Violence, Health and Society
Lead Research Organisation:
City, University of London
Department Name: School of Social Sciences
Abstract
Violence causes harms to health, especially long-lasting harms to mental health. Mental health is significantly impacted by violence. These harms to mental health can be more long-lasting than the immediate harms to physical health. They have consequences that reverberate through a person's life impacting on their functioning in society, with still further consequences. Reducing such 'upstream' determinants of poor mental health would significantly improve the health of the population. Investigating the effectiveness of potential interventions to reduce exposure to violence is central to the proposal.
Within the field of violence, we have special interest in domestic and sexual violence because these are significant causes of inequalities in mental health. We address how to mainstream these issues across multiple sectors rather than seeing them as only of specialised concern. Our Consortium aims to mainstream violence prevention at higher and earlier stages than before.
Multiple institutions are relevant to preventing violence. They include not only health services, but also law enforcement (most violence is a crime), social services (especially important for child protection), 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 mental ill health are complicated since they are mediated by many social systems (institutions). Identifying these connections (causal pathways) would aid the development of more effective interventions.
The data needed to assess the 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 cross-sector cost-benefit comparisons, we also need to adapt and extend our metrics to capture the new forms of technology-facilitated abuse. The Consortium aims to improve the measurement framework and data availability to aid the cross-sector evaluation of interventions. It seeks to develop cooperation between academics and professionals as to how this is best done. After reaching agreement on how to proceed, we would develop the data needed to assess interventions. This involves developing cooperation between data providers, agreements on common categories, and making data more available. This involves care and attention to issues of data protection and the development of bespoke agreements on data sharing that respect the communities that generate data.
We would unlock the potential in multiple data sources with increased cooperation over a shared measurement framework. These data sets include major national surveys such as the Adult Psychiatric Morbidity Survey (national survey of mental health that includes information on experience of violence), and the Crime Survey for England and Wales (national survey that includes changes over time in violence and their consequences). They include administrative data sets from professions and practices, including the police, health and social services, specialised services and technology companies. We would locate data analysts of multiple data sets in the same space to facilitate technical cooperation between usually separate disciplines.
With the newly improved data, we would use academic, statistical, and practitioner knowledge and the resources of the Consortium to assess key interventions. These are interventions at the level of institutions and systems. We leave to others the issue of addressing the treatment of trauma in individuals already affected by violence. Our focus is the 'prevention' of violence in the population.
The aim is to reduce the harm to health, especially mental health, by identifying the most effective interventions to reduce violence in the population.
Within the field of violence, we have special interest in domestic and sexual violence because these are significant causes of inequalities in mental health. We address how to mainstream these issues across multiple sectors rather than seeing them as only of specialised concern. Our Consortium aims to mainstream violence prevention at higher and earlier stages than before.
Multiple institutions are relevant to preventing violence. They include not only health services, but also law enforcement (most violence is a crime), social services (especially important for child protection), 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 mental ill health are complicated since they are mediated by many social systems (institutions). Identifying these connections (causal pathways) would aid the development of more effective interventions.
The data needed to assess the 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 cross-sector cost-benefit comparisons, we also need to adapt and extend our metrics to capture the new forms of technology-facilitated abuse. The Consortium aims to improve the measurement framework and data availability to aid the cross-sector evaluation of interventions. It seeks to develop cooperation between academics and professionals as to how this is best done. After reaching agreement on how to proceed, we would develop the data needed to assess interventions. This involves developing cooperation between data providers, agreements on common categories, and making data more available. This involves care and attention to issues of data protection and the development of bespoke agreements on data sharing that respect the communities that generate data.
We would unlock the potential in multiple data sources with increased cooperation over a shared measurement framework. These data sets include major national surveys such as the Adult Psychiatric Morbidity Survey (national survey of mental health that includes information on experience of violence), and the Crime Survey for England and Wales (national survey that includes changes over time in violence and their consequences). They include administrative data sets from professions and practices, including the police, health and social services, specialised services and technology companies. We would locate data analysts of multiple data sets in the same space to facilitate technical cooperation between usually separate disciplines.
With the newly improved data, we would use academic, statistical, and practitioner knowledge and the resources of the Consortium to assess key interventions. These are interventions at the level of institutions and systems. We leave to others the issue of addressing the treatment of trauma in individuals already affected by violence. Our focus is the 'prevention' of violence in the population.
The aim is to reduce the harm to health, especially mental health, by identifying the most effective interventions to reduce violence in the population.
Technical Summary
Violence causes harms to health, especially long-lasting harms to mental health. Preventing 'upstream' determinants of poor mental health would significantly improve the health of the population. We have special interest in domestic and sexual violence because these are significant causes of inequalities in mental health. We intend to investigate the effectiveness of potential interventions to reduce the violence that harms mental health.
