Age of first self-harm act in childhood and adolescence: A scoping review protocol
Bibliographic record
Abstract
Background: Self-harm in youth is associated with adverse outcomes for many. The age of first self-harm is not often reported in the literature and there is considerable heterogeneity in how it is reported and in the methods used to estimate it. The objective of this study will be to examine the age of first self-harm act in childhood and adolescence and to identify the research methods used to assess this. Methods: This scoping review will follow JBI guidance. Five electronic databases, Medline, PsycInfo, CINAHL Plus, Embase, and Web of Science will be searched from inception. Grey literature will be searched via Google Scholar. Studies reporting the age of first act of self-harm in young people aged 17 years and younger are of interest. Any study design and methodology will be eligible for inclusion. Included studies may use any self-harm definition, any measures used to assess self-harm and the age of the first act. The focus can be in any context, including health services presenting or community samples. Title and abstract screening and full text screening will be carried out by two reviewers independently. The data extraction tool will be piloted by two reviewers independently, included studies will undergo data extraction by one reviewer and this will be checked by a second, independent reviewer. Results: The resulting data will be presented using descriptive statistics, in tabular format, and accompanied with a narrative presentation of results. The results of this study will be distributed by publication in an academic journal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.128 | 0.096 |
| Meta-epidemiology (narrow) | 0.006 | 0.008 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.022 | 0.016 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.088 | 0.023 |
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".