The Efficacy of the <scp>iCanCope</scp> Mobile Application for Neurofibromatosis Type 1 ( <scp>NF1</scp> ): A Three‐Arm Randomized Controlled Trial
Bibliographic record
Abstract
Neurofibromatosis Type 1 (NF1) is an autosomal dominant genetic disorder that presents with severe chronic pain (CP) in adults. A limited number of NF1 research studies have evaluated behaviorally based interventions to address CP. The current study evaluated the efficacy of cognitive behavior therapy delivered via mobile application. The three-arm (treatment as usual [control], iCanCope only [iCC-NF], iCanCope + contingency management [iCC-NF + CM]) randomized clinical trial of 108 adults with NF1 and CP was completed during a 2-month intervention period. Significant improvements in pain interference (p = 0.005, d = 0.815) occurred in the iCC-NF + CM group when compared to the control group. Outcomes for pain self-efficacy (p = 0.009, d = 0.718), pain inflexibility (p = 0.026, d = 0.629), and chronic pain acceptance (p = 0.036, d = 0.653) significantly improved among the iCC-NF + CM group when compared to the control group. No significant differences were noted between iCC-NF + CM and iCC-NF. The current findings offer preliminary evidence of the added benefit of contingency management to mobile pain applications and provide an auxiliary treatment option for individuals with NF1. Trial Registration: ClinicalTrials.gov identifier: 2000029045.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".