Psychoeducational interventions for borderline personality disorder: A scoping review.
Bibliographic record
Abstract
Background: As a psychosocial intervention, psychoeducation (PE) consists primarily in delivering up-to-date information about a mental illness to a patient, including diagnosis and treatment. PE has been shown to effectively decrease symptoms and prevent relapse across mental illnesses, including personality disorders. Correspondingly, PE is considered to be an important and lighter resource to support the recovery of mental health patients. To this date, no systematic reviews have been conducted to examine de role of psychoeducational interventions for Borderline Personality Disorder (BPD.) The aim of this study is to synthesize the current evidence about the benefits of psychoeducational interventions for the treatment of BPD.Methods: This review will follow the PRISMA guidelines for scoping reviews. We will search the following electronic databases: PubMed, PsychINFO, WoS, CINAHL, LILACS. Grey literature will be identified through ProQuest Dissertations, Theses Global and web searches for clinical resources. We will include articles and resources in English, that describe psychoeducational interventions in BPD without any consideration of publishing date. Two reviewers will independently screen all titles, abstracts, and full-text citations.Discussion: This scoping review aims sumamrize the extant literature concerining psychoeducational interventions for patients with BPD, focusing on intervention deliverey (i.e. online, face-to-face, groups, etc) which topics are treated (i.e. diagnosis, course of illness, treatment, etiology, etc), what is the target population (i.e. patients, staff, family members) and intervention duration. The findings can be used for future research and also for developing new interventions.
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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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".