Investigating cognitive and motivational proximal outcomes in a randomized clinical trial of writing about the future self to reduce drinking.

BACKGROUND: Drinking identity (the extent to which one links the self with drinking alcohol) is a unique risk factor for college students' hazardous drinking that is not directly targeted by existing interventions. We conducted a study that aimed to decrease drinking identity among college students with hazardous drinking. We adapted a writing task about the future self and tested whether three writing sessions could decrease drinking identity and change drinking. We also investigated whether two additional factors (writing perspective and inclusion of participants' social networks) would enhance task impact. The present study evaluated whether posited proximal cognitive and motivational outcomes (drinking identity, self-efficacy, readiness to change, and drinking intentions) changed immediately after each writing session. METHOD: The study is a randomized clinical trial in which hypotheses and analyses were pre-registered. Participants were 328 college students who met hazardous drinking criteria. The study had a 2 (narrative writing topic: low-risk drinker vs. reduced smartphone use) × 2 (writing perspective: first-person vs. non-first-person) × 2 (social network instruction: instructed to include vs. not) factorial design. Proximal outcomes were drinking identity, self-efficacy, readiness to change, and drinking intentions. The clinical outcome was alcohol consumption. Participants completed three laboratory sessions at weekly intervals that included the writing task and pre- and post-task assessments. RESULTS: Results were largely null, except that readiness to reduce drinking was higher in the low-risk drinker condition and increased over the lab sessions. Time effects indicated that reductions in drinking identity, drinking intentions, and alcohol consumption, and increases in self-efficacy were observed but did not change above and beyond control conditions. CONCLUSIONS: Findings indicate the need to strengthen the writing task and select a more appropriate control task to target proposed proximal outcomes. Future studies might try personalizing the task, evaluating its efficacy with individuals motivated to change their drinking, and using a control task that does not involve imagining a future self.

Evaluating distress as a moderator of the relationship between drinking identity and hazardous drinking during the post-college transition.

Drinking identity (the extent to which one associates the self with drinking alcohol) is a robust predictor of young adult hazardous drinking (HD; heavy drinking and alcohol-related problems), and decreases in drinking identity have been linked to the decline in HD that often occurs following college graduation. Identifying moderators is key to recognizing who is most at risk for continued HD given a drinking identity vulnerability. Using data from a longitudinal study of graduating college students from the U.S., we evaluated distress (depression, anxiety, stress symptoms) as a potential moderator. Between- and within-person components of drinking identity and distress were evaluated to consider both individual differences and variations within a person across time and changing contexts. Study hypotheses and data analysis plan were preregistered. Graduating college students who met HD criteria (N = 422) completed implicit and explicit drinking identity measures (assessed using reaction time and self-report measures, respectively), distress symptom questionnaires, and self-reported alcohol consumption and problems at four-month intervals for 2.5 years. Results supported moderation at the between-person level for alcohol consumption, with higher levels of implicit drinking identity and distress linked to greater subsequent alcohol consumption. Only between-person main effects for (explicit) identity and distress were linked to more subsequent alcohol-related problems. Though moderation findings were mixed, having a stronger drinking identity and/or greater distress was linked to continued HD risk in this sample. Individuals with these risk factors may benefit from enhanced prevention efforts to help graduates transition out of HD post-college.

Online cognitive bias modification for interpretation to reduce anxious thinking during the COVID-19 pandemic.

