Treatment for Anxiety and Comorbid Depressive Disorders: Transdiagnostic Cognitive-Behavioral Strategies.

Anxiety and depressive disorders are common psychiatric conditions with high rates of co-occurrence. Although traditional cognitive-behavioral therapy (CBT) protocols targeting individual anxiety and depressive disorder diagnoses have been shown to be effective, such "single-diagnosis" approaches pose challenges for providers who treat patients with multiple comorbidities and for large-scale dissemination of and training in evidence-based psychological treatments. To help meet this need, newer "transdiagnostic" CBT interventions targeting shared underlying features across anxiety, depressive, and related disorders have been developed in recent years. Here we provide a rationale for and description of the transdiagnostic CBT model, followed by an overview of key therapeutic strategies included in transdiagnostic CBT protocols for patients with anxiety disorders and comorbid depression. We conclude with a brief review of the empirical evidence in support of transdiagnostic CBT for individuals with anxiety and depressive disorders and identify directions for future research.

Ethical dilemmas posed by mobile health and machine learning in psychiatry research.

The application of digital technology to psychiatry research is rapidly leading to new discoveries and capabilities in the field of mobile health. However, the increase in opportunities to passively collect vast amounts of detailed information on study participants coupled with advances in statistical techniques that enable machine learning models to process such information has raised novel ethical dilemmas regarding researchers' duties to: (i) monitor adverse events and intervene accordingly; (ii) obtain fully informed, voluntary consent; (iii) protect the privacy of participants; and (iv) increase the transparency of powerful, machine learning models to ensure they can be applied ethically and fairly in psychiatric care. This review highlights emerging ethical challenges and unresolved ethical questions in mobile health research and provides recommendations on how mobile health researchers can address these issues in practice. Ultimately, the hope is that this review will facilitate continued discussion on how to achieve best practice in mobile health research within psychiatry.

L'application des technologies numériques à la recherche psychiatrique entraîne rapidement de nouvelles découvertes et capacités en matière de santé mobile. Cependant, la multiplication des opportunités de recueillir passivement d'immenses quantités d'informations détaillées sur les participants aux études combinée aux progrès des techniques statistiques permettant aux modèles d'apprentissage automatique de traiter de telles informations a soulevé de nouveaux dilemmes éthiques concernant l'obligation des chercheurs: (i) de surveiller les effets indésirables et d'intervenir en conséquence; (ii) d'obtenir un consentement pleinement éclairé et volontaire; (iii) de protéger la vie privée des participants; et enfin, (iv) d'améliorer la transparence des puissants modèles d'apprentissage automatique afin de garantir une application éthique et impartiale dans le domaine des soins psychiatriques. Ce rapport identifie les défis qui en découlent ainsi que les questions éthiques non résolues en matière de santé mobile. Il formule également des recommandations sur la façon dont les chercheurs en santé mobile peuvent résoudre ces problèmes dans la pratique. À terme, nous espérons que ce rapport favorisera la poursuite des discussions portant sur les moyens de définir des méthodes de recherche adéquates pour la santé mobile en psychiatrie.

La aplicación de la tecnología digital a la investigación en psiquiatría está conduciendo rápidamente a descubrimientos y capacidades nuevas en el ámbito de la salud móvil. No obstante, el incremento de las oportunidades para recopilar pasivamente grandes volúmenes de información detallada sobre los participantes en los estudios, junto con los avances en las técnicas de estadística que permiten a los modelos de aprendizaje automático procesar tal información, ha planteado nuevos dilemas éticos relativos a los deberes de los investigadores: (i) hacer un seguimiento de los eventos adversos e intervenir en consecuencia; (ii) obtener un consentimiento voluntario plenamente informado; (iii) proteger la privacidad de los participantes; y (iv) aumentar la transparencia de los modelos potentes de aprendizaje automático para asegurar que puedan aplicarse de manera ética y justa en la atención psiquiátrica. En este análisis se destacan tanto los desafíos éticos nuevos como las cuestiones éticas aún sin resolver en la investigación sobre la salud móvil y se formulan recomendaciones sobre cómo los investigadores de la salud móvil pueden abordar dichas cuestiones en la práctica. En última instancia, se espera que este análisis facilite un debate continuo sobre cómo lograr las mejores prácticas en la investigación de la salud móvil dentro de la psiquiatría.

A Preliminary Examination of the Effects of Transdiagnostic Versus Single Diagnosis Protocols on Anger During the Treatment of Anxiety Disorders.