The focus is on the prevention of violence rather than the mitigation of its harms by the treatment of individuals. We will use complex systems analysis as part of building a theory of change. Multiple systems are relevant: law enforcement (most violence is a crime), social services (especially for child protection), specialised services (Third Sector organisations that help victim/survivors of violence), and governmental bodies (law, policy and data quality). The interactions between these institutions (systems) is rarely simple and direct; generating perverse outcomes and 'wicked problems'.
The data needed to evaluate interventions is currently weak. This is partly because each specialised academic discipline and profession has a different way of measuring violence. The Consortium aims to improve the measurement framework and data availability and to develop harmonised core metrics for cross-sector cost-benefit comparisons. Data sources include: Adult Psychiatric Morbidity Survey, the Crime Survey for England and Wales, administrative data from police, health, social services, specialised services and technology companies.
With the newly improved data, we would evaluate interventions that are at the level of institutions and systems and have potential for prevention.
This grant is funded by the UK Prevention Research Partnership (UKPRP) which is administered by the Medical Research Council on behalf of the UKPRP's 12 funding partners: British Heart Foundation; Cancer Research UK; Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Engineering and Physical Sciences Research Council; Economic and Social Research Council; Health and Social Care Research and Development Division, Welsh Government; Health and Social Care Public Health Agency, Northern Ireland; Medical Research Council; Natural Environment Research Council; National Institute for Health Research; The Health Foundation; The Wellcome Trust.
The focus is on the prevention of violence rather than the mitigation of its harms by the treatment of individuals. We will use complex systems analysis as part of building a theory of change. Multiple systems are relevant: law enforcement (most violence is a crime), social services (especially for child protection), specialised services (Third Sector organisations that help victim/survivors of violence), and governmental bodies (law, policy and data quality). The interactions between these institutions (systems) is rarely simple and direct; generating perverse outcomes and 'wicked problems'.
The data needed to evaluate interventions is currently weak. This is partly because each specialised academic discipline and profession has a different way of measuring violence. The Consortium aims to improve the measurement framework and data availability and to develop harmonised core metrics for cross-sector cost-benefit comparisons. Data sources include: Adult Psychiatric Morbidity Survey, the Crime Survey for England and Wales, administrative data from police, health, social services, specialised services and technology companies.
With the newly improved data, we would evaluate interventions that are at the level of institutions and systems and have potential for prevention.
This grant is funded by the UK Prevention Research Partnership (UKPRP) which is administered by the Medical Research Council on behalf of the UKPRP's 12 funding partners: British Heart Foundation; Cancer Research UK; Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Engineering and Physical Sciences Research Council; Economic and Social Research Council; Health and Social Care Research and Development Division, Welsh Government; Health and Social Care Public Health Agency, Northern Ireland; Medical Research Council; Natural Environment Research Council; National Institute for Health Research; The Health Foundation; The Wellcome Trust.
Organisations
Publications
Bhavsar V
(2020)
The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders.
in BJPsych open
Ashdown-Franks G
(2020)
Predictors of physical activity recording in routine mental healthcare
in Mental Health and Physical Activity
Widnall E
(2020)
User Perspectives of Mood-Monitoring Apps Available to Young People: Qualitative Content Analysis.
in JMIR mHealth and uHealth
Brunckhorst O
(2020)
Depression, anxiety, and suicidality in patients with prostate cancer: a systematic review and meta-analysis of observational studies
in Prostate Cancer and Prostatic Diseases
Carson L
(2020)
Multisite data linkage projects in mental health research.
in The lancet. Psychiatry
Stubbs B
(2020)
Risk of Hospitalized Falls and Hip Fractures in 22,103 Older Adults Receiving Mental Health Care vs 161,603 Controls: A Large Cohort Study.
in Journal of the American Medical Directors Association
Cross L
(2020)
Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group.
in International journal of population data science
Colling C
(2020)
Predicting high-cost care in a mental health setting.
in BJPsych open
Viani N
(2020)
Temporal information extraction from mental health records to identify duration of untreated psychosis.
in Journal of biomedical semantics
Bishara D
(2020)
The anticholinergic effect on cognition (AEC) scale-Associations with mortality, hospitalisation and cognitive decline following dementia diagnosis.
in International journal of geriatric psychiatry
Howes OD
(2020)
Aberrant Salience, Information Processing, and Dopaminergic Signaling in People at Clinical High Risk for Psychosis.
in Biological psychiatry
Stewart R
(2020)
Extent of disease at first cancer presentation and previous anxiety and depressive symptoms: the HUNT study.
in The British journal of psychiatry : the journal of mental science
Jayasinghe L
(2020)
Clinician-recalled quoted speech in electronic health records and risk of suicide attempt: a case-crossover study.
in BMJ open
Bishara D
(2020)
The anticholinergic effect on cognition (AEC) scale-Associations with mortality, hospitalisation and cognitive decline following dementia diagnosis.
in International journal of geriatric psychiatry
Carson LE
(2020)
Cohort profile: the eLIXIR Partnership-a maternity-child data linkage for life course research in South London, UK.