Anxiety disorders are highly prevalent, and rates increased during the COVID-19 pandemic. However, most individuals with elevated anxiety do not access treatment due to barriers such as stigma, cost, and availability. Digital mental health programs, such as cognitive bias modification for interpretation (CBM-I), hold promise in increasing access to care. Before widely disseminating CBM-I, we must rigorously test its effectiveness and determine whom it is best positioned to benefit. The present study (which is a substudy of a parent trial) compared CBM-I against psychoeducation offered through the public website MindTrails, and also tested whether baseline anxiety tied to COVID-19 influenced the rate of change in anxiety and interpretation bias during and after each intervention. Adults with moderate-to-severe anxiety symptoms were randomly assigned to complete five sessions of either CBM-I or psychoeducation as part of a larger trial, and 608 enrolled in this substudy after Session 1. As predicted (https://osf.io/2dyzr), CBM-I was superior to psychoeducation at reducing anxiety symptoms (on the OASIS but not the DASS-21-AS: d = -0.31), reducing negative interpretation bias (d range = -0.34 to -0.43), and increasing positive interpretation bias (d = 0.79) by the end of treatment. Results also indicated that individuals higher (vs. lower) in baseline COVID-19 anxiety had stronger decreases in anxiety symptoms while receiving CBM-I but weaker decreases in anxiety symptoms (on the DASS-21-AS) while receiving psychoeducation. These findings suggest that CBM-I may be a useful anxiety-reduction tool for individuals experiencing higher anxiety tied to uncertain events such as the COVID-19 pandemic.

Writing about the future self to shift drinking identity: An experimental investigation.

College student drinking is prevalent and costly to public and personal health, leading to calls to identify and target novel mechanisms of behavior change. We aimed to manipulate drinking identity (a cognitive risk factor for hazardous drinking) via three sessions of narrative writing about a future self. We tested whether writing could shift drinking identity and would be accompanied by changes in alcohol consumption and problems. Participants were college students meeting hazardous drinking criteria (N = 328; Mage = 20.15; 59% women, 40% men, 1% gender-diverse; 60% white; 23% Asian; 12% multiple races; 2% other racial groups; 8% identified as Hispanic/Latino/a/x). The study had a 2 [narrative writing topic: low-risk drinker vs. reduced smartphone use] × 2 [writing perspective: first person vs. non-first-person] × 2 [social network instruction: instructed to include vs. not] factorial design. Outcomes were drinking identity, drinking refusal self-efficacy, alcohol consumption, alcohol-related problems, and craving. Participants completed three writing sessions and online follow-up assessments at 2, 4, and 12 weeks. The study is a registered clinical trial; hypotheses and analyses were preregistered (https://osf.io/vy2ep/). Contrary to predictions, narrative writing about a future self as a low-risk drinker did not significantly impact outcomes. Null results extended to expected interactions with writing perspective and social network instructions. The narrative writing task did not shift drinking or alcohol-related outcomes. Future experimental work may benefit from greater flexibility in conceptualizing a future self, recruiting individuals interested in behavior change, and more sensitive measures of drinking identity.

Investigating psychiatric symptoms as predictors of the reasons people do not regulate their emotions in daily life.

Investigations into emotion dysregulation predominantly focus on ineffective strategy selection and implementation. However, little empirical attention has been given to the possibility that failure to engage in emotion regulation (ER) may also indicate emotion dysregulation, especially when the reason for not regulating suggests skill or motivational deficits. We randomly sampled ER strategy use up to six times per day for 5 weeks in 113 adults with elevated social anxiety. When participants reported not engaging in any recent ER, they indicated their reason for not regulating. Data were collected between 2018 and 2019. Participants reported not regulating in 60.9% of surveys. The most frequently endorsed reason for not regulating was "I was not experiencing any thoughts/feelings that I wanted to change," followed by "I did not want to put in the effort," then "I did not know what to do," and finally, "I did not think I was capable." After controlling for within- and between-person state affect, participants with lower trait-level social anxiety, depression, and emotion dysregulation scores were more likely to report no ER because they were not experiencing any thoughts/feelings that they wanted to change relative to the other three reasons that might reflect barriers to effective regulation. Trait-level generalized worry and alcohol use did not significantly predict between nonregulation reasons. Findings from these preregistered analyses suggest that not regulating-especially among persons higher in social anxiety, depression, and emotion dysregulation-may indicate ER skill or motivation deficits that point to opportunities for intervention. Results may not generalize to more demographically or clinically diverse samples. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline.

