Stories to Communicate Individual Risk for Opioid Prescriptions for Back and Kidney Stone Pain: Protocol for the Life STORRIED Multicenter Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Prescription opioid misuse in the United States is a devastating public health crisis; many chronic opioid users were originally prescribed this class of medication for acute pain. Video narrative-enhanced risk communication may improve patient outcomes, such as knowledge of opioid risk and opioid use behaviors after an episode of acute pain. OBJECTIVE: Our objective is to assess the effect of probabilistic and narrative-enhanced opioid risk communication on patient-reported outcomes, including knowledge, opioid use, and patient preferences, for patients who present to emergency departments with back pain and kidney stone pain. METHODS: This is a multisite randomized controlled trial. Patients presenting to the acute care facilities of four geographically and ethnically diverse US hospital centers with acute renal colic pain or musculoskeletal back and/or neck pain are eligible for this randomized controlled trial. A control group of patients receiving general risk information is compared to two intervention groups: one receiving the risk information sheet plus an individualized, visual probabilistic Opioid Risk Tool (ORT) and another receiving the risk information sheet plus a video narrative-enhanced probabilistic ORT. We will study the effect of probabilistic and narrative-enhanced opioid risk communication on the following: risk awareness and recall at 14 days postenrollment, reduced use or preferences for opioids after the emergency department episode, and alignment with patient preference and provider prescription. To assess these outcomes, we administer baseline patient surveys during acute care admission and follow-up surveys at predetermined times during the 3 months after discharge. RESULTS: A total of 1302 patients were enrolled over 24 months. The mean age of the participants was 40 years (SD 14), 692 out of 1302 (53.15%) were female, 556 out of 1302 (42.70%) were White, 498 out of 1302 (38.25%) were Black, 1002 out of 1302 (76.96%) had back pain, and 334 out of 1302 (25.65%) were at medium or high risk. Demographics and ORT scores were equally distributed across arms. CONCLUSIONS: This study seeks to assess the potential clinical role of narrative-enhanced, risk-informed communication for acute pain management in acute care settings. This paper outlines the protocol used to implement the study and highlights crucial methodological, statistical, and stakeholder involvement as well as dissemination considerations. TRIAL REGISTRATION: ClinicalTrials.gov NCT03134092; https://clinicaltrials.gov/ct2/show/NCT03134092. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/19496.
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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 | 0.023 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.061 | 0.009 |
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".