in follow-up at 3 (AUC = .77, 95% CI = .68-.87) and 6 (AUC = .80, 95% CI = .71-.90) months, and showed low predictive properties for psychological or minor forms of sexual coercion. Good indexes of inter-rater reliability were also obtained (Andrés Pueyo et al., 2011).
The Ethics Review Committee of the Provincial Maternity Hospital and the National Clinical Hospital of Córdoba approved the research protocol and its administration in the five institutions. The risk assessments were conducted between October 1, 2014 and August 1, 2016, in the context of routine professional practice in the five public community health facilities of the city. In all, we trained 40 assessors (one social worker, one nurse, and several psychologists, physicians, and advanced Psychology students). All of them received 4-to-8-hour training according to their time availability.
Participants were recruited during routine interviews by professionals who explained the aims, methodology and implications of their participation, as well as their freedom to refuse or withdraw their participation in the study at any time without any negative consequences for them. If they agreed to participate, an informed consent was required before they proceeded to the semi-structured interview. Assessments were conducted on the basis of the interviews with women and assessors were not required to consult other sources. Following the principles of the structured professional judgment model, we asked assessors to report a summary risk rating in order to compare using numerical scores.
This was a prospective multicentre study with a follow-up at a minimum of one month. The calculated follow-up time between the IPV risk assessment and the end of the follow-up period for the current sample ranged from 47 to 311 days (M = 133.70, DS = 49.82). There is complete follow-up data for 230 women (72% of those approached). Follow-up interviews were made personally (n = 28, 12%) or by telephone (n = 202, 88%) between January 22, 2015 and December 19, 2016. During this phase, three women did not appear for the scheduled personal interview and 88 women could not be reached after 10 telephone calls. Thus, the follow-up periods varied according to the availability of the women to respond the interview. The personal interview was made by the same assessor as at base assessment. Telephone assessments were made by trainee advanced psychology undergraduates. Of those women contacted by phone, only 6% refused participation during follow-up. At the beginning of the telephone conversation, instructions were provided to guarantee the safety of the victims during the time the call lasted.
In the follow-up, assessors asked women for information about the occurrence after the baseline assessment of several behavioural indicators of physical and sexual violence perpetrated by the current or ex-intimate partner about whom they reported in the base assessment. These indicators included: slapping, pulling hair, pushing, hitting, beating, dragging, kicking, attempted strangulation or attempted burning, throwing objects to hurt, using a knife, weapon or object to attack, forced sex under threats, intimidation or physical coercion, and finally, threats of physical damage against her or her relatives. If participants were detected as being currently victims of violence, they were contacted by the professional who evaluated them in their reference institution so that they could put appropriate protection interventions into effect.
Descriptive analyses (i.e., mean, standard deviation, range, percentages) were performed to explore the distribution and dispersion of variables. A chi-square test was calculated to analyse the independence between summary risk ratings at the baseline assessment and the outcome variable dichotomised as violence present (1 = any indicator occurring at least once during follow-up) or absent (0 = no indicator during follow up), and also to analyse independence between each risk factor and subsequent violence. RVD summary risk ratings were used as an independent variable in analyses.
Only risk factors with a significant association with an outcome variable in bivariate analyses were added to obtain RVD scores. We did not score the RVD if more than four items had missing data. In consequence, seven cases were considered missing for the total score variable, but not for the item level analysis. Internal consistency analyses were performed, and normal distribution was explored using the Kolmogorov-Smirnov test. A Mann-Whitney test was used to compare the RVD total scores between women who had suffered one or more IPV event during follow-up and those who had not.
Receiver Operating Characteristic (ROC) curve analyses were used to examine the predictive validity of the RVD total score and summary risk ratings to predict IPV. ROC curve analysis is widely used in predictive validity research for violence risk assessment tools (Singh, Desmarais, & Van Dorn, 2013). The ROC curve is a plot of the true and false positive rates for the tool, and the area under the curve (AUC) parameter (range 0-1) can be used to compare accuracy between measures. It is particularly useful, as it provides data that are fairly independent of the base rate of violence in a population (Mossman, 1994). Instruments or clinicians able to distinguish violent from non-violent individuals with nearly perfect accuracy would have ROC-AUCs approaching 1.0, and AUC .50 represents no better than random prediction. In general, ROC-AUCs of .75 are considered large effect sizes (Dolan & Doyle, 2000), but recent recommendations on how to report ROC analysis results have been taken into account (Singh, 2014).
