MyofAPPcial:用于改善肌筋膜疼痛综合征临床推理的新型技术辅助工具的结构有效性。

IF 4.4 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL European Journal of Clinical Investigation Pub Date : 2024-09-06 DOI:10.1111/eci.14313
Juan Antonio Valera-Calero, Umut Varol, Ricardo Ortega-Santiago, Marcos José Navarro-Santana, María José Díaz-Arribas, Jorge Buffet-García, Gustavo Plaza-Manzano
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引用次数: 0

摘要

背景:物理治疗师在诊断肌筋膜触发点(MTrPs)时遇到了挑战,这对治疗肌筋膜疼痛至关重要,但由于其复杂的转归疼痛模式而难以诊断。我们的目的是评估一款互动软件(MyofAPPcial)能否提高肌肉骨骼疾病专业理疗师(作为临床医生、研究人员和教育工作者)识别与特定 MTrPs 相关的转归疼痛模式的能力,并探讨他们对将该技术定期纳入其专业环境的看法:在开发出应用程序后,进行了一项描述性横断面调查研究。调查询问了参与者的人口统计学特征、专业经验、两次知识测试(先是没有 MyofAPPcial 支持的测试,后是有 MyofAPPcial 支持的测试)以及 18 项移动医疗应用程序可用性问卷:59名参与者完成了调查(47.5%为临床医生,62.5%为研究人员/教育工作者)。各组在年龄、性别和专业经验方面具有可比性(P > .05)。不过,临床医生接受的 MPS 培训时间较短(p = .007),每周处理的病例较多(p .05),总分也较低(p > .05)。在第二项知识测试中,两组的所有项目均为满分。最后,MyofAPPcial 在满意度和应用程序实用性方面得分很高,临床医生和研究人员/教育工作者之间没有差异(除了研究人员/教育工作者使用起来更方便 p = .02):MyofAPPcial提高了物理治疗师准确识别MTrPs的能力,在临床医生和研究人员/教育工作者中的接受度很高。
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MyofAPPcial: Construct validity of a novel technological aid for improving clinical reasoning in the management of myofascial pain syndrome

Background

Physiotherapists encounter challenges in diagnosing myofascial trigger points (MTrPs), which are crucial for managing myofascial pain but difficult due to their complex referred pain patterns. We aimed to assess if an interactive software (MyofAPPcial) can enhance the ability of physical therapists specialized in musculoskeletal disorders (as clinicians and as researchers and educators) to identify referred pain patterns associated with specific MTrPs and to explore their opinion about incorporating this technology regularly into their professional setting.

Methods

After developing the app, a descriptive cross-sectional survey study was conducted. Participants were asked about their demographic characteristics, professional experience, two knowledge tests (first without and later with MyofAPPcial support) and the 18-item mHealth app usability questionnaire.

Results

Fifty-nine participants completed the survey (47.5% clinicians and 62.5% researchers/educators). Groups were comparable in terms of age, gender and professional experience (p > .05). However, clinicians coursed shorter specific MPS trainings (p = .007) and handle more cases a week (p < .001). In the first knowledge test, participants in both the groups were more accurate in identifying pain maps of highly prevalent MTrPs than those with a moderate or low prevalence (p < .001), with no differences between the groups for individual items (all, p > .05) nor the total score (p > .05). In the second knowledge test, perfect scores were obtained for all items in both the groups. Finally, MyofAPPcial scored high satisfaction and app usefulness, with no difference between clinicians and researchers/educators (except greater convenience of use for researchers/educators p = .02).

Conclusions

MyofAPPcial enhances physiotherapists' ability to accurately identify MTrPs, with a good acceptation among clinicians and researchers/educators.

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CiteScore
9.50
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3.60%
发文量
192
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期刊介绍: EJCI considers any original contribution from the most sophisticated basic molecular sciences to applied clinical and translational research and evidence-based medicine across a broad range of subspecialties. The EJCI publishes reports of high-quality research that pertain to the genetic, molecular, cellular, or physiological basis of human biology and disease, as well as research that addresses prevalence, diagnosis, course, treatment, and prevention of disease. We are primarily interested in studies directly pertinent to humans, but submission of robust in vitro and animal work is also encouraged. Interdisciplinary work and research using innovative methods and combinations of laboratory, clinical, and epidemiological methodologies and techniques is of great interest to the journal. Several categories of manuscripts (for detailed description see below) are considered: editorials, original articles (also including randomized clinical trials, systematic reviews and meta-analyses), reviews (narrative reviews), opinion articles (including debates, perspectives and commentaries); and letters to the Editor.
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Ceramide and phosphatidylcholine lipids-based risk score predicts major cardiovascular outcomes in patients with heart failure. Issue Information [225Ac]Ac-PSMA for the treatment of metastatic castration-resistant prostate cancer: A systematic review and meta-analysis. Machine learning for stroke in heart failure with reduced ejection fraction but without atrial fibrillation: A post-hoc analysis of the WARCEF trial. Structural aspects of CEACAM1 interactions.
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