Violence, Health and Society: VISION
Lead Research Organisation:
City, University of London
Department Name: School of Social Sciences
Abstract
Violence causes harms to health. The harms to mental health can be more long-lasting than the immediate harms to physical health and have consequences that reverberate through a person's life impacting on their functioning in society. Reducing such 'upstream' determinants of poor mental health would significantly improve the health of the population. This would reduce health inequalities since being a victim of violence is more prevalent among those who are already disadvantaged.
The Consortium would investigate the effectiveness of interventions to reduce violence and, thus, reduce health inequalities. Within the field of violence, we have special interest in domestic and sexual violence because these are significant causes of inequalities in mental health, which have been relatively neglected in the scientific and statistical evidence base. We address how to mainstream these issues across multiple sectors rather than seeing them as only of specialised concern.
Multiple institutions are relevant to preventing violence. They include not only health services, but also criminal law enforcement (most violence is a crime), civil law (e.g. domestic protection orders), specialised services (Third Sector organisations that help victim/survivors of violence), and governmental bodies concerned with law, policy and data quality. The connections between violence and ill health are complicated since they are mediated by many of these institutions. Identifying these connections would aid the development of more effective interventions while a complex systems analysis captures the adaptive behaviour between these systems.
The data needed to assess the effectiveness and cost-effectiveness of interventions is currently weak. This is partly because each specialised academic discipline and profession has a different way of measuring violence, which makes cooperation across these differences difficult. Not only do we need harmonised core metrics for the evaluation of interventions and cross-sector cost-benefit comparisons, we also need to adapt and extend our metrics to capture newly identified forms of abuse such as that facilitated by technology. The Consortium aims to improve the measurement framework and data availability to aid the evaluation of interventions. This is premised on cooperation between academics and practitioners. The project seeks to identify profiles of persons and incidents exposed to violence and link data from multiple services and surveys. We would assist services to make their own data more useable and more available. This involves care and attention to issues of data protection and the development of bespoke agreements on data sharing that respect communities that generate data.
We would unlock the potential in multiple data sources rather than collect new data. These datasets include major national surveys such as the Adult Psychiatric Morbidity Survey, and the Crime Survey for England and Wales, and also administrative data sets from professions and practitioners, including the police, solicitors, health and specialised services. These datasets will be linked in a new integrated dataset and provide an evidence base upon which a cost-benefit framework and risk assessment tools can be developed.
With the linked data and new tools, we would assess key interventions. These are interventions at the level of institutions and systems. Our focus is the prevention of violence in the population rather than the treatment of trauma in individuals. The Consortium seeks to mainstream evidence of the significance of violence for health in policy making. We would engage with decision-makers concerned with the commissioning of services and policy makers concerned with priorities for public expenditure, as well as wider publics.
The aim is to reduce the harm to health, especially mental health, by identifying the most effective and cost-effective interventions to reduce violence in the population.
The Consortium would investigate the effectiveness of interventions to reduce violence and, thus, reduce health inequalities. Within the field of violence, we have special interest in domestic and sexual violence because these are significant causes of inequalities in mental health, which have been relatively neglected in the scientific and statistical evidence base. We address how to mainstream these issues across multiple sectors rather than seeing them as only of specialised concern.
Multiple institutions are relevant to preventing violence. They include not only health services, but also criminal law enforcement (most violence is a crime), civil law (e.g. domestic protection orders), specialised services (Third Sector organisations that help victim/survivors of violence), and governmental bodies concerned with law, policy and data quality. The connections between violence and ill health are complicated since they are mediated by many of these institutions. Identifying these connections would aid the development of more effective interventions while a complex systems analysis captures the adaptive behaviour between these systems.
The data needed to assess the effectiveness and cost-effectiveness of interventions is currently weak. This is partly because each specialised academic discipline and profession has a different way of measuring violence, which makes cooperation across these differences difficult. Not only do we need harmonised core metrics for the evaluation of interventions and cross-sector cost-benefit comparisons, we also need to adapt and extend our metrics to capture newly identified forms of abuse such as that facilitated by technology. The Consortium aims to improve the measurement framework and data availability to aid the evaluation of interventions. This is premised on cooperation between academics and practitioners. The project seeks to identify profiles of persons and incidents exposed to violence and link data from multiple services and surveys. We would assist services to make their own data more useable and more available. This involves care and attention to issues of data protection and the development of bespoke agreements on data sharing that respect communities that generate data.
We would unlock the potential in multiple data sources rather than collect new data. These datasets include major national surveys such as the Adult Psychiatric Morbidity Survey, and the Crime Survey for England and Wales, and also administrative data sets from professions and practitioners, including the police, solicitors, health and specialised services. These datasets will be linked in a new integrated dataset and provide an evidence base upon which a cost-benefit framework and risk assessment tools can be developed.
With the linked data and new tools, we would assess key interventions. These are interventions at the level of institutions and systems. Our focus is the prevention of violence in the population rather than the treatment of trauma in individuals. The Consortium seeks to mainstream evidence of the significance of violence for health in policy making. We would engage with decision-makers concerned with the commissioning of services and policy makers concerned with priorities for public expenditure, as well as wider publics.
The aim is to reduce the harm to health, especially mental health, by identifying the most effective and cost-effective interventions to reduce violence in the population.
