Online Ambassador Visits for Hospitalized Children With Cancer: Qualitative Evaluation of Implementation
Bibliographic record
Abstract
BACKGROUND: Children with cancer or cancer-like disease risk treatment-related isolation, which can negatively impact their peer relationships and social competencies and exacerbate their loneliness. During the COVID-19 pandemic, increased online socialization became the new normal imposed by national isolation guidelines. To adhere to the treatment-related isolation guidelines, children with cancer were offered online classmate "ambassador" visits during hospitalization. OBJECTIVE: This study aimed to identify facilitators and barriers to online classmate "ambassador" visits during children with cancer's hospitalization through a qualitative descriptive process evaluation using the Consolidated Framework for Implementation Research. METHODS: From January to April 2022, we conducted 39 individual semistructured interviews with hospitalized children (n=16), their classmates (n=16), teachers from their schools (n=3), and study nurses (n=4) from involved hospitals. Most interviews (n=37, 95%) were conducted online using Microsoft Teams or Google Meet, while 2 (5%) interviews were conducted in person at the participants' residences. This approach allowed us to gain a broad understanding of the facilitators and barriers to online ambassador visits. RESULTS: We identified four themes: (1) working together, (2) ensuring participation, (3) staying connected, and (4) together online. The themes are described in terms of facilitators and barriers to online ambassador visits with 3 Consolidated Framework for Implementation Research domains: innovation, individuals, and the implementation process. CONCLUSIONS: Addressing the social needs of hospitalized children through online visits with their classmates may be relevant when one-on-one meetings are problematic. The online visits are highly dependent on collaboration between study nurses and teachers and assessing the needs of the hospitalized children. While a high degree of adult engagement and a stable internet connection are pivotal, these online visits can promote much-needed social interaction between children across physical settings.
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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 | 0.044 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".