Individuals high in social anxiety symptoms often exhibit elevated state anxiety in social situations. Research has shown it is possible to detect state anxiety by leveraging digital biomarkers and machine learning techniques. However, most existing work trains models on an entire group of participants, failing to capture individual differences in their psychological and behavioral responses to social contexts. To address this concern, in Study 1, we collected linguistic data from N=35 high socially anxious participants in a variety of social contexts, finding that digital linguistic biomarkers significantly differ between evaluative vs. non-evaluative social contexts and between individuals having different trait psychological symptoms, suggesting the likely importance of personalized approaches to detect state anxiety. In Study 2, we used the same data and results from Study 1 to model a multilayer personalized machine learning pipeline to detect state anxiety that considers contextual and individual differences. This personalized model outperformed the baseline's F1-score by 28.0%. Results suggest that state anxiety can be more accurately detected with personalized machine learning approaches, and that linguistic biomarkers hold promise for identifying periods of state anxiety in an unobtrusive way.

State and Trait Emotion Regulation Diversity in Social Anxiety.

Emotion regulation (ER) diversity, defined as the variety, frequency, and evenness of ER strategies used, may predict social anxiety (SA) severity. In a sample of individuals with high (n=113) or low (n=42) SA severity, we tested whether four trait ER diversity metrics predicted group membership. We generalized existing trait ER diversity calculations to repeated-measures data to test if state-level metrics (using two weeks of EMA data) predicted SA severity within the higher severity group. As hypothesized (osf.io/xadyp), higher trait ER diversity within avoidance-oriented strategies predicted greater likelihood of belonging to the higher severity group. At the state-level, higher diversity across all ER strategies, and within and between avoidance- and approach-oriented strategies, predicted higher SA severity (but only after controlling for number of submitted EMAs). Only diversity within avoidance-oriented strategies was significantly correlated across trait and state levels. Findings suggest that high avoidance-oriented ER diversity may co-occur with higher SA severity.

Minimal Effect of Messaging on Engagement in a Digital Anxiety Intervention.

This study evaluated the effectiveness of different recruitment messages for encouraging enrollment in a digital mental health intervention (DMHI) for anxiety among 1,600 anxious patients in a large healthcare system. Patients were randomly assigned to receive a standard message, or one of five messages designed to encourage enrollment: Three messages offered varying financial incentives, one message offered coaching, and one message provided consumer testimonials. Patients could then click a link in the message to visit the DMHI website, enroll, and start the first session. We examined the effects of message features and message length (short vs. long) on rates of site clicks, enrollment, and starting the first session. We also tested whether demographic and clinical factors derived from patients' electronic health records were associated with rates of enrollment and starting the first session to understand the characteristics of patients most likely to use DMHIs in this setting. Across messages, 19.4% of patients clicked a link to visit the DMHI website, but none of the messages were significantly associated with rates of site clicks, enrollment, or starting the first session. Females (vs. males) had a greater probability of enrollment. No other demographic or clinical variables were significantly associated with enrollment or starting the first session. Findings provide guidance for resource allocation decisions in larger scale DMHI implementations in healthcare settings.

Web-Based Cognitive Bias Modification Program for Young People With Social Anxiety and Hazardous Alcohol Use: Feasibility, Acceptability, and Preliminary Efficacy Study.

