Anatomical Sciences Education最新文献

The Cognitive Theory of Multimedia Learning (CTML) suggests humans learn through visual and auditory sensory channels. Haptics represent a third channel within CTML and a missing component for experiential learning. The objective was to measure visual and haptic behaviors during spatial tasks. The haptic abilities test (HAT) quantifies results in several realms, accuracy, time, and strategy. The HAT was completed under three sensory conditions using sight (S), haptics (H), and sight with haptics (SH). Subjects (n = 22, 13 females (F), 20-28 years) completed the MRT (10.6 ± 5.0, mean ± SD) and were classified as high or low spatial abilities scores with respect to mean MRT: high spatial abilities (HSA) (n = 12, 6F, MRT = 13.7 ± 3.0), and low spatial ability (LSA) groups (n = 10, 7F, MRT = 5.6 ± 2.0). Video recordings gaze and hand behaviors were compared between HSA and LSA groups across HAT conditions. The HSA group spent less time fixating on mirrored objects, an erroneous answer option, of HAT compared to the LSA group (11.0 ± 4.7 vs. 17.8 ± 7.3 s, p = 0.020) in S conditions. In haptic conditions, HSA utilized a hand-object interaction strategy characterized as palpation, significantly less than the LSA group (23.2 ± 16.0 vs. 43.1 ± 21.5 percent, p = 0.022). Before this study, it was unclear whether haptic sensory inputs appended to the mental schema models of the CTML. These data suggest that if spatial abilities are challenged, LSA persons both benefit and utilize strategies beyond the classic CTML framework by using their hands as a third input channel. This data suggest haptic behaviors offer a third type of sensory memory resulting in improved cognitive performance.

The topic of vertical integration of the basic and clinical sciences is an area of great concern and active investigation in medical education. To explore the feasibility of integrating basic sciences into the clinical phase of medical education, gross anatomy was selected as an appropriate discipline. Anatomy faculty, clerkship directors, medical students, and graduate students developed case-based anatomy modules with a design consistent with the principles of self-directed learning. This pilot study aimed to explore medical student responses to the integration of anatomy sessions during clinical clerkships. One-hour anatomy sessions were conducted during rotations of the following clerkships: internal medicine, pediatrics, family medicine, neurology, obstetrics and gynecology, and general surgery during the academic year 2022-2023. Each session consisted of four case-based stations. Voluntary, anonymous surveys were distributed at the end of each session. Descriptive statistics of survey responses from the 490 participants revealed the overall ratings of the anatomy sessions to be above an 8.50 on a scale of 1.00 (low) to 9.00 (high). A small q thematic analysis of the open-ended survey questions revealed the following themes: relevance of clinical correlations presented, a timely review of anatomical content, appreciation for the collaborative setting and interactivity among the participants, and constructive feedback regarding areas needing improvement. Students reported a high overall rating of the anatomy sessions and shared positive comments about these vertically integrated anatomy experiences. With a reduction in the amount of anatomy instruction during the pre-clinical years and limited exposure during the clinical years, anatomy sessions like the ones proposed could allow for the fluid incorporation of gross anatomy across all 4 years of medical school.

Speech-language pathologists need to accurately identify structures/landmarks on swallow imaging. Foundational learning begins in graduate training. This study aimed to determine graduate student accuracy at identifying anatomical structures/landmarks during swallow evaluations and to determine if accuracy was predicted by type of imaging, anatomical structure, case type (i.e., normal/abnormal). Researchers recruited first-year graduate speech-language pathology students. Each participant reviewed five static images from lateral radiographic swallow studies and five static images from endoscopic swallow studies across 10 cases. Participants identified key anatomic structures and landmarks by clicking on the structure/landmark within a web-based platform. Two experienced speech-language pathologists reviewed and coded participant responses for accuracy. Sixteen graduate speech-language pathology students participated in a within-subjects design. Overall participant accuracy in identification of structure/landmarks was 69% (range 46%-88%). Binomial logistic regression was performed to study the effects of anatomical structure, case type (i.e., normal/abnormal), and image type on likelihood of participant accuracy in identifying anatomical structures (X²(4) = 143.65, p < 0.001). Only anatomical structure was statistically significant (X²(4) = 187.729, p < 0.001). The model explained 23.2% (Nagelkerke's R squared) of the variance in accuracy and correctly classified 78.4% of cases. Sensitivity was 92.1%, specificity was 47.3%, positive predictive value was 79.84%, and negative predictive value was 72.50%. The area under the ROC curve was 0.754, 95% CI [0.716, 0.791]. Graduate student's ability to correctly identify structures/landmarks overall was lower than desired and accuracy varied per structure. Results have implications for improving graduate student training for identification of structures/landmarks on swallow imaging.

Medical schools are required to assess and evaluate their curricula and to develop exam questions with strong reliability and validity evidence, often based on data derived from statistically small samples of medical students. Achieving a large enough sample to reliably and validly evaluate courses, assessments, and exam questions would require extensive data collection over many years, which is inefficient, especially in the fast-changing educational environment of medical schools. This article demonstrates how advanced quantitative methods, such as bootstrapping, can provide reliable data by resampling a single dataset to create many simulated samples. This economic approach, among others, allows for the creation of confidence intervals and, consequently, the accurate evaluation of exam questions as well as broader course and curriculum assessments. Bootstrapping offers a robust alternative to traditional methods, improving the psychometric quality of exam questions, and contributing to fair and valid assessments in medical education.

