A mixed-methods approach to evaluate producer knowledge, attitudes and practices towards food safety
Notice bibliographique
Résumé
The knowledge and attitudes towards food safety and reported use of good production practices (GPP) were investigated among dairy, broiler chicken and niche-market producers in Canada. A mailed questionnaire was administered to all dairy producers enrolled in dairy herd improvement organizations in Canada in 2008. The response percentage was 20.9% (2185/10,474). Respondents who reported completion of a dairy-health management education course were less likely to support the availability of unpasteurized milk for consumers (OR=0.74, 95% CI: 0.60, 0.92) and more likely to be concerned about antimicrobial resistance (OR=1.37, 95% CI: 1.11, 1.69). Knowledge gaps were also identified (e.g. zoonotic potential of 'Brucella'). Latent class analysis identified five groups of producers based on their reported use of GPP: "minimal", "sanitation-only", "employee-visitor hygiene", "typical" and "ideal" users (11.1%, 23.8%, 20.2%, 37.1 % and 7.7% of respondents, respectively). Respondents in the "ideal users" group used more GPP and were more likely to have completed an educational course in food safety compared to each other group. Mailed and web-based questionnaires were administered to all broiler chicken producers registered in British Columbia, Ontario and Quebec in 2008. The response percentage was 33.2% (642/1932). Greater than 80% and 21.1% of respondents indicated that 'Salmonella' and 'Campylobacter ', respectively, can be transmitted from chicken to humans. Respondents who rated the Safe, Safer, Safest program requirements as effective (70%) or easy (49%) to implement were more likely to report the use of five of six highly recommended GPP. A questionnaire was administered and 23 semi-structured qualitative interviews were conducted with niche-market (i.e. organic and small-scale) producers in Ontario during 2008-2009. In total, 575 questionnaires were collected. Disinfection of food animal drinking water and post-harvest produce wash water was reported by <40% of respondents. Primary themes identified in semi-structured interviews included concerns about imported products, suggestions to tailor on-farm food safety programs by farm scale and ensure that they are user-friendly and cost-recoverable, and the importance of producer education and government support. Baseline estimates for the knowledge, attitudes and practices towards food safety were identified, which can be used to support future decision-making regarding food safety programs and education for producers.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,034 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».