Financial relationships between patient and consumer representatives and the health industry: A systematic review
Bibliographic record
Abstract
BACKGROUND: Patients and consumers are increasingly engaged in health policymaking, research and drug regulation. Having financial relationships with the health industry creates situations of conflicts of interest (COI) and might compromise their meaningful and unbiased participation. OBJECTIVE: To synthesize available evidence on the financial relationships between the health industry and patient and consumer representatives and their organizations. METHODS: We systematically searched MEDLINE and EMBASE. We selected studies and abstracted data in duplicate and independently. We reported on outcomes related to financial relationships of individuals with, and/or funding of organizations by the health industry. RESULTS: We identified a total of 14 510 unique citations, of which 24 reports of 23 studies were eligible. Three studies (13%) addressed the financial relationship of patient and consumer representatives with the health industry. Of these, two examined the proportion of public speakers in drug regulatory processes who have financial relationships; the proportions in the two studies were 25% and 19% respectively. Twenty studies (87%) addressed funding of patient and consumer organizations. The median proportion of organizations that reported funding from the health industry was 62% (IQR: 34%-69%) in questionnaire surveys, and 75% (IQR: 58%-85%) in surveys of their websites. Among organizations for which there was evidence of industry funding, a median proportion of 29% (IQR: 27%-44%) acknowledged on their websites receiving that funding. CONCLUSION: Financial relationships between the health industry and patient and consumer representatives and their organizations are common and may not be disclosed. Stricter regulation on disclosure and management is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.008 |
| 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".