The role of NGO administrative data in understanding the impact of COVID-19 on survivors of domestic abuse

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  • 1 Women’s Aid Federation of England, , United Kingdom and University of London, , UK
  • | 2 Women’s Aid Federation of England, , UK
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COVID-19 quickly changed the context of domestic abuse in England. Within weeks of the first COVID-19 related death, the country was in lockdown. A quick response was essential for understanding the needs of survivors. With limited time to establish new data collection mechanisms, the role of administrative data was central in shaping the response by the Women’s Aid Federation of England. This article explores the opportunities and challenges of using administrative data to understand and respond to the impact of COVID-19 on survivors of domestic abuse in England, using analysis by Women’s Aid of administrative data as a case study. The article discusses the challenges, such as the complexity of analysing a longitudinal administrative dataset, and the need for increased skills and capacity within the NGO research environment. We also reflect on ethical considerations in light of the context of frontline workers responding to the pandemic, the opportunities for collaboration with other sector partners and academics and the benefits of being able to undertake reactive analysis to inform policy. The article concludes that our access to administrative data bolstered our ability to respond expediently to the pandemic, and achieve the long-term benefits of the partnerships that we built during this time.

Abstract

COVID-19 quickly changed the context of domestic abuse in England. Within weeks of the first COVID-19 related death, the country was in lockdown. A quick response was essential for understanding the needs of survivors. With limited time to establish new data collection mechanisms, the role of administrative data was central in shaping the response by the Women’s Aid Federation of England. This article explores the opportunities and challenges of using administrative data to understand and respond to the impact of COVID-19 on survivors of domestic abuse in England, using analysis by Women’s Aid of administrative data as a case study. The article discusses the challenges, such as the complexity of analysing a longitudinal administrative dataset, and the need for increased skills and capacity within the NGO research environment. We also reflect on ethical considerations in light of the context of frontline workers responding to the pandemic, the opportunities for collaboration with other sector partners and academics and the benefits of being able to undertake reactive analysis to inform policy. The article concludes that our access to administrative data bolstered our ability to respond expediently to the pandemic, and achieve the long-term benefits of the partnerships that we built during this time.

Key messages

  • Administrative data offered Women’s Aid a timely and ethical approach to understanding the impact of the COVID-19 pandemic with minimal impact on survivors or the services that support them.

  • The nature of administrative data creates unique challenges for researchers as well as opportunities for relevant, impactful research.

  • More resources, collaboration and research are needed to understand administrative data sources held by NGOs.

Introduction

Administrative data are collected through routine operations rather than originating for research purposes (Penner and Dodge, 2019; Kendall, 2020). Within the field of tackling violence against women and girls (VAWG) in England, administrative data are produced by statutory organisations, such as the police and social services, and violence against women service providers. Administrative data collected by service providers are most commonly recorded by staff to support their day-to-day work and meet contractual obligations to their funders and commissioners. Administrative data are often used to provide insight into the demand for services, service use or quality of services, helping those services to provide an efficient service and supporting decisions on resource allocation (Kendall, 2020). When used effectively, they can provide rich findings to ensure an evidence-based approach to practice and policy in response to violence against women. In 2017, the Commission on the Status of Women (CSW), recognising its value, called on member states to improve their use of administrative data (United Nations Women, 2013). In the same year, in England and Wales, the Office of National Statistics (ONS) first published administrative data from violence against women service providers with the aim of ‘bringing together statistics to enable more thorough analysis of how domestic abuse is dealt with at the local level’ (ONS, 2017a).

In 2020, the COVID-19 pandemic led to a rapid change in patterns of violence against women and the service response (Women’s Aid, 2020). The unprecedented speed with which services had to respond, along with the clear and considerable impact on victim-survivors1 of domestic abuse, necessitated a quick response. With limited time to establish new data collection mechanisms, the role of administrative data was central in shaping Women’s Aid Federation of England’s (hereafter, ‘Women’s Aid’) response.

This article explores the opportunities and challenges of using administrative data to understand and respond to the impact of COVID-19 on survivors of domestic abuse in England. It uses Women’s Aid’s access to live administrative data as a case study to explore broader questions about the role of civil society’s administrative data in responding to COVID-19. It ends with a call for increased relationship building and collaboration between NGOs and academic institutions.

Women’s Aid’s administrative data and analysis during the COVID-19 pandemic

Women’s Aid holds two sources of administrative data. On Track is Women’s Aid’s case management and outcomes monitoring system that contains data on the experiences of over 120,000 women supported by local domestic abuse services across England. Routes to Support2 is the UK-wide database of VAWG services and refuge vacancies. It contains information on the availability of refuge spaces and the nature of service provision.

