Population Segmentation for COVID-19 Vaccine Outreach: A Clustering Analysis and Implementation in Missouri.

OBJECTIVES: The purpose of this work was to segment the Missouri population into unique groups related to COVID-19 vaccine acceptance using data science and behavioral science methods to develop tailored vaccine outreach strategies. METHODS: Cluster analysis techniques were applied to a large data set that aggregated vaccination data with behavioral and demographic data from the American Community Survey and Deloitte's HealthPrism™ data set. Outreach recommendations were developed for each cluster, specific to each group's practical and motivational barriers to vaccination. RESULTS: Following selection procedures, 10 clusters-or segments-of census tracts across Missouri were identified on the basis of k -means clustering analysis of 18 different variables. Each cluster exhibited unique geographic, demographic, socioeconomic, and behavioral patterns, and outreach strategies were developed on the basis of each cluster's practical and motivational barriers. DISCUSSION: The segmentation analysis served as the foundation for "working groups" comprising the 115 local public health agencies (LPHAs) across the state. LPHAs with similar community segments in their service area were grouped together to discuss their communities' specific challenges, share lessons learned, and brainstorm new approaches. The working groups provided a novel way for public health to organize and collaborate across the state. Widening the aperture beyond Missouri, population segmentation via cluster analysis is a promising approach for public health practitioners interested in developing a richer understanding of the types of populations they serve. By pairing segmentation with behavioral science, practitioners can develop outreach programs and communications campaigns that are personalized to the specific behavioral barriers and needs of the population in focus. While our work focused on COVID-19, this approach has broad applicability to enhance the way public health practitioners understand the populations they serve to deliver more tailored services.

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.

Affective states and nonsuicidal self-injury (NSSI): Results from an ecological momentary assessment study of veterans with NSSI disorder.

BACKGROUND: The affective states most strongly associated with nonsuicidal self-injury (NSSI) remain poorly understood, particularly among veterans. This study used ecological momentary assessment (EMA) to examine relationships between affect ratings and NSSI urges and behaviors among veterans with NSSI disorder. METHODS: Participants (N = 40) completed EMA entries via mobile phone for 28 days (3722 total entries). Entries included intensity ratings for five basic affective states, as well as NSSI urges and behaviors, during the past 4 hours. RESULTS: Bivariate analyses indicated that each affect variable was significantly associated with both NSSI urges and behaviors. Angry/hostile and sad were most strongly associated with both NSSI urges and behaviors. A multivariate regression revealed that angry/hostile, disgusted with self, and happy (inversely related) were contemporaneously (within the same period) associated with NSSI behaviors, whereas all five basic affective states were contemporaneously associated with NSSI urges. In a lagged model, angry/hostile and sad were associated with subsequent NSSI urges but not behaviors. CONCLUSIONS: Findings highlight the relevance of particular affective states to NSSI and the potential utility of targeting anger in treatments for NSSI among veterans. There is a need for future EMA research study to further investigate temporal relationships between these variables.

Adapting cognitive bias modification to train healthy prospection.

Prospection, the mental simulation of future events, has been theoretically linked to physical and mental health. Prior studies have found that prospection is malleable; however, no research to our knowledge has tested whether a scalable intervention explicitly targeting the simulation of positive future outcomes can lead to more generalized positive prospection, and enhance positive outlook and reduce distress. The current study tested a novel, web-based cognitive bias modification for interpretation (CBM-I) program designed to shift prospective bias towards more positive (as opposed to negative) representations of future outcomes among 172 participants selected for having a relatively negative baseline expectancy bias. Results showed that following CBM-I, participants in active training conditions exhibited more positive expectations about the future, and increased self-efficacy and growth mindset. Also, optimism increased and depression and anxiety symptoms decreased following active training, but this also occurred for the control condition. Analyses did not suggest that changes in positive expectations mediated changes in positive outlook outcomes. Results suggest that an online prospection intervention can lead to more positive expectations about future events and improve positive outlook, though open questions remain about what accounts for the training effects.

Inconsistencies in self-reports of suicidal ideation and attempts across assessment methods.

