Using IT to Improve Outcomes for Children Living With Cancer (SyMon-SAYS): Protocol for a Single-Institution Waitlist Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Children and adolescents with cancer may experience multiple disease- and treatment-related symptoms that negatively affect health-related quality of life. Routine symptom surveillance thus constitutes an important component of supportive care in pediatric oncology. The Symptom Monitoring and Systematic Assessment and Reporting System in Young Survivors (SyMon-SAYS) system will administer, score, interpret, and display the results of symptom assessments captured weekly using patient-reported outcomes presented via the electronic health record (EHR) portal between clinic visits in oncology ambulatory settings, when patients are likely to be more symptomatic. This study is testing a digital system for routine symptom surveillance that includes EHR-based reports to clinicians and alerts for severe symptoms. OBJECTIVE: In this randomized trial, we are examining the effects of the SyMon-SAYS system on perceived barriers to symptom management, self-efficacy, and symptom severity. Better self-management and timely clinical intervention to address symptoms promote adherence to treatment plans, strengthen child and parent self-efficacy, improve interactions between children, parents, and their clinical providers, and optimize clinical outcomes. METHODS: The SyMon-SAYS system is integrated into the EHR to streamline the presentation of symptom scores and delivery of alerts for severe symptoms to clinicians using EHR (Epic) messaging functionalities. Children (aged 8 to 17 years) complete the weekly symptom assessment and review the symptom report by logging into the patient portal (Epic MyChart). This single-institution waitlist randomized controlled trial is recruiting 200 children (aged 8-17 years) with cancer and their parents, guardians, or caregivers. Participating dyads are randomly assigned to receive the intervention over 16 weeks (Group A: 16-week SyMon-SAYS intervention; Group B: 8-week usual care and then an 8-week SyMon-SAYS intervention). Analyses will (1) evaluate the efficacy of SyMon-SAYS at week 8 and the maintenance of those effects at week 16; (2) evaluate factors associated with those efficacy outcomes, including contextual factors, adherence to the SyMon-SAYS intervention, demographic characteristics, and clinical factors; and (3) evaluate predictors of adherence to the SyMon-SAYS intervention and preference of SyMon-SAYS versus usual care. RESULTS: Data collection is currently in progress. We hypothesize that at 8 weeks, those receiving the SyMon-SAYS intervention will report decreased parent-perceived barriers to managing their children's symptoms, increased parent and child self-efficacy, decreased child symptom burden, and ultimately better child health-related quality of life, compared to waitlist controls. Feasibility, acceptability, and engagement from the perspectives of the children with cancer, their parents, and their clinicians will be examined using mixed methods. CONCLUSIONS: We anticipate that this system will facilitate prompt identification of problematic symptoms. Additionally, we hypothesize that with the availability of graphical symptom reports over time, and timely provider responses, children or parents will become better informed and take an active role in managing their symptoms, which will further improve clinical outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04789720; https://clinicaltrials.gov/study/NCT04789720. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50993.
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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 | 0.029 | 0.027 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.085 | 0.013 |
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".