Biological, psychological and social processes that explain celebrities’ influence on patients’ health-related behaviors
Bibliographic record
Abstract
BACKGROUND: Celebrities can have substantial influence as medical advisors. However, their impact on public health is equivocal: depending on the advice's validity and applicability, celebrity engagements can benefit or hinder efforts to educate patients on evidence-based practices and improve their health literacy. This meta-narrative analysis synthesizes multiple disciplinary insights explaining the influence celebrities have on people's health-related behaviors. METHODS: Systematic searches of electronic databases BusinessSource Complete, Communication & Mass Media Complete, Humanities Abstracts, ProQuest Political Science, PsycINFO, PubMed, and Sociology Abstracts were conducted. Retrieved articles were used to inform a conceptual analysis of the possible processes accounting for the substantial influence celebrities may have as medical advisors. RESULTS: Fourteen mechanisms of celebrity influence were identified. According to the economics literature, celebrities distinguish endorsed items from competitors and can catalyze herd behavior. Marketing studies tell us that celebrities' characteristics are transferred to endorsed products, and that the most successful celebrity advisors are those viewed as credible, a perception they can create with their success. Neuroscience research supports these explanations, finding that celebrity endorsements activate brain regions involved in making positive associations, building trust and encoding memories. The psychology literature tells us that celebrity advice conditions people to react positively toward it. People are also inclined to follow celebrities if the advice matches their self-conceptions or if not following it would generate cognitive dissonance. Sociology explains how celebrities' advice spreads through social networks, how their influence is a manifestation of people's desire to acquire celebrities' social capital, and how they affect the ways people acquire and interpret health information. CONCLUSION: There are clear and deeply rooted biological, psychological and social processes that explain how celebrities influence people's health behaviors. With a better understanding of this phenomenon, medical professionals can work to ensure that it is harnessed for good rather than abused for harm. Physicians can discuss with their patients the validity of celebrity advice and share more credible sources of health information. Public health practitioners can debunk celebrities offering unsubstantiated advice or receiving inappropriate financial compensation, and should collaborate with well-meaning celebrities, leveraging their influence to disseminate medical practices of demonstrated benefit.
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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 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.004 | 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".