Suicide researchers commonly use a variety of assessment methods (e.g., surveys and interviews) to enroll participants into studies and assign them to study conditions. However, prior studies suggest that different assessment methods and items may yield different responses from participants. This study examines potential inconsistencies in participants' reports of suicidal ideation (SI) and suicide attempt (SA) across commonly used assessment methods: phone screen interview, in-person interview, self-report survey, and confidential exit survey. To test the reliability of the effects, we replicated the study across two samples. In both samples, we observed a notable degree of inconsistent reporting. Importantly, the highest endorsement rates for SI/SA were on a confidential exit survey. Follow-up assessments and analyses did not provide strong support for the roles of purposeful inaccuracy, random responding, or differences in participant experiences/conceptualizations of SI. Although the reasons for such inconsistencies remain inconclusive, results suggest that classification of suicidal/control participants that uses multiple items to capture a single construct, that uses a Graded Scale to capture a broad spectrum of thoughts and behaviors, and that takes into account consistency of responding across such items may provide clearer and more homogenous groups and is recommended for future study. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Anger precedes and predicts nonsuicidal self-injury in veterans: Findings from an ecological momentary assessment study.

Veterans have high rates of suicide, and nonsuicidal self-injury (NSSI) is one of the strongest predictors of suicide risk; however, there is presently little known about antecedents of NSSI that might inform intervention efforts. Accumulating research suggests that anger and hostility play an important role in NSSI, but whether these emotions precede and predict NSSI is currently unknown. The aim of the current study was to examine the temporal relationships between anger/hostility and NSSI urges and behavior among veterans diagnosed with NSSI disorder. Our hypothesis was that angry/hostile affect would predict subsequent NSSI urge and engagement, but not vice versa. Forty veterans with NSSI disorder completed a 28-day ecological momentary assessment study with three daily prompts to report on their affect and NSSI urges and engagement. Multilevel cross-lagged path modeling was used to determine the direction of effects between angry/hostile affect and NSSI urges and engagement over time. Consistent with our hypothesis, results indicated that the lagged effects of angry/hostile affect on subsequent NSSI urge and engagement were significant, whereas the lagged effects of NSSI urge and engagement on angry/hostile affect were not significant. Findings highlight the importance of assessing and treating anger among veterans who engage in NSSI.

Psychological outcomes following sexual assault: Differences by sexual assault setting.

Sexual assault is associated with increased psychological distress. It is possible that military sexual assault (MSA) is associated with heightened psychological distress compared to adult sexual assault that occurs pre- or postmilitary service due to the nature of the military setting. Veterans and service members (N = 3,114; 19.6% women) who participated in the Post-Deployment Mental Health Study completed self-report measures of sexual assault history, symptoms of posttraumatic stress disorder (PTSD), symptoms of depression, hazardous alcohol use, drug use, and suicidal ideation. Women who reported a history of MSA endorsed higher levels of all types of psychological distress than women who did not experience adult sexual assault. Women who reported a history of MSA also endorsed higher levels of PTSD and depression symptoms than women who experienced pre- or postmilitary adult sexual assault. Men who reported a history of adult sexual assault, regardless of setting, reported higher levels of PTSD and depression symptoms than individuals who did not experience adult sexual assault. MSA was associated with higher psychological distress than pre- or postmilitary adult sexual assault among women. Among men, distress associated with MSA was comparable to sexual assault outside the military. Women may face unique challenges when they experience sexual assault in the military, and men may face additional stigma (compared to women) when they experience sexual assault, regardless of setting. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Post-traumatic symptom severity mediates the association between combat exposure and suicidal ideation in veterans.

OBJECTIVE: Previous studies of military veterans have produced mixed findings regarding whether combat exposure is directly related to suicidal ideation or is indirectly related to suicidal ideation via its influence on other factors. The present study used a longitudinal design to test the hypothesis that post-traumatic stress disorder (PTSD) symptom severity mediates the effect of combat exposure on suicidal ideation in veterans. METHOD: Participants included 319 post-9/11 veterans (83.4% male; 42.1% White/52.1% Black; Mage  = 39.7) assessed at baseline, 6, and 12 months. Structural equation modeling and bootstrapped confidence intervals were employed to examine the direct and indirect relationships between combat exposure, suicidal ideation, and PTSD symptom severity. RESULTS: Results from the mediation model, in which demographic variables and non-combat trauma were included as covariates, revealed that the indirect effect of combat exposure on suicidal ideation via PTSD symptom severity was statistically significant, accounting for 64.1% of the covariance between combat exposure and suicidal ideation. CONCLUSIONS: This study provides longitudinal evidence that the effects of combat exposure on suicidal ideation are mediated by PTSD symptom severity, suggesting the importance of targeting such symptoms in treatment to mitigate suicide risk among veterans with combat exposure.

