Nutrition care practices of primary care providers for weight management in multidisciplinary primary care settings in Ontario, Canada - a qualitative study
Bibliographic record
Abstract
BACKGROUND: Despite the recommended guidelines on addressing diet for the management and prevention of obesity in primary care, the literature highlights that their implementation has been suboptimal. In this paper, we provide an in-depth understanding of current nutrition-related weight management practices of primary care providers (PCPs) working in relatively new multidisciplinary health care settings in Ontario. METHODS: Three types of multidisciplinary primary care settings were included (2 Family Health Teams, 3 Community Health Centres and 1 Nurse Practitioner-Led Clinic). Participants (n = 20) included in this study were nurse practitioners (n = 13) and family physicians (n = 7) supporting care for adult patients (18 years or older). In-depth interviews were transcribed, coded and the content was analyzed using an integrated approach. RESULTS: Our analysis showed that most PCPs used anthropometric measures such as weight for screening patients who would benefit from nutrition counselling with a dietitian. The topic of nutrition was generally brought up either during physical examinations, when patients were diagnosed with a chronic disease, or when blood markers were out of normal range. Participants also mentioned that physical examinations are no longer occurring annually, with most PCPs offering episodic care. All participants reported utilizing dietetic referrals, noting the enablers for providing the referral, which included access to an on-site dietitian. Nonetheless, dietetic referrals were mostly used when patients had an obesity-related co-morbidity. Participants mentioned that healthy eating advice was reinforced during follow-up visits with patients only when there was enough time to do so. Electronic Health Records (EHRs) were utilized to facilitate message reinforcement by PCPs, who perceived EHRs to be helpful for viewing what was discussed in the session with the dietitian. CONCLUSIONS: PCPs mostly used objective measures to screen for patients who would benefit from nutrition counselling rather than diet assessment, which undermines the importance of dietary intake and overemphasizes weight. With physical examinations occurring less frequently, there will be additional missed opportunities for addressing nutrition-related concerns. The presence of a dietitian on site allowed for PCPs to refer patients to nutrition counselling. Having sufficient time during medical visits and EHRs seemed to facilitate message reinforcement by PCPs in follow-up visits with patients.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".