Measuring training effectiveness of laboratory biosafety program offered at African Center for Integrated Laboratory Training in 22 President’s Emergency Plan for AIDS Relief supported countries (2008–2014)
Notice bibliographique
Résumé
INTRODUCTION: The African Center for Integrated Laboratory Training (ACILT) in Johannesburg, South Africa offered a laboratory biosafety program to improve laboratory biosafety practices in 22 President's Emergency Plan for AIDS Relief (PEPFAR) supported countries. This manuscript evaluates the transference of newly gained knowledge and skills to the participants' place of employment for HIV and TB diagnostic laboratory programs. It also serves as a follow-on to a previously published manuscript that measured training effectiveness for all courses offered at ACILT. METHODS: ACILT offered 20 Laboratory Biosafety and Infrastructure courses (2008-2014), also referred as biosafety course/course comprising of 14 core laboratory safety elements to 402 participants from 22 countries. In 2015, participants received 22 e-questions divided into four categories: (1) Safety Policies, (2) Management's Engagement, (3) Safety Programs and (4) Assessments of Safety Practices to determine retrospectively the training effectiveness of biosafety practices in their place of employment 6 months before and after attending their course. We used Kirkpatrick model to assess the transference of knowledge, skills and obstructive factors. RESULTS: 20% (81/402) of the participants completed the e-questionnaire. The overall percentage of positive responses indicating implementation of new safety practices increased from 50% to 84%. Improvement occurred in all four categories after attending the course, with the greatest increases in Safety Policies (67-94%) and Safety Programs (43-91%). Creating a safety committee, allocating resources, and establishing a facility safety policy were important drivers for implementing and maintaining laboratory safety practices. In addition, accredited laboratories and countries with national safety regulations or policies had a higher percentage of improvements. The most reported challenges were inadequate funding and lack of management enforcement. CONCLUSIONS: PEPFAR and other partners' investments in training institutions, such as ACILT, were effective in building sustainable country ownership to strengthen biosafety practices and were leveraged to combat zoonotic diseases and COVID-19. Although support continues at the national/regional level, a standardized, coordinated and continent-wide sustainable approach to offer a biosafety program-like ACILT is missing. Continuous offerings of biosafety programs similar to ACILT could contribute to sustainable strengthening of laboratory biosafety, QMS and pandemic preparedness.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».