Dysregulated anger is often present in the emotional (i.e., anxiety, mood, and related) disorders; however, it is rarely targeted in treatment. Transdiagnostic treatments, which focus on processes that contribute to dysregulated emotions across the range of psychopathology, might represent an efficient way to treat this anger. Using a subset of data from a recently completed equivalency trial comparing the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP) to single diagnosis protocols (SDPs) for specific disorders, this study began exploring whether the UP led to great reductions in anger compared with the SDPs. Results indicated that there was a small, nonsignificant, decrease in anger in the UP condition, whereas there was a moderate, nonsignificant increase in anger in the SDP condition. At posttreatment, UP patients had significantly lower anger scores than patients who received an SDP. These preliminary results suggest that transdiagnostic treatments may be well poised to target dyregulated anger in the context of emotional disorders.

Applying the Unified Protocol Transdiagnostic Treatment to Nonsuicidal Self-Injury and Co-Occurring Emotional Disorders: A Case Illustration.

This article presents the use of a transdiagnostic, emotion-focused treatment with a young woman with nonsuicidal self-injury (NSSI), social anxiety disorder, and generalized anxiety disorder. The patient also presented with subclinical depressive, posttraumatic stress, and eating disorder symptoms. The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (Barlow et al., 2011), a cognitive-behavioral intervention designed to be applicable across anxiety, depressive, and related disorders with strong emotional components, was used to address the range of Laura's presenting concerns. After 16 individual treatment sessions, Laura experienced significant reductions in NSSI (and urges to engage in NSSI) as well as observable improvements in her self-reported ability to respond more adaptively to intense emotion. She also reported moderate reductions in her anxiety disorder symptoms. This case illustration demonstrates how a short-term, transdiagnostic treatment approach can be flexibly applied to a variety of problems maintained by aversive and avoidant reactions to intense emotion.

A preliminary investigation of the effects of the unified protocol on temperament.

Previous research has shown that two dimensions of temperament referred to as neuroticism/behavioral inhibition (N/BI) and extraversion/behavioral activation (E/BA) are key risk factors in the development and maintenance of anxiety and mood disorders (Brown & Barlow, 2009). Given such findings, these temperamental dimensions may represent promising treatment targets for individuals with emotional disorders; however, to date, few studies have investigated the effects of psychological treatments on temperamental constructs generally assumed to be "stable, inflexible, and pervasive" (American Psychiatric Association, 2000). The present study addresses this gap in the literature by examining the effects of the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP; Barlow et al., 2011), a cognitive-behavioral therapy designed to target core processes of N/BI and E/BA temperaments, in a sample of adults with principal anxiety disorders and a range of comorbid conditions. Results revealed small effects of the UP on N/BI and E/BA compared with a waitlist control group at post-treatment. Additionally, decreases in N/BI and increases in E/BA during treatment were associated with improvements in symptoms, functioning, and quality of life. Findings provide preliminary support for the notion that the UP treatment facilitates beneficial changes in dimensions of temperament.

A roadmap to address stress in graduate students: How to develop and disseminate a student-led single-session evidence based intervention.

Objective: This manuscript describes an evidence-based, student-led, single-session group intervention to support emotional wellbeing among graduate students. The present objective is to provide a roadmap for other universities. Participants: Key participants include clinical psychology graduate students (leader and workshop facilitators), faculty supervisor, representatives from receiving departments or schools, and institutional advocates. Methods: The two-hour workshop was based on four core transdiagnostic cognitive behavioral skills, including psychoeducation about emotions, mindful emotional awareness, cognitive flexibility, and behavior change. The workshop was designed and continues to be led by trained graduate students. Results: Key steps and lessons learned are presented for the exploration, preparation, implementation, and sustainment phases. Conclusions: This program has the potential to be flexibly replicated at other universities to assist with graduate student mental health. It provides unique supports for recipients and unique training opportunities for student facilitators.

Determining Distinct Suicide Attempts From Recurrent Electronic Health Record Codes: Classification Study.

