Risky or dysregulated behaviors such as non-suicidal self-injury, risky substance use, aggression, and disordered eating co-occur at higher-than-expected rates; dimensional, structural and personality-informed models of psychopatholgy may help to explain these patterns of covariation. We used latent variable models to test three transdiagnostic models of risky behaviors in two community samples: youth aged 14-20 (N=565, Sample 1), and first-year university students (N=627, Sample 2). In both samples, fit indices favored a hierarchical model wherein a higher-order general risky behavior factor was indicated by three lower-order dimensions: internalizing risky behaviors, comprised of self-injurious behaviours, prescription drug misuse, and maladaptive weight control behaviors; disinhibited risky behaviors, comprised of substance misuse, risky sex, and intoxicated driving; and, antagonistic risky behaviors, comprised of physical aggression toward objects and people, intoxicated driving, and law-violating behaviors. Next, we examined associations between risky behavior dimensions, self-reported personality traits, and performance on computerized approach/avoidance tasks in Sample 2. Internalizing risky behaviors were most strongly associated with neuroticism and negative urgency, while disinhibited and antagonistic risky behaviors were most strongly associated with sensitivity to reward and sensation seeking. Antagonistic risky behaviors were negatively associated with agreeableness and conscientiousness, while disinhibited risky behaviors were negatively associated with sensitivity to punishment. Results support the potential of a dimensional transdiagnostic model to identify meaningful patterns of co-occurrence that are distinguishable in terms of personality.
Background Mobile application-delivered interpretation bias modification (IBM) has shown efficacy in treating health anxiety. However, not all individuals achieve optimal outcomes, and prior research has not identified clear predictors of IBM treatment success. Leveraging precision medicine techniques, such as machine learning, may enhance the prediction of treatment outcomes. Methods Participants were drawn from a three-arm randomized controlled trial (N=212), comprising a mobile application-delivered IBM treatment group (N=70), an attention control group (N=70), and a waitlist group (N=72). Six machine learning models, particularly the support vector machine (SVM), were employed to predict the remission of health anxiety based on baseline clinical and demographic variables for each group. Feature importance analysis was conducted to identify the most predictive variables of treatment improvement. Results The findings indicated that the SVM algorithm demonstrated favorable classification performance in predicting improvement for the treatment (AUC = 0.701) and attention control (AUC = 0.857) groups, in contrast to its limited performance for the waitlist group (AUC = 0.538). Feature importance analysis revealed that catastrophic interpretation for specific physical diseases and depressive symptoms were more predictive of mobile application-delivered IBM treatment outcomes or natural recovery, while demographic variables showed less predictive power. Conclusions This exploratory analysis suggests that supervised machine learning may help characterize multivariate prognostic patterns associated with improvement in digital health anxiety interventions. The specific predictors identified, catastrophic interpretation for specific physical diseases and depressive symptoms, offer clinically actionable targets for pretreatment assessment, potentially informing more personalized treatment strategies aligned with precision medicine approaches.
Low positive affect (i.e., PA) is a hallmark of depression commonly associated with maladaptive use of emotion regulation strategies and a low preference for PA states. Motivational models of emotion regulation propose that the use of emotion regulation strategies subserves the attainment of specific emotion goals. Yet, these associations have not been investigated in the context of daily-life PA regulation in depression. The present study used a 7-day experience-sampling design in a sample of clinically depressed individuals (N = 65) to assess whether prohedonic goals aimed at either increasing PA or reducing negative affect (i.e., NA) were (1) prospectively associated with the deployment of specific regulatory strategies (i.e., distraction, reappraisal, acceptance) and (2) concurrently associated with the efficacy of those strategies in boosting positive and dampening negative affective states. Lagged multilevel models revealed distinct motivational signatures. Activating the goal to reduce NA prospectively predicted greater subsequent use of acceptance, which was in turn effective at improving affective states. Reappraisal was infrequently selected and showed no significant associations with prohedonic goals or later affect. While accounting for reappraisal and acceptance, distraction improved subsequent affect (i.e., increased PA, decreased NA) only when paired with a concurrent goal to increase PA, but resulted in the opposite pattern when this goal was absent. Future studies should assess a wider array of emotion goals and emotion regulation dynamics in depression, as well as the long-term adaptiveness of these interactions.
