Improved implicit self-esteem is associated with extended antidepressant effects following a novel synergistic intervention.

INTRODUCTION: In a previously published randomized controlled trial, automated self-association training (ASAT), a novel digital intervention, was found to extend the rapid antidepressant effect of a single infusion of ketamine for at least 30 days. In this secondary analysis, we aimed to understand the potential role of implicit self-esteem in the combined antidepressant effect of ketamine and ASAT training, by investigating the novel synergistic treatment's effects on implicit self-associations and their relation to symptom improvement. METHODS: A total of 154 adults (ages 18-60) with treatment-resistant unipolar depression and lower-than-normative explicit self-esteem were randomized in a double-blind, parallel-arm design to receive one of three treatment allocations: an active/active treatment combination consisting of one infusion of ketamine (0.5 mg/kg) followed by four days of ASAT ( ~ 30-40 min/day), or one of two control arms that lacked either the active drug or the active behavioral component. The Implicit Association Test (IAT) was used to behaviorally assess the strength of association between self-related stimuli and negative concepts. Linear regression models were used to test the relationship between group assignment, IAT scores acquired immediately post-treatment, and both acute and extended clinical outcomes (% change in Montgomery-Asberg Depression Rating Scale scores, relative to pre-treatment baseline) in the trial. RESULTS: The group assigned to ketamine + ASAT intervention, compared to the other groups, had a pattern of IAT scores indicating more positive self-associations immediately after treatment relative to the control arms (F(1, 131) = 3.979; p = 0.048). In regression models, IAT scores tracked with concurrent (acute post-treatment) % change in MADRS scores across all treatment arms (p = 0.001), and mediated more extended (Day 30) depression improvements specifically for the ketamine+ASAT arm (group * IAT interaction term: ß = -0.201; p = 0.049). DISCUSSION: Our findings suggest that changing implicit self-worth during a post-ketamine 'plasticity window' is one key mechanism whereby the novel ketamine+ASAT treatment combination exerts its antidepressant benefit, confirming the intended treatment target at the level of implicit cognition. Future studies should seek to further enhance the reliability of the biobehavioral intervention's impact on implicit cognition, as this mechanism appears linked to the intervention's enduring clinical benefits.

Ten-Year Stability of an Insomnia Sleeper Phenotype and Its Association With Chronic Conditions.

OBJECTIVE: To identify distinct sleep health phenotypes in adults, examine transitions in sleep health phenotypes over time, and subsequently relate these to the risk of chronic conditions. METHODS: A national sample of adults from the Midlife in the United States study ( N = 3683) provided longitudinal data with two time points (T1: 2004-2006, T2: 2013-2017). Participants self-reported on sleep health (regularity, satisfaction, alertness, efficiency, duration) and the number and type of chronic conditions. Covariates included age, sex, race, education, education, partnered status, number of children, work status, smoking, alcohol, and physical activity. RESULTS: Latent transition analysis identified four sleep health phenotypes across both time points: good sleepers, insomnia sleepers, weekend catch-up sleepers, and nappers. Between T1 and T2, the majority (77%) maintained their phenotype, with the nappers and insomnia sleepers being the most stable. In fully adjusted models with good sleepers at both time points as the reference, being an insomnia sleeper at either time point was related to having an increased number of total chronic conditions by 28%-81% at T2, adjusting for T1 conditions. Insomnia sleepers at both time points were at 72%-188% higher risk for cardiovascular disease, diabetes, depression, and frailty. Being a napper at any time point related to increased risks for diabetes, cancer, and frailty. Being a weekend catch-up sleeper was not associated with chronic conditions. Those with lower education and unemployed were more likely to be insomnia sleepers; older adults and retirees were more likely to be nappers. CONCLUSION: Findings indicate a heightened risk of chronic conditions involved in suboptimal sleep health phenotypes, mainly insomnia sleepers.

Pre-pandemic circadian phase predicts pandemic alcohol use among adolescents.

