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The deadline to provide feedback using the link above is 30 June 2024.
Two researchers of the VISION consortium project presented at the Health Studies Conference in July.
Dr Elizabeth Cook, Senior Lecturer at City, University of London, presented Indirect victims of violence: mental health and the close relatives of serious assault victims in England.
Dr Annie Bunce, Research Fellow at City, University of London, presented Prevalence and nature of workplace bullying and harassment and associations with mental health conditions in England: a cross-sectional probability sample survey
The free event was on 1 July at University College London (UCL) and organised by the UK Data Service in collaboration with UCL and the National Centre for Social Research. The conference provided updates from the data producers of key UK social surveys with health-related content, such as the Health Survey for England, Understanding Society and the English Longitudinal Study of Ageing. There were also presentations by researchers who conducted analyses using health data.
VISION researchers from the Systematic Review working group (Andri Innes, Sophie Carlisle, Hannah Manzur, Elizabeth Cook, Jessica Corsi and Natalia Lewis) have published a systematic review and meta-analysis in PLOS One, estimating prevalence of physical violence against people in insecure migration status. This is the first review of its type, synthesizing global data on violence against migrants in all types of insecure status.
The review finds that around 1 in 3 migrants in insecure status experience physical violence. Violence included physical interpersonal, community and state violence. Insecure status was conceptualised encompassing undocumented status, lapsed statuses, asylum seeking and other pending applications, and any status that embeds a form of insecurity by tying status to a particular relationship (such as spousal or employer-employee). Studies were only included in the review if the violence happened while the victim was in insecure status.
The VISION team reviewed academic literature published between January 2000 and May 2023, across social and health sciences. The study was global in scope, although data was limited by the English language search.
Key Findings
More than one in four migrants in insecure status disclosed intimate partner violence specifically. Spousal visas embed a particular risk of violence because the visa status is connected to an intimate partner relationship, creating an important power disparity. Nevertheless, there was no significant difference in prevalence of violence by gender across the dataset. Prevalence also did not differ meaningfully across geographic region, perpetrator, status type or time frame.
The most significant findings included that violence exposure is not meaningfully different for people in undocumented status than in other types of insecure status. Physical violence is a concern across all types of insecure migration status types.
The findings were limited because of high levels of heterogeneity in the data. It was also difficult to consider intersectional identity characteristics such as age, race or ethnicity, nationality, religion, marital status, socio-economic status, education level or motivation for migration because these were not standardised across included studies. This suggests that further and specified research is needed in this area.
The review is open access and is available to read in full here.
The latest research by VISION colleagues, Vanessa Gash and Niels Blom at City, finds serious negative effects of intimate partner violence and abuse (IPVA) on labour market outcomes, with 3.6% of those who experienced intimate partner violence losing their jobs because of the abuse. Furthermore, 1 in 10 of those who experienced intimate partner violence took a period of leave from work, with 1 in 4 of those who took leave needing to take a month or more off work.
Based on a large statistically representative sample for England and Wales, this research is one of the first to examine different types of IPVA, with five categories distinguished in the analysis.
The report examines differences between those who experienced; (1) physical abuse, (2) sexual abuse, (3) stalking, (4) coercive or controlling behaviour, as well as those who were (5) threatened with abuse by a current or former intimate partner. There were strong differences in prevalence of IPVA by sex, with women disproportionately exposed to threats (34% compared to 15% for men) and to sexual violence (7% compared to 3% for men). Additionally, compared to men, women were more likely to report multiple types of violence and abuse.
Job loss is associated with all five forms of IPVA, and the risks were highest for those who experienced: stalking, sexual violence as well as physical threats by an intimate partner. The research also includes qualitative findings from those with lived experience of IPVA and abuse. Participants noted an ongoing stigmatisation of victims of abuse, which had serious impacts on disclosure. Victim-survivors noted their fear of being declared ‘unfit for work’ and of becoming a ’marked person’ should they disclose their abuse to relevant managers.
Policy implications
Though IPVA was found to have significant effects on victims’ experiences at work, those with lived experience noted a reluctance to disclose IPVA to relevant managers.
Employers may therefore want to consider enhanced IPVA and DA support systems for employees in the workplace.
While we can expect enhanced support to improve job retention and productivity, we currently lack the appropriate data to directly examine these effects
For further information please download the full report below and / or contact Dr Vanessa Gash at vanessa.gash.1@city.ac.uk.
