Publications by authors named "Chilman N"
Article Synopsis
- A systematic review and meta-analysis examined the mortality risk from infectious diseases (excluding COVID-19) in individuals with severe mental illness (SMI) like schizophrenia and bipolar disorder.
- The analysis included 29 studies, revealing that those with SMI are more than twice as likely to die from any infectious disease and over three times more likely to die from respiratory infections compared to the general population.
- Variations in findings were influenced by factors such as the specific SMI diagnosis, gender, and the type of infection studied.
Aims: The associations of prior homelessness with current health are unknown. Using nationally representative data collected in private households in England, this study aimed to examine Common Mental Disorders (CMDs), physical health, alcohol/substance dependence, and multimorbidities in people who formerly experienced homelessness compared to people who never experienced homelessness.
Methods: This cross-sectional study utilised data from the 2007 and 2014 Adult Psychiatric Morbidity Surveys.
Purpose: People with severe mental illness (SMI) experience high levels of unemployment. We aimed to better understand the associations between clinical, social, and demographic inequality indicators and unemployment.
Methods: Data were extracted from de-identified health records of people with SMI in contact with secondary mental health services in south London, UK.
Objectives: To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching.
Setting: South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London.
Background: Premature mortality is a well-documented adverse outcome for people living with severe mental illnesses (SMI). Emerging evidence suggests that area-level factors play a role that are experienced disproportionately by this population. This review assesses the potential association between area-level factors and mortality in people with SMI.
View Article and Find Full Text PDFBackground: Analyzing Twitter posts enables rapid access to how issues and experiences are socially shared and constructed among communities of health service users and providers, in ways that traditional qualitative methods may not.
Objective: To enrich the understanding of mental health crisis care in the United Kingdom, this study explores views on crisis resolution teams (CRTs) expressed on Twitter. We aim to identify the similarities and differences among views expressed on Twitter compared with interviews and focus groups.
Objectives: We set out to develop, evaluate and implement a novel application using natural language processing to text mine occupations from the free-text of psychiatric clinical notes.
Design: Development and validation of a natural language processing application using General Architecture for Text Engineering software to extract occupations from de-identified clinical records.
Setting And Participants: Electronic health records from a large secondary mental healthcare provider in south London, accessed through the Clinical Record Interactive Search platform.