BACKGROUND: Interpretation bias modification (IBM) and approach bias modification (ApBM) cognitive retraining interventions can be efficacious adjunctive treatments for improving social anxiety and alcohol use problems. However, previous trials have not examined the combination of these interventions in a young, comorbid sample. OBJECTIVE: This study aims to describe the feasibility, acceptability, and preliminary efficacy of a web-based IBM+ApBM program for young adults with social anxiety and hazardous alcohol use ("Re-Train Your Brain") when delivered in conjunction with treatment as usual (TAU). METHODS: The study involved a 3-arm randomized controlled pilot trial in which treatment-seeking young adults (aged 18-30 y) with co-occurring social anxiety and hazardous alcohol use were randomized to receive (1) the "integrated" Re-Train Your Brain program, where each session included both IBM and ApBM (50:50 ratio), plus TAU (35/100, 35%); (2) the "alternating" Re-Train Your Brain program, where each session focused on IBM or ApBM in an alternating pattern, plus TAU (32/100, 32%); or (3) TAU only (33/100, 33%). Primary outcomes included feasibility and acceptability, and secondary efficacy outcomes included changes in cognitive biases, social anxiety symptoms, and alcohol use. Assessments were conducted at baseline, after the intervention period (6 weeks after baseline), and 12 weeks after baseline. RESULTS: Both Re-Train Your Brain program formats were feasible and acceptable for young adults. When coupled with TAU, both integrated and alternating programs resulted in greater self-reported improvements than TAU only in anxiety interpretation biases (at the 6-week follow-up; Cohen d=0.80 and Cohen d=0.89) and comorbid interpretation biases (at the 12-week follow-up; Cohen d=1.53 and Cohen d=1.67). In addition, the alternating group reported larger improvements over the control group in generalized social anxiety symptoms (at the 12-week follow-up; Cohen d=0.83) and alcohol cravings (at the 6-week follow-up; Cohen d=0.81). There were null effects on all other variables and no differences between the intervention groups in efficacy outcomes. CONCLUSIONS: Should these findings be replicated in a larger randomized controlled trial, Re-Train Your Brain has the potential to be a scalable, low-cost, and non-labor-intensive adjunct intervention for targeting interpretation and comorbidity biases as well as generalized anxiety and alcohol-related outcomes in the real world. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12620001273976; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364131. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/28667.

Shifting Episodic Prediction With Online Cognitive Bias Modification: A Randomized Controlled Trial.

Negative future thinking pervades emotional disorders. This hybrid efficacy-effectiveness trial tested a four-session, scalable online cognitive bias modification program for training more positive episodic prediction. 958 adults (73.3% female, 86.5% White, 83.4% from United States) were randomized to positive conditions with ambiguous future scenarios that ended positively, 50/50 conditions that ended positively or negatively, or a control condition with neutral scenarios. As hypothesized (preregistration: https://osf.io/jrst6), positive training participants improved more than control participants in negative expectancy bias (d = -0.58), positive expectancy bias (d = 0.80), and self-efficacy (d = 0.29). Positive training was also superior to 50/50 training for expectancy bias and optimism (d = 0.31). Training gains attenuated yet remained by 1-month follow-up. Unexpectedly, participants across conditions improved comparably in anxiety and depression symptoms and growth mindset. Targeting a transdiagnostic process with a scalable program may improve bias and outlook; however, further validation of outcome measures is required.

Changes in Learning From Social Feedback After Web-Based Interpretation Bias Modification: Secondary Analysis of a Digital Mental Health Intervention Among Individuals With High Social Anxiety Symptoms.

BACKGROUND: Biases in social reinforcement learning, or the process of learning to predict and optimize behavior based on rewards and punishments in the social environment, may underlie and maintain some negative cognitive biases that are characteristic of social anxiety. However, little is known about how cognitive and behavioral interventions may change social reinforcement learning in individuals who are anxious. OBJECTIVE: This study assessed whether a scalable, web-based cognitive bias modification for interpretations (CBM-I) intervention changed social reinforcement learning biases in participants with high social anxiety symptoms. This study focused on 2 types of social reinforcement learning relevant to social anxiety: learning about other people and learning about one's own social performance. METHODS: Participants (N=106) completed 2 laboratory sessions, separated by 5 weeks of ecological momentary assessment tracking emotion regulation strategy use and affect. Approximately half (n=51, 48.1%) of the participants completed up to 6 brief daily sessions of CBM-I in week 3. Participants completed a task that assessed social reinforcement learning about other people in both laboratory sessions and a task that assessed social reinforcement learning about one's own social performance in the second session. Behavioral data from these tasks were computationally modeled using Q-learning and analyzed using mixed effects models. RESULTS: After the CBM-I intervention, participants updated their beliefs about others more slowly (P=.04; Cohen d=-0.29) but used what they learned to make more accurate decisions (P=.005; Cohen d=0.20), choosing rewarding faces more frequently. These effects were not observed among participants who did not complete the CBM-I intervention. Participants who completed the CBM-I intervention also showed less-biased updating about their social performance than participants who did not complete the CBM-I intervention, learning similarly from positive and negative feedback and from feedback on items related to poor versus good social performance. Regardless of the intervention condition, participants at session 2 versus session 1 updated their expectancies about others more from rewarding (P=.003; Cohen d=0.43) and less from punishing outcomes (P=.001; Cohen d=-0.47), and they became more accurate at learning to avoid punishing faces (P=.001; Cohen d=0.20). CONCLUSIONS: Taken together, our results provide initial evidence that there may be some beneficial effects of both the CBM-I intervention and self-tracking of emotion regulation on social reinforcement learning in individuals who are socially anxious, although replication will be important.