BACKGROUND: Prior suicide attempts are a relatively strong risk factor for future suicide attempts. There is growing interest in using longitudinal electronic health record (EHR) data to derive statistical risk prediction models for future suicide attempts and other suicidal behavior outcomes. However, model performance may be inflated by a largely unrecognized form of "data leakage" during model training: diagnostic codes for suicide attempt outcomes may refer to prior attempts that are also included in the model as predictors. OBJECTIVE: We aimed to develop an automated rule for determining when documented suicide attempt diagnostic codes identify distinct suicide attempt events. METHODS: From a large health care system's EHR, we randomly sampled suicide attempt codes for 300 patients with at least one pair of suicide attempt codes documented at least one but no more than 90 days apart. Supervised chart reviewers assigned the clinical settings (ie, emergency department [ED] versus non-ED), methods of suicide attempt, and intercode interval (number of days). The probability (or positive predictive value) that the second suicide attempt code in a given pair of codes referred to a distinct suicide attempt event from its preceding suicide attempt code was calculated by clinical setting, method, and intercode interval. RESULTS: Of 1015 code pairs reviewed, 835 (82.3%) were nonindependent (ie, the 2 codes referred to the same suicide attempt event). When the second code in a pair was documented in a clinical setting other than the ED, it represented a distinct suicide attempt 3.3% of the time. The more time elapsed between codes, the more likely the second code in a pair referred to a distinct suicide attempt event from its preceding code. Code pairs in which the second suicide attempt code was assigned in an ED at least 5 days after its preceding suicide attempt code had a positive predictive value of 0.90. CONCLUSIONS: EHR-based suicide risk prediction models that include International Classification of Diseases codes for prior suicide attempts as a predictor may be highly susceptible to bias due to data leakage in model training. We derived a simple rule to distinguish codes that reflect new, independent suicide attempts: suicide attempt codes documented in an ED setting at least 5 days after a preceding suicide attempt code can be confidently treated as new events in EHR-based suicide risk prediction models. This rule has the potential to minimize upward bias in model performance when prior suicide attempts are included as predictors in EHR-based suicide risk prediction models.

Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone App-Led Cognitive Behavioral Therapy for Depression Under Therapist Supervision: Open Trial.

BACKGROUND: Major depressive disorder affects approximately 1 in 5 adults during their lifetime and is the leading cause of disability worldwide. Yet, a minority receive adequate treatment due to person-level (eg, geographical distance to providers) and systems-level (eg, shortage of trained providers) barriers. Digital tools could improve this treatment gap by reducing the time and frequency of therapy sessions needed for effective treatment through the provision of flexible, automated support. OBJECTIVE: This study aimed to examine the feasibility, acceptability, and preliminary clinical effect of Mindset for Depression, a deployment-ready 8-week smartphone-based cognitive behavioral therapy (CBT) supported by brief teletherapy appointments with a therapist. METHODS: This 8-week, single-arm open trial tested the Mindset for Depression app when combined with 8 brief (16-25 minutes) video conferencing visits with a licensed doctoral-level CBT therapist (n=28 participants). The app offers flexible, accessible psychoeducation, CBT skills practice, and support to patients as well as clinician guidance to promote sustained engagement, monitor safety, and tailor treatment to individual patient needs. To increase accessibility and thus generalizability, all study procedures were conducted remotely. Feasibility and acceptability were assessed via attrition, patient expectations and feedback, and treatment utilization. The primary clinical outcome measure was the clinician-rated Hamilton Depression Rating Scale, administered at pretreatment, midpoint, and posttreatment. Secondary measures of functional impairment and quality of life as well as maintenance of gains (3-month follow-up) were also collected. RESULTS: Treatment credibility (week 4), expectancy (week 4), and satisfaction (week 8) were moderate to high, and attrition was low (n=2, 7%). Participants self-reported using the app or practicing (either on or off the app) the CBT skills taught in the app for a median of 50 (IQR 30-60; week 4) or 60 (IQR 30-90; week 8) minutes per week; participants accessed the app on an average 36.8 (SD 10.0) days and completed a median of 7 of 8 (IQR 6-8) steps by the week 8 assessment. The app was rated positively across domains of engagement, functionality, aesthetics, and information. Participants' depression severity scores decreased from an average Hamilton Depression Rating Scale score indicating moderate depression (mean 19.1, SD 5.0) at baseline to a week 8 mean score indicating mild depression (mean 10.8, SD 6.1; d=1.47; P<.001). Improvement was also observed for functional impairment and quality of life. Gains were maintained at 3-month follow-up. CONCLUSIONS: The results show that Mindset for Depression is a feasible and acceptable treatment option for individuals with major depressive disorder. This smartphone-led treatment holds promise to be an efficacious, scalable, and cost-effective treatment option. The next steps include testing Mindset for Depression in a fully powered randomized controlled trial and real-world clinical settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329.

