Restraint and Seclusion: The Perspective of Service Users and Staff Members
Bibliographic record
Abstract
BACKGROUND: Restrictive measures may have important physical and psychological consequences on all persons involved. The current study examined how these are perceived by persons with intellectual disabilities and staff. MATERIALS AND METHODS: Interviews were conducted with eight persons with intellectual disabilities who experienced a restrictive measure and their care providers. They were queried on their understanding of the restrictive measure, its impact on the relationship, their emotions and alternative interventions. RESULTS: Restrictive measures were experienced negatively by persons with intellectual disabilities and their care providers. Service users reported feeling sad and angry, whereas staff mentioned feeling anxious. Moreover, persons with intellectual disabilities appeared to understand the goal of restrictive measures (e.g. ensuring their own and others' safety) and identified alternative interventions (e.g. speaking with a staff member or taking a walk). CONCLUSION: This study sheds further light on how persons with intellectual disabilities and staff experience the application of restrictive measures. Debriefing sessions with service users and staff may help minimize negative consequences.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".