Nurses' and Nursing Students' Perceptions Toward People Living with Obesity: A Scoping Review Protocol
Bibliographic record
Abstract
Introduction: There is significant and pervasive weight bias, weight stigma, and weight-based discrimination everywhere today, even in healthcare settings. Studies have shown that health care professionals (HCPs) hold negative perceptions toward people living with obesity (PLO), which results in heightened health risks for patients. Nurses play a central role in health promotion and the health management of PLO. Thus, identifying nurses' and nursing students' perceptions toward PLO within healthcare practice or educational contexts is paramount to consider further exploratory and intervention studies. Objective: We aim to review and map nurses' and nursing students' perceptions toward PLO from available literature. Method: A search of MEDLINE via PubMed, CINAHL Plus with Full Text (EBSCOhost), and PsycINFO (OVID) will be conducted to identify relevant studies in English, French, Spanish, Portuguese, or Italian on nurses' and nursing students' weight bias. The period covered will be from January 1, 2005, onward, including those available up until our scheduled search in January 2024. Two independent reviewers will conduct screening, study selection, and data extraction. Data will be charted according to the study design, the research setting, years and regions of publication, concepts, and use of theoretical models. The results will be summarized and reported, identifying implications for nursing research and practice. Discussion and Research Spin-offs: This scoping review will inform nursing research and facilitate the development of educational and clinical tools aimed at preventing and reducing weight bias among nurses to promote nursing and interdisciplinary care that upholds principles of equity, diversity, and inclusion.
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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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".