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用于人体解剖学教学的移动应用程序综述:搜索与质量评估研究

Reviewing Mobile Apps for Teaching Human Anatomy: Search and Quality Evaluation Study.

作者信息

Rivera García Guadalupe Esmeralda, Cervantes López Miriam Janet, Ramírez Vázquez Juan Carlos, Llanes Castillo Arturo, Cruz Casados Jaime

机构信息

Tecnológico Nacional de México, Instituto Tecnológico Superior de Pánuco, Pánuco, Veracruz, Mexico.

Facultad de Medicina de Tampico "Dr. Alberto Romo Caballero" de la Universidad Autónoma de Tamaulipas, Tampico, Tamaulipas, Mexico.

出版信息

JMIR Med Educ. 2025 Feb 14;11:e64550. doi: 10.2196/64550.


DOI:10.2196/64550
PMID:39951706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11888001/
Abstract

BACKGROUND: Mobile apps designed for teaching human anatomy offer a flexible, interactive, and personalized learning platform, enriching the educational experience for both students and health care professionals. OBJECTIVE: This study aimed to conduct a systematic review of the human anatomy mobile apps available on Google Play, evaluate their quality, highlight the highest scoring apps, and determine the relationship between objective quality ratings and subjective star ratings. METHODS: The Mobile App Rating Scale (MARS) was used to evaluate the apps. The intraclass correlation coefficient was calculated using a consistency-type 2-factor random model to measure the reliability of the evaluations made by the experts. In addition, Pearson correlations were used to analyze the relationship between MARS quality scores and subjective evaluations of MARS quality item 23. RESULTS: The mobile apps with the highest overall quality scores according to the MARS (ie, sections A, B, C, and D) were Organos internos 3D (anatomía) (version 4.34), Sistema óseo en 3D (Anatomía) (version 4.32), and VOKA Anatomy Pro (version 4.29). To measure the reliability of the MARS quality evaluations (sections A, B, C, and D), the intraclass correlation coefficient was used, and the result was "excellent." Finally, Pearson correlation results revealed a significant relationship (r=0.989; P<.001) between the quality assessments conducted by health care professionals and the subjective evaluations of item 23. CONCLUSIONS: The average evaluation results of the selected apps indicated a "good" level of quality, and those with the highest ratings could be recommended. However, the lack of scientific backing for these technological tools is evident. It is crucial that research centers and higher education institutions commit to the active development of new mobile health apps, ensuring their accessibility and validation for the general public.

摘要

背景:专为人体解剖学教学设计的移动应用程序提供了一个灵活、互动且个性化的学习平台,丰富了学生和医疗保健专业人员的教育体验。 目的:本研究旨在对谷歌应用商店中可用的人体解剖学移动应用程序进行系统评价,评估其质量,突出评分最高的应用程序,并确定客观质量评级与主观星级评级之间的关系。 方法:使用移动应用程序评分量表(MARS)对应用程序进行评估。使用一致性类型2因素随机模型计算组内相关系数,以衡量专家评估的可靠性。此外,使用皮尔逊相关性分析MARS质量得分与MARS质量项目23的主观评估之间的关系。 结果:根据MARS(即A、B、C和D部分),总体质量得分最高的移动应用程序是Organos internos 3D(anatomía)(版本4.34)、Sistema óseo en 3D(Anatomía)(版本4.32)和VOKA Anatomy Pro(版本4.29)。为了衡量MARS质量评估(A、B、C和D部分)的可靠性,使用了组内相关系数,结果为“优秀”。最后,皮尔逊相关性结果显示,医疗保健专业人员进行的质量评估与项目23的主观评估之间存在显著关系(r=0.989;P<0.001)。 结论:所选应用程序的平均评估结果表明质量处于“良好”水平,可以推荐评分最高的应用程序。然而,这些技术工具缺乏科学支持是显而易见的。研究中心和高等教育机构必须致力于积极开发新的移动健康应用程序,确保其对公众的可及性和有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db6/11888001/6d074f503fbc/mededu_v11i1e64550_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db6/11888001/58083f091512/mededu_v11i1e64550_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db6/11888001/6d074f503fbc/mededu_v11i1e64550_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db6/11888001/58083f091512/mededu_v11i1e64550_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db6/11888001/6d074f503fbc/mededu_v11i1e64550_fig2.jpg

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本文引用的文献

[1]
The Efficacy of the Smartphone App for the Self-Management of Low Back Pain: A Systematic Review and Assessment of Their Quality through the Mobile Application Rating Scale (MARS) in Italy.

Life (Basel). 2024-6-13

[2]
Digital Apps to Improve Mobility in Adults with Neurological Conditions: A Health App-Focused Systematic Review.

Healthcare (Basel). 2024-4-30

[3]
Mobile Apps for Patients with Peritoneal Dialysis: Systematic App Search and Evaluation.

Healthcare (Basel). 2024-3-25

[4]
Applying the Participatory Slow Design Approach to a mHealth Application for Family Caregivers in Pediatric Ear, Nose, and Throat Surgery.

Healthcare (Basel). 2024-2-8

[5]
Evaluation of Mobile Applications for Patients with Diabetes Mellitus: A Scoping Review.

Healthcare (Basel). 2024-1-31

[6]
The Added Value of Face-to-Face Supervision to a Therapeutic Exercise-Based App in the Management of Patients with Chronic Low Back Pain: A Randomized Clinical Trial.

Sensors (Basel). 2024-1-16

[7]
Mobile Apps for COVID-19: A Systematic Review of Reviews.

Healthcare (Basel). 2024-1-8

[8]
The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection.

Healthcare (Basel). 2023-11-19

[9]
Impact of AfterAMI Mobile App on Quality of Life, Depression, Stress and Anxiety in Patients with Coronary Artery Disease: Open Label, Randomized Trial.

Life (Basel). 2023-10-5

[10]
Designing an Informative App for Neurorehabilitation: A Feasibility and Satisfaction Study by Physiotherapists.

Healthcare (Basel). 2023-9-14

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