Pediatricians’ Competence in Prevention, Risk Determination or Detection of Suicidal Behavior in Children: Cross-Sectional Survey Study
Bibliographic record
Abstract
Background. Child and adolescent suicides remain one of the most painful public issues. The COVID-19 pandemic has aggravated this topic as the number of suicides among children population has increased in this period. Research and practice guidelines identify the leading role of primary care physicians in the prevention, identification, and routing of patients with suicidal behavior. At the same time, there were no studies on pediatricians’ competence in the field of suicides. Objective. The aim of the study is to study pediatricians’ competence in prevention, risk determination or and detection of suicidal behavior. Methods. Cross-sectional study was conducted with the usage of original electronic questionnaire aimed on identifying the level of pediatricians’ competence in evaluating suicidal behavior in children. Questionnaire included 18 questions. Results. We have received 208 electronic questionnaires. 97.1% of specialists have confirmed that they evaluate emotional status of their patients during admission. During admission: 86.1% of specialists have considered the characteristics of children appearance, facial expression, voice intonation, 65.4% — have asked questions about mood, 62.5% — have interviewed parents. 98.6% of specialists pay attention to the presence of self-inflicted injuries marks, 88.4% — ask about the origin of these injuries. Only 36.1% of respondents ask patients about suicidal thoughts, intentions, or actions. Only 69.3% of specialists are ready to refer their patients to psychologist, and 51.7% — to psychiatrist. Conclusion. Even though most surveyed pediatricians notice signs of suicidal intent (low mood, self-inflicted injuries), they avoid discussing the topic of suicide during admission. Increasing the competence of pediatricians should be aimed on destigmatisation in the field of mental health, increasing the knowledge level, and developing practical skills in working with children with suicidal behavior.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".