We evaluated whether the decision support tools (written case formulation, list of treatment goals, plot of progress monitoring data) of the case formulation approach to cognitive behavior therapy (CBT) predicted the prevention and resolution of episodes of symptom deterioration and lack of progress during treatment and the relationship of these episodes to dropout and end-of-treatment symptoms.Participants were adults who received naturalistic CBT for symptoms of depression (n = 314) measured with the Beck Depression Inventory (BDI) and/or anxiety (n = 398) measured with the Burns Anxiety Inventory (BurnsAI). We defined a not-on-track (NOT) episode as a reliable worsening of symptoms (deterioration) or a period of five or more sessions without reliable improvement compared to intake (lack of progress). The research team rated the presence of each decision support tool in the clinical record and the therapist rated whether dropout was premature or uncollaborative.NOT episodes predicted increased end-of-treatment BDI and BurnsAI scores. Resolution of NOT episodes predicted decreased end-of-treatment BDI and BurnsAI scores and lower likelihood of premature dropout. Positive effects of the resolution of NOT episodes were larger than their negative effects. No decision support tool predicted reduced occurrence of NOT episodes. The case formulation predicted resolution of NOT episodes defined by BDI scores.The large positive effect of the resolution of NOT episodes on end-of-treatment symptoms suggests the resolution of NOT episodes can strengthen the treatment. Therapist use of a case formulation appears to contribute to that helpful process.
Mobile health interventions represent a scalable and accessible alternative to traditional therapy, which often is out of reach due to high costs and societal stigma. Rumination is considered a key mechanism of emotional disorders and represents a potential treatment target for digital health interventions. The current study investigated the role of rumination as a mediator of the reduction in depression and anxiety reported after the use of a gamified mobile app based on the Facilitating Thought Progression (FTP) framework. One hundred-one adults with mild to moderate depression were randomized to the FTP intervention or a waitlist control group and completed weekly assessments of depression, anxiety, and rumination over 8 weeks. Multilevel structural equation modeling revealed that reduction in rumination significantly mediated decreases in depression and anxiety in the intervention group but not in the waitlist condition. These findings suggest that the FTP app targeted rumination and further highlights its role as a critical target for interventions for depression and anxiety.
Behavioral researchers are rarely trained in using interim analysis within group sequential designs for behavioral trials, but reviewers and oversight boards may require its discussion and consideration. Interim analysis within a group sequential design can be employed for various ethical or logistical reasons in behavioral clinical trials, including to limit risk/harm and to maximize benefit for research participants and the general public. Yet, depending on the research goals and context of the trial, these strategies are not always necessary or appropriate for every trial. When they are useful and appropriate, group sequential trials require rigorous design. This paper aims to inform behavioral intervention researchers about the importance of considering the implications of incorporating or not incorporating a group sequential design with interim analyses in the early phase of study development, considerations in deciding whether to include these methods, how to implement them if they are included, and how to report results from these trials. Examples are provided of study types (e.g., relating to suicide risk) that may merit or not merit use of these designs, and a decision map is provided. Ethical, statistical, and practical implications are discussed.
Based on influential theories of rumination, this study aimed to model and evaluate intervention strategies. 95 adults at risk for depression completed ≥50% of a 21-day ecological momentary assessment. Idiographic network models were estimated and Control Theory principles applied to identify intervenable nodes and simulate effects of Cognitive Training, Self-System Therapy, Metacognitive Therapy and combined intervention approaches on rumination and related variables. Constructs from self-regulatory and metacognitive models of rumination appeared among the most intervenable variables. Promotion focus and Negative beliefs about rumination had the greatest simulated impact. Negative beliefs also showed broad reach in its impact. Simulated intervention effects remained focal and intervention order did not affect outcomes. We observed substantial individual variability in treatment response. Control Theory offers a promising framework for identifying intervention targets. We discuss the benefits and downsides of applying a modeling approach to intervention research.
