Pediatric psychiatric inpatients' perspectives of aggression management: Discernment in the doorway
Bibliographic record
Abstract
PROBLEM: Aggressive behavior is common on psychiatric inpatient units. Seclusion and restraint interventions to manage patients' aggressive behavior may have the consequence of being traumatizing for patients. Pediatric psychiatric patients' perspective on the use of seclusion and restraint interventions is not present in the literature. METHODS: This hermeneutic nursing research study asked the question, "How might we understand children's experiences of seclusion and restraints on an inpatient psychiatric unit?" Four past pediatric psychiatric inpatients shared their hospitalization experiences that occurred within the previous year when they were 10 years old. The texts of the research interviews were compared to Attachment Theory for a deeper understanding of the meaning of the message. FINDINGS: Participants commonly described experiences with seclusion and restraints as feeling trapped and alone in a dark room. They recommended the nurses step into the room with them to help them heal. Interpretively, the rooms on inpatient units could be considered as actual and metaphorical spaces of possible harm or healing. CONCLUSION: The participant's voices expand understanding of nurse's use of discernment at the doorway of a patient room to ensure the most therapeutic care is provided to the patient in these spaces through a secure nurse-patient relationship.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.005 |
| 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".