Weighted Blankets for Agitation in Hospitalized Patients with Dementia: Protocol for a Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND There are limited therapies approved for the treatment of aggression and agitation in patients with dementia. While antipsychotics and benzodiazepines are commonly used, these medications have been associated with significant side effects and US Food and Drug Administration (FDA) boxed warnings. Weighted blankets have been associated with decreased anxiety and improved sleep. Weighted blankets are potentially a nonpharmacologic option to reduce agitation in hospitalized patients with dementia. OBJECTIVE The aim of this study is to investigate the effect of weighted blankets on aggression and agitation in hospitalized patients with dementia. METHODS A pilot study will be conducted on a total of 30 hospitalized patients with a documented clinical diagnosis of dementia and ongoing agitated behaviors admitted to a medicine or psychiatry service. Patients will be randomly allocated to receive either a weighted blanket for 3 nights or continued usual care. The primary outcome is the change in the observational version of the Cohen-Mansfield Agitation Inventory (CMAI-O) over the course of the 3-night study period. The secondary outcomes are changes in Edmonton Symptom Assessment System Revised (ESAS-r) and Clinical Global Impression (CGI) scores, hours of sleep, use of antipsychotics and benzodiazepines, and incidence of delirium. Identical study assessments will be completed for both the usual care and the weighted blanket study groups. At 5 study time points (baseline, postnight 1, postnight 2, postnight 3, and a final assessment 48-72 h after the last use of the weighted blanket), patients will be assessed with the CMAI-O, ESAS-r, and CGI tools. All assessments will be completed by the bedside nurse or patient care assistant caring for the patient each day. Within 2 to 4 weeks post discharge from the hospital, study coordinators will contact the patient’s legally authorized representative (LAR) to assess for continued use of the weighted blanket. RESULTS Enrollment of participants began on April 23, 2023. As of November 2024, a total of 24 participants have been enrolled in the study. Baseline characteristics of enrolled participants will be analyzed and reported upon completion of enrollment. We anticipate completing data collection by March 2026. CONCLUSIONS The study will determine the effect of weighted blankets on agitation in hospitalized patients with dementia. Insights into the effect of weighted blankets on sleep will also be gained. The results of this study will be relevant in the setting of increasing numbers of older adults with dementia exhibiting agitation, leading to increased hospitalizations, caregiver burden, and health care costs. CLINICALTRIAL ClinicalTrials.gov NCT03643991; http://clinicaltrials.gov/ct2/show/NCT03643991 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/57264
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.032 | 0.034 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.086 | 0.012 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".