Depression is commonly treated with either psychotherapy or antidepressants, but patients differ widely in their comparative responses. Identifying the most effective treatment for each individual is crucial to optimizing scarce resources, particularly in low-resource settings. This study evaluated the feasibility and acceptability of a precision treatment trial comparing psychotherapy based on behavioral activation (the Healthy Activity Program) with antidepressant medication (fluoxetine) in adults with depression in primary care settings in India. A single-blind, two-arm randomized controlled pilot was conducted with adults aged ≥18 years with moderate to severe depression (PHQ-9 score≥10) from eight primary healthcare centers in Bhopal, India. Primary outcomes were feasibility and acceptability, assessed using indicators of study implementation (recruitment, randomization, treatment fidelity, completeness of assessments, biologic sample collection, and safety) and participant engagement (retention and treatment adherence). Secondary outcomes included changes in depressive symptoms, remission, and patients’ subjective sense of improvement at the 3-month endpoint. Of 578 individuals screened, 180 were eligible and 76 (42%) enrolled. Retention was 82% at 3 months. Psychotherapy participants attended 5.6/6-8 sessions, while medication participants consumed 57.9% of prescribed doses. Completion rates of study assessments were high (72–100%), and missing data were minimal, although some baseline measures were burdensome and were subsequently shortened for the main trial. Biologic sample collection was feasible, with 67% of participants consenting to blood draws. Depressive symptoms improved across both arms, with 45.2% achieving remission. However, treatment responses varied substantially within each arm (psychotherapy: –9.1 [SD=6.5]; medication: –7.6 [SD=6.9]), indicating marked individual heterogeneity. This pilot demonstrated the feasibility and acceptability of implementing a precision treatment trial for depression in Indian primary care, identified refinements to optimize procedures for the main trial, and supported the potential to identify the optimal treatment for each patient.
Caregivers of individuals with schizophrenia face substantial psychological burden, with higher depression rates than the general population. Profamille, a multifamily psychoeducational program offered in France since 1993 and regularly updated, integrates cognitive-behavioral strategies to improve caregivers’ mood and coping skills. Mood was assessed using CES-D-20 and PHQ-9 scales, allowing a distinction between major depressive disorder and other forms of depression, referred to here as subclinical depression. A systematic waiting period between inclusion and program start enables caregivers to prepare and fully engage.We conducted a retrospective analysis of all French groups participating in version V3.2 (2011–2019). Using archival data, we randomly selected two subsamples of participants: a pseudo-control group (i.e., waiting-period control group; N = 1,116) and an active intervention group (N = 1,117).At baseline, in both groups, slightly more than half of caregivers had CES-D scores >16, indicating clinically relevant depressive symptoms.Profamille significantly improved caregivers’ mood: 29% of initially Depressed participants became Non-depressed in the active group versus 8% in controls, and 53% of participants with subclinical depression became Non-depressed versus 25% in controls. Exploratory subgroup analyses suggested a consistent pattern of intervention effects across caregiver and patient characteristics. Non-depressed caregivers maintained stable mood over time, with a trend toward preventive effects compared to the waiting period group.These findings, based on a large retrospective sample with an acceptable missing data rate (12.3%), support the effectiveness, sustainability, and acceptability of Profamille, highlighting its potential to improve caregiver well-being across diverse clinical and demographic contexts.
The cognitive behavioral model (CBM) for obsessive-compulsive disorder (OCD) theorizes that unwanted thoughts become obsessions when appraised using obsessive beliefs (responsibility/threat, need to control thoughts, and perfectionism). These beliefs are posited to uniquely relate to OCD symptom dimensions and maintain obsessions; however, no study has examined this naturalistically over time. We used an ecological momentary assessment (EMA) design to examine the naturalistic occurrence of obsessive beliefs, their prediction of concurrent and subsequent obsessions, and associations with baseline OCD symptom dimensions. Participants with OCD (n = 49) completed EMA items regarding current obsessions and obsessive beliefs 7x/day for 7 days. Data were analyzed using multilevel models controlling for compulsions. An obsessive belief was endorsed during 55.8% of prompts when an obsession was present. In contrast, an obsession was present for over three-fourths (77.4%) of prompts in which an obsessive belief was endorsed. When controlling for compulsions, greater obsessive beliefs were associated with greater obsessions concurrently but were associated with a decrease in obsessions at the next time point. Lower obsessive beliefs were associated with fewer obsessions concurrently but an increase in obsessions at the next time point. Momentary obsessive beliefs were differentially related to baseline OCD symptom dimensions, exhibiting both convergence and deviations from prior work. Findings supported the CBM such that obsessive beliefs occurred frequently, were associated with exacerbated obsessions, and differentially related to symptom dimensions. However, increases in beliefs did not predict subsequent increases in obsessions, suggesting that other variables may maintain obsessions in the long-term.
