Challenges and Opportunities for Speech‐Language Pathology Services in Comprehensive Head and Neck Cancer Care: Insights From a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Speech-language pathologists serve a critical role within multidisciplinary head and neck cancer care teams. Provision of speech-language pathology services for head and neck cancer patients varies by region and is not well characterized. METHODS: A mixed methods scoping assessment was conducted with a purposive sample of speech-language pathologists from designated comprehensive head and neck cancer centers. Each speech-language pathologist completed a 31-item survey and 60-min semi-structured interview. RESULTS: Analysis of survey responses and qualitative interviews identified three major themes: unsuitable infrastructure; multilevel barriers; and the need to champion speech-language pathology services. Speech-language pathologists consistently reported inadequate resources, inequitable services, and increasing job responsibilities associated with growing patient complexity and caseloads. CONCLUSIONS: Significant systemic barriers impede the effective delivery of speech-language pathology services in head and neck cancer care. Our findings and recommendations create an important foundation for healthcare agency decisions on the allocation and funding of speech-language pathology services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".