Department of Neurosurgery, School of Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands.
Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands.
JMIR Mhealth Uhealth. 2020 May 11;8(5):e15628. doi: 10.2196/15628.
Parkinson disease monitoring is currently transitioning from periodic clinical assessments to continuous daily life monitoring in free-living conditions. Traditional Parkinson disease monitoring methods lack intraday fluctuation detection. Electronic diaries (eDiaries) hold the potential to collect subjective experiences on the severity and burden of motor and nonmotor symptoms in free-living conditions.
This study aimed to develop a Parkinson disease-specific eDiary based on ecological momentary assessments (EMAs) and to explore its validation.
An observational cohort of 20 patients with Parkinson disease used the smartphone-based EMA eDiary for 14 consecutive days without adjusting free-living routines. The eDiary app presented an identical questionnaire consisting of questions regarding affect, context, motor and nonmotor symptoms, and motor performance 7 times daily at semirandomized moments. In addition, patients were asked to complete a morning and an evening questionnaire.
Mean affect correlated moderate-to-strong and moderate with motor performance (R=0.38 to 0.75; P<.001) and motor symptom (R=0.34 to 0.50; P<.001) items, respectively. The motor performance showed a weak-to-moderate negative correlation with motor symptoms (R=-0.31 to -0.48; P<.001). Mean group answers given for on-medication conditions vs wearing-off-medication conditions differed significantly (P<.05); however, not enough questionnaires were completed for the wearing-off-medication condition to reproduce these findings on individual levels.
We presented a Parkinson disease-specific EMA eDiary. Correlations between given answers support the internal validity of the eDiary and underline EMA's potential in free-living Parkinson disease monitoring. Careful patient selection and EMA design adjustment to this targeted population and their fluctuations are necessary to generate robust proof of EMA validation in future work. Combining clinical Parkinson disease knowledge with practical EMA experience is inevitable to design and perform studies, which will lead to the successful integration of eDiaries in free-living Parkinson disease monitoring.
帕金森病的监测目前正从定期的临床评估向日常生活中的连续监测转变。传统的帕金森病监测方法缺乏日内波动检测。电子日记（eDiaries）有可能在日常生活条件下收集关于运动和非运动症状严重程度和负担的主观体验。
本研究旨在开发一种基于生态瞬时评估（EMA）的帕金森病专用电子日记，并探讨其验证。
一项观察性队列研究纳入了 20 名帕金森病患者，他们在 14 天内连续使用基于智能手机的 EMA 电子日记，而不调整日常生活习惯。电子日记应用程序每天在半随机时刻呈现一个由 7 次相同的问题组成的问卷，内容涉及情绪、环境、运动和非运动症状以及运动表现。此外，患者被要求每天早上和晚上完成一份问卷。
平均情绪与运动表现（R=0.38 至 0.75；P<.001）和运动症状（R=0.34 至 0.50；P<.001）的项目呈中度至强相关和中度相关。运动表现与运动症状呈弱至中度负相关（R=-0.31 至 -0.48；P<.001）。在药物治疗期间与药物失效期间给出的平均组回答差异显著（P<.05）；然而，在药物失效期间完成的问卷数量不足以在个体水平上重现这些发现。
我们提出了一种帕金森病专用的 EMA 电子日记。给出的答案之间的相关性支持电子日记的内部有效性，并强调了 EMA 在自由生活中的帕金森病监测中的潜力。为了在未来的工作中生成 EMA 验证的有力证据，需要对特定人群及其波动进行仔细的患者选择和 EMA 设计调整。将临床帕金森病知识与实用的 EMA 经验相结合是设计和进行研究的必要条件，这将导致电子日记在自由生活中的帕金森病监测中的成功整合。
Zotero 插件
