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https://doi.org/10.1177/08862605221090562
Journal of Interpersonal Violence
2023, Vol. 38(1-2) NP1141 –NP1162
© The Author(s) 2022
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sagepub.com/journals-permissions
DOI: 10.1177/08862605221090562
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Original Research
1120916JIVXXX10.1177/08862605221090562Journal of Interpersonal ViolenceSharratt et al.
research-article2022
Childhood Abuse and
Neglect, Exposure to
Domestic Violence and
Sibling Violence: Profiles
and Associations With
Sociodemographic
Variables and Mental
Health Indicators
Kathryn Sharratt
1
, Samantha J. Mason
1
,
Gillian Kirkman
1
, Dominic Willmott
2
,
Danielle McDermott
3
, Susan Timmins
1
, and
Nadia M. Wager
1
Abstract
Research indicates substantial overlap between child abuse and neglect
(CAN), exposure to domestic violence and sibling abuse, with multiple
victimisation experiences conferring greater risk for adverse mental health
outcomes than does exposure to a single subtype. The application of latent
class analysis (LCA) to child maltreatment has gained momentum, but it
remains the case that few studies have incorporated a comprehensive range of
subtypes, meaning that real-life patterns in victimisation experiences cannot
be accurately modelled. Based on self-report data from an ethnically diverse
1
University of Huddersfield, Huddersfield, UK
2
Manchester Metropolitan University, Manchester, UK
3
Leeds Trinity University, Leeds, UK
Corresponding Author:
Kathryn Sharratt, Department of Behavioural and Social Sciences, The University of
Huddersfield, Queensgate, Huddersfield HD1 3DH, UK.
Email: k.sharratt@hud.ac.uk
NP1142 Journal of Interpersonal Violence 38(1-2)
sample (N= 2813) of 10–17 year olds in the United Kingdom, the current
study used LCA to model constellations among nine types of maltreatment in
the home (physical, emotional and sexual abuse; physical and emotional
neglect; exposure to physical and verbal domestic violence, or a drug-related
threat; and sibling violence). A four-class solution comprising of a low vic-
timisation class (59.3% of participants), an emotional abuse and neglect class
(19.0%), a high verbal domestic violence class (10.5%) and a maltreatment and
domestic violence class (11.2%) provided the best fit for the data. Associations
with sociodemographic variables were examined, revealing differences in the
composition of the classes. Compared to the low victimisation class, par-
ticipants in the verbal domestic violence class, emotional abuse and neglect
class and especially the maltreatment and domestic violence class, reported
higher symptoms of anxiety and depression and an increased likelihood of
non-suicidal self-injury, suicide ideation and suicide attempt. The findings
carry important implications for understanding patterns of child maltreat-
ment, and the implications for preventative strategies and support services are
discussed.
Keywords
childhood maltreatment, child abuse and neglect, exposure to domestic
violence, sibling violence, anxiety, depression, latent class analysis
Introduction
The World Health Organisation (2020) defines child maltreatment as ‘the
abuse and neglect that occurs to children under 18 years of age […] which
results in actual or potential harm to the child’. This is commonly in-
terpreted to comprise physical, sexual and emotional abuse and neglect
(Felitti et al., 1998), but researchers have increasingly elected to include
exposure to domestic abuse (Gardner et al., 2019)inthedefinition of child
maltreatment. Child abuse and neglect (CAN) and domestic abuse often
co-occur within families (Radford et al., 2011), and children who are
subjected to direct abuse in addition to witnessing violence between their
parents have been described as ‘doubly victimised’(Hamby et al., 2010).
Despite sibling abuse occurring more frequently than abuse by a parent
(Button & Gealt, 2010), it is rarely incorporated into definitions of mal-
treatment and remains severely under-researched (Van Berkel et al., 2018).
Maltreatment and other forms of family violence are considered to be
amongst the most intense sources of stress that a child can suffer in their
early years (WHO, 2018), rendering these phenomena a significant public
health concern.
2Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1143
Considering that child maltreatment often goes unidentified, unreported or
unrecorded in the United Kingdom (Bentley et al., 2020), national victim-
isation surveys are capable of providing more accurate estimates of the true
extent of the problem. The Crime Survey for England and Wales (CSEW)
estimates that 8.5 million people (equivalent to one-fifth of the adult pop-
ulation) aged 18–74 are subject to at least one type of maltreatment before the
age of 16 (Office for National Statistics, 2020). However, the CSEW has not
adopted the international definition of a child, meaning that offences against
persons aged 16–17 are not represented in these figures. Focussing on
maltreatment before the age of 18, an international systematic review of self-
reported lifetime victimisation revealed variable estimates of physical abuse
(3.6–32.6%), sexual abuse (0.7–27.8%), emotional abuse (4.0–66.7%) and
neglect (5.6–77.8%) depending on sample characteristics and definitions of
CAN (Moody et al., 2018). Statistics on other forms of maltreatment are more
scarce in comparison, but a survey of over 4000 children and their parents/
guardians in the United Kingdom estimated that 12% of under 11s and 17.5%
of 11–17 year olds witness domestic violence at some point during their
childhood (Radford et al., 2011). Another study of 12-year olds in the United
Kingdom (n= 6838) revealed that 26.2% of children surveyed had experi-
enced sibling bullying in the past six months (Dantchev & Wolke, 2019).
Notwithstanding the importance of estimates pertaining to specific forms of
maltreatment, it should not be assumed that these victimisation experiences
occur in isolation. Indeed, the large body of literature on Adverse Child
Experiences (ACEs) evidences substantial overlap between abuse, neglect,
exposure to domestic violence and sibling abuse, alongside other harmful non-
victimisation experiences such as parental divorce, mental health problems or
incarceration (Bellis et al., 2015;Lacey et al., 2020). Children who experience
one type of maltreatment are much more likely to report another, with a
retrospective survey of 8887 American adults reporting that 34.6% of those
who were maltreated as a child experienced at least two forms of abuse
(Edwards et al., 2003). Moreover, in the United Kingdom, Radford et al.