Later circadian timing during adolescence is linked to worse sleep, more severe depression and greater alcohol involvement, perhaps due to circadian misalignment imposed by early school schedules. School schedules shifted later during the COVID-19 pandemic, ostensibly reducing circadian misalignment and potentially mitigating problems with depression and alcohol. We used the pandemic as a natural experiment to test whether adolescent drinkers with later circadian timing showed improvements in sleep, depression and alcohol involvement. Participants were 42 adolescents reporting alcohol use. We assessed circadian phase via dim light melatonin onset prior to the pandemic, then conducted remote assessments of sleep, depressive symptoms and alcohol use during the pandemic. Mixed-effects models were used to test for pandemic effects, covarying for age, sex, time since baseline evaluation, and current school/work status. Adolescents with later circadian timing reported less sleep than other teens on school nights, both before and during the pandemic. Although school night sleep increased during the pandemic (F = 28.36, p < 0.001), those increases were not greater for individuals with later circadian timing. Individuals with later circadian timing reported larger increases in alcohol use than other teens during the pandemic (X2 = 36.03, p < 0.001). Depressive symptoms increased during the pandemic (X2 = 46.51, p < 0.001) but did not differ based on circadian timing. Consistent with prior reports, adolescents with later circadian timing obtained less sleep, and later school schedules facilitated increased sleep duration. Nonetheless, individuals with later circadian timing reported the sharpest increases in alcohol use, suggesting that circadian timing contributes to risk for alcohol use beyond the effects of insufficient sleep.

Elusive hypersomnolence in seasonal affective disorder: actigraphic and self-reported sleep in and out of depressive episodes.

BACKGROUND: Hypersomnolence has been considered a prominent feature of seasonal affective disorder (SAD) despite mixed research findings. In the largest multi-season study conducted to date, we aimed to clarify the nature and extent of hypersomnolence in SAD using multiple measurements during winter depressive episodes and summer remission. METHODS: Sleep measurements assessed in individuals with SAD and nonseasonal, never-depressed controls included actigraphy, daily sleep diaries, retrospective self-report questionnaires, and self-reported hypersomnia assessed via clinical interviews. To characterize hypersomnolence in SAD we (1) compared sleep between diagnostic groups and seasons, (2) examined correlates of self-reported hypersomnia in SAD, and (3) assessed agreement between commonly used measurement modalities. RESULTS: In winter compared to summer, individuals with SAD (n = 64) reported sleeping 72 min longer based on clinical interviews (p < 0.001) and 23 min longer based on actigraphy (p = 0.011). Controls (n = 80) did not differ across seasons. There were no seasonal or group differences on total sleep time when assessed by sleep diaries or retrospective self-reports (p's > 0.05). Endorsement of winter hypersomnia in SAD participants was predicted by greater fatigue, total sleep time, time in bed, naps, and later sleep midpoints (p's < 0.05). CONCLUSION: Despite a winter increase in total sleep time and year-round elevated daytime sleepiness, the average total sleep time (7 h) suggest hypersomnolence is a poor characterization of SAD. Importantly, self-reported hypersomnia captures multiple sleep disruptions, not solely lengthened sleep duration. We recommend using a multimodal assessment of hypersomnolence in mood disorders prior to sleep intervention.

International pooled patient-level meta-analysis of ketamine infusion for depression: In search of clinical moderators.

Depression is disabling and highly prevalent. Intravenous (IV) ketamine displays rapid-onset antidepressant properties, but little is known regarding which patients are most likely to benefit, limiting personalized prescriptions. We identified randomized controlled trials of IV ketamine that recruited individuals with a relevant psychiatric diagnosis (e.g., unipolar or bipolar depression; post-traumatic stress disorder), included one or more control arms, did not provide any other study-administered treatment in conjunction with ketamine (although clinically prescribed concurrent treatments were allowable), and assessed outcome using either the Montgomery-Åsberg Depression Rating Scale or the Hamilton Rating Scale for Depression (HRSD-17). Individual patient-level data for at least one outcome was obtained from 17 of 25 eligible trials [pooled n = 809]. Rates of participant-level data availability across 33 moderators that were solicited from these 17 studies ranged from 10.8% to 100% (median = 55.6%). After data harmonization, moderators available in at least 40% of the dataset were tested sequentially, as well as with a data-driven, combined moderator approach. Robust main effects of ketamine on acute [~24-hours; ß*(95% CI) = 0.58 (0.44, 0.72); p < 0.0001] and post-acute [~7 days; ß*(95% CI) = 0.38 (0.23, 0.54); p < 0.0001] depression severity were observed. Two study-level moderators emerged as significant: ketamine effects (relative to placebo) were larger in studies that required a higher degree of previous treatment resistance to federal regulatory agency-approved antidepressant medications (≥2 failed trials) for study entry; and in studies that used a crossover design. A comprehensive data-driven search for combined moderators identified statistically significant, but modest and clinically uninformative, effects (effect size r ≤ 0.29, a small-medium effect). Ketamine robustly reduces depressive symptoms in a heterogeneous range of patients, with benefit relative to placebo even greater in patients more resistant to prior medications. In this largest effort to date to apply precision medicine approaches to ketamine treatment, no clinical or demographic patient-level features were detected that could be used to guide ketamine treatment decisions.Review Registration: PROSPERO Identifier: CRD42021235630.

Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction.

BACKGROUND: Machine learning tools such as random forests provide important opportunities for modeling large, complex modern data generated in medicine. Unfortunately, when it comes to understanding why machine learning models are predictive, applied research continues to rely on 'out of bag' (OOB) variable importance metrics (VIMPs) that are known to have considerable shortcomings within the statistics community. After explaining the limitations of OOB VIMPs - including bias towards correlated features and limited interpretability - we describe a modern approach called 'knockoff VIMPs' and explain its advantages. METHODS: We first evaluate current VIMP practices through an in-depth literature review of 50 recent random forest manuscripts. Next, we recommend organized and interpretable strategies for analysis with knockoff VIMPs, including computing them for groups of features and considering multiple model performance metrics. To demonstrate methods, we develop a random forest to predict 5-year incident stroke in the Sleep Heart Health Study and compare results based on OOB and knockoff VIMPs. RESULTS: Nearly all papers in the literature review contained substantial limitations in their use of VIMPs. In our demonstration, using OOB VIMPs for individual variables suggested two highly correlated lung function variables (forced expiratory volume, forced vital capacity) as the best predictors of incident stroke, followed by age and height. Using an organized analytic approach that considered knockoff VIMPs of both groups of features and individual features, the largest contributions to model sensitivity were medications (especially cardiovascular) and measured medical risk factors, while the largest contributions to model specificity were age, diastolic blood pressure, self-reported medical risk factors, polysomnography features, and pack-years of smoking. Thus, we reach very different conclusions about stroke risk factors using OOB VIMPs versus knockoff VIMPs. CONCLUSIONS: The near-ubiquitous reliance on OOB VIMPs may provide misleading results for researchers who use such methods to guide their research. Given the rapid pace of scientific inquiry using machine learning, it is essential to bring modern knockoff VIMPs that are interpretable and unbiased into widespread applied practice to steer researchers using random forest machine learning toward more meaningful results.

The association between multidimensional sleep health and gestational weight gain.

BACKGROUND: Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep health framework is needed. OBJECTIVES: This secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n = 745) examined associations between mid-pregnancy sleep health indicators, multidimensional sleep health and gestational weight gain (GWG). METHODS: Sleep domains (i.e. regularity, nap duration, timing, efficiency and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined 'healthy' sleep in each domain with empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis and composite score defined as the sum of healthy sleep domains. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD) and high (>+1 SD). RESULTS: Nearly 50% of the participants had a healthy sleep profile (i.e. healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of unhealthy sleep in each domain. The individual sleep domains were associated with a 20%-30% lower risk of low or high GWG. Each additional healthy sleep indicator was associated with a 10% lower risk of low (vs. moderate), but not high, GWG. Participants with late timing, long duration and low efficiency (vs. healthy) profiles had the strongest risk of low GWG (relative risk 1.5, 95% confidence interval 0.9, 2.4). Probabilistic bias analysis suggested that most associations between individual sleep health indicators, sleep health profiles and GWG were biased towards the null. CONCLUSIONS: Future research should determine whether sleep health is an intervention target for healthy GWG.

Prototyping Apps for the Management of Sleep, Fatigue, and Behavioral Health in Austere Far-Forward Environments: Development Study.

