Depression, Insomnia
Conditions
Keywords
Insomnia, Depression, Anxiety, CBT-I, Cognitive Behavioral Therapy for Insomnia
Brief summary
Several lines of evidence suggest that unhealthy sleep patterns contribute to depressive symptoms through disruption of brain networks that regulate emotional functions. However, we do not yet know to what degree the emotion regulation brain network is modified by the restoration of sleep, or whether the degree to which a sleep intervention modifies these neural targets mediates reductions in other depressive symptoms including suicidality. The overall aim is to test the efficacy of an established sleep intervention (Cognitive Behavioral Therapy for Insomnia (CBT-I)) in reducing depressive symptoms through improving emotion regulation brain function in individuals with elevated depressive symptoms and clinically meaningful sleep disturbance. In this study, we will assess feasibility of recruitment and retention as well as target engagement. Target engagement is defined as the treatment effect on increasing mPFC-amygdala connectivity, and/or decreasing amygdala reactivity during emotion reactivity and regulation paradigms. Participants will be 70 adults experiencing at least moderate sleep disturbances and who also have elevated anxious and/or depressive symptoms. Emotion distress and sleep disruption will be assessed prior to, and weekly while receiving six Cognitive Behavioral Therapy for Insomnia (CBT-I) across a period of 8 weeks. CBT-I improves sleep patterns through a combination of sleep restriction, stimulus control, mindfulness training, cognitive therapy targeting dysfunctional beliefs about sleep, and sleep hygiene education. Using fMRI scanning, emotion regulation network neural targets will be assayed prior to and following completion of CBT-I treatment.
Interventions
BEHAVIORALCognitive Behavioral Therapy for Insomnia
Participants will meet with a psychologist once a week for six weeks to complete a brief CBT-I intervention. Cognitive Behavioral Therapy for Insomnia consists of a cognitive therapy and a behavioral therapy. The cognitive therapy is designed to identify incorrect ideas about sleep, challenge their validity, and replace them with correct information. This therapy tries to reduce worry, anxiety, and fear that one won't sleep by providing accurate information about sleep. The behavioral therapy increases sleep quality by limiting excessive time spent in bed to increase homeostatic sleep drive and sleep consolidation.
Sponsors
National Institute of Mental Health (NIMH)
Stanford University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Intervention model description
This is a single-armed trial. All participants will receive Cognitive Behavioral Therapy for Insomnia
Eligibility
Sex/Gender
ALL
Age
25 Years to 60 Years
Healthy volunteers
No
Inclusion criteria
* Ages 25-60 * Subjective complaint of sleep disturbance for ≥ 3 months (ISI≥10) * Subjective complaint of depression (BDI≥14) and not at imminent risk for suicide, as measured by CSSRS assessment * Fluent and literate in English * Written informed consent. * Reside within 60 miles of Stanford University
Exclusion criteria
* Presence of other sleep or circadian rhythm disorders * Medications that would significantly impact sleep, alertness, or mood * \>14 alcoholic drinks per week or \>4 drinks per occasion * General medical condition, disease or neurological disorder that interferes with the assessments or outpatient participation * Substance abuse or dependence * Mild traumatic brain injury * Severe impediment to vision, hearing and/or hand movement, likely to interfere with the ability to follow study protocols * Pregnant or breast feeding * Current or lifetime history of bipolar disorder or psychosis * Current or or expected cognitive behavior therapy or other evidence-based psychotherapies for another condition * Received CBT-I within the past year * Acute or unstable chronic illness * Current exposure to trauma, or exposure to trauma within the past 3 months * Working a rotating shift that overlaps with 2400h. * Presence of suicidal ideations representing imminent risk as determined by the empirically-supported, standardized suicide risk assessment to the
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Assessed at week 0 and week 11 | The Conscious condition of the Facial Expressions of Emotion task measures supraliminal (without backward masking) emotional face processing. Amygdala activation while viewing threat-related emotional faces relative to neutral faces was quantified using functional magnetic resonance imaging (fMRI) as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional faces using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to emotional faces, relative to neutral faces. A negative value for the change in amygdala activation means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes. |
| Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Assessed at week 0 and week 11 | The Nonconscious condition of the Facial Expressions of Emotion task measures subliminal (with backward masking) emotional face processing. Amygdala activation while viewing threat-related emotional faces relative to neutral faces was quantified using fMRI as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional faces using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to emotional faces, relative to neutral faces. A negative value for the change in amygdala activation means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes. |
| Change in Amygdala Activation During the Emotion Regulation Scenes Task | Assessed at week 0 and week 11 | Participants are asked to look or decrease their emotional response to negative and neutral valence images taken from the International Affective Picture System. Amygdala activation while viewing emotional scenes relative to neutral scenes, and while passively viewing emotional scenes relative to down-regulating emotion, was quantified using fMRI as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional scenes or while downregulating using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to the task demands, and a negative value means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes |
| Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Assessed at week 0 and week 11 | This outcome tested whether amygdala connectivity with regions of the mPFC was changed following treatment using psychophysiological interaction (PPI) analysis for this contrast/task. Regions of the mPFC include: dorsal anterior cingulate cortex (dACC), ventromedial prefrontal cortex (vmPFC), dorsomedial prefrontal cortex (dmPFC), subgenual anterior cingulate cortex (sgACC), pregenual anterior cingulate cortex (pACC). PPI analyses produce a beta weight for each participant at each timepoint, and represents the degree to which the connectivity of the amygdala and mPFC is modulated by task conditions. A positive value means average connectivity increases in the task-contrast, and a positive value for the change score means an increase in average connectivity following CBT-I treatment. It is theorized that higher amygdala connectivity is associated with better outcomes. |
| Change in Beck Depression Inventory (BDI) | Assessed at week 0 and week 11 | This measure is of the Beck Depression Inventory-II total score after excluding one sleep item. The BDI-II is a 21-item self-report scale with high validity and reliability that assesses the severity of depression symptoms. The depression items consist of: sadness, pessimism, past failure, loss of pleasure, guilty feelings, punishment feelings, self-dislike, self-criticalness, suicidal thoughts or wishes, crying, agitation, loss of interest, indecisiveness, worthlessness, loss of energy, irritability, changes in appetite, concentration difficulty, tiredness or fatigue, and loss of interest in sex. Items are scored from 0 to 3, and summed to create an overall score of 0 to 63. higher scores indicate greater levels of severity. The ranges for depression are: 0-13 minimal, 14-19 mild, 20-28 moderate, and 29-63 severe. A negative change score means that average depression symptom severity was reduced following CBT-I treatment. |
| Change in PSG Sleep Efficiency | Assessed at week 0 and week 11 | Sleep efficiency (SE) is the percentage of total time in bed actually spent sleeping. Based on the overnight PSG sleep recording, SE will be calculated as the total time (minutes) spent asleep (sum of Stages N1, N2, N3, and REM) divided by the total time (minutes) in bed, and multiplied by 100. A positive change score means average sleep efficiency increased following CBT-I treatment. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in Actigraph Sleep Efficiency (SE) as a Measure of Sleep Continuity | Assessed at week 0 and week 11 | Sleep Efficiency (SE) is calculated as TST divided by total time spent in bed, multiplied by 100. |
| Change in PSG Sleep Onset Latency (SOL) as a Measure of Sleep Architecture | Assessed at week 0 and week 11 | Sleep onset latency is the time it takes to fall asleep, specifically the amount of time in minutes from LightsOff, which is the time at which the participant started trying to sleep, to stage 1 sleep. A negative change score means it took less time to fall asleep following CBT-I treatment. |
| Change in PSG Number of Arousals as a Measure of Sleep Architecture | Assessed at week 0 and week 11 | Number of Arousals is determined by number of times of awakening by EEG changes. A negative change score means on average there were fewer overnight arousals following CBT-I treatment. |
| Change in PSG Wake After Sleep Onset (WASO) as a Measure of Sleep Architecture | Assessed at week 0 and week 11 | Wake After Sleep Onset (WASO) are periods of wakefulness occurring after sleep onset, before final awakening (sleep offset) measured by EEG changes. A negative change value means there was less WASO on average after CBT-I treatment. |
| Change in PSG Total Sleep Time (TST) as a Measure of Sleep Architecture | Assessed at week 0 and week 11 | Total Sleep Time (TST) is the total time (minutes) spent asleep, from the start of sleep onset to sleep offset, subtracting any periods of wakefulness. TST includes stages N1, N2, N3, and REM sleep. A positive change score means the average TST increased following CBT-I. |
| Change in Beck Scale of Suicidal Ideation Total Score | Assessed at week 0 and week 11 | The Beck Scale of Suicidal Ideation (BSSI) is designed to assess the severity of suicidal ideation over the past week. The total score is derived from the sum of the first 19 items, creating an overall score ranging from 0 to 38. Scores of 0 are interpreted as no suicidal ideation, 1-8 as low levels, 9-16 as moderate levels, and 17-38 as high levels. A negative change score means an average reduction in suicidal ideation following CBT-I treatment. |
| Change in Insomnia Severity Index (ISI) Scale Score | Assessed at week 0 and week 11 | Subjective ratings of sleep disturbance and insomnia severity will be assessed with the Insomnia Severity Index. The Insomnia Severity Index (ISI) is a 7-item self-report measure of insomnia type, severity, and impact on functioning. The items consist of severity of sleep onset, sleep maintenance, early morning awakenings, sleep dissatisfaction, interference with daytime functioning, noticeability of sleep problems by others, and distress caused by sleep difficulties. Items are scored from 0 to 4 (0 = no problem, 4 = very severe problem), then summed to create an overall score of 0 to 28. Score ranges of insomnia are: 0-7 absent, 8-14 sub-threshold, 15-21 moderate, and 22-28 severe. The ISI has good validity and reliability. A negative change score means average insomnia symptoms improved following CBT-I treatment. |