Anorexia nervosa (AN) is a serious psychiatric illness. Despite its severity, most individuals with AN never achieve full recovery and more than 50% of patients relapse after treatment. One of the primary reasons that many treatments are limited in their effectiveness, is that they do not specifically target cognitive-affective pathology. Furthermore, many treatments are limited by lack of scalability. New treatments that target cognitive-affective pathology (e.g., anxiety, fear) and that are scalable are needed to improve both outcomes and access to evidence-based care. As such, the current open series trial (N = 10) piloted a new digital, exposure-based modular treatment for AN-related fear and anxiety, called Digital Facing Eating Disorder Fears (FED-F). FED-F consists of five digital modules focused on four common AN fears: weight gain, food, social eating, and physical sensations, and one module of cognitive re-structuring. Modules are complemented by homework assignments and light-touch coaching. FED-F had high feasibility, acceptability, mixed findings for target engagement (i.e., decreased avoidance behaviors), and good initial clinical efficacy, with pre-post effect sizes ranging from small to large, dependent on the type of fear. Overall, FED-F is a promising new digital treatment that could be used to decrease anxiety-based cognitions and behaviors present in AN. Future work should test FED-F in a randomized controlled trial design especially with populations who may have difficulty accessing evidence-based care.
Psychological flexibility and mindfulness are core constructs in contemporary models of adaptive functioning and clinical intervention. Although these constructs are conceptually linked, the empirical strength and consistency of their association remain unclear. This study presents the first meta-analytic review examining the correlation between psychological flexibility and mindfulness across published studies. A systematic literature search identified 45 eligible studies comprising a total of 16,316 participants. Effect sizes were calculated as Pearson's r and transformed into Fisher's z for analysis. Random-effects models were estimated using restricted maximum likelihood (REML). Between-study heterogeneity was evaluated using Q, I2, and τ2 statistics. Moderator analyses tested whether study characteristics (sample type, mean age, year of publication, sample size) and measurement features (type of psychological flexibility and mindfulness instrument, number of items) explained heterogeneity. Publication bias was assessed via funnel plots, regression tests, and the trim-and-fill method. The overall pooled correlation between psychological flexibility and mindfulness was significant (r = .44, 95% CI [.41, .53], p < .0001). Substantial heterogeneity was observed (I2 = 92.6%), warranting moderation analyses. Measurement-level moderators (type of psychological flexibility scale, number of items) significantly influenced effect sizes, whereas sample type, age, year, and sample size did not. Subgroup analyses revealed stronger correlations for AAQ-16 and AAO-II compared to other measures, and for FFMQ relative to MAAS. Publication bias analyses indicated no evidence of missing studies, and the trim-and-fill procedure confirmed the robustness of results (r = .44). Psychological flexibility and mindfulness demonstrate a robust positive association across diverse populations and instruments. However, the magnitude of this relationship varies by measurement tools, underscoring the importance of construct operationalization in future research. These findings highlight the interdependence of psychological flexibility and mindfulness within contemporary process-based models of adaptive functioning and suggest that interventions targeting one construct may enhance the other.
Emotion Context Insensitivity (ECI) hypothesizes that depression relates to blunted positive and negative emotion reactivity. Despite broad support for ECI, studies often generate contrary results. The primary goal of this paper was to ascertain whether these disparities might be due to the use of different measurement strategies. One conventional questionnaire and four multilevel emotion reactivity assessments were used to examine this possibility in a sample of 712 general population adults. The questionnaire method revealed that depressive symptoms were related to lower positive and higher negative emotion reactivity; however, these relations were largely explained by individuals’ average affect. The four multilevel emotion reactivity approaches generated highly consistent findings that both positive and negative emotion reactivity are negatively related to depressive symptoms, even controlling for individuals’ average affect. Multilevel methods provided strong support for ECI, whereas the questionnaire method did not distinguish well between individuals’ emotion reactivity and their average affect.