To incorporate the length of time from the day of base assessment until the follow-up assessment, survival analyses were carried out. The time-at-risk taken into account was the total of days between assessments. The dichotomous outcome variable was used in a Kaplan-Meier bivariate survival analysis. Cox regression survival analysis was used to examine whether the RVD summary risk ratings added incrementally to the RVD numerical score. A measure’s incremental validity is its ability to provide significant information to the prediction when an alternate variable has already been entered in the model. In doing so, the RVD scores were first entered in a hierarchical Cox regression at block 1, while the summary risk ratings were entered at block 2, with time-at-risk entered as the time variable, and the dichotomous IPV event as the status.
The statistical significance level used was p < .05. Statistical analyses were performed with the IBM SPSS software version 24.0 (IBM Corp., 2016). The data was entered in an ad hoc database with security measures.Results
The overall victimisation rate at follow up was 9%, i.e., 21 participants reporting at least one event of IPV by their partner or ex-partner during that period. The most frequent outcome was threats (7.4%), followed by slapping, pulling hair or pushing (4.3%), forced sex (3.9%), hitting or beating (2.2%). The remaining violent behaviours had a prevalence rate of 1.3% each.
The summary risk rating estimated at the baseline assessment was significantly associated with the occurrence of violence during follow-up, χ2(2, N = 225) = 68.99, p < .001 (Table 2).
We conducted an item-level analysis to know if single items had a unique association with IPV victimisation during follow-up (Table 3). Five vulnerability factors were independent of the IPV condition established prospectively. They were therefore removed from subsequent predictive analysis.
After removing variables not associated with violence in the bivariate analysis, a total score was calculated with one point for each risk factor present. Cases with four or more items without information were removed to avoid cells with missing data. Initial analyses using the Kolmogorov-Smirnov test suggested that the total RVD scores in the entire sample were not normally distributed, D(315) = 0.28, p < .001. The total mean score for participants who completed the follow-up was 2.54 (SD = 3.27, range 0-14, Mdn = 1) and showed no significant difference with the mean of missing cases (M = 2.62, SD = 3.27, Mdn = 1) (U = 9891.50, p = .697). The reliability of the 14-item scale was moderate to high (α = .85). RVD scores were higher for those women who had suffered one or more IPV event during follow-up (M = 8.55, SD = 4.48, Mdn = 9) compared with those who had not (M = 1.91, SD = 2.44, Mdn = 1), U = 472.5, p < .001.
The total score AUC was .89 (95% CI =.79 to .98, p < .001), while the summary risk rating AUC was .88 (95% CI = .80 to .97, p < .001). This suggests that the probability that a randomly selected victim woman had a higher score or a higher risk rating than a randomly selected non-victim woman was 89% and 88%, respectively. Although there is considerable variability in what constitutes a small, moderate, and large value for AUC (Singh et al., 2013), there is general agreement that this effect size represents good discrimination (Rice & Harris, 2005).
Survival analyses take differences in time-at-risk into account and check for unequal follow-up times between participants. Low-risk participants not only suffered fewer events of IPV during follow-up than participants in the moderate- and high-risk groups, but also suffered them later in time. The mean survival time for those participants with high and moderate risk was 157.8 (EE = 30.8) and 175.2 days (EE = 12.5), respectively, versus 287.9 days (EE = 2.9) for participants with a low risk level. The risk groups emerged as significant predictors (log rank = 76.4, df = 2, p < .001) (Figure 1). The mean number of follow-up days did not differ between groups (F = 1.09, p = .34), so differences cannot be attributed to differences in time-at-risk.
