INS NYC 2024 Program

Poster	Poster Session 05 Program Schedule 02/15/2024 02:30 pm - 03:45 pm Room: Majestic Complex (Posters 61-120) Poster Session 05: Neuropsychiatry \| Addiction/Dependence \| Stress/Coping \| Emotional/Social Processes Final Abstract #91 A Naturalistic Assessment of Reaction Time and Impulsivity in Individuals with Mood Disorders Mindy Ross, University of Illinois Chicago, Chicago, United States Theresa Nguyen, University of Illinois Chicago, Chicago, United States Emma Ning, University of Illinois Chicago, Chicago, United States Andrea Cladek, University of Illinois Chicago, Chicago, United States Sarah Kabir, University of Illinois Chicago, Chicago, United States Amruta Barve, University of Illinois Chicago, Chicago, United States Ellyn Kennelly, Wayne State University, Detroit, United States Faraz Hussain, University of Illinois Chicago, Chicago, United States Jennifer Duffecy, University of Illinois Chicago, Chicago, United States Scott Langenecker, The Ohio State University, Columbus, United States John Zulueta, University of Illinois Chicago, Chicago, United States Alexander Demos, University of Illinois Chicago, Chicago, United States Michelle Chen, Rutgers, The State University of New Jersey, New Brunswick, United States Olusola Ajilore, University of Illinois Chicago, Chicago, United States Alex Leow, University of Illinois Chicago, Chicago, United States Category: Assessment/Psychometrics/Methods (Adult) Keyword 1: cognitive functioning Keyword 2: mood disorders Keyword 3: technology Objective: Cognitive fluctuations are prevalent among individuals with mood disorders. However, real-world cognitive fluctuations are often difficult to assess in traditional neuropsychological assessments that only take a snapshot of the individual's cognitive functioning. The purpose of this study was to examine the utility of a novel, naturalistic, smartphone-based go/no-go task to detect within-day fluctuations in reaction time and impulsivity associated with mood disorders in the wild. Participants and Methods: Participants with (n = 46; bipolar disorders = 5, depressive disorders = 41) and without (n = 17) mood disorders completed a go/no-go (GNG) task on their personal iPhones as part of a larger study. The GNG task consisted of “go” trials, in which participants were instructed to shake their phones as quickly as possible following a blue stimulus dot, and “no-go” trials, in which participants were to refrain from shaking their phone following a green stimulus dot. The accuracy of the response and reaction time were recorded. Participants also completed the Quick Inventory of Depressive Symptomatology (QIDS) at baseline. Linear mixed effects models were used to examine the effects of hour of the day and depression severity on incorrect responses to no-go trials (commission errors) and reaction time. Results: There was a significant difference in reaction time based on the trial type; incorrect no-go trials had faster reaction times than correct go trials, suggesting that accuracy on the no-go trials may be an index for impulsivity. Hour of the day had a significant quadratic effect on the accuracy of no-go trials and reaction time, such that participants tended to respond faster and less accurately in the afternoon compared to mornings and evenings, particularly on the no-go trials. Moreover, depression severity as determined by the baseline QIDS score had a significant linear effect on reaction time in that those who were more depressed had slower reaction times compared to those who were less depressed. Lastly, a practice effect was observed in no-go trials with improved trial accuracy following more completed GNG tasks; this effect, however, did not impact reaction time. Conclusions: We propose a novel, smartphone-based go/no-go task capable of being completed repeatedly in a naturalistic setting due to its short and gamified nature. This task is sensitive to the influence of time of day and depression severity on reaction time and impulsivity. Since cognitive performance is impacted by mood disorder symptoms, our GNG task could serve to monitor real-time fluctuations in aspects of cognition without increasing the time burden on these individuals.

Poster

02/15/2024
02:30 pm - 03:45 pm
Room: Majestic Complex (Posters 61-120)

Poster Session 05: Neuropsychiatry | Addiction/Dependence | Stress/Coping | Emotional/Social Processes

Final Abstract #91

A Naturalistic Assessment of Reaction Time and Impulsivity in Individuals with Mood Disorders

Mindy Ross, University of Illinois Chicago, Chicago, United States
Theresa Nguyen, University of Illinois Chicago, Chicago, United States
Emma Ning, University of Illinois Chicago, Chicago, United States
Andrea Cladek, University of Illinois Chicago, Chicago, United States
Sarah Kabir, University of Illinois Chicago, Chicago, United States
Amruta Barve, University of Illinois Chicago, Chicago, United States
Ellyn Kennelly, Wayne State University, Detroit, United States
Faraz Hussain, University of Illinois Chicago, Chicago, United States
Jennifer Duffecy, University of Illinois Chicago, Chicago, United States
Scott Langenecker, The Ohio State University, Columbus, United States
John Zulueta, University of Illinois Chicago, Chicago, United States
Alexander Demos, University of Illinois Chicago, Chicago, United States
Michelle Chen, Rutgers, The State University of New Jersey, New Brunswick, United States
Olusola Ajilore, University of Illinois Chicago, Chicago, United States
Alex Leow, University of Illinois Chicago, Chicago, United States

Category: Assessment/Psychometrics/Methods (Adult)

Keyword 1: cognitive functioning
Keyword 2: mood disorders
Keyword 3: technology

Objective:

Cognitive fluctuations are prevalent among individuals with mood disorders. However, real-world cognitive fluctuations are often difficult to assess in traditional neuropsychological assessments that only take a snapshot of the individual's cognitive functioning. The purpose of this study was to examine the utility of a novel, naturalistic, smartphone-based go/no-go task to detect within-day fluctuations in reaction time and impulsivity associated with mood disorders in the wild.

Participants and Methods:

Participants with (n = 46; bipolar disorders = 5, depressive disorders = 41) and without (n = 17) mood disorders completed a go/no-go (GNG) task on their personal iPhones as part of a larger study. The GNG task consisted of “go” trials, in which participants were instructed to shake their phones as quickly as possible following a blue stimulus dot, and “no-go” trials, in which participants were to refrain from shaking their phone following a green stimulus dot. The accuracy of the response and reaction time were recorded. Participants also completed the Quick Inventory of Depressive Symptomatology (QIDS) at baseline. Linear mixed effects models were used to examine the effects of hour of the day and depression severity on incorrect responses to no-go trials (commission errors) and reaction time.

Results:

There was a significant difference in reaction time based on the trial type; incorrect no-go trials had faster reaction times than correct go trials, suggesting that accuracy on the no-go trials may be an index for impulsivity. Hour of the day had a significant quadratic effect on the accuracy of no-go trials and reaction time, such that participants tended to respond faster and less accurately in the afternoon compared to mornings and evenings, particularly on the no-go trials. Moreover, depression severity as determined by the baseline QIDS score had a significant linear effect on reaction time in that those who were more depressed had slower reaction times compared to those who were less depressed. Lastly, a practice effect was observed in no-go trials with improved trial accuracy following more completed GNG tasks; this effect, however, did not impact reaction time.

Conclusions:

We propose a novel, smartphone-based go/no-go task capable of being completed repeatedly in a naturalistic setting due to its short and gamified nature. This task is sensitive to the influence of time of day and depression severity on reaction time and impulsivity. Since cognitive performance is impacted by mood disorder symptoms, our GNG task could serve to monitor real-time fluctuations in aspects of cognition without increasing the time burden on these individuals.