MétaCan
Menu
Retour à la cohorte
Enregistrement W4415615988 · doi:10.1097/01.jaa.0000000000000271

The ripple effect of teaching

2025· article· en· W4415615988 sur OpenAlexaff
Lauren Fogelgren

Notice bibliographique

RevueJAAPA · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueInnovations in Medical Education
Établissements canadiensMusée de la Civilisation
Organismes subventionnairesnon disponible
Mots-clésNothingGriefFace (sociological concept)FeelingConversationBad habitVulnerability (computing)Sitting

Résumé

récupéré en direct d'OpenAlex

“If we do not intubate him now, he will die.” This is the last thing I remember about my father's death. I could feel cold rippling down my back and a lump forming in my throat as I thought about the past year. My dad was sitting up and talking to us—I couldn't imagine he needed intubation. How did I not catch this? Should I have pushed the medical team harder for answers? I never thought I would sit on the other side of the patient's bed, my heart pounding as I watched the machines beep and hum around my father. I had spent years taking care of critically ill patients, providing comfort in their most vulnerable moments. Now, it was my dad who lay there, helpless and struggling. There is an intense vulnerability on the other side, an overwhelming rush of emotions, a desire to hold on, to fix. No amount of training could prepare me for the grief I was feeling. But as the hours passed and the prognosis grew dimmer, reality became clear: there was nothing I could do to change the outcome. I thought about the thousands of patients I've cared for. I saw the faces of my PA students. I thought back on discussions and reflections about how we navigate intense emotions, ways to console family members, and the things we do to humanize the practice of medicine. As I stood watching my dad, hoping his team would be good enough, a face I knew walked through the door—one of my former students. Here she was, the PA on my dad's ICU care team. She walked in slowly, her face softening as I watched her connect the dots. She was the first to speak to my family. Her tone was calm, and she told us very directly what the medical plan would be. My father was lightly sedated; she gently approached him and held his hand. She sat with my family while we cried and explained the next steps in his care with clarity and compassion. Tears welled in my eyes and my chest constricted as I listened. I was overcome with emotion, experiencing the student I once guided now providing care to my family. I felt the power of teaching and mentorship come full circle. After my father was extubated, he whispered in a raspy voice to my student, “You're doing a great job.” Four days later, I entered his room and found her again, sitting with my sister, hugging her. My father took his last breath just moments later. I devote myself to teaching students about the emotional intelligence necessary to provide compassionate care. The trust, knowledge, and skills this student and I had cultivated in our academic relationship found a deep home in this personal setting. I witnessed the ripple effect of that power, and was humbled. We teach for these moments beyond the walls of the classroom. Lessons taught in lectures are not the sole markers of a successful medical career. Rather, deeper lessons I had imparted were now evident in the way she treated my family, and I realized the true impact of our relationship. Witnessing her provide care to my dad reminded me of the profound impact we, as educators and preceptors, have in shaping the future of healthcare. My lasting memory will be standing next to my deceased father and trembling with sorrow as grief consumed me. At this most vulnerable moment, my student embraced me, giving meaning to this heartbreak. On the days when it feels hard to teach or to take the extra time to help a student, consider the ways you are shaping providers that may one day care for those you love. When we feel cynical, overburdened, and exhausted, when we think about quitting medicine, consider our work as it extends into the providers we are forming. We often don't get the chance to see the effects of our teaching at the bedside. I'm grateful for this exception.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,727
Score d'incertitude au seuil0,279

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,003
Tête enseignante GPT0,346
Écart entre enseignants0,343 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJAAPAMême sujetInnovations in Medical EducationTravaux en français237 207