Adherence to Home-Based Swallowing Therapy Using a Mobile System in Head and Neck Cancer Survivors
Bibliographic record
Abstract
Purpose A large knowledge gap related to dysphagia treatment adherence was identified by a recent systematic review: Few existing studies report on adherence, and current adherence tracking relies heavily on patient self-report. This study aimed to report weekly adherence and dysphagia-specific quality of life following home-based swallowing therapy in head and neck cancer (HNC). Method This was a quasi-experimental pretest–posttest design. Patients who were at least 3 months post–HNC treatment were enrolled in swallowing therapy using a mobile health (mHealth) swallowing system equipped with surface electromyography (sEMG) biofeedback. Participants completed a home dysphagia exercise program across 6 weeks, with a target of 72 swallows per day split between three different exercise types. Adherence was calculated as percent trials completed of trials prescribed. The M. D. Anderson Dysphagia Inventory (MDADI) was administered before and after therapy. Results Twenty participants (75% male), with an average age of 61.9 years ( SD = 8.5), completed the study. The majority had surgery ± adjuvant (chemo)radiation therapy for oral (10%), oropharyngeal (80%), or other (10%) cancers. Using an intention-to-treat analysis, adherence to the exercise regimen remained high from 84% in Week 1 to 72% in Week 6. Radiation therapy, time since cancer treatment, medical difficulties, and technical difficulties were all found to be predictive of poorer adherence at Week 6. A statistically significant improvement was found for composite, emotional, and physical MDADI subscales. Conclusions When using an mHealth system with sEMG biofeedback, adherence rates to home-based swallowing exercise remained at or above 72% over a 6-week treatment period. Dysphagia-specific quality of life improved following this 6-week treatment program.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".