P009: Fighting Fatigue: Designing a Multidisciplinary Intervention for Cancer-Related Fatigue.
Bibliographic record
Abstract
OBJECTIVES: This program was developed in response to the pervasiveness of fatigue reported by cancer patients. Patients of the Northeast Cancer Centre (necc), including those receiving care at one of 14 Community Oncology Clinic Network (cocn) sites, are routinely screened for distress using the Edmonton Symptom Assessment System (esas). Patients reporting cancerrelated fatigue (crf) were referred to the Supportive Care Program (scp) for individual interventions, including psychosocial, nutrition, and physiotherapy services. To ensure access for patients to receive guidance encompassing a variety of strategies for crf, a psychoeducational class was developed by an inter-professional team within the scp at necc. METHODS: The scp created an inter-professional committee to develop an interactive, psychoeducational class for cancer patients. The focus was multidimensional, supported with current evidence-based guidelines on fatigue, and developed with expertise from the fields of social work, neuropsychology, nutrition, and physiotherapy. Additional input was received from a group of cancer survivors. A electronic slide presentation and patient workbook highlight objectives, including understanding crf, learning management strategies, and building a personalized plan. The class is professionally facilitated by members of the scp and offered monthly at the necc. Patients are welcome to bring caregivers. Several strategies to promote the intervention included centre-wide distribution of posters and information sessions for oncology health care providers. RESULTS: An integrated psychoeducational intervention targeting crf was created and offered to patients of the necc beginning in spring 2012. Initial feedback via formal evaluation was overwhelmingly positive as it related to patients receiving evidence-based guidelines to self-manage crf. CONCLUSIONS: To improve accessibility for patients throughout Northeastern Ontario, this intervention will be offered by telemedicine in fall 2012. In future research, patient-reported outcomes for the management of crf will be tracked.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".