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Psychosocial Intervention 22 (2013) 153-160
1132-0559/$ - see front matter © 2013 Colegio Oficial de Psicólogos de Madrid. Todos los derechos reservados
Psychosocial Intervention
www.elsevier.es/psi
PSYCHOSOCIAL
INTERVENTION
Vol
.
22
,
No
.
2
,
August
2013
Psychosocial Intervention
Intervención Psicosocial
Vol. 22, No. 2, August 2013
ISSN: 1132-0559
www.elsevier.es/psi
COORDINADORA ESTATAL
DE INTERVENCIÓN SOCIAL
Batterer intervention programmes: A meta-analytic review of effectiveness
Esther Arias, Ramón Arce* y Manuel Vilariño
Departamento de Psicología Social, Básica y Metodología, Universidad de Santiago de Compostela
Key words:
Batterer
Intervention programme
Recidivism
Reoffending
Effectiveness
Meta-analysis.
Palabras clave:
Maltratador
Programa de intervención
Recidiva
Recaída en el maltrato
Eficacia
Metaanálisis
ABSTRACT
A meta-analysis of the state-of-the-art on the efficacy of batterer treatment programmes was conducted
from the year 1975 to 2013. A total of 19 Spanish and English language research articles were retrieved
yielding 49 effect sizes from a sample of 18,941 batterers. The results revealed that the recidivism rate as
measured by couple reports (CR) was significantly higher than the rate based on official reports (OR), since
the recidivism as measured by OR is underestimated. Overall, treatment showed a non significant positive
weighted mean effect, δ = 0.41. Nevertheless, the counternull effect size, ES
counternull
=0.82, suggested a null
effect was as probable as a treatment efficacy rate of 38%. The intervention type was not a significant
moderator of recidivism, but the counternull effect sizes, ES
counternull
= 0.82 and 0.94, revealed an efficacy
rate of 38% and 42% based on ORs, for Duluth Model and behavioral-cognitive treatment, respectively. The
long-term treatment interventions had a significantly positive medium effect size, δ = 0.49. The implications
of these findings for the design and assessment of future intervention programmes are discussed.
© 2013 Colegio Oficial de Psicólogos de Madrid. All rights reserved.
Programas de intervención con maltratadores: Una revisión meta-analítica de su
efectividad
RESUMEN
Este artículo presenta la revisión metaanalítica llevada a cabo con el fin de conocer el estado actual de la
eficacia de los programas de tratamiento a maltratadores según los trabajos publicados desde 1975 a 2013.
Del total de 19 artículos en inglés y en español recuperados se extrajeron 49 tamaños de efecto a partir de
una muestra total de 18.941 maltratadores. Los resultados muestran que el índice de recaída según reflejan
los informes de parejas era significativamente superior que el de los informes oficiales, dado que en estos
últimos está subestimado. En general el tratamiento presentaba un tamaño del efecto medio ponderado
positivo pero no significativo (δ = 0.41). Sin embargo el valor contranulo del tamaño del efecto, ES
contranulo
=
0.82, indicaba que el efecto nulo era tan probable como un índice de eficacia del tratamiento del 38%. El
tipo de intervención no moderaba significativamente la recaída, aunque los valores contranulos del tamaño
del efecto ES
contranulo
= 0.82 y 0.94 indicaban un índice de eficacia del 38% y 42% respectivamente, de acuerdo
a los informes oficiales, para el tratamiento con el modelo Duluth y el cognitivo conductual respectivamen-
te. Las intervenciones a largo plazo tenían un tamaño del efecto medio significativo positivo de δ = 0.49. Se
comenta la implicación que estos resultados pueda tener para el diseño y evaluación de programas de in-
tervención futuros.
© 2013 Colegio Oficial de Psicólogos de Madrid. Todos los derechos reservados.
Prior to the first meta-analysis on the efficacy of batterers’
treatment programmes, the reviews of intervention programmes
yielded contradictory results. Thus, while Hamberger and Hastings
(1993), and Rosenfeld (1992) concluded that treatments did not
work, Davis and Taylor (1999) found that the effect of treatment was
substantial, h = 0.41. Though several authors (Babcok, Green, & Robie,
2004) assert these effect sizes are modest in terms of Cohen’s (1988)
classification categories, i.e., a small effect size (h < 0.50), it should be
noted that Cohen himself indicated that the magnitude of the effect
size should not be taken as an absolute value, but should rather be
interpreted according to the effects anticipated in a given context.