BACKGROUND: Military service inherently includes frequent periods of high-stress training, operational tempo, and sustained deployments to austere far-forward environments. These occupational requirements can contribute to acute and chronic sleep disruption, fatigue, and behavioral health challenges related to acute and chronic stress and disruption of team dynamics. To date, there is no centralized mobile health platform that supports self- and supervised detection, monitoring, and management of sleep and behavioral health issues in garrison and during and after deployments. OBJECTIVE: The objective of this study was to adapt a clinical decision support platform for use outside clinical settings, in garrison, and during field exercises by medics and soldiers to monitor and manage sleep and behavioral health in operational settings. METHODS: To adapt an existing clinical decision support digital health platform, we first gathered system, content, and context-related requirements for a sleep and behavioral health management system from experts. Sleep and behavioral health assessments were then adapted for prospective digital data capture. Evidence-based and operationally relevant educational and interventional modules were formatted for digital delivery. These modules addressed the management and mitigation of sleep, circadian challenges, fatigue, stress responses, and team communication. Connectivity protocols were adapted to accommodate the absence of cellular or Wi-Fi access in deployed settings. The resulting apps were then tested in garrison and during 2 separate field exercises. RESULTS: Based on identified requirements, 2 Android smartphone apps were adapted for self-monitoring and management for soldiers (Soldier app) and team supervision and intervention by medics (Medic app). A total of 246 soldiers, including 28 medics, received training on how to use the apps. Both apps function as expected under conditions of limited connectivity during field exercises. Areas for future technology enhancement were also identified. CONCLUSIONS: We demonstrated the feasibility of adapting a clinical decision support platform into Android smartphone-based apps to collect, save, and synthesize sleep and behavioral health data, as well as share data using adaptive data transfer protocols when Wi-Fi or cellular data are unavailable. The AIRE (Autonomous Connectivity Independent System for Remote Environments) prototype offers a novel self-management and supervised tool to augment capabilities for prospective monitoring, detection, and intervention for emerging sleep, fatigue, and behavioral health issues that are common in military and nonmilitary high-tempo occupations (eg, submarines, long-haul flights, space stations, and oil rigs) where medical expertise is limited.

Age Trends in Actigraphy and Self-Report Sleep Across the Life Span: Findings From the Pittsburgh Lifespan Sleep Databank.

OBJECTIVE: Sleep changes over the human life span, and it does so across multiple dimensions. We used individual-level cross-sectional data to characterize age trends and sex differences in actigraphy and self-report sleep dimensions across the healthy human life span. METHODS: The Pittsburgh Lifespan Sleep Databank consists of harmonized participant-level data from sleep-related studies conducted at the University of Pittsburgh (2003-2019). We included data from 1065 (n = 577 female; 21 studies) Pittsburgh Lifespan Sleep Databank participants aged 10 to 87 years without a major psychiatric, sleep, or medical condition. All participants completed wrist actigraphy and the self-rated Pittsburgh Sleep Quality Index. Main outcomes included actigraphy and self-report sleep duration, efficiency, and onset/offset timing, and actigraphy variability in midsleep timing. RESULTS: We used generalized additive models to examine potentially nonlinear relationships between age and sleep characteristics and to examine sex differences. Actigraphy and self-report sleep onset time shifted later between ages 10 and 18 years (23:03-24:10 [actigraphy]; 21:58-23:53 [self-report]) and then earlier during the 20s (00:08-23:40 [actigraphy]; 23:50-23:34 [self-report]). Actigraphy and self-report wake-up time also shifted earlier during the mid-20s through late 30s (07:48-06:52 [actigraphy]; 07:40-06:41 [self-report]). Self-report, but not actigraphy, sleep duration declined between ages 10 and 20 years (09:09-07:35). Self-report sleep efficiency decreased over the entire life span (96.12-93.28), as did actigraphy variability (01:54-01:31). CONCLUSIONS: Awareness of age trends in multiple sleep dimensions in healthy individuals-and explicating the timing and nature of sex differences in age-related change-can suggest periods of sleep-related risk or resilience and guide intervention efforts.

Self-reported sleep and circadian characteristics predict alcohol and cannabis use: A longitudinal analysis of the National Consortium on Alcohol and Neurodevelopment in Adolescence Study.