Dr Vanessa Gash is a Reader in the Department of Sociology and Criminology at City and a member of the UKPRP VISION team based at the Violence & Society Centre.
Dr Niels Blom is a Research Fellow at the Violence & Society Centre and a member of the UKPRP VISION team.
In 2022, the UK Office for National Statistics (ONS) developed a prototype violence against women and girls (VAWG) dashboard. The tool presents statistics and charts on violence against women and girls in England and Wales, drawing on multiple sources. However, due to re-prioritisation at ONS, maintenance of the dashboard was halted and from 1st April 2024 it will no longer be accessible.
The VISION consortium is consulting on whether there is need for a VAWG data dashboard. This consultation is seeking views on:
Whether the dashboard was useful
Who used it and why
If the dashboard was to continue, what aspects should be kept, dropped or added.
The Qualtrics consultation link is now closed because the consultation is over.
Anyone interested in the idea of a VAWG data dashboard is welcome to respond to the survey, particularly if interested in using one in the future.
Answer as many questions as you like. You can provide contact details or complete this anonymously. The findings will be used to draft a report and provide recommendations on whether the dashboard should continue. The report will include a list of the groups and organisations that participated (where details are provided). Individuals will not be named, although quotes may be taken from the text provided. The report may be published, for example on the VISION website.
The ONS VAWG dashboard was available online until 31 March 2024. Therefore, if you would like to participate in this consultation, please view the sample screenshots of the tool below.
Despite violence being recognised as a harm to health, it is not consistently or adequately captured in healthcare data systems. Administrative health records could be a valuable source for researching violence and understanding the needs of victims, but such datasets are currently underutilised for this purpose.
Anastasia worked with Hospital Episode Statistics Accident and Emergency (HES A&E) and the Emergency Care Data Set (ECDS) while on secondment at the Department of Health and Social Care (DHSC), with helpful review provided by researchers in the department.
Among the datasets reviewed in the study, the South Wales Violence Surveillance dataset (police and emergency department data linked by Public Health Wales) had the most detail about violent acts and their contexts, while the Clinical Practice Research Datalink (CPRD) provided the more extensive range of socioeconomic factors about patients and extensive linkage with other datasets. Currently, detailed safeguarding information is routinely removed from the ECDS extracts provided to researchers, limiting its utility for violence research. In the HES A&E, only physical violence was consistently recorded.
Addressing these limitations and increasing awareness of the potential utility of health administrative datasets to violence-related research has the potential to provide insight into the health service needs of victims.
VISION researchers Dr Annie Bunce and Dr Estela Capelas Barbosa have been working with administrative data provided by specialist domestic and sexual violence and abuse (DSVA) support services.
Whilst the wealth and breadth of the data collected creates exciting opportunities for improving our understanding of patterns in experiences of violence and service use, the process of preparing the data for analysis has its challenges. Such challenges- and potential strategies for overcoming them- are not well documented, creating missed opportunities for improving the utilisation of specialist services’ data.
In their new publication, Annie and Estela, along with City, University of London PhD student, Katie Smith, and Dr Sophie Carlisle, a former VISION researcher, reviewed the scope and merits of administrative data generally, and that collected by specialist DSVA services specifically, and the evidence to date for its use by researchers.
They found that the extent to which new insights on violence from specialist services’ data can be used to inform policy and practice is limited by three interrelated challenges: different approaches to the measurement of violence and abuse; the issue of disproportionate funding and capacity of services, and the practicalities of multi-agency working.
Nonetheless, the authors maintain the unique contribution to knowledge on violence that can be provided by DSVA services’ administrative data, and are hopeful that the paper will encourage further discussion about how to better utilise it. Additional resources, collaboration between multiple agencies, service providers and researchers, and the integration of specialist services’ data with other sources of data on violence are needed to maximise policy impact. Given the benefits individuals and society stand to gain, this is a worthwhile endeavour.
VISION researchers Dr Polina Obolenskaya, Dr Elouise Davies and Dr Niels Blom will present at the Crime Surveys User Conference 2024 on 6 February 2024 in Islington, London.
The event brings data producers and data users together to share updates on the development of the surveys and to showcase research that is being carried out using the data. It is organised by the UK Data Service in collaboration with the Office for National Statistics, Scottish Government and the Home Office.
Polina – The rise, fall and stall of violence in England and Wales: How have risks of violence changed for groups in the population?
