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Enregistrement W4390645857

The Association Between Remote Work During the First Wave of the Pandemic and Faculty Perceptions of Their Productivity and Career Trajectory: A Cross Sectional Survey.

2023· article· en· W4390645857 sur OpenAlexaboutno aff
Siobhán Byrne, Brad C. Astor, Arjang Djamali, Laura Zakowski

Notice bibliographique

RevuePubMed · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueWork-Family Balance Challenges
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPandemicProductivityWork (physics)Cross-sectional studyPerceptionPsychologyQuarter (Canadian coin)Medical educationMedicineAssociation (psychology)Health careCoronavirus disease 2019 (COVID-19)Political scienceGeographyEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Early in the pandemic, studies documented that there are gendered differences in many factors related to working during the pandemic, especially for caregivers. This study aimed to focus on the effects of remote work, rather than the pandemic in general, on perceptions of productivity and career trajectory in research and education faculty at an academic health center. METHODS: A questionnaire was developed and distributed to all faculty in the Department of Medicine. We obtained demographic information and asked respondents to report the effect that remote work had on their research or teaching productivity. Those who reported a decrease in productivity were asked to choose a degree of impact. We also asked about the level of concern for the effect remote work would have on their career trajectory in research and teaching and about the impact of remote work on academic wellness. RESULTS: We received responses from 51.4% of 479 faculty. A little less than half were females, and most were subspecialists. More than half (60.6%) were responsible for providing care to children, parents, or others. Nearly one-quarter of respondents (22.8%) reported a negative effect of remote work on teaching productivity, which was more pronounced in senior faculty versus junior faculty (28.6% vs 16.5%, P = 0.03). Few faculty (7.4%) were concerned about their career trajectory in teaching; however, those who provided care at home were significantly more likely to be concerned (10.7% vs 2.1%, P = 0.01). Over half of respondents (56.6%) reported a negative effect of remote work on research productivity; this was significantly higher for tenure faculty than clinician educators (71.9% vs 50.7%, P = 0.01). Almost half of respondents (39.6%) were concerned about their career trajectory in research, and this concern was significantly higher in specialists than in generalists (42.9% vs 15.8%, P = 0.02) and in clinician educators versus clinicians (39.7% vs 0.0%, P = 0.007). A small number of faculty (11.5%) reported a negative impact of remote work on their academic wellness; this impact was higher in specialists than in generalists (13.2% vs 3.7%, P = 0.05). There were no significant differences in any areas of concern for males versus females or in those with or without leadership roles. CONCLUSIONS: In this single-center study during the first wave of the pandemic, faculty perceived reduced productivity in teaching, research, and academic wellness. Our study found that remote work concerns were overall more evenly distributed across gender and those responsible for caregiving than had been reported previously; however, caregivers were more concerned about their career trajectory in teaching than noncaregivers. The lack of significant differences may have been due to several factors: remote work allowed flexibility when caregiving arrangements were disrupted; remote work was required of all faculty, mitigating concerns that caregivers were singled out; and institutional support offset some of the challenges. Further studies are needed to determine whether social or operational interventions in academic health centers can reduce the negative perception of remote working on academic productivity.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Incitatifs · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,998
Score d'incertitude au seuil0,011

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,086
Tête enseignante GPT0,287
Écart entre enseignants0,202 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineIncitatifs
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
Publié2023
Routes d'admission1
Résumé présentoui

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