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Record W4402094876 · doi:10.1108/bfj-08-2023-0709

Food safety knowledge, attitudes and practices (KAP) of street vendors: a cross-sectional study in Jordan

2024· article· en· W4402094876 on OpenAlexaff
Nour Amin Elsahoryi, Amin N. Olaimat, Hanan Abu Shaikha, Batool Tabib, Richard A. Holley

Bibliographic record

VenueBritish Food Journal · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCross-sectional studyFood safetyBusinessEnvironmental healthMarketingAdvertisingFood scienceMedicine

Abstract

fetched live from OpenAlex

Purpose This study examined the knowledge, attitudes and practices (KAP) regarding food safety and hygiene among street food vendors (SFVs) in Jordan, along with associated factors. Design/methodology/approach This study utilized a cross-sectional design and targeted a sample of 405 SFVs in Jordan's two most densely populated cities. Data were collected through in-person interviews using a validated and reliable structured questionnaire. Descriptive analysis and linear regression were conducted using SPSS v.25 software to examine associations and predict outcomes. Findings The findings reveal that SFVs possess a moderate level of knowledge but exhibit negative attitudes and inadequate practices regarding food safety. Significant associations were identified between age, education level, work experience, marital status, gender and the vendors' KAP. Older SFVs tend to exhibit lower knowledge and attitudes, whereas those with more experience and higher education levels demonstrate better KAP. Marital status and gender also influence knowledge and attitudes. Originality/value This study fills a critical gap in the research landscape by comprehensively examining the knowledge, attitudes and practices of street food vendors regarding food safety, with a focus on Jordan. Its findings shed light on the challenges facing the street food vending industry and offer actionable recommendations for enhancing food safety practices. As such, the study's originality and significance lie in its potential to drive positive change within this vital culinary tradition, safeguarding public health and economic livelihoods. Highlights - The study's novelty lies in its exploration of street food vendors' knowledge, attitudes, and practices (KAP) related to food safety, a facet critical to understanding and addressing the challenges facing this industry. It offers an in-depth examination of factors such as education, experience, age, and marital status that influence vendors' adherence to food safety measures. By focusing on the two most populous cities in Jordan, the study not only provides a comprehensive picture of the situation but also sets the groundwork for policy recommendations and interventions. - The research highlights a series of concerning findings. Street food vendors exhibit a moderate level of knowledge regarding food safety, with substantial gaps in understanding specific pathogens and transmission routes. Negative attitudes towards food safety are prevalent, translating into suboptimal hygiene practices. The study's results underscore the urgent need for tailored interventions to address these challenges and improve overall food safety practices within the street food vending sector. - The findings offer actionable insights for policymakers, public health authorities, and local governments. They suggest targeted educational initiatives to enhance vendors' understanding of food safety principles and their significance in preventing foodborne illnesses. Furthermore, the study emphasizes the need for improved infrastructure, access to clean water, and proper sanitation facilities to support vendors in implementing safer practices. By highlighting the associations between socio-demographic factors and food safety KAP, the study offers a blueprint for crafting interventions that address the unique needs of different subgroups of street food vendors.

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)0.001
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 score0.142
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.043
GPT teacher head0.317
Teacher spread0.274 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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