TY - JOUR
T1 - The association between neighbourhood characteristics and physical victimisation in men and women with mental disorders
AU - Bhavsar, Vishal
AU - Sanyal, Jyoti
AU - Patel, Rashmi
AU - Shetty, Hitesh
AU - Velupillai, Sumithra
AU - Stewart, Robert
AU - Broadbent, Matthew
AU - Maccabe, James H.
AU - Das-Munshi, Jayati
AU - Howard, Louise M.
PY - 2020
Y1 - 2020
N2 - Background How neighbourhood characteristics affect the physical safety of people with mental illness is unclear.Aims To examine neighbourhood effects on physical victimisation towards people using mental health services.Method We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health Service mental health services in Southeast London. Sociodemographic and clinical data, and diagnostic information on use of acute hospital care (from Hospital Episode Statistics, linked to Clinical Record Interactive Search), were collected in this group, defined as 'cases' and concurrently sampled controls. Multilevel logistic regression models estimated associations (odds ratios, ORs) between neighbourhood-level fragmentation, crime, income deprivation, and population density and physical victimisation.Results Based on a human-rated gold standard, the NLP algorithm had a positive predictive value of 0.92 and sensitivity of 0.98 for (clinically recorded) physical victimisation. A 1 s.d. increase in neighbourhood crime was accompanied by a 7% increase in odds of physical victimisation in women and an 13% increase in men (adjusted OR (aOR) for women: 1.07, 95% CI 1.01-1.14, aOR for men: 1.13, 95% CI 1.06-1.21, P for gender interaction, 0.218). Although small, adjusted associations for neighbourhood fragmentation appeared greater in magnitude for women (aOR = 1.05, 95% CI 1.01-1.11) than men, where this association was not statistically significant (aOR = 1.00, 95% CI 0.95-1.04, P for gender interaction, 0.096). Neighbourhood income deprivation was associated with victimisation in men and women with similar magnitudes of association.Conclusions Neighbourhood factors influencing safety, as well as individual characteristics including gender, may be relevant to understanding pathways to physical victimisation towards people with mental illness.
AB - Background How neighbourhood characteristics affect the physical safety of people with mental illness is unclear.Aims To examine neighbourhood effects on physical victimisation towards people using mental health services.Method We developed and evaluated a machine-learning-derived free-text-based natural language processing (NLP) algorithm to ascertain clinical text referring to physical victimisation. This was applied to records on all patients attending National Health Service mental health services in Southeast London. Sociodemographic and clinical data, and diagnostic information on use of acute hospital care (from Hospital Episode Statistics, linked to Clinical Record Interactive Search), were collected in this group, defined as 'cases' and concurrently sampled controls. Multilevel logistic regression models estimated associations (odds ratios, ORs) between neighbourhood-level fragmentation, crime, income deprivation, and population density and physical victimisation.Results Based on a human-rated gold standard, the NLP algorithm had a positive predictive value of 0.92 and sensitivity of 0.98 for (clinically recorded) physical victimisation. A 1 s.d. increase in neighbourhood crime was accompanied by a 7% increase in odds of physical victimisation in women and an 13% increase in men (adjusted OR (aOR) for women: 1.07, 95% CI 1.01-1.14, aOR for men: 1.13, 95% CI 1.06-1.21, P for gender interaction, 0.218). Although small, adjusted associations for neighbourhood fragmentation appeared greater in magnitude for women (aOR = 1.05, 95% CI 1.01-1.11) than men, where this association was not statistically significant (aOR = 1.00, 95% CI 0.95-1.04, P for gender interaction, 0.096). Neighbourhood income deprivation was associated with victimisation in men and women with similar magnitudes of association.Conclusions Neighbourhood factors influencing safety, as well as individual characteristics including gender, may be relevant to understanding pathways to physical victimisation towards people with mental illness.
KW - data linkage
KW - electronic health records
KW - Natural language processing
KW - neighbourhood characteristics
KW - violence
UR - http://www.scopus.com/inward/record.url?scp=85092444309&partnerID=8YFLogxK
U2 - 10.1192/bjo.2020.52
DO - 10.1192/bjo.2020.52
M3 - Article
AN - SCOPUS:85092444309
SN - 2056-4724
VL - 6
JO - BJPsych Open
JF - BJPsych Open
IS - 4
M1 - e73
ER -