Partnership approach: A good practice in teaching mental health
Notice bibliographique
Résumé
Background/Objective: This paper examines the ternary relations that a Nursing Unit in a regional university campus in South Australia has created in delivering a mental health course to its first-year students studying in the Bachelor of Nursing program. The partnership may be described as three-cornered, where one corner would be the nursing students and the university represented by the academic teaching in the course, another would be the mental health clinicians, and the third corner would be the mental health care workplaces represented by the mental health nurses working with the students during placement. The outcomes of this three-way relationship on students’ course experience and satisfaction is the focus of this paper. Methods: The impact of the partnership in teaching a mental health course on eleven (n=11) students was determined through a twelve-item questionnaire administered at the conclusion of the course. The questionnaire examined students’ experience with the partnership approach, clinician-driven activities, best aspects of the course, impact on learning, and areas for improving future offerings. The collaborative initiative was also evaluated by an academic, three mental health clinicians and three mental health nurses using a modified one-minute questionnaire examining the most important outcome gained from the partnership, the best aspects of the partnership in delivering the course, areas to be included or expanded in the future, and personal and professional impact on university staff, clinicians and nurses. Main findings: The majority of students found the conduct of the mental health course to be a pleasant learning experience. The inclusion of mental health clinicians provided many learning opportunities and afforded a better understanding of the role(s) of mental health nurses. Students felt positive about mental health nursing and some decided that they might pursue the speciality. The best things about the course from the students’ perspective were being close to the reality of mental health practice, learning from real-life experiences, and the opportunity to put theory into practice in the mental health care workplaces. The best aspect of the partnership for the academic and clinicians was helping students better understand mental health issues by creating a real-life learning environment. For the mental health nurses in health care facilities, the best outcome was the opportunity to impart knowledge, broaden career paths, and demystify mental health. Conclusions: This partnership between the university and industry in teaching mental health is a radical departure from traditional university formats. Findings from this pilot study showed an overall satisfaction with the partnership approach in teaching and learning mental health. The partnership was mutually beneficial; it was instrumental in bringing mental health to life, broadening career options for students and building human capacity. This is the start of an on-going academic and industry partnership which will provide the basis for future collaboration opportunities in education, research and clinical practice in a rural and regional setting.
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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 | 0,134 | 0,116 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,022 | 0,063 |
| Communication savante | 0,024 | 0,025 |
| Science ouverte | 0,006 | 0,038 |
| Intégrité de la recherche | 0,015 | 0,033 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,004 |
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 ».