45-LB: A Qualitative Study to Understand Why People Living with Obesity and General/Family Practitioners Experience Therapeutic Inertia in Obesity
Bibliographic record
Abstract
Medical nutrition therapy and physical activity are often used exclusively for obesity treatment despite the availability of effective adjunctive interventions, including psychological intervention, pharmacological therapy, and bariatric surgery. We conducted a qualitative study through interviews with people living with obesity (PwO) and general/family practitioners (GP/FPs) to better understand the factors contributing to healthcare decision-making and therapeutic inertia in obesity management. Phone interviews were conducted by the same investigator using discussion guides informed by the Theoretical Domains Framework (TDF) . Eligibility criteria for PwO included having a BMI over 30 kg/m2. A total of 20 PwO and 20 GP/FPs across Canada were interviewed with representation across gender and ethnicity. PwO also varied in obesity classification and experience with management strategies. GP/FPs varied in practice type, local community, and awareness of the 2020 Canadian Adult Obesity Clinical Practice Guidelines. Themes related to therapeutic inertia mapped to all 14 TDF domains. Both PwO and GP/FPs often perceived obesity to be a secondary health priority that is associated with negative emotions, which had pervasive influence on obesity management. PwO were hesitant to explore new strategies due to financial barriers, access to support, and concerns of adverse side-effects, effectiveness, and sustainability of interventions that support eating and physical activity behavioral changes. GP/FPs were limited in time and resources, and were hesitant to recommend specific treatments due to concerns of risks, effectiveness, and accessibility. GP/FPs were also hesitant to make referrals due to skepticism of whether other healthcare providers can provide better care. Future research will validate these themes in a larger, national sample of PwO and GP/FPs to understand how individuals can overcome the therapeutic inertia. Disclosure D. C. Lau: Advisory Panel; Amgen Canada, Novartis Canada, Novo Nordisk Canada Inc., Board Member; Canadian Association of Bariatric Physicians and Surgeons, Consultant; Pfizer Inc., Viatris Inc., Research Support; Novo Nordisk Canada Inc., Speaker’s Bureau; AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Canadian Collaborative Research Network, CME at Sea, Eli Lilly and Company, HLS Therapeutics Inc., Novo Nordisk Canada Inc., Obesity Canada. I. Patton: None. R. Lavji: Employee; Novo Nordisk Canada Inc., Stock/Shareholder; Moderna, Inc., Novo Nordisk, Pfizer Inc. A. Belloum: None. G. Ng: Other Relationship; Novo Nordisk Canada Inc. R. Modi: Advisory Panel; Bausch Health, Canada, Eli Lilly and Company, Novo Nordisk Canada Inc., Other Relationship; Takeda Canada.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".