Determinants of adherence to obesity medication: A narrative review
Bibliographic record
Abstract
The increasing prevalence of obesity, complex nature of this chronic disease, and risks of developing obesity-related comorbidities outline the need for sustainable and effective management for people living with obesity. In addition to behavioral interventions, obesity medications (OMs) are increasingly considered an integral part of management of people living with obesity. OM adherence is essential to achieve the health benefits of these medications. Adherence to medications, defined as the process by which patients take their medications as prescribed, is determined by a range of factors and can be broken down into phases: initiation, implementation, and persistence (the persistence phase includes discontinuation/stopping treatment). Obesity-specific challenges exist to optimize OM adherence, which may explain varying OM adherence compared with medication for other chronic diseases (diabetes, hypertension, dyslipidemia, and osteoporosis). However, lessons can be learned from other chronic diseases to improve OM adherence, for example from type 2 diabetes and hypertension. This review aims to provide practical guidance for identifying OM- and obesity-specific determinants of adherence and discusses adherence determinants per adherence phase and obesity management phase (weight gain, weight loss, and weight stabilization/regain). This practical guidance will assist with developing obesity-specific interventions to improve OM adherence. PRACTITIONER POINTS: OMs are increasingly considered as an integral part of obesity management; however, like with all chronic disease medications, low adherence to these medications is often observed, impacting their therapeutic effect. Adherence to obesity medication can be affected at any phase of obesity management (weight gain, weight loss, and weight stabilization/regain) so considering the disease phase can help identify potential reasons for low adherence. Future initiatives to improve adherence to obesity medication should be a key focus of discussions at each opportunity with healthcare professionals, including thorough evaluation and targeted education, all in a supportive and stigma-free manner.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".