Psychoeducational interventions for borderline personality disorder: A scoping review.
Bibliographic record
Abstract
Psychoeducation, delivering up-to-date information about mental illness is crucial for supporting patients' recovery. While recognized for various disorders, its role in borderline personality disorder (BPD) lacks review. This study synthesizes the current evidence about psychoeducational interventions for BPD. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, this scoping review consulted databases (PubMed, PsychINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature, and Información Científica y Técnica en Salud de América Latina y el Caribe), and grey literature (ProQuest Dissertations and Theses Global and Google Scholar). A Complementary search (contacting relevant researchers and including relevant references from included articles) was included. Two reviewers screened and extracted the data using the Template for Intervention Description and Replication checklist. Seven studies were analyzed, and positive effects were found on diverse outcomes: BPD symptoms, coping strategies, well-being, communication, quality of life, social functioning, perceived stress, mental health symptoms, and stigma. Psychoeducational interventions for BPD can help people who experience BPD to optimize their recovery process. However, replication and improvements are to yield sustained effects and reach more to this population. (PsycInfo Database Record (c) 2026 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 | 0.012 | 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".