Nurses’ Role in Obesity Management in Adults in Primary Healthcare Settings Worldwide: A Scoping Review
Bibliographic record
Abstract
Obesity is a chronic, prevalent, and complex health condition that adversely impairs physical and mental health. The World Health Organization calls for integrating obesity care into existing chronic disease management programs within primary healthcare services. This scoping review aimed to examine registered nurses' roles in the primary healthcare management of individuals with obesity. A scoping review was conducted using the Johanna Briggs Institute methodology framework. Thematic analysis was used to identify and categorize nurses' roles in primary healthcare obesity management of adults. Of 1142 documents included in this review, 15 papers met the inclusion criteria. Thematic analysis yielded the following six themes representing nurses' major roles: patient-centred care, patient assessments, therapeutic interventions, care management, patient education, and professional development. This review identified that the literature on nurses' roles primarily described their focus on lifestyle interventions (mainly nutrition and physical activity), anthropometric measurements, health planning, goal setting, supportive care, monitoring progress, and arranging follow-up. The Discussion highlights the importance of determining RN knowledge gaps and biases. More research is required to determine the need for additional RN pre-and or post-education related to obesity as a complex chronic disease.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".