“Push” versus “Pull” for mobilizing pain evidence into practice across different health professions: A protocol for a randomized trial
Bibliographic record
Abstract
BACKGROUND: Optimizing pain care requires ready access and use of best evidence within and across different disciplines and settings. The purpose of this randomized trial is to determine whether a technology-based "push" of new, high-quality pain research to physicians, nurses, and rehabilitation and psychology professionals results in better knowledge and clinical decision making around pain, when offered in addition to traditional "pull" evidence technology. A secondary objective is to identify disciplinary variations in response to evidence and differences in the patterns of accessing research evidence. METHODS: Physicians, nurses, occupational/physical therapists, and psychologists (n = 670) will be randomly allocated in a crossover design to receive a pain evidence resource in one of two different ways. Evidence is extracted from medical, nursing, psychology, and rehabilitation journals; appraised for quality/relevance; and sent out (PUSHed) to clinicians by email alerts or available for searches of the accumulated database (PULL). Participants are allocated to either PULL or PUSH + PULL in a randomized crossover design. The PULL intervention has a similar interface but does not send alerts; clinicians can only go to the site and enter search terms to retrieve evidence from the cumulative and continuously updated online database. Upon entry to the trial, there is three months of access to PULL, then random allocation. After six months, crossover takes place. The study ends with a final three months of access to PUSH + PULL. The primary outcomes are uptake and application of evidence. Uptake will be determined by embedded tracking of what research is accessed during use of the intervention. A random subset of 30 participants/ discipline will undergo chart-stimulated recall to assess the nature and depth of evidence utilization in actual case management at baseline and 9 months. A different random subset of 30 participants/ discipline will be tested for their skills in accessing evidence using a standardized simulation test (final 3 months). Secondary outcomes include usage and self-reported evidence-based practice attitudes and behaviors measured at baseline, 3, 9, 15 and 18 months. DISCUSSION: The trial will inform our understanding of information preferences and behaviors across disciplines/practice settings. If this intervention is effective, sustained support will be sought from professional/health system initiatives with an interest in optimizing pain management. TRIAL REGISTRATION: Registered as NCT01348802 on clinicaltrials.gov.
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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 | 0.121 | 0.116 |
| Meta-epidemiology (narrow) | 0.009 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.105 | 0.025 |
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".