| Change in 36-Item Short Form Survey (SF-36) Score | Assessed at week 0 and week 11 | The SF-36 measures health-related quality of life based on eight domains: physical activity, social activities, limitations in activities due to physical health problems, bodily pain, general mental health, limitations in activities due to emotional problems, vitality, and general health perceptions. Items are recoded then averaged together to create each an average score for all items that the respondent answered. The eight subscales are then into two component summary t-scores (Mental and Physical Component Summary t-scores), each with a mean of 50 and a standard deviation of 10. A t-score higher than 50 means better mental or physical health than the general population, and a t-score below 50 means worse than the general population. Instructions for scoring these component scores recommends that they be set to missing if any subscales are missing. A positive change score means the Component Summary Score improved following CBT-I. |
| Change in Beck Anxiety Inventory (BAI) | Assessed at week 0 and week 11 | The BAI is a 21-item self-report scale that assesses the severity of anxiety symptoms. Items are scored from 0 to 3 (0 = not at all, 3 = severe), then summed to create an overall score range of 0 to 63. Higher scores indicate greater levels of severity, and the ranges for anxiety levels are: 0-9 normal to minimal, 10-18 mild to moderate, 19-29 moderate to severe, and 30-63 severe. The BAI consists of two factors: somatic and cognitive. A negative change score means that average anxiety symptom severity was reduced following CBT-I treatment. |
| Change in Respiratory Sinus Arrhythmia (RSA)- Measured by PSG | Assessed at week 0 and week 11 | RSA is the phenomenon of an increased heart rate during inhalation and a decreased heart rate during exhalation. Since these fluctuations are controlled mainly by vagal influences on the heart, RSA serves as a reliable metric for measuring parasympathetic activity. RSA has been proven to be a reliable measure of emotion regulation and emotional responding in numerous studies. |
| Change in Sleep Physiology Measured by PSG | Assessed at week 0 and week 11 | Fronto-central EEG power spectral density analysis associated with sleep stages will be calculated in the Delta (0.5-Hz), Theta (4-7Hz), Alpha (7-11Hz), Sigma (12-15Hz), Beta-1 (15-20Hz), Beta-2 (20-35Hz) and Gamma (35-45Hz) bands, according to published methods. A positive change score means there was an increase in absolute power in the specified frequency band following CBT-I treatment. |
| Change in Columbia Suicide Severity Rating Scale | Assessed at week 0 and week 11 | The Columbia Suicide Severity Rating Scale (CSSRS) is a 12-item checklist that was designed to quantify the severity of suicidal ideation and behavior. It is composed of two parts. The first six questions ask about suicidal ideation and behavior in the past month while the last six questions ask about suicidal ideation and behavior since the last visit. The CSSRS has been proven to be reliable and valid. It has also been shown to have high sensitivity and specificity to the different suicidal behavior classifications. The CSSRS does not provide a numerical score but categorizes risk levels based on responses. We report the proportions of risk at each timepoint. |
| Change in Actigraph Sleep Onset Latency (SOL) as a Measure of Sleep Continuity | Assessed at week 0 and week 11 | Sleep Onset Latency (SOL) is the time (minutes) from lights out to actually falling asleep (sleep onset). |
| Change in Actigraph Number of Arousals as a Measure of Sleep Continuity | Assessed at week 0 and week 11 | Number of Arousals is determined by number of times of awakening as seen on the actigraph data. |
| Change in Actigraph Wake After Sleep Onset (WASO) as a Measure of Sleep Continuity | Assessed at week 0 and week 11 | Wake After Sleep Onset (WASO) are periods of wakefulness occurring after sleep onset, before final awakening (sleep offset). |
| Change in Actigraph Total Sleep Time (TST) as a Measure of Sleep Continuity | Assessed at week 0 and week 11 | Total Sleep Time (TST) is the total time spent asleep, from the start of sleep onset to sleep offset subtracting any periods of wakefulness. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| CBT-I Cognitive Behavioral Therapy for Insomnia: Participants will meet with a psychologist once a week for six weeks to complete a brief CBT-I intervention. Cognitive Behavioral Therapy for Insomnia consists of a cognitive therapy and a behavioral therapy. The cognitive therapy is designed to identify incorrect ideas about sleep, challenge their validity, and replace them with correct information. This therapy tries to reduce worry, anxiety, and fear that one won't sleep by providing accurate information about sleep. The behavioral therapy increases sleep quality by limiting excessive time spent in bed to increase homeostatic sleep drive and sleep consolidation. | 51 |
| Total | 51 |
Withdrawals & dropouts
| Period | Reason | FG000 |
|---|---|---|
| Overall Study | Lost to Follow-up | 1 |
| Overall Study | Withdrawal by Subject | 2 |
Baseline characteristics
| Characteristic | CBT-I |
|---|---|
| Age, Categorical <=18 years | 0 Participants |
| Age, Categorical >=65 years | 0 Participants |
| Age, Categorical Between 18 and 65 years | 51 Participants |
| Age, Continuous | 40.2 Years STANDARD_DEVIATION 10.9 |
| Ethnicity (NIH/OMB) Hispanic or Latino | 4 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 47 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants |
| Race (NIH/OMB) Asian | 18 Participants |
| Race (NIH/OMB) Black or African American | 1 Participants |
| Race (NIH/OMB) More than one race | 2 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 2 Participants |
| Race (NIH/OMB) White | 28 Participants |
| Region of Enrollment United States | 51 participants |
| Sex: Female, Male Female | 33 Participants |
| Sex: Female, Male Male | 18 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 51 |
| other Total, other adverse events | 14 / 51 |
| serious Total, serious adverse events | 0 / 51 |
Outcome results
Primary
Change in Amygdala Activation During the Emotion Regulation Scenes Task
