Use of a Novel Digital Intervention to Reduce Delirium Associated Agitation: A Randomized Clinical Trial
Bibliographic record
Abstract
Abstract Background: We aimed to determine if a novel digital therapeutic intervention could reduce agitation and unscheduled medication use in an adult delirious acute care population. Methods: Delirious participants were randomly allocated (1:1) to receive standard of care plus a single 4-hour exposure to the digital intervention “MindfulGarden”, which uses a screen-based delivery to display a nature landscape with dynamic adjustment of screen content in response to movement and sound or standard of care only. Findings: Between March 2021 and January 2022, 73 participants were enrolled with 70 completing the trial protocol and included in the final analysis with a mean age of 61 years and 68% being male (35 intervention, 35 control). Mean RASS was significantly lower across the 4-hour study period in the intervention arm 0·3 (0·85) vs 0·9 (0·93), p=0·01. Interpretation: Exposure to a nature-based dynamic digital intervention showed benefits in agitation reduction.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".