(2011) found that in comparison to non-maltreated children, those aged <11
and 11–17 years old who had been subject to severe maltreatment by a
parent/guardian were 2.8 and 2.9 times more likely to witness domestic
violence, respectively. In addition, a survey of school pupils in the United
States (n= 8122), revealed that child maltreatment and exposure to do-
mestic violence are associated with a significant increase in the odds of
experiencing sibling abuse (OR = 4.00 and 2.06, respectively; Button &
Gealt, 2010).
Child maltreatment has been implicated in the development of serious
mental health problems, with a recent global meta-analysis comprising of 106
studies demonstrating that individuals subjected to any type of maltreatment
(physical, sexual and emotional abuse, neglect and exposure to intimate
Sharratt et al. 3
NP1144 Journal of Interpersonal Violence 38(1-2)
partner violence) were 2.48 more likely to experience a depressive disorder
and 1.68 times more likely to develop an anxiety disorder (Gardner et al.,
2019). A second meta-analysis of 15 studies from the international literature
found that all types of CAN (physical, sexual and emotional abuse, and
physical and emotional neglect) were associated with significantly increased
odds of suicide attempt (Liu et al., 2017). However, at least half of the studies
included in these reviews were based on retrospective recall from adults,
meaning that there is a general paucity of information on the short-term
consequences of maltreatment among the current generation of children and
adolescents –a necessary precursor to informing the delivery of services to
this group (Radford et al., 2011). Crucially, there is mounting evidence that
exposure to multiple adversities or victimisation experiences accumulates to
produce more deleterious consequences than does exposure to a single type
(Bellis et al., 2015;Finkelhor et al., 2007;Petruccelli et al., 2019). For in-
stance, a meta-analysis of 23 studies from Australia found that exposure to
three types of CAN almost doubled the risk of depressive and anxiety dis-
orders compared to exposure to one subtype (Moore et al., 2015). Moreover, a
longitudinal study in the United States (n= 457) revealed that witnessing
domestic violence in addition to being the direct victim of child abuse is
associated with more severe internalising and externalising problems than
experiencing either of these phenomena separately (Moylan et al., 2010).
Although the practice of computing a simple additive count is a common
approach to examining the consequences of multiple victimisation, it assumes
that the constituent forms of maltreatment are equally traumatic (Petruccelli
et al., 2019). This approach also assumes that each type of maltreatment
confers an equal risk for all other types of maltreatment, ignoring any naturally
occurring patterns in victimisation experiences (Debowska et al., 2017). In
contrast, the application of person-centred techniques, such as latent class
analysis, enables real-life constellations in maltreatment to be identified
(Lanza & Rhoades, 2013). Participants are assigned to a group (or ‘class’)
based on their pattern endorsement of items pertaining to victimisation ex-
periences, enabling the association between class membership and other
external variables to be investigated. Two global systematic reviews of studies
that have applied person-centred approaches to the study of child maltreat-
ment are available from Debowska et al. (2017) and Rivera et al. (2018).
Having adopted a comparable definition of maltreatment that incorporates
physical, sexual and emotional abuse, neglect and exposure to domestic
violence, a consensus was reached that two to four classes is usually sufficient
to represent naturally occurring profiles of maltreatment. According to
Debowska et al. (2017), 12 out of the 16 studies reviewed identified a class
characterised by little to no experience of maltreatment. This class accounted
for the largest proportion of participants in nine of the studies, representing
approximately 80–85% of participants in samples of the general population.
4Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1145
Where a poly-victimisation class was revealed, this accounted for the smallest
proportion of participants (approximately 2–10% of participants in samples of
the general population), but the likelihood of experiencing adverse mental
health outcomes, including symptoms of anxiety, depression and post-
traumatic stress, was significantly higher for this group (Debowska et al.,
2017). Remaining victimisation classes were much more heterogeneous in
nature and varied according to the particular types of maltreatment included in
the analyses. Indeed, Rivera et al. (2018) identified substantial variation in the
indicators used to model classes of maltreatment across the 14 studies in-
cluded in their review. Not one study included all five indicators of mal-
treatment, four omitted indicators of neglect, five omitted indicators of
emotional abuse, and only two included indicators of exposure to domestic
violence. The omission of important indicators severely limits the extent to
which real-life constellations in maltreatment experiences can be accurately
modelled, potentially over-looking significant associations with mental health
outcomes.
Considering the seriousness of the impact of child maltreatment on mental
health, preventing the occurrence of such harmful experiences is a global
priority (WHO, 2020). Examining the association between individual and
family characteristics and child maltreatment can inform the development of
preventative strategies by supporting the identification of ‘high-risk’indi-
viduals, as well as developing an understanding of the mechanisms that
contribute to child maltreatment (Gilbert et al., 2012). With the exception of
physical abuse (males - 7.7%; females - 7.5%), females are disproportionately
represented among victims of all other types of maltreatment captured by the
CSEW, including emotional abuse (males - 6.8%; females - 11.8%), sexual
abuse (males - 3.5%; females - 11.5%) and exposure to domestic violence
(males - 7.6%; females - 11.9%; ONS, 2020). Other factors associated with
experiencing child maltreatment include economic disadvantage, low edu-
cational attainment, non-White ethnicity, belonging to a one-parent house-
hold, a larger number of children in the household and parental mental health
and substance misuse problems (Black et al., 2001;Doidge et al., 2017;
Sidebotham & Golding, 2001). Research examining the association between
child/family variables and multiple victimisation experiences tends to adopt
broader definitions that also incorporate non-maltreatment victimisation and/
or other non-victimisation adversities, creating an equivocal picture due to the
inclusion of a heterogeneous assortment of items. For instance, a global meta-
analysis of 96 studies revealed that female gender was the only variable to
predict multiple ACEs (Petruccelli et al., 2019). Meanwhile, a survey of
children and their caregivers in the United States (n = 2030) revealed that
poly-victims were more likely to be boys, older children, city-dwellers,
residents of one-parent households and children of Black ethnic origin and
low socioeconomic status (Finkelhor et al., 2007). As noted previously,
Sharratt et al. 5
NP1146 Journal of Interpersonal Violence 38(1-2)
simply summing the number of victimisation experiences overlooks het-
erogeneity maltreatment experiences, negating the possibility that certain
family/child characteristic might be associated with qualitatively different
victimisation experiences. However, at present there is a scarcity of person-
centred analyses that have examined the association between maltreatment
profiles and individual/family characteristics (Rivera et al., 2018).