BACKGROUND: Growing evidence indicates that sleep characteristics predict future substance use and related problems. However, most prior studies assessed a limited range of sleep characteristics, studied a narrow age span, and included few follow-up assessments. Here, we used six annual assessments from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study, which spans adolescence and young adulthood with an accelerated longitudinal design, to examine whether multiple sleep characteristics in any year predict alcohol and cannabis use the following year. METHODS: The sample included 831 NCANDA participants (423 females; baseline age 12-21 years). Sleep variables included circadian preference, sleep quality, daytime sleepiness, the timing of midsleep (weekday/weekend), and sleep duration (weekday/weekend). Using generalized linear mixed models (logistic for cannabis; ordinal for binge severity), we tested whether each repeatedly measured sleep characteristic (years 0-4) predicted substance use (alcohol binge severity or cannabis use) the following year (years 1-5), covarying for age, sex, race, visit, parental education, and previous year's substance use. RESULTS: Greater eveningness, more daytime sleepiness, later weekend sleep timing, and shorter sleep duration (weekday/weekend) all predicted more severe alcohol binge drinking the following year. Only greater eveningness predicted a greater likelihood of any cannabis use the following year. Post-hoc stratified exploratory analyses indicated that some associations (e.g., greater eveningness and shorter weekend sleep duration) predicted binge severity only in female participants, and that middle/high school versus post-high school adolescents were more vulnerable to sleep-related risk for cannabis use. CONCLUSIONS: Our findings support the relevance of multiple sleep/circadian characteristics in the risk for future alcohol binge severity and cannabis use. Preliminary findings suggest that these risk factors vary based on developmental stage and sex. Results underscore a need for greater attention to sleep/circadian characteristics as potential risk factors for substance use in youth and may inform new avenues to prevention and intervention.

A precision medicine tool to understand who responds best to hearing aids in late-life depression.

OBJECTIVES: Accumulating evidence suggests that hearing loss (HL) treatment may benefit depressive symptoms among older adults with Major Depressive Disorder (MDD), but the specific individual characteristics of those who stand to improve most are unknown. METHODS: N = 37 patients ≥60 years with HL and MDD received either active or sham hearing aids in this 12-week double-blind randomized controlled trial. A combined moderator approach was utilized in the analysis in order to examine multiple different pretreatment individual characteristics to determine the specific qualities that predicted the best depressive symptom response to hearing aids. Pretreatment characteristics included: Hearing Handicap Inventory for the Elderly (HHIE-S), pure tone average (PTA), speech reception threshold (SRT), Short Physical Performance Battery (SPPB), cognition (Repeatable Battery for the Assessment of Neuropsychological Status). RESULTS: The analysis revealed a combined moderator, predicting greater improvement with active versus sham hearing aids, that had a larger effect size than any individual moderator (combined effect size [ES] = 0.49 [95% CI: 0.36, 0.76]). Individuals with worse hearing-related disability (HHIE-S: individual ES = -0.16), speech recognition (SRT: individual ES = -0.14), physical performance (SPPB: individual ES = 0.41), and language functioning (individual ES = 0.19) but with relatively less severe audiometric thresholds (PTA: individual ES = 0.17) experienced greater depressive symptom improvement with active hearing aids. CONCLUSIONS: Older adults with relatively worse HL-related, physical, and cognitive functioning may stand to benefit most from hearing aids. Given the large number of older adults experiencing HL and MDD, a non-invasive and scalable means of targeting those most likely to respond to interventions would be valuable.

Racial-ethnic Differences in Actigraphy, Questionnaire, and Polysomnography Indicators of Healthy Sleep: The Multi-Ethnic Study of Atherosclerosis.

A paradigm shift in sleep science argues for a systematic, multidimensional approach to investigate sleep's association with disease and mortality and to address sleep disparities. We utilized the comprehensive sleep assessment of the Multi-Ethnic Study of Atherosclerosis (2010- 2013), a cohort of U.S. White, Black, Chinese, and Hispanic adults and older adults (n=1,736; mean age=68.3), to draw 13 sleep dimensions and create composite Sleep Health Scores to quantify multidimensional sleep health disparities. After age and sex adjustment in linear regression, compared to White participants, Black participants showed the greatest global sleep disparity, then Hispanic and Chinese participants. We estimated relative 'risk' of obtaining favorable sleep compared to White adults at the component level by race/ethnicity (lower is worse). The largest disparities were in objectively-measured sleep timing regularity (RRBlack [95% CI]: 0.37 [0.29,0.47], RRHispanic: 0.64 [0.52,0.78], RRChinese: 0.70 [0.54,0.90]) and duration regularity (RRBlack: 0.55 [0.47,0.65], RRHispanic: 0.76 [0.66,0.88], RRChinese: 0.74 [0.61,0.90]), after sex and age adjustment. Disparities in duration and continuity were also apparent, and Black adults were additionally disadvantaged in %N3 (slow wave sleep), sleepiness, and sleep timing (24-hour placement). Sleep timing regularity, duration regularity, duration, and continuity may comprise a multidimensional cluster of targets to reduce racial-ethnic sleep disparities.