Anger mediates the relationship between posttraumatic stress disorder and suicidal ideation in veterans.

BACKGROUND: Theoretical models and cross-sectional empirical studies of suicide indicate that anger is a factor that may help explain the association between posttraumatic stress disorder (PTSD) and suicide, but to date no longitudinal studies have examined this relationship. The current study used longitudinal data to examine whether changes in anger mediated the association between changes in PTSD symptomatology and suicidal ideation (SI). METHODS: Post 9/11-era veterans (N = 298) were assessed at baseline, 6-months, and 12-month time points on PTSD symptoms, anger, and SI. Analyses covaried for age, sex, and depressive symptoms. Multilevel structural equation modeling was used to examine the three waves of data. RESULTS: The effect of change in PTSD symptoms on SI was reduced from B = 0.02 (p = .008) to B = -0.01 (p = .67) when change in anger was added to the model. Moreover, the indirect effect of changes in PTSD symptoms on suicidal ideation via changes in anger was significant, B = 0.02, p = .034. The model explained 31.1% of the within-person variance in SI. LIMITATIONS: Focus on predicting SI rather than suicidal behavior. Sample was primarily male. CONCLUSIONS: Findings suggest that the association between PTSD and SI is accounted for, in part, by anger. This study further highlights the importance of anger as a risk factor for veteran suicide. Additional research on clinical interventions to reduce anger among veterans with PTSD may be useful in reducing suicide risk.

Decomposing implicit associations about life and death improves our understanding of suicidal behavior.

The Death/Suicide Implicit Association Test (IAT) is effective at detecting and prospectively predicting suicidal thoughts and behaviors. However, traditional IAT scoring procedures used in all prior studies (i.e., D-scores) provide an aggregate score that is inherently relative, obfuscating the separate associations (i.e., "Me = Death/Suicide," "Me = Life") that might be most relevant for understanding suicide-related implicit cognition. Here, we decompose the D-scores and validate a new analytic technique called the Decomposed D-scores ("DD-scores") that creates separate scores for each category ("Me," "Not Me") in the IAT. Across large online volunteer samples (N > 12,000), results consistently showed that a weakened association between "Me = Life" is more strongly predictive of having a history of suicidal attempts than is a stronger association between "Me = Death/Suicide." These findings replicated across three different versions of the IAT and were observed when calculated using both reaction times and error rates. However, among those who previously attempted suicide, a strengthened association between "Me = Death" is more strongly predictive of the recency of a suicide attempt. These results suggest that decomposing traditional IAT D-scores can offer new insights into the mental associations that may underlie clinical phenomena and may help to improve the prediction, and ultimately the prevention, of these clinical outcomes.

Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk.

Objective tools to assess suicide risk are needed to determine when someone is at imminent risk. This pilot laboratory investigation utilized a within-subjects design to identify patterns in text messaging (SMS) unique to high-risk periods preceding suicide attempts. Individuals reporting a history of suicide attempt (N=33) retrospectively identified past attempts and periods of lower risk (e.g., suicide ideation). Language analysis software scored 189,478 text messages to capture three psychological constructs: self-focus, sentiment, and social engagement. Mixed-effects models tested whether these constructs differed in general (means) and over time (slopes) two weeks before a suicide attempt, relative to lower-risk periods. Regarding mean differences, no language features uniquely differentiated suicide attempts from other episodes. However, when examining patterns over time, anger increased and positive emotion decreased to a greater extent as one approached a suicide attempt. Results suggest private electronic communication has the potential to provide real-time digital markers of suicide risk.

How badly will I feel if you don't like me?: Social anxiety and predictions of future affect.

