INS NYC 2024 Program

Poster	Poster Session 04 Program Schedule 02/15/2024 12:00 pm - 01:15 pm Room: Shubert Complex (Posters 1-60) Poster Session 04: Neuroimaging \| Neurostimulation/Neuromodulation \| Teleneuropsychology/Technology Final Abstract #53 A Case Study: Remote Digital Cognitive Assessment of On and Off Medication States in Parkinson’s Disease Valerie Humphreys, University of Pennsylvania, Philadelphia, United States Dung Pham, University of Pennsylvania, Philadelphia, United States Kimberly Halberstadter, University of Pennsylvania, Philadelphia, United States Defne Tim, University of Pennsylvania, Philadelphia, United States Casey Halpern, University of Pennsylvania, Philadelphia, United States Roy Hamilton, University of Pennsylvania, Philadelphia, United States Dawn Mechanic-Hamilton, University of Pennsylvania, Philadelphia, United States Category: Neurodegenerative Disorders Keyword 1: technology Keyword 2: assessment Keyword 3: Parkinson's disease Objective: Mobile app-based cognitive testing may serve as a timely and cost-effective tool for capturing subtle and fluctuating impairments in cognition. These tools must be validated in real-world settings with relevant populations. The majority of patients with Parkinson’s Disease (PD) experience cognitive impairment over the course of the disease, ranging from mild cognitive impairment to dementia. Patients with PD report fluctuations in their motor and cognitive abilities on and off medications. The current case study aims to study at-home usability and feasibility of the Mobile Cognitive Assessment Performance Platform (mCAPP) in a patient with PD, experiencing cognitive fluctuations, to evaluate its potential use for detecting and monitoring day-to-day cognitive changes. Participants and Methods: The participant was a 73 year-old male with an advanced professional degree. He had symptoms for 10 years and reported improvement in his cognition on PD medication. Motor symptoms included tremor, reduced dexterity, and balance impairment. Participation included two in-clinic testing sessions and 12 sessions of at-home testing with mCAPP. The participant recorded self-ratings of his medication state, from very ‘ON’ to very ‘OFF’, on a 5-point scale, and level of fatigue, stress, and anxiety, on a 10-point scale. In-person visits included paper-and-pencil neuropsychological assessments and the mCAPP tasks, which include a memory flip-card game (Concentration Memory), a stroop-like task with three blocks (Brick Drop), and a symbol-digit-modalities-like task with three difficulty levels (Space Impostors). A mobile phone with the mCAPP app was sent home with the participant to collect data twice daily for 6 days. Results: The participant reported medium levels of stress (M=6.0, SD=1.4) and fatigue (M=6.3, SD=2.3), and a low level of anxiety (M=0.9, SD=0.8) across ‘ON’ and ‘OFF’ states. A comparison of mean response times ‘ON’ and ‘OFF’ medications was conducted for each mCAPP task using independent-sample t-tests. On the Brick Drop task, response time was slower in the ‘OFF’ state compared to the ‘ON’ state for word reading block (p=.03), the color naming block (p<.001) and the inhibition block (p=.03) and remained significant for the inhibition block when accounting for performance on the simple response speed block (reading). On the Concentration Memory Task, average response time was significantly slower in the ‘OFF’ state compared to ON’ state on non-lure trials (distinct card pairs; p<.001) and lure trials (similar card pairs; p<.001). No significant differences were found on the Space Impostors task. Conclusions: This case study provides support for initial usability and feasibility for at-home mobile digital cognitive assessment in PD. The detection of expected slower response times during ‘OFF’ states compared to ‘ON’ states demonstrates that the mCAPP app is sensitive to differences in medication state, including when accounting for simple motor speed. Taken together, the current findings reflect the potential of mobile cognitive testing tools to monitor cognition remotely and inform adjustments to treatment.

Poster

02/15/2024
12:00 pm - 01:15 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 04: Neuroimaging | Neurostimulation/Neuromodulation | Teleneuropsychology/Technology

Final Abstract #53

A Case Study: Remote Digital Cognitive Assessment of On and Off Medication States in Parkinson’s Disease

Valerie Humphreys, University of Pennsylvania, Philadelphia, United States
Dung Pham, University of Pennsylvania, Philadelphia, United States
Kimberly Halberstadter, University of Pennsylvania, Philadelphia, United States
Defne Tim, University of Pennsylvania, Philadelphia, United States
Casey Halpern, University of Pennsylvania, Philadelphia, United States
Roy Hamilton, University of Pennsylvania, Philadelphia, United States
Dawn Mechanic-Hamilton, University of Pennsylvania, Philadelphia, United States

Category: Neurodegenerative Disorders

Keyword 1: technology
Keyword 2: assessment
Keyword 3: Parkinson's disease

Objective:

Mobile app-based cognitive testing may serve as a timely and cost-effective tool for capturing subtle and fluctuating impairments in cognition. These tools must be validated in real-world settings with relevant populations. The majority of patients with Parkinson’s Disease (PD) experience cognitive impairment over the course of the disease, ranging from mild cognitive impairment to dementia. Patients with PD report fluctuations in their motor and cognitive abilities on and off medications. The current case study aims to study at-home usability and feasibility of the Mobile Cognitive Assessment Performance Platform (mCAPP) in a patient with PD, experiencing cognitive fluctuations, to evaluate its potential use for detecting and monitoring day-to-day cognitive changes.

Participants and Methods:

The participant was a 73 year-old male with an advanced professional degree. He had symptoms for 10 years and reported improvement in his cognition on PD medication. Motor symptoms included tremor, reduced dexterity, and balance impairment. Participation included two in-clinic testing sessions and 12 sessions of at-home testing with mCAPP. The participant recorded self-ratings of his medication state, from very ‘ON’ to very ‘OFF’, on a 5-point scale, and level of fatigue, stress, and anxiety, on a 10-point scale. In-person visits included paper-and-pencil neuropsychological assessments and the mCAPP tasks, which include a memory flip-card game (Concentration Memory), a stroop-like task with three blocks (Brick Drop), and a symbol-digit-modalities-like task with three difficulty levels (Space Impostors). A mobile phone with the mCAPP app was sent home with the participant to collect data twice daily for 6 days.

Results:

The participant reported medium levels of stress (M=6.0, SD=1.4) and fatigue (M=6.3, SD=2.3), and a low level of anxiety (M=0.9, SD=0.8) across ‘ON’ and ‘OFF’ states. A comparison of mean response times ‘ON’ and ‘OFF’ medications was conducted for each mCAPP task using independent-sample t-tests. On the Brick Drop task, response time was slower in the ‘OFF’ state compared to the ‘ON’ state for word reading block (p=.03), the color naming block (p<.001) and the inhibition block (p=.03) and remained significant for the inhibition block when accounting for performance on the simple response speed block (reading). On the Concentration Memory Task, average response time was significantly slower in the ‘OFF’ state compared to ON’ state on non-lure trials (distinct card pairs; p<.001) and lure trials (similar card pairs; p<.001). No significant differences were found on the Space Impostors task.

Conclusions:

This case study provides support for initial usability and feasibility for at-home mobile digital cognitive assessment in PD. The detection of expected slower response times during ‘OFF’ states compared to ‘ON’ states demonstrates that the mCAPP app is sensitive to differences in medication state, including when accounting for simple motor speed. Taken together, the current findings reflect the potential of mobile cognitive testing tools to monitor cognition remotely and inform adjustments to treatment.