Technical Summary
The vision underlying the Consortium on 'Violence, Health and Society' is that improving the knowledge base on violence and using this knowledge to inform changes to policy and practice will improve population health and reduce health inequalities. It will do so by acting on 'upstream' harms to health caused by violence. Research on such interventions is developing but is held back by weak theory and weak data. Theory is weak because it is often focused on individuals rather than on the system level. We will develop systems analysis using complexity theory that allows consideration of feedback loops that generate wicked problems and perverse outcomes. We will embed questions about the significance of multiple intersecting inequalities including gender and ethnicity into the theory underpinning the systems framework. Data is weak because, collected by multiple agencies for their own purposes, it is fragmented and incommensurable. We will work with data providers to develop survey and administrative data in health, justice and specialised services and translate it into our shared measurement framework. We will curate existing datasets rather than collect new data. We will use natural language processing to turn free-text narratives into quantitative data. We will integrate data using probabilistic individual profiles, which offers a powerful new route to data linkage that avoids the dangers of identifying real people. We will interrogate our newly improved data with questions about the nature of the causal pathways connecting violence, health and society to identify promising sites of intervention. We will develop cost-benefit analysis and evaluate interventions, using findings to build the theory of change. With our partners in health, justice, specialised services and government, we will seek to embed the new measurement in practice, to enable evidence-based feedback on developments to reduce violence and thereby improve health and reduce health inequalities.
Publications
Adisa O
(2023)
Community mental health through a complex systems lens.
in The Lancet. Public health
Glebov OO
(2023)
Antidepressant drug prescription and incidence of COVID-19 in mental health outpatients: a retrospective cohort study.
in BMC medicine
Dheensa S
(2023)
Healthcare Professionals' Own Experiences of Domestic Violence and Abuse: A Meta-Analysis of Prevalence and Systematic Review of Risk Markers and Consequences.
in Trauma, violence & abuse
Innes A
(2023)
Accounting for inequalities: divided selves and divided states in International Relations
in European Journal of International Relations
Mueller C
(2023)
Beyond confusion: Embedding psychiatry in delirium research and clinical practice.
in Acta psychiatrica Scandinavica
Chaturvedi J
(2023)
Development of a Corpus Annotated With Mentions of Pain in Mental Health Records: Natural Language Processing Approach.
in JMIR formative research
Ashdown-Franks G
(2023)
"Triggered by the sound of other runners": An exploration of parkrun mentions in mental health hospital records in the UK
in Mental Health and Physical Activity
Li L
(2023)
Characterizing the Differences in Descriptions of Violence on Reddit During the COVID-19 Pandemic.
in Journal of interpersonal violence
Kadra-Scalzo G
(2023)
Adverse outcomes associated with recorded victimization in mental health electronic records during the first UK COVID-19 lockdown.
in Social psychiatry and psychiatric epidemiology
Moffa G
(2023)
Sexual abuse and psychotic phenomena: a directed acyclic graph analysis of affective symptoms using English national psychiatric survey data.
in Psychological medicine
Maria Tanczer L
(2023)
Technology and Domestic and Family Violence - Victimisation, Perpetration and Responses
Chang CK
(2023)
Life expectancy, mortality risks and cause of death in patients with serious mental illness in South East London: a comparison between 2008-2012 and 2013-2017.
in Psychological medicine
Spinazzola E
(2023)
The effect of the COVID-19 pandemic on the treated incidence of psychotic disorders in South London.
in Psychiatry research
Cook E
(2023)
Parallels in Practice: Applying Principles of Research Integrity and Ethics in Domestic Violence Fatality Review (DVFR)
in Journal of Family Violence
Yorganci E
(2023)
Survival and critical care use among people with dementia in a large English cohort.
in Age and ageing
Knight R
(2023)
Borrowing strength from clinical trials in analysing longitudinal data from a treated cohort: investigating the effectiveness of acetylcholinesterase inhibitors in the management of dementia.
in International journal of epidemiology
Heslin M
(2023)
Prevalence of HIV in mental health service users: a retrospective cohort study.
in BMJ open
Straw I
(2023)
Safeguarding patients from technology-facilitated abuse in clinical settings: A narrative review.
in PLOS digital health
Forbes C
(2023)
A survey and stakeholder consultation of Independent Domestic Violence Advisor (IDVA) programmes in English maternity services.
in BMC pregnancy and childbirth
Dixon S
(2023)
General practice wide adaptations to support patients affected by DVA during the COVID-19 pandemic: a rapid qualitative study.
in BMC primary care
Chaturvedi J
(2023)
Development of a Knowledge Graph Embeddings Model for Pain.
in AMIA ... Annual Symposium proceedings. AMIA Symposium
Pinto Da Costa M
(2023)
Investigating time-dependent COVID-19 pandemic mental health data: Challenges and opportunities of using panel data analysis.
in PLoS medicine
Bhavsar V
(2023)
Intimate partner violence perpetration and mental health service use in England: analysis of nationally representative survey data.
in BJPsych open
Laurell A
(2024)
Estimating demand for potential disease-modifying therapies for Alzheimer's disease in the UK
in The British Journal of Psychiatry
Das-Munshi J
(2024)
Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study - ADDENDUM.
in The British journal of psychiatry : the journal of mental science
Stewart R
(2024)
Natural language processing - relevance to patient outcomes and real-world evidence.
in Expert review of pharmacoeconomics & outcomes research
Bellis M
(2024)
The Commercial Determinants of Violence: Identifying Opportunities for Violence Prevention through a Public Health-Based Framework Analysis
in International Journal of Environmental Research and Public Health
Chaturvedi J
(2024)
Identifying Mentions of Pain in Mental Health Records Text: A Natural Language Processing Approach.
in Studies in health technology and informatics
Downes L
(2024)
COVID-19 adaptations to a training and support programme to improve primary care response to domestic abuse: a mixed methods rapid study.
in BMC primary care
Fadeeva A
(2024)
Using Primary Care and Emergency Department Datasets for Researching Violence Victimisation in the UK: A Methodological Review of Four Sources
in Social Sciences