Televised medical talk shows--what they recommend and the evidence to support their recommendations: a prospective observational study
Bibliographic record
Abstract
OBJECTIVE: To determine the quality of health recommendations and claims made on popular medical talk shows. DESIGN: Prospective observational study. SETTING: Mainstream television media. SOURCES: Internationally syndicated medical television talk shows that air daily (The Dr Oz Show and The Doctors). INTERVENTIONS: Investigators randomly selected 40 episodes of each of The Dr Oz Show and The Doctors from early 2013 and identified and evaluated all recommendations made on each program. A group of experienced evidence reviewers independently searched for, and evaluated as a team, evidence to support 80 randomly selected recommendations from each show. MAIN OUTCOMES MEASURES: Percentage of recommendations that are supported by evidence as determined by a team of experienced evidence reviewers. Secondary outcomes included topics discussed, the number of recommendations made on the shows, and the types and details of recommendations that were made. RESULTS: We could find at least a case study or better evidence to support 54% (95% confidence interval 47% to 62%) of the 160 recommendations (80 from each show). For recommendations in The Dr Oz Show, evidence supported 46%, contradicted 15%, and was not found for 39%. For recommendations in The Doctors, evidence supported 63%, contradicted 14%, and was not found for 24%. Believable or somewhat believable evidence supported 33% of the recommendations on The Dr Oz Show and 53% on The Doctors. On average, The Dr Oz Show had 12 recommendations per episode and The Doctors 11. The most common recommendation category on The Dr Oz Show was dietary advice (39%) and on The Doctors was to consult a healthcare provider (18%). A specific benefit was described for 43% and 41% of the recommendations made on the shows respectively. The magnitude of benefit was described for 17% of the recommendations on The Dr Oz Show and 11% on The Doctors. Disclosure of potential conflicts of interest accompanied 0.4% of recommendations. CONCLUSIONS: Recommendations made on medical talk shows often lack adequate information on specific benefits or the magnitude of the effects of these benefits. Approximately half of the recommendations have either no evidence or are contradicted by the best available evidence. Potential conflicts of interest are rarely addressed. The public should be skeptical about recommendations made on medical talk shows. Additional details of methods used and changes made to study protocol.
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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 | 0.011 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".