Using Smartphones to Reduce Research Burden in a Neurodegenerative Population and Assessing Participant Adherence: A Randomized Clinical Trial and Two Observational Studies.
Using Smartphones to Reduce Research Burden in a Neurodegenerative Population and Assessing Participant Adherence: A Randomized Clinical Trial and Two Observational Studies.
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DOI：
10.2196/31877
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发表时间：
2022-02-04
影响因子：
5
通讯作者：
Onnela JP
中科院分区：
文献类型：
--
作者：
Beukenhorst AL;Burke KM;Scheier Z;Miller TM;Paganoni S;Keegan M;Collins E;Connaghan KP;Tay A;Chan J;Berry JD;Onnela JP
智能手机研究提供了一个机会，以低负担的参与者收集频繁的数据。因此，智能手机可以使数据收集的人进行性神经退行性疾病，如肌萎缩侧索硬化症在高频率的一段时间。然而，患者认知和功能能力的逐渐下降也可能阻碍长期收集患者报告结果、录音和位置数据的可行性。本研究的目的是调查调查数据的完整性，录音，被动收集的位置数据从3个智能手机为基础的肌萎缩侧索硬化症患者的研究。我们分析了3项研究的数据完整性：2项观察性队列研究（研究1：N=22;持续时间=12周;研究2：N=49;持续时间=52周）和1项临床试验（研究3：N=49;持续时间=20周）。在这些研究中，参与者被要求完成每周调查;每周录音;在后台，应用程序收集传感器数据，包括位置数据。对于三项研究和三个数据流中的每一项，我们使用Kaplan-Meier方法估计至停药时间。我们使用考克斯比例风险回归分析确定了应用停药的预测因素。我们量化了早期辍学者和参与时间更长的参与者的数据完整性。至停药时间在为期一年的观察性研究中最短，在临床试验中最长。在研究3个月后，大多数参与者仍然完成了调查和录音：研究1为77%（17/22），研究2为59%（29/49），研究3为96%（22/23）。3个月后，被动收集的位置数据分别收集了95%（21/22），86%（42/49）和100%（23/23）的参与者。考克斯回归没有提供证据表明基线时的人口统计学特征或疾病严重程度与损耗相关，尽管其效力有些不足。被动收集位置数据的平均数据完整性最高。对于大多数参与者来说，数据完整性随着时间的推移而下降;平均数据完整性通常在参与者退出前一个月较低。此外，与长期坚持的参与者相比，在第一个研究月退出的人的数据完整性较低（数据点很少）（数据完整性在75%左右波动）。这三项研究成功地从神经退行性疾病人群中纵向收集了智能手机数据。尽管患者的身体和认知能力逐渐下降，但停药时间高于典型的智能手机研究。我们的研究为参与神经退行性疾病人群的参与提供了一个重要的基准。为了提高数据的完整性，收集被动数据（如位置数据）并识别可能在研究初始阶段坚持的参与者可能是有用的。ClinicalTrials.gov NCT03168711; https://clinicaltrials.gov/ct2/show/NCT03168711
Smartphone studies provide an opportunity to collect frequent data at a low burden on participants. Therefore, smartphones may enable data collection from people with progressive neurodegenerative diseases such as amyotrophic lateral sclerosis at high frequencies for a long duration. However, the progressive decline in patients’ cognitive and functional abilities could also hamper the feasibility of collecting patient-reported outcomes, audio recordings, and location data in the long term. The aim of this study is to investigate the completeness of survey data, audio recordings, and passively collected location data from 3 smartphone-based studies of people with amyotrophic lateral sclerosis. We analyzed data completeness in three studies: 2 observational cohort studies (study 1: N=22; duration=12 weeks and study 2: N=49; duration=52 weeks) and 1 clinical trial (study 3: N=49; duration=20 weeks). In these studies, participants were asked to complete weekly surveys; weekly audio recordings; and in the background, the app collected sensor data, including location data. For each of the three studies and each of the three data streams, we estimated time-to-discontinuation using the Kaplan–Meier method. We identified predictors of app discontinuation using Cox proportional hazards regression analysis. We quantified data completeness for both early dropouts and participants who remained engaged for longer. Time-to-discontinuation was shortest in the year-long observational study and longest in the clinical trial. After 3 months in the study, most participants still completed surveys and audio recordings: 77% (17/22) in study 1, 59% (29/49) in study 2, and 96% (22/23) in study 3. After 3 months, passively collected location data were collected for 95% (21/22), 86% (42/49), and 100% (23/23) of the participants. The Cox regression did not provide evidence that demographic characteristics or disease severity at baseline were associated with attrition, although it was somewhat underpowered. The mean data completeness was the highest for passively collected location data. For most participants, data completeness declined over time; mean data completeness was typically lower in the month before participants dropped out. Moreover, data completeness was lower for people who dropped out in the first study month (very few data points) compared with participants who adhered long term (data completeness fluctuating around 75%). These three studies successfully collected smartphone data longitudinally from a neurodegenerative population. Despite patients’ progressive physical and cognitive decline, time-to-discontinuation was higher than in typical smartphone studies. Our study provides an important benchmark for participant engagement in a neurodegenerative population. To increase data completeness, collecting passive data (such as location data) and identifying participants who are likely to adhere during the initial phase of a study can be useful. ClinicalTrials.gov NCT03168711; https://clinicaltrials.gov/ct2/show/NCT03168711
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影响因子：
4.6
作者：
Kiang MV;Chen JT;Krieger N;Buckee CO;Alexander MJ;Baker JT;Buckner RL;Coombs G 3rd;Rich-Edwards JW;Carlson KW;Onnela JP
通讯作者：
Onnela JP
影响因子：
5.2
作者：
Torous J;Kiang MV;Lorme J;Onnela JP
通讯作者：
Onnela JP
影响因子：
3.4
作者：
Beukenhorst AL;Collins E;Burke KM;Rahman SM;Clapp M;Konanki SC;Paganoni S;Miller TM;Chan J;Onnela JP;Berry JD
通讯作者：
Berry JD
影响因子：
4.4
作者：
Cedarbaum, JM;Stambler, N;Nakanishi, A
通讯作者：
Nakanishi, A
影响因子：
2.3
作者：
Druce, Katie L.;Dixon, William G.;McBeth, John
通讯作者：
McBeth, John