Bibliographic record
Abstract
Adolescent suicide and suicidal behaviours have become major public health issues in recent years. Suicide is widely recognized as a major cause of mortality in young people, and nonfatal suicidal behaviours in young people are associated with considerable morbidity. Suicidal behaviour in adolescence covers a wide spectrum of phenomena for which an exact definition and an understanding of the interrelations remain controversial.1 The epidemiology of youth suicide is a fascinating story. The 20th century produced a steady rise in the incidence of suicide in young males punctuated by decreases during the World Wars; however, since the 1 990s, rates of suicide in young men have steadily declined. This was partly due to an increased number of cars with catalytic converters and to declines in rates of unemployment and divorce.2 Some researchers, especially in the United States, have strongly supported the important role of selective serotonin reuptake inhibitors use in explaining the reduction of adolescent suicide,3'4 a claim refuted by Biddle et al.2 Following the introduction of the black box warning, there was a new rise in adolescent suicide, which some authors attributed to reduced prescriptions of these agents, although Wheeler et al5 have vigorously disputed this interpretation. One other major epidemiologic finding in recent years has been the finding that, in China, southern India, and Singapore, the accepted sex differences for suicide are reversed, and that young females are more at risk for suicide than males.6 In these young females, mental illness seems to be less of a factor in their suicides than has been reported in the West7 and most fatalities are due to pesticide ingestion. Undoubtedly, the restriction of the use of pesticides is a very important preventative measure in these countries.8 It has become increasingly clear that family genetic studies play an important role in understanding suicide and that, especially in youth, suicide is inherited distinctively from any concurrent psychiatric illness.9 It has also become increasingly apparent that genetic transmission is more characteristic of suicide in youth than that of suicide in older people. The biological mechanism that may be involved is probably related to serotonin metabolism and low turnover of 5-hydroxyindoleacetic acid as measured in the cerebral spinal fluid, which in turn is related to aggression and impulsivity.10 This, combined with a genetic predisposition for a heightened stress reaction via genetic mechanisms in the hypothalamo-pituitary-adrenal axis, provides a plausible basis for beginning to understanding suicide in youth. Psychological risk factors that have been the focus of recent attention include overgeneralized autobiographical memory associated with interpersonal relationships,12 deficits in problem solving,13 as well as high levels of impulsiveaggressiveness. 14 Additional potential precursors of suicidal behaviour in depressed adolescents are other early development traits, such as temperament and emotional regulation.15 Adolescent suicidal behaviour also seems to be related to just about all types of serious psychiatric disorder, including: eating disorders,16 schizophrenia,17 and, of course, all forms of depression, especially bipolar disorder. Social risk factors for adolescent suicide include parental separation, divorce, and family discord, as well as child abuse and imitation.18 Media reporting and, naturally, alcohol and drug abuse are also important facilitators of suicide among young people. Bullying and peer victimization are extremely dangerous precipitators19,20 and, together with the understudied effects of immigration, are reviewed more extensively in this issue's In Review.21,22 A new social force impinging on youth suicide is the Internet.2 As an increasingly popular source of information, concerns have been raised about the existence of websites that promote suicide23 as well as suicide websites that have been claimed to have facilitated suicide pacts among strangers. …
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".