Primary health care providers' roles and responsibilities: A qualitative exploration of ‘<i>who does what</i>’ in the treatment and management of persons affected by obesity
Bibliographic record
Abstract
Obesity is now considered a national epidemic. Guidelines to manage persons who are overweight or affected by obesity are available but rarely relevant and applicable to primary care clinicians’ expertise. A qualitative descriptive narrative approach was used to identify challenges of primary care professionals in regard to the management of obesity. A literature review was conducted and input from experts was integrated with findings from interviews with Primary-Care Physicians, Physician Assistants, Nurse Practitioners, and Patient Advocates. Transcripts were coded using a thematic analysis approach. Two main challenges, associated with communication among the primary care team and with patients, emerged: (1) a lack of interprofessional integration and; (2) challenges in conceptualizing obesity as a chronic condition, contributing to lack of proactivity and communication in treating and managing persons who are overweight or affected by obesity. A causal factor is the dearth of standardized procedures, applicable at a primary care level. Lack of systematic procedures for the communication with, and management of, persons who are overweight or affected by obesity, and of clearly delineated roles of each primary care team member can undermine continuous care, and can contribute to a sense of disempowerment for both providers and the patients. Both would, thus, benefit from standardized clinical protocols. Behavioral training to the primary care team would also facilitate the communication with at-risk patients and would provide guidance to address the psychological and behavioral aspects of being overweight or affected by obesity in order to facilitate lifestyle changes.
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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 | 0.029 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".