MétaCan
Menu
Back to cohort
Record W1740514563 · doi:10.3109/10884600009040632

Medical and Nursing Student's Perceptions of Obesity

2000· article· en· W1740514563 on OpenAlexaffabout
Betty E. A. Petrich

Bibliographic record

VenueJournal of Addictions Nursing · 2000
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsVictorian Order of Nurses
Fundersnot available
KeywordsOverweightTheme (computing)ObesityPerceptionPsychologyQualitative researchNursingDescriptive researchMedicineFamily medicineMedical educationGerontologySociology

Abstract

fetched live from OpenAlex

This purpose of this qualitative, descriptive study was to describe the perceptions of medical and nursing students towards obesity. This study utilized King's (1981, 1983, 1986, 1989, 1990, 1991, 1992, 1994, 1995, 1996, 1997a, 1997b) ideas and nursing theory as a guide for achieving this purpose. The research was conducted with 28 medical and 102 nursing students attending three universities in Southern Ontario and one in Western New York. Students were given a survey containing six open-ended questions. The research objectives were answered by analyzing the themes that originated from the student's responses to the survey questions. Although the study findings identified similarities and differences in perspectives between the two groups of students, the theme that appeared most prevalent throughout student's writings was feeeling repulsed at the appearance of someone whom they perceived to be overweight. Both groups of students also perceived obesity as unhealthy and assumed that individuals who were overweight were inactive, lazy, and lacked self control. Further, the study's findings indicated that the majority of both groups of students had received minimal instruction on the etiology and treatment of obesity. Findings further demonstrated that students had limited clinical experiences in caring for, and/or treating patients who are overweight or obese.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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.

Opus teacher head0.036
GPT teacher head0.482
Teacher spread0.446 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Addictions NursingSame topicObesity and Health PracticesFrench-language works237,207