The current study investigated whether high and low socially anxious individuals would show differences in affective forecasting accuracy (i.e., the prediction of emotional states in response to future events) to positive versus negative social evaluation. High (n=94) and low (n=98) socially anxious participants gave a speech and were randomly assigned to receive a positive or negative evaluation. For affective forecasts made proximally (moments before the speech), those low in social anxiety overpredicted their affect to a greater extent to a negative evaluation versus a positive evaluation. In contrast, those high in social anxiety overpredicted their affect to positive and negative evaluations comparably, and failed to adjust their prediction for a future hypothetical negative evaluation - in effect, not learning from their prior forecasting error. Results suggest that affective forecasting biases deserve further study as a maintaining factor for social anxiety symptoms.

Identification of Imminent Suicide Risk Among Young Adults using Text Messages.

Suicide is the second leading cause of death among young adults but the challenges of preventing suicide are significant because the signs often seem invisible. Research has shown that clinicians are not able to reliably predict when someone is at greatest risk. In this paper, we describe the design, collection, and analysis of text messages from individuals with a history of suicidal thoughts and behaviors to build a model to identify periods of suicidality (i.e., suicidal ideation and non-fatal suicide attempts). By reconstructing the timeline of recent suicidal behaviors through a retrospective clinical interview, this study utilizes a prospective research design to understand if text communications can predict periods of suicidality versus depression. Identifying subtle clues in communication indicating when someone is at heightened risk of a suicide attempt may allow for more effective prevention of suicide.

A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression.

Although social anxiety and depression are common, they are often underdiagnosed and undertreated, in part due to difficulties identifying and accessing individuals in need of services. Current assessments rely on client self-report and clinician judgment, which are vulnerable to social desirability and other subjective biases. Identifying objective, nonburdensome markers of these mental health problems, such as features of speech, could help advance assessment, prevention, and treatment approaches. Prior research examining speech detection methods has focused on fully supervised learning approaches employing strongly labeled data. However, strong labeling of individuals high in symptoms or state affect in speech audio data is impractical, in part because it is not possible to identify with high confidence which regions of a long speech indicate the person's symptoms or affective state. We propose a weakly supervised learning framework for detecting social anxiety and depression from long audio clips. Specifically, we present a novel feature modeling technique named NN2Vec that identifies and exploits the inherent relationship between speakers' vocal states and symptoms/affective states. Detecting speakers high in social anxiety or depression symptoms using NN2Vec features achieves F-1 scores 17% and 13% higher than those of the best available baselines. In addition, we present a new multiple instance learning adaptation of a BLSTM classifier, named BLSTM-MIL. Our novel framework of using NN2Vec features with the BLSTM-MIL classifier achieves F-1 scores of 90.1% and 85.44% in detecting speakers high in social anxiety and depression symptoms.

Testing the Efficacy of Attention Bias Modification for Suicidal Thoughts: Findings From Two Experiments.

This study explores whether four sessions of attention bias modification (ABM) decreases suicide-specific attentional bias. We conducted two experiments where suicide ideators completed either a Training or Control version of ABM, a computer-based intervention intended to target attentional bias. Suicide-specific attentional bias was measured using adapted Stroop and probe discrimination tasks. The first experiment with community-based suicide ideators did not show that ABM impacts attentional bias or suicidal ideation. The second experiment with clinically severe suicidal inpatients yielded similar results. Post-hoc findings suggest that the type of attentional bias targeted by the current intervention may differ from the type that marks suicide risk. There remains little to no evidence that the ABM intervention changes suicide-specific attentional bias or suicidal ideation.

Suicide and self-injury-related implicit cognition: A large-scale examination and replication.

Suicide and self-injury are difficult to predict because at-risk individuals are often unable or unwilling to report their intentions. Therefore, tools to reliably assess risk without reliance on self-report are critically needed. Prior research suggests that people who engage in suicidal and nonsuicidal self-injury (NSSI) often implicitly (i.e., outside conscious control) associate themselves with self-harm and death, indicating that self-harm-related implicit cognition may serve as a useful behavioral marker for suicide risk. However, earlier studies left several critical questions about the robustness, sensitivity, and specificity of self-harm-related implicit associations unaddressed. We recruited a large sample of participants (N = 7,015) via a public web-based platform called Project Implicit Mental Health (PIMH) to test several hypotheses about self-harm-related implicit associations using the Implicit Association Test (IAT). Participants were randomly assigned to complete 1 of 3 self-harm IATs (Self + Cutting using picture stimuli, Self + Suicide using word stimuli, Self + Death using word stimuli). Results replicated prior studies demonstrating that self-harm-related implicit associations were stronger among individuals with (vs. without) a history of suicide attempt and NSSI. Results also suggested that self-harm-related implicit associations are robust (based on internal replication), are sensitive to recency and severity of self-harm history (e.g., stronger associations for more recent and more lethal prior suicide attempts), and correlate with specific types of self-harm behaviors. These findings clarify the nature of self-harm-related implicit cognition and highlight the IAT's potential to track current risk for specific types of self-harm in ways that more fixed risk factors cannot. (PsycINFO Database Record

