A Survey of Family Medicine Department Chairs About Faculty With Disabilities: A CERA Study.
Notice bibliographique
Résumé
BACKGROUND AND OBJECTIVES: Despite 21 million US adults having a disability, little is known about the types of disabilities among faculty in family medicine departments, accommodations used, or work limitations. METHODS: We surveyed family medicine department chairs electronically about the number, types of disabilities encountered, accommodations and associated costs, and attitudes toward family medicine faculty with disabilities. This 10-item survey was part of the Council of Academic Family Medicine Educational Research Alliance omnibus survey. Data were summarized using descriptive statistics. RESULTS: The survey response rate was 59% (88/148). Types of disabilities were reported for approximately 50 faculty members by 31 department chairs; only seven knew about the disability at hiring. The most common impairments were mobility, hearing, and mental health problems. Accommodations included adjusting schedules, additional time to meet tasks, and assistive technology. No additional costs were reported for accommodations by about one-third of respondents while costs were over $5,000 for approximately one-quarter. Most chairs reported that faculty performance was similar to peers without disabilities (42.2%) or adequate but not at the level of peers (40%); only one reported inadequate job performance. Faculty members with disabilities appeared to be accepted by peers, patients, learners, and staff, and only two faculty left their program because of the disability. CONCLUSIONS: Most chairs did not report experience with faculty members with disabilities. The disabilities encountered and accommodations were not unusual, but costs were sometimes high. While about half of chairs reported adequate or superior job performance for their faculty with disabilities, a sizeable minority judged such faculty to have poorer performance than peers despite reporting wide acceptance of faculty with disabilities by patients and colleagues. This study raises concerns about potential underreporting by faculty with disabilities and poorer perceived job performance despite wide acceptance and provision of accommodations, sometimes at high cost.
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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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
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 ».