Participants are asked to look or decrease their emotional response to negative and neutral valence images taken from the International Affective Picture System. Amygdala activation while viewing emotional scenes relative to neutral scenes, and while passively viewing emotional scenes relative to down-regulating emotion, was quantified using fMRI as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional scenes or while downregulating using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to the task demands, and a negative value means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable image data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Emotion Regulation Scenes Task | Negative > Neutral | 0.35 Beta weights (arbitrary units) | Standard Deviation 0.56 |
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Emotion Regulation Scenes Task | Look Negative > Decrease Negative | -0.05 Beta weights (arbitrary units) | Standard Deviation 0.28 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Emotion Regulation Scenes Task | Negative > Neutral | 0.05 Beta weights (arbitrary units) | Standard Deviation 0.71 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Emotion Regulation Scenes Task | Look Negative > Decrease Negative | 0.03 Beta weights (arbitrary units) | Standard Deviation 0.39 |
Comparison: Analysis of Emotion Regulation Scenes task Negative \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.65Mixed Models Analysis
Comparison: Analysis of Emotion Regulation Scenes task Look Negative \> Decrease Negative amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.65Mixed Models Analysis
Primary
Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging
The Conscious condition of the Facial Expressions of Emotion task measures supraliminal (without backward masking) emotional face processing. Amygdala activation while viewing threat-related emotional faces relative to neutral faces was quantified using functional magnetic resonance imaging (fMRI) as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional faces using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to emotional faces, relative to neutral faces. A negative value for the change in amygdala activation means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed the pre-treatment baseline, and who had interpretable image data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Fear > Neutral | 0.11 Beta weights (arbitrary units) | Standard Deviation 0.32 |
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Threat > Neutral | 0.22 Beta weights (arbitrary units) | Standard Deviation 0.6 |
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Anger > Neutral | 0.11 Beta weights (arbitrary units) | Standard Deviation 0.36 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Fear > Neutral | -0.18 Beta weights (arbitrary units) | Standard Deviation 0.34 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Threat > Neutral | -0.25 Beta weights (arbitrary units) | Standard Deviation 0.63 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Anger > Neutral | -0.07 Beta weights (arbitrary units) | Standard Deviation 0.4 |
Comparison: Analysis of Conscious Fear \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.008Mixed Models Analysis
Comparison: Analysis of Conscious Threat \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.08Mixed Models Analysis
Comparison: Analysis of Conscious Anger \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.49Mixed Models Analysis
Primary
Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging
The Nonconscious condition of the Facial Expressions of Emotion task measures subliminal (with backward masking) emotional face processing. Amygdala activation while viewing threat-related emotional faces relative to neutral faces was quantified using fMRI as a marker of Emotion Regulation Network engagement. Blood-oxygenation level dependent (BOLD) signal change before and after CBT-I treatment was compared by modeling the activity of the amygdala while viewing emotional faces using generalized linear models, producing beta weights for each participant and timepoint. A positive beta-weight at pre-treatment means that the amygdala increased its activity in response to emotional faces, relative to neutral faces. A negative value for the change in amygdala activation means that average amygdala reactivity decreased following treatment. It is theorized that higher amygdala emotional reactivity is associated with worse outcomes.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable image data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Fear > Neutral | -0.01 Beta weights (arbitrary units) | Standard Deviation 0.24 |
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Threat > Neutral | 0.009 Beta weights (arbitrary units) | Standard Deviation 0.41 |
| Pre-treatment Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Anger > Neutral | 0.02 Beta weights (arbitrary units) | Standard Deviation 0.22 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Fear > Neutral | -0.01 Beta weights (arbitrary units) | Standard Deviation 0.35 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Threat > Neutral | -0.01 Beta weights (arbitrary units) | Standard Deviation 0.58 |
| Change in Amygdala Activation | Change in Amygdala Activation During the Facial Expressions of Emotion Task (Nonconscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Anger > Neutral | 0.001 Beta weights (arbitrary units) | Standard Deviation 0.3 |
Comparison: Analysis of Nonconscious Fear \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.99Mixed Models Analysis
Comparison: Analysis of Nonconscious Threat \> Neutral amygdala reactivity was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.99Mixed Models Analysis
Primary
Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging
This outcome tested whether amygdala connectivity with regions of the mPFC was changed following treatment using psychophysiological interaction (PPI) analysis for this contrast/task. Regions of the mPFC include: dorsal anterior cingulate cortex (dACC), ventromedial prefrontal cortex (vmPFC), dorsomedial prefrontal cortex (dmPFC), subgenual anterior cingulate cortex (sgACC), pregenual anterior cingulate cortex (pACC). PPI analyses produce a beta weight for each participant at each timepoint, and represents the degree to which the connectivity of the amygdala and mPFC is modulated by task conditions. A positive value means average connectivity increases in the task-contrast, and a positive value for the change score means an increase in average connectivity following CBT-I treatment. It is theorized that higher amygdala connectivity is associated with better outcomes.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable image data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-dmPFC Connectivity | -0.04 Beta weights (arbitrary units) | Standard Deviation 0.46 |
| Pre-treatment Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-sgACC Connectivity | -0.09 Beta weights (arbitrary units) | Standard Deviation 0.39 |
| Pre-treatment Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-pACC Connectivity | 0.007 Beta weights (arbitrary units) | Standard Deviation 0.55 |
| Pre-treatment Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-vmPFC Connectivity | -0.08 Beta weights (arbitrary units) | Standard Deviation 0.51 |
| Pre-treatment Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-dACC Connectivity | 0.004 Beta weights (arbitrary units) | Standard Deviation 0.49 |
| Change in Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-vmPFC Connectivity | -0.10 Beta weights (arbitrary units) | Standard Deviation 0.55 |
| Change in Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-dACC Connectivity | 0.02 Beta weights (arbitrary units) | Standard Deviation 0.63 |
| Change in Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-dmPFC Connectivity | -0.02 Beta weights (arbitrary units) | Standard Deviation 0.66 |
| Change in Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-pACC Connectivity | -0.10 Beta weights (arbitrary units) | Standard Deviation 0.6 |
| Change in Amygdala Activation | Change in Amygdala-Medial Prefrontal Cortex Connectivity During the Facial Expressions of Emotion Task (Conscious Condition) as Assessed by Functional Magnetic Resonance Imaging | Amygdala-sgACC Connectivity | 0.14 Beta weights (arbitrary units) | Standard Deviation 0.49 |
Comparison: Analysis of amygdala-dACC connectivity from the Conscious Fear \> Neutral task/contrast was done by applying linear mixed effects models testing the effect of treatment-time on connectivity. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.86Mixed Models Analysis
Comparison: Analysis of amygdala-dmPFC connectivity from the Conscious Fear \> Neutral task/contrast was done by applying linear mixed effects models testing the effect of treatment-time on connectivity. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.86Mixed Models Analysis
Comparison: Analysis of amygdala-pACC connectivity from the Conscious Fear \> Neutral task/contrast was done by applying linear mixed effects models testing the effect of treatment-time on connectivity. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.83Mixed Models Analysis
Comparison: Analysis of amygdala-sgACC connectivity from the Conscious Fear \> Neutral task/contrast was done by applying linear mixed effects models testing the effect of treatment-time on connectivity. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.23Mixed Models Analysis
Comparison: Analysis of amygdala-vmPFC connectivity from the Conscious Fear \> Neutral task/contrast was done by applying linear mixed effects models testing the effect of treatment-time on connectivity. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.83Mixed Models Analysis
Primary
Change in Beck Depression Inventory (BDI)
This measure is of the Beck Depression Inventory-II total score after excluding one sleep item. The BDI-II is a 21-item self-report scale with high validity and reliability that assesses the severity of depression symptoms. The depression items consist of: sadness, pessimism, past failure, loss of pleasure, guilty feelings, punishment feelings, self-dislike, self-criticalness, suicidal thoughts or wishes, crying, agitation, loss of interest, indecisiveness, worthlessness, loss of energy, irritability, changes in appetite, concentration difficulty, tiredness or fatigue, and loss of interest in sex. Items are scored from 0 to 3, and summed to create an overall score of 0 to 63. higher scores indicate greater levels of severity. The ranges for depression are: 0-13 minimal, 14-19 mild, 20-28 moderate, and 29-63 severe. A negative change score means that average depression symptom severity was reduced following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: All participants who competed pre-treatment baseline and with interpretable data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Beck Depression Inventory (BDI) | 17.5 units on a scale | Standard Deviation 6.2 |
| Change in Amygdala Activation | Change in Beck Depression Inventory (BDI) | -6.61 units on a scale | Standard Deviation 7.6 |
Comparison: Analysis of change in depression symptom severity score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: <0.0001Mixed Models Analysis
Primary
Change in PSG Sleep Efficiency
Sleep efficiency (SE) is the percentage of total time in bed actually spent sleeping. Based on the overnight PSG sleep recording, SE will be calculated as the total time (minutes) spent asleep (sum of Stages N1, N2, N3, and REM) divided by the total time (minutes) in bed, and multiplied by 100. A positive change score means average sleep efficiency increased following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable image data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in PSG Sleep Efficiency | 78.9 Sleep Efficiency (%) | Standard Deviation 15.1 |
| Change in Amygdala Activation | Change in PSG Sleep Efficiency | 8.57 Sleep Efficiency (%) | Standard Deviation 15.56 |
Comparison: Analysis of change in sleep efficiency was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.002Mixed Models Analysis
Secondary
