Self-harm in midlife: analysis using data from the Multicentre Study of Self-harm in England
Bibliographic record
Abstract
BACKGROUND: In England suicide rates are highest in midlife (defined as age 40-59). Despite a strong link with suicide there has been little focus on self-harm in this age group.AimTo describe characteristics and treatment needs of people in midlife who present to hospital following self-harm. METHOD: Data from the Multicentre Study of Self-harm in England were used to examine rates over time and characteristics of men and women who self-harm in midlife. Data (2000-2013) were collected via specialist assessments or hospital records. Trends were assessed by negative binomial regression models. Comparative analysis used logistic regression models for binary outcomes. Repetition and suicide mortality were assessed by Cox proportional hazards models. RESULTS: A quarter of self-harm presentations were made by people in midlife (n = 24 599, 26%). Incidence rates increased over time in men, especially after 2008 (incidence rate ratio [IRR] 1.07, 95% CI 1.02-1.12, P < 0.01), and were positively correlated with national suicide incidence rates (r = 0.52, P = 0.05). Rates in women remained relatively stable (IRR 1.00, 95% CI 1.00-1.02, P = 0.39) and were not correlated with suicide. Alcohol use, unemployment, housing and financial factors were more common in men; whereas indicators of poor mental health were more common in women. In men and women 12-month repetition was 25%, and during follow-up 2.8% of men and 1.2% of women died by suicide. CONCLUSION: Self-harm in midlife represents a key target for intervention. Addressing underlying issues, alcohol use and economic factors may help prevent further self-harm and suicide.Declaration of interestK.H. and N.K. are members of the Department of Health's National Suicide Prevention Advisory Group. N.K. chaired the National Institute for Health and Care Excellence (NICE) guideline development group for the longer-term management of self-harm and the NICE Topic Expert Group which developed the quality standards for self-harm services. N.K. also chairs the NICE guideline committee for the management of depression. All other authors declare no conflict of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".