Child maltreatment is a global problem and is certainly not unique to the
UK (Moody et al., 2018). However, the UK recently ranked 27
th
out of 41 of
the ‘richest’countries in the world on indicators of child wellbeing (UNICEF,
2020). Ranking in the bottom third for overall mental health, and with only
two countries reporting lower levels of life satisfaction, this suggests that the
UK is a long way from meeting the targets set in the 2030 Agenda for
Sustainable Development (United Nations, 2015). There is a need to rapidly
address the factors that contribute to poor mental health, and child mal-
treatment within the family is understood to be one of the most damaging
experiences a child can have due to the betrayal of supposed close rela-
tionships and trust (Malloy et al., 2016). Therefore, the objective of the current
study was to support the development of preventative strategies and victim
support services by examining the association between profiles of mal-
treatment and sociodemographic variables and indicators of mental wellbeing.
Considering the limitations of previous research, the current study utilised
self-report data collected from 10-17 year olds (as opposed to retrospective
recall from adults) and applied LCA to identify naturally occurring profiles
among nine indicators of maltreatment within the home (physical, sexual and
emotional abuse; physical and emotional neglect; exposure of physical and
verbal domestic violence, or a drug-related threat; and sibling abuse). We
anticipated that a large proportion of participants would belong to a class
characterised by minimal maltreatment experiences, and a small proportion to
a poly-victimisation class, but no further predictions were made about the
number, nature or associations of the classes.
Method
Participants
This paper draws on cross-sectional survey data (N= 2813) collected from
four primary schools, five secondary schools and two tertiary colleges in 2019.
Seven of these schools/colleges were located in the North of England, with the
remaining four in the South of the country. Participants were aged 10–17 (M=
14.58; SD = 2.12) and a little over half were female (n= 1499; 53.3%). The
sample was ethnically diverse, with participants identifying as White (n=
1074; 38.3%), Mixed Heritage (n= 916; 32.7%), Asian/Asian British (n=
655; 23.4%) and Black/African/Caribbean/Black British (n= 133; 4.7%). Just
6Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1147
over two thirds of participants reported living in an urban area (n= 1766;
63.3%) and slightly more indicated that they were living with both parents (n=
1913; 68.4%). Just over one quarter of participants reported having three or
more siblings (n= 796; 28.5%).
Procedure
Questionnaires were completed in classrooms, mostly via the online survey
tool Qualtrics (n= 2393; 85.1%), but a small number were completed in a
paper and pencil format (n= 420; 14.9%). Ethical approval was granted by the
lead University’s ethics panel, and permissions were also obtained from
participating schools and colleges. Researchers were present throughout to
answer any questions that the children and young people had. Informed
consent was obtained from both students and their parents, and participation
was voluntary without any compensation or reward. Participants were assured
that their answers would remain confidential and were reminded of their right
to withdraw at any time. Students were provided with details of helplines and
counselling services where they could seek support if they had experienced
maltreatment and/or if participation in the study caused any distress.
Measures
The sociodemographic questionnaire captured participants sex (male; fe-
male), age, ethnic group (White; Mixed Heritage; Asian/Asian British; Black/
African/Caribbean/Black British), location (urban; rural), household situation
(living with both biological parents; one biological parent; one biological and
one step-parent; neither parent) and number of siblings.
The Child Victimization Experiences Questionnaire (Choo et al., 2011)
captured lifetime experiences of maltreatment perpetrated by parents,
guardians or other adults living in the home. Seven items inquired into ex-
periences of physical abuse (e.g. slapping, beating with objects, kicking and
choking), eight sexual abuse (e.g. inappropriate touching, sex, being shown
sexual scenes, made to pose nude) and six emotional abuse (e.g. being in-
sulted, embarrassed or made to feel like a bad person). Physical neglect was
captured by three items (e.g. made to wear dirty clothes) and emotional neglect
by five items (e.g. not offered encouragement or made to feel unloved). A
specific type of maltreatment was regarded as present if a child or young
person endorsed at least one item belonging to that category.
Exposure to domestic violence was captured by one item pertaining to
verbal violence (‘Have you seen adults in your home shouting and screaming
in a way that frightened you?’), two items pertaining to physical violence
(‘Have you seen adults in your home hurt each other physically, e.g. hitting,
kicking, slapping?’and ‘Have you seen adults in your home use knives, guns,
Sharratt et al. 7
NP1148 Journal of Interpersonal Violence 38(1-2)
sticks or other objects to hurt or scare someone else inside your home?’), and
one item concerning a drug-related threat (‘Has anyone in your home taken
alcohol or drugs and then behaved in a way that frightened you’). Items were
scored dichotomously as ‘yes’or ‘no’, and a child was regarded as having
experienced physical violence if they endorsed at least one item.
