Why go to the emergency department? Perspectives from persons with borderline personality disorder
Bibliographic record
Abstract
Through this qualitative study, we explored frequent emergency department use by persons with borderline personality disorder from their perspective. Interpretive description guided the study design, and data were collected through interviews with six individuals diagnosed with borderline personality disorder who had at least 12 emergency department visits for reasons related to their mental illness within a 1-year timeframe. Using thematic data analysis, we articulate the participants' experiences through two broad themes: cyclic nature of emergency department use and coping skills and strategies. Unstable community management that leads to self- or crisis presentation to the emergency department often perpetuated emergency department use by our participants and the ensuing interventions aimed at acute stabilization. The participants identified a desire for human interaction and feelings of loneliness, failure of community resources (such as crisis lines or therapy), and safety concerns following suicidal ideation, self-harm, or substance use as the main drivers for their emergency department visits. Our participants identified several potential strategies to protect them against unnecessary emergency department use and improve their health care overall. More work is needed to explore the viability and effectiveness of these suggestions.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".