Determinants of Referral Outcomes for Victim–Survivors Accessing Specialist Sexual Violence and Abuse Support Services

ABSTRACT

Sexual violence and abuse (SVA) is highly prevalent globally, has devastating and wide-ranging effects on victim-survivors, and demands the provision of accessible specialist support services. In the UK, Rape Crisis England & Wales (RCEW), a voluntary third sector organization, is the main provider of specialist SVA services. Understanding the profile of victim-survivors who are referred to RCEW and their referral outcomes is important for the effective allocation of services. Using administrative data collected by three Rape Crisis Centres in England between April 2016 and March 2020, this study used multinomial regression analysis to examine the determinants of victim-survivors’ referral outcomes, controlling for a wide range of potentially confounding variables. The findings demonstrate that support needs, more so than the type of abuse experienced, predicted whether victim-survivors were engaged with services. Particularly, the presence of mental health, substance misuse and social, emotional, and behavioral needs were important for referral outcomes. The referral source also influenced referral outcomes, and there were some differences according to demographic characteristics and socioeconomic factors. The research was co-produced with stakeholders from RCEW, who informed interpretation of these findings. That victim-survivors’ engagement with services was determined by their support needs, over and above demographic characteristics or the type of abuse they had experienced, demonstrates the needs-led approach to service provision adopted by RCEW, whereby resources are allocated effectively to those who need them most.

KEYWORDS:

• Sexual violence
• sexual abuse
• specialist services
• support needs
• engagement
• rape crisis centers
• referral outcomes

Research conducted across the world persistently documents the high prevalence of sexual victimization throughout the lifespan, including childhood sexual abuse (CSA), sexual assault of adults, and sexual harassment within workplaces and educational settings (International Society for Traumatic Stress Studies, Sexual Violence Briefing Paper Work Group, 2018). In the UK, it is estimated that approximately 16.6% of adults aged 16 years and over (7.9 million) have experienced sexual assault (including attempts) in adulthood, with 1.9 million being victims of rape (7.7% women and 0.2% men) (Office for National Statistics, 2023). The National Society for the Prevention of Cruelty to Children (National Society for the Prevention of Cruelty to Children, 2021) estimated that the prevalence of any sexual abuse in children aged 11–17 is 16.5%, and in young people aged 18–24 is 24.1%. In the United States, over half of women and almost 1 in 3 men have experienced sexual violence involving physical contact during their lifetimes, and 1 in 4 women and around 1 in 26 men have experienced completed or attempted rape (Centers for Disease Control and Prevention, 2022). In Australia, 17% of women (1.6 million) and 4.3% of men (385,000) have experienced sexual assault since the age of 15 (Australian Bureau of Statistics, 2021). In Canada, approximately 30% of women and 8% of men have been a victim of sexual assault at least once since the age of 15 (Cotter & Savage, 2019). The Australian Child Maltreatment Study (Haslam et al., 2023) found that overall, 28.5% of the Australian population (aged 16 and over) had experienced CSA, and for young people aged 16–24 the prevalence of sexual abuse was 25.7%.

Sexual violence can be both a standalone criminal incident and a form of domestic and family violence (Coates et al., 2022). It can include rape (completed or attempted), sex trafficking, unwanted touching, sexual harassment, threats, intimidation, peeping, online sexual abuse and taking indecent images without consent, and traditional harmful practices such as female genital mutilation and forced marriage (Post et al., 2011) (hereon referred to as sexual violence and abuse; SVA). Survivors of SVA experience profound and wide-ranging effects, from physical and mental health problems to financial, social, and family-related issues (Gregory et al., 2022; International Society for Traumatic Stress Studies, Sexual Violence Briefing Paper Work Group, 2018; Macy et al., 2018), including impacts on employment and economic wellbeing, educational achievements and career attainments (Boden et al., 2007; Diette et al., 2017; Gill-Dosanjh et al., 2019; Loya, 2015; Potter et al., 2018; Saied-Tessier, 2014), and housing stability and homelessness (Gilroy et al., 2016; Stermac & Paradis, 2001). Sexual abuse in childhood is considered an “adverse childhood experience” (ACE), and the ACEs literature documents the negative effects of CSA on adult physical, psychological, and socioeconomic well-being (Downing et al., 2021; Hashemi et al., 2021).

Such wide-ranging impacts of SVA mean victim-survivors often have multiple needs when it comes to their recovery. To address these needs, victim-survivors may seek help from specialist support services which have developed across the world (Grossman et al., 2009; Macy et al., 2018), many of which are located in the third sector (they are neither public nor private sector), including voluntary and community organizations. In the UK, most specialist support services take a broader remit of domestic abuse (DA), within which support for SVA is available, whilst few are tailored specifically for supporting survivors of SVA (Bunce et al., 2023). Support offered comes in many forms, including helplines, individual advocacy, group work, counseling, safety planning, legal advocacy and child advocacy (Ward et al., 2013; Wegrzyn et al., 2022; Zweig et al., 2021). Support is tailored to individual’s complex and changing needs (Hester & Lilley, 2018), often involving multiple services that can be long- or short-term (Gill-Dosanjh et al., 2019; Macy et al., 2018). The recurrent lack of long-term funding for third sector specialist services means not all victim-survivors who seek help get through the door (Robinson & Hudson, 2011).

As part of their daily work, specialist services collect administrative data for monitoring and evaluation purposes, which can be made available for research (Bunce et al., 2023). Such data has contributed to a considerable evidence base around help-seeking (e.g., Masho & Alvanzo, 2010; Ullman & Filipas, 2001), barriers to disclosure and service access (Thiara & Roy, 2020; Thiara et al., 2012), the effect of interventions upon various victim-survivor outcomes (Carlisle et al., 2023), the profile of service users, and experiences of SVA (Lovett & Kelly, 2016). Partly as a function of there being more DA services than SVA-specific services, there is less SVA-specific literature (Carlisle et al., 2023; Silk, 2023), which is why we focus on SVA in this paper.

