Notice bibliographique
Résumé
Nursing educators globally have called for mentorship to help address the nursing faculty shortage. Mentorship is perceived as vital to maintaining high-quality education programs. While there is emerging evidence to support the value of mentorship in other disciplines, the extant state of the evidence for mentorship in nursing academia is not well-established. Little is known about the current state of mentorship or the barriers and facilitators for implementing mentorship programs in Canadian nursing schools. The overarching aim of this dissertation was to explore the current state of mentorship in nursing academia. Three methodologies were employed to examine this phenomenon: 1. A systematic review of the evidence. 2. A cross sectional survey of nursing faculty. 3. Semi-structured interviews with nursing faculty members from across Canada. Descriptive statistics and thematic analysis were used to analyze the data. The results of all three phases were integrated to develop a more robust and meaningful picture of mentorship. Within the literature there is no clear differentiation and operationalization of program and individual outcomes of mentorship nor is there discussion of the role of formal (matched) and informal (self-selected) mentorship within schools that identify mentorship programs. While generally, in the literature at an individual level, mentorship is reported to positively impact behavioural, career, attitudinal, relational, and motivational outcomes; it is important to note that the methodological quality of the mentorship studies is weak. Additionally, while outcomes can be categorized as noted above, it is also apparent that whether academics seek out their own mentors through informal and established networks or are matched with mentors in a formalized program it is difficult to untangle whether the outcomes are a result of the formal program or individual efforts. The survey and interview data revealed that the majority of Canadian nursing schools lack formal mentorship programs and those that exist are largely informal, vary in scope and components, and lack common definitions or goals. Individual perceptions of factors influencing mentorship program implementation include (a) training and guidelines; (b) quality of relationships; (c) choice and availability of mentors; (d) organizational support; (e) time and competing priorities; (f) culture of the institution; and, (g) evaluation of mentorship outcomes. Dyad, peer, group, constellation, and distance mentorship models are present and components include guidelines, training, professional development workshops, purposeful linking of mentors and mentees, and mentorship coordinators. Evaluation of mentorship, where it exists, remains mostly descriptive, anecdotal, and lacks common evaluative metrics. The results from this study confirm lack of formalized mentorship programs in Canadian schools of nursing. To ensure success in developing mentorship programs, academic leaders need to consider multiple barriers, facilitators, models and components to meet their specific needs. Further rigorous evaluation of mentorship programs and components is needed to identify if mentorship programs are achieving specified goals.
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 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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».