Opposing relationships of childhood threat and deprivation with stria terminalis white matter.

While stress may be a potential mechanism by which childhood threat and deprivation influence mental health, few studies have considered specific stress-related white matter pathways, such as the stria terminalis (ST) and medial forebrain bundle (MFB). Our goal was to examine the relationships between childhood adversity and ST and MFB structural integrity and whether these pathways may provide a link between childhood adversity and affective symptoms and disorders. Participants were young adults (n = 100) with a full distribution of maltreatment history and affective symptom severity. Threat was determined by measures of childhood abuse and repeated traumatic events. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education). Participants underwent diffusion spectrum imaging. Human Connectome Project data was used to perform ST and MFB tractography; these tracts were used as ROIs to extract generalized fractional anisotropy (gFA) from each participant. Childhood threat was associated with ST gFA, such that greater threat was associated with less ST gFA. SED was also associated with ST gFA, however, conversely to threat, greater SED was associated with greater ST gFA. Additionally, threat was negatively associated with MFB gFA, and MFB gFA was negatively associated with post-traumatic stress symptoms. Our results suggest that childhood threat and deprivation have opposing influences on ST structural integrity, providing new evidence that the context of childhood adversity may have an important influence on its neurobiological effects, even on the same structure. Further, the MFB may provide a novel link between childhood threat and affective symptoms.

Experimentally imposed circadian misalignment alters the neural response to monetary rewards and response inhibition in healthy adolescents.

BACKGROUND: Sleep and circadian timing shifts later during adolescence, conflicting with early school start times, and resulting in circadian misalignment. Although circadian misalignment has been linked to depression, substance use, and altered reward function, a paucity of experimental studies precludes the determination of causality. Here we tested, for the first time, whether experimentally-imposed circadian misalignment alters the neural response to monetary reward and/or response inhibition. METHODS: Healthy adolescents (n = 25, ages 13-17) completed two in-lab sleep schedules in counterbalanced order: An 'aligned' condition based on typical summer sleep-wake times (0000-0930) and a 'misaligned' condition mimicking earlier school year sleep-wake times (2000-0530). Participants completed morning and afternoon functional magnetic resonance imaging scans during each condition, including monetary reward (morning only) and response inhibition (morning and afternoon) tasks. Total sleep time and circadian phase were assessed via actigraphy and salivary melatonin, respectively. RESULTS: Bilateral ventral striatal (VS) activation during reward outcome was lower during the Misaligned condition after accounting for the prior night's total sleep time. Bilateral VS activation during reward anticipation was lower during the Misaligned condition, including after accounting for covariates, but did not survive correction for multiple comparisons. Right inferior frontal gyrus activation during response inhibition was lower during the Misaligned condition, before and after accounting for total sleep time and vigilant attention, but only during the morning scan. CONCLUSIONS: Our findings provide novel experimental evidence that circadian misalignment analogous to that resulting from school schedules may have measurable impacts on healthy adolescents' reward processing and inhibition of prepotent responses.

Physiological sleep measures predict time to 15-year mortality in community adults: Application of a novel machine learning framework.