Sibling violence was measured by the item ‘Have you been mistreated or
bullied by your brother(s) or sister(s), step-brother/step-sister or cousin(s) at
home?’. Participants answered ‘yes’or ‘no’.
The PROMIS Depression Short Form (PROMIS Health Organization and
PROMIS Cooperative Group, 2012a) captures thoughts and feelings over the
past seven days (e.g. feeling unhappy, stressed and not caring about anything).
The 14 items are answered on a scale ranging from 1 (never) to 5 (almost
always), yielding a possible range of scores from 14 to 70. Higher scores
represent more severe symptoms of anxiety (Cronbach’s alpha was 0.97).
The PROMIS Anxiety Short Form (PROMIS Health Organization and
PROMIS Cooperative Group, 2012b) captures thoughts and feelings over the
past seven days (e.g. feeling nervous, worried, getting scared easily and being
unable to relax). The 13 items are answered on a scale ranging from 1 (never)
to 5 (almost always), yielding a possible range of scores from 13 to 65. Higher
scores represent more severe symptoms of depression (Cronbach’s alpha was
0.94).
Suicidal phenomena were measured using three items. The item ‘Have
you ever harmed yourself on purpose in a way that was not to take your life?’
captured lifetime history of non-suicidal self-injury. Meanwhile, suicide
ideation was measured by asking ‘Have you ever felt so unhappy that you
have thought about killing yourself?’and suicide attempt was measured by
asking ‘Have you ever tried to commit suicide or tried to do something that
meant you could die?’. Participants answered ‘yes’or ‘no’.
Statistical Analysis
Latent class analysis (LCA) was performed to identify homogenous groups (or
classes) of children and young people based on their experiences of nine types
of maltreatment (physical abuse, sexual abuse, emotional abuse, physical
neglect, emotional neglect, exposure to verbal domestic violence, exposure to
physical domestic violence, witnessing a drug-related threat and sibling
abuse). Using MPlus Version 7, models with an increasing number of classes
were specified in an iterative manner. The Lo–Mendell–Rubin likelihood ratio
test (LMR-LRT; Lo et al., 2001) assesses improvement in fit between
competing models and is used to elucidate the most appropriate number of
classes. A non-significant value (p> .05) suggests that the model with one
fewer class provides a more parsimonious fit to the data. At this point, there is
little empirical support for the inclusion of an additional latent class and the
8Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1149
specification of further models ceases. The success of the models was assessed
using a range of statistical indicators pertaining to goodness of fit, including
the Akaike Information Criterion (AIC; Akaike, 1987); Bayesian Information
criterion (BIC; Schwartz, 1978) and sample size adjusted BIC (
SSA
BIC;
Schwartz, 1978), where lower values indicate better fitting models. Partici-
pants were assigned to a single class according to posterior probabilities, with
the entropy statistic (Ramaswamy et al., 1993) evaluating the quality of the
classification of participants by the model. Values range from 0 to 1, with 0.75
considered acceptable and 0.80 considered high (Wang & Wang, 2012).
Selection of the best-fitting model was also influenced by the inspection of
latent profile plots to ascertain whether the classes represented distinct and
conceptually meaningful constellations in maltreatment experiences.
Following identification of the most appropriate latent class solution,
multinomial logistic regression was performed to examine the composition of
the classes based on sociodemographic variables. Age (continuous), sex (0 =
female; 1 = male), ethnicity (0 = White; 1 = non-White), location (0 = urban; 1
= rural), household situation (0 = living with both parents; 1 = not living with
both parents) and number of siblings (0 = 3 or more siblings; 1 = 0-2 siblings)
were entered as predictors in the analysis, and class membership was the
categorical outcome variable.
Associations between class membership and indicators of mental health
were also investigated, using binary logistic regression for the categorical
dependent variables (NSSI, suicide ideation and suicide attempt) and linear
regression for the continuous dependent variables (anxiety and depression).
Class membership was dummy coded and entered as a categorical inde-
pendent variable. Age (continuous), sex (male/female), ethnicity (White/non-
White), location (urban/rural), household situation (living with both parents/
not living with both parents) and number of siblings (0-2 siblings/3+ siblings)
were also entered as covariates.
Results
Latent Class Enumeration
LCA was used to determine the optimal number of classes based on expe-
riences of maltreatment. Beginning with a two-class solution, a series of
models with an increasing number of classes were specified and tested (Table
1). The LMR-LRT for the five- and six-class solutions were non-significant,
suggesting that they did not provide a better fit for the data than the solution
with one fewer classes. The LRM-LRT was statistically significant for the
four-class solution and this achieved a lower AIC and
SA
BIC than the two- and
three-class solutions. Moreover, the four-class solution achieved the lowest
BIC of all models tested, and this has been identified as a particularly reliable
Sharratt et al. 9
NP1150 Journal of Interpersonal Violence 38(1-2)
indicator of the most appropriate number of latent classes (Nylund et al.,
2007). The entropy statistic for the four-class model was 0.79, suggesting that
the data was adequately captured by this solution.
Inspection of the latent profile plot (Figure 1) confirmed that the four-class
solution provided conceptually meaningful typologies of maltreatment. Im-
portantly, the classes could be distinguished by differences in the constellation
of maltreatment experiences, rather than simply reflecting increases in the
likelihood of experiencing certain forms of maltreatment (Lanza & Rhoades,
2013).
Average item response probabilities indicate the likelihood of endorsing a
particular item conditional on latent class membership (Table 2). Latent class 1
(n= 253; 10.5% of participants) comprised of individuals with a very high
Table 1. Fit indices for the latent class analysis.
