Innovation in the Treatment of Persistent Pain in Adults With NF1: Implementation of the iCanCope Mobile App
Bibliographic record
Abstract
Background Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic condition affecting 1 in 2500 individuals. Over 50% of individuals with NF1 report significant pain and discomfort, which may be associated with benign and malignant tumors, but is often not localized to a structural lesion, thus presenting treatment challenges for patients and their medical caregivers. To date, there are very few treatments aside from surgical intervention to mitigate pain. Objective We developed the iCanCope-NF mobile app for pain self-management. iCanCope-NF is a customized self-monitoring and pain management mobile app designed to provide resources and support for those having chronic pain due to NF1. The app enables users to access daily pain monitoring and quality of life check-ins, allows them to plot interrelated variables on various timelines to observe trends in pain and interference across different areas of life (such as sleep, physical activity, and mood), and provides them with the option to set physiological and psychological goals as well as a robust library of written and video resources to help manage pain symptoms and to better cope with NF1. Methods This paper evaluated the iCanCope-NF to reduce pain severity and interference in adults with NF1. A total of 80 participants across 3 different groups (control, iCanCope-NF access condition, and iCanCope-NF contingency management condition where subjects were provided monetary incentives for engaging with the various features within the app [CM]) completed a randomized clinical trial in which evaluations were completed at intake (initial day of participation), discharge (2 months after intake), and 6 weeks after discharge. Results Preliminary data analysis demonstrated individuals randomized to the iCanCope-NF + CM had greater engagement with the mobile app than individuals who were randomized to iCanCope-NF. Additionally, individuals in the iCanCope-NF + CM consistently checked in more (SD 59.5/60 days) than individuals in the iCanCope-NF group (SD 51/60 days). Pain interference, as measured by the Pain Interference Index (PII), was significantly different across all 3 groups at discharge: control (M=6.3), iCanCope (M=5.7), iCanCope + CM (M=5.1), P<.05. Conclusions Qualitative interviews completed at discharge for individuals with access to the app indicated that the app was a “wonderful measuring tool” and “provided credibility of my pain symptoms,” and that it was a dramatic and distinctive aide in the monitoring and tracking of their pain symptoms. We demonstrated preliminary acceptability and efficacy for iCanCope-NF as the first pain self-management tool for individuals with NF1. iCanCope-NF + CM was successful in increasing engagement and decreasing pain interference. Trial Registration ClinicalTrials.gov NCT04561765; https://clinicaltrials.gov/ct2/show/NCT04561765 Conflicts of Interest None declared.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".