Thus, if this effect size is contrasted with the effect size between
cognitive distortions and violence as measured in d = 0.82 (Chereji,
Pintea, & David, 2012), corresponding to a 68.5% improvement with
treatment in contrast to 32.5% of the control group (a large effect
size), the results do not appear to be promising. Notwithstanding the
foregoing, in comparison to the treatment efficacy of delinquents as
*e-mail: ramon.arce@usc.es
DOI: http://dx.doi.org/10.5093/in2013a18
INFORMACIÓN ARTÍCULO
Historia artículo:
Recibido: 14/09/2012
Aceptado: 28/02/2013
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154 E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160
measured by the recidivism rate with a small effect size of d ranging
from 0.23 to 0.42 (Redondo, Sánchez-Meca, & Garrido, 1999, 2001,
2002), the data obtained by Davis and Taylor represent an increase
similar to the treatment efficacy expected in this context. Moreover,
the effect size of Davis and Taylor (1999) entails a 20% increase in the
recidivism rate, which is equated to 40% of batterers reoffending in
comparison to the 60% of non-treated offenders. Previous meta-
analyses have identified moderators with significant positive effects
with a small treatment efficacy effect size (Babcok et al., 2004; Feder
& Wilson, 2005; Levesque & Gelles, 1998). Furthermore, these
authors have obtained inconsistent results or even negative
treatment effects. Though the effect sizes were small, they were
comparable to those obtained for the treatment of delinquents and
were indicative of treatment efficacy. To put it another way, a woman
is 5% less likely to be reassaulted by a man who was arrested,
sanctioned, and sent to a batterers’ programme than by a man who
was simply arrested and sanctioned (Babcock et al., 2004, p. 1044).
Working with an estimated population of 100,000 batterers, this
would equal 5,000 fewer batterers; in relation to the hypothetical
recidivism base rate of approximately 25% (Bennett, Call, Flett, &
Stoops, 2005; Gondolf, 2004) this would imply a recidivism rate of
around 20,000 of treated batterers.
The most consistent results highlight that the recidivism base rate
of non-treated batterers as measured by Official Reports (ORs) is
lower (21%) than the measure based on Couple Reports (CRs), which
is estimated to be 35% (Babcock et al., 2004; O’Leary et al., 1989;
Rosenfled, 1992). Surprisingly, previous meta-analyses have tended
to focus on design variables, e.g., experimental vs. quasi-experimental
variables, which have a methodological-scientific significance but do
not provide specific guidelines aimed at enhancing treatment
efficacy. With this purpose in mind, Arce and Fariña (2010), Lila,
Oliver, Galiana, and Gracia (2013) and McGuire, Mason, and O’Kane
(2000) have defined variables which are considered to be
fundamental for the implementation of batterers’ treatment,
specifically for those ordered in the community such as: contents,
length (number and interval between sessions), duration,
intervention level, risk assessment, treatment adherence and
progress, and the rationale underlying intervention. First,
programmes that are tailored to the specific needs of each batterer
enhance treatment efficacy (Holtzworth-Munroe, Meehan, Herron,
Rehman, & Stuart, 2000), whereas standard programmes with
similar content across the board for all batterers not only lack efficacy
but may even prove counterproductive due to the failure to adapt the
intervention to the needs of each batterer (Bowen, Gilchrist, & Beech,
2005). Thus, programmes should seek to address the specific needs
of each individual batterer though in practice this strategy is almost
always neglected. Second, gender violence is entrenched in a culture
of violence that has been described as a form of toxic cognition that
is essentially internal, stable, and global (Maruna, 2004).
Consequently, brief interventions are less effective than long-term
programmes since the duration of each session as well as the number
of and interval between sessions have a decisive impact on the
acquisition and consolidation of socio-cognitive skills given that
domestic violence is grounded in internal, stable, and global
cognition associated to ongoing recidivism and violent behaviour
(Collie, Vess, & Murdoch, 2007; Hutchings, Gannon, & Gilchrist,
2010), which is highly resistant to treatment and hinders adherence
(Isorna, Fernández-Ríos, & Souto, 2010; Wormith & Olver, 2002).
Third, conventional interventions, of which multimodal interventions
(cognitive-behavioural) have proven to be most effective (Beelman &
Lösel, 2006; Redondo et al., 1999, 2001, 2002), have focused
exclusively on the batterer and have often neglected other aspects
that are crucial for social integration and competence through social
bonding and employment. Thus, alienation or unemployment foster
the continuity of a cycle of violence (Fariña, Arce, & Novo, 2008;
Gracia, Herrero, Lila, & Fuente, 2009). Moreover, multimodal
interventions involving individual (cognition) and group
(behavioural) sessions achieve better outcomes than group-only
sessions (Arce & Fariña, 2010; Novo, Fariña, Seijo, & Arce, 2012). An
exhaustive control of treatment adherence and progress is not
feasible in group sessions, and they fail to stengthen responsibility
taking among batterers. Thus, multimodal and multilevel
interventions involving individual and group sessions are more
effective than exclusively individual sessions. Forth, a treatment
requires an ongoing means of measuring the effects of treatment –in
this case, teatment progress. In general contexts, such as clinical
evaluation, the aim of the assessment is to determine treatment
outcomes, but forensic or prison contexts require a differential
diagnosis of feigning (American Psychiatric Association, 2000)
focused on ensuring treatment adherence and progress. In other
words, the feigning of treatment adherence and progress is prevalent
among convicted batterers and sexual offenders who seek to gain
prison benefits, hence the high risk of recidivism. Fifth, the
therapeutic rationale underlying most batterer treatment
programmes undermines treatment efficacy in two ways. Treating
batterers as patients implies batterers are not responsible for their
own behaviour owing to exogenous causes, which hinders treatment
adherence and progress, and justifies the persistance of a culture of
violence (Maruna & Copes, 2005). Furthermore, the professional
implementing the treatment programme may be conceived as an
unwitting accomplice aiding the batterer. An alternative is a rationale
whereby the role of the professional is to apply the law and serve the
wider interests of society to ensure the batterers become fully aware
that they are the only ones to be held directly accountable for their
behaviour.