Model AIC BIC
SSA
BIC LRT pEntropy
2 classes 18,144.31 18,257.21 18,196.84 3419.93 <0.001 0.83
3 classes 17,724.31 17,896.63 17,804.48 434.53 <0.001 0.84
4 classes 17,410.69 17,642.42 17,518.51 329.47 <0.001 0.79
5 classes 17,372.49 17,663.65 17,507.96 57.48 0.06 0.79
6 classes 17,344.05 17,694.62 17,507.16 47.84 0.22 0.79
Note. AIC = Akaike information criterion, BIC = Bayesian information criterion,
SSA
BIC = sample
size adjusted BIC, LRT = Lo-Mendell-Rubin’s adjusted likelihood ratio test.
Figure 1. Latent profile plot of childhood maltreatment and exposure to violence.
Class 1 (dotted line) = 10.5% participants; Class 2 (dashed line) = 59.3% participants;
Class 3 (dash-dot line) = 19.0% participants; Class 4 (solid line) = 11.2% participants.
10 Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1151
probability of endorsing verbal domestic violence (0.95); moderate proba-
bilities of endorsing a drug-related threat (0.44) and physical domestic vi-
olence (0.42); and low or very low probabilities of endorsing items relating to
abuse, neglect and sibling violence (ranging from 0.01 to 0.30). This class was
labelled the ‘high verbal domestic violence class’. Class 2 (n= 1757; 59.3% of
participants) was characterised by very low item response probabilities for all
items (not exceeding 0.1%) and so was labelled the ‘low victimisation class’.
Class 3 (n= 496; 19.0%) comprised of individuals with a high probability of
endorsing emotional abuse (0.84); a moderate probability of endorsing
emotional neglect (0.50); and low or very low probabilities of endorsing items
relating to all other forms of abuse and domestic violence exposure (ranging
from 0.03 to 0.34). In considering the characteristics of this class, it was
labelled the ‘emotional abuse and neglect class’. Class 4 (n= 307; 11.2% of
participants) was characterised by very high item response probabilities for
emotional abuse (0.98), emotional neglect (0.97) and verbal domestic vio-
lence (0.93); a moderate-high item response probability for physical abuse
(0.69); moderate item response probabilities for physical domestic violence
(0.56), drug-related threat (0.54), sibling violence (0.50) and physical neglect
(0.45); and a low item-response probability for sexual abuse (0.17). Con-
sequently, this final class was labelled the ‘maltreatment and domestic vio-
lence class’.
Association with Sociodemographic Variables and Indicators of
Mental Health
Next, we examined the composition of the latent classes using sociodemo-
graphic characteristics (see Table 3 for prevalence and descriptive statistics).
Table 2. Average item response probabilities for the four-class solution.
Class 1 Class 2 Class 3 Class 4
Physical abuse 0.12 0.03 0.37 0.69
Sexual abuse 0.01 0.00 0.03 0.17
Emotional abuse 0.22 0.06 0.84 0.98
Physical neglect 0.02 0.01 0.16 0.45
Emotional neglect 0.07 0.02 0.50 0.97
Physical domestic violence 0.42 0.01 0.06 0.56
Verbal domestic violence 0.95 0.10 0.35 0.93
Drug-related threat 0.44 0.02 0.05 0.54
Sibling violence 0.30 0.05 0.24 0.50
Note. Class 1 = high verbal domestic violence; class 2 = low victimisation; class 3 = emotional abuse
and neglect; class 4 = maltreatment and domestic violence.
Sharratt et al. 11
NP1152 Journal of Interpersonal Violence 38(1-2)
Multinomial logistic regression was performed with Class 2 (low victimisation
class) used as the reference category. Compared to Class 2, being female
significantly increased the odds of belonging to Class 1 (high verbal domestic
violence class; OR = 1.71; 95% CI = 1.29/2.28; p< .001) and Class 4
(maltreatment and domestic violence class; OR = 1.94; 95% CI = 1.46/2.56; p
< .001) but did not predict membership to Class 3 (emotional abuse and
neglect class; OR = 1.08; 95% CI = .87/1.33; p= .492). Being of White ethnic
origin significantly increased the odds of belonging to Class 3 (OR = 3.10;
95% CI = 2.43/3.96; p< .001) and Class 4 (OR = 3.31; 95% CI = 2.44/4.48; p
< .001), but it was inversely related to membership to Class 1 (OR = .55; 95%
CI = .38/.79; p= .001). Living with both parents significantly decreased the
odds of membership to all abuse classes, including Class 1 (OR = .40; 95% CI
= .30/.54; p< .001), Class 3 (OR = .62; 95% CI = .49/.78; p< .001) and Class 4
(OR = .33; 95% CI = .25/.44; p< .001). Meanwhile, living with three or more
siblings predicted membership to Class 3 (OR = 1.27; 95% CI = 1.00/1.61; p=
.047) and Class 4 (OR = 1.72; 95% CI = 1.30/2.27; p< .001), but had no
significant bearing on membership to Class 1 (OR = 1.07; 95% CI = .79/1.45;
p= .674). Age and location (urban/rural) did not increase the odds of be-
longing to any of the abuse classes (p> .05).
We also examined the association between class membership and indi-
cators of mental health (see Table 3 for prevalence and descriptive statistics).
Binary logistic regression was employed for the categorical dependent var-
iables (NSSI, suicide ideation and suicide attempt) and linear regression for
the continuous dependent variables (anxiety and depression), with Class 2
Table 3. Frequency (%) or Mean (SD) for sociodemographic and psychological
variables across the four latent classes.