Within the modest literature on victim-survivors’ engagement with specialist SVA services specifically, most studies have taken a qualitative approach. The findings demonstrate that victim-survivors seeking support for multiple needs experience considerable hurdles to accessing services (Quadara et al., 2017). For example, victim-survivors of SVA with co-morbid mental health issues can be considered beyond the remit of statutory services, and their needs more likely to be met by specialist third sector organizations (Bond et al., 2018). Few studies have considered how victim-survivors engage with specialist SVA services following initial referral. Findings suggest that victim-survivors can and do engage with specialist SVA services and that the flexibility of support is a key driver of engagement; however, victim-survivors from certain groups such as male victims, ethnic minorities and the LGBT community experience higher levels of unmet need and stigma and discrimination which impacts on engagement with services (e.g., Campbell et al., 2001, Viliardos et al., 2023; Cowburn et al., 2015; Hester & Lilley, 2018; Hester et al., 2012; Javaid, 2017).

A smaller still body of studies have focused on identifying which factors determine the success of referrals to SVA support services. There is some research to suggest that whether victim-survivors self-refer or are referred by other agencies is important. Studies have found that victim-survivors who self-refer to third-sector specialist SVA services perceive them to be independent of statutory agencies (e.g., health services and police) and thus have more confidence to engage with them; specialist services may have to work harder to engage victim-survivors referred to them by statutory agencies as they may be more wary (Robinson & Hudson, 2011). Those who self-refer may also have exhausted informal support options and been encouraged to seek formal support (Green et al., 2024), which could mean they are more ready to engage. The Independent Inquiry into Child Sexual Abuse found that the single most common reason respondents provided for disengaging from support was thinking that it was not helping them (Gekoski et al., 2020). Other reasons included the experience being too traumatic, not feeling ready, the reactions of professionals to disclosure, the quality of counselling support, and the capacity of services to offer any additional or ongoing support.

To the authors’ knowledge, no studies have specifically examined whether the type of abuse or support needs, or a combination of the two, and referral source determine whether victim-survivors engage or not with SVA support services in the UK. Manning et al. (2019) compared victim-survivors of SVA with and without mental health complaints and found no differences in patterns of long-term engagement with an Independent Sexual Violence Advocate (ISVA). Mental health was the only support need examined and, whilst the type of abuse was considered, this was only in terms of history of DA, and the relationship between this and engagement was not assessed. Research that examines a broader range of support needs and assesses how these and the type of abuse experienced are associated with whether or not victim-survivors are engaged with services is needed to inform service provision.

This study aimed to address this, by examining the characteristics of victim-survivors of SVA who sought services from Rape Crisis Centres (RCCs) in an English county between April 2016 and March 2020. Once a referral has been accepted, all victim-survivors go through an assessment service and, following a successful assessment, join a waiting list to receive services. We highlight the profiles of those who are waitlisted, actively engaged with, or not engaged with services during this time period, in terms of socio-demographics, referral source, type of abuse experienced and support needs, and examine whether and how these factors determine referral outcomes.

Methods

Data Description

Rape Crisis England & Wales (RCEW) is the membership organization for 39 RCCs in England and Wales. These centers deliver specialist support services to women and girls affected by rape, CSA and/or other forms of sexual violence; with some also providing services for men and boys. Practical and emotional support for victim-survivors is offered in various forms, including telephone helplines, face-to-face counseling, online video counseling, group work, advocacy, Independent Sexual Violence Advocates (ISVAs), outreach, and various other types of individual or group support and therapy. RCEW also undertake prevention and awareness raising work and provide training for external agencies.

Rape Crisis Centers routinely collect administrative data about victim-survivors accessing their services for monitoring and case management purposes, which is recorded in a centralized data management system. The development of robust reporting requirements over the years has meant increasingly more data are collected. Information collected includes sociodemographics, experiences of SVA, victim-perpetrator relationship, impacts/support needs, risk level, referral routes, engagement with different services and contact with the criminal justice system. Pre-determined coding categories and reporting tools are shared across RCCs (Lovett & Kelly, 2016). Sociodemographic information is categorized at the point of intake, alongside information around the reason for seeking support based on the survivor’s report and, where necessary, the assessment of the frontline worker. Due to their survivor-centered ethos and focus on providing services to meet survivors’ needs, RCEW takes a non-intrusive approach to data collection whereby only what is appropriate is asked and/or what survivors choose to disclose is recorded (Westmarland et al., 2010, cited in Lovett & Kelly, 2016). Data on experiences of SVA are collected in two main ways: (1) information is gathered on the “presenting incident,” which is the reason the victim-survivor contacted the RCC, and contextual information can be added under “incident summary;” and (2) in another section of the database, details of every incident the victim-survivor has experienced throughout their lifetime are recorded, if disclosed. The current study utilized data from (1) only, as everybody in the database has information under presenting incident, whilst more detailed information from (2) is only available for those who engage with services, with more details collected the longer they are engaged.

Data for this study were provided by three RCCs in an English county. The data were collected between April 2016 and March 2020 and inputted to the aforementioned centralized data management system. The case management files for the three RCCs were extracted by RCEW’ research team and transferred to the researchers once all personal identifiers (including name, address and contact details) and open text fields had been removed. To enable statistical analysis of the data, the case management files from the three RCCs were merged into one using Stata 17.

The final merged dataset contained a total of 12,396 referrals or self-referrals to RCEW, relating to 10,704 individuals. There was substantial missing information, particularly on accommodation status (16.7%), primary perpetrator (15.5%), and employment status (15.1%). Missing data was dealt with using listwise deletion, meaning only cases with data on all the variables of interest were included in analyzes. Cases relating to children (under 16) were included in analyzes if parents had consented to provide data on their protected characteristics. This led to our analytical sample of 8,228 (self-) referrals, relating to 7,128 individuals. We carried out analysis on case-level data, in which the main unit of analysis were unique individual cases. Some victim-survivors have multiple referrals within the data collection period and so appear more than once in the dataset. This can be because victim-survivors are not ready to address their trauma when referred by, for example, social care or police, and come back as a self-referral later when they are ready.

