Development and preliminary evaluation of a rehabilitation consult for survivors of head and neck cancer: an intervention mapping protocol
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Evidence suggests that rehabilitation interventions can improve function and quality of life in survivors of head and neck cancer (HNC), but there is a lack of coordinated, integrated services, and those offered are inconsistent. To address these gaps, we will develop and conduct preliminary evaluation of a rehabilitation consult, built on the theoretical foundations of goal setting and self-management, and composed of a brief functional evaluation, a resource compendium, and collaborative goal-setting and action planning processes. METHODS/DESIGN: The development of the rehabilitation consult will be guided by intervention mapping, which consists of six steps: 1. Needs assessment; 2. Definition of program objectives; 3. Selection of theory-based intervention methods; 4. Production and pretesting; 5. Adoption, implementation and sustainability planning; 6. Process and effect evaluation. Within the intervention mapping framework, an iterative process of constructing drafts and mini-evaluations with consumers and experts will be used, modifying the rehabilitation consult intervention until a version suitable for formal evaluation is established. The rehabilitation consult will then be evaluated using a prospective, mixed method, single group design with 30 survivors of head and neck cancer. Outcomes will be assessed pre- and post-intervention and at 6-month follow-up. DISCUSSION: Survivors of head and neck cancer have among the most complex rehabilitation needs of all cancer patients. The rehabilitation consult is expected to improve knowledge and uptake of rehabilitation resources and strategies in survivors of head and neck cancer and thereby improve long-term function and quality of life. If the rehabilitation consult is effective in cancer patients with such high and diverse needs, this project will produce a toolkit that will be adaptable for other types of cancer in other jurisdictions.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it