Clarifying whether physiological sleep measures predict mortality could inform risk screening; however, such investigations should account for complex and potentially non-linear relationships among health risk factors. We aimed to establish the predictive utility of polysomnography (PSG)-assessed sleep measures for mortality using a novel permutation random forest (PRF) machine learning framework. Data collected from the years 1995 to present are from the Sleep Heart Health Study (SHHS; n = 5,734) and the Wisconsin Sleep Cohort Study (WSCS; n = 1,015), and include initial assessments of sleep and health, and up to 15 years of follow-up for all-cause mortality. We applied PRF models to quantify the predictive abilities of 24 measures grouped into five domains: PSG-assessed sleep (four measures), self-reported sleep (three), health (eight), health behaviours (four), and sociodemographic factors (five). A 10-fold repeated internal validation (WSCS and SHHS combined) and external validation (training in SHHS; testing in WSCS) were used to compute unbiased variable importance metrics and associated p values. We observed that health, sociodemographic factors, and PSG-assessed sleep domains predicted mortality using both external validation and repeated internal validation. The PSG-assessed sleep efficiency and the percentage of sleep time with oxygen saturation <90% were among the most predictive individual measures. Multivariable Cox regression also revealed the PSG-assessed sleep domain to be predictive, with very low sleep efficiency and high hypoxaemia conferring the highest risk. These findings, coupled with the emergence of new low-burden technologies for objectively assessing sleep and overnight oxygen saturation, suggest that consideration of physiological sleep measures may improve risk screening.

Ecological momentary assessment of stress, racism and other forms of discrimination during pregnancy using smartphone technology.

BACKGROUND: In the United States, there are considerable racial inequities in adverse perinatal outcomes. Exposure to racism, sexism, and other forms of oppression may help explain these inequities. OBJECTIVES: To describe the application of real-time data collection using ecological momentary assessment (EMA) and smartphone technology to assess exposure to stress, racism, sexism, microaggressions, and other forms of oppression. METHODS: The Postpartum Mothers Mobile Study (PMOMS) is an ongoing longitudinal cohort study that began recruitment in December 2017. Participants delivering at a hospital in Pittsburgh, PA are recruited by 29 weeks' gestation. Using smartphones and smart scales, participants complete daily surveys related to psychosocial, behavioural, and contextual factors and weigh themselves weekly for approximately 15 months. We provide a preliminary descriptive analysis of EMA self-reported measures of stress, racism, sexism, and microaggressions; and non-EMA measures of stress and major discrimination. RESULTS: The sample (n = 230) is 63.5% White, 24.8% Black/African American, and 7% Hispanic origin. The most commonly reported item from the Major Discrimination Scale is being unfairly fired (18.1% of the sample). Of those, 31.7% and 17.1% attribute unfair firing to their gender and race, respectively. From the random EMA measures, on average, participants report experiences of racism and sexism at least once daily, in an average 12-hour day over the 4-week period. Black participants indicate about two experiences per day of racism, and White participants indicate more than 1 per day of sexism. Mean stress levels from the EMA measures were similar to the stress measures collected at baseline. CONCLUSIONS: The methods applied in PMOMS provide real-time data regarding how participants' daily experiences of stress and discrimination influence their lives. Future work will include understanding if and how these EMA measures may relate to already established measures of racism, sexism, and stress; and ultimately understanding associations with perinatal inequities.

Interactions between childhood maltreatment and combat exposure trauma on stress-related activity within the cingulate cortex: a pilot study.

Childhood trauma may sensitize the brain, increasing vulnerability to maladaptive stress responses following adulthood trauma exposure. Previous work has identified the cingulum as a white matter pathway that may be sensitized to adulthood trauma by childhood maltreatment. In this pilot study of young adult male military veterans (N = 28), we examined a priori regions of interest (ROIs) connected by the cingulum, including regions involved in cognitive processes and stress responses. Our goal was to examine the interaction between childhood maltreatment and combat exposure on stress-related activity within cingulum-associated ROIs. As such we utilized a mild cognitive stress task, a performance-titrated multi-source interference task (MSIT). We found that childhood maltreatment moderated the effect of combat exposure on stress-related, interference-evoked activity within the dorsal anterior cingulate cortex (dACC, activation), subgenual ACC (sgACC, deactivation) and posterior midcingulate cortex (pMCC, deactivation). Greater combat exposure was associated with greater interference-evoked activation within the dACC, and less sgACC and pMCC deactivation among individuals with more severe childhood maltreatment. Our findings suggest that child maltreatment sensitizes these anterior and mid-cingulate regions to later life trauma. These findings may have implications for cognitive control, autonomic regulation/stress reactivity, and responses to noxious/aversive stimuli, which may contribute to increased psychiatric vulnerability.

Preliminary Evidence That Real World Sleep Timing and Duration are Associated With Laboratory-Assessed Alcohol Response.

