The Wellness Ambassador Program: A Student-Led Initiative to Promote Wellness and Connection Among Trainees During and Beyond the COVID-19 Pandemic
Notice bibliographique
Résumé
To the Editor: Medical student well-being is closely associated with the level of social support they can access. Students with inadequate social support are at greater risk of experiencing depression and burnout. 1 Furthermore, social support is positively correlated with empathy, a core competency for medical trainees. 2 Social isolation has become a hallmark of many students’ medical school experience since schools in Canada moved to virtual learning due to the COVID-19 pandemic. Students entering medical school in the fall of 2020 were deprived of in-person opportunities to connect with classmates, experiences that had been fundamental to developing a sense of community and belonging among students in previous years. In the 2020–2021 academic year, 54.0% of first-year medical students at the University of Toronto reported a level of social isolation that contributed to their daily stress. The same students also reported feelings of disconnectedness and lack of social support. To address these challenges, we developed the Wellness Ambassador (WA) program. This involved training a group of preclerkship medical students at the University of Toronto to navigate resources related to equity, mental health, diversity and inclusion, sexual violence prevention and support, and crisis identification. These students became WAs and served as resources for their peers. The program allowed students to anonymously access WAs for support in resource navigation. In addition, WAs created weekly social media posts to highlight resources and ways to cope with stress and cultivate wellness. The program encouraged social connection with a Virtual Med Lounge series, a casual and inclusive platform for students to connect with their peers online. Students who attended these sessions reported feeling connected and supported. Inadequate social support for medical students is detrimental to their mental health and academic performance. The COVID-19 pandemic has exacerbated the need for social connection. Through initiatives like the WA program, we are creating student connections and improving access to formal wellness resources during and beyond the COVID-19 pandemic. Acknowledgments: The authors thank the members of the 2020–2021 Wellness Ambassador team, including Eyram Asem, Michal Coret, Amal Ga’al, Shamini Vijaya Kumar, Danny Ma, Fahmeeda Murtaza, Christie Tan, Sam Wier, and Faiyaz Zaman, for their outstanding work. Furthermore, they thank Caroline Park and Anna Chen, Student Health Initiatives and Education general coordinators in 2020–2021 and 2019–2020, respectively, for their leadership and continued support of the Wellness Ambassador program as well as Dr. Tony Pignatiello and Shayna Kulman-Lipsey, both of the Office of Health Professions Student Affairs, for their generous support and commitment to student wellness.
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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 | 0,003 | 0,017 |
| 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 | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,007 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».