Incentives for clinical teachers: On why their complex influences should lead us to proceed with caution
Notice bibliographique
Résumé
INTRODUCTION: When medical education programs have difficulties recruiting or retaining clinical teachers, they often introduce incentives to help improve motivation. Previous research, however, has shown incentives can unfortunately have unintended consequences. When and why that is the case in the context of incentivizing clinical teachers remains unclear. The purposes of this study, therefore, were to understand what values and motivations influence teaching decisions; and to delve deeper into how teaching incentives have been perceived. METHODS: An interpretive description methodology was used to improve understanding of the development and delivery of teaching incentives. A purposeful sampling strategy identified a heterogenous sample of clinical faculty teaching in undergraduate and postgraduate contexts. Sixteen semi-structured interviews were conducted and transcripts were analyzed using an iterative process to develop a thematic structure that accounts for general trends and individual variations. RESULTS: Clinicians articulated interrelated and dynamic personal and environmental factors that had linear, dual-edged and inverted U-shaped impacts on their motivations towards teaching. Barriers were frequently rationalized away, but cumulative barriers often led to teaching attrition. Clinical teachers were motivated when they felt valued and connected to their learners, peers, leadership, and/or the medical education community. While incentives aimed at producing these connections could be perceived as supportive, they could also negatively impact motivation if they were impersonal, inequitable, inefficient, or poorly framed. DISCUSSION/CONCLUSION: These findings reinforce the literature suggesting that it is necessary to proceed with caution when labeling any particular factor as a motivator or barrier to teaching. They take us deeper, however, towards understanding how and why clinical teachers' perceptions are unique, dynamic and fluid. Incentive schemes can be beneficial for teacher recruitment and retention, but must be designed with nuance that takes into account what makes clinicians feel valued if the strategy is to do more good than harm.
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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 | 0,001 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,001 |
| 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.
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