ArticleFrontiers in public health2023
The moderating role of perceived health risks on the acceptance of genetically modified food.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Public perception of genetically modified organisms (GMOs) in Montenegro: insight for sustainable biotechnology and policy development.GM crops & food · 2026Article
- Understanding Consumer Acceptance of Genetically Modified Foods: A Theory of Planned Behavior-Brand Equity-Sociodemographic Interactions.Foods (Basel, Switzerland) · 2026Article
- Advances in Genetic Engineering Techniques for Improved Forest Trees: Applications in Biomass, Stress Resilience and Carbon Sequestration.International journal of molecular sciences · 2025Review
- Importance-Performance Map Analysis of the Drivers for the Acceptance of Genetically Modified Food with a Theory of Planned Behavior Groundwork.Foods (Basel, Switzerland) · 2025Article
- Effect on consumers' sustainable purchase intention of dietary supplement purine labeling.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The public perspective on genetically modified foods (GMFs) has been intensely debated and scrutinized. Often, discussions surrounding GMF tend to revolve solely around the potential health risks associated with their consumption. However, it is essential to acknowledge that public perceptions of genetically modified foods are multifaceted, encompassing environmental concerns, ethical considerations, and economic implications. This paper studies the factors predicting GMF acceptance employing the representative sample of the Czech population (N = 884, aged 18-90 years, M ± SD: 48.17 ± 17.72; 53.40% women, 18.04% with higher education). The research relies on the Behavioral Change Model and the Health Belief Model. We employ hierarchical ordinal regressions to study the effects of information, environmental concerns, perceived health risks, food habits, purchasing habits, and socio-demographics on GMF acceptance. The results suggest that the (un)willingness to purchase GMF is primarily driven by the health risks - the environmental concerns were largely unimportant. The impact of information provision on GMF acceptance proved positive, suggesting information and education to be the main channels of creating public acceptance. The intrinsic interest regarding information related to GMF had an adverse impact on the perception of GMF morality. The benefits of the GMF proved unrelated to the GMF acceptance, indicating the gap in the information campaign. The research provides valuable insights for policymakers, public health professionals, and market researchers to communicate the GMF agenda effectively to the general public.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.