ObjectivesTo assess the feasibility, predictive value, and user satisfaction of objectively quantifying motor function in Parkinson’s disease (PD) through a tablet-based application (iMotor) using self-administered tests.MethodsPD and healthy controls (HCs) performed finger tapping, hand pronation–supination and reaction time tasks using the iMotor application.ResultsThirty-eight participants (19 with PD and 17 HCs) were recruited in the study. PD subjects were 53% male, with a mean age of 67.8 years (±8.8), mean disease duration of 6.5 years (±4.6), Movement Disorders Society version of the Unified Parkinson Disease Rating Scale III score 26.3 (±6.7), and Hoehn & Yahr stage 2. In the univariate analysis, most tapping variables were significantly different in PD compared to HC. Tap interval provided the highest predictive ability (90%). In the multivariable logistic regression model reaction time (reaction time test) (p = 0.021) and total taps (two-target test) (p = 0.026) were associated with PD. A combined model with two-target (total taps and accuracy) and reaction time produced maximum discriminatory performance between HC and PD. The overall accuracy of the combined model was 0.98 (95% confidence interval: 0.93–1). iMotor use achieved high rates of patients’ satisfaction as evaluated by a patient satisfaction survey.ConclusioniMotor differentiated PD subjects from HCs using simple alternating tasks of motor function. Results of this feasibility study should be replicated in larger, longitudinal, appropriately designed, controlled studies. The impact on patient care of at-home iMotor-assisted remote monitoring also deserves further evaluation.

Objective Pilot study to evaluate computer-guided deep brain stimulation (DBS) programming designed to optimize stimulation settings using objective motion sensor-based motor assessments. Materials and Methods Seven subjects (5 males; 54-71 years) with Parkinson's disease (PD) and recently implanted DBS systems participated in this pilot study. Within two months of lead implantation, the subject returned to the clinic to undergo computer-guided programming and parameter selection. A motion sensor was placed on the index finger of the more affected hand. Software guided a monopolar survey during which monopolar stimulation on each contact was iteratively increased followed by an automated assessment of tremor and bradykinesia. After completing assessments at each setting, a software algorithm determined stimulation settings designed to minimize symptom severities, side effects, and battery usage. Results Optimal DBS settings were chosen based on average severity of motor symptoms measured by the motion sensor. Settings chosen by the software algorithm identified a therapeutic window and improved tremor and bradykinesia by an average of 35.7% compared to baseline in the “off” state (p<0.01). Conclusions Motion sensor-based computer-guided DBS programming identified stimulation parameters that significantly improved tremor and bradykinesia with minimal clinician involvement. Automated motion sensor-based mapping is worthy of further investigation and may one day serve to extend programming to populations without access to specialized DBS centers.

Women experience a unique health trajectory after PD diagnosis as suggested by differing comorbid disease burden and health care utilization compared to men. Future studies of sex differences in care needs, care quality, comorbidity related disability, PD progression, and non-clinical factors associated with disability are needed to inform research agendas and clinical guidelines that may improve quality survival for women with PD.

This randomized trial will evaluate the mechanisms of three chronic pain treatments: cognitive therapy (CT), mindfulness meditation (MM), and activation skills (AS). We will determine the extent to which late-treatment improvement in primary outcome (pain interference) is predicted by early-treatment changes in cognitive content, cognitive process, and/or activity level. The shared versus specific role of these mechanisms across the three treatments will be evaluated during treatment (Primary Aim), and immediately post-treatment to examine relapse mechanisms (Secondary Aim). We will enroll 300 individuals with chronic pain (with low back pain as a primary or secondary condition), with 240 projected to complete the study. Participants will be randomly assigned to eight, 1.5 h telehealth group sessions of CT, MM, or AS. Mechanisms and outcomes will be assessed twice daily during 2-week baseline, 4week treatment period, and 4-week post-treatment epoch via random cue-elicited ecological momentary assessment (EMA); activity level will be monitored during these time epochs via daily monitoring with ActiGraph technology. The primary outcome will be measured by the PROMIS 5-item Pain Interference scale. Structural equation modeling (SEM) will be used to test the primary aims. This study is pre-registered on clinicaltrials.gov (Identifier: NCT03687762). This study will determine the temporal sequence of lagged mediation effects to evaluate rates of change in outcome as a function of change in mediators. The findings will provide an empirical basis for enhancing and streamlining psychosocial chronic pain interventions. Further, results will guide future efforts towards optimizing maintenance of gains to effectively reduce relapse risk.