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Record W2018622279 · doi:10.1159/000365508

Perceptions of Genetic Testing for Personalized Nutrition: A Randomized Trial of DNA-Based Dietary Advice

2014· article· en· W2018622279 on OpenAlexafffund
Daiva E. Nielsen, Sarah C. Shih, Ahmed El‐Sohemy

Bibliographic record

VenueLifestyle Genomics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsRandomized controlled trialLikert scaleMedicineIntervention (counseling)Nutrition EducationPerceptionGerontologyPsychologyInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Direct-to-consumer (DTC) genetic tests have facilitated easy access to personal genetic information related to health and nutrition; however, consumer perceptions of the nutritional information provided by these tests have not been evaluated. The objectives of this study were to assess individual perceptions of personalized nutrition and genetic testing and to determine whether a personalized nutrition intervention modifies perceptions. METHODS: A double-blind, parallel-group, randomized controlled trial was conducted among healthy men and women aged 20-35 years (n = 138). Participants in the intervention group (n = 92) were given a report of DNA-based dietary advice and those in the control group (n = 46) were given a general dietary advice report. A survey was completed at baseline and 3 and 12 months after distributing the reports to assess perceptions between the two groups. RESULTS: No significant differences in perceptions of personalized nutrition and genetic testing were observed between the intervention and control group, so responses of both groups were combined. As compared to baseline, participant responses increased significantly toward the positive end of a Likert scale at 3 months for the statement 'I am interested in the relationship between diet and genetics' (mean change ± SD: 0.28 ± 0.99, p = 0.0002). The majority of participants indicated that a university research lab (47%) or health care professional (41%) were the best sources for obtaining accurate personal genetic information, while a DTC genetic testing company received the fewest selections (12%). Most participants (56%) considered dietitians to be the best source of personalized nutrition followed by medical doctors (27%), naturopaths (8%) and nurses (6%). CONCLUSIONS: These results suggest that perceptions of personalized nutrition changed over the course of the intervention. Individuals view a research lab or health care professional as better providers of genetic information than a DTC genetic testing company, and registered dietitians are considered to be the best providers of personalized nutrition advice.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 designRandomized trial
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

Citations53
Published2014
Admission routes2
Has abstractyes

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