Literature DB >> 23740912

Integration of basic sciences and clinical sciences in oral radiology education for dental students.

Mariam T Baghdady1, Heather Carnahan, Ernest W N Lam, Nicole N Woods.   

Abstract

Educational research suggests that cognitive processing in diagnostic radiology requires a solid foundation in the basic sciences and knowledge of the radiological changes associated with disease. Although it is generally assumed that dental students must acquire both sets of knowledge, little is known about the most effective way to teach them. Currently, the basic and clinical sciences are taught separately. This study was conducted to compare the diagnostic accuracy of students when taught basic sciences segregated or integrated with clinical features. Predoctoral dental students (n=51) were taught four confusable intrabony abnormalities using basic science descriptions integrated with the radiographic features or taught segregated from the radiographic features. The students were tested with diagnostic images, and memory tests were performed immediately after learning and one week later. On immediate and delayed testing, participants in the integrated basic science group outperformed those from the segregated group. A main effect of learning condition was found to be significant (p<0.05). The results of this study support the critical role of integrating biomedical knowledge in diagnostic radiology and shows that teaching basic sciences integrated with clinical features produces higher diagnostic accuracy in novices than teaching basic sciences segregated from clinical features.

Entities:  

Keywords:  basic science education; dental education; oral radiology; radiographs

Mesh:

Year:  2013        PMID: 23740912

Source DB:  PubMed          Journal:  J Dent Educ        ISSN: 0022-0337            Impact factor:   2.264


  11 in total

1.  Why Content and Cognition Matter: Integrating Conceptual Knowledge to Support Simulation-Based Procedural Skills Transfer.

Authors:  Jeffrey J H Cheung; Kulamakan M Kulasegaram; Nicole N Woods; Ryan Brydges
Journal:  J Gen Intern Med       Date:  2019-06       Impact factor: 5.128

2.  Faculty reflections on the process of building an integrated preclerkship curriculum: a new school perspective.

Authors:  Mohammed K Khalil; Jonathan D Kibble
Journal:  Adv Physiol Educ       Date:  2014-09       Impact factor: 2.288

3.  Generative Retrieval Does Not Improve Long-Term Retention of Regional Anesthesia Ultrasound Anatomy in Unengaged Learners.

Authors:  Jennifer F Potter; Amanda M Kleiman; Emmarie G Myers; Timothy J Herberg; Allison J Bechtel; Katherine T Forkin; Lauren K Dunn; Stephen R Collins; Julie L Huffmyer; Ashley M Shilling; Edward C Nemergut
Journal:  J Educ Perioper Med       Date:  2019-04-01

4.  Evaluation of different teaching methods in the radiographic diagnosis of proximal carious lesions.

Authors:  Beatriz de Carvalho Rocha; Beatriz Salomão Porto-Alegre Rosa; Thaís Santos Cerqueira; Sergio Lins de-Azevedo-Vaz; Gabriella Lopes de Rezende Barbosa; Liana Matos Ferreira; Francielle Silvestre Verner; Maria Augusta Visconti
Journal:  Dentomaxillofac Radiol       Date:  2020-11-13       Impact factor: 2.419

5.  Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices.

Authors:  Kristina Lisk; Anne M R Agur; Nicole N Woods
Journal:  Perspect Med Educ       Date:  2016-06

Review 6.  Is the diagnostic radiological image an underutilised resource? Exploring the literature.

Authors:  William A S Cox; Penelope Cavenagh; Fernando Bello
Journal:  Insights Imaging       Date:  2019-02-06

7.  Constructing an experiential education model in undergraduate radiology education by the utilization of the picture archiving and communication system (PACS).

Authors:  Yingqian Chen; Keguo Zheng; Shanshan Ye; Jifei Wang; Ling Xu; Ziping Li; Quanfei Meng; Jianyong Yang; Shi-Ting Feng
Journal:  BMC Med Educ       Date:  2019-10-21       Impact factor: 2.463

8.  Dental students' ability to detect maxillary sinus abnormalities: A comparison between panoramic radiography and cone-beam computed tomography.

Authors:  Lucas de Paula Lopes Rosado; Izabele Sales Barbosa; Sibele Nascimento de Aquino; Rafael Binato Junqueira; Francielle Silvestre Verner
Journal:  Imaging Sci Dent       Date:  2019-09-24

9.  Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study.

Authors:  Jay Hegdé
Journal:  J Med Imaging (Bellingham)       Date:  2020-02-04

10.  Training methods that improve MD-PhD student self-efficacy for clinical research skills.

Authors:  Mathew Sebastian; Matthew A Robinson; Leanne Dumeny; Kyle A Dyson; Joseph C Fantone; Wayne T McCormack; W Stratford May
Journal:  J Clin Transl Sci       Date:  2019-10-14
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