Public health nurse referrals for paediatric weight management: A nested mixed‐methods study
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To (a) characterise and determine proportions of referred and enrolled children and (b) explore public health nurses' (PHNs) experiences, perspectives and recommendations regarding a new nurse-led referral pathway for paediatric weight management. BACKGROUND: Children with obesity and their families in Canada access specialised services for obesity management through physician referral. Since this requirement can prevent timely access to health services, we established and tested a referral pathway whereby PHNs directly refer children to specialised care for obesity management. DESIGN: Nested mixed-methods study reported using GRAMMS. METHOD: Our research study included children (2-17 years of age; body mass index ≥85th percentile) referred by a PHN to the Pediatric Centre for Weight and Health (PCWH; Stollery Children's Hospital, Edmonton, Alberta, Canada) from April 2017-September 2018. We summarised referral and enrolment data using descriptive statistics and conducted one-on-one, semi-structured telephone interviews with PHNs; interviews were audio-recorded, transcribed verbatim, managed using NVivo 12 and analysed by two independent reviewers using content analysis. RESULTS: Our sample included 79 referred children (4.4 ± 1.8 years old; 3.4 ± 1.3 BMI z-score; 52.7% male), of which 47 (59.5%) enrolled in care. PHNs' (n = 11) experiences, perspectives and recommendations regarding the new referral pathway were grouped into four categories: (a) practicality of the referral pathway (e.g., simple and straightforward), (b) utility of the referral pathway (e.g., economic and timesaving), (c) uptake of the referral pathway (e.g., physician's influence) and (d) recommendations to improve the referral pathway (e.g., having electronic access to the referral form). CONCLUSIONS: A PHN-specific referral pathway led most children and families to enrol in paediatric weight management and overall was perceived as acceptable and appropriate among PHNs. RELEVANCE TO CLINICAL PRACTICE: Our results highlight the valuable role that PHNs can play in directly referring children to specialised services for weight management. This pathway has the potential to reduce wait times and enhance treatment enrolment.
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".