The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students.

Introduction: Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. In this study, we use wearable devices to understand how the shape of the heart rate curve during sleep relates to mental health. Methods: As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the USA during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached. Results: Sleep periods characterized by reaching the lowest heart rate later during sleep are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females. Conclusion: Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health.

The Cyborg Method: A Method to Identify Fraudulent Responses from Crowdsourced Data.

Crowdsourcing is an essential data collection method for psychological research. Concerns about the validity and quality of crowdsourced data persist, however. A recent documented increase in the number of invalid responses within crowdsourced data has highlighted the need for quality control measures. Although a number of approaches are recommended, few have been empirically evaluated. The present study evaluated a Cyborg Method that used automated evaluation of participant meta-data and a review of short answer responses. Two samples were recruited - in the first, the Cyborg Method was applied after data collection to gauge the extent to which invalid responses were collected when a priori quality controls were absent. In the second, the Cyborg Method was applied during data collection to determine if the method would proactively screen invalid responses. Results suggested that Cyborg Method identified a substantial portion of invalid responses and both automated and human evaluation components was necessary. Furthermore, the Cyborg Method could be applied proactively to screen invalid responses and substantially reduced the per participant cost of data collection. These results suggest that the Cyborg Method is a promising means by which to collect high quality crowdsourced data.

Mapping PTSD, depression, and anxiety: A network analysis of co-occurring symptoms in treatment-seeking first responders.

First responders are at high risk for a range of co-occurring mental health conditions due to their repeated exposure to traumatic events. When first responders present for treatment, their complex presentation of symptoms including posttraumatic stress disorder (PTSD), depression, and generalized anxiety disorder (GAD) can prove challenging to differentiate for clinical purposes. Network analysis provides a means to identify the nuanced associations between the symptoms of these conditions and to identify groups of related symptoms. In this study, a treatment-seeking sample of first responders (N = 432) completed self-report measures of PTSD, depression, and GAD. Network analysis was used to identify symptom clusters within the sample. Our cross-sectional data yielded six empirically distinct communities: depression symptoms, GAD symptoms, and four communities comprising PTSD symptoms - intrusion and avoidance; irritability and aggression; negative affect; and arousal and sleep. Network associations underscore the heterogeneity of PTSD and also highlight overlapping and diverging symptoms of depression and GAD. These findings are discussed within the context of existing research on first responders, and recommendations for further study and treatment interventions are provided.

A large clinical trial to improve well-being during the transition to college using wearables: The lived experiences measured using rings study.

INTRODUCTION: The transition to college is a period of elevated risk for a range of mental health conditions. Although colleges and universities strive to provide mental health support to their students, the high demand for these services makes it difficult to provide scalable, cost-effective solutions. OBJECTIVE: To address these issues, the present study aims to compare the efficacy of three different treatments using a large cohort of 600 students transitioning to college. Interventions were selected based on their potential for generalizability and cost-effectiveness on college campuses. METHODS: The study is a Phase II parallel-group, four-arm, randomized controlled trial with 1:1 allocation that will assign 600 participants to one (n = 150 per condition) of four arms: 1) group-based therapy, 2) physical activity program, 3) nature experiences, or 4) weekly assessment condition as a control group. Physiological data will be collected from all participants using a wearable device to develop algorithmic mental and physical health functioning predictions. Once recruitment is complete, modeling strategies will be used to evaluate the outcomes and effectiveness of each intervention. DISCUSSION: The findings of this study will provide evidence as to the benefits of implementing scalable and proactive interventions using technology with the goal of improving the well-being and success of new college students.

Assessment of Traumatic Stress Symptoms During the Acute Posttrauma Period.

A substantial majority of adults in the United States will experience a potentially traumatic event (PTE) in their lifetime. A considerable proportion of those individuals will go on to develop posttraumatic stress disorder (PTSD). Distinguishing between those who will develop PTSD and those who will recover, however, remains as a challenge to the field. Recent work has pointed to the increased potential of identifying individuals at greatest risk for PTSD through repeated assessment during the acute posttrauma period, the 30-day period after the PTE. Obtaining the necessary data during this period, however, has proven to be a challenge. Technological innovations such as personal mobile devices and wearable passive sensors have given the field new tools to capture nuanced in vivo changes indicative of recovery or nonrecovery. Despite their potential, there are numerous points for clinicians and research teams to consider when implementing these technologies into acute posttrauma care. The limitations of this work and considerations for future research in the use of technology during the acute posttrauma period are discussed.