The assessment of batterers’ treatment programme efficacy has
been the source of much controversy regarding reliability of
measures. Though recidivism in domestic violence is the most
extensively used criterion for measuring treatment efficacy, a wide
range of measures have been employed to assess recidivism rates
such as police or court reports, trial convictions, prison sentencing,
victim reports, partner reports, or even batterer self-reports. Due to
the considerable amount of overlapping between police, court, and
prison databases, these data are often jointly referred to as Official
Reports/Registers. Nevertheless, the reliability of these sources as an
estimate of recidivism remains a controversial issue in the literature
(Novo et al., 2012). For instance, meta-analysis (Babcock et al., 2004;
O’Leary et al., 1989; Rosenfeld, 1992) have found a 21% recidivism
rate based on ORs and 35% rate based on CRs ( = 0.42), i.e., CRs
report 0.42 standard deviation more recidivism than ORs (a medium
effect size). A further instance concerns the treatment effects on
cognition that sanction and forerun (in comparison to cognitive
distortions that have not been shown to precede violence) violence
(Maruna & Mann, 2006) –in this case intimate partner violence,
what Novo et al. (2012) referred to as the internal mechanisms
underlying violence. Though the reliability of these measures based
on psychometric instruments has been attested, recidivism continues
to be the standard measure of batterers’ treatment efficacy, both in
the field of science and in terms of socio-political assessment.
Ever since the advent of batterer re-education programmes, two
models have been the most extensively used for the treatment of
batterers, i.e., the Duluth Model and interventions that have been
encompassed under the umbrella term of Cognitive-Behavioural
Treatment programmes (CBT). The former, which is currently the
most prominent of the two models, takes its name from the
pioneering programme set up in Duluth (Minnesota) and combines a
gender (feminist) approach with a psychoeducational approach
grounded in the assumption that the primary cause of gender
violence is patriarchal and sexist ideology that sanctions male
dominance and relegates women to submissive obedience. Hence,
the goal of treatment is to challenge male dominance and to foster
egalitarian relationships. On the other hand, CBT programmes
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E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160 155
envisage violence as a learned behaviour, which is best offset by
promoting and reinforcing non-violent alternatives aimed at
developing social skills and anger management (Babcock et al. 2004).
A further option arising from literature reviews and meta-analysis is
the creation of another treatment category referred to as “Other
Types of Intervention” (OTI) covering a wide variety of treatment
programmes such as Psychodynamic counselling, Anger Management,
and Mind Body Bridging.
Thus, the aim of this study was to perform a meta-analysis to
learn the state-of-the-art of the efficacy of batterer treatment
programmes from the 1975 to 2013 by assessing studies measuring
treatment efficacy in terms of the recidivism rate.
Method
Database search
The search was restricted to studies assessing batterers’
treatment programmes efficacy from 1975, one year after
Martinson’s (1974) doctrine suggesting that “nothing works” in
relation to the treatment of delinquents, to the present date (2013).
A review of the batterers’ treatment literature was undertaken
using the following search strategies: a) search in broad spectrum
databases (both small databases and specialized databases with
quality control such as Scopus and the Web of Knowledge were
included), such as PsycInfo, ERIC, Scirus, Google, and Google
Academia; b) search in gender violence observatories (e.g., www.
work-with-perpetrators.eu; www.VAWnet.org; www.mincava.
umn.edu; www.courtinnovation.org; www.cienciaspenales.net;
www.iresweb.org); c) researchers in the field were contacted (i.e.,
the corresponding authors of both retrieved and excluded articles
were contacted); and d) the reference sections of previous meta-
analysis were reviewed and cross-referenced.
The list of keywords was generated through a system of successive
approximations whereby relevant keywords cited in the articles and
previous meta-analysis were cross-referenced. The most productive
keywords (other keywords overlapped with the search results) were:
batterer, intervention program, evaluation, assessment, effectiveness,
intimate partner violence, partner-violent men, recidivism,
reoffending, attrition, domestic violence, batterers’ reeducation
programmes, gender violence aggressors, recidivism, programmes
evaluation, prison treatment, and efficacy.
Criteria for inclusion in the study
Bearing in mind the objectives of the meta-analysis, in order to be
selected for the study the articles retrieved from the database search
should meet the following criteria: a) report sample size; b) report
recidivism rate for treatment completers; c) recidivism measured by
ORs (official reports, e.g., police, court, or prison reports) and couple
reports (the aggressor self-reports were excluded since batterers
tend to underreport the true incidence of abuse which would
contaminate the results); d) describe the treatment theoretical
approach, contents, and duration of the intervention programme;
and e) measure recidivism during the follow-up period (studies with
a follow-up shorter than 6 months were discarded). In studies where
relevant data were lacking, the authors were contacted to request
additional data to be subsequently added to the meta-analysis. By
applying these criteria, 19 articles from Spanish and English authors
were retrieved, yielding 49 effect sizes from a sample of 18,941
batterers.
