Communicating with children and families about obesity and weight‐related topics: a scoping review of best practices
Bibliographic record
Abstract
BACKGROUND: Healthcare professionals have called for direction on how best to communicate about weight-related topics with children and families. Established scoping review methodology was used to answer the question: 'How can healthcare professionals best communicate with children and their families about obesity and weight-related topics?' METHODS: We searched four scientific databases, two grey literature repositories and 14 key journals (2005-2016). Inclusion criteria were (i) children up to and including 18 years of age and/or their parents; (ii) communication about healthy weight, overweight, obesity or healthy/active living; and (iii) healthcare setting. RESULTS: Thirty-two articles were included. Evidence-based best practices were largely absent from the literature, although the following guiding principles were identified: (i) include all stakeholders in discussions; (ii) raise the topic of weight and health early and regularly; (iii) use strengths-based language emphasizing health over weight; (iv) use collaborative goal-setting to engage children and parents and (v) augment discussions with appropriate tools and resources. Guidance on how to implement these principles and how to negotiate relevant contextual factors (e.g. age, culture and disability) is still needed. CONCLUSION: Despite agreement on a number of guiding principles, evidence-based weight-related communication best practices are lacking. Rigorous, empirical evaluations of communication approaches are urgently required, especially those that include children's perspectives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".