Figure 1 shows the rate of IPV events over time for the three summary risk rating groups (low, moderate, high). Log rank tests found significant differences between IPV events of the low risk group (top line) and both the moderate-risk group (middle line), χ2(1) = 51.45, p < .001, and high-risk group (bottom line), χ2(1) = 84.40, p < .001. No significant difference was found between the moderate- and high-risk groups, χ2(1) = 2.20, p = .14.
To account for variations in follow-up time and to assess the incremental contribution of summary risk ratings in predicting recidivism with the RVD scores, a hierarchical Cox regression survival analysis was conducted. The RVD total score was entered at block 1, the summary risk ratings variable at block 2, with the time-at-risk entered as the time variable and the dichotomous IPV variable as the status. The summary risk ratings were entered as a categorical variable (low, moderate and high), and as three dummy variables each collapsing two risk categories (i.e., low vs. moderate/high, low/moderate vs. high, and low/high vs. moderate).
A significant block 1 effect was revealed, χ2(1) = 76.04, p < .001, -2LL = 139.26. The summary risk ratings entered as block 2 produced a significant improvement to the model’s fit (χ2 change = 7.61, df = 1, p < .01). The predictive model composed of the RVD scores and the moderate/high vs. low risk variable showed a good adjustment (-2LL = 131.643, χ2 = 79.64, df = 2, p < .001). Thus, this analysis shows that summary risk ratings added incrementally to numerical RVD scores (Table 4).
The primary goal of this research was to see if the RVD, an instrument for estimating IPV risk in community health facilities, is applicable to populations in Argentina. Our results show that the accuracy of the prediction of future IPV events was good for an adapted 14-item version of the instrument and closely resembled the prediction efficacy of the original RVD 16-item version, and other risk assessment measures in the context of IPV (Nicholls et al., 2013). Furthermore, results show that the summary risk judgments increase the predictive power of the numerical RVD score. Similar findings have been reported for the SARA (Kropp & Hart, 2000) and give support to the idea that little difference exists between actuarial (statistical) and structured tools in predicting violent reoffending, although this does not suggest they are equally informative for case planning, particularly when the goal is to reduce risk (Campbell, French, & Gendreau, 2009). Therefore, we believe that this study provides a sound evidence base for the use of structured violence risk assessment instruments within community facilities where women attend on a regular basis. Physicians, nurses, social workers, psychologists, and other professionals working across a number of professional settings are likely to encounter individuals experiencing IPV, in part due to its negative physical and mental health consequences (Campbell, 2002a; Messing & Thaller, 2015). Thus, an IPV risk assessment instrument, such as the RVD, could be utilised in safety planning, advocacy and counselling (Campbell, 2002b). As was pointed out in a previous validation study, this does not necessarily mean that these instruments will also be effective in any female population or that other instruments will also be effective in this group (Snowden, Gray, & Taylor, 2010). Clearly, further research is needed to secure a sound evidence base for any specific female population (e.g., adolescent or young, disabled or mentally disordered). However, these results support the converging evidence indicating that the combination of a few out of several possible risk factors can be used to produce an effective prediction instrument and that these factors appear to cross most cultural boundaries (Snowden et al., 2010). Hence, while direct evidence is still needed, it would seem likely that this instrument will be effective in other Latin American countries.
As the literature reveals a shortage of prospective, longitudinal studies (Nicholls et al., 2013), the design of this study is a strength, since the occurrence of violence was registered prospectively, which minimized confirmatory biases in the risk assessment process. Nonetheless, prospective predictive research is hampered by meeting the clinical goals of risk assessment, i.e., risk management and prevention (de Vogel & de Ruiter, 2006; Dernevik, Grann, & Johansson, 2002). Thus, it is very likely that subsequent risk management was influenced by the results of the risk assessment. In our study, professionals were able to use the results of the RVD ratings, for instance, for decisions concerning requests for protection orders or to encourage women to make a police report. High-risk participants were referred to specialised care services where they would receive protection measures. In consequence, a higher RVD risk rating could cause increased surveillance, leading to more effective risk management and treatment and to fewer episodes of violence to observe during follow-up. So, the predictive validity indexes that we obtained were already high and similar to those reported for the original study (Arbach & Andrés-Pueyo, 2014), but might have been even higher if the results had not already been used to manage risk.