In response to the COVID-19 pandemic, Women’s Aid drew on these administrative data sources, alongside data from surveys of survivors and service providers. The analysis completed to date was limited to descriptive statistics, used to summarise key trends and findings. Some of the initial findings relating to March–July 2020 were published in A Perfect Storm (Women’s Aid, 2020). Other findings were not published but were shared directly with policymakers. Inferential analysis of Women’s Aid’s administrative datasets to understand the impact of the COVID-19 pandemic is being undertaken in partnership with academic institutes, findings from which will be published soon.

Challenges and opportunities of administrative data

A safe and ethical sample of survivors

Many survivors experienced an increase in the severity of abuse and reduced avenues for escape during the COVID-19 lockdowns (Williamson et al, 2020a; Women’s Aid, 2020). Needless to say, data collection should not put survivors at risk of further harm. Administrative data collected by domestic abuse services offer one of the safest options for data collection from survivors: not putting the survivor at risk of physical harm, but equally important, not subjecting them to any emotional distress or re-traumatisation.

Women’s Aid’s administrative data are collected via frontline staff in domestic abuse services. Accordingly, we know that the survivors in our sample are already in contact with expert professionals who can offer safety planning, emotional support and anything else the survivor may need. This offers a key advantage of using administrative data over alternative data collection methods such as online surveys. Surveys can reach survivors who are not accessing support and offer anonymity in their responses, meaning that they can freely open up about their experiences. While every effort is made to ensure survivors responding to surveys are aware of available support (for example, by including helpline numbers in the introduction to the survey), it is not always possible to follow up or provide direct support. Providing follow-up support can be particularly difficult when surveys are circulated online and reach survivors in different countries. Particular challenges arise when survivors mention that they need support in their survey response, which may not be read until weeks later.

Protecting the privacy and confidentiality of personal information is critical in ensuring safe and ethical data collection, where a breach of confidentiality has the potential to put survivors at risk of further violence and discourage them from accessing support services (Bowstead, 2019). It is necessary to take steps to ensure the safe processing and analysis of administrative data. The ONS (2017b) outlines ‘five safes’ which guide their work and ensure that data is de-identified and used safely. They consider who is completing the research, the impact of the research, security of data and the anonymity of data (ONS, 2017b). A complete discussion of the considerations in anonymising data is beyond the scope of this article; however, the Administrative Data Research UK have lots of valuable resources. The importance of taking steps to ensure safe use of data was even more acute during the COVID-19 pandemic. Many more survivors spent more time at home with their abusers due to measures such as lockdown and working from home (Gregory and Williamson, 2021). Lots of abusers used these lockdown restrictions to exert control over victim-survivors, including increased monitoring and surveillance of behaviours and online activity, making privacy and confidentiality a more pressing issue and the role of administrative data even more valuable (Women’s Aid, 2020).

In this instance, administrative data offered access to a large sample. Women’s Aid’s Routes to Support dataset contains detailed information on over 500 VAWG services and detail on refuge vacancies that become available across the UK. Women’s Aid’s On Track dataset is used by over 85 organisations covering all regions of England and contains over 120,000 survivor journeys through support. Nonetheless, as Bowstead (2019) emphasises, administrative datasets are generated for particular purposes and therefore ‘provide only a partial picture of the complexity of women’s help-seeking due to domestic violence’ (p. 21). The administrative data we collect serves to provide information to funders and allow organisations to manage their caseloads, which has an impact on the nature of the collected data. Furthermore, Women’s Aid’s administrative data are taken from a restricted group of organisations.

For the Routes to Support dataset, the inclusion criteria state that organisations must provide evidence that they are a dedicated provider of domestic abuse or VAWG services and must be non-profit. Accordingly, the sample does not include all organisations that offer support to victim-survivors. Similarly, organisations using On Track are a self-selected group and are not representative.

Unlike many administrative datasets (Penner and Dodge, 2019: 12), inclusion in the On Track dataset is, however, dependent on survivors’ consent. As Kendall (2020) points out, ‘Requiring written informed consent for inclusion in administrative registry-based databases can result in disproportionate refusal of consent among more socially disadvantaged populations’ (p. 32). As a result, the On Track dataset risks sharing the two effects Kendall observes, first, that assumptions based on a potentially biased dataset may be incorrect and second, that they may not recognise the needs of disadvantaged populations. As many services started remotely supporting survivors due to COVID-19, the mechanisms for gathering consent were forced to change because gathering written consent was no longer feasible.