Co-production/co-design

The current study was co-produced with RCEW. We conducted a research prioritization workshop including RCEW and five other third sector specialist services partner organizations in January 2023. The aim of the workshop was to develop research questions and research designs to enable increased use of administrative records from domestic and sexual violence and abuse (DSVA) specialist services in academic research, which would be beneficial to service providers. Rape Crisis (RCEW) were the only representatives at this workshop that primarily focus on SVA. The workshop surfaced that a clear priority for RCEW was understanding the determinants of engagement with services as an outcome. Stakeholders from RCEW had ongoing input, particularly with regard to interpreting the findings.

Measurement

All coding of variables into categories was done by two authors and any discrepancies were resolved by discussion with the third author. Categories were also discussed with and approved by stakeholders from RCEW. The dependent variable was victim-survivors’ referral outcome following initial contact with RCEW, i.e. whether or not they were engaged with the service. The referral outcome was measured using the current status variable, for which there were 27 possible response categories. These were recoded into our referral outcome variable with three categories of engaged, waitlisted and not engaged (see Table 1). We considered a positive referral outcome to be when someone was, or had, engaged with the service. It is important to note that non-engagement can be due to a number of reasons, including the referral being inappropriate, victim-survivors not engaging for their own reason(s), services not being available, or difficulty contacting the victim-survivor (Domestic Abuse Commissioner, 2021). Thus, not being engaged is not synonymous with being turned away. There is a temporal component to the waitlisted group because all victim-survivors are automatically transferred to the waitlist following initial assessment (therefore those that are engaged with services have all been on the waitlist previously) and our data reflect victim-survivors on the waitlist at a snapshot in time, as well as a supply component because if individuals have very specific needs and there is no such specialist worker available, they will be on the waitlist for longer. Table 2 shows that, of the referrals into RCEW during this period for which we had full data (n = 8,228), 50% were not engaged with services, 9% were on a waiting list and 42% were engaged with services. See Table 2 for descriptive statistics of all variables.

Table 1. Categorization of dependent and independent variables.

Referral outcome
Engaged	active engaging with service; active to service; actively engaging with service; group only; infrequent; one off session; planned closure; unplanned closure; referred on
Waitlisted	advocacy and counselling waiting list; advocacy waiting list; counselling waiting list; assessment waiting list; initial assessment booked
Not engaged	contact us letter sent; declined service; deferred; did not engage; disengaged; information/advice only; referral incomplete; referral withdrawn; inappropriate referral; not brought to service; dual status client - service denied; service denied; service withdrawn
Type of abuse
Rape	rape; rape in partnership/marriage; rape by peer/trusted adult/adult/adult relative/child/child family member/group; gang related rape; attempted rape
SVA	assault by penetration; voyeurism; sexual assault by a trusted adult/adult relative/adult/child/child family member; sexual bullying; penetration by object; gang related sexual violence; forced sexual activity in public; exposed to sexual images; sexual harassment/violence/exploitation; (serious) sexual assault; female genital mutilation
CR, CSA, other CA	forced into as child; childhood physical abuse; childhood sexual assault/exploitation; child abduction/domestic slavery
Other SVA	witnessed sexual violence; prostitution; pornography; sexualized behavior; exposure; trafficking; revenge porn; making indecent images; sexting; distributing indecent images
Non-sexual violence and abuse	abduction; verbal abuse; stalking and harassment; psychological abuse; internet related abuse; grooming; forced imprisonment; physical abuse; harassment; institutional abuse; financial abuse; emotional abuse; domestic violence; control; torture; stalking
Harmful practices	honor crime; harmful practices; forced marriage; ritual abuse; dowry related abuse; peer exploitation; isolation
Support needs
Mental health	anxiety; depression; PTSD; agoraphobia; OCD; claustrophobia; hearing voices; post trauma symptoms; delusions; hallucinations; triggers; panic attacks; intrusive thoughts; compulsions; dissociation; obsessive thoughts; flashbacks; mental health; phobias; self harm; severe and enduring mental health; personality problems; prescription medication
Suicide	overdose; suicidal thoughts; suicide attempts
Substance misuse	alcohol misuse; drug misuse
Physical health	memory loss; physical injuries; body problems
Sexual health	gynae disorder; sexual problems; sexual transmitted illness; pregnancy as a result of abuse; forced termination of pregnancy; termination of pregnancy
Social	bullying; work difficulties; parenting problems; family relationship breakdown; homelessness; interruption to education; loss of work/income; relationship problems; interruption to employment; social isolation; isolation; school truancy; bereavement/loss; study difficulties; relationship breakdown; adoption
Emotional	anger/aggression; mistrust; fear; self-blame; confusion; guilt/shame; hyper-vigilance; stress; lack of insight/understanding; low mood; low self-esteem; negative self-image
Behavioral	bed wetting; restrictions to movements/activities; sleep problems; nightmares; eating problems; sexualized behavior; behavioral issues; mimicking abusive behavior; sexuality issues; gender issues

SVA = sexual violence and abuse, CR = child rape, CSA = child sexual abuse, CA = child abuse, CJS = criminal justice system.

Table 2. Descriptive statistics of victim-survivors not engaged with, waitlisted for, or engaged with Rape Crisis England & Wales Services.