Previous findings support the belief that appropriately structured risk assessment can prevent violence by informing risk management decisions (Belfrage et al., 2012; López-Ossorio et al., 2017). Thus, as a fruitful line of research in our region, we propose the systematic study of the preventive efficacy that can be obtained by matching the RVD assessment results with the available resources.
The RVD has proven to be a useful tool for the evaluation and management of short-term risk. This is a strength, considering that the critical period of highest recidivism of aggressors is found within the first six months (López-Ossorio et al., 2017). Whether the instrument is useful beyond that period is an empirical question, and it should be explored in future studies. The same applies to the question of whether our findings would be replicated if other forms of violence were used as a criterion. It must be taken into account that the available evidence indicates that physical violence against a partner can be significantly differentiated from other forms of violence, such as lethal violence, or that they can even be different phenomena (Santos Hermoso & Gonzalez Álvarez, 2017). Therefore, the use of RVD is recommended for assessing the risk of the behaviour for which it was validated, i.e., physical violence.
Despite the novelty of this study in the context in which it was developed, some limitations must be considered when interpreting the results. First, the sample was derived from only one Argentinean adult female community sample, thereby limiting generalisation. Nevertheless, we consider this group to be representative of women of the general population attending community facilities, because they are largely similar in demographic characteristics to the total population of adult women in this city (see Gobierno de Córdoba, 2010).
Second, inter-rater reliability of the tool, i.e., the degree of agreement among raters, remains a subject for future research. The workload of professionals and the limited time in public institutions made it difficult to carry out independent evaluations. Although their training was aimed to reduce any assessors’ biases, it is not possible to know in this study the extent to which the assessments were based on the same clues.
A final limitation is that data regarding violent outcomes may not always be reliable. For example, it is possible that women do not report incidents of physical violence in the telephone follow-up calls due to lack of confidence with the interviewer or to an inadequate environment when answering the phone call. Nonetheless, training and supervision of the interviewers was carried out to minimize this effect, and the value of this methodology for screening sensitive topics has been established elsewhere (Mealer & Jones, 2014). Furthermore, although the base rate of violence was relatively low (9%), regional accounts report figures of IPV victims in the last year prior to the assessment ranging from 8 to 25% in other South American countries (Bott et al., 2012). It should be noted, however, that most of these limitations would have had a negative effect on the predictive accuracy of the RVD, and thus the findings might have been even stronger without these limitations.Conclusions
The present study is the first evaluation of violence risk assessments completed using the revised version of the RVD, and the first study to include the RVD summary risk ratings in the prediction model. Its findings add essential new information to the growing evidence supporting structured professional judgment as an approach to assess and manage risk for violent outcomes among females attending community health facilities. They also contribute to the emerging practice of including structured violence risk assessment in Latin American professional contexts and institutions (Arbach & Andrés-Pueyo, 2016; Folino, 2015; Goldstein et al., 2015). An important next step will be to examine whether consideration of a predetermined list of risk factors, and the use of RVD in particular, improves risk management efforts and ultimately reduces the prevalence and severity of violent outcomes. Finally, a comprehensive assessment of violence risk should include consideration of other contextual or institutional factors that have been identified as important variables increasing or decreasing the likelihood of IPV (e.g., the resources available for intervention and the knowledge of such resources by professionals) (Colombini et al., 2008). Although there have been some recent efforts in this area (Belfrage et al., 2012), further work is needed, especially in more disadvantaged regions.