Utilising established data infrastructure

Within days of the first national lockdown, Women’s Aid was approached by government departments seeking data to understand how COVID-19 was affecting survivors and services. Government departments were seeking information on changes to the prevalence and severity of domestic abuse, changes to demand for services and the impact of COVID-19 on service providers. Women’s Aid was able to provide government departments with weekly figures on the availability of refuge vacancies, disaggregated by region. Analysis of these figures showed that during the first national lockdown (from 23 March to 31 May 2020), there was a 40.6 per cent reduction in the number of vacancies posted by refuge services to the Routes to Support database from the same period in 2019 (Women’s Aid, 2020).

With an established research and evaluation team and data infrastructure already in place to collect and analyse information from both internal, direct services and domestic abuse services across England, Women’s Aid was able to understand aspects of the impact of the COVID-19 pandemic as it happened. The prior commitment and substantial investment in establishing this infrastructure were crucial. However, the capacity and resources to establish data infrastructure are rare within the domestic abuse support sector. This particularly affects specialist services run by and for minoritised people, who are disproportionately underfunded (Banga and Roy, 2020) and thus less likely to have this infrastructure in place.

The analysis of administrative data held by NGOs such as Women’s Aid can have natural links to policmakers through the policy focus of their work. Where data are gathered through resources that receive funding from government departments, as with Routes to Support, there can be additional links and ongoing awareness of the value of administrative data analysis at a government level. These ongoing relationships can make it easier for NGOs to work with decision-makers to ensure that findings are used accurately and effectively to influence policy. It also allows NGOs to provide evidence on an ongoing basis to help contribute to evidence-based decision making at a national policy level.

Our ability to analyse administrative data sources was crucial at the start of the COVID-19 pandemic to raise awareness through media coverage and provide the insight needed to create fast policy change.

As mentioned earlier, Women’s Aid analysis revealed the falling levels of refuge vacancies at the start of the pandemic. Feedback from government sources with whom the analysis was shared was that these data played a vital role in the fast introduction of emergency funding for refuge services and the creation of additional emergency spaces. Our analysis of administrative data was then crucial in monitoring the impact of this funding and showed an increase of 361 refuge spaces between May and November 2020, a large part of these due to this emergency funding (Women’s Aid, 2021a).

Furthermore, the COVID-19 pandemic placed tremendous stress on an already overstretched sector, with many services seeing increased demand during the first national lockdown alongside decreased space availability for a wide range of reasons (Banga and Roy, 2020; Women’s Aid, 2020a). The COVID-19 pandemic exacerbated existing structural and racialised inequalities, affecting Black and minoritised survivors and staff (Banga and Roy, 2020). Analysis of administrative data offered an opportunity to understand the impacts of COVID-19 without further burdening staff or negatively affecting the time they had to support survivors.

Longitudinal data

The rapidly changing context of COVID-19 meant real-time, longitudinal data were crucial. Women’s Aid’s administrative datasets allowed us to monitor the impact of the easing of restrictions and subsequent local and national lockdowns. Through weekly snapshots of the number of times a space in a refuge became vacant and the resulting vacancy was listed on Routes to Support, we monitored the impact of emergency funding pots on the number of spaces becoming available. The reduction in vacancies becoming available was attributed by providers to a range of factors (Women’s Aid, 2020), and could not be addressed by increasing the number of spaces held by refuge providers alone. From September 2020 snapshots of data showed the number of refuge vacancies listed on Routes to Support return to similar levels to 2019, which, while by no means indicating sufficient availability to meet demand, could indicate the success of these funding pots in addressing the additional, temporary lack of availability (Women’s Aid, 2020).

One challenge we faced was responding to such a rapidly changing environment and adapting our databases to ensure that the administrative data we collected included relevant information. In collaboration with representatives from domestic abuse services, additional fields were added to our On Track database to capture specific information about COVID, such as whether the survivor had had COVID, been vaccinated, any changes to their experiences of abuse, and other impacts such as delays to court cases.

Longitudinal analysis of administrative data poses particular challenges. The mechanisms of data collection and the structure of the datasets mean that some fields may be overwritten as circumstances change and new information is recorded. For Women’s Aid, this occurred where we had prioritised the need for simplicity in the systems and database collecting the information. Further complexities in Women’s Aid’s administrative datasets arise because of changes in the sample: services open, close and expand, meaning it is challenging to do repeated detailed cross-sectional analysis over many years. There is scope for improvements in Women’s Aid use of administrative data through joining up of datasets in the analysis. This would allow data from Routes to Support to provide the context and detail on the sample of services contributing data to On Track.