Class 1 Class 2 Class 3 Class 4
Age 14.9 (2.1) 14.7 (2.1) 14.1 (2.1) 14.2 (2.2)
Sex (female) 159 (62.8%) 882 (50.2%) 259 (52.2%) 199 (64.8%)
Ethnicity (White) 57 (22.6%) 535 (30.7%) 290 (60.2%) 192 (63.4%)
Location (urban) 168 (66.9%) 1134 (65.0%) 287 (58.5%) 177 (58.4%)
Living with both parents 141 (55.7%) 1330 (75.7%) 307 (61.9%) 137 (44.6%)
Number of siblings (3+) 72 (28.7%) 450 (25.7%) 149 (30.2%) 125 (41.3%)
Depression 25.8 (11.6) 19.3 (7.8) 28.4 (13.0) 39.9 (14.8)
Anxiety 21.6 (8.1) 17.0 (5.7) 23.3 (8.8) 31.1 (11.1)
NSSI 90 (36.0%) 202 (11.7%) 145 (30.0%) 177 (59.0%)
Suicide ideation 112 (44.8%) 233 (13.6%) 189 (39.0%) 202 (68.0%)
Suicide attempt 35 (14.0%) 47 (2.7%) 59 (12.2%) 83 (28.1%)
Note. Class 1 = high verbal domestic violence; class 2= low victimisation; class 3 = emotional abuse
and neglect; class 4 = maltreatment and domestic violence.
12 Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1153
(low victimisation class) used as the reference category throughout. Compared to
Class 2, participants in Class 1 (high verbal domestic violence class) reported
higher symptoms of depression (B= 5.83; 95% CI = 4.45/7.20; p< .001) and
anxiety (B= 4.30; 95% CI = 3.29/5.32; p< .001), and an increased odds of NSSI
(OR = 3.88; 95% CI = 2.83/5.31; p< .001), suicide ideation (OR = 4.63; 95% CI
= 3.43/6.25; p< .001) and suicide attempt (OR = 5.01; 95% CI = 3.09/8.12; p<
.001). Participants in Class 3 (emotional abuse and neglect class) reported even
higher symptoms of depression (B= 8.54; 95% CI = 7.46/9.62; p< .001) and
anxiety (B= 5.74; 95% CI = 4.96/6.52; p< .001), and also an increased odds of
NSSI (OR = 3.50; 95% CI = 2.69/4.57; p< .001), suicide ideation (OR = 4.29;
95% CI = 3.34/5.51; p< .001) and suicide attempt (OR = 4.50; 95% CI = 2.91/
6.94; p< .001). For participants in Class 4 (maltreatment and domestic violence
class), symptoms of depression (B= 19.08; 95% CI = 17.74/20.41; p< .001) and
anxiety (B= 13.07; 95% CI = 12.08/14.05; p< .001) were higher still and there
was an even greater odds of experiencing NSSI (OR = 11.38; 95% CI = 8.37/
15.47; p< .001), suicide ideation (OR = 14.37; 95% CI = 10.52/19.62; p< .001)
and suicide attempt (OR = 12.36; 95% CI = 8.03/19.04; p< .001).
Discussion
Child maltreatment is a multi-facetted problem and children subject to one
type of maltreatment are at increased risk of experiencing other types (Button
& Gealt, 2010;Edwards et al., 2003;Hamby et al., 2010;Radford et al., 2011).
Moreover, there is mounting evidence that exposure to multiple advertises and
victimisation experiences has a cumulative impact on mental health, resulting
in more deleterious consequence than does exposure to a single type of
victimisation (Bellis et al., 2015;Moore et al., 2015;Moylan et al., 2010;
Finkelhor et al., 2007). There is also interest in linking victimisation expe-
riences to child and family characteristics (Petruccelli et al., 2019) in order to
facilitate the development of strategies designed to protect children from harm
(Gilbert et al., 2012). Although research in the field of poly-victimisation has
commonly adopted a simple additive approach to calculating the number of
maltreatment experiences, recognition that this does not adequately capture
heterogeneity in victimisation experiences has contributed to a gradual in-
crease in the application of person-centred analyses (Debowska et al., 2017).
This approach allows the identification of naturally occurring patterns in
victimisation experiences, but to date, many studies have adopted a narrow
definition of maltreatment that does not allow wide-ranging victimisation
experiences to be captured in their entirety (Rivera et al., 2018). Therefore, the
objective of the current study was to utilise latent class analysis to identify
profiles among nine types of maltreatment in the home (physical, sexual and
emotional abuse; physical and emotional neglect; exposure to verbal or
physical domestic violence, or a drug-related threat; and sibling abuse), and to
Sharratt et al. 13
NP1154 Journal of Interpersonal Violence 38(1-2)
inspect the association between profile of maltreatment and indicators of
mental health and sociodemographic variables.
Commensurate with previous research (Debowska et al., 2017;Rivera
et al., 2018), a solution comprising of four latent classes was found to provide
the most parsimonious and conceptually meaningful approach to modelling
patterns in maltreatment experiences. The low victimisation class was
characterised by little to no endorsement of all maltreatment indicators.
Although this still accounted for the largest proportion of participants
(59.3%), this class was less numerous than in most studies of the general
population (where it typically accounts for around 80–85% of participants;
Debowska et al., 2017). This is most likely attributable to the inclusion of a
wider range of maltreatment indicators, increasing the chances that children’s
victimisation experiences were captured by the questionnaire. This finding
emphasises the importance of including a comprehensive range of subtypes in
future research, since failure to do so carries the risk of underestimating the
proportion of children who are subject to maltreatment.
We also recovered an emotional abuse and neglect class, which accounted
for 19.0% of children in the sample. This class was characterised by a high
likelihood of experiencing emotional abuse, a moderate likelihood of ex-
periencing emotional neglect, and low-very low likelihoods of experiencing
all other types of maltreatment. In contrast to the Crime Survey for England
and Wales, which reveals that females are disproportionately represented
among victims of emotional abuse (ONS, 2020), this class comprised of a
similar proportion of boys and girls (48.8% and 52.2%, respectively). Again,
the inclusion of a wider range of items pertaining to both emotional abuse and
neglect most likely enabled boys’and girls’experiences to be more accurately
captured. Compared to the low victimisation class, members of this class
reported significantly higher symptoms of anxiety and depression, and a
higher likelihood of non-suicidal self-injury, suicide ideation and suicide
attempt. Emotional abuse and neglect are the least frequently measured
subtypes in child abuse research (Moody et al., 2018), but given the seri-
ousness of these associations, it is imperative that they are included in future
research so that the true impact of child maltreatment on mental health can be
properly ascertained.