Álvarez, M., Andrés-Pueyo, A., Augé, M., Bogajo, F., Choy, A., Fernández, R., … Serratusel, L. (2011). Protocolo de valoración del riesgo de violencia contra la mujer por parte de su pareja o ex-pareja (RVD-BCN) [The Barcelona guide for severe intimate partner violence risk assessment]. Barcelona, España: Circuito Barcelona contra la violencia hacia las mujeres, Ayuntamiento de Barcelona, Consorcio Sanitario de Barcelona e Instituto Catalán de las Mujeres [Barcelona network against gender violence, Barcelona City Council, Barcelona Health Council and Catalan Institute of Women]. Retrieved from
Alvarez López, E., Brito, C., Arbach, K., Andrés-Pueyo, A. (2010). Detección de la violencia contra la pareja por profesionales de la salud [Detection of intimate partner violence by health professionals]. Anuario de Psicología Jurídica, 20, 31–41. Retrieved from
Andrés Pueyo, A., Arbach, K., Lopez-Ferrer, S., & Nguyen-Vo, T. (2011). Projecte de validació del Protocol de Valoració del Risc de Violencia de Parella contra la Dona (RVD-BCN) [Project for the validation study of the Barcelona guide for severe intimate partner violence risk assessment]. Universitat de Barcelona, Barcelona, España.
Andrés-Pueyo, A., Lopez-Ferrer, S., & Alvarez López, E. (2008). Valoración del riesgo de violencia contra la pareja por medio de la SARA [Intimate partner violence risk assessment using the SARA]. Papeles Del Psicólogo, 29, 107-122. Retrived from
Arbach, K., & Andrés-Pueyo, A. (2014). Evaluación del riesgo de violencia contra la pareja: validación y eficacia predictiva del RVD-Bcn [Intimate partner violence risk assessment: Validation and predictive efficacy of the RVD-Bcn]. In E. García (Ed.), Manual de psicopatología forense: comportamiento humano y Tribunales de Justicia (pp. 477–504). México DF, México: Manual Moderno.
Arbach, K., & Andrés-Pueyo, A. (2016). Violence risk assessment practices in Spain. In J. P. Singh, S. Fazel, & S. Bjørkly (Eds.), International perspectives on risk assessment. Oxford, UK: Oxford University Press.
Arbach, K., Bondaruk, A., Carubelli, S., Palma, F., & Singh, J. P. (2017). Evaluación forense de la peligrosidad: una aproximación a las prácticas profesionales en Latinoamérica [Forensic assessment of dangerousness: An approach to professional practices in Latin America]. Psiencia: Revista Latinoamericana de Ciencia Psicológica, 9, 1–15. https://doi.org/10.5872/psiencia/9.1.23
Arce, R., & Fariña, F. (2010). Diseño e implementación del Programa Galicia de reeducación de maltratadores: una respuesta psicosocial a una necesidad social y penitenciaria [Design and implementation of the Galicia Program of reeducation of abusers: A psychosocial response to a social and penitentiary need]. Psychosocial Intervention, 19, 153-166. https://doi.org/10.5093/in2010v19n2a7
Belfrage, H., Strand, S., Storey, J. E., Gibas, A., Kropp, R., & Hart, S. (2012). Assessment and management of risk for intimate partner violence by police officers using the Spousal Assault Risk Assessment Guide. Law and Human Behavior, 36, 60-7. https://doi.org/10.1037/h0093948
Bott, S., Guedes, A., Goodwin, M., & Mendoza, J. (2012). Violence against women in Latin America and the Caribbean: A comparative analysis of population-based data from 12 countries. Washington, DC: Pan American Health Organization.
Campbell, J. C. (1995). Assessing dangerousness: Violence by sexual offenders, batterers, and child abusers. Thousand Oaks, CA: Sage Publications, Inc.
Campbell, J. C. (2002a). Health consequences of intimate partner violence. The Lancet, 359(9314), 1331-1336. https://doi.org/10.1016/S0140-6736(02)08336-8
Campbell, J. C. (2002b). Safety planning based on lethality assessment for partners of batterers in intervention programs. Journal of Aggression, Maltreatment & Trauma, 5, 129-43.