Data quality

Administrative data carry a unique set of challenges around data quality compared to data gathered primarily for research purposes. For example, the datasets were often primarily designed to monitor service provision and may not include the best variables for research purposes (Bowstead, 2019). As Kendall (2020) explains, ‘the quality of administrative data is only as good as the human and information system resources that are collecting, entering, analysing and reporting on these data’ (p. 13). One challenge for Women’s Aid was balancing the need for quality data with the needs of survivors accessing services.

A key strength of Women’s Aid’s data quality is that many of the data are input by frontline staff who have built rapport with the survivors in the sample. As part of a project funded by London Councils to support commissioning of services in London, Women’s Aid’s Routes to Support dataset collects information on the demographics and needs of survivors when they enter or leave a London-based refuge. Staff at refuge services are asked to record certain information on women entering or leaving a refuge including demographic information relating to protected characteristics3 and additional support needs. Unpublished data analysis shows higher proportions of these data recorded in the sample of women leaving a refuge than those entering a refuge. This suggests that the relationship with the support worker plays a crucial role in data collection, although there remains tension in collecting any demographic data due to the nature of asking people to identify in a pre-defined list of categories specific to locations and time.

Nonetheless, Women’s Aid’s administrative data still include data errors and inconsistencies, as hundreds of frontline staff generated the data. These staff may have a different understanding of questions or definitions, have received various levels of training around data entry, and are time-poor. As Kendall explains, ‘A challenge related to administrative data is that the service providers who create administrative records are focused on doing their jobs, not on data quality, and are often over-worked’ (Kendall, 2020). Inconsistencies in the data also arise because of different processes between organisations and services. For example, some organisations triage their referrals, streaming through one point of entry, while others have more dispersed referral pathways, going directly to the range of services. Naturally, this affects the data that are collected.

Capacity, skills and partnerships

A key strength of Women’s Aid’s administrative data is their integration with the domestic abuse support sector. This provided the connections with survivors and frontline staff through which the data infrastructure was designed. For example, during the design and pilot of On Track, survivors were asked what is important to them and how they felt when being asked questions. As a result of their feedback, additional questions were added which focused on their resilience and wellbeing in recognition that these ‘soft’ outcomes were equally important as more traditional outcomes such as access to housing.

Furthermore, the analysis was done by women who specialise in the issues and nuances of research on domestic abuse and had a strong understanding of the processes of domestic abuse support services. Women’s Aid found that there is often a ‘time lag’ before staff using On Track enter complete information onto the system. Accordingly, a three-month period from the end date of the reporting period allows time for input and considerably increases the quality of data available for that period.

The connections with survivors and frontline staff allow administrative data to be interpreted in context. For example, when Women’s Aid began looking at administrative data in response to COVID-19, testimony and feedback from the survivors and service providers who access their services daily shaped the research questions and provided context for understanding the findings. For example, rather than only reporting a decrease in refuge vacancy availability, Women’s Aid indicated the reasons for this. Such knowledge allowed Women’s Aid to shape the research and survey questions used in their dedicated research into the impact of COVID-19 on service providers (Women’s Aid, 2020).

Where an NGO does not have the resources to analyse large volumes of data, this can form a barrier to making the best use of administrative data. This was exacerbated by COVID-19 as, like everyone, Women’s Aid’s Research and Evaluation team had to adapt to home-working, living under lockdown and for many of the women-only workforce, home-schooling responsibilities. Given the nature of the work support staff at domestic abuse services do, the potential for vicarious trauma may increase due to this impact on work/life balance and providers reported negative impacts on anxiety and mental health for their staff (Women’s Aid, 2020). This is true also for staff at NGOs including Women’s Aid working on this topic. This severely curtailed the depth and scope of the analysis. Further limitations arose due to a lack of access to analytical software and limitations in advanced research skills.

Existing partnerships with academics have proved invaluable in supporting Women’s Aid’s research during COVID-19. Pro-bono advice and guidance led to amendments to some data collection methods and improved data quality, and access to bespoke training built the team’s data analysis skills. Building partnerships across those researching VAWG is essential to progressing our understanding of survivors accessing support services. However, these relationships take time to develop, particularly given the context of competitive funding shaping the women’s sector (Women’s Aid, 2021b). The fragile funding landscape and the potential to cause further harm to survivors through poor-quality research makes trust between partners a prerequisite to fruitful collaborative research. This challenge is not exclusive to the field of VAWG in England, as Penner and Dodge (2019: 14) observe more widely: ‘Data-sharing can be difficult in contexts marked by suspicion and mistrust, and larger conversations around privacy remain important’.