	Not engaged (n = 4,076)		Waitlisted (n = 701)		Engaged (n = 3,451)		Total (n = 8,228)
	N	%	N	%	N	%	N	%
Rape
Not mentioned	1650	40.5	307	43.8	1636	47.4	3593	43.7
Mentioned	2426	59.5	394	56.2	1815	52.6	4635	56.3
Pearsonchi2(2) = 36.4, p-value = 0.000
Sexual violence and abuse
Not mentioned	2729	67.0	389	55.5	2034	58.9	5152	62.6
Mentioned	1347	33.0	312	44.5	1417	41.1	3076	37.4
Pearsonchi2(2) = 67.9, p-value = 0.000
CR, CSA and other CA
Not mentioned	2467	60.5	387	55.2	1774	51.4	4628	56.2
Mentioned	1609	39.5	314	44.8	1677	48.6	3600	43.8
Pearsonchi2(2) = 63.5, p-value = 0.000
Other sexual violence and abuse
Not mentioned	4037	99.0	695*	98.7	3378	97.9	8107	98.5
Mentioned	39	1.0	N<10		73	2.1	121	1.5
Pearsonchi2(2) = 17.5, p-value = 0.000
Non-sexual
Not mentioned	3669	90.0	607	86.6	3011	87.3	7287	88.6
Mentioned	407	10.0	94	13.4	440	12.7	941	11.4
Pearsonchi2(2) = 17.0, p-value = 0.000
Harmful practices
Not mentioned	4047	99.3	695*	99.1	3418	99.0	8160	99.2
Mentioned	29	0.7	N<10		33	1.0	68	0.8
Pearsonchi2(2) = 1.4, p-value = 0.503
Mental health need
Not mentioned	749	18.4	69	9.8	389	11.3	1207	14.7
Mentioned	3327	81.6	632	90.2	3062	88.7	7021	85.3
Pearsonchi2(2) = 89.6, p-value = 0.000
Suicide-related need
Not mentioned	3540	86.8	476	67.9	2910	84.3	6926	84.2
Mentioned	536	13.2	225	32.1	541	15.7	1302	15.8
Pearsonchi2(2) = 161.3, p-value = 0.000
Substance misuse need
Not mentioned	3655	89.7	617	88.0	3179	92.1	7451	90.6
Mentioned	421	10.3	84	12.0	272	7.9	777	9.4
Pearsonchi2(2) = 18.9, p-value = 0.000
Physical health need
Not mentioned	3891	95.5	640	91.3	3244	94.0	7775	94.5
Mentioned	185	4.5	61	8.7	207	6.0	453	5.5
Pearsonchi2(2) = 22.7, p-value = 0.000
Sexual health need
Not mentioned	3970	97.4	677	96.6	3341	96.8	7988	97.1
Mentioned	106	2.6	24	3.4	110	3.2	240	2.9
Pearsonchi2(2) = 3.0, p-value = 0.227
Social need
Not mentioned	3177	77.9	363	51.8	2380	69.0	5920	71.9
Mentioned	899	22.1	338	48.2	1071	31.0	2308	28.1
Pearsonchi2(2) = 229.0, p-value = 0.000
Emotional need
Not mentioned	2382	58.4	239	34.1	1560	45.2	4181	50.8
Mentioned	1694	41.6	462	65.9	1891	54.8	4047	49.2
Pearsonchi2(2) = 216.7, p-value = 0.000
Behavioural need
Not mentioned	3113	76.4	349	49.8	2347	68.0	5809	70.6
Mentioned	963	23.6	352	50.2	1104	32.0	2419	29.4
Pearsonchi2(2) = 222.9, p-value = 0.000
Referral source
Self-referral	1133	27.8	230	32.8	1190	34.5	2553	31.0
Healthcare referral	952	23.4	180	25.7	833	24.1	1965	23.9
Police/Court/CJS referral	1060	26.0	173	24.7	660	19.1	1893	23.0
Social care/education referral	407	10.0	45	6.4	301	8.7	753	9.2
Voluntary sector referral	311	7.6	41	5.8	226	6.5	578	7.0
Individual	213	5.2	32	4.6	241	7.0	486	5.9

Pearson chi² (10) = 94.8, p-value = 0.000.

Notes: Based on Rape Crisis England & Wales data from three centres (2016–2020). CR = child rape, CSA = child sexual abuse, CA = child abuse, CJS = criminal justice system.

The independent variables for type of abuse included rape; SVA (any type of sexual violence or abuse that is not rape or any type of rape, sexual abuse, or other abuse experienced as a child); child rape, childhood sexual abuse and other child abuse (CR, CSA, and other CA); other SVA (witnessed sexual violence, prostitution, pornography, sexualized behavior, exposure, trafficking and revenge porn, making indecent images, distributing indecent images and sexting); non-sexual violence and abuse, and harmful practices. The type of abuse variables were created by taking information from the original variables of “presenting incident” and “incident summary”. To capture multiple experiences of different types of abuse for individual victim-survivors, binary dummy variables were created for each possible response entered under presenting incident and incident summary, which were then recoded into the six types of abuse variables outlined above (see Table 1).

The independent variables for support needs included mental health, suicide, substance misuse, physical health, sexual health, social (e.g., homelessness, work difficulties, relationship breakdown), emotional (e.g., mistrust, fear, low self-esteem) and behavioral (e.g., restrictions to movements/activities, sleep problems, eating problems). The support needs variables were created by taking information recorded as impacts from the “presenting incident” victim-survivors were referred for, under the original variable of “incident impact.” Again, to capture the potentially multiple support needs for individual victim-survivors, binary dummy variables were created for each possible response entered under incident impact, which were then recoded into the eight support need variables outlined above (see Table 1).

The independent variable of referral source was a recoded version of the original variable collected by RCEW, which had eight categories (health, police, social care, court/criminal justice system (CJS), education, voluntary sector, individual, and self-referral). Due to small group sizes court/CJS was combined with police, and education combined with social care, meaning the final referral source variable had six categories.

Sociodemographic characteristics (age, gender, ethnicity, sexual orientation, disability, relationship to primary perpetrator, dependants, benefits, accommodation, and employment status) were used to examine the profile of subgroups and to adjust for potential confounding in multivariable analyzes.