Campbell, J. C., Webster, D., & Glass, N. (2009). The danger assessment. Journal of Interpersonal Violence, 24, 653-674. https//doi.org/10.1300/J146v05n02_08
Campbell, M. A., French, S., & Gendreau, P. (2009). The prediction of violence in adult offenders: A meta-analytic comparison of instruments and methods of assessment. Criminal Justice and Behavior, 36, 567-90. https://doi.org/10.1177/0093854809333610
Capaldi, D. M., Knoble, N. B., Shortt, J. W., & Kim, H. K. (2012). A systematic review of risk factors for intimate partner violence. Partner Abuse, 3, 231-280. https://doi.org/10.1891/1946-65184.108.40.206.A
Cattaneo, L. B., & Goodman, L. A. (2005). Risk factors for reabuse in intimate partner violence: A cross-disciplinary critical review. Trauma, Violence, & Abuse, 6, 141-175. https://doi.org/10.1177/1524838005275088
Colombini, M., Mayhew, S., & Watts, C. (2008). Health-sector responses to intimate partner violence in low- and middle-income settings: A review of current models, challenges and opportunities. Bulletin of the World Health Organization, 86, 635-642. https://doi.org/10.2471/BLT.07.045906
Consejo Nacional de las Mujeres. (2016). Plan nacional de acción para la prevención, asistencia y erradicación de la violencia contra las mujeres 2017-2019. Ley 26.485 [National plan of action for the prevention, assistance and eradication of violence against women 2017-2019. Law 26.485]. Ciudad Autónoma de Buenos Aires.
de Vogel, V., & de Ruiter, C. (2006). Structured professional judgment of violence risk in forensic clinical practice: A prospective study into the predictive validity of the Dutch HCR-20. Psychology, Crime & Law, 12, 321-336. https://doi.org/10.1080/10683160600569029
Dernevik, M., Grann, M., & Johansson, S. (2002). Violent behaviour in forensic psychiatric patients: Risk assessment and different risk-management levels using the HCR-20. Psychology, Crime & Law, 8, 93-111. https://doi.org/10.1080/10683160208401811
Dolan, M., & Doyle, M. (2000). Violence risk prediction: Clinical and actuarial measures and the role of the Psychopathy Checklist. British Journal of Psychiatry, 177, 303-311. Retrived from
Echeburúa, E., Amor, P. J., Loinaz, I., & de Corral, P. (2010). Escala de predicción del riesgo de violencia grave contra la pareja revisada (EPV-R) [Reviewed scale for the prediction of the risk of serious violence against the couple]. Psicothema, 22, 1054-1060. Retrived from
Echeburúa, E., Fernández-Montalvo, J., & de Corral, P. (2009). Predicción del riesgo de homicidio y de violencia grave en la relación de pareja. Instrumentos de evaluación del riesgo y adopción de medidas de protección [Predicting the risk of homicide and serious violence in the couple’s relationship. Instruments for risk assessment and adoption of protective measures]. Valencia, España: Centro Reina Sofía para el Estudio de la Violencia.
Echeburúa, E., Loinaz, I., Perez, M., Martinez, M., De Corral, P., Arbach, K., … Andrés-Pueyo, A. (2013). Intimate partner violence risk assessment and management in community and in prison samples in Spain: Current evidence and future challenges. 13th International Conference of Forensic Mental Health Services: Empowering Forensic Mental Health Services. International Association of Forensic Mental Health Services. Manchester, UK.
Folino, J. O. (2015). Predictive efficacy of violence risk assessment instruments in Latin-America. The European Journal of Psychology Applied to Legal Context, 7, 51-58. https://doi.org/10.1016/j.ejpal.2014.11.006
Garrido-Antón, M. J. (2012). Validación del procedimiento de valoración del riesgo de los casos de violencia de género del Ministerio del Interior de España [Validation of the risk assessment procedure for cases of gender violence of the Spanish Home Ministry]. Departamento de Psicología Biológica y de la Salud. Universidad Autónoma de Madrid. Madrid.
Gobierno de Córdoba. (2010). Censo Nacional 2010. Población de la Ciudad de Córdoba [National Census 2010. Population of the City of Córdoba]. Retrieved from
Goldstein, N. E. S., Houck, M. J., & Folino, J. O. (2015). Tópicos actuales de la investigación internacional sobre riesgo de violencia [Current topics of international research on violence risk]. Revista Criminalidad, 57(1), 27-43. Retrived from
Goñi, U. (2016). Argentina’s women joined across South America in marches against violence. The Guardian. Retrieved from
Hanson, K., Helmus, L., & Bourgon, G. (2007). The validity of risk assessments for intimate partner violence: A meta-analysis. Ottawa, ON: Public Safety Canada.