Additional funding pots made available due to the pandemic have created opportunities to collaborate and form ongoing partnerships. The Research Integrity Framework on Domestic Violence and Abuse, published in November 2020, brought together the knowledge and experience of academic and NGO partners, creating a helpful framework for future collaboration and best practice in researching domestic abuse (Williamson et al, 2020b). The framework recognises the value of partnerships, emphasises the need for these to consider power relations and prioritise research by and for minoritised people and smaller organisations. It also acknowledges the responsibility of generating ethical research that represents the voices of victim-survivors. The Research Integrity Framework is available online for others to take and adapt to their countries.

Conclusion

Women’s Aid’s analysis of their administrative data offered an opportunity to provide timely insight into the impact of the COVID-19 pandemic on victim-survivors of domestic abuse and the services that support them. In sharing this experience, we hope to start a discussion about the role of administrative data in responding to crises and other service providers’ use of administrative data.

Administrative data offer one of the safest options for data collection from survivors who are accessing services. The survivors in the datasets used by Women’s Aid were already in contact with the professionals who can support them. The prior investment in establishing data infrastructure was key to accessing and analysing administrative data. This allowed Women’s Aid to respond to the COVID-19 pandemic as it happened and provided the contacts to disseminate the findings among policymakers and maximise the impact of the research. For example, in the announcement of the second national lockdown, the Prime Minister explicitly mentioned that people fleeing domestic violence were exempt from the restrictions.

The longitudinal data offered by the administrative datasets allowed Women’s Aid to explore the impact of the pandemic by offering a baseline for comparison. Longitudinal analysis of administrative data poses particular challenges as fields may be overwritten and the sample changes. The primary purposes of Women’s Aid’s administrative datasets were to monitor service provision and support casework. Accordingly, they may not offer the optimal data for research purposes, although they do benefit from the relationship between the survivor and their frontline worker. A key strength of Women’s Aid’s administrative data is their integration with the domestic abuse support sector. This allows for the analysis to consider the processes of data collection in domestic abuse support services. Building partnerships across those researching VAWG is essential to progressing the use of administrative data.

Notes

1

We use the term victim-survivor here to acknowledge that the sample includes women who died and to reflect the different terms women use to describe themselves and the fact that there can be a journey from one to the other.

2

Run in partnership with Women’s Aid Federation of Northern Ireland, Scottish Women’s Aid and Welsh Women’s Aid.

3

Under the Equality Act 2010 it is against the law to discriminate against nine characteristics (age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, sexual orientation) known as protected characteristics.

Acknowledgements

The authors would like to thank Dr Janet Bowstead and Dr Sarika Seshadri for their support and guidance during the development of this article.

Conflict of interest

The authors declare that there is no conflict of interest.

References

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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Kendall, T. (2020) A Synthesis of Evidence on the Collection and Use of Administrative Data on Violence against Women: Background Paper for the Development of Global Guidance, New York: UN Women, https://www.unwomen.org/en/digital-library/publications/2020/02/background-paper-synthesis-of-evidence-on-collection-and-use-of-administrative-data-on-vaw.

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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Penner, A.M. and Dodge, K.A. (2019) Using administrative data for social science and policy, The Russell Sage Foundation Journal of the Social Sciences, 5(2): 118, doi: 10.7758/RSF.2019.5.2.01.

    • Search Google Scholar
    • Export Citation
  • United Nations Women (2013) UN Women (United Nations Entity for Gender Equality and the Empowerment of Women). 2013. Elimination of All Forms of Violence Against Women and Girls: 57th Commission on the Status of Women – Agreed Conclusions, New York: UN Women, https://www.unwomen.org/-/media/headquarters/attachments/sections/csw/57/csw57-agreedconclusions-a4-en.pdf?la=en&vs=700.

    • Search Google Scholar
    • Export Citation
  • Williamson, E., Lombard, N. and Brooks-Hay, O. (2020a) Domestic violence and abuse, coronavirus, and the media narrative, Journal of Gender-Based Violence, 4(2): 28994.

    • Search Google Scholar
    • Export Citation
  • Williamson, E. and Devaney, J. Women’s Aid, Welsh Women’s Aid, Scottish Women’s Aid, Women’s Aid Federation of Northern Ireland (2020b) Research Integrity Framework on Domestic Violence and Abuse, Bristol: Women’s Aid, https://www.womensaid.org.uk/wp-content/uploads/2020/11/Research-Integrity-Framework-RIF-on-Domestic-Violence-and-Abuse-DVA-November-2020.pdf.

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    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Women’s Aid (2021a) The Domestic Abuse Report 2021: The Annual Audit, Bristol: Women’s Aid.

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    • Search Google Scholar
    • Export Citation
  • 1 Women’s Aid Federation of England, , United Kingdom and University of London, , UK
  • | 2 Women’s Aid Federation of England, , UK

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