Elouise – When there’s more than one assailant: Understanding variation in victims’ needs
Niels – New Crime Survey for England and Wales integration code: Impact for investigating rare events such as different intimate partner perpetrator types
However, recently, ‘Understanding Society’, the United Kingdom Household Panel Survey (UKHLS), began fielding a small battery of questions relating to violence experience. Here, we examined the strengths and weaknesses of these UKHLS measures with similar indices from the Crime Survey for England and Wales (CSEW), a widely used and regarded but cross-sectional survey.
Vanessa and Niels empirically assessed the extent to which the UKHLS variables are comparable with those in the CSEW to determine the viability of the UKHLS for the longitudinal study of (fear of) violence and its consequences.
Overall, they regarded the UKHLS to provide an important resource for future panel research on the consequences of victimisation. They found the indicators measuring physical assault to be similar in both sets of data, but also noted differences in prevalence and/or different distributions by socioeconomic group for the indices relating to being threatened and of feeling unsafe.
Nonetheless, Vanessa and Niels maintain their utility for researchers in this field, allowing researchers to uncover new inequalities in violence exposure.
The Crime Survey for England and Wales (CSEW) and its predecessor, the British Crime Survey (BCS), are widely used by both academics and government to assess the level of crime and its impact on society. While the survey has run since 1982, combining the multiple years of the survey can be complex and mistakes are easily made. As a researcher in criminology who frequently uses the CSEW and its predecessor, I have produced detailed Stata code to combine data from multiple survey years to support other researchers who also analyse the CSEW in Stata (or would like to start). I worked with the UK Data Service (UKDS) and the Office for National Statistics (ONS) to share the code and develop guidance for its use.
With this code, you can specify what you need, namely, which years of the Crime Survey you want to merge and if you want the adolescent and young adult panels, the bolt-on datasets that provide uncapped codes, and/or if you want to use the ethnic minority booster samples. As a result, the code can be easily tailored for each researcher’s needs.
By combining multiple survey sweeps, analysts can examine temporal trends. A combined file also enables analysts to look at low prevalence offences, population groups, or consequences, that do not have a high enough frequency in a single year.
Two examples are given below on how this integrated dataset provides new and exciting opportunities.
Example 1: Revealing gender and age differences in trends in experiencing violence
We used our integrated crime survey dataset to examine temporal trends in different types of violence, and whether these varied by gender and age.
After a rise in violent crime in the 1980s, there was a decade of steady decline followed by a decade of stability (blue line, Figure 1a). However, for other crimes, which can also be considered violent, the patterns observed are different. After a short period of decline in the 1990s, sexual violence against women remained relatively stable until around 2010 when it began to increase, reaching the 20 years high by 2020. Additionally, there has been a sharp rise in threats reported by women in the last 5 years of data, making threats almost as prevalent as at its peak in the late 1990s.
The trends in violent crime for men follow a broadly similar pattern as for women, but at a higher rate. Unlike women, however, men did not experience an increase in threats in the more recent period.
Figure 1. Prevalence of violence by type of violence and gender, 1982 to 2020
a) Proportion of women experiencing violence by type of violence
b) Proportion of men experiencing violence by type of violence
Source: Authors’ analysis using CSEW/BCS data from 1982 to 2019/2020.
Notes: Weighted proportions. Violent crime includes the following offences: Serious wounding, other wounding, common assault, attempted assault, serious wounding with sexual motive, other wounding with sexual motive. Sexual violence includes the following offences: rape, attempted rape and indecent assault. Due to low frequencies, sexual violence is not reported here for men.
Figure 2 reveals that there has been major change in the age profile of victims over the past 40 years. 16- to 19-year-olds were almost 3 times as likely to become a victim of violence as people aged 30 to 39 in the mid-1990s. But violence against this group has declined rapidly since then: while they continue to be the group that is most likely to be victim of violence with 7.2% annual victimization in 2020, this used to be over 28% in the mid-1990s. While risk of violence has declined for all the ages under 40, the shift has been the largest for the younger groups.
Relatively few people over 50 become victims of violence compared to younger age groups in each time period. However, closer inspection reveals there is a significant increase in the risks of violence among the older age groups (60-69 and 70 and older) since the late 1990s, and particularly since 2015.
Overall, the age profile of victims has shifted massively over the decades, there is now much less variation in rates between age groups.
Figure 2 Prevalence of violence (including violent crime, threats, robberies, and sexual violence) by age group, 1982 to 2020.
