Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
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Introduction: Augmented Reality (AR) has emerged as a transformative tool in health professions education, offering immersive and interactive learning experiences. This study aimed to develop and evaluate VASHA, a handheld AR application for training physicians and radiologic technicians in recognizing commonly missed fractures in extremities.
Methods: A mobile AR-based training application was developed to teach six commonly missed fractures, including the glenohumeral (shoulder) joint, cubitus (elbow) joint, radiocarpal (wrist) joint, acetabulofemoral (hip) joint, tibiofemoral (knee) joint, and talocrural (ankle) joint. A one-group pre-test and post-test study design was implemented with 46 participants to assess learning outcomes and user experience. Participants engaged in a four-week self-paced training using the VASHA application. Learning was evaluated through a 30-item multiple-choice knowledge test administered before and after the intervention, and user experience was assessed using a validated six-item questionnaire.
Results: Participants demonstrated an improvement in fracture recognition, with post-test scores (18.08 ± 4.42( being significantly higher than pre-test scores (13.91 ± 2.63) (p < 0.001). This increase in knowledge was consistent across different genders and professional backgrounds (physicians and radiologic technicians). Additionally, over 90% of participants reported a positive learning experience, highlighting the VASHA application's ease of use, educational effectiveness, and engagement.
Conclusions: This study provides evidence supporting the integration of handheld AR as a cost-effective, interactive, and scalable learning tool for fracture detection training. The findings suggest that AR-based learning enhances diagnostic accuracy, spatial reasoning, and engagement in health professions education. Future research should explore comparative studies to assess its effectiveness against traditional learning methods.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12400565 | PMC |
http://dx.doi.org/10.1186/s12909-025-07813-4 | DOI Listing |