Statistical methods

Data management, descriptive analyzes and regression analyzes were conducted in Stata 17. To examine which factors contributed to the outcome of referrals, a series of multinomial logistic regressions were conducted, controlling for potentially confounding variables. In Table 3, we examined the associations between type of abuse, support needs, referral source, and referral outcome. All models controlled for all sociodemographic variables of age, gender, ethnicity, sexual orientation, disability, primary perpetrator, number of dependants, benefits, accommodation, and employment status. Results were displayed in relative risk ratios (RRR). Too few observations of waitlisted were present for other SVA and harmful practices (N < 10), therefore for the multinomial logistic analyzes, the coefficients for these types of abuse are not presented to avoid misinterpretation.

Table 3. Referral outcomes based on type of abuse and support needs. Results from multinomial logistic regression analyses, relative risk ratios (RRR) and p-values are presented.

	Model a		Model b		Model c
	Waitlisted vs. not		Engaged vs. not		Engaged vs.
	engaged (base)		engaged (base)		waitlisted (base)
	RRR	p	RRR	p	RRR	p
Type of abuse
Rape	1.041	0.729	0.998	0.979	0.959	0.716
Sexual violence and abuse	1.446	0.000	1.25	0.000	0.864	0.143
CR, CSA and other CA	1.089	0.470	1.186	0.011	1.089	0.470
Other sexual violence and abuse	N<10		1.692	0.013	N<10
Non-sexual	1.199	0.182	1.152	0.084	0.961	0.765
Harmful practices	N<10		0.822	0.472	N<10
Support needs
Mental health need	1.330	0.048	1.604	0.000	1.206	0.203
Suicide-related need	1.615	0.000	0.915	0.245	0.566	0.000
Substance misuse need	0.741	0.032	0.641	0.000	0.865	0.308
Physical health need	1.002	0.992	0.96	0.715	0.958	0.796
Sexual health need	0.873	0.574	1.064	0.676	1.219	0.408
Social need	1.900	0.000	1.28	0.000	0.674	0.000
Emotional need	1.509	0.000	1.394	0.000	0.924	0.444
Behavioral need	1.762	0.000	1.117	0.074	0.634	0.000
Referral source
Self-referral (Ref.)
Healthcare referral	1.049	0.677	0.944	0.387	0.900	0.354
Police/Court/CJS referral	1.096	0.446	0.733	0.000	0.668	0.001
Social care/education referral	0.643	0.019	0.814	0.032	1.265	0.215
Voluntary sector referral	0.747	0.125	0.795	0.025	1.064	0.746
Individual referral	0.788	0.274	1.055	0.630	1.338	0.175
Gender
Woman (Ref.)
Man	0.901	0.484	0.722	0.000	0.802	0.143
Age
Under 16	5.515	0.000	1.243	0.103	0.225	0.000
16–25	1.118	0.417	0.778	0.003	0.696	0.01
26–35 (Ref.)
36–45	0.928	0.586	1.152	0.079	1.241	0.117
46–55	0.786	0.134	1.441	0.000	1.833	0.000
56 and over	0.910	0.668	1.723	0.000	1.893	0.003
Ethnicity
White (Ref.)
Asian (British)	2.330	0.005	2.240	0.000	0.962	0.890
Black (British)	1.112	0.657	1.135	0.329	1.021	0.932
Mixed/Multiple	1.121	0.63	1.069	0.627	0.954	0.841
Sexual orientation
Heterosexual (Ref.)
Bisexual	1.100	0.643	1.155	0.269	1.05	0.812
Gay or lesbian	1.029	0.908	1.341	0.047	1.303	0.283
Other	1.486	0.255	1.239	0.373	0.834	0.596
Undisclosed	0.413	0.000	1.168	0.029	2.828	0.000
Accommodation status
Homeowner/family (Ref.)
Social housing	0.775	0.049	0.712	0.000	0.919	0.513
Private renter	1.071	0.586	0.768	0.001	0.717	0.009
Other/temp	0.603	0.001	0.729	0.000	1.209	0.236
Employment status
Employed (Ref.)
Unemployed	0.632	0.000	0.510	0.000	0.808	0.074
Student	0.59	0.001	0.806	0.015	1.366	0.054
Unable to work or retired	0.663	0.018	0.621	0.000	0.936	0.703
Disability
No disability (Ref.)
Disability	1.265	0.015	0.968	0.56	0.765	0.006
Primary perpetrator
Current partner (Ref.)
Ex-partner	0.926	0.663	0.933	0.509	1.008	0.967
Relative	0.964	0.830	1.012	0.907	1.050	0.777
Acquaintance	0.920	0.581	0.987	0.887	1.074	0.643
Stranger	0.560	0.007	0.779	0.029	1.392	0.127
Dependents
None (Ref.)
One	1.012	0.935	0.960	0.617	0.949	0.711
Two	0.891	0.459	0.741	0.001	0.831	0.241
Three	1.021	0.921	0.845	0.176	0.828	0.363
Four or more	1.034	0.885	0.657	0.003	0.635	0.059
Benefits
No benefits (Ref.)
Receives benefits	1.626	0.000	1.631	0.000	1.003	0.977
Constant	0.070	0.000	0.596	0.000	8.510	0.000

Analyzes based on Rape Crisis England & Wales data from three centers (2016–2020). Ref. = reference category. N<10 for those waitlisted of those who have experienced other sexual violence and abuse and harmful practices. CR = child rape, CSA = child sexual abuse, CA = child abuse, CJS = criminal justice system.

As a robustness check, we conducted a series of binary logistic regressions with first waitlisted grouped together with those not engaged in one model, versus those who were actively engaged with services; and then waitlisted grouped together with engaged in the second model, versus those who were not engaged. The conclusions were very similar to those in the multinomial regressions (available upon request). We also ran robustness analyzes where the type of abuse and support needs variables were entered into the model separately, which led to the same conclusions (available upon request).

