10th Annual Evidence-Based Practice/Research Conference Evidence for Practice: Origins and New Directions October 8, 2018
Bibliographic record
Abstract
Background: Evidence indicated that use of the PARO robotic pet reduced difficult behavioral and psychological symptoms with patients diagnosed with dementia; however, there was no evidence found in using the PARO robotic pet in adult patients with behavioral disturbances in the acute care setting.Methods: The Pittsburgh Agitation Scale (PAS) and Zung Self-Rating Anxiety Scale (Zung) along with physiologic measures of heart rate (HR), respiratory rate (RR), blood pressure (BP), and pulse oximeter (SPO2) readings before and after the treatment of the PARO in the experimental group vs listening to the television or music in the control group were used to determine if agitation and/or anxiety could be decreased in 40 subjects at two facilities in the Baylor Scott & White Health System.Results: Comparison of all measures, whether physiological (HR, RR, BP, SPO2), agitation (PAS), or anxiety (Zung), showed no statistically significant contrasts at the 95% confidence level with P value set at 0.05 between the experimental and control groups for the PAS test between before and after relaxation, or between exposure episodes before or after relaxation method; however, a clinically significant lowering of the distributional location of the Zung anxiety score was noted in the experimental group after exposure to the relaxation method.Conclusion: Based on the results, further research needs to be conducted with the use of the PARO to determine if the robotic seal will reduce agitation and anxiety in patients in the acute care hospital setting.Further research with a larger sample size and in more than one healthcare system is necessary to demonstrate the statistical significance that the use of the PARO reduces anxiety and agitation in this patient population. 2.1.A.
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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 | 0.119 | 0.210 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".