Data analysis
The procedure consisted of a bare-bones meta-analysis. As the
measure of recidivism is often expressed as percentages/proportions
and in the studies where this was not the case it was converted into
proportions, the measure of recidivism adopted in this meta-analysis
was the proportion of reoffending batterers (data on recidivism in
other offences were excluded) during the follow-up period. The
measure of the effect size was calculated on the basis of the difference
in proportions. This involves a previous non-linear transformation of
proportions since the simple difference in proportions is not an
accurate estimate of effect size –the difference in proportions does
not provide a scale of equal detectable units. The effect size in terms
of proportions was calculated using Cohen’s h (1988) and Hedges
and Olkin’s δ (1985) based on the procedure of Kraemer and Andrews
(1982). The results of both methods of analysis were similar, with
almost equivalent sizes in the low values and a slightly larger size for
the higher for the δ statistics. Nonetheless, this did not affect the
qualitative evaluation of the effect size.
In the h index, the percentages were transformed into Φ by the
formula 2arcsin√p. The substraction of the transformed proportions
was h. For the δ statistics, in line with the procedure of Kraemer-
Andrews, the pre- post test effect size was estimated by the difference
of the inverse of the normal cumulative distribution function,
Φ
–1
.
Thus, δ is the difference of the inverse function of the probability of
the experimental group minus the control,
^
δ
1
= Φ
–1
(
^
p
1
E
) – Φ
–1
(
^
p
1
C
). The
difference of the inverse function in percentages (δ) or of the Φ (h),
that is, an effect size of 0.20, 0.50, and 0.80 was considered to be
small, medium, and large respectively. The δ was the index of choice
for the results of the meta-analysis. The studies that met the inclusion
criteria were classified as either experimental or quasi-experimental.
The experimental design studies (see Table 1 for the list of retrieved
articles and the selection criteria) show two recidivism rates, one for
the experimental group, i.e., batterers who had completed treatment
and another for the control group, i.e., non-treated batterers. The
batter intervention studies with a non-equivalent control group
design, e.g., studies comparing treatment completers with treatment
dropouts, were classified as quasi-experimental (see Table 2 for the
list of the 13 retrieved articles and the selection criteria). Given that
treatment non-compliance is associated to recidivism, i.e., recidivism
rates among treatment dropouts are higher or even doubled the rate
among non-treated batterers (Bennett & Williams, 2001; Dutton,
Bodnarchuk, Kropp, Hart, & Ogloff, 1997), studies contrasting the
recidivism rates of non-equivalent control groups artificially amplify
treatment efficacy. As for these designs, the recidivism rate contrast
values were .21 for ORs, and .35 for CRs, which are in accordance
with the base rates that have been consistently reported in the
literature (Babcock et al., 2004; O’Leary et al., 1989; Rosenfeld, 1992).
Once the effect sizes had been calculated, the following were
computed: the weighted mean δ for the entire sample size; the
observed weighted mean variance (S
2
δw
); standard deviation (SD
δw
);
the true variance (S
δ2
); standard error (SE
δ
); and the confidence
interval (90% CI). If the interval contained zero, it indicated
heterogeneity (no significant effect) and further analysis was
conducted to successively examine other moderators.
To estimate the practical utility of treatments, the Binomial Effect
Size Display (BESD) was applied (Rosenthal & Rubin, 1982)
transforming δ into r by means of the formula r = δ/√δ
2
+ 4. The r was
converted to a BESD by means of the formula (.50± r/2) * 100. The
measure of overlapping distributions was performed by U1 statistic
(Cohen, 1988).
Most of the effect sizes were not significant (the confidence
intervals contained 0), indicating the acceptance of H
0
. However, the
confidence intervals were not exactly precise for accepting the null
hypothesis (Cortina & Dunlap, 1997; Frick, 1996). For the effects that
were not significant (the confidence interval contained 0) with a
medium or large effect size, the hypothesis of a null effect (0) was
contrasted by means of ES
counternull
(Rosenthal & Rubin, 1994)
,
the
formula for the size in terms of the correlation being, r
counternull
=
√(4r
2
)/(1 + 3r
2
).
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156 E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160
Coding
For the analysis of moderators the following were coded: the
recidivism variables (OR, n = 18,148, k = 33; CR, n = 1,456, k = 13);
follow-up time (less than 12 months, k = 13; more than 12 months, k
= 35); duration of treatment (< 16 sessions/weeks and > 16 sessions/
weeks); intervention level (individual vs. multilevel –the multilevel
intervention contingency was not registered); type of session
(individual, group, or combined –no type of intervention [individual or
combined] contingency was registered. Although Stith, Rosen, &
McCollum, 2004 defined a couple intervention as an individual
intervention [experimental group 1], actually this is not an individual
intervention); contents (adapted to the needs of each batterer vs.
homogeneous for all batterers –only one contingency was registered
that may be attributed to adapted content, but it referred to clinical
cases [group 3 of the study of Coulter & VandeWeerd, 2009], not to
batterer treatment); treatment adherence and progress (control of
treatment adherence and progress: yes vs. no –no contingency was
registered in the measurement of this variable); rationale behind the
intervention (therapeutic vs. re-educational –information was not
available for coding this variable in a reliable way); risk control (yes vs.
no –information was not available for coding this variable in a reliable
way); and treatment type (Duluth, k = 29; CBT, k = 8; and OTI, k = 9).
