Relationship between paediatricians and the pharmaceutical and commercial milk formula industries: an explanatory mixed methods study
Bibliographic record
Abstract
OBJECTIVE: To describe and understand relationships between paediatricians and industry in Colombia. METHODS: Mixed methods study composed of three phases: quantitative (cross-sectional study, e-survey to paediatricians) describing interaction patterns and evaluating the factors that explain the perceived need for industry visits to health services and their influence through multivariate analyses; qualitative (grounded theory study, semistructured interviews) to create an explanatory theory; and an integrative phase (mixed methods explanatory study). RESULTS: We surveyed 218 paediatricians (mean age, 45.2 years), nearly all of whom interacted with industry monthly, mainly with the commercial milk- formula industry (CMFI). Sponsored trips to attend conferences and not having teaching activities were associated with a perception of the potential effects of the trips on prescribing practices. Moreover, being sponsored for an international trip was associated with the perception of indispensability of industry visits for maintaining continuing medical education (CME). In the qualitative phase, four phenomena emerged; two related to the quantitative findings: 'Paediatrician's dependence on industry for CME', and 'Colombian health context facilitates a closer relationship between paediatricians and industry'. Two emerged as explaining factors: 'Normalisation of paediatrician-industry interaction' and 'Paediatrician's prescriptive power: mediator between their conflict of interest with industry and patients'. The integration showed how the qualitative phase explained the quantitative findings. CONCLUSIONS: Most paediatricians frequently interact with industry, mainly with the CMFI, and this is perceived as necessary for CME. The normalisation of the paediatrician-industry interaction leads to the underestimation and invisibility of its effects, which fosters the notion of its necessity for the paediatric field.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".