An Exploratory Analysis of Cortical Hyperexcitability, Anxious Tendencies, and Sleep
Dublin Core
Title
An Exploratory Analysis of Cortical Hyperexcitability, Anxious Tendencies, and Sleep
Creator
Logan R Caola
Date
September 8th, 2020
Description
Cortical hyperexcitability reflects abnormal or aberrant neural processes and has been associated with visual distortions, discomfort, and hallucinations. Abnormal visual behaviors have previously been found to exist within non-clinical populations. The present study explored the previously implied relationship between anxiety, sleep patterns, and cortical hyperexcitability. Three inventories were used to gather data; the General Anxiety Disorder inventory (GAD-7; Löwe et al., 2008) measured anxiety, the Pittsburgh Sleep Quality Index (PSQI: Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) measured problematic sleep behaviors, and the Cortical Hyperexcitability index version two (CHi-II; Braithwaite, Marchant, Takahashi, Dewe, & Watson, 2015; Fong, Takahashi, & Braithwaite, 2019) measured cortical hyperexcitability, which is composed of three separate dimensions, or ‘factors’. In order to analyse the three factors, this study utilised three separate multiple regression models (n = 97), and a correlation analysis was used to analyse the relationship between anxiety symptoms and problematic sleep behaviors. Some significant results were found in support of the relationship between anxiety and cortical hyperexcitability. No significant results were found for the relationship between sleep and cortical hyperexcitability. A significant correlation analysis found that there is a significant positive relationship between anxiety and sleep. Collectively, these findings provide additional external validation for the CHi-II as an indirect proxy measure for symptoms of cortical hyperexcitability.
Subject
Cortical hyperexcitability, Anxiety, Problematic Sleep
Source
Participants
Due to the ongoing pandemic, 34 participants were gathered from Lancaster University student-based Facebook groups. This was an attempt to gather students in a similar manner to common recruitment without the use of in-person interaction. In addition to the gathered 34, 63 additional participants were used from previously collected data, gathered in-person also from Lancaster University students. Overall, 97 participants were gathered for this study. The mean age of participants was 21 (age range 18-33 years), of which 65 (67%) were female. Informed consent was obtained from all participants.
Materials
Due to the remote nature of the study, each of the surveys used was a digital variant made on Qualtrics.
The Cortical Hyperexcitability II (CHi-II) is one of the first verified measures of cortical hyperexcitability. The CHi-II consists of 30 items and takes 20 to 25 minutes to complete. Each item focuses on a specific experience followed by two 7-point Likert scales, to measure participant’s frequency and intensity of each experience (Fong et al., 2019). The CHi-II can be broken down into three separate factors. Factor one, “Heightened Visual Sensitivity and Discomfort”, which consists of 11 items. Factor two, “Aura-Like Visual Hallucinatory Experiences”, which consists of nine items. Factor three, “Distorted Visual Perception,” which consists of six items (see Fong et al., 2019). For each of the three factors, intensity and frequency scores were added for a global score of each factor, for each participant. These global factor scores were then divided by the number of items in each factor, respectively, to provide an average for each participant for each factor. There are four items that are not part of any factor. Although these items were recorded in data collection, they are not used in this analysis.
The General Anxiety Disorder assessment (GAD-7) measures anxious tendencies and has been established as conceptually valid and reliable in measuring anxiety in non-clinical populations (Löwe et al., 2008). The GAD7 consists of seven items with a 4-point Likert scale of frequency for responses. All items will be scored (never – 0, almost always – 3) and be added together to form a global anxiety score. A higher score indicates a greater level of anxiety. Total scoring will have a range of 0-21, with set cut offs for mild (5-10), moderate (10-15), and severe anxiety (15+). This inventory should only take about 5 to 10 minutes to complete.
The Pittsburgh Sleep Quality Index (PSQI) is a measure of sleep quality and sleep disturbances over the past month, and has demonstrated good psychometric properties with various populations, including non-clinical subjects (Buysse et al., 1989; Grandner et al., 2006; Mollayeva et al., 2015). The PSQI has been found to have high internal validity, high test-retest consistency, and is one of the most direct methods of measuring sleep quality (Mollayeva et al., 2015). The PSQI consists of 19 items measuring: subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. All 19 items are scored and added to form a conclusory global score (range 0 to 21), a higher score indicating an increased presence of sleep disturbances (Buysse et al., 1989). This inventory should only take about 10 to 15 minutes.
Overall, these three surveys should take 35 to 50 minutes to complete. Once each score is coded from the digital surveys, researchers used R Studio to find various predicted relationships or significance between scores. Each participant was given an anonymous participant ID, and a randomised order to complete the three surveys, in order to avoid order effects.
Procedure
Participants were contacted through email, where they were given participant IDs, in order to anonymise their results, and the order in which they were to complete the three surveys. One link was sent to each participant which contained separate links for each survey. The main link also contained a participant information form, which informed participants about what the study consisted of and what was expected of them, and a consent form. Participants were advised to complete the surveys in an isolated area, free from distractions, and all in one sitting. After the three main surveys were completed the participants received a debrief form.
Analysis
To uncover significant positive relationships between the two variables, sleep and anxiety, and cortical excitability, three separate multiple regression models were conducted. Three regression models were conducted separately by the “visreg,” “tidyverse,” “pwr,” and “gvlma” packages installed under the R statistical program (version 3.6.1, R Development Core Team, 2019; see Champely, 2020; Breheny & Burchett, 2017; Pena & Slate, 2019; Wickham et al., 2019). For the multiple regressions, the independent variables, or ‘predictor variables’, used for each were the universal sleep (PSQI) and anxiety (GAD-7) scores. For the dependent variables, each of the three factors of the CHi-II were used, respectively.
