A scoping review of research on complementary and alternative medicine (CAM) and the mass media: Looking back, moving forward
Bibliographic record
Abstract
BACKGROUND: The use of complementary and alternative medicine (CAM) has become more common in Western developed countries in recent years, as has media reporting on CAM and related issues. Correspondingly, media reports are a primary information source regarding decisions to use CAM. Research on CAM related media reports is becoming increasingly relevant and important; however, identifying key concepts to guide future research is problematic due to the dispersed nature of completed research in this field. A scoping review was conducted to: 1) determine the amount, focus and nature of research on CAM and the mass media; and 2) summarize and disseminate related research results. METHODS: The main phases were: 1) searching for relevant studies; 2) selecting studies based on pre-defined inclusion criteria; 3) extracting data; and 4) collating, summarizing and reporting the results. RESULTS: Of 4,454 studies identified through various search strategies, 16 were relevant to our objectives and included in a final sample. CAM and media research has focused primarily on print media coverage of a range of CAM therapies, although only a few studies articulated differences within the range of therapies surveyed. Research has been developed through a variety of disciplinary perspectives, with a focus on representation research. The research reviewed suggests that journalists draw on a range of sources to prepare media reports, although most commonly they cite conventional (versus CAM) sources and personal anecdotes. The tone of media reports appears generally positive, which may be related to a lack of reporting on issues related to risk and safety. Finally, a variety of discourses within media representations of CAM are apparent that each appeal to a specific audience through resonance with their specific concerns. CONCLUSION: Research on CAM and the mass media spans multiple disciplines and strategies of inquiry; however, despite the diversity in approach, it is clear that issues related to production and reception of media content are in need of research attention. To address the varied issues in a comprehensive manner, future research needs to be collaborative, involving researchers across disciplines, journalists and CAM users.
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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 | 0.037 | 0.133 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.045 | 0.046 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".