Kids With Cancer Still Need School: Addressing Communication Gaps Regarding Neurocognitive Late Effects with a Massive Open Online Course (Preprint)
Bibliographic record
Abstract
BACKGROUND Pediatric cancer survivors are at high risk for neurocognitive late effects that hinder active school participation. Obtaining needed educational supports can improve outcomes, yet evidence suggests that oncology providers are not well prepared to discuss signs and symptoms of cognitive late effects with families, limiting patients’ access to support. Online continuing medical education (CME) offers a scalable and accessible strategy to address these knowledge gaps globally. OBJECTIVE The objective of this study was to develop, launch, and evaluate a massive open online course (MOOC), Kids with Cancer Still Need School, aimed at enhancing provider understanding of neurocognitive late effects of pediatric cancer and their relation to educational participation. METHODS The course was developed using evidence synthesis and parent interviews, iteratively refined through stakeholder feedback, and piloted in live CME sessions before dissemination to the pediatric oncology community. Hosted on Coursera, the MOOC consists of four modules covering pathophysiology, communication, school supports, and use of “Return-to-School Roadmaps.” The evaluation plan compared course enrollment, completion, and pre- to posttest knowledge gains. In a local subsample, medical documentation and neuropsychology referral behaviors were assessed. Knowledge change was analyzed using repeated-measures ANOVA. RESULTS Between March 2021 and July 2025, 629 actively interacted with course material, and 155 completed the course, yielding a 24.6% completion rate. Learners represented 81 countries, led by the United Kingdom (39%), United States (21%), India (13%), Philippines (9%), and Canada (5%). Among 315 learners who completed at least 6 of 10 knowledge items, 88 completed both pre- and posttests. Knowledge scores improved significantly from M=3.75 (SD=1.66) to M=5.84 (SD=2.45); F(1,87)=37.81; P<.001; partial η²=.303. In a local subsample, practice change was supported by 80% compliance with medical documentation and a 42% increase in neuropsychology referrals. CONCLUSIONS These data offer an example of a successful parent/provider stakeholder collaboration that achieved high completion, global reach, and measurable improvements in provider knowledge and practice. Completion of the freely accessible Kids with Cancer CME exceeded typical MOOC rates of 5%–10% overall and 36%–40% in CE/CME courses. Findings suggest that scalable, stakeholder-informed educational interventions can enhance provider-family communication and promote neurocognitive care in pediatric oncology. CLINICALTRIAL Not applicable
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".