Heise, L., & García-Moreno, C. (2002). Violence by intimate partners. In E. G. Krug, L. L. Dahlber, J. A. Mercy, A. B. Zwi, & R. Lozano (Eds.), WHO report on violence and health (pp. 87-121). Geneva, Switzerland: World Health Organization.
Hilton, N. Z., Harris, G. T., Rice, M. E., Lang, C., Cormier, C. A., & Lines, K. J. (2004). A brief actuarial assessment for the prediction of wife assault recidivism: The Ontario domestic assault risk assessment. Psychological Assessment, 16, 267-75. https://doi.org/10.1037/1040-35220.127.116.117
Instituto Nacional de Estadística y Censos [National Institute of Statistics and Census]. (2018). Registro único de casos de violencia contra las mujeres. Resultados estadísticos 2013-2017 [Unique record of violence against women cases. Statistical results 2013-2017]. Ciudad Autónoma de Buenos Aires, Argentina.
Kropp, R. (2008). Intimate partner violence risk assessment and management. Violence and Victims, 23, 202-220. https://doi.org/10.1891/0886-6708.23.2.202
Kropp, R., & Gibas, A. (2010). The Spousal Assault Risk Assessment Guide (SARA). In R. K. Otto & K. S. Douglas (Eds.), Handbook of violence risk assessment (pp. 227-250). New York, NY: Routledge/Taylor & Francis Group.
Kropp, R., & Hart, S. (2000). The Spousal Assault Risk Assessment (SARA) guide: Reliability and validity in adult male offenders. Law and Human Behavior, 24, 101-118. https://doi.org/10.1023/A:1005430904495
Kropp, R., Hart, S. D., & Belfrage, H. (2005). The Brief Spousal Assault Form for the evaluation of risk (B-SAFER). Vancouver, BC: ProActive Resolutions Inc.
Kropp, R., Hart, S. D., Webster, C. D., & Eaves, D. (1999). Spousal Assault Risk Assessment Guide (SARA). Toronto, ON: Multi-Health Systems.
Kropp, R., Hart, S. D., Webster, C. D., & Eaves, D. (2004). Guía para la evaluación del riesgo de violencia conyugal SARA [Spousal Assault Risk Assessment Guide, SARA]. (Spanish version by J. Ó. Folino, Ed., La Plata, Argentina: Ed. Interfase Forense).
Krug, E. G., Mercy, J. A., Dahlberg, L. L., Zwi, A. B., Mercy, J. A., Zwi, A. B., & Lozano, R. (2002). The world report on violence and health. The Lancet, 360, 1083-1088. https://doi.org/10.1016/S0140-6736(02)11133-0
Lila, M., Oliver, A., Galiana, L., & Gracia, E. (2013). Predicting success indicators of an intervention programme for convicted intimate-partner violence offenders: The Contexto Programme. The European Journal of Psychology Applied to Legal Context, 5, 73-95. https://doi.org/10.1174/021347413806196681
Lila, M., Oliver, A., Lorenzo, M.-V., & Catalá, A. (2013). Valoración del riesgo de reincidencia en violencia contra la mujer en las relaciones de pareja: importancia del apoyo social [Assessment of the recidivism risk of violence against women in relationships: Importance of social support]. Revista de Psicología Social, 28, 225-236. https://doi.org/10.1174/021347413806196681
Loinaz, I. (2014). Typologies, risk and recidivism in partner-violent men with the B-SAFER: A pilot study. Psychology, Crime & Law, 20, 183-198. https://doi.org/10.1080/1068316X.2013.770854
López-Ossorio, J. J., González, J. L., & Andrés-Pueyo, A. (2016). Eficacia predictiva de la valoración policial del riesgo de la violencia de género [Predictive effectiveness of police assessment of the gender violence risk]. Psychosocial Intervention, 25, 1-7. https://doi.org/10.1016/j.psi.2015.10.002
López-Ossorio, J. J., González Álvarez, J. L., Buquerín Pascual, S., García, L. F., & Buela-Casal, G. (2017). Factores de riesgo asociados con la reincidencia policial en violencia contra la pareja en España [Risk factors associated with police recidivism in violence against couples in Spain]. International Journal of Clinical and Health Psychology, 17, 107-119. https://doi.org/10.1016/j.ijchp.2016.12.001
Mealer, M., & Jones, J. (2014). Methodological and ethical issues related to qualitative telephone interviews on sensitive topics. Nurse Researcher, 21(4), 32-7. https://doi.org/10.7748/nr2014.03.21.4.32.e1229
Messing, J. T., & Thaller, J. (2015). Intimate partner violence risk assessment: A primer for social workers. British Journal of Social Work, 45, 1804-1820. https://doi.org/10.1093/bjsw/bcu012
Mossman, D. (1994) Assessing predictions of violence: Being accurate about accuracy. Journal of Consulting and Clinical Psychology, 62, 783-792.