Intervening on high-risk responses during ecological momentary assessment of suicidal thoughts: Is there an effect on study data?

Ecological momentary assessment (EMA) is increasingly used to study suicidal thoughts and behaviors (STBs). There is a potential ethical obligation for researchers to intervene when receiving information about suicidal thoughts in real time. A possible concern, however, is that intervening when receiving responses that indicate high risk for suicide during EMA research may impact how participants respond to questions about suicidal thoughts and thus affect the validity and integrity of collected data. We leveraged data from a study of adults and adolescents (N = 434) recruited during a hospital visit for STBs to examine whether monitoring and intervening on high-risk responses affects subsequent participant responding. Overall, we found mixed support for the notion that intervening on high-risk responses influences participants' ratings. Although we observed some evidence of discontinuity in subsequent responses at the threshold used to trigger response-contingent interventions, it was not clear that such discontinuity was caused by the interventions; lower subsequent responses could be due to effective intervention, participant desire to not be contacted again, or regression to the mean. Importantly, the likelihood of completing surveys did not change from before to after response-contingent intervention. Adolescents were significantly more likely than adults, however, to change their initial suicidal intent ratings from above to below the high-risk threshold after viewing automated response-contingent pop-up messages. Studies explicitly designed to assess the potential impact of intervening on high-risk responses in real-time monitoring research are needed, as this will inform effective, scalable strategies for intervening during moments of high suicide risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Heterogeneity in suicide risk: Evidence from personalized dynamic models.

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

Helpful for all? Examining the effects of psychotherapy treatment history on outcomes of single session, transdiagnostic cognitive behavioral interventions for university students.

Brief, transdiagnostic interventions are an efficient form of mental health care for resource-limited settings like universities. Little research, however, has examined for whom these treatments are most effective. One important factor may be psychotherapy treatment history. Here, we evaluate if treatment history influences the effects of a single-session cognitive behavioral group intervention with optional digital follow-up support across two independent, university-based studies. Undergraduate (N = 143) and graduate (N = 51) students reported their psychotherapy treatment history and completed self-report measures of emotional health before and approximately 1-month following the intervention. Across both samples, psychotherapy treatment history did not moderate changes in depression, anxiety, or emotional avoidance following the intervention. However, participants who were currently receiving psychotherapy began the workshop with lower coping self-efficacy than peers with no prior psychotherapy and saw larger gains in coping self-efficacy at follow-up. Results suggest that regardless of whether a student has previously received psychotherapy, they may benefit from brief, group transdiagnostic interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Latent Profile Analysis of Urges for Suicidal and Self-Harming Behavior: The Role of Social Support Instability.

College counseling centers are seeing increasing rates of suicidal thoughts and behaviors, and nonsuicidal self-injury (NSSI) among students. The high degree of need and limited resources underscores the need for novel approaches to identify at-risk students. We used latent profile analysis (LPA) to identify subgroups of students (n = 371) with different patterns of interpersonal factors and examine whether these subgroups differed by risk for self-injurious thoughts and behaviors. The best-fitting LPA had three profiles, which differed in urges to die by suicide and engage in NSSI. The profile with low average social support and higher instability (greater day-to-day fluctuations of self-reported social support and rejection) was associated with greatest risk, suggesting that this combination leaves individuals more vulnerable to suicide and NSSI.

Suicidal thinking as affect regulation.

Nine percent of people worldwide report thinking about suicide at some point during their lives. A fundamental question we currently lack a clear answer to is: why do suicidal thoughts persist over time? One possibility is that suicidal thoughts serve adaptive functions for people who experience them. We tested whether suicidal thinking may serve as a form of affect regulation. In a real-time monitoring study among adults with recent suicidal thoughts (N = 105), we found that participants often endorsed using suicidal thinking as a form of affect regulation. The occurrence of suicidal thinking was followed by decreased negative affect. However, when assessing the direction of the relationship between suicidal thinking and negative affect, we also found positive bidirectional associations between them. Finally, using suicidal thinking as a form of affect regulation predicted the frequency and severity of suicidal thinking at later time points. These findings may help explain the persistence of suicidal thoughts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Real-time digital monitoring of a suicide attempt by a hospital patient.