Digital model platforms and applications are common in anatomy education and continue to grow in number, which suggests that educators and students find use for these tools despite the lack of widely accepted best practices. Consequently, it is a challenge for educators to mindfully integrate digital models into curriculum. This short-term, longitudinal study investigated the effects of integrating a monoscopic digital model as a teaching tool during lectures on reproductive and endocrine anatomy as an intervention in a community college human anatomy and physiology course. Student use and perceptions of digital models were analyzed for correlation with the nature of the course content and the intervention (n = 92). Academic content significantly affected self-reported student use (p < 0.001) as well as student perceived usefulness of the model (p = 0.02). These findings support the conjecture that digital anatomy models may be better for achieving certain specific learning goals opposed to all learning goals. Integration of digital models as an instructional method did not consistently influence student behavior but it made a difference in participant ability to recognize this technology outside of the lecture. Overall, participants had a positive perception of digital models, although they were not perceived as more important than all other curricular resources. Inclusion of monoscopic digital models for teaching anatomy should be considered by educators since teaching with digital models can demonstrate strengths and weaknesses for students within the context the of learning objectives, assisting students to make more informed decisions about effective learning tools.

Cognitive structures are the mental representation of domain knowledge and its organization. A preliminary investigation of the cognitive structure of gross anatomy knowledge was conducted on physiotherapy students. The criterion-related validation study examined two data modeling strategies (multidimensional scaling and Pathfinder networks) as potential visual and quantitative representations of cognitive structure. Two criterion standards were used: expert cognitive structure (concurrent) and the student's unit grade (predictive). The raw data for both data modeling strategies were generated from an online survey of paired comparisons of 20 anatomical structures and concepts relevant to musculoskeletal clinical practice. Convenience sampling was used to recruit first-semester physiotherapy students (n = 31), gross anatomy course instructors (n = 4), and domain experts (n = 3) who completed the online survey. The results indicated moderate-to-high effect sizes, regarding the level of agreement (reliability, accuracy, and association) between student and expert cognitive structures. Multiple regression analysis was performed to examine the potential relationships with unit grades. Six predictor variables accounted for 68.9% of the variance in unit grade, indicating a large effect size. The results provide preliminary evidence of concurrent and predictive criterion-related validity for using data modeling strategies to represent cognitive structure in this knowledge domain and population. Further research is indicated to assess the potential impact of this innovative use of data modeling strategies for cognitive structure mapping on gross anatomy education, adaptive learning, and competency-based education, leading to the long-term development of expertise.

Australia and Aotearoa New Zealand (AANZ) medical schools have been impacted by curricular changes and the introduction of virtual microscopy (VM). No survey has explicitly described the outcome of these events on histology education in AANZ. This study provides a cross-sectional overview of histology education in accredited medical schools across AANZ in 2022-2023. Responses were received from 83% (19/23) of Australian medical schools, and 50% (1/2) of medical schools in Aotearoa New Zealand. VM, either exclusively (42%) or combined with traditional microscopy (37%), emerged as the preferred mode for delivering histology education. Common instructional methods included face-to-face lectures (26%) and synchronous online live lectures (26%). A significant proportion (84%) of educators supplemented resources with virtual microscopy websites. Integration of histology education was prevalent (79%), primarily with pathology (32%) or gross anatomy (26%). On average, medical students in the region spent a maximum of 21 ± 17 h in face-to-face histology laboratories throughout their degree. Histology education was predominantly taught by academics with a PhD degree. This study also examined the similarities and differences in histology education between AANZ and the global landscape. Through this examination, the present study positions AANZ within the broader context of histology education worldwide discusses key factors impacting histology education, and advocates for action to mitigate a looming shortage of pathologists in AANZ. In light of these findings, AANZ medical schools should integrate histology and pathology, establish a core curriculum, and promote flexible teaching modalities.

Qualitative longitudinal research (QLR) focuses on changes in perceptions, interpretations, or practices through time. Despite longstanding traditions in social science, QLR has only recently appeared in anatomical sciences education (ASE). While some existing methodology papers guide researchers, they take a narrow view of QLR and lack specificity for ASE. This discursive article aims to (1) describe what QLR is and its benefits, its philosophies, methodologies and methods, considerations, and quality indicators, and (2) critically discuss examples of QLR in ASE. Underpinned by relativist ontology and subjectivist epistemology, time can be understood as fluid/subjective or fixed/objective. QLR is a flexible, creative, and exploratory methodology, often associated with other methodologies. Sampling is typically purposive, with repeated and recursive data collection methods, and complex three-strand analyses (themes, cases, and time), enabling cross-sectional and longitudinal analyses. QLR involves ethical, relationship, analytical, dissemination, and funding considerations. Key quality indicators relate to qualitative research as well as temporal aspects. Most of the nine ASE papers reviewed explored changes in anatomy learners, but few labeled their methodology as QLR. Just under half described their sampling as purposive, most employed pre-planned and standardized repeated interviews, analyzed their data cross-sectionally, and utilized qualitative data analysis software. Most cited the confirmability and transferability of their studies, but few cited credibility and dependability elements. Study timeframes and tempos were generally clear, but details of longitudinal retention/attrition were often lacking, and longitudinal data analysis was not often conducted. We therefore provide recommendations for the conduct of QLR in ASE.