An assessment of program information on pediatric anesthesiology fellowship websites
Notice bibliographique
Résumé
There have been multiple studies that evaluated the websites of various fellowships and many of them were lacking specific details.1-3 These types of studies are crucial since applicants rely heavily on fellowship program websites for information. Addressing the shortcomings of the website material presented will assist applicants in making informed decisions about where to apply and selecting the program that best suits their needs. Fellowship programs can also benefit from this study by identifying areas for improvement in their website content to effectively showcase their program's strengths and attract potential applicants. This study aims to evaluate and compare the information available between different pediatric anesthesiology fellowship websites to identify areas that need to be improved. There were 61 ACGME pediatric anesthesiology fellowships in the United States at the time of this inquiry. Researchers then used the search engine, Google, to gather websites of the 61 available pediatric anesthesiology fellowship programs. Two researchers were only able to find 60 of the websites through Google. 24 different criteria were used to evaluate each pediatric anesthesiology fellowship website that similar studies used to critique other fellowship webpages.1, 4, 5 Two researchers independently evaluated whether or not the criteria were fulfilled by the websites as shown in Table 1. In the event of a disagreement between these evaluators, a third impartial researcher settled the discrepancy. The results with each criterion are shown in Table 1. The websites, on average, covered 13.19 out of 24 criteria (54.9%), with individual counts ranging from 8 to 20. 40 out of the 60 websites (66.7%) had more than 50% of the information available. Although most of the 60 websites met more than 50 percent of the criteria, there were a few categories that many websites lacked such as case log numbers, call responsibilities, clinic/office responsibilities, alumni, and summary. The decision was made to not assess the quality of the information to ensure objectivity in the evaluation process. While our researchers did not pinpoint the specific information sought by pediatric fellows when they were applying, addressing specific details that are underreported provides opportunities for enhancing the site because they can potentially yield valuable insights. For example, case logs allow applicants to be informed about the procedures they will be performing Providing applicants with information about their responsibilities in clinics, including pain or perioperative settings, and during on-call periods provides perspective into a fellow's daily routine and anticipated work–life balance. Alumni information allows applicants to contact previous graduates for details of the fellowship experience, ascertain their personal impressions of the training program, examine the career trajectory of previous trainees, and potential for their own career development based on graduate performance. Program summaries on websites would provide an excellent way for applicants to quickly identify points that make the fellowships unique, without having to browse throughout the whole website. By enhancing the content and presentation of websites, program directors can empower applicants to become more knowledgeable about what each program offers, ultimately fostering a more effective and mutually beneficial selection process. The data that support the findings of this study are available in Accreditation Council for Graduate Medical Education (ACGME) at https://apps.acgme.org/ads/Public/Reports/ReportRun. These data were derived from the following resources available in the public domain: Accreditation Council for Graduate Medical Education (ACGME), https://apps.acgme.org/ads/Public/Reports/Report/1.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».