BACKGROUND: Sleep timing and evening chronotype have been implicated in alcohol use problems but research has yet to study them in relation to theory-driven laboratory-based measures of alcohol use disorder risk. The current study examined (i) whether chronotype, sleep timing, and/or sleep duration are associated with alcohol response (subjective stimulation, sedation, and behavioral disinhibition) and (ii) if sex and race moderate these associations. METHODS: Adult drinkers (N = 144; 46 female participants) completed 2 counterbalanced beverage administration sessions (alcohol and nonalcohol) during which they rated stimulation/sedation and completed a cued go/no-go task. They reported bed and waketimes over 10 days. RESULTS: Later sleep timing was associated with greater increases in alcohol stimulation, but among male and White participants only. Later sleep timing (among male participants) and greater eveningness (examined among White male participants only) were associated with greater overall stimulation on average in the alcohol session relative to the nonalcohol session, irrespective of alcohol consumption. More variable sleep duration was associated with greater increases in sedation. CONCLUSIONS: These findings offer preliminary, but novel evidence that sleep characteristics may relate to the relative stimulating and sedating effects of alcohol, thereby influencing the risk for alcohol problems.

Using optimal combined moderators to define heterogeneity in neural responses to randomized conditions: Application to the effect of sleep loss on fear learning.

Comparing the neural outcomes of two randomized experimental groups is a primary aim of many functional neuroimaging studies. However, between-group effects can be obscured by heterogeneity in neural responses. Optimal Combined Moderator (OCM) approaches have previously been used to clarify heterogeneity in clinical outcomes following treatment randomization. We show that OCMs can also be used to clarify heterogeneity in the effect of a randomized experimental condition on neural responses. In 78 healthy adults aged 18-30 from the Effects of Dose-Dependent Sleep Disruption on Fear and Reward (SFeRe) study, we used demographic, clinical, genetic, and polysomnographic characteristics to develop OCMs for the effect of a randomized sleep restriction (SR) versus normal sleep (NS) condition on blood-oxygen-level dependent responses in the right amygdala (RAmyg) and subgenual anterior cingulate cortex (sgACC) during fear conditioning (FC) and extinction (FE) paradigms. The OCM for the RAmyg during FE was strongest [r (95% CI) = 0.52 (0.42, 0.68)], withstood cross-validation, and divided the sample into two subgroups with opposing experimental effects. Among N = 48 participants ("SR < NS"), those with SR exhibited less RAmyg activation during FE than those with NS [d (95%CI) = -1.10 (-1.86, -0.77)]. Among the remaining N = 30 participants ("SR > NS"), those with SR exhibited greater RAmyg activation during FE following SR than those with NS [d (95%CI) = 0.87 (0.37,1.78)]. SR > NS participants were more likely to be female, white, l/l genotype carriers, and have a psychiatric history. They had less sleep (overall and in REM), lower REM density, and lower spindle activity (12-16 Hz). Applying OCMs to randomized studies with neural outcomes can clarify neural heterogeneity and jumpstart mechanistic research; with further validation they also offer promise for personalized brain-based treatments and interventions.

Less is more: Patient-level meta-analysis reveals paradoxical dose-response effects of a computer-based social anxiety intervention targeting attentional bias.

BACKGROUND: The past decade of research has seen considerable interest in computer-based approaches designed to directly target cognitive mechanisms of anxiety, such as attention bias modification (ABM). METHODS: By pooling patient-level datasets from randomized controlled trials of ABM that utilized a dot-probe training procedure, we assessed the impact of training "dose" on relevant outcomes among a pooled sample of 693 socially anxious adults. RESULTS: A paradoxical effect of the number of training trials administered was observed for both posttraining social anxiety symptoms and behavioral attentional bias (AB) toward threat (the target mechanism of ABM). Studies administering a large (>1,280) number of training trials showed no benefit of ABM over control conditions, while those administering fewer training trials showed significant benefit for ABM in reducing social anxiety (P = .02). These moderating effects of dose were not better explained by other examined variables and previously identified moderators, including patient age, training setting (laboratory vs. home), or type of anxiety assessment (clinician vs. self-report). CONCLUSIONS: Findings inform the optimal dosing for future dot-probe style ABM applications in both research and clinical settings, and suggest several novel avenues for further research.