‘Gut health’ and the microbiome in the popular press: a content analysis
Bibliographic record
Abstract
OBJECTIVE: Extensive research and important discoveries on the microbiome have led to a growth in media coverage. This study explores how the microbiome has been portrayed in press sources popular among American and Canadian audiences. DESIGN: Content analysis. METHODS: Using the FACTIVA Database, we compiled a finalised data set of (N=830) articles from press sources popular among American and Canadian audiences which were published between 1 January 2018 and 11 October 2019 and which contained at least one of the following search terms: 'microbiome', 'microbiota', 'gut health', 'healthy gut', 'unhealthy gut', 'gut bacteria', 'probiotic' or 'probiotics.' We performed content analysis on the articles to determine how often ideas of the microbiome were presented as beneficial, in which health contexts, and whether actions could be taken to reap stated benefits. We compared this portrayal of benefits with critical portrayals of the microbiome. RESULTS: Almost all of the articles (94%) described health benefits associated with the microbiome with many (79%) describing actions which could be taken to reap stated benefits. Articles most often described health benefits in more broad, general context (34%) and most commonly outlined actions related to food/drug (45%) as well as probiotic (27%) intake. Only some articles (19%) provided microbiome-related critiques or limitations. Some of the articles (22%) were focused on highlighting specific research developments, and in these articles, critiques or limitations were more common. CONCLUSIONS: Articles discussing the microbiome published for American and Canadian audiences typically hype the microbiome's impact and popularise gut health trends while only offering a little in the way of communicating microbiome science. Lifestyle choices including nutrition, taking probiotics, stress management and exercise are often promoted as means of reaping the microbiome-related health benefits. The trend of actionable 'gut health' is foregrounded over more evidence-based descriptions of microbiome science.
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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 | 0.019 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.044 | 0.061 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".