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Record W2098449208 · doi:10.1186/1472-6939-15-58

Ocular gene transfer in the spotlight: implications of newspaper content for clinical communications

2014· article· en· W2098449208 on OpenAlexafffundabout
Shelly Benjaminy, Tania Bubela

Bibliographic record

VenueBMC Medical Ethics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsNewspaperFraming (construction)TimelinePsychological interventionClinical trialPhilosophy of medicineMedicinePublic relationsPolitical scienceAlternative medicineLawHistoryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Ocular gene transfer clinical trials are raising hopes for blindness treatments and attracting media attention. News media provide an accessible health information source for patients and the public, but are often criticized for overemphasizing benefits and underplaying risks of novel biomedical interventions. Overly optimistic portrayals of unproven interventions may influence public and patient expectations; the latter may cause patients to downplay risks and over-emphasize benefits, with implications for informed consent for clinical trials. We analyze the news media communications landscape about ocular gene transfer and make recommendations for improving communications between clinicians and potential trial participants in light of media coverage. METHODS: We analyzed leading newspaper articles about ocular gene transfer (1990-2012) from United States (n = 55), Canada (n = 26), and United Kingdom (n = 77) from Factiva and Canadian Newsstand databases using pre-defined coding categories. We evaluated the content of newspaper articles about ocular gene transfer for hereditary retinopathies, exploring representations of framing techniques, research design, risks/benefits, and translational timelines. RESULTS: The dominant frame in 61% of stories was a celebration of progress, followed by human-interest in 30% of stories. Missing from the positive frames were explanations of research design; articles conflated clinical research with treatment. Conflicts-of-interest and funding sources were similarly omitted. Attention was directed to the benefits of gene transfer, while risks were only reported in 43% of articles. A range of visual outcomes was described from slowing vision loss to cure, but the latter was the most frequently represented even though it is clinically infeasible. Despite the prominence of visual benefit portrayals, 87% of the articles failed to provide timelines for the commencement of clinical trials or for clinical implementation. CONCLUSIONS: Our analysis confirms that despite many initiatives to improve media communications about experimental biotechnologies, media coverage remains overly optimistic and omits important information. In light of these findings, our recommendations focus on the need for clinicians account for media coverage in their communications with patients, especially in the context of clinical trial enrolment. The development of evidence-based communication strategies will facilitate informed consent and promote the ethical translation of this biotechnology.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.199
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.199
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0130.020
Science and technology studies0.0020.003
Scholarly communication0.0090.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.158
GPT teacher head0.457
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2014
Admission routes3
Has abstractyes

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