Health provider and service-user experiences of sensory modulation rooms in an acute inpatient psychiatry setting
Bibliographic record
Abstract
BACKGROUND: Sensory modulation rooms (SMRs) are therapeutic spaces that use sensory modulation concepts and strategies to assist service users to self-regulate and modulate arousal levels. SMRs are increasingly being explored as strength-based and person-centered adjuncts to care for people receiving inpatient psychiatry services. The aim of this study is to understand health provider and inpatient service user perceptions on the use of SMRs on acute psychiatric units. METHODS: We conducted semi-structured interviews with ten service users and nine health providers (four occupational therapists and five nurses) regarding their experiences of the SMRs located on three acute inpatient units in a large urban tertiary care hospital. We audio recorded and transcribed the focus groups and used thematic analysis to analyze the data. RESULTS: Our results suggested four common themes amongst health provider and service user experiences of sensory modulation rooms: (1) service user empowerment through self-management, (2) emotional regulation, (3) an alternative to current practices, and (4) health provider and service user education. CONCLUSION: Our study supports the ecological utility of SMRs as person-centred adjunct therapeutic space viewed positively by both service users and health providers. This understanding of SMRs is critical for future service design, research and policy aimed at improving the service user experience and care for this population. Future research is needed to validate the experience of the SMRs with other patient groups and health providers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".