Brief mindfulness-oriented interventions (MOIs) to improve psychiatric symptoms in a psychiatric inpatient unit: a randomized controlled feasibility trial
Bibliographic record
Abstract
Background Mindfulness-based interventions are effective in treating numerous psychiatric symptoms, but data about brief mindfulness-oriented intervention (MOI) use with psychiatric inpatients are limited. We investigated whether a brief MOI was feasible and effective in reducing psychosis and other symptoms in a psychiatric inpatient unit.Methods In an assessor-blinded feasibility randomized-controlled trial, adult psychiatric inpatients were randomized to the intervention or control group. Feasibility outcomes included enrollment rate, retention rate and intervention-completion rate. The quantitative outcome was the impact on symptom reduction (mean and % difference in Brief Psychiatric Rating Scale (BPRS) between baseline and 7-day follow-up scores). Exploratory outcomes included improvement in quality of sleep, mindfulness and quality of life. Qualitative intervention feedback was obtained from therapists and participants.Results Feasibility outcomes were 39.2% participant enrollment, 85% study completion and 81.8% intervention completion. No symptom outcomes significantly differed. There were no significant differences in exploratory outcomes. Interventionists reported system-level barriers in treatment delivery; patients subjectively reported enjoying the intervention.Conclusion The MOI is feasible in the inpatient psychiatric setting. There were no significant effects on psychiatric symptoms during the follow-up period, but no adverse effects were reported. Therapeutic effects could be further investigated in longer-term interventions and larger confirmatory RCTs.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".