Coding reliability. The coding was carried out separately by two
researchers who agreed on all of the coding of the different categories.
Thus, coding was reliable.
Results. The results reveal a significantly higher rate (+.156), z =
13.0, p < .001, with a very substantial difference (< 13 SD) in
recidivisms as measured by CRs in comparison to ORs. Thus, the ORs
entail covert recidivism given that this rate may be higher as many
couples refused to report their partner’s recidivism due to the threat
of re-victimization (i.e., a woman may fear that the disclosure of
recidivism in the presence of her partner may lead to subsequent
retribution), a recidivism rate of .156 that was significantly greater, z
= 51.23, p < .001, than the statistically admissible margin of error
(.05).
Outlier analysis
Prior to performing the meta-analysis, an outlier analysis was
performed to avoid contaminating the results. As treatment efficacy
varies according to the variable under assessment, an outlier analysis
was conducted for each measure, with the decision criterion being
±2SD of the mean effect size δ. The results found that three studies of
Stith et al. (2004) were more than 2 standard deviations above the
mean for treatment efficacy and were thus eliminated.
Global analysis
Figure 1 illustrates the procedure for calculating the 17 meta-
analysis, as well as the resulting effect sizes (δ), the number of
studies (k) included in each analysis, and the sample size (n). Of the
Table 1
Quasi-experimental designs
Study n Treatment type and
intervention format
Duration an d length
of intervention
Measure of recidivism
during follow-up
Recidivism rate % Recidivism rate δ
1. Saunders (1996) G1: 61
G2: 68
G1: Duluth + CBT
G2: Psychodynamic process
Group
12 sessions + 20
support (32 weeks)
24 months (OR -CR) OR
G1: 23.2%
G2: 20.3%
CR
G1: 34%
G2: 33.3%
OR
-0.07
0.02
CR
0.03
0.05
2. Dobash, Dobash,
Cavanagh and Lewis
(1996)
40 Duluth
Group
6-7 months 12 months (OR -CR) OR: 7% CR: 33% OR: 0.67 CR: 0.05
3. Murphy, Musser, and
Maton, (1998)
235 Duluth
(format not specified)
22 sessions 12-18 months (OR) OR:15.7% 0.2
4. Babcock and Steiner
(1999)
106 Duluth
Group
36 weeks 24 months (OR) OR: 8% 0.6
5. Jones and Gondolf
(2002)
P1:213
P2:208
P3:215
P4:217
Duluth
Group
P1: 3 months
P2: 3 months
P3: 5.5 months
P4: 9 months
15 and 30 months
(OR)
OR
P1
P2
P3
P4
15m
31.5%
31.8%
26.2%
24.7%
30m
41.2%
38.6%
34.2%
28.2%
OR
P1
P2
P3
P4
15m
-0.32
-0.33
-0.17
-0.12
30m
-0.58
-0.52
-0.4
-0.23
6. Jenkins and Menton
(2003)
114 CBT
Group
9 weeks 30 months (OR) OR: 10% 0.47
7. Bowen, Gilchrist, and
Beech (2005)
86 Duluth
Group
24 weeks + 5
sessions
11 months (OR) OR: 21% 0
8. Bennet, Call, Flett, and
Stoops (2005)
384 Duluth
Group
24 weeks 18 months (OR) OR: 15.4% 0.21
9. Labriola, Rempel, and
Davis (2005)
157 Duluth
Group
26 weeks 12 months (OR) OR: 6% 0.75
10. Tolleffson and Gross
(2006)
102 Duluth
Group
20 sessions 7-58 months (OR) OR: 18% 0.11
11. Tollefson, Webb,
Shumway, Block, and
Nakamura (2009)
57 Mind-body Bridging
Group
8-10 sessions 9-27 months (OR) OR: 9% 0.53
12. Coulter and
VandeWeerd (2009)
G1:1424
G2: 9386
G3:1712
G1 and G2 Duluth Group
G3 specialized Treatment
G1: 8-12 weeks
G2: 26 weeks
G3: 26 sem-1year
1-10 years (OR) OR
G1: 8.8%
G2: 8.3%
G3: 8.6%
OR
G1: 0.55
G2: 0.58
G3: 0.56
13. Pérez, Giménez-
Salinas, and Juan
(2012)
598 CBT
Group
25 weeks 12 months (OR) OR: 4.6% 0.88
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E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160 157
46 initial effect sizes, with a sample of 18,941 subjects, the δ weighted
mean was 0.41, 90% CI [-0.12, 0.94], that is, the results revealed a non
significant positive treatment effect. What is more, treatment may
have considerable negative effects: as much as a 6% increase in the
recidivism rate. Notwithstanding this, the effect size is not necessarily
null, ES
counternull
= 0.82, that is, there is as much evidence to support a
un null treatment effect as there is to show a 38% intervention
efficacy rate. Nevertheless, the credibility interval of the effect size