Trauma-induced sleep disturbances often persist after successful posttraumatic stress disorder (PTSD) treatment. While integrated protocols combining sleep and exposure-based treatments may maximize outcomes, prior studies are limited and have largely relied on subjective sleep measures or failed to include long-term follow up assessments. Active-duty service members with PTSD (n = 82) were randomly assigned to Compressed Prolonged Exposure (CPE) treatment or Trauma Management Therapy (TMT), which integrates exposure therapy with sleep hygiene training and other skills-based interventions. PTSD symptoms and actigraphy-based sleep were measured at baseline, posttreatment, 3- and 6-month follow-up and data were compared between groups and across time. Posttreatment, both groups showed negligible to small changes in sleep compared to baseline. However, the TMT group evidenced improvements in most sleep parameters by the 3- and 6-month follow-ups, while sleep health generally worsened in the CPE group over time. Between groups, those randomized to TMT exhibited better sleep efficiency (g = 0.24) and onset latency (g = -0.34) at 3-month follow-up, and better sleep quality (g = 0.70), efficiency (g = 0.51), and wake after sleep onset (g = -0.52) at 6-month follow-up. Within both treatment groups, poorer sleep at the 6-month follow-up was correlated with greater PTSD symptom severity measured at the same time point. Integrated treatment for sleep and PTSD produced superior objective sleep outcomes compared to exposure alone, with the most meaningful improvements in sleep observed 6 months after treatment completion. Several critical directions for future studies are discussed.
Exposure and response prevention (EX/RP) is a first-line treatment for obsessive-compulsive disorder (OCD), yet many patients fail to achieve full remission. Among the strongest predictors of treatment outcome is patient adherence—particularly to between-session exposure exercises and ritual prevention. However, limited research has examined factors that influence adherence. This study aimed to replicate and extend prior findings by identifying predictors of both treatment outcome and adherence among medicated adults with OCD undergoing EX/RP, and by evaluating adherence as a potential mediator of treatment outcome. The sample consisted of 121 adults with OCD who received a standard course of EX/RP over 8 weeks. Therapists rated patient adherence at each exposure session using the Patient EX/RP Adherence Scale. Potential predictors were identified based on existing literature and were tested individually; whether adherence mediated other significant predictors of outcome was tested in single mediation models. Greater patient adherence significantly predicted better treatment outcomes. Higher treatment expectancy and lower baseline avoidance significantly predicted greater adherence. Patient adherence fully mediated the relationship between treatment expectancy and treatment outcome, and also between baseline avoidance and treatment outcome. Patient adherence appears to be a key mechanism linking patient characteristics to EX/RP outcome. These findings underscore the importance of systematically monitoring and reinforcing adherence, proactively addressing avoidance, and enhancing treatment expectations to optimize treatment outcomes in EX/RP.
There is a lack of longitudinal research examining the relationships between internalising symptoms and well-being via functional impairment. Decentering is a malleable and clinically relevant characteristic that may disrupt the links among these constructs over time, but this is yet to be explored. A community sample (N = 386) completed monthly self-report surveys for 12 months, assessing internalising symptoms (depression, generalised anxiety, social anxiety, panic), impairment, well-being and decentering. Multilevel structural equation modelling was conducted to analyse the within-person association between symptoms and well-being mediated by impairment (in the same month and subsequent months), as well as a moderated-mediation model with decentering as the moderator (in the same month and as individual differences). Further, the mediation model was tested over time bidirectionally. Within a given month, higher levels of symptoms significantly predicted lower well-being via impairment, and prospective analyses revealed that these effects were bidirectional. Decentering significantly reduced the impact of one's symptoms on impairment on a given month and throughout the study, but not the impact of impairment on well-being. Thus, decentering was supported as a protective factor that reduces the link between symptoms and impairment. Further research is needed to uncover different ways to protect well-being, particularly because low well-being also predicted elevated symptoms over time. These novel findings indicate that the inverse cycle between symptoms and well-being may be maintained by impairment, but the short-term and cumulative effects of symptoms on impairment could be reduced by decentering. As such, impairment and decentering may be important therapeutic targets when aiming to promote well-being in the context of symptoms.