Suicide is among the most devastating problems facing clinicians, who currently have limited tools to predict and prevent suicidal behavior. Here we report on real-time, continuous smartphone and sensor data collected before, during, and after a suicide attempt made by a patient during a psychiatric inpatient hospitalization. We observed elevated and persistent sympathetic nervous system arousal and suicidal thinking leading up to the suicide attempt. This case provides the highest resolution data to date on the psychological, psychophysiological, and behavioral markers of imminent suicidal behavior and highlights new directions for prediction and prevention efforts.

A randomized, controlled, pilot study of acamprosate added to escitalopram in adults with major depressive disorder and alcohol use disorder.

We sought to examine the efficacy and safety of acamprosate augmentation of escitalopram in patients with concurrent major depressive disorder (MDD) and alcohol use disorders. Twenty-three adults (43% female; mean ± SD age, 46 ± 14 years) were enrolled and received 12 weeks of treatment with psychosocial support; escitalopram, 10 to 30 mg/d; and either acamprosate, 2000 mg/d (n = 12), or identical placebo (n = 11). Outcomes included change in clinician ratings of depressive symptoms, MDD response and remission rates, changes in frequency and intensity of alcohol use, retention rates, and adverse events. Twelve subjects (acamprosate, n = 7; placebo, n = 5) completed the study. There was significant mean reduction in ratings of depressive symptoms from baseline in both treatment arms (P < 0.05), with no significant difference between the groups. Those in the acamprosate group had a 50% MDD response rate and a 42% remission rate, whereas those in the placebo arm had a 36% response and remission rate (not significant). Those assigned to acamprosate had significant reduction in number of drinks per week and drinks per month during the trial, whereas those assigned to placebo demonstrated no significant change in any alcohol use parameter, but the between-group difference was not significant. There were no significant associations between change in depressive symptoms and change in alcohol use. Attrition rates did not differ significantly between the 2 arms. Acamprosate added to escitalopram in adults with MDD and alcohol use disorders was associated with reduction in the frequency of alcohol use. The present study was not powered to detect superiority versus placebo. Further study in a larger sample is warranted.

The absence of depressive symptoms is not the presence of wellness: validation of the Clinical Positive Affect Scale.

OBJECTIVE: Many patients with depression respond or remit with current treatments, but often experience persistent distress, in part because they perceive that they have not returned to their normal or premorbid state. Some continue to have a lack of subjective psychological well-being and positive affect following treatment. It would be useful to measure these deficits and explore whether interventions can improve them. Currently, no clinically useful scale has been developed to measure positive affect. To fill this gap, we developed the Clinical Positive Affect Scale (CPAS). METHOD: The purpose of this study is to describe the development and validation of the CPAS, a 16-item self-report measurement of self-perceived affective and cognitive correlates of positive affect, in a sample of 300 college students. RESULTS: A principal component analysis with varimax rotation showed one major factor of positive affect, with all items revealing high loadings (≥ 0.65) on the single factor. The CPAS also demonstrated good internal consistency (α = 0.97) and strong part-whole correlations. Finally, the CPAS revealed some degree of divergent validity through moderately strong negative correlations with validated measures of depression, anxiety and drug abuse. CONCLUSIONS: This study supports the validity of the CPAS, which may help clinicians and researchers to assess patients' current self-perceived levels of hedonic capacity and enthusiasm for life.

The Effectiveness of a Brief Telehealth and Smartphone Intervention for College Students Receiving Traditional Therapy: Longitudinal Study Using Ecological Momentary Assessment Data.

BACKGROUND: Brief interventions such as mental health apps and single-session interventions are increasingly popular, efficacious, and accessible delivery formats that may be beneficial for college students whose mental health needs may not be adequately met by college counseling centers. However, no studies so far have examined the effectiveness of these modes of treatment for college students who are already receiving traditional therapy, despite it being common among this population. OBJECTIVE: The aim of this study was to compare the differences in self-reported momentary negative affect between college students in therapy and not in therapy who received a brief single-session intervention delivered by counseling center staff and a supplemental mobile app. METHODS: Data for this study were drawn from E-Manage, a brief mobile health intervention geared toward college students. Participants in the study were 173 college students who indicated whether they had received therapy. We conducted a multilevel model to determine whether there were differences between those in therapy versus not in therapy in negative affect reported throughout the study. Following this, we conducted multilevel models with therapy status as the predictor and negative affect as the outcome. RESULTS: Results of the multilevel model testing showed that the cross-level interaction between the time point (ie, pre- vs postexercise) and therapy status was significant (P=.008), with the reduction in negative affect from pre- to postexercise greater for those in therapy (b=-0.65, 95% CI -0.91 to -0.40; P<.001) than it was for those not in therapy (b=-0.31, 95% CI -0.43 to -0.19; P<.001). Therapy status was unassociated with both the pre-exercise (b=-1.69, 95% CI -3.51 to 0.13; P=.07) and postexercise (b=-1.37, 95% CI -3.17 to 0.43; P=.14) ratings of negative affect. CONCLUSIONS: These findings suggest that app-based and single-session interventions are also appropriate to use among college students who are receiving traditional therapy. A randomized controlled trial comparing students receiving therapy to students receiving therapy and E-Manage will be necessary to determine to what extent E-Manage contributed to the reductions in negative affect that therapy-attending college students experienced.

