Nutrition education and cooking workshops for families of children with cancer: a feasibility study
Bibliographic record
Abstract
Abstract Background Perturbations of food intake are common in children with cancer and are often caused by changes in the sense of taste and nausea. The VIE (Valorization, Implication, Education) project proposes family-based nutrition and cooking education workshops during the cancer treatments. Process evaluation during implementation allows to assess if the intervention was delivered as planned and to determine its barriers and facilitators. The objective was to describe the implementation process of a nutrition education and cooking workshop program for families of children during active treatment of cancer in a non-randomized non-controlled feasibility study. Methods Six open-to-all in-hospital workshops were offered on a weekly basis during a one-year implementation phase. Multiple data collection methods were used including field notes, survey, questionnaires and activity reports. Data were collected from the facilitator and families from the Division of Hematology-Oncology. Survey respondents were mostly mothers (n=19, 73%) and the mean time since child’s diagnosis was 7.98 (± 0.81) months. Qualitative data were codified using hybrid content analysis. The first deductive analysis was based on the Steckler & Linnan concepts. Subthemes were then identified inductively. Quantitative data were presented with descriptive statistics. Results Attendance was low and 71% of the planned workshops were cancelled. The principal barriers to participation referred the child’s medical condition, parental presence at the child’s bedside and challenges related to logistics and time management. The level of interest in the topics addressed was found high or very high for 92% of the participants. The themes that were perceived as the most useful by parents were related to the child’ specific medical condition. Conclusions Despite high interest, workshops in a face-to-face format are poorly feasible in the context of pediatric oncology. Web-based video is a promising avenue to increase accessibility of the nutritional information provided in the workshops. According to our results, the workshops are now offered online as short video capsules. We believe that this will address the barriers encountered by families, provide a better access to information and evaluate of the impact of the intervention. Key words: nutrition workshops, culinary demonstration, process evaluation, childhood cancer, parents
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".