A Pain eHealth Platform for Engaging Obese, Older Adults with Chronic Low Back Pain in Nonpharmacological Pain Treatments: Protocol for a Pilot Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Low back pain is a costly healthcare problem and the leading cause of disability among adults in the United States. Primary care providers urgently need effective ways to deliver evidence-based, nonpharmacological therapies for chronic low back pain. Guidelines published by several government and national organizations have recommended nonpharmacological and nonopioid pharmacological therapies for low back pain. OBJECTIVE: The Pain eHealth Platform (PEP) pilot trial aims to test the feasibility of a highly innovative intervention that (1) uses an electronic health record (EHR) query to systematically identify a phenotype of obese, older adults with chronic low back pain who may benefit from Web-based behavioral treatments; (2) delivers highly tailored messages to eligible older adults with chronic low back pain via the patient portal; (3) links affected patients to a Web app that provides education on the efficacy of evidence-based, nonpharmacological, behavioral pain treatments; and (4) directs patients to existing Web-based health treatment tools. METHODS: Using a three-step modified Delphi method, an expert panel of primary care providers will define a low back pain phenotype for an EHR query. Using the defined low back pain phenotype, an EHR query will be created to identify patients who may benefit from the PEP. Up to 15 patients with low back pain will be interviewed to refine the tailored messaging, esthetics, and content of the patient-facing Web app within the PEP. Up to 10 primary care providers will be interviewed to better understand the facilitators and barriers to implementing the PEP, given their clinic workflow. We will assess the feasibility of the PEP in a single-arm pragmatic pilot study in which secure patient portal invitations containing a hyperlink to the PEP Web app are sent to 1000 patients. The primary outcome of the study is usability as measured by the System Usability Scale. RESULTS: Qualitative interviews with primary care providers were completed in April 2019. Qualitative interviews with patients will begin in December 2019. CONCLUSIONS: The PEP will leverage informatics and the patient portal to deliver evidence-based nonpharmacological treatment information to adults with chronic low back pain. Results from this study may help inform the development of Web-based health platforms for other pain and chronic health conditions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14525.
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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 | 0.035 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.070 | 0.014 |
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".