Muñoz Vicente, J. M., & López-Ossorio, J. J. (2016). Valoración psicológica del riesgo de violencia: alcance y limitaciones para su uso en el contexto forense [Psychological assessment of violence risk: Scope and limitations for its use in the forensic context]. Anuario de Psicología Jurídica, 26, 130-140. https://doi.org/10.1016/j.apj.2016.04.005
Nicholls, T. L., Pritchard, M. M., Reeves, K. A., & Hilterman, E. (2013). Risk assessment in intimate partner violence: A systematic review of contemporary approaches, 4, 76-168. https://doi.org/10.1891/1946-6518.104.22.168
Otto, R. K., & Douglas, K. (2010). Handbook of violence risk assessment. New York, NY: Taylor & Francis Group.
Rice, M. E., & Harris, G. T. (2005). Comparing effect sizes in follow-up studies: ROC Area, Cohen’s d, and r. Law and Human Behavior, 29, 615-20. htts://doi.org/10.1007/s10979-005-6832-7
Santos Hermoso, J., & Gonzalez Álvarez, J. L. (2017). Homicidio de pareja en España (2007-2016): tiempo entre denuncia, valoración policial del riesgo y muerte [Intimate partner homicide in Spain (2007-2016): Time between complaint, police risk assessment and death]. Behavior and Law Journal, 3, 1-10. Retrived from
Singh, J. P. (2014). Five opportunities for innovation in violence risk assessment research. Journal of Threat Assessment and Management, 1, 179-184. https://doi.org/10.1037/tam0000018
Singh, J. P., Condemarín, C., & Folino, J. O. (2013). El uso de instrumentos de evaluación del riesgo de violencia en Argentina y Chile [The use of violence risk assessment instruments in Argentina and Chile]. Revista Criminalidad, 55, 279-290. Retrieved from
Singh, J. P., Desmarais, S. L., & Van Dorn, R. A. (2013). Measurement of predictive validity in violence risk assessment studies: A second-order systematic review. Behavioral Sciences & the Law, 31, 55-57.
Snowden, R. J., Gray, N. S., & Taylor, J. (2010). Risk assessment for future violence in individuals from an ethnic minority group. International Journal of Forensic Mental Health, 9, 118-123. https://doi.org/10.1080/14999013.2010.501845
WHO. (2013, November 22). Intimate partner violence prevalence: Data by WHO income region. Global Health Observatory data repository. Retrieved from
Cite this article as: Arbach, K., & Bobbio, A. (2018). Intimate partner violence risk assessment in community health facilities: A multisite longitudinal study. Psychosocial Intervention, 27, 105-112. https://doi.org/10.5093/pi2018a13
Funding: Support for this study was provided by the Ministry of Science and Technology of Córdoba, the National Council of Scientific and Technological Research, and the National Agency of Scientific and Technological Promotion from Argentina. The funders had no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
Correspondence: firstname.lastname@example.org (K. Arbach).
Copyright © 2018. Colegio Oficial de Psicólogos de Madrid