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Record W4386116338 · doi:10.2196/44150

Consumer Awareness of Food Defense Measures at Food Delivery Service Providers and Food Manufacturers: Web-Based Consumer Survey Study

2023· article· en· W4386116338 on OpenAlexvenueno aff
Manabu Akahane, Yoshiyuki Kanagawa, Yoshihisa Takahata, Yasuhiro Nakanishi, Takemi Akahane, Tomoaki Imamura

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
FundersMinistry of Health, Labour and Welfare
KeywordsFood safetyLikert scaleEnvironmental healthFood securityFood hygieneMarketingBusinessHygienePsychologyMedicineAgriculture

Abstract

fetched live from OpenAlex

BACKGROUND: Various stages of the food chain, from production to processing to distribution, can impact food safety. The concept of "food defense" has emerged as a countermeasure against intentional contamination of food with foreign substances. Although knowledge of food hygiene is common among consumers, there are currently no reports of consumer surveys on food defense. OBJECTIVE: This study aims to investigate consumer awareness of food defense and food safety. We analyzed the results focusing on how consumers behave when they find abnormalities in food to further our knowledge on promoting food defense measures. METHODS: Participants completed a web-based questionnaire that included items related to awareness of food safety and food defense, as well as actions to be taken in cases of food abnormalities, such as contamination by foreign substances, the presence of a bad smell in purchased food, and the inclusion of extra items not selected by the individual. The participants were asked to indicate their preference among the 5 suggested actions in each case using a 6-point Likert scale. Data analysis involved aggregating responses into binary values. Stepwise linear regression analysis was conducted to examine the relationship between selected actions and questionnaire items, such as sex, age, and personality. RESULTS: A total of 1442 respondents completed the survey, and the majority of participants placed importance on food safety when making food purchases. The recognition of each term was as follows: 95.2% (n=1373) for "food security and safety," 95.6% (n=1379) for "food hygiene," and 17.1% (n=247) for "food defense." The percentages of those who answered that they would "eat without worrying" in the case of "contamination by foreign substances," "bad smell," or "including unpurchased product" in the frozen food they purchased were 9.1% (n=131), 4.8% (n=69), and 30.7% (n=443), respectively. The results showed that contacting the manufacturer was the most common action when faced with contaminated food or food with a bad smell. Interestingly, a significant percentage of respondents indicated they would upload the issue on social networking sites. Logistic regression analysis revealed that male participants and the younger generation were more likely to choose the option of eating contaminated food without worrying. Additionally, the tendency to upload the issue on social networking sites was higher among respondents who were sociable and brand-conscious. CONCLUSIONS: The findings of this study indicate that if food intentionally contaminated with a foreign substance is sold and delivered to consumers, it is possible consumers may eat it and experience health problems. Therefore, it is crucial for not only food manufacturers but also food delivery service providers to consider food defense measures such as protecting food from intentional contamination. Additionally, promoting consumer education and awareness regarding food defense can contribute to enhancing food safety throughout the food chain.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.142
GPT teacher head0.342
Teacher spread0.200 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2023
Admission routes1
Has abstractyes

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