Linkages Between Childhood Maltreatment, Intimate Partner Violence, and Posttraumatic Stress Disorder Symptoms in Pregnant Hispanic Women: A Network Analysis.

Pregnant Hispanic women are at increased risk for posttraumatic stress disorder (PTSD) in part due to greater risk of childhood maltreatment, intimate partner violence (IPV), and pregnancy-related vulnerabilities. However, PTSD, is a highly heterogenous diagnosis with numerous presentations. Individual PTSD symptoms may be differentially associated with specific types of maltreatment, IPV. Determining how IPV exposure across the lifespan is associated with specific symptoms of PTSD in pregnant Hispanic women is necessary to develop group-relevant models of this disorder and targeted interventions. The present study examined a network model of PTSD symptoms, childhood maltreatment, and adulthood IPV in a sample of pregnant Hispanic women (N = 198). Childhood emotional abuse and adulthood psychological distress had the highest bridge centrality. These types of exposures were most strongly associated with social isolation. Childhood emotional abuse was associated with more individual PTSD symptoms than any IPV type. These findings suggest that associations between PTSD symptoms and different types of IPV exposure vary. In addition, robust associations between childhood emotional abuse and PTSD symptoms suggest that this domain may be particularly important for the clinical assessment and intervention for pregnant women.

Proactive Electronic Visits for Smoking Cessation and Chronic Obstructive Pulmonary Disease Screening in Primary Care: Randomized Controlled Trial of Feasibility, Acceptability, and Efficacy.

BACKGROUND: Most smokers with chronic obstructive pulmonary disease (COPD) have not yet been diagnosed, a statistic that has remained unchanged for over two decades. A dual-focused telehealth intervention that promotes smoking cessation, while also facilitating COPD screening, could help address national priorities to improve the diagnosis, prevention, treatment, and management of COPD. The purpose of this study was to preliminarily evaluate an integrated asynchronous smoking cessation and COPD screening e-visit (electronic visit) that could be delivered proactively to adult smokers at risk for COPD, who are treated within primary care. OBJECTIVE: The aims of this study were (1) to examine e-visit feasibility and acceptability, particularly as compared to in-lab diagnostic pulmonary function testing (PFT), and (2) to examine the efficacy of smoking cessation e-visits relative to treatment as usual (TAU), all within primary care. METHODS: In a randomized clinical trial, 125 primary care patients who smoke were randomized 2:1 to receive either proactive e-visits or TAU. Participants randomized to the e-visit condition were screened for COPD symptoms via the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE). Those with scores ≥2 were invited to complete both home spirometry and in-lab PFTs, in addition to two smoking cessation e-visits. Smoking cessation e-visits assessed smoking history and motivation to quit and included completion of an algorithm to determine the best Food and Drug Administration-approved cessation medication to prescribe. Primary outcomes included measures related to (1) e-visit acceptability, feasibility, and treatment metrics; (2) smoking cessation outcomes (cessation medication use, 24-hour quit attempts, smoking reduction ≥50%, self-reported abstinence, and biochemically confirmed abstinence); and (3) COPD screening outcomes. RESULTS: Of 85 participants assigned to the e-visits, 64 (75.3%) were invited to complete home spirometry and in-lab PFTs based on CAPTURE. Among those eligible for spirometry, 76.6% (49/64) completed home spirometry, and 35.9% (23/64) completed in-lab PFTs. At 1 month, all cessation outcomes favored the e-visit, with a significant effect for cessation medication use (odds ratio [OR]=3.22). At 3 months, all cessation outcomes except for 24-hour quit attempts favored the e-visit, with significant effects for cessation medication use (OR=3.96) and smoking reduction (OR=3.09). CONCLUSIONS: A proactive, asynchronous e-visit for smoking cessation and COPD screening may offer a feasible, efficacious approach for broad interventions within primary care. TRIAL REGISTRATION: ClinicalTrials.gov NCT04155073; https://clinicaltrials.gov/ct2/show/NCT04155073.