Utilization of the Medical Research Council Evaluation Framework in the Development of Technology for Symptom Management
Bibliographic record
Abstract
BACKGROUND: Technology is becoming an important medium for supporting patients in health care. However, successful application depends on user acceptability. The Advanced Symptom Management System (ASyMS) involves patients reporting cancer chemotherapy-related symptoms using mobile phone technology. OBJECTIVE: The aim of this article was to report a study of how young people were involved in the development of ASyMS using the Medical Research Council framework for evaluating complex interventions. METHODS: A convenience sample of young people aged 13 to 18 years undergoing cancer chemotherapy were recruited from 2 principal cancer treatment centers in London. RESULTS: In phase 1, young people selected 5 symptoms from an adapted version of the Memorial Symptom Assessment Scale that were most important to them. In phase 2, young people completed the ASyMS-YG PDA (personal digital assistant) questionnaire daily on days 1 to 14 of a cycle of chemotherapy and pre/post-use questionnaires. In phase 1, 5 young people chose diarrhea, nausea, vomiting, constipation, and weight loss as the most important symptoms. In phase 2, 25 young people reported positively to using PDA technology, found ASyMS-YG simple and easy to complete, and liked that they were monitored at home. In addition to the 5 core symptoms, the ASyMS-YG reports showed the number (n = 37) of other symptoms young people experienced. CONCLUSIONS: This early development work indicates the acceptability of ASyMS-YG and has informed an exploratory trial (phase 3) and randomized controlled trial (stage 4). IMPLICATIONS FOR PRACTICE: This study reaffirms the importance of promoting communication between young people and health professionals.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".