Source: Authors’ analysis using CSEW/BCS data from 1982 to 2019/2020.
Example 2: Investigating smaller groups: Differences in wellbeing impact between intimate partner perpetrators
Our integrated crime survey dataset allows for the study of minority groups that are relatively small or forms of violence that are not often reported.
For example, only by combining twenty years of the crime survey (2001 to 2020) do we have sufficient sample size to study the impact physical intimate partner violence has on wellbeing and health, and how it differs between various types of intimate partner perpetrator.
Firstly, it is important to note that physical violence by any type of intimate partner has a higher risk of high emotional impact (Figure 3a) and a higher risk of injury (Figure 3b) than violence by other types of perpetrators.
Figure 3a below shows that the emotional impact reported by female victims is higher when the violence was committed by a current or former spouse/partner compared to if it was done by a current or former boy/girlfriend. Women were more likely to say they were ‘very much’ affected by the violence when it was committed by a current or former spouse/partner. It could be that the proximity of spousal relationships, which are often cohabitating, and their average longer duration account for some of the greater report impact. However, in contrast to emotional impact, figure 3b (below) shows that women are more likely to get an injury(ies) by violence by current spouses than by former spouses.
Overall, this study highlighted that physical violence by an intimate partner has a more severe wellbeing and health impact than violence by others, but also the need to differentiate intimate partner violence and abuse by not only the type of violence/abuse but also the type of intimate partner.
Figure 3 Estimated emotional wellbeing and risk of injuries for women following physical intimate partner violence, differences between intimate partner perpetrators.
a) Respondent’s reported emotional impact (showing the highest category).
b) Respondent’s reported physical health impact (showing the risk of injury)
Source: Authors’ analysis using CSEW/BCS data from 2001 to 2019/2020.
Notes: Respondent’s self-assessed emotional impact measured in four categories: not impacted, little impact, quite a lot, very much impacted. Respondent’s self-assessed risk of injuries is measured in three categories: no force was used, force was used but no injury was sustained, force was used that led to an injury. Figures are based on average marginal effects following ordered logit models controlling for key (socio)demographics. Significance was tested in additional models.
What the merger code does and doesn’t do
The Stata code enables users to merge the raw CSEW/BCS datasets. Consequently, at the moment, this code does not harmonize variables that change (slightly) over different years. Considering the measurement of many variables changes over the years, the users of this combined file need to make their own decisions on what operationalisations work best for their research and for the years they use.
Most of the time new variable names are used when a new measurement is used. However, for a few variables, different measurements seem to be used in different years, but they have the same variable name (for instance for household income variables such as tothhin2). In the current code, these variables are treated as being the same. Therefore, users need to carefully check the variables that they use for the relevant years.
Next, this code does not work in the secure researcher environment as provided by UKDS or ONS because the datasets in these environments have different names and the structure of the folders is different.
Overall, the merger code will save researchers precious time in combining the surveys that they want to use. As we have shown here, combining survey sweeps can benefit the study of trends in victimisation. The code can also be used for studying groups or crimes that are too rare to study using only a single sweep, therefore, this code may provide an incentive for studying marginalised groups and specific crimes, contributing to new insights into victimisation.
Citation for merged code
Blom, Niels (2023). Code for Merging Waves of the Crime Survey of England and Wales and the British Crime Survey, 1982-2020. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-856494
Examples in this blog are from
Blom, N., Obolenskaya, P., Phoenix, J., and Pullerits M. (2023, September 11-13). Differentiating intimate partner violence by perpetrator relationship type. Types of crimes committed and consequences for victims’ health and wellbeing by different types of intimate partner perpetrators [Conference Presentation]. European Conference on Domestic Violence, Reykjavik, Iceland.
Obolenskaya, P. & Blom, N. (2023, September 6-9). The rise, fall and stall of violence in England and Wales: how have risks of violence changed for different groups? [Conference Presentation]. EuroCrim 23rd Annual Conference of the European Society of Criminology, Florence, Italy.
Data reference
Office for National Statistics. Crime Survey for England and Wales, 2001-2002 to 2019-2020 and British Crime Survey 1982 to 2001 [data collections]. UK Data Service SN: 8812, 8608, 8464, 8321, 8140, 7889, 7619, 7422, 7252, 6937, 6627, 6367, 6066, 5755, 5543, 5347, 5324, 5059, 4787.