Low positive affect (i.e., PA) is a hallmark of depression commonly associated with maladaptive use of emotion regulation strategies and a low preference for PA states. Motivational models of emotion regulation propose that the use of emotion regulation strategies subserves the attainment of specific emotion goals. Yet, these associations have not been investigated in the context of daily life PA regulation in depression. The present study used a 7-day experience-sampling design in a sample of clinically depressed individuals (N = 65) to assess whether pro-hedonic goals aimed at either increasing PA or reducing negative affect (i.e., NA) were (1) prospectively associated with the deployment of specific regulatory strategies (i.e., distraction, reappraisal, acceptance) and (2) concurrently associated with the efficacy of those strategies in boosting positive and dampening negative affective states. Lagged multilevel models revealed distinct motivational signatures. Activating the goal to reduce NA prospectively predicted greater subsequent use of acceptance, which was in turn effective at improving affective states. Reappraisal was infrequently selected and showed no significant associations with pro-hedonic goals or later affect. While accounting for reappraisal and acceptance, distraction improved subsequent affect (i.e., increased PA, decreased NA) only when paired with a concurrent goal to increase PA, but resulted in the opposite pattern when this goal was absent. Future studies should assess a wider array of emotion goals and emotion regulation dynamics in depression, as well as the long-term adaptiveness of these interactions.
This study investigated whether a compliance-contingent, shortened time-out (TO) improves behavioral and emotional responses compared to a standard punishment-escalation TO among youth with conduct problems (CP) and varying callous-unemotional (CU) traits. Forty-six 7-12-year-olds in an 8-week summer treatment program completed a counterbalanced within-subject crossover: Standard TO (10-minute start; misbehavior doubled duration; fixed release criteria) vs. Modified TO (10-minute start; compliance enabled reduction to 5 minutes; additional supportive questions). Independent observers coded behavior and affect during TO episodes; staff logged TO characteristics. Analyses used zero-inflated negative binomial and mixed-effects models with covariates. Higher CU predicted fewer TO assignments but less compliance in the Standard TO condition. Contrary to predictions, the Modified TO condition showed higher aggression, lower compliance, and less calm behavior relative to Standard TO. Post-TO, higher CU was related to greater perceived aversiveness in Standard but not Modified TO. Making TO duration behaviorally negotiable did not enhance compliance and may signal rule flexibility for youth with CP and elevated CU traits. Findings of this study support emphasizing structured, consistent, non-negotiable consequences when treating youth with CP and CU.
Asian Americans are proportionately the fastest-growing racial group in the United States yet remain among the least likely to seek mental health services, often facing significant cultural and structural barriers. This state-of-the-science review synthesizes existing research on culturally adapted psychotherapy, with a focus on cognitive-behavioral therapy (CBT) for Asian American populations. Meta-analytic findings suggest that culturally adapted interventions, particularly those that utilize deep structural adaptations (e.g., those that incorporate cultural values, beliefs and worldviews), yield improved treatment outcomes compared to standard approaches or surface structure adaptations (e.g., more superficial modifications such as ethnic and linguistic match). However, few studies have examined culturally adapted CBT (CA-CBT) specifically for Asian Americans and much more work needs to be done. Future research needs to address several limitations and recommendations for future research are provided. Advancing CA-CBT is crucial for reducing health disparities and improving mental health outcomes by offering culturally relevant and effective services that may be more effective for diverse and underserved populations.
Engagement in nonsuicidal self-injury (NSSI) can be predicted by affective dynamics (e.g., variability, inertia, and intensity). However, little is known about affective dynamics in relation to NSSI urges that are not acted upon, a phenomenon worth further study given its high rate of occurrence. Such a phenomenon should be studied in real-time through ecological momentary assessment (EMA), given the varying durations and frequency of NSSI urges. The current study examined affective dynamics in relation to EMA-reported NSSI urges and compared affective dynamics among participants with only EMA-reported NSSI urges to those with both EMA-reported NSSI urges and any EMA-reported NSSI behaviors. The sample included 93 young adults (ages 18-34) with past-month NSSI urges or behaviors. Dynamic structural equation modeling (DSEM) was used to analyze between-person affective dynamics. Results showed that greater NSSI urges were associated with greater negative affect variability and intensity, and lower positive affect intensity. Further, individuals who engaged in any NSSI behavior had significantly higher negative affect variability and intensity than those who only reported NSSI urges (but not behaviors) during EMA, even when controlling for past month NSSI behaviors at baseline. This study has important implications for risk identification and later treatment of NSSI urges.
