Tuti Timothy, Winters Niall, Muinga Naomi, Wanyama Conrad, English Mike, Paton Chris
Department of Education, University of Oxford, Oxford, United Kingdom.
Kellogg College, University of Oxford, Oxford, United Kingdom.
JMIR Res Protoc. 2019 Jul 26;8(7):e13034. doi: 10.2196/13034.
Although smartphone-based clinical training to support emergency care training is more affordable than traditional avenues of training, it is still in its infancy and remains poorly implemented. In addition, its current implementations tend to be invariant to the evolving learning needs of the intended users. In resource-limited settings, the use of such platforms coupled with serious-gaming approaches remain largely unexplored and underdeveloped, even though they offer promise in terms of addressing the health workforce skill imbalance and lack of training opportunities associated with the high neonatal mortality rates in these settings.
This randomized controlled study aims to assess the effectiveness of offering adaptive versus standard feedback through a smartphone-based serious game on health care providers' knowledge gain on the management of a neonatal medical emergency.
The study is aimed at health care workers (physicians, nurses, and clinical officers) who provide bedside neonatal care in low-income settings. We will use data captured through an Android smartphone-based serious-game app that will be downloaded to personal phones belonging to the study participants. The intervention will be adaptive feedback provided within the app. The data captured will include the level of feedback provided to participants as they learn to use the mobile app, and performance data from attempts made during the assessment questions on interactive tasks participants perform as they progress through the app on emergency neonatal care delivery. The primary endpoint will be the first two complete rounds of learning within the app, from which the individuals' "learning gains" and Morris G intervention effect size will be computed. To minimize bias, participants will be assigned to an experimental or a control group by a within-app random generator, and this process will be concealed to both the study participants and the investigators until the primary endpoint is reached.
This project was funded in November 2016. It has been approved by the Central University Research Ethics Committee of the University of Oxford and the Scientific and Ethics Review Unit of the Kenya Medical Research Institute. Recruitment and data collection began from February 2019 and will continue up to July 31, 2019. As of July 18, 2019, we enrolled 541 participants, of whom 238 reached the primary endpoint, with a further 19 qualitative interviews conducted to support evaluation. Full analysis will be conducted once we reach the end of the study recruitment period.
This study will be used to explore the effectiveness of adaptive feedback in a smartphone-based serious game on health care providers in a low-income setting. This aspect of medical education is a largely unexplored topic in this context. In this randomized experiment, the risk of performance bias across arms is moderate, given that the active ingredient of the intervention (ie, knowledge) is a latent trait that is difficult to comprehensively control for in a real-world setting. However, the influence of any resulting bias that has the ability to alter the results will be assessed using alternative methods such as qualitative interviews.
Pan African Clinical Trials Registry PACTR201901783811130; https://pactr.samrc.ac.za/TrialDisplay. aspx?TrialID=5836.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/13034.
尽管基于智能手机的临床培训以支持急救培训比传统培训途径更经济实惠,但它仍处于起步阶段,实施情况不佳。此外,其目前的实施往往无法适应目标用户不断变化的学习需求。在资源有限的环境中,尽管此类平台与严肃游戏方法相结合在解决这些环境中与高新生儿死亡率相关的卫生人力技能失衡和缺乏培训机会方面具有潜力,但在很大程度上仍未得到探索和开发。
这项随机对照研究旨在评估通过基于智能手机的严肃游戏提供适应性反馈与标准反馈对医疗保健提供者在新生儿医疗急救管理方面知识获取的有效性。
该研究针对在低收入环境中提供床边新生儿护理的医护人员(医生、护士和临床干事)。我们将使用通过基于安卓智能手机的严肃游戏应用程序捕获的数据,该应用程序将下载到属于研究参与者的个人手机上。干预措施将是应用程序内提供的适应性反馈。捕获的数据将包括在参与者学习使用移动应用程序时提供给他们的反馈水平,以及参与者在通过应用程序进行新生儿急救护理交付的交互式任务的评估问题期间所做尝试的性能数据。主要终点将是应用程序内的前两轮完整学习,从中将计算个体的“学习收获”和莫里斯G干预效应大小。为了尽量减少偏差,将通过应用程序内的随机生成器将参与者分配到实验组或对照组,并且在达到主要终点之前,此过程对研究参与者和研究人员均保密。
该项目于2016年11月获得资助。它已获得牛津大学中央大学研究伦理委员会和肯尼亚医学研究所科学与伦理审查单位的批准。招募和数据收集于2019年2月开始,并将持续到2019年7月31日。截至2019年7月18日,我们招募了541名参与者,其中238人达到主要终点,并进行了另外19次定性访谈以支持评估。一旦我们到达研究招募期结束,将进行全面分析。
本研究将用于探索在低收入环境中基于智能手机的严肃游戏中适应性反馈对医疗保健提供者的有效性。在这种情况下,医学教育的这一方面在很大程度上是一个未被探索的主题。在这个随机实验中,鉴于干预的活性成分(即知识)是一种潜在特征,在现实环境中难以全面控制,各臂之间性能偏差的风险适中。然而,将使用定性访谈等替代方法评估任何可能改变结果的偏差的影响。
泛非临床试验注册中心PACTR201901783811130;https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=5836。
国际注册报告标识符(IRRID):PRR1-10.2196/13034。