INS NYC 2024 Program

Poster	Poster Session 04 Program Schedule 02/15/2024 12:00 pm - 01:15 pm Room: Majestic Complex (Posters 61-120) Poster Session 04: Neuroimaging \| Neurostimulation/Neuromodulation \| Teleneuropsychology/Technology Final Abstract #77 Using Digital Passive Metrics to Assess the Impact of Sedentary Activity and Sleep on Processing Speed among Middle-Aged and Older Hispanics/Latinos Shay Nakahira, John A. Burns School of Medicine, Honolulu, United States Martha Lopez, University of California San Diego, San Diego, United States Alexander Demos, University of Illinois Chicago, Chicago, United States Itzel Cuevas, University of California San Diego, San Diego, United States Aastha Dubey, University of California San Diego, San Diego, United States Ricardo Bentancourt, University of California San Diego, San Diego, United States Emma Churchill, University of California San Diego, San Diego, United States Lina Scandalis, University of California San Diego, San Diego, United States Linda Gallo, San Diego State University, San Diego, United States Erin Sundermann, University of California San Diego, San Diego, United States Douglas Galasko, University of California San Diego, San Diego, United States Greg Talavera, San Diego State University, San Diego, United States María Marquine, Duke University School of Medicine, Durham, United States Raeanne Moore, University of California San Diego, San Diego, United States Category: Teleneuropsychology/ Technology Keyword 1: cognitive processing Keyword 2: sleep Keyword 3: technology Objective: Hispanics/Latinos/as/x (hereafter Latinos) are the largest ethnic or racial minority group in the United States (U.S.), yet remain widely underrepresented in research studies. Digital biomarkers, derived from various sources such as smartphones and wearables, can provide valuable insights into the relationship between lifestyle factors and cognition. Emerging research suggests that higher levels of sedentary behavior and poor sleep quality may be associated with lower levels of cognitive function, poor health outcomes, and the development of chronic diseases. In this study, we explored the relationship between a digital biomarker of processing speed, derived from smartphone typing speed, with sedentary activity and sleep efficiency among middle-aged and older Latinos. Participants and Methods: Participants included 59 Hispanic/Latino adults aged 50-70 years old living in southern California enrolled in the SALUD-Tech study (Age: M= 58.6, SD= 5.1; 70% female; Education: M=11.5, SD=4.0; 86% primarily Spanish-speaking; 80% bilingual). Participants replaced their native smartphone keyboards with the Keywise AI research keyboard (available in English and Spanish). The custom keyboard tracks keystroke metadata as people are typing (e.g., interkey time, backspace ratio). Participants also wore Fitbit smartwatches that recorded sleep and sedentary activity. Digital health data collection occurred for 30 days, with participants contributing 8,278 total typing sessions. A mixed effects model was applied to analyze typing sessions across the day for each participant, with typing speed as a function of the number of sedentary minutes per day, change in sedentary minutes across days, and number of minutes slept per night controlling for age, sex, education level, primary language, and motor precision. Results: Results showed an expected diurnal pattern with the keystroke data, demonstrating slower typing in the morning and evening relative to the afternoon. Days where participants had high sedentary activity (relative to themselves) were associated with a more pronounced diurnal pattern (i.e., more evening slowing) relative to days that they were more active. Further, results revealed significant interactions with this pattern and sleep, such that on days participants were more active, the amount of sleep received the prior night had a lesser impact on the degree of typing slowing throughout the day. Specifically, when participants slept less (e.g., 5.8 hours) the night before more sedentary days, slowing in typing speed from day to evening was more pronounced (i.e., from 440 ms to 600 ms) relative to the slowing in typing speed in the evening following longer nights of sleep (e.g., 7.6 hours; from 440 ms to 500 ms). Conclusions: In this study, we demonstrated that when middle-aged and older Latinos are more sedentary, they are more vulnerable to processing speed slowing over the course of the day, particularly on days they sleep less. These findings reveal the ways that these digital data assessment methods can be utilized to detect subtle changes of processing speed that are temporarily linked to sedentary behavior and sleep variation. This could potentially enable the short-term assessment of outcomes for interventions to modify these behaviors, in order to improve brain health and possibly reduce the risk of Alzheimer’s disease and related dementias in this population.

