Association between BDNF levels and suicidal behaviour: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Suicide is a worldwide public health concern that claims close to 1 million lives each year. Suicidal behaviour is a significant risk factor for completed suicide and is much more prevalent than completed suicide. Many internal and external factors contribute to the risk of suicidal behaviour. Recent research has focused on biological markers in suicide risk, including brain-derived neurotrophic factor (BDNF). BDNF is a protein involved in the growth, function, and maintenance of the nervous system. It has been implicated in psychiatric disorders and suicide. While some evidence suggests that reduced levels of BDNF are associated with suicide, the precise relationship has yet to be determined. The aim of this study is to review the literature examining the relationship between levels of BDNF and suicidal behaviour. METHODS: A predefined search strategy will be implemented to search the following electronic databases: PubMed/MEDLINE, Excerpta Medica Database (EMBASE), PsycINFO, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) from inception. The articles will be screened by two independent authors (RE and SP) using predetermined inclusion and exclusion criteria. Discrepancies will be resolved by consensus, or by a third author (ZS) in cases of disagreement. The primary outcome will be the association between levels of BDNF and suicidal behaviour. A meta-analysis will be conducted if appropriate. Quality of evidence and risk of bias will be evaluated. DISCUSSION: The findings of this review will assist in identifying and treating individuals at increased risk of suicide. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015015871 .
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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 | 0.050 | 0.054 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.023 | 0.015 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.065 | 0.007 |
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".