Characterizing implicit mental health associations across clinical domains.

BACKGROUND AND OBJECTIVES: Implicit associations are relatively uncontrollable associations between concepts in memory. The current investigation focuses on implicit associations in four mental health domains (alcohol use, anxiety, depression, and eating disorders) and how these implicit associations: a) relate to explicit associations and b) self-reported clinical symptoms within the same domains, and c) vary based on demographic characteristics (age, gender, race, ethnicity, and education). METHODS: Participants (volunteers over age 18 to a research website) completed implicit association (Implicit Association Tests), explicit association (self + psychopathology or attitudes toward food, using semantic differential items), and symptom measures at the Project Implicit Mental Health website tied to: alcohol use (N = 12,387), anxiety (N = 21,304), depression (N = 24,126), or eating disorders (N = 10,115). RESULTS: Within each domain, implicit associations showed small to moderate associations with explicit associations and symptoms, and predicted self-reported symptoms beyond explicit associations. In general, implicit association strength varied little by race and ethnicity, but showed small ties to age, gender, and education. LIMITATIONS: This research was conducted on a public research and education website, where participants could take more than one of the studies. CONCLUSIONS: Among a large and diverse sample, implicit associations in the four domains are congruent with explicit associations and self-reported symptoms, and also add to our prediction of self-reported symptoms over and above explicit associations, pointing to the potential future clinical utility and validity of using implicit association measures with diverse populations.

Examining potential iatrogenic effects of viewing suicide and self-injury stimuli.

The high-stakes nature of self-injurious thoughts and behaviors (SITBs) raises ethical questions and concerns. The authors examined the iatrogenic risk of recently developed behavioral measures such as the suicide or self-injury Implicit Association Tests (IATs), which include repeated and rapid presentation of SITB-related images (e.g., of cut skin) and words (e.g., death, suicide). The impact of these IATs was investigated across a series of 3 studies involving: adult web-based respondents (n = 3,304), undergraduate students (n = 100), and adolescent psychiatric inpatients (n = 89). There was minimal change in self-injurious or suicidal urges detected across all IAT studies. A slight mood decline was detected across the 3 samples, but was isolated to female research participants and 1 type of IAT that presented SITB-related images (vs. words only). Given the increasing use of novel SITB-relevant stimuli in behavioral and neurobiological studies, these findings may help researchers balance clinical sensitivity and clinical science. (PsycINFO Database Record

Pain analgesia among adolescent self-injurers.

Although non-suicidal self-injury (NSSI) involves self-inflicted physical harm, many self-injurers report feeling little or no pain during the act. Here we test: (1) whether the pain analgesia effects observed among adult self-injurers are also present among adolescents, and (2) three potential explanatory models proposing that habituation, dissociation, and/or self-criticism help explain the association between NSSI and pain analgesia among adolescents. Participants were 79 adolescents (12-19 years) recruited from the community who took part in a laboratory-based pain study. Results revealed that adolescent self-injurers have a higher pain threshold and greater pain endurance than non-injurers. Statistical mediation models revealed that the habituation and dissociation models were not supported; however, a self-critical style does mediate the association between NSSI and pain analgesia. The present findings extend earlier work by highlighting that a self-critical style may help to explain why self-injurers exhibit pain analgesia. Specifically, the tendency to experience self-critical thoughts in response to stressful events may represent a third variable that increases the likelihood of both NSSI and pain analgesia. Prospective experimental studies are needed to replicate and tease apart the direction of these associations, and may provide valuable leads in the development of effective treatments for this dangerous behavior problem.