Perceived Burdensomeness and Thwarted Belongingness in Text Messages of Suicide Attempt Survivors.

OBJECTIVE: Perceived burdensomeness and thwarted belongingness are considered interpersonal risk factors for suicide. Examining these themes in personal text messages may help identify proximal suicide risk. METHOD: Twenty-six suicide attempt survivors provided personal text messages and reported dates for past periods characterized by positive mood, depressed mood, suicidal ideation (with no attempt), or the two-week period leading up to suicide attempt(s). Texts were then classified into the applicable period based on matching dates. Texts (N = 194,083; including n = 86,705 outgoing texts) were coded for perceived burdensomeness and thwarted belongingness by masked trained raters. Multilevel models were fit to examine whether the target themes (combined into one overall interpersonal risk variable due to low base rate) were more prevalent in texts sent during higher risk episodes (e.g., suicide attempt vs. depressed mood episodes). RESULTS: 0.57% of outgoing texts contained either target theme. As hypothesized, logistic models showed participants were more likely to send texts containing the target themes during suicide attempt episodes relative to suicidal ideation (with no attempt) episodes, depressed mood episodes, and positive mood episodes, and during suicidal ideation (with no attempt) episodes relative to positive mood episodes. All contrasts were robust to post-hoc correction except for suicide attempt episodes vs. ideation (with no attempt) episodes. No other significant pairwise differences for episode type emerged. CONCLUSIONS: Despite the small sample size and low base rate of target themes in the texts, perceived burdensomeness and thwarted belongingness were associated with intra-individual suicide risk severity in personal text messages.

Assessing Emotion Polyregulation in Daily Life: Who Uses It, When Is It Used, and How Effective Is It?

Most research on emotion regulation has focused on understanding individual emotion regulation strategies. Preliminary research, however, suggests that people often use several strategies to regulate their emotions in a given emotional scenario (polyregulation). The present research examined who uses polyregulation, when polyregulation is used, and how effective polyregulation is when it is used. College students (N = 128; 65.6% female; 54.7% White) completed an in-person lab visit followed by a 2-week ecological momentary assessment protocol with six randomly timed survey prompts per day for up 2 weeks. At baseline, participants completed measures assessing past-week depression symptoms, social anxiety-related traits, and trait emotion dysregulation. During each randomly timed prompt, participants reported up to eight strategies used to change their thoughts or feelings, negative and positive affect, motivation to change emotions, their social context, and how well they felt they were managing their emotions. In pre-registered analyses examining the 1,423 survey responses collected, polyregulation was more likely when participants were feeling more intensely negative and when their motivation to change their emotions was stronger. Neither sex, psychopathology-related symptoms and traits, social context, nor subjective effectiveness was associated with polyregulation, and state affect did not moderate these associations. This study helps address a key gap in the literature by assessing emotion polyregulation in daily life. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00166-x.

Examining social reinforcement learning in social anxiety.

