Research Center for Clinical Neuroimmunology and Neuroscience Basel, University of Basel, University Hospital Basel, Basel, Switzerland.
Department of Neurology, University Hospital Basel, Basel, Switzerland.
J Med Internet Res. 2021 Nov 18;23(11):e30394. doi: 10.2196/30394.
Smartphones and their built-in sensors allow for measuring functions in disease-related domains through mobile tests. This could improve disease characterization and monitoring, and could potentially support treatment decisions for multiple sclerosis (MS), a multifaceted chronic neurological disease with highly variable clinical manifestations. Practice effects can complicate the interpretation of both improvement over time by potentially exaggerating treatment effects and stability by masking deterioration.
The aim of this study is to identify short-term learning and long-term practice effects in 6 active tests for cognition, dexterity, and mobility in user-scheduled, high-frequency smartphone-based testing.
We analyzed data from 264 people with self-declared MS with a minimum of 5 weeks of follow-up and at least 5 repetitions per test in the Floodlight Open study, a self-enrollment study accessible by smartphone owners from 16 countries. The collected data are openly available to scientists. Using regression and bounded growth mixed models, we characterized practice effects for the following tests: electronic Symbol Digit Modalities Test (e-SDMT) for cognition; Finger Pinching and Draw a Shape for dexterity; and Two Minute Walk, U-Turn, and Static Balance for mobility.
Strong practice effects were found for e-SDMT (n=4824 trials), Finger Pinching (n=19,650), and Draw a Shape (n=19,019) with modeled boundary improvements of 40.8% (39.9%-41.6%), 86.2% (83.6%-88.7%), and 23.1% (20.9%-25.2%) over baseline, respectively. Half of the practice effect was reached after 11 repetitions for e-SDMT, 28 repetitions for Finger Pinching, and 17 repetitions for Draw a Shape; 90% was reached after 35, 94, and 56 repetitions, respectively. Although baseline performance levels were highly variable across participants, no significant differences between the short-term learning effects in low performers (5th and 25th percentile), median performers, and high performers (75th and 95th percentile) were found for e-SDMT up to the fifth trial (β=1.50-2.00). Only small differences were observed for Finger Pinching (β=1.25-2.5). For U-Turn (n=15,051) and Static Balance (n=16,797), only short-term learning effects could be observed, which ceased after a maximum of 5 trials. For Two Minute Walk (n=14,393), neither short-term learning nor long-term practice effects were observed.
Smartphone-based tests are promising for monitoring the disease trajectories of MS and other chronic neurological diseases. Our findings suggest that strong long-term practice effects in cognitive and dexterity functions have to be accounted for to identify disease-related changes in these domains, especially in the context of personalized health and in studies without a comparator arm. In contrast, changes in mobility may be more easily interpreted because of the absence of long-term practice effects, even though short-term learning effects might have to be considered.
智能手机及其内置传感器可通过移动测试来测量与疾病相关领域的功能。这可以改善疾病特征描述和监测,并有可能支持多发性硬化症 (MS) 的治疗决策,MS 是一种具有高度变化临床表现的多方面慢性神经系统疾病。练习效应可能会使治疗效果变得复杂,因为它可能通过夸大治疗效果来改善,也可能通过掩盖病情恶化来保持稳定。
本研究旨在确定在用户计划的、高频智能手机测试中,用于认知、灵巧性和移动性的 6 种主动测试中的短期学习和长期练习效应。
我们分析了来自 264 名自我报告的 MS 患者的数据,这些患者在 Floodlight Open 研究中至少有 5 周的随访,并且每个测试至少重复 5 次。该研究对来自 16 个国家的智能手机所有者开放。收集的数据对科学家开放。使用回归和有界增长混合模型,我们对以下测试的练习效应进行了描述:电子符号数字模态测试 (e-SDMT) 用于认知;手指捏合和绘制形状用于灵巧性;两分钟步行、U 形转弯和静态平衡用于移动性。
我们发现 e-SDMT(n=4824 次试验)、手指捏合(n=19650 次)和绘制形状(n=19019 次)存在强烈的练习效应,建模边界改善分别为 40.8%(39.9%-41.6%)、86.2%(83.6%-88.7%)和 23.1%(20.9%-25.2%)。e-SDMT 在 11 次重复后达到一半的练习效果,手指捏合达到 28 次重复,绘制形状达到 17 次重复;达到 90%分别需要 35、94 和 56 次重复。尽管参与者的基线表现水平差异很大,但在 e-SDMT 的前五次试验中,并未发现低表现者(第 5 百分位和第 25 百分位)、中位数表现者和高表现者(第 75 百分位和第 95 百分位)之间的短期学习效果存在显著差异(β=1.50-2.00)。在手指捏合方面仅观察到微小差异(β=1.25-2.5)。对于 U 形转弯(n=15051)和静态平衡(n=16797),仅观察到短期学习效果,在最多 5 次试验后停止。对于两分钟步行(n=14393),既没有观察到短期学习也没有观察到长期练习效应。
基于智能手机的测试有望监测 MS 和其他慢性神经系统疾病的疾病轨迹。我们的发现表明,在这些领域中识别与疾病相关的变化时,必须考虑认知和灵巧功能的长期强烈练习效应,尤其是在个性化健康和没有对照组的研究中。相比之下,由于没有长期的练习效应,移动性的变化可能更容易解释,尽管可能需要考虑短期学习效应。