An evaluation of clinical practice guidelines for self-harm in adolescents: The role of borderline personality pathology.
Bibliographic record
Abstract
Borderline personality disorder (BPD) is associated with high rates of self-harm, suicide attempts, and death by suicide in adults and adolescents. Screening and assessment of BPD in self-harming adolescents could be an important clinical intervention. The aim of this article was to identify whether existing clinical practice guidelines (CPGs) for the care of self-harm in adolescents considered the screening, diagnosis, and/or treatment of BPD. Previous work by Courtney, Duda, Szatmari, Henderson, and Bennett (2018) used Preferred Reporting Items for Systematic Reviews and Meta-Analyses methods to identify 10 CPGs relevant to self-harm in children and adolescents. In this study, the 10 CPGs were reviewed for content about screening, assessment, and/or treatment recommendations for adolescents with BPD. Out of the 10 CPGs, 4 acknowledged the association between BPD and self-harm in adolescents. There was minimal to no guidance provided in the CPGs regarding specific screening, assessment, or treatment strategies for BPD. This may be due to the lack of evidence for efficacy and effectiveness of screening for BPD, thereby limiting the development of guideline recommendations. Studies that examine the impact of screening for BPD in clinical settings are needed. In the interim, CPGs should cite the prevalence of BPD in adolescents who self-harm and reference research showing the benefit of treatment with dialectical behavioral therapy for self-harm and suicide attempts in youth with BPD. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.357 | 0.723 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.008 | 0.012 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".