in BMJ open
Carson L
(2020)
Multisite data linkage projects in mental health research.
in The lancet. Psychiatry
Stewart R
(2020)
Applied natural language processing in mental health big data
in Neuropsychopharmacology
Iqbal E
(2020)
The side effect profile of Clozapine in real world data of three large mental health hospitals.
in PloS one
Bowie J
(2020)
A systematic review of tools used to assess body image, masculinity and self-esteem in men with prostate cancer.
in Psycho-oncology
Ive J
(2020)
Generation and evaluation of artificial mental health records for Natural Language Processing.
in NPJ digital medicine
Mansour H
(2020)
Severe mental illness diagnosis in English general hospitals 2006-2017: A registry linkage study
in PLOS Medicine
Mansour R
(2020)
Late-life depression in people from ethnic minority backgrounds: Differences in presentation and management.
in Journal of affective disorders
Vithayathil M
(2020)
Risk of acute pancreatitis among people with severe mental illness.
in Journal of affective disorders
Cliffe C
(2020)
Suicide attempts requiring hospitalization in patients with eating disorders: A retrospective cohort study.
in The International journal of eating disorders
Liang CS
(2021)
Mortality rates in Alzheimer's disease and non-Alzheimer's dementias: a systematic review and meta-analysis.
in The lancet. Healthy longevity
Yorganci E
(2021)
Quality indicators for dementia and older people nearing the end of life: A systematic review
in Journal of the American Geriatrics Society
Das-Munshi J
(2021)
Inequalities in glycemic management in people living with type 2 diabetes mellitus and severe mental illnesses: cohort study from the UK over 10 years.
in BMJ open diabetes research & care
Viani N
(2021)
A natural language processing approach for identifying temporal disease onset information from mental healthcare text.
in Scientific reports
Mueller C
(2021)
Antipsychotic use in dementia: the relationship between neuropsychiatric symptom profiles and adverse outcomes.
in European journal of epidemiology
Mascio A
(2021)
Cognitive Impairments in Schizophrenia: A Study in a Large Clinical Sample Using Natural Language Processing.
in Frontiers in digital health
Dutta R
(2021)
Temporal and diurnal variation in social media posts to a suicide support forum.
in BMC psychiatry
Wickersham A
(2021)
Educational attainment trajectories among children and adolescents with depression, and the role of sociodemographic characteristics: longitudinal data-linkage study.
in The British journal of psychiatry : the journal of mental science
Al-Harrasi AM
(2021)
Motor signs in Alzheimer's disease and vascular dementia: Detection through natural language processing, co-morbid features and relationship to adverse outcomes.
in Experimental gerontology
Kung B
(2021)
Identifying subtypes of depression in clinician-annotated text: a retrospective cohort study.
in Scientific reports
Sommerlad A
(2021)
Effect of trazodone on cognitive decline in people with dementia: Cohort study using UK routinely collected data
in International Journal of Geriatric Psychiatry
Ford E
(2021)
The Potential of Research Drawing on Clinical Free Text to Bring Benefits to Patients in the United Kingdom: A Systematic Review of the Literature.
in Frontiers in digital health
Perera G
(2021)
Mortality among mental health services for older adults during the COVID-19 pandemic: a retrospective analysis from South London.
in International psychogeriatrics
Description | Improving analytical skills within a third-sector Domestic Violence and Abuse specialist service - Women's Aid Federation: improving data management and skills in regression analysis in R |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | Improved capacity of the organisation to support survivors of domestic violence and abuse. |
Description | Violence, Health and Society: VISION |
Amount | £7,128,297 (GBP) |
Funding ID | MR/V049879/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 10/2021 |
End | 09/2026 |
Description | Improvement of capacity of understanding administrative data: influencing data practices of Imkaan and the Angelou-Centre |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Third sector organisations |
Results and Impact | Multiple online discussions have been held between the Research, Evaluation and Development team at Imkaan and members of the Angelou-Centre and researchers at the Violence and Society centre to understand how to improve the understanding and use of data routinely collected by the North Consortium or Imkaan more widely in their provision of specialist support to women who have experienced domestic violence and abuse, in the by-and-for context. The engagement impacted practice of data collection at Angelou-Centre, with contributions to their new case management system, but more importantly influenced their understanding of what types of analyses are possible with the data they currently hold. |
Year(s) Of Engagement Activity | 2020 |
Description | Improvement of capacity of understanding administrative data: influencing data practices of Women's Aid Federation |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Third sector organisations |
Results and Impact | Multiple online discussions have been held between the Research and Policy team at Women's Aid Federation and researchers at the Violence and Society centre to understand how to improve the understanding and use of data routinely collected by WA in their provision of specialist support to women who have experienced domestic violence and abuse. The engagement impacted practice of data collection at WA, but more importantly influenced their understanding of what types of analyses are possible with the data they currently hold. |
Year(s) Of Engagement Activity | 2020 |