BACKGROUND AND OBJECTIVES: Reinforcement learning biases have been empirically linked to anhedonia in depression and theoretically linked to social anhedonia in social anxiety disorder, but little work has directly assessed how socially anxious individuals learn from social reward and punishment. METHODS: N = 157 individuals high and low in social anxiety symptoms completed a social probabilistic selection task that involved selecting between pairs of neutral faces with varying probabilities of changing to a happy or angry face. Computational modeling was performed to estimate learning rates. Accuracy in choosing the more rewarding face was also analyzed. RESULTS: No significant group differences were found for learning rates. Contrary to hypotheses, participants high in social anxiety showed impaired punishment learning accuracy; they were more accurate at choosing the most rewarding face than they were at avoiding the most punishing face, and their punishment learning accuracy was lower than that of participants low in social anxiety. Secondary analyses found that high (vs. low) social anxiety participants were less accurate at selecting the more rewarding face on more (vs. less) punishing face pairs. LIMITATIONS: Stimuli were static, White, facial images, which lack important social cues (e.g., movement, sound) and diversity, and participants were largely non-Hispanic, White undergraduates, whose social reinforcement learning may differ from individuals at different developmental stages and those holding more marginalized identities. CONCLUSIONS: Socially anxious individuals may be less accurate at learning to avoid social punishment, which may maintain negative beliefs through an interpersonal stress generation process.

Maturing Out: Between- and Within-Persons Changes in Social-Network Drinking, Drinking Identity, and Hazardous Drinking Following College Graduation.

Many college students reduce hazardous drinking (HD) following graduation without treatment. Identifying cognitive mechanisms facilitating this "natural" reduction in HD during this transition is crucial. We evaluated drinking identity as a potential mechanism and tested whether within-person changes in one's social network's drinking were linked to within-person changes in drinking identity and subsequent within-person changes in HD. A sample of 422 undergraduates reporting HD was followed from six months before until two years after graduation. Their drinking, drinking identity, and social networks were assessed online. Within-person changes in drinking identity did not mediate the relationship between within-person changes in social network drinking and personal HD, though significant positive between-person associations among all constructs were found. Instead, there was some evidence that within-person changes in drinking identity followed changes in HD, suggesting that drinking identity may function as a marker versus mechanism of "natural" HD reduction during transition out of college.

Implicit and explicit COVID-19 associations and mental health in the United States: a large-scale examination and replication.

BACKGROUND: Given the sensitive nature of COVID-19 beliefs, evaluating them explicitly and implicitly may provide a fuller picture of how these beliefs vary based on identities and how they relate to mental health. OBJECTIVE: Three novel brief implicit association tests (BIATs) were created and evaluated: two that measured COVID-19-as-dangerous (vs. safe) and one that measured COVID-19 precautions-as-necessary (vs. unnecessary). Implicit and explicit COVID-19 associations were examined based on individuals' demographic characteristics. Implicit associations were hypothesized to uniquely contribute to individuals' self-reports of mental health. METHODS: Participants (N = 13,413 US residents; April-November 2020) were volunteers for a COVID-19 study. Participants completed one BIAT and self-report measures. This was a preregistered study with a planned internal replication. RESULTS: Results revealed older age was weakly associated with stronger implicit and explicit associations of COVID-as-dangerous and precautions-as-necessary. Black and Asian individuals reported greater necessity of taking precautions than White individuals (with small-to-medium effects); greater education was associated with greater explicit reports of COVID-19-as-dangerous and precautions-as-necessary with small effects. Replicated relationships between COVID-as-dangerous explicit associations and mental health had very small effects. CONCLUSIONS: Implicit associations did not predict mental health but there was evidence that stronger COVID-19-as-dangerous explicit associations are weakly associated with worse mental health.

Effects of Mass Shootings on Mental Illness Stigma in the United States.

Although the vast majority of people with mental illness (PWMI) are not violent, Americans tend to think they are more dangerous than the general population. Because negative media portrayals may contribute to stigma, we used time-series analyses to examine changes in the public's perceived dangerousness of PWMI around six mass shootings whose perpetrators were reported to have a mental illness. From 2011 to 2019, 38,094 U.S. participants completed an online study assessing implicit and explicit perceived dangerousness of PWMI. There were large, upward spikes in perceived dangerousness the week of the Sandy Hook mass shooting that were relatively short-lived. However, there was not a consistent pattern of effects for other events analyzed, and any other spikes observed were smaller. Effects tended to be larger for explicit versus implicit perceived dangerousness. Sandy Hook seemed to temporarily worsen perceived dangerousness of PWMI, but this pattern was not observed for other mass shootings.

