Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jul 26, 2019
Open Peer Review Period: Jul 29, 2019 - Sep 23, 2019
Date Accepted: Dec 15, 2019
Date Submitted to PubMed: Apr 27, 2020
(closed for review but you can still tweet)
Development and validation of mHealth monitoring for Parkinson’s disease based on ecological momentary assessments
ABSTRACT
Background:
Parkinson’s disease (PD) monitoring is making a transition from periodic clinical assessments to continuous daily life monitoring in ‘free-living’ conditions. Traditional PD monitor methods lack intraday fluctuation detection. Electronical diaries (eDiaries) hold potential to collect subjective experiences on the severity and burden of (non-)motor symptoms in free-living conditions.
Objective:
We aim to develop a PD specific eDiary based on ecological momentary assessments (EMA) and explore its validation.
Methods:
An observational cohort of twenty PD patients used the smartphone-based EMA eDiary for fourteen consecutive days without adjusting free-living routines. It presented an identical questionnaire consisting questions regarding affect, context, motor and non-motor symptoms and motor performance seven times daily at semi-randomized moments. Additionally, patients were asked to complete a morning and an evening questionnaire.
Results:
Mean affect correlated respectively moderate to strong and moderate with motor performance (R = 0.38 – 0.75, p<0.001) and motor symptom (R = 0.34 – 0.50, p<0.001) items. Motor performance showed a weak to moderate negative correlation with motor symptoms (R = -0.31 - -0.48, p<0.001). Group mean answers given in on- versus wearing off-medication conditions differed significantly (p < 0.05), however not enough questionnaires were completed in wearing off condition to reproduce these findings on individual levels.
Conclusions:
We present a PD specific EMA-eDiary. Correlations between given answers support the internal validity of the eDiary and underline EMA’s potential in free-living PD 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 PD knowledge with practical EMA experience is inevitable to design and perform studies which will lead to successful integration of eDiaries in free-living PD monitoring.
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Copyright
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