Intimate partner violence, suicidality, and self-harm: a probability sample survey of the general population in England
Bibliographic record
Abstract
Background: While intimate partner violence (IPV) is a recognised risk factor for psychiatric disorder, its links with self-harm and suicidality are not understood. Methods: Analysis of a 2014 probability sample survey of 7058 adults (16+) in the English general population. Multivariable logistic regression models quantified associations between IPV and past-year non-suicidal self-harm, suicidal thoughts, and suicide attempts. Outcomes: A fifth (21·4%, n=1702) of adults reported lifetime experience of IPV. In 66·0% this included physical IPV, 66·4% emotional, 28·4% economic, and 9·5% sexual. Half (49·3%) experienced more than one type. Rates were higher in women, 35-54-year-olds, and those living in rented accommodation or deprived neighbourhoods. Among people who had attempted suicide in the past year half (49·7%) had experienced IPV, 23·1% experienced IPV in the past year (39·6% of women, 9·4% of men). After adjusting for potential confounders including adversities, the odds of past-year suicide attempt were 2·82 (95% CI:1·54-5·17) times higher in IPV victims than non-victims. Adjusted odds ratios for past-year self-harm (2·20, 1·37-3·53) and suicidal thoughts (1·85, 1·39-2·46) were also raised. Sexual IPV was ten times more common in women than men, and an IPV type associated with particularly high odds self-harm and suicidality. Interpretation: IPV is common in England (especially among women) and strongly associated with self-harm and suicidality (especially sexual IPV). People presenting to services after self-harm should be asked about IPV. Interventions designed to reduce the prevalence and duration of IPV may protect and improve the lives of people at risk of suicide and self-harm. Funding Information: NHS Digital commissioned APMS 2014 with funding from the Department of Health and Social Care in England (DHSC). This research was supported by the UK Prevention Research Partnership (Violence, Health and Society; MR-VO49879/1), which is funded by the British Heart Foundation, 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), Medical Research Council, National Institute for Health Research, Natural Environment Research Council, Public Health Agency (Northern Ireland), The Health Foundation, and Wellcome. DK is funded by Wellcome Trust and the Elizabeth Blackwell Institute Bristol. Declaration of Interests: LA chairs England’s cross-government National Suicide Prevention Strategy Advisory Group. On behalf of all other authors, the corresponding author states that there are no other conflicts of interests. Ethics Approval Statement: The original survey was approved by the West London National Research Ethics Committee 14/LO/0411, RIT0985, 139324. The secondary analyses were approved by IMJEE Research Ethics Committee, City, University of London (ETH2122-0299). The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Verbal informed consent was obtained.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".