Family–health professional relations in pediatric weight management: an integrative review
Bibliographic record
Abstract
In this integrative review, we examined contemporary literature in pediatric weight management to identify characteristics that contribute to the relationship between families and health professionals and describe how these qualities can inform healthcare practices for obese children and families receiving weight management care. We searched literature published from 1980 to 2010 in three electronic databases (MEDLINE, PsycINFO and CINAHL). Twenty-four articles identified family-health professional relationships were influenced by the following: health professionals' weight-related discussions and approaches to care; and parents' preferences regarding weight-related terminology and expectations of healthcare delivery. There was considerable methodological heterogeneity in the types of reports (i.e. qualitative studies, review articles, commentaries) included in this review. Overall, the findings have implications for establishing a positive clinical relationship between families and health professionals, which include being sensitive when discussing weight-related issues, using euphemisms when talking about obesity, demonstrating a non-judgmental and supportive attitude and including the family (children and parents) in healthcare interactions. Experimental research, clinical interventions and longitudinal studies are needed to build on the current evidence to determine how best to establish a collaborative partnership between families and health professionals and whether such a partnership improves treatment adherence, reduces intervention attrition and enhances pediatric weight management success.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".