Objectives: The aim of this study was to assess expectations of performance that exist in the marketplace for entry-level pathologists' assistants (PathAs), defined as recent graduates of a pathologists' assistant program on their first day of employment.
Methods: A voluntary, anonymous survey was distributed to pathologist and PathA members of the American Society for Clinical Pathology by email. We assessed 98 professional activities of PathAs using a 5-point scale of expectations based on levels of trust placed in them. We also collected demographic information.
Results: A total of 728 participants responded to this survey, including 280 pathologists and 448 PathAs. We classified 98 activities according to expectations: independent performance (20/98), developing independence (48/98), and not expected of PathAs (5/98). Some activities (25/98) were indeterminate yet likely represent areas of developing independence.
Conclusions: This study demonstrates an expectation for entry-level PathAs to perform some activities included in the scope of practice independently but eventually to develop independent proficiency for most professional activities. A minority of activities were identified as responsibilities that are not expected of PathAs. Entry-level PathAs, therefore, remain "works in progress," with an expectation for independent performance of core activities while developing abilities in many areas of professional practice.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1093/ajcp/aqac065 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Detection of cervical cell based on multi-scale spatial information.
Sci Rep
January 2025
School of Computer and Information Science, Chongqing Normal University, Chongqing, 401331, China.
Cervical cancer poses a significant health risk to women. Deep learning methods can assist pathologists in quickly screening images of suspected lesion cells, greatly improving the efficiency of cervical cancer screening and diagnosis. However, existing deep learning methods rely solely on single-scale features and local spatial information, failing to effectively capture the subtle morphological differences between abnormal and normal cervical cells.
View Article and Find Full Text PDFDeep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images.
J Transl Med
January 2025
Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Accurate and fast histological diagnosis of cancers is crucial for successful treatment. The deep learning-based approaches have assisted pathologists in efficient cancer diagnosis. The remodeled microenvironment and field cancerization may enable the cancer-specific features in the image of non-cancer regions surrounding cancer, which may provide additional information not available in the cancer region to improve cancer diagnosis.
View Article and Find Full Text PDFUse of Lung Volume Recruitment Technique in Patients With Chronic Respiratory Disease Among Brazilian Health Professionals.
Pulm Med
January 2025
Post Graduation Department, Escola Superior de Ciências da Saúde (ESCS), Brasilia, Distrito Federal, Brazil.
Lung volume recruitment (LVR) is a stacked-breath assisted inflation technique in which consecutive insufflations are delivered, without exhaling in between, until the maximum tolerable inflation capacity is reached. Although LVR is recommended in some neuromuscular disease guidelines, there is little information detailing when and how allied health professionals (AHPs) prescribe LVR. This study is aimed at describing the use of LVR in practice across Brazil.
View Article and Find Full Text PDFChronic inflammation in a radium dial painter cohort: elevated neutrophil to lymphocyte ratio and radiation-induced hearing loss.
J Radiol Prot
January 2025
WSU, Richland, Washington, UNITED STATES.
The radium dial painters (RDP) are a well-described group of predominantly young women who incidentally ingested 226Ra and 228Ra as they painted luminescent watch dials in the first part of the twentieth century. In 1974 pathologist Dr. William D.
View Article and Find Full Text PDFDeep learning helps discriminate between autoimmune hepatitis and primary biliary cholangitis.
JHEP Rep
February 2025
Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany.
Background & Aims: Biliary abnormalities in autoimmune hepatitis (AIH) and interface hepatitis in primary biliary cholangitis (PBC) occur frequently, and misinterpretation may lead to therapeutic mistakes with a negative impact on patients. This study investigates the use of a deep learning (DL)-based pipeline for the diagnosis of AIH and PBC to aid differential diagnosis.
Methods: We conducted a multicenter study across six European referral centers, and built a library of digitized liver biopsy slides dating from 1997 to 2023.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!