Results

Table 3 presents the results from the multinomial logistic regressions used to test for differences between those who were engaged, not engaged or waitlisted, depending on type of abuse, support needs and referral source. The models in Table 3 show that those who experienced SVA had a higher probability of engagement and to be waitlisted, compared to non-engaging, than those who did not experience SVA (RRR = 1.250, p < .001 and RRR = 1.446, p < 0.001, respectively). Experiencing child rape, childhood sexual abuse and other child abuse (CR, CSA and other CA) significantly increased the likelihood of engagement (vs non-engagement) (RRR = 1.186, p = 0.011). Experiencing other SVA significantly increased the likelihood of engagement versus non-engagement (RRR = 1.692, p = 0.013). There was no evidence for differences in referral outcome by rape, non-sexual victimization or harmful practices.

Those with a mental health need had a higher probability of being engaged and to be waitlisted, compared to non-engaging, than those without a mental health need (RRR = 1.604, p < 0.001 and RRR = 1.330, p = 0.048 respectively). Those with a substance misuse need had a higher probability of not engaging compared to both being waitlisted or engaged (RRR = 0.741, p = 0.032 and RRR = 0.641, p < 0.001, respectively). Those with a need relating to suicide were significantly more likely to be waitlisted than not engaged once other (mental health) needs were taken into account (RRR = 1.615, p < 0.001), but also significantly less likely to be engaged than waitlisted (RRR = 0.566, p < 0.001). Having a suicide-related support need did not significantly predict being engaged compared to not engaged. Those with social, emotional, and behavioral support needs had a higher probability of being waitlisted than not engaged compared to those without these support needs (model a). Those with a social or emotional support need (but not a behavioral support need) also had a higher probability of being engaged than not engaged than those without these support needs (model b). Those with a social or behavioral support need (but not an emotional support need) had a lower probability of being engaged than waitlisted (model c).

Those who were referred to RCEW from the police/court/CJS; social care/education, or another voluntary sector agency were significantly less likely to be engaged than not engaged compared to those who self-referred (RRR = 0.733, p < 0.001; RRR = 0.814, p = 0.032, and RRR = 0.795, p = 0.025, respectively). Police/court/CJS referrals were also less likely to be engaged than waitlisted (RRR = 0.668, p = 0.001) and social care/education referrals were less likely to be waitlisted than not engaged (RRR = 0.643, p = 0.019) compared to those who self-referred.

In terms of socio-demographic factors, men had a lower probability of being engaged than not engaged compared to women (RRR = 0.722, p < 0.001), with no significant differences when it came to being waitlisted in any models. In terms of age, those under 16 were more likely to be waitlisted than not engaged (RRR = 5.515, p < 0.001) but less likely to be engaged than waitlisted (RRR = 0.225, p < 0.001) compared to 26-to-35-year-olds. Those aged 16–25 were significantly less likely to be engaged than not engaged compared to those aged 26–35 (RRR = 0.778, p = 0.003), whilst those aged 46–55 and 56 and over were more likely to be engaged (RRR = 1.441, p < 0.001 and RRR = 1.723, p < 0.001, respectively). Those who were from an Asian ethnic background were more than twice as likely to be engaged and waitlisted than not engaged, compared to those who were White (RRR = 2.240, p < 0.001 and RRR = 2.330, p = 0.005, respectively); there was no evidence of any other differences in referral outcomes for any other ethnic groups. Those who did not disclose their sexual orientation were more likely to be engaged than either waitlisted or not engaged, and less likely to be waitlisted than not engaged compared to those who identified as heterosexual. There were no significant differences in the likelihood of being engaged compared to not engaged depending on disability, however those with a disability were significantly more likely to be waitlisted than not engaged (RRR = 1.265, p = 0.015) but less likely to be engaged than waitlisted (RRR = 0.765, p = 0.006) than those without a disability.

Relationship to the primary perpetrator was not reliably associated with referral outcome. Both accommodation and employment status were important determinants of engagement; instability in housing tenure and employment decreased the likelihood of being engaged in all models. Those who received some form of benefits had a higher probability of being either engaged or waitlisted than not engaged in models a and b, compared to those who did not report receiving any benefits. The likelihood of being engaged compared to not engaged was significantly lower for those with two or four or more dependants in comparison to having no dependants.

Discussion

The goal of this study was to explore factors that could be determinants of the outcome of referrals to RCEW, in terms of whether victim-survivors are waitlisted, engaged, or not engaged with services, whilst controlling for potential confounders. The findings suggest that the key drivers of referral outcomes are support needs, particularly mental health, substance misuse and social, emotional and behavioral needs; having experienced SVA, CR, CSA, and other CA and other SVA; referral source; gender; age (particularly being younger or being older); being of Asian ethnicity; socioeconomic factors of accommodation and employment status and receipt of benefits and having two or more dependents. Overall, findings from the models suggest that the needs profile of victim-survivors is a stronger predictor of the referral outcome than the type of abuse experienced. Results showed few differences between the waitlisted and engaged groups, with the most notable differences between those not engaged and engaged.

There are multiple potential mechanisms and explanations for these findings. Due to there being limited comparable studies, we largely draw upon consultation with RCEW stakeholders to interpret our findings. Given the common conception that supporting rape victims is RCEW’ primary remit, it is perhaps surprising that having experienced rape was not significantly associated with referral outcome in this study. While over half of cases in the data involved rape (56.3%), that other types of abuse, but not rape, were predictive of referral outcome demonstrates the broad spectrum of experiences of SVA that RCEW responds to and suggests that victim-survivors of other types of SVA besides rape are not deprioritised. Those who had experienced other SVA, which included having witnessed sexual violence, prostitution, pornography, sexualized behavior, exposure, trafficking, revenge porn, making indecent images, distributing indecent images and sexting, were more likely to be engaged than not engaged. Stakeholder consultation suggested such cases likely relate to high-risk survivors and/or children, who are likely to be prioritized for immediate support and additional effort made to keep them engaged. This finding also shows that, whilst RCEW is a needs-led service, risk is still important and responded to. There is limited research about engagement with services by people who have experienced these types of abuse, which future research should investigate further.

