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April 18, 2017; 88 (16 Supplement) April 28, 2017

What factors predict Fitbit adherence in Stroke and Parkinson disease? (P6.029)

Katrina Schrader, Helena Mentis, Michael Phipps, Erik Barr, Ann Gruber-Baldini, Karen Yarbrough, F. Rainer Von Coelln, Lisa Shulman
First published April 17, 2017,
Katrina Schrader
1University of Maryland School of Medicine Baltimore MD United States
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Helena Mentis
3Information Systems, University of Maryland Baltimore County Baltimore MD United States
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Michael Phipps
1University of Maryland School of Medicine Baltimore MD United States
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Erik Barr
2Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine Baltimore MD United States
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Ann Gruber-Baldini
2Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine Baltimore MD United States
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Karen Yarbrough
1University of Maryland School of Medicine Baltimore MD United States
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F. Rainer Von Coelln
1University of Maryland School of Medicine Baltimore MD United States
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Lisa Shulman
1University of Maryland School of Medicine Baltimore MD United States
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Citation
What factors predict Fitbit adherence in Stroke and Parkinson disease? (P6.029)
Katrina Schrader, Helena Mentis, Michael Phipps, Erik Barr, Ann Gruber-Baldini, Karen Yarbrough, F. Rainer Von Coelln, Lisa Shulman
Neurology Apr 2017, 88 (16 Supplement) P6.029;

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Abstract

Objective: To investigate predictors of adherence to wearing the Fitbit activity monitor in patients with Parkinson disease (PD) and stroke.

Background: Exercise and activity improve symptoms of PD and stroke, and aid in primary and secondary stroke prevention. However, adherence to physical activity programs is low and little is known about adherence to daily activity monitoring.

Design/Methods: Patients (n=19, age=58.8+/−11, range 37–83Y) with PD (n=12) and stroke (n=8) participated in a pilot study to investigate feasibility and adherence of Fitbit monitoring to track activity between clinical office visits.

Results: Comparing PD and stroke, PD patients were more disabled (Rankin; p= .004) but more likely to be employed (p= .03). Stroke patients were more depressed (PROMIS; p=.045), more cognitively impaired (MoCA; p=.02) and had lower numeracy (Subjective Numeracy Scale; p=.03). Fitbit data was collected for 28–53 days (mean=32.9). Patients used the Fitbit for 86% of days and 13.5 hours/day on average. Average steps/day were 6041+/−2797. The only significant predictor of adherence to the Fitbit (% of days used) was medical co-morbidity (r=−.46, p=.047) such that those with greater comorbidity (Cumulative Illness Rating Scale) wore the Fitbit less. Other high correlations with adherence (but nonsignificant) were: PROMIS Self-Efficacy for Managing Medications (r=.57), Self-Efficacy for Managing Social Interactions (r=.46), greater e-Health Literacy (eHEALs; r=.39), and less pain (r=−.37). Adherence showed low correlation (r<.2) with disease severity, disability, cognition, depression, age and socioeconomic status.

Conclusions: The strongest predictor of adherence to daily activity monitoring was level of medical co-morbidity. Other determinants of adherence were self-efficacy for managing conditions, e-Health literacy and pain. Age and level of disability did not affect daily use of small wireless monitors to track activity in stroke and PD.

Disclosure: Dr. Schrader has nothing to disclose. Dr. Mentis has nothing to disclose. Dr. Phipps has nothing to disclose. Dr. Barr has nothing to disclose. Dr. Gruber-Baldini has nothing to disclose. Dr. Yarbrough has nothing to disclose. Dr. Von Coelln has nothing to disclose. Dr. Shulman has received personal compensation in an editorial capacity for AAN Neurology Now. Dr. Shulman has received research support from Biotie Therapies.

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