suggested the existence of further moderators. Thus, the studies
were classified according to the duration of the follow-up period,
Table 2
Experimental designs
Study n Treatment type and
intervention format
Duration and length
of intervention
Measure of recidivism
during follow-up
Recidivism rate % Recidivism rateδ
1. Davis, Taylor, and
Maxwell (1998)
376
G1: 129
G2:61
GC: 186
Duluth
Group
39 hours
GE1: 8 weeks
GE2: 26 weeks
GC: TBC
6 and 12 months
(OR-CR)
OR 6m
G1: 7%
G2: 15%
GC: 22%
CR 6m
G1: 23%
G2: 19%
GC: 21%
OR 12 m
G1: 10%
G2: 25%
GC: 26%
CR 12m
G1: 14%
G2: 18%
GC: 22%
OR 6m
G1: 0.7
G2: 0.26
CR 6m
G1: -0.07
G2: 0.07
OR 12 m
G1: 0.64
G2: 0.03
CR 12m
G1: 0.31
G2: 0.14
2. Dunford (2000) 861
G1: 168
G2: 153
G3: 173
GC: 150
CBT
G1 and G2 Group
G3 Individual
G1: 12 months (6
session weekly and 6
month)
G2: 26 weeks +
6-month
G3: 12-month
6 months (CR)
12 months (OR)
OR
G1: 4%
G2: 3%
G3: 6%
GC: 4%
CR
G1:29 %
G2: 30%
G3: 27%
GC: 35%
OR
G1: 0
G2: 0.13
G3: -0.19
CR
G1:0.17
G2: 0.14
G3: 0.22
3. Feder and Dugan
(2004)
404 Duluth
GE: Programme
GC: Conditional
26 weeks 12 months (OR) GE: 24%
GC: 21%
GE: -0.1
4. Stith, Rosen, and
McCollum (2004)
39
GE1: 14
GE2: 16
GC: 9
Duluth + CBT
GE1 Partner
individual
GE2: Partners Group
GC: Pretest and
follow-up
6 weeks 6 and 24 months (CR) 6 months
GE1: 43%
GE2: 25%
GC: 67%
12 months
GE1: 0%
GE2: 13%
GC: 50%
6 months
GE1:0.62
GE2:1.11
12 months
GE1:1.53
GE2:1.13
5. Lin et al. (2009) 301
GE: 70
GC: 231
Duluth + CBT
Group
12-18 weeks 6 and 9 months (CR) 6 months
GE:34.3%
GC:34.2%
9 months
GE:27.1%
GC:21.2%
6 months
-0.003
9 months
-0.19
6. Taylor and Maxwell
(2009)
629
GE:317
GC: 312
Duluth
Group
5 days 6 and 12 months (OR) 6 months
GE:65.9%
GC:65.7%
12 months
GE:68.6%
GC:69.6%
6 months
-0.005
12 months
0.03
GLOBAL
K = 46
δ = 0.41
N = 18,941
OR
k = 33
δ = 0.42
n = 18,148
CR
k = 13
δ = 0.05
n = 1,456
FOLLOW-UP FOLLOW-UP
TREATMENT
DURATION
TREATMENT
DURATION
TYPE OF
INTERVENTION
TYPE OF
INTERVENTION
< 1 year
k = 4
δ = 0.18
n = 593
< 1 year
k = 29
δ = 0.04
n = 17,555
< 1 year
k = 8
δ = 0.03
n = 1,188
< 1 year
k = 5
δ = 0.12
n = 268
Duluth
k = 24
δ = 0.41
n = 15,044
Duluth
k = 5
δ = 0.12
n = 217
TCC
k = 3
δ = 0.18
n = 494
TCC
k = 5
δ = 0.47
n = 1,206
OTI
k = 5
δ = 0.06
n = 745
OTI
k = 4
δ = 0.52
n = 1,898
> 16 sessions
k = 19
δ = 0.49
n = 14,517
≤ 16 sessions
k = 14
δ = 0.18
n = 3,631
≤ 16 sessions
k = 6
δ = 0.16
n = 434
> 16 sessions
k = 5
δ = 0.14
n = 420
Figure 1. Meta-analytical model for examining recidivism reports, duration of follow-up, and intervention type as moderators
Note. OR = Official reports; CR = Couple reports; δ = weighted mean effect size; k = number of effect sizes for each analysis; CBT = cognitive-behavioural treatment programmes;
OTI = other types of intervention. In the analysis of the moderator treatment duration the results of the study of Lin et al. (2009) were not included since the duration of the in-
tervention was not accurately specified (from 12 to 18 weeks).
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158 E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160
since previous reviews claim it is one of the main moderators of
criminal recidivism (Gondolf, 2000, 2002; Redondo et al., 2001) and
since prior analysis have found differences in recidivism as measured
by ORs or CRs in relation to the follow-up period.
Effects due to the variable of the measure of recidivism
The meta-analysis of the ORs with an n of 18,148 batter ers found
a non significant positive weighted mean treatment effect, δ = 0.42,
90% CI [-0.07, 0.91]. However, as the magnitude of the size was close
to medium, the counternull effect was computed, ES
counternull
= 0.84,
indicating that the probability of finding a null recidivism treatment
effect is equal to getting a 39% success rate. As for the meta-analysis
of the CRs with a total population of 1,456 batterers, treatment effect
was not significant, δ = 0.05, 90% CI [-0.52, 0.63]. Moreover, the CI
showed that treatment might have negative or even detrimental
effects leading to increased recidivism rates reaching 27.8% (δ =
-0.52).
