Evaluation of a Remote Symptom Assessment and Management (SAM) System for People Receiving Adjuvant Chemotherapy for Breast or Colorectal Cancer: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: The Symptom Assessment and Management (SAM) program is a structured, online, nurse-supported intervention to support symptom self-management in people receiving adjuvant chemotherapy post surgery for breast or colorectal cancer. OBJECTIVE: The objective of this study was to describe the development, implementation strategy, and evaluation of the SAM system. METHODS: The development of the SAM program involved 3 phases. In phase 1, the web app was developed through consultation with consumers and clinicians and of the literature to ensure that the system was evidence-based and reflected the realities of receiving treatment and supporting patients through treatment. In phase 2, 7 participants recorded the severity of 6 symptoms daily over the course of 1 cycle of chemotherapy. In phase 3, 17 participants recorded their symptoms daily over the course of 3 cycles of chemotherapy. Once symptoms were recorded, participants received immediate feedback on the severity of their symptoms and self-management recommendations, which could include seeking immediate medical attention. Data on quality of life, symptom burden, anxiety and depression, distress, and self-efficacy were collected during treatment; participants' perceptions of the SAM program were evaluated following participation via interview. RESULTS: The outcomes of the SAM project include the development of a system that is reliable and easy to use and navigate. Participants reported benefits related to using the SAM program that included feeling more in control of managing their symptoms and feeling reassured. Engagement with the system on a daily basis was variable, with some participants completing the symptom tracker daily and others engaging some of the time. The feedback from all participants was that the system was easy to navigate and the information was relevant and supportive. CONCLUSIONS: The SAM program has the potential to enhance the management of symptoms for people receiving chemotherapy treatment. The system creates an accurate repository of symptoms that can be accessed easily and highlight patterns in symptom experience. These can be shared with clinicians, with patient permission, to inform and support treatment plans. The potential to predict the risk of developing severe symptoms can be developed to anticipate the need for care and support. Further considerations on how to increase engagement with the system, the value of the system for people diagnosed with other tumor types and treatment regimes, and the incorporation of the system into everyday clinical practice are needed.
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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 | 0.000 |
| 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".