Aggregating heart rate variability indices across sleep stage epochs ignores significant variance through the night.

BACKGROUND: Heart rate variability (HRV) is a widely utilized biomarker of autonomic regulatory functioning, and concomitant health and pathological states. A growing body of work is exploring HRV under sleeping conditions. Most of this literature utilizes either averaged HRV indices calculated from multiple sleep stage epochs, or averaged HRV throughout the night. Both approaches implicitly assume that HRV within sleep epoch types is consistent throughout the night. Given the robust literature indicating the existence of an endogenous cardiovascular circadian rhythm as well as the potential for effects for cumulative time asleep, we hypothesized that HRV would vary across distinct sleep epochs. METHODS: Participants underwent at least one night of home polysomnography that included electroencephalogram, electromyogram, and electrocardiogram (N = 73). All rapid eye movement (REM) and non-REM stage 2 (N2) sleep epochs with a duration greater than or equal to 5 min were identified for HRV analysis. Time and frequency domain indices of HRV were calculated for each sleep stage epoch. Linear mixed models were used to examine main effects of time on HRV indices for N2 and REM sleeps epochs respectively. RESULTS: Main effects of time were observed for all models. Patterns emerged for both the N2 and REM epochs, suggesting HRV indices are non-stationary (ie variable) across distinct sleep epochs through the course of the night. CONCLUSIONS: The present findings indicate HRV is non-stationary across sleep stage epochs. Aggregating HRV indices across sleep stage epochs likely obscures important transient effects and increases risk of type-I and type-II errors.

Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions.

The suicide rate (currently 14 per 100,000) has barely changed in the United States over the past 100 years. There is a need for new ways of preventing suicide. Further, research has revealed that suicidal thoughts and behaviors and the factors that drive them are dynamic, heterogeneous, and interactive. Most existing interventions for suicidal thoughts and behaviors are infrequent, not accessible when most needed, and not systematically tailored to the person using their own data (e.g., from their own smartphone). Advances in technology offer an opportunity to develop new interventions that may better match the dynamic, heterogeneous, and interactive nature of suicidal thoughts and behaviors. Just-In-Time Adaptive Interventions (JITAIs), which use smartphones and wearables, are designed to provide the right type of support at the right time by adapting to changes in internal states and external contexts, offering a promising pathway toward more effective suicide prevention. In this review, we highlight the potential of JITAIs for suicide prevention, challenges ahead (e.g., measurement, ethics), and possible solutions to these challenges.

An Ecological Momentary Intervention Study of Emotional Responses to Smartphone-Prompted CBT Skills Practice and the Relationship to Clinical Outcomes.

The practice of therapeutic skills outside of sessions in which they are learned is one presumed key component of cognitive behavioral therapy (CBT). Yet, our understanding of how skills practice relates to clinical outcomes remains limited. Here, we explored patients' emotional responses to CBT skills practice in a pilot study pairing smartphone-app-delivered skills reminders and guided practice (ecological momentary intervention [EMI]) using ecological momentary assessment (EMA). Participants (n = 25) were adults recently hospitalized for a suicide attempt or severe suicidal thinking. They received brief inpatient CBT (1 to 3 sessions covering core CBT skills from the Unified Protocol), followed by 1 month of EMI and EMA after discharge. On average, participants reported modest reductions in negative affect after skills use (i.e., immediate responses; median time elapsed = 4.30 minutes). Additionally, participants tended to report less negative affect when the timepoint preceding the current assessment included EMI skills practice, rather than EMA alone (i.e., delayed responses; median time elapsed between prompts = 2.17 hours). Immediate effects were unrelated to longer-term clinical outcomes, whereas greater delayed effects were associated with lower symptom severity at follow-up. Future studies should further examine how CBT skills use in daily life may alleviate symptoms.