In addition, a correlation analysis was used to determine if there was a significant relationship between the GAD-7 and PSQI scores in order to validate the use of this particular sample. Particularly, this relationship should be significant as found by previous studies, a non-significant result would show that this particular sample is problematic.
Finally, to ensure no major deviations occurred between the two separately-collected groups of participants, descriptive statistics of both groups were gathered and a T-test analysis of all variables were conducted.
Due to the ongoing pandemic, 34 participants were gathered from Lancaster University student-based Facebook groups. This was an attempt to gather students in a similar manner to common recruitment without the use of in-person interaction. In addition to the gathered 34, 63 additional participants were used from previously collected data, gathered in-person also from Lancaster University students. Overall, 97 participants were gathered for this study. The mean age of participants was 21 (age range 18-33 years), of which 65 (67%) were female. Informed consent was obtained from all participants.
Materials
Due to the remote nature of the study, each of the surveys used was a digital variant made on Qualtrics.
The Cortical Hyperexcitability II (CHi-II) is one of the first verified measures of cortical hyperexcitability. The CHi-II consists of 30 items and takes 20 to 25 minutes to complete. Each item focuses on a specific experience followed by two 7-point Likert scales, to measure participant’s frequency and intensity of each experience (Fong et al., 2019). The CHi-II can be broken down into three separate factors. Factor one, “Heightened Visual Sensitivity and Discomfort”, which consists of 11 items. Factor two, “Aura-Like Visual Hallucinatory Experiences”, which consists of nine items. Factor three, “Distorted Visual Perception,” which consists of six items (see Fong et al., 2019). For each of the three factors, intensity and frequency scores were added for a global score of each factor, for each participant. These global factor scores were then divided by the number of items in each factor, respectively, to provide an average for each participant for each factor. There are four items that are not part of any factor. Although these items were recorded in data collection, they are not used in this analysis.
The General Anxiety Disorder assessment (GAD-7) measures anxious tendencies and has been established as conceptually valid and reliable in measuring anxiety in non-clinical populations (Löwe et al., 2008). The GAD7 consists of seven items with a 4-point Likert scale of frequency for responses. All items will be scored (never – 0, almost always – 3) and be added together to form a global anxiety score. A higher score indicates a greater level of anxiety. Total scoring will have a range of 0-21, with set cut offs for mild (5-10), moderate (10-15), and severe anxiety (15+). This inventory should only take about 5 to 10 minutes to complete.
The Pittsburgh Sleep Quality Index (PSQI) is a measure of sleep quality and sleep disturbances over the past month, and has demonstrated good psychometric properties with various populations, including non-clinical subjects (Buysse et al., 1989; Grandner et al., 2006; Mollayeva et al., 2015). The PSQI has been found to have high internal validity, high test-retest consistency, and is one of the most direct methods of measuring sleep quality (Mollayeva et al., 2015). The PSQI consists of 19 items measuring: subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. All 19 items are scored and added to form a conclusory global score (range 0 to 21), a higher score indicating an increased presence of sleep disturbances (Buysse et al., 1989). This inventory should only take about 10 to 15 minutes.
Overall, these three surveys should take 35 to 50 minutes to complete. Once each score is coded from the digital surveys, researchers used R Studio to find various predicted relationships or significance between scores. Each participant was given an anonymous participant ID, and a randomised order to complete the three surveys, in order to avoid order effects.
Procedure
Participants were contacted through email, where they were given participant IDs, in order to anonymise their results, and the order in which they were to complete the three surveys. One link was sent to each participant which contained separate links for each survey. The main link also contained a participant information form, which informed participants about what the study consisted of and what was expected of them, and a consent form. Participants were advised to complete the surveys in an isolated area, free from distractions, and all in one sitting. After the three main surveys were completed the participants received a debrief form.
Analysis
To uncover significant positive relationships between the two variables, sleep and anxiety, and cortical excitability, three separate multiple regression models were conducted. Three regression models were conducted separately by the “visreg,” “tidyverse,” “pwr,” and “gvlma” packages installed under the R statistical program (version 3.6.1, R Development Core Team, 2019; see Champely, 2020; Breheny & Burchett, 2017; Pena & Slate, 2019; Wickham et al., 2019). For the multiple regressions, the independent variables, or ‘predictor variables’, used for each were the universal sleep (PSQI) and anxiety (GAD-7) scores. For the dependent variables, each of the three factors of the CHi-II were used, respectively.
In addition, a correlation analysis was used to determine if there was a significant relationship between the GAD-7 and PSQI scores in order to validate the use of this particular sample. Particularly, this relationship should be significant as found by previous studies, a non-significant result would show that this particular sample is problematic.
Finally, to ensure no major deviations occurred between the two separately-collected groups of participants, descriptive statistics of both groups were gathered and a T-test analysis of all variables were conducted.
Format
Excel Workbook “.xlsx” file
Rights
N/A
Language
English
Type
Data
LUSTRE
Supervisor
Jason Braithwaite
Project Level
MSC
Topic
Neuropsychology
Sample Size
97
Statistical Analysis Type
Regression, T-Test
Files
Citation
Logan R Caola, “An Exploratory Analysis of Cortical Hyperexcitability, Anxious Tendencies, and Sleep,” LUSTRE, accessed April 29, 2024, https://www.johnntowse.com/LUSTRE/items/show/99.