Improving caretaker mental welfare through targeted on-farm euthanasia training programs
Notice bibliographique
Résumé
Swine employee retention factors are multi-faceted, complicated, inter-twined, and often differ from other businesses. Positive factors of the job include direct pig interaction, career enhancement opportunities and reliable and varied tasks. However, negative factors of the job may include early starts and long hours, weekend shifts, challenging environmental conditions, lower salaries compared to other entry level positions, repetitive work, cultural differences, and tasks that are mentally challenging. In 2022, 17.8% of workers employed in animal production and aquaculture were Hispanic and/or Latino from South American countries. The North American Free Trade Agreement (NAFTA; TN) visa which “allows qualified Canadian and Mexican citizens to seek temporary entry into the United States to engage in business activities at a professional level.” This gives some foreign workers the opportunity to seek employment in the U.S. These caretakers on pig farms are front line that have to engage in challenging yet highly important tasks to ensure pig welfare. One of these tasks is timely euthanasia. Previous studies suggest that caretakers performing euthanasia are at an increased risk of emotional mismanagement, physical ailments, unresolved grief, depression, substance abuse, and even suicide. Improved and supported caretaker psychological welfare can be met through focused and relevant training that are based around personality and learning style preference. One personality assessment tool is the Predictive Index (PI) Behavioral Assessment. This is an untimed, free-choice, self-report tool based on two questions. Question one asked caretakers to select as many words from a provided list that they thought represented how others expect them to act. The second question asked caretakers to select as many words from a provided list on how they identified themselves. These selected words are automatically categorized by the PI algorithm software and a caretaker is allocated a behavioral profile based on dominance, extraversion, patience, formality, and objectivity. There is no published literature using the PI Behavioral Assessment to (a) identify a swine caretakers’ PI profile, (b) allocate them to a specifically designed on-boarding swine euthanasia training and, (c) to determine if the PI Behavioral Assessment positively supports their psychological welfare. Therefore, the overall goal of this thesis was to improve caretaker mental welfare through targeted on-farm euthanasia training programs. The specific objective to meet this aim was to determine if a tailored swine euthanasia training tool based on the PI Behavioral Assessment improves caretaker euthanasia attitudes, perceptions and supports caretaker mental welfare. Swine euthanasia training modules based on the PI Behavioral Assessment and surveys were created and tested on TN-visa holding swine caretakers employed on commercial sow farms. Our data indicates that Mexican caretakers on TN visas have positive perceptions (P 0.0034) and are decisive (P 0.0001). In addition, they are knowledgeable in diagnosing and performing euthanasia when a pig or piglet get sick or is compromised (P 0.0045). These caretakers are compassionate but do not feel bad about euthanizing pigs or piglets (P 0.0001). Overall, caretakers saw value in both the PI Behavioral Assessment combined with the on-farm euthanasia training (P 0.15). In conclusion, the PI Behavioral Assessment tool combined with a specialized euthanasia module training that was designed around learning, demonstrated value in supporting TN caretaker mental welfare. It is recommended that this tool and specialized module training be integrated into swine euthanasia training.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».