Change in 36-Item Short Form Survey (SF-36) Score
The SF-36 measures health-related quality of life based on eight domains: physical activity, social activities, limitations in activities due to physical health problems, bodily pain, general mental health, limitations in activities due to emotional problems, vitality, and general health perceptions. Items are recoded then averaged together to create each an average score for all items that the respondent answered. The eight subscales are then into two component summary t-scores (Mental and Physical Component Summary t-scores), each with a mean of 50 and a standard deviation of 10. A t-score higher than 50 means better mental or physical health than the general population, and a t-score below 50 means worse than the general population. Instructions for scoring these component scores recommends that they be set to missing if any subscales are missing. A positive change score means the Component Summary Score improved following CBT-I.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed the pre-treatment baseline, and who had interpretable SF-36 data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in 36-Item Short Form Survey (SF-36) Score | Mental Component T-Score | 31.72 t-score | Standard Deviation 9.27 |
| Pre-treatment Amygdala Activation | Change in 36-Item Short Form Survey (SF-36) Score | Physical Component T-Score | 54.38 t-score | Standard Deviation 6.75 |
| Change in Amygdala Activation | Change in 36-Item Short Form Survey (SF-36) Score | Mental Component T-Score | 7.64 t-score | Standard Deviation 14.59 |
| Change in Amygdala Activation | Change in 36-Item Short Form Survey (SF-36) Score | Physical Component T-Score | 0.25 t-score | Standard Deviation 9.2 |
Comparison: Analysis of change in SF-36 Mental Component Score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: <0.0001Mixed Models Analysis
Comparison: Analysis of change in SF-36 Physical Component Score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.94Mixed Models Analysis
Secondary
Change in Actigraph Number of Arousals as a Measure of Sleep Continuity
Number of Arousals is determined by number of times of awakening as seen on the actigraph data.
Time frame: Assessed at week 0 and week 11
Secondary
Change in Actigraph Sleep Efficiency (SE) as a Measure of Sleep Continuity
Sleep Efficiency (SE) is calculated as TST divided by total time spent in bed, multiplied by 100.
Time frame: Assessed at week 0 and week 11
Secondary
Change in Actigraph Sleep Onset Latency (SOL) as a Measure of Sleep Continuity
Sleep Onset Latency (SOL) is the time (minutes) from lights out to actually falling asleep (sleep onset).
Time frame: Assessed at week 0 and week 11
Secondary
Change in Actigraph Total Sleep Time (TST) as a Measure of Sleep Continuity
Total Sleep Time (TST) is the total time spent asleep, from the start of sleep onset to sleep offset subtracting any periods of wakefulness.
Time frame: Assessed at week 0 and week 11
Secondary
Change in Actigraph Wake After Sleep Onset (WASO) as a Measure of Sleep Continuity
Wake After Sleep Onset (WASO) are periods of wakefulness occurring after sleep onset, before final awakening (sleep offset).
Time frame: Assessed at week 0 and week 11
Secondary
Change in Beck Anxiety Inventory (BAI)
The BAI is a 21-item self-report scale that assesses the severity of anxiety symptoms. Items are scored from 0 to 3 (0 = not at all, 3 = severe), then summed to create an overall score range of 0 to 63. Higher scores indicate greater levels of severity, and the ranges for anxiety levels are: 0-9 normal to minimal, 10-18 mild to moderate, 19-29 moderate to severe, and 30-63 severe. The BAI consists of two factors: somatic and cognitive. A negative change score means that average anxiety symptom severity was reduced following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: All participants who competed pre-treatment baseline and with data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Beck Anxiety Inventory (BAI) | 9.87 units on a scale | Standard Deviation 5.88 |
| Change in Amygdala Activation | Change in Beck Anxiety Inventory (BAI) | -3.78 units on a scale | Standard Deviation 7.97 |
Comparison: Analysis of change in anxiety symptom severity score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: <0.0001Mixed Models Analysis
Secondary
Change in Beck Scale of Suicidal Ideation Total Score
The Beck Scale of Suicidal Ideation (BSSI) is designed to assess the severity of suicidal ideation over the past week. The total score is derived from the sum of the first 19 items, creating an overall score ranging from 0 to 38. Scores of 0 are interpreted as no suicidal ideation, 1-8 as low levels, 9-16 as moderate levels, and 17-38 as high levels. A negative change score means an average reduction in suicidal ideation following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Beck Scale of Suicidal Ideation Total Score | 1.74 score on a scale | Standard Deviation 3.88 |
| Change in Amygdala Activation | Change in Beck Scale of Suicidal Ideation Total Score | -1.11 score on a scale | Standard Deviation 4.8 |
Comparison: Analysis of change in suicidal ideation score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: <0.0001Mixed Models Analysis
Secondary
Change in Columbia Suicide Severity Rating Scale
The Columbia Suicide Severity Rating Scale (CSSRS) is a 12-item checklist that was designed to quantify the severity of suicidal ideation and behavior. It is composed of two parts. The first six questions ask about suicidal ideation and behavior in the past month while the last six questions ask about suicidal ideation and behavior since the last visit. The CSSRS has been proven to be reliable and valid. It has also been shown to have high sensitivity and specificity to the different suicidal behavior classifications. The CSSRS does not provide a numerical score but categorizes risk levels based on responses. We report the proportions of risk at each timepoint.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable CSSRS data at the respective timepoint.