The next most numerous class, accounting for 11.2% of participants, was a
maltreatment and domestic violence class. This class was characterised by
moderate to very high probabilities of experiencing physical and emotional
abuse and neglect; sibling abuse; and exposure to physical and verbal do-
mestic violence, and a drug-related threat. Although the likelihood of ex-
periencing sexual abuse was low, this group was more likely than any other to
report experiencing this type of victimisation. This suggests that when sexual
abuse occurs within the home, it is most often experienced in conjunction with
several other types of maltreatment, rather than in isolation. In this particularly
14 Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1155
complex class, violence occurs within several dyads in the family, including
between parents/adults, from parents/adults towards children, and between
children/siblings. We did not collect information on the parent/adult re-
sponsible for perpetrating domestic abuse and child abuse, but in the event that
this is the same person, it might be attributable to a lack of non-violent conflict
resolution strategies for dealing with disputes and the challenges associated
with parenting, or the internalisation of social norms (e.g. patriarchal attitudes)
than condone violence against certain family members (Buffarini et al., 2021).
This raises the possibility that perpetrator programmes designed to address
deficits in interpersonal skills and attitudes that normalise violence, have the
potential to reduce violence against multiple family members, including
children. Another explanation for the co-occurrence of violence within
families is the contagion effect, whereby negative styles of interaction are
transmitted from one dyad to another (Van Berkel et al., 2018). For instance,
parents/adults subjected to domestic abuse might be traumatised by their own
victimisation experiences, leading to difficulties meeting the basic needs of
children within the household. Stemming from a social learning theory
perspective (Bandura, 1977), scholars contend that children who witness
violence or neglect in the home begin to imitate these behaviours in their own
relationships, resulting in aggression or a lack of supportive and empathic
behaviours towards siblings (Button & Gealt, 2010). Further, violence be-
tween siblings contributes to parental stress, increasing the potential for harsh
and dysfunctional parenting strategies (Van Berkel et al., 2018). The co-
occurrence of multiple forms of violence among several family members calls
for an integrated response to the problem involving several agencies/services
and a systemic approach to intervention.
Members of the maltreatment and domestic violence class demonstrated
the poorest psychological wellbeing, as evidenced by the highest symptoms of
anxiety and depression, and the greatest proportion of children reporting a
history of non-suicidal self-injury, self-harm and suicide attempt. In cases
where violence is perpetrated by more than one family member, this might
mean that several people in the home are associated with traumatic memories,
reducing the availability of support mechanisms, and placing an even greater
demand on children’s personal coping strategies. Further, self-blame is often a
significant component of victimisation trauma, and children who are subject to
violence from multiple sources might find it more difficult to resist this
negative self-attribution (Finkelhor et al., 2007). These findings highlight the
importance of identifying the breath of children’s maltreatment experiences –
simply knowing that a child has been maltreated does not necessarily illu-
minate the degree of suffering and the potential seriousness of the impact on
mental health.
Lastly, we recovered a high verbal domestic violence class, characterised
by a very high probability of endorsing verbal domestic violence, moderate
Sharratt et al. 15
NP1156 Journal of Interpersonal Violence 38(1-2)
probabilities of endorsing exposure to physical domestic violence and a drug-
related threat and low or very low probabilities of endorsing all forms of direct
maltreatment from parents/adults and siblings. Compared to the low-
victimisation class, children belonging to this class reported higher symp-
toms of depression and anxiety, and an increased likelihood of non-suicidal
self-injury, suicide ideation and suicide attempt. Despite the lower likelihood
of direct maltreatment, it would appear that children might be indirectly
affected by the emotional pain inflicted on parents/adults within the home, and
professionals should be aware that this could be manifest in a range of
different symptomology. This class accounted for 10.5% of participants, a
similar proportion to the aforementioned maltreatment and domestic violence
class. Previous research revealed that witnessing domestic violence confers an
increased risk for other types of maltreatment (Hamby et al., 2010;Radford
et al., 2011), but in contrast, the current findings highlight that it should not be
assumed that a child who is exposed to domestic violence is also likely to have
experienced direct maltreatment. Further inspection of the item response
probabilities indicates that direct maltreatment is more likely to be associated
with exposure to multiple forms of domestic violence (physical, verbal and a
drug-related threat) than is exposure to verbal domestic violence only. This
observation illustrates the usefulness of person-centred approaches in dis-
covering qualitative differences in victimisation profiles that might signal a
differential risk of other maltreatment experiences.
Differences were also observed in the sociodemographic composition of
these two classes. Having three or more siblings predicted membership to the
maltreatment and domestic violence class but not the high verbal domestic
violence class. Moreover, members of the maltreatment and domestic violence
class were more likely to be White whereas member of the high verbal
domestic violence class were more likely to be non-White. Previous research
by Finkelhor et al. (2007) also demonstrated that poly-victims were more
likely to come from larger families, and although these children were more
likely to be of Black ethnic origin, this might be attributable to the inclusion of
a wider range of victimisation types in Finkelhor et al.’s study, including non-
maltreatment. From an evolutionary perspective, it has been argued that
siblings are natural-born competitors for material goods and parental attention
(Dantchev & Wolke, 2019). This might explain why children from the
maltreatment and domestic violence class were the most likely to report
sibling abuse and having three or more siblings. These findings might carry
important implications for the targeting of secondary prevention initiatives
designed to protect children from further victimisation following exposure to a
single type of maltreatment. However, this should not be the responsibility of a
single sector, and close collaboration is required between agencies/services
working with both adult and child victims in order to appropriately target
interventions and monitor progress.