Stakeholder consultation suggested that the higher likelihood of engagement for those with a mental health need could be linked to the availability of local mental health service provision and the quality of those services. The finding that those with a substance misuse-related need were more likely to not be engaged with services is in line with previous literature which suggests that the siloing of services and lack of cross-training and comprehensive understanding of co-occurring DSVA, substance misuse and mental health can force victim-survivors to choose to prioritize one service over another (Fox, 2020; Holly et al., 2012). Stakeholder consultation also highlighted that victim-survivors with substance misuse-related needs may need to be referred multiple times before they are ready to engage with services. Victim-survivors with suicide-related support needs were most likely to be waitlisted compared to engaged or not engaged. It is possible that suicidality was confounded with other mental health issues. It could also be that victim-survivors with suicide-related needs were on the waiting list pending referral to other specialist mental health services, which typically have long waiting lists (Brooker & Durmaz, 2015). RCEW strives to stay in contact with victim-survivors who are waiting for support to reduce the risk of them disengaging, which qualitative research suggests can be effective (Walshe, 2020); hence victim-survivors may have remained on the RCC’s waiting list until their ongoing referral was complete. In relation to findings regarding suicide attempts and ideation, stakeholders also highlighted potential variability in recording practices here, due to workers’ different thresholds for recording. Presenting with social, emotional, and behavioral support needs was reliably associated with a higher likelihood of being engaged with services; possibly due to the comparative availability of general counseling and advocacy services to meet such needs (Hester & Lilley, 2018).

Our findings suggest that those who self-refer into RCEW are more likely to engage with services than those referred by police/court/CJS, social/education or other voluntary sector agencies. Overall, that self-referrals are positively associated with engagement is unsurprising and likely to do with victim-survivors’ readiness to engage, that is, they referred themselves for support when they felt ready to receive it. Those referred by statutory agencies, on the other hand, may have had negative experiences with these agencies which influenced their likelihood of subsequently engaging with specialist third sector services. Another possibility is that those who self-referred were more likely to be engaged because it was not the first time they had accessed RCEW, and they were more ready to engage this time. The finding that healthcare referrals were not associated with engagement is more surprising, as previous research suggests healthcare responses and referral processes are similarly negatively perceived by victim-survivors to that of the police (SafeLives, 2021). At the same token, it is surprising that those referred by other voluntary sector agencies were also less likely to engage with RCEW, although this could also be down to readiness and/or previous negative experience. Stakeholder consultation highlighted that the validity of data on referral source is limited in that direct referrals are not always captured because, due to political and funding issues, statutory services often close cases and signpost to RCEW instead of following formal referral processes.

The finding that men were more likely to be not engaged with services than engaged in the current study is in line with the growing evidence base on the challenges of engaging men in SVA support services (Javaid, 2017; Viliardos et al., 2023; Widanaralalage et al., 2022). Such studies suggest that once men have overcome the barriers to accessing specialist SVA services, which are traditionally perceived as for women only, lack of understanding, discrimination, and stereotypical assumptions by professionals can discourage engagement.

Whilst the negative association between unstable employment/accommodation status and having children and being engaged with services is in line with previous research (Anderson et al., 2023; Loya, 2014), the finding that receiving benefits was positively associated with being engaged even when controlling for all of these other factors is somewhat surprising. Although, stakeholder consultation suggested that substantial local specialist service provision for help securing benefits might explain this. It is possible that receiving benefits increased trust in the system more generally and therefore encouraged engagement with RCEW. This interpretation is somewhat circular, however, because RCEW are also likely to have helped victim-survivors with benefits, so it could be that those who were already engaged with RCEW services were more likely to have received support to secure benefits (Hester & Lilley, 2018).

Previous research generally finds that ethnic minority members are less likely to approach services, particularly statutory ones (Thiara & Roy, 2020); although some studies have found that those from British South Asian communities are accessing specialist non-statutory services (Anitha, 2019; Cowburn et al., 2015). Our finding is in line with this latter study. Stakeholder consultation suggested that people from Asian communities who have accessed RCCs, who face additional hurdles in doing so, may have made a particularly considered, active decision to engage, and it is this resolve that underlies their continued engagement. It is also important to note that the current sample was overwhelmingly White, representing the region in England these RCCs are based.

The finding that those with a disability were more likely to be waitlisted than either engaged or disengaged with services could be support for findings from previous studies that disability acts as a barrier to accessing services (Scriver et al., 2013), although this cannot be physical accessibility of RRC premises due to RCEW accessibility standards (Rape Crisis, n.d.).

The current study has important strengths. It is the first study to explore beyond barriers to accessing RCCs, to provide evidence of the needs-driven approach to service provision adopted by RCEW and other specialist SVA services. The study was co-produced with RCEW, meaning input from relevant stakeholders and experts on the ground was gained throughout, from initial discussions of the research question, to the research design, and particularly when interpreting results.

It is important to highlight some limitations of the data. Data pertain to a population of service users and are thus not representative of all survivors of SVA. The majority of the sample were White, so findings cannot be generalized to survivors from racial and ethnic minority groups. Analysis of differences by gender identity was limited because the numbers of transmen, transwomen, and non-binary people were too low to enable any further disaggregated analysis. Having previously collected data under sex, RCEW now collects both sex registered at birth and gender identity, which will enable further analyzes in future. Due to data not being collected for research purposes, there were inevitable issues of quality and missingness. However, additional analyzes demonstrated the robustness of our findings. While this study design was quantitative and cross-sectional, and we engaged with stakeholders at design and interpretation stages, we did not have input from people with lived experience, which can be valuable for demonstrating how pathways to support services are not straightforward (Quadara et al., 2017). Furthermore, the cross-sectional nature of the data provides a snapshot at a point in time, meaning some of the characteristics of those waitlisted, engaged or not engaged may relate to when this snapshot was taken, and some of the variation found may not be meaningful. It is important to note that the transition from initial referral, to being waitlisted, to being engaged in services is a pathway and not an “event”; not least because victim-survivors often have chaotic lives, and RCCs are under resourced (Howarth & Robinson, 2016). Whilst all victim-survivors are waitlisted, case managers can choose to target resources toward people who are particularly vulnerable or at high risk of disengaging whilst waiting for services. Mixed methods and longitudinal research could improve understanding of the complexities of these pathways, including reasons underlying (dis)engagement.

