THE MENTALLY ILL AND SOCIAL EXCLUSION: A CRITICAL EXAMINATION OF THE USE OF SECLUSION FROM THE PATIENT'S PERSPECTIVE
Bibliographic record
Abstract
Nurses in psychiatric settings have an important role to play in the application of seclusion, a measure that continues to be a frequently used intervention for the management of disturbing patient behaviours. Albeit a controversial measure, isolating patients remains a common institutional practice that has received widespread attention from a political, ethical, legal, and clinical standpoint. Although there is an abundance of scientific work on the subject, few studies have examined the experience of patients being confined. In order to improve the quality of nursing care surrounding this measure it appeared essential to obtain data on patients' perspectives, information deemed valuable in orienting nursing interventions. This qualitative study, guided by a phenomenological research design, aimed at describing and gaining a better understanding of patients with a severe and persistent psychiatric disorder who were placed in a seclusion room while hospitalized on a closed psychiatric unit. Using a semi-structured, non-directive interview format, a total of six patients participated in this study. Content analysis of participants' narratives yielded three main themes that appeared to be central to their experience of seclusion: their experience of seclusion on an emotional level, their perception of this intervention, and how they coped during their stay in the seclusion room. Major findings emerging from this nursing study centred on the following dimensions: patients' perceptions of seclusion as a punitive measure and a modality for social control and, the experience of seclusion serving as an intensification of already existing feelings of exclusion, rejection, abandonment, and isolation. In addition the findings also suggest that it is not seclusion per se that impacts on their negative perception and negative emotional experience but rather the lack of nurse-patient contact during the seclusion experience. Furthermore, whether patients coped by regressing, acting out, or taking on a more compliant stance, they appeared to be motivated by a need to connect with staff. This points to the importance of the relational aspects of nursing care when applying this restrictive measure. A need for modifying the institutional culture surrounding seclusion and transforming nursing practices are discussed as are future research endeavours.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".