Poster

02/15/2024
12:00 pm - 01:15 pm
Room: Majestic Complex (Posters 61-120)

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

Final Abstract #77

Using Digital Passive Metrics to Assess the Impact of Sedentary Activity and Sleep on Processing Speed among Middle-Aged and Older Hispanics/Latinos

Shay Nakahira, John A. Burns School of Medicine, Honolulu, United States
Martha Lopez, University of California San Diego, San Diego, United States
Alexander Demos, University of Illinois Chicago, Chicago, United States
Itzel Cuevas, University of California San Diego, San Diego, United States
Aastha Dubey, University of California San Diego, San Diego, United States
Ricardo Bentancourt, University of California San Diego, San Diego, United States
Emma Churchill, University of California San Diego, San Diego, United States
Lina Scandalis, University of California San Diego, San Diego, United States
Linda Gallo, San Diego State University, San Diego, United States
Erin Sundermann, University of California San Diego, San Diego, United States
Douglas Galasko, University of California San Diego, San Diego, United States
Greg Talavera, San Diego State University, San Diego, United States
María Marquine, Duke University School of Medicine, Durham, United States
Raeanne Moore, University of California San Diego, San Diego, United States

Category: Teleneuropsychology/ Technology

Keyword 1: cognitive processing
Keyword 2: sleep
Keyword 3: technology

Objective:

Hispanics/Latinos/as/x (hereafter Latinos) are the largest ethnic or racial minority group in the United States (U.S.), yet remain widely underrepresented in research studies. Digital biomarkers, derived from various sources such as smartphones and wearables, can provide valuable insights into the relationship between lifestyle factors and cognition. Emerging research suggests that higher levels of sedentary behavior and poor sleep quality may be associated with lower levels of cognitive function, poor health outcomes, and the development of chronic diseases. In this study, we explored the relationship between a digital biomarker of processing speed, derived from smartphone typing speed, with sedentary activity and sleep efficiency among middle-aged and older Latinos.

Participants and Methods:

Participants included 59 Hispanic/Latino adults aged 50-70 years old living in southern California enrolled in the SALUD-Tech study (Age: M= 58.6, SD= 5.1; 70% female; Education: M=11.5, SD=4.0; 86% primarily Spanish-speaking; 80% bilingual). Participants replaced their native smartphone keyboards with the Keywise AI research keyboard (available in English and Spanish). The custom keyboard tracks keystroke metadata as people are typing (e.g., interkey time, backspace ratio). Participants also wore Fitbit smartwatches that recorded sleep and sedentary activity. Digital health data collection occurred for 30 days, with participants contributing 8,278 total typing sessions. A mixed effects model was applied to analyze typing sessions across the day for each participant, with typing speed as a function of the number of sedentary minutes per day, change in sedentary minutes across days, and number of minutes slept per night controlling for age, sex, education level, primary language, and motor precision.

Results:

Results showed an expected diurnal pattern with the keystroke data, demonstrating slower typing in the morning and evening relative to the afternoon. Days where participants had high sedentary activity (relative to themselves) were associated with a more pronounced diurnal pattern (i.e., more evening slowing) relative to days that they were more active. Further, results revealed significant interactions with this pattern and sleep, such that on days participants were more active, the amount of sleep received the prior night had a lesser impact on the degree of typing slowing throughout the day. Specifically, when participants slept less (e.g., 5.8 hours) the night before more sedentary days, slowing in typing speed from day to evening was more pronounced (i.e., from 440 ms to 600 ms) relative to the slowing in typing speed in the evening following longer nights of sleep (e.g., 7.6 hours; from 440 ms to 500 ms).

Conclusions:

In this study, we demonstrated that when middle-aged and older Latinos are more sedentary, they are more vulnerable to processing speed slowing over the course of the day, particularly on days they sleep less. These findings reveal the ways that these digital data assessment methods can be utilized to detect subtle changes of processing speed that are temporarily linked to sedentary behavior and sleep variation. This could potentially enable the short-term assessment of outcomes for interventions to modify these behaviors, in order to improve brain health and possibly reduce the risk of Alzheimer’s disease and related dementias in this population.