In terms of policy and practice implications, the current study has some important implications, particularly in relation to the cultural sensitivity of services and how they can best meet the needs of clients with specific vulnerabilities such as being in economic or housing crisis. Whilst the UK has developed policies to support victim-survivors of DA (e.g., improved access to unemployment benefits; UK Government, 2019), this is less so the case for SVA. In both policy and research, SVA is often convoluted with DA, but they are different, and whilst DA organizations often include support for SVA within their offering, victim-survivors of SVA may prefer to access services that specifically and primarily focus on SVA. The messages and awareness about help available need to be clearer so that victim-survivors of SVA know what support they can get and how to access the services they need. At the service level, our findings suggest that focusing on the provision of benefits, and on victim-survivors with mental health and substance use needs and those who have not self-referred, might facilitate engagement with SVA support. These needs are wide-ranging, and it is unclear in what sequence and combination interventions to address them are effective, therefore RCEW and other specialist SVA services could co-develop interventions with people with lived experience to increase victim-survivor engagement. Understanding how certain vulnerabilities and difficulties effect people’s ability to access and engage with services will help service providers identify who might need additional resource or support (and, with insights from future longitudinal analyzes; when). This could shape future service provision by ensuring support is person-centered and “meets people where they are”, which can improve engagement (Viliardos et al., 2023, Hester & Lilley, 2018).

Our findings also underscore the need for ringfenced, sustainable funding for specialist SVA services in the UK, which would enable services to actively engage with a higher proportion of people seeking their help. Whilst this study has demonstrated that RCEW is addressing the needs of victim-survivors even in the current climate of piecemeal and insecure funding, it is inevitable that many victim-survivors continue to be underserved. A priority area for allocating additional resources is services for survivors who are suffering with complex and multiple problems, especially mental illnesses and substance abuse (Sosenko et al., 2020). The current findings only pertain to the UK, therefore these policy and practice implications may be less relevant in countries with different service provision landscapes and referral processes. However, as there are some parallels in practices from country to country, we hope some of the issues discussed are useful for policymakers and practitioners in other countries.

This study has highlighted some questions for future research. Firstly, data analyzed in the current study do not tell us what services victim-survivors may have wanted but were unable to receive, which is important to explore to better understand the need for and provision of services. Further, cases categorized as “not engaged” in this study included those where the referral was inappropriate, and where victim-survivors had not engaged for their own reason(s), the latter being by far the larger group, despite the best efforts of RCC staff. Future research could explore reasons for case closure further. Research could also explore potential differences in referral outcomes between those who engage for a single session and those who are engaged with services over a longer period of time, and explore why some victim-survivors only engage for one session. Finally, research is needed on use, barriers, and access to services among survivors from underserved populations, including ethnic and cultural minorities, people with disabilities, the financially vulnerable, sexual and gender minorities, and those with comorbid mental health conditions and/or problematic substance use. In terms of ethnic minority groups, future research could explore generational impacts on patterns of engagement across groups.

Conclusion

The findings from our cross-sectional analysis suggest associations between victim-survivor’s support needs (and, to a lesser extent, abuse histories), referral source, socioeconomic circumstances, demographic characteristics, and their referral outcomes following access to RCCs. Summarising our findings, there were fewer associations between abuse types and the referral outcome than support needs. Victim-survivors who had experienced SVA; child rape, childhood sexual abuse and other child abuse; and other SVA were more likely to be engaged. Those with mental health needs and social, emotional, or behavioral-related needs were more likely to be engaged, whilst those with substance misuse needs were less likely to be engaged. Victim-survivors with suicide-related needs and those with a disability were most likely to be waitlisted. Those referred to RCEW from police/court/CJS; social care/education, or another voluntary sector agency were less likely to be engaged than those who self-referred. Men were less likely to be engaged, as were those in the youngest age groups, whilst those in older age groups were more likely to be engaged. Those from an Asian ethnic group were more likely to be engaged, as were those who received benefits, whilst those with unstable housing or employment and with children were less likely to be engaged. Overall, these findings suggest that the likelihood of being engaged or otherwise with services is more associated with victim-survivors’ needs than their abuse histories, and that RCEW’ needs-led approach to support provision is keeping many victim-survivors engaged, even those with substantial support needs. Longitudinal analyzes are needed to better understand engagement with services over time and to identify the mechanisms underlying such associations. Future research should also explore whether services obtained actually meet victim-survivors’ needs, for example using data from RCEW’ outcomes framework. Whilst RCEW and other specialist DSVA services in the UK are undoubtedly doing their best with the resource and capacity they have got, investment of adequate resources for specialist third sector services is greatly needed. The struggle to deliver services with such limited resources is, as voiced by one of this study’s stakeholders “like going to war, not going to work.” Until this is no longer the case, the extent to which victim-survivors’ needs can be met will be limited.

Ethical standards and informed consent

The secondary data analyzes were approved by the committee at City, University of London that considers medium-risk applications (ETH21220–299). The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Acknowledgment

The authors would like to thank Amelia Handy, Rebekah Brant and the Rape Crisis team for all their contributions to this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by a grant from the UK Prevention Research Partnership (Violence, Health and Society; MR-VO49879/1. The views expressed in this article are those of the authors and not necessarily those of the UK Prevention Research Partnership.

Notes on contributors

Annie Bunce

Annie Bunce is a Research Fellow in Criminology at the Violence and Society Centre, City, University of London.

Niels Blom

Niels Blom is a Research Fellow in Criminology at the Violence and Society Centre, City, University of London.

Estela Capelas Barbosa

Estela Capelas Barbosa is a Senior Lecturer in Health Economics at the University of Bristol and UKPRP VISION Co-Deputy Director.