Introducing Narrative Practices in a Locked, Inpatient Psychiatric Unit
Bibliographic record
Abstract
INTRODUCTION: Narrative approaches to psychotherapy are becoming more prevalent throughout the world. We wondered if a narrative-oriented psychotherapy group on a locked, inpatient unit, where most of the patients were present involuntarily, could be useful. The goal would be to help involuntary patients develop a coherent story about how they got to the hospital and what happened that led to their being admitted and link that to a story about what they would do after discharge that would prevent their returning to hospital in the next year. METHODS: A daily, one-hour narrative group was implemented on one of three locked adult units in a psychiatric hospital. Quality-improvement procedures were already in place for assessing outcomes by unit using the BASIS-32 (32-item Behavior and Symptom Identification Scale). Unit outcomes were compared for the four quarters before the group was started and then four months after the group had been ongoing. RESULTS: The unit on which the narrative group was implemented had a mean overall improvement in BASIS-32 scores of 2.8 units, compared with 1.0 unit for the other locked units combined. The results were statistically significant at the p < 0.0001 level. No differences were found between units for the four quarters prior to implementation of the intervention, and no other changes occurred during the quarter in which the group was conducted. Qualitative descriptions of the leaders' experiences are included in this report. CONCLUSIONS: A daily, one-hour narrative group can make a difference in a locked inpatient unit, presumably by creating cognitive structure for patients in how to understand what has happened to them. Further research is indicated in a randomized, controlled-trial format.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".