Stability and spread: A novel method for quantifying transitions within multivariate binary time series data.

We present a novel method for quantifying transitions within multivariate binary time series data, using a sliding series of transition matrices, to derive metrics of stability and spread. We define stability as the trace of a transition matrix divided by the sum of all observed elements within that matrix. We define spread as the number of all non-zero cells in a transition matrix divided by the number of all possible cells in that matrix. We developed this method to allow investigation into high-dimensional, sparse data matrices for which existing binary time series methods are not designed. Results from 1728 simulations varying six parameters suggest that unique information is captured by both metrics, and that stability and spread values have a moderate inverse association. Further, simulations suggest that this method can be reliably applied to time series with as few as nine observations per person, where at least five consecutive observations construct each overlapping transition matrix, and at least four time series variables compose each transition matrix. A pre-registered application of this method using 4 weeks of ecological momentary assessment data (N = 110) showed that stability and spread in the use of 20 emotion regulation strategies predict next timepoint affect after accounting for affect and anxiety's auto-regressive and cross-lagged effects. Stability, but not spread, also predicted next timepoint anxiety. This method shows promise for meaningfully quantifying two unique aspects of switching behavior in multivariate binary time series data.

Inferring sleep disturbance from text messages of suicide attempt survivors: A pilot study.

OBJECTIVE: Identifying digital markers of sleep disturbance-a known suicide risk factor-may aid in the detection of imminent suicide risk. This study examined sleep-related communication and texting patterns in personal text messages (N = 86,705) of suicide attempt survivors. METHOD: Twenty-six participants provided dates of past suicide attempts and 2-week periods of positive mood, depressed mood, or suicidal ideation. Linguistic Inquiry Word Count was used to identify sleep-related texts via a custom dictionary. Mixed effect models were fitted to test the association between suicide/mood episode type (e.g., attempt versus ideation) and three outcomes: likelihood of a text including sleep-related content, nightly count of texts sent from midnight to 5:00 AM, and sum of unique hour bins from midnight to 5:00 AM with outgoing texts. RESULTS: Analyses with a sleep dictionary that was manually revised to be more accurate (but not the original unedited dictionary) showed sleep-related communication was more likely during depressed mood episodes than positive mood episodes. Otherwise, there were no significant differences in sleep-related communication or objective texting patterns across episode type. CONCLUSIONS: Although we did not detect differences in sleep-related communication tied to suicidal thoughts or behaviors, sleep-related communication may differ as a function of within-person mood level.

The role of uncertainty, worry, and control in well-being: Evidence from the COVID-19 outbreak and pandemic in U.S. and China.

Uncertainty about the future often leads to worries about what the future will bring, which can have negative consequences for health and well-being. However, if worry can act as a motivator to promote efforts to prevent undesirable future outcomes, those negative consequences of worry may be mitigated. In this article, we apply a novel model of uncertainty, worry, and perceived control to predict psychological and physical well-being among four samples collected in China (Study 1; during the early COVID-19 outbreak in China) and the United States (Studies 2-4, during 4 weeks in May 2020, 4 weeks in November 2020, and cross-sectionally between April and November 2020). Grounded in the feeling-is-for-doing approach to emotions, we hypothesized (and found) that uncertainty about one's COVID-19 risk would predict greater worry about the virus and one's risk of contracting it, and that greater worry would in turn predict poorer well-being. We also hypothesized, and found somewhat mixed evidence, that perceptions of control over 1's COVID-19 risk moderated the relationship between worry and well-being such that worry was related to diminished well-being when people felt they lacked control over their risk for contracting the virus. This study is one of the first to demonstrate an indirect path from uncertainty to well-being via worry and to demonstrate the role of control in moderating whether uncertainty and worry manifest in poor well-being. (PsycInfo Database Record (c) 2023 APA, all rights reserved).