Pediatric Central Nervous System Tumor Survivor and Caregiver Experiences with Multidisciplinary Telehealth
Bibliographic record
Abstract
Abstract Purpose: Telehealth use to facilitate cancer survivorship care is accelerating; however, patient satisfaction and barriers to facilitation have not been studied amongst pediatric central nervous system (CNS) tumor survivors. We assessed the telehealth experiences of survivors and caregivers in the Pediatric Neuro-Oncology Outcomes Clinic at Dana-Farber/ Boston Children’s Hospital. Methods: Cross-sectional study of completed surveys among patients and caregivers with ≥ 1 telehealth multidisciplinary survivorship appointment from January 2021 through March 2022. Results: Thirty-three adult survivors and 41 caregivers participated. The majority agreed or strongly agreed that telehealth visits started on time [65/67 (97%)], scheduling was convenient [59/61 (97%)], clinician’s explanations were easy-to-understand [59/61 (97%)], listened carefully/addressed concerns [56/60 (93%)], and spent enough time with them [56/59 (95%)]. However, only 58% (n=35/60) of respondents agreed or strongly agreed they would like to continue with telehealth and 48% (n=32/67) agreed telehealth was as effective as in person office visits. Adult survivors were more likely than caregivers to prefer office visits for personal connection [23/32 (72%) vs 18/39 (46%), p=0.027]. Conclusion: Offering telehealth multi-disciplinary services may provide more efficient and accessible care for a subset of pediatric CNS tumor survivors. Despite some advantages, patients and caregivers were divided on whether they would like to continue with telehealth and whether telehealth was as effective as office visits. To improve survivor and caregiver satisfaction, initiatives to refine patient selection as well as enhance personal communication through telehealth systems should be undertaken.
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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 | 0.005 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".