Given that the confidence intervals for both the ORs and CRs
measures of recidivism had a negative lower limit, i.e., though
treatment had a positive weighted mean effect it may also have had
a negative effect, further search for moderators was undertaken to
identify the variables underlying the difference in effects.
Effects due to the measure of recidivism and follow-up time. In line
with previous studies that assert that recidivism occurs primarily
within the first two years, and in the case of domestic violence in the
first six months (Gondolf, 2000, 2002; Redondo et al., 2001), the two
follow-up categories were coded: < 12 months and ≥ 12 months. The
results revealed an effect size for recidivism as measured by ORs at
12-month follow-up (k = 4) of δ = 0.18, 90% CI [-0.36, 0.65], that is, a
positive but non significant mean effect size that may even be highly
negative (succinctly, the recidivism rate may rise to 17.7%), whereas
for a follow-up period longer than 12 months (k = 29) of δ = 0.04, 90%
CI [-0.45, 0.53] there is a not significant or near null effect that can
be very negative (i.e., it can lead to a 22.0% increase in the recidivism
rate). Likewise, the treatment effects in the measure of recidivism in
CRs revealed a non significant mean effect close to 0, with negative
effects of 28.3% at 12-month follow-up (k = 8), δ = 0.03, 90% CI [-0.59,
0.65] and non significant positive and potentially negative effects
reaching 18.2% in the follow-up period longer than 12 months, (k =
5), δ = 0.12, 90% CI [-0.37, 0.61]. These results indicated the confidence
intervals of δ had a negative lower limit both in the OR and CR
measures and in both follow-up periods, thus an analysis of the
moderators was conducted. At this point, the moderator type of
analysis was the best candidate for analysis, since numerous studies
have reported that treatment type has effects on recidivism, the
highest effects being observed in cognitive-behavioural treatments
(Redondo et al., 1999, 2001, 2002). Bearing in mind that the effects
size were not significant and overlapped (U1 = .00 and .04, for the
overlapping distribution of the short and long-term follow-up in the
ORs and CRs, respectively), the variance for the short and long-term
follow-up in the ORs and CRs was small (S
2
= 0.11, and 0.14 for short-
term follow-up in the ORs and CRs, respectively, and 0.09 and 0.09
for the long-term follow-up in the ORs and CRs, respectively), and
the distribution of treatment types for each of the follow-up periods
would entail several cells with insufficient studies, the ORs and the
CRs were aggregated for the analysis of treatment types (cognitive-
behavioural, Duluth, and others).
Effects due to the measure of recidivism and the type of intervention.
The results of the meta-analysis exhibited a non significant positive
mean effect in the ORs for the Duluth Model treatment type (k = 24),
δ = 0.41, 90% CI [-0.09, 0.92]; a non significant positive mean effect
for the CBT programmes (k = 5), δ = 0.47, 90% CI [-0.20, 1.14]; and a
significant positive mean effect and a moderate size for the OTI (k =
4), δ = 0.52, 90% CI [0.29, 0.75]. As the effect sizes were not significant
for the Duluth Model or the CBT programmes, but were approximately
a medium size, they were contrasted with a null effect. Counternull
effect size was 0.82 for the Duluth Model, that is, data suggested that
the probability of the null effect for the Duluth Model in reducing
recidivism was equal to a 38% efficacy rate. As for the CBT
programmes, a ES
counternull
= 0.94 supported as much a null effect as a
42% success rate. In the measure of recidivism based on CRs the
results found a non significant positive mean treatment effect of the
Duluth Model (k = 5), δ = 0.12, 90% CI [-0.06, 0.30]; a non significant
positive mean effect of the CBT programmes (k = 3), δ = 0.18, 90% CI
[-0.08, 0.44]; and a non significant negative mean effect of the OTI,
(k = 5), δ = -0.06, 90% CI [-0.81, 0.69]. In other words, treatment may
even have negative effects on recidivism rates reaching 37.5%.
Effects due to the measure of recidivism and the duration of the
intervention. The measure of recidivism based on ORs in the brief
interventions had a non significant positive weighted mean effect
(k = 14), δ = 0.18, 90% CI [-0.58, 0.94]; and long-term programmes had
a statistically significant weighted mean positive effect (k = 19),
δ = 0.49, 90% CI [0.05, .93), i.e., a medium positive effect size.
The treatment effects as measured by CRs in brief interventions
had a non significant weighted mean positive effect (k = 6), δ = 0.16,
90% CI [-0.07, 0.39]; long-term treatment programmes had a non
significant weighted mean positive effect (k = 5), δ = 0.14, 90% CI
[-0.09, 0.37].
Discussion
This meta-analysis has certain limitations that should be borne in
mind when extrapolating or generalizing the results to other
populations. First, the effects of a meta-analysis may be inadvertently
contaminated by other variables that preclude the estimate of an
effect size due to treatment. Second, details of several of the moderators
initially selected for this study were not fully reported or were not
accurately measured by the studies selected for this meta-analysis.
Third, the measures for batterer treatment efficacy based on ORs and
CRs were not entirely accurate since they entailed a margin error in
the estimates of the recidivism rates (hidden victimization/undetected
delinquency). Most of the interventions were evaluated by the authors
themselves who were conscious that the continuity of their
intervention programme depended on positive outcomes which may
undermine the reliability of the evaluation (thus, the detected outliers
were the 3 effect sizes of the same author with a positive effect 2SD >
M, whereas the interventions with the highest negative effect sizes
corresponded to the external assessments of Jones and Gondolf, 2002).