| Arm | Measure | Group | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | No Risk | 37 Participants |
| Pre-treatment Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | Low Risk | 13 Participants |
| Pre-treatment Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | Moderate Risk | 0 Participants |
| Pre-treatment Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | High Risk | 0 Participants |
| Change in Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | High Risk | 0 Participants |
| Change in Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | No Risk | 41 Participants |
| Change in Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | Moderate Risk | 1 Participants |
| Change in Amygdala Activation | Change in Columbia Suicide Severity Rating Scale | Low Risk | 5 Participants |
Comparison: Analysis of change in suicidal risk was done by applying ordinal logistic regression (proportional odds model) testing the effect of treatment-time on the probability of being in a higher risk category. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.03Mixed Models Analysis
Secondary
Change in Insomnia Severity Index (ISI) Scale Score
Subjective ratings of sleep disturbance and insomnia severity will be assessed with the Insomnia Severity Index. The Insomnia Severity Index (ISI) is a 7-item self-report measure of insomnia type, severity, and impact on functioning. The items consist of severity of sleep onset, sleep maintenance, early morning awakenings, sleep dissatisfaction, interference with daytime functioning, noticeability of sleep problems by others, and distress caused by sleep difficulties. Items are scored from 0 to 4 (0 = no problem, 4 = very severe problem), then summed to create an overall score of 0 to 28. Score ranges of insomnia are: 0-7 absent, 8-14 sub-threshold, 15-21 moderate, and 22-28 severe. The ISI has good validity and reliability. A negative change score means average insomnia symptoms improved following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had ISI data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Insomnia Severity Index (ISI) Scale Score | 15.7 units on a scale | Standard Deviation 3.83 |
| Change in Amygdala Activation | Change in Insomnia Severity Index (ISI) Scale Score | -7.98 units on a scale | Standard Deviation 3.96 |
Comparison: Analysis of change in insomnia symptom severity score was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: <0.0001Mixed Models Analysis
Secondary
Change in PSG Number of Arousals as a Measure of Sleep Architecture
Number of Arousals is determined by number of times of awakening by EEG changes. A negative change score means on average there were fewer overnight arousals following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable PSG data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in PSG Number of Arousals as a Measure of Sleep Architecture | 21.96 Number of Awakenings | Standard Deviation 7.3 |
| Change in Amygdala Activation | Change in PSG Number of Arousals as a Measure of Sleep Architecture | -1.44 Number of Awakenings | Standard Deviation 9.67 |
Comparison: Analysis of change in number of awakenings derived from PSG was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.33Mixed Models Analysis
Secondary
Change in PSG Sleep Onset Latency (SOL) as a Measure of Sleep Architecture
Sleep onset latency is the time it takes to fall asleep, specifically the amount of time in minutes from LightsOff, which is the time at which the participant started trying to sleep, to stage 1 sleep. A negative change score means it took less time to fall asleep following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable PSG data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in PSG Sleep Onset Latency (SOL) as a Measure of Sleep Architecture | 30.29 Minutes | Standard Deviation 39.34 |
| Change in Amygdala Activation | Change in PSG Sleep Onset Latency (SOL) as a Measure of Sleep Architecture | -11.44 Minutes | Standard Deviation 47.96 |
Comparison: Analysis of change in sleep onset latency (PSG) was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.28Mixed Models Analysis
Secondary
Change in PSG Total Sleep Time (TST) as a Measure of Sleep Architecture
Total Sleep Time (TST) is the total time (minutes) spent asleep, from the start of sleep onset to sleep offset, subtracting any periods of wakefulness. TST includes stages N1, N2, N3, and REM sleep. A positive change score means the average TST increased following CBT-I.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable PSG data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in PSG Total Sleep Time (TST) as a Measure of Sleep Architecture | 362.23 Minutes | Standard Deviation 93.31 |
| Change in Amygdala Activation | Change in PSG Total Sleep Time (TST) as a Measure of Sleep Architecture | 5.67 Minutes | Standard Deviation 103.27 |
Comparison: Analysis of change in PSG TST was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.66Mixed Models Analysis
Secondary
Change in PSG Wake After Sleep Onset (WASO) as a Measure of Sleep Architecture
Wake After Sleep Onset (WASO) are periods of wakefulness occurring after sleep onset, before final awakening (sleep offset) measured by EEG changes. A negative change value means there was less WASO on average after CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: Participants who completed pre-treatment baseline, and who had interpretable PSG data at the respective timepoint.