16 Journal of Interpersonal Violence 0(0)
Sharratt et al. NP1157
The current study should be interpreted in light of several limitations. First,
we recruited participants from a small selection of schools and colleges and
did not include children under the age of 10. This study warrants replication
among a larger and more diverse sample to ascertain whether the findings can
be generalised to children and adolescents as a whole. Second, we relied
entirely on self-reported lifetime maltreatment, which was coded dichoto-
mously (yes/no). This meant that we could not ascertain the age of onset or the
frequency of maltreatment, which are important factors in predicting the
severity of the impact on mental health (Rivera et al., 2018). Information
pertaining to the sex of the perpetrator also was not collected, though this is
understood to influence both the frequency/severity of abuse and the severity
of post-traumatic stress symptomology among male victims (Gil, 2014).
Future research should endeavour to use multi-rater assessments including a
combination of self-report and parent/professional ratings, especially as the
latter can be particularly useful in terms of gauging the age of onset and the
severity or chronicity of abuse. It will also be important that future studies use
assessments of mental health outcomes that have been validated for use within
general population samples of children and young people. Third, the adoption
of a cross-sectional design also precluded the identification of any causal
relationships. It is entirely plausible, for instance, that one-parent households
might reflect the breakdown of relationships following domestic or child
abuse, as opposed to being a risk factor for the occurrence of violence. Further,
children with mental health problems might be more vulnerable to abuse, and
therefore we cannot be certain that indicators of poor mental health reflect a
consequence of their victimisation. Longitudinal research is required to es-
tablish cause-effect relationships and developmental trajectories in mental
health sequelae.
In conclusion, the current study provides important information how child
abuse and neglect, exposure to domestic violence and sibling abuse can
intersect to produce complex patterns of poly-victimisation. Compared to the
low victimisation class, participants in the high verbal domestic violence
class, emotional abuse and neglect class, and especially the maltreatment and
domestic violence class, reported higher symptoms of anxiety and depression
and an increased likelihood of non-suicidal self-injury, suicide ideation and
suicide attempt. Associations with sociodemographic profiles also revealed
important differences in the composition of the classes, such as an increased
likelihood of one-parent families and larger families (more siblings) in the
most severely victimised class. These findings indicate that future research
would benefit from the incorporation of a broader range of victimisation
experiences –academics investigating child abuse and neglect should be
cognisant of exposure to domestic violence and sibling abuse, and vice versa.
Although these findings already carry important implications for policy and
practice, further research is needed to clarify our understanding of the
Sharratt et al. 17
NP1158 Journal of Interpersonal Violence 38(1-2)
antecedents and consequences of maltreatment profiles so that we might be in
a better position to identify the most vulnerable and severely victimised
children with a view to implementing targeted prevention and harm reduction
programmes.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: This work was supported by the pub-
lication is based on data collected by the None in Three Research Centre. The research
was funded by the UK Research and Innovation (UKRI) (project reference: AH/
P014240/1) and University of Huddersfield. The contents of this publication are the
sole responsibility of its authors and can in no way be taken to reflect the views of the
UKRI.
ORCID iDs
Kathryn Sharratt https://orcid.org/0000-0002-0870-0568
Dominic Willmott https://orcid.org/0000-0002-7449-6462
Nadia M. Wager https://orcid.org/0000-0002-4817-7556
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Author Biographies
Kathryn Sharratt is a Senior Lecturer in Criminology at the University of
Huddersfield. She has published research on the consequences of parental
imprisonment for children and families, and on the impact of investigations
into suspicious child deaths on police detectives. She also has a keen interest
Sharratt et al. 21
NP1162 Journal of Interpersonal Violence 38(1-2)
in measuring the extent and impact of child maltreatment using latent profile/
class analysis.
Samantha J. Mason is a Research Assistant with the None in Three Centre at
the University of Huddersfield. Her research interests include child mal-
treatment and the health and wellbeing of children and adolescents. She has
previously worked on projects funded by the National Institute for Health
Research (NIHR) and Prostate Cancer UK.
Gillian Kirkman is Subject Leader in Social Work at the University of
Huddersfield. As a qualified social worker, she has worked in the fields of
child protection, family support, looked after children, and adoption and
fostering. Her current research focuses on young people’s experiences of
dating/intimate partner violence using mixed methods.
Dominic Willmott, PhD, is a Senior Lecturer in Forensic Psychology at
Manchester Metropolitan University. His primary area of expertise is juror
bias in rape trials, and in 2020 he was appointed Academic Advisor to the
Victim Commissioner for England & Wales. More broadly he has published
work on attitudes towards sexual and domestic violence, offending moti-
vations, and child maltreatment.
Danielle McDermott is an Associate Senior Lecturer in Forensic Psychology
at Leeds Trinity University. She previously worked for the Prison Service,
delivering and designing cognitive skills programmes aimed at increasing
emotion management and interpersonal skills. Her research interests are in the
areas of offending cognitions and interventions, and psychological correlates
of self-harm and suicide in offender populations.
Susan Timmins is a Senior Lecturer in Secondary Education at the University
of Huddersfield. Previously a teacher in Business and ICT, she has co-
ordinated projects to monitor and raise attainment across school subjects.
Her research interests involve computer science and education gaming,
teacher leadership, and online learning and pedagogy.
Nadia M. Wager, PhD, is a Reader in Forensic Psychology at the University
of Huddersfield. She has a long history of evaluating community interventions
for victims of serious crimes, including modern-day slavery and child sexual
abuse. She also has a keen interest in quantifying societal responses to
victimisation and the application of restorative justice in sexual victimisation
cases.
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