Taking these limitations into account in generalizing the results, the
following conclusions may be drawn:
On the whole, the treatment of batterers had a positive but non
statistically significant effect. As for some specific treatments, it may
also have had considerably negative effects both in ORs and CRs.
Nevertheless, this does not imply that the batterers’ treatment
efficacy rate is null, given that the probability of an effect being null
is equal to a 38% efficacy rate which is quite a respectable efficacy.
Hence, the evidence remains inconclusive and sharp conclusions
cannot be drawn (Eckhardt et al., 2013; Smedslund, Dalsbo, Steiro,
Winsvold, & Clench-Aas, 2011).
Treatment efficacy was not sensitive to the moderator duration of
the follow-up (short-term vs. long-term) in the ORs or CRs. In other
words, the follow-up period was not a differential indicator of
treatment efficacy, which contradicts the findings of Gondolf that
the greatest recidivism rate occurs during the first months (Gondolf,
2000, 2002).
The ‘type of intervention’ moderator (Duluth Model, CBT or OTI
Programmes) had no significant effects in CRs or ORs for the Duluth
Model and the CBT Programmes though the effects were significant
for the OTIs. The lack of a significant treatment effect in the Duluth
Model and CBT Programmes corroborated the findings of Babcok et
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E. Arias et al. / Psychosocial Intervention 22 (2013) 153-160 159
al. (2004). However, the contrast of the observed effect size with a
null effect size (0 efficacy rate) showed that the evidence for
supporting a null recidivism efficacy rate in the ORs for the Duluth
Model and CBT treatment programmes was the same as a 38% and
42% efficacy rate, respectively. As for the positive effects of the OTIs,
these rest on psychological-psychiatric treatment (Coulter &
VandeWeerd, 2009) in which the main aim of treatment is
psychopathology, not gender violence. Thus, this intervention is the
most apt for addressing the needs of batterers. Consequently, further
studies are required on the effects of treatment type to identify those
variables that are mitigating its potential effects, such as the control
of treatment adherence (Arce, Fariña, Carballal, & Novo, 2009), the
psychological adjustment (Lila, Gracia, & Murgui, 2013) or the
motivation for change (Eckhardt et al., 2013).
The ‘duration of the intervention’ moderator (brief vs. long) had
no significant effect in the CRs whereas in ORs, long-term
interventions had a significant mean effect size though no significant
mean effect size was found in brief interventions. Thus, long-term
interventions were more efficacious in the ORs, i.e., they officially
reduce recidivism, but do not appear to do so in the daily life of
couples (CRs).
Though the treatment of batterers may have negative effects on
recidivism rates, treatment should be aimed at achieving positive
effects, i.e., the implementation of treatment programmes that entail
negative effects is entirely unacceptable. This underscores the need
to identify the characteristics of treatment efficacy studies with
considerable negative effect sizes, which in this meta-analysis were
as follows: Group 3 of The San Diego Navy Experiment (Dunford,
2000), that was characterized for being brief (< 16 sessions) and CBT
being applied individually in a military base; some of the Jones and
Gondolf’s (2002) studies that were characterized as group
interventions based on the Duluth Model; and the study by Lin et al.
(2009) that was defined as a mixed (Duluth Model and CBT) group
treatment programme. In short, no nexus was found between the
treatment programmes which would indicate other causes are
responsible for the negative treatment effects. These findings suggest
that further research is required to ascertain the causes underlying
these negative effects.
In conclusion, overall, the treatment of batterers is not efficacious,
though some programmes were (k = 16 for the positive effect of a
small effect size or larger than ≥ 0.20) or had negative effects (k = 7).
Of the moderators, only the type of intervention (i.e., OTIs) and the
duration of the intervention (long-term) were significant, i.e.,
interventions adapted to the batterers’ needs (OTI: psychological-
psychiatric programme for batterers with psychopathology) and
long-term interventions, which would indicate that (toxic) cognition
that sanctions domestic violence is highly resistant to treatment.
Nonetheless, the results remain inconsistent and further studies are
required to assess the efficacy of batterer treatment programmes,
i.e., to examine moderators that may explain why some batterers
respond to treatment yet others fail to do so under similar treatment
programmes. This calls for authors, reviewers, and editors to provide
explicit details regarding the treatment contents, techniques, and
methods. This study has focused on certain variables that are crucial
for the assessment of treatment, but have often been neglected in
the literature, since initially they have been considered of minor
importance though the results of this meta-analysis have shown
they are robust, e.g., the techniques and methods applied that involve
active, focused, collaborative learning (the principle of responsibility),
the implementation of treatment programmes by specialized and
trained staff, and the implementation of additional judicial measures
(Lila, García, & Lorenzo, 2010; McGuire et al., 2000).
Conflicts of interest
The authors of this article declare no conflicts of interest.
Acknowledgements
This research has been sponsored by a grant of the Spanish
Ministry of Science and Innovation to the project “Reeducación de
penados por violencia de género: Implementación y evaluación de
programas de tratamiento” (Ref.: EDU2011-24561).
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