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in PSG Wake After Sleep Onset (WASO) as a Measure of Sleep Architecture | 58.3 Minutes | Standard Deviation 63.02 |
| Change in Amygdala Activation | Change in PSG Wake After Sleep Onset (WASO) as a Measure of Sleep Architecture | -27.74 Minutes | Standard Deviation 66.42 |
Comparison: Analysis of change in wake after sleep onset (WASO) was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.013Mixed Models Analysis
Secondary
Change in Respiratory Sinus Arrhythmia (RSA)- Measured by PSG
RSA is the phenomenon of an increased heart rate during inhalation and a decreased heart rate during exhalation. Since these fluctuations are controlled mainly by vagal influences on the heart, RSA serves as a reliable metric for measuring parasympathetic activity. RSA has been proven to be a reliable measure of emotion regulation and emotional responding in numerous studies.
Time frame: Assessed at week 0 and week 11
Secondary
Change in Sleep Physiology Measured by PSG
Fronto-central EEG power spectral density analysis associated with sleep stages will be calculated in the Delta (0.5-Hz), Theta (4-7Hz), Alpha (7-11Hz), Sigma (12-15Hz), Beta-1 (15-20Hz), Beta-2 (20-35Hz) and Gamma (35-45Hz) bands, according to published methods. A positive change score means there was an increase in absolute power in the specified frequency band following CBT-I treatment.
Time frame: Assessed at week 0 and week 11
Population: All participants who competed pre-treatment baseline and with interpretable PSG data at the respective timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Theta (4-7Hz) | 18.77 Absolute spectral power, µV²/Hz | Standard Deviation 2.29 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Beta-1 (15-20Hz) | 9.82 Absolute spectral power, µV²/Hz | Standard Deviation 2.68 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Delta (0.5-4Hz) | 29.52 Absolute spectral power, µV²/Hz | Standard Deviation 2.41 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Beta-2 (20-35Hz) | 9.23 Absolute spectral power, µV²/Hz | Standard Deviation 2.36 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Alpha (7-11Hz) | 17.47 Absolute spectral power, µV²/Hz | Standard Deviation 2.68 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Gamma (35-45Hz) | 2.90 Absolute spectral power, µV²/Hz | Standard Deviation 1.86 |
| Pre-treatment Amygdala Activation | Change in Sleep Physiology Measured by PSG | Sigma (12-15Hz) | 14.03 Absolute spectral power, µV²/Hz | Standard Deviation 2.85 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Gamma (35-45Hz) | 0.13 Absolute spectral power, µV²/Hz | Standard Deviation 1.68 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Delta (0.5-4Hz) | 0.04 Absolute spectral power, µV²/Hz | Standard Deviation 1.56 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Theta (4-7Hz) | 0.40 Absolute spectral power, µV²/Hz | Standard Deviation 1.4 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Sigma (12-15Hz) | 0.25 Absolute spectral power, µV²/Hz | Standard Deviation 1.23 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Beta-1 (15-20Hz) | 0.15 Absolute spectral power, µV²/Hz | Standard Deviation 1.11 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Beta-2 (20-35Hz) | 0.08 Absolute spectral power, µV²/Hz | Standard Deviation 1.29 |
| Change in Amygdala Activation | Change in Sleep Physiology Measured by PSG | Alpha (7-11Hz) | 0.37 Absolute spectral power, µV²/Hz | Standard Deviation 1.03 |
Comparison: Analysis of change in PSG Delta absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.96Mixed Models Analysis
Comparison: Analysis of change in PSG Theta absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.23Mixed Models Analysis
Comparison: Analysis of change in PSG Alpha absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.11Mixed Models Analysis
Comparison: Analysis of change in PSG Sigma absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.44Mixed Models Analysis
Comparison: Analysis of change in PSG Beta-1 absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.68Mixed Models Analysis
Comparison: Analysis of change in PSG Beta-2 absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.74Mixed Models Analysis
Comparison: Analysis of change in PSG Gamma absolute power was done by applying linear mixed effects models testing the effect of treatment-time. Random intercepts at the individual participant level are included to account for the clustering of observations within individuals across time. All statistical models include age and sex as covariates of non-interest.p-value: 0.84Mixed Models Analysis