Predictors of pharmacotherapy outcomes for body dysmorphic disorder: a machine learning approach.

BACKGROUND: Serotonin-reuptake inhibitors (SRIs) are first-line pharmacotherapy for the treatment of body dysmorphic disorder (BDD), a common and severe disorder. However, prior research has not focused on or identified definitive predictors of SRI treatment outcomes. Leveraging precision medicine techniques such as machine learning can facilitate the prediction of treatment outcomes. METHODS: The study used 10-fold cross-validation support vector machine (SVM) learning models to predict three treatment outcomes (i.e. response, partial remission, and full remission) for 97 patients with BDD receiving up to 14-weeks of open-label treatment with the SRI escitalopram. SVM models used baseline clinical and demographic variables as predictors. Feature importance analyses complemented traditional SVM modeling to identify which variables most successfully predicted treatment response. RESULTS: SVM models indicated acceptable classification performance for predicting treatment response with an area under the curve (AUC) of 0.77 (sensitivity = 0.77 and specificity = 0.63), partial remission with an AUC of 0.75 (sensitivity = 0.67 and specificity = 0.73), and full remission with an AUC of 0.79 (sensitivity = 0.70 and specificity = 0.79). Feature importance analyses supported constructs such as better quality of life and less severe depression, general psychopathology symptoms, and hopelessness as more predictive of better treatment outcome; demographic variables were least predictive. CONCLUSIONS: The current study is the first to demonstrate that machine learning algorithms can successfully predict treatment outcomes for pharmacotherapy for BDD. Consistent with precision medicine initiatives in psychiatry, the current study provides a foundation for personalized pharmacotherapy strategies for patients with BDD.

Mechanisms of cognitive-behavioral therapy effects on symptoms of body dysmorphic disorder: a network intervention analysis.

BACKGROUND: Body dysmorphic disorder (BDD) is a severe and undertreated condition. Although cognitive-behavioral therapy (CBT) is the first-line psychosocial treatment for this common disorder, how the intervention works is insufficiently understood. Specific pathways have been hypothesized, but only one small study has examined the precise nature of treatment effects of CBT, and no prior study has examined the effects of supportive psychotherapy (SPT). METHODS: This study re-examined a large trial (n = 120) comparing CBT to SPT for BDD. Network intervention analyses were used to explore symptom-level data across time. We computed mixed graphical models at multiple time points to examine relative differences in direct and indirect effects of the two interventions. RESULTS: In the resulting networks, CBT and SPT appeared to differentially target certain symptoms. The largest differences included CBT increasing efforts to disengage from and restructure unhelpful thoughts and resist BDD rituals, while SPT was directly related to improvement in BDD-related insight. Additionally, the time course of differences aligned with the intended targets of CBT; cognitive effects emerged first and behavioral effects second, paralleling cognitive restructuring in earlier sessions and the emphasis on exposure and ritual prevention in later sessions. Differences in favor of CBT were most consistent for behavioral targets. CONCLUSIONS: CBT and SPT primarily affected different symptoms. To improve patient care, the field needs a better understanding of how and when BDD treatments and treatment components succeed. Considering patient experiences at the symptom level and over time can aid in refining or reorganizing treatments to better fit patient needs.

Efficacy of App-Based Cognitive Behavioral Therapy for Body Dysmorphic Disorder with Coach Support: Initial Randomized Controlled Clinical Trial.

INTRODUCTION: Body dysmorphic disorder (BDD) is severe, chronic, and undertreated. Apps could substantially improve treatment access. OBJECTIVE: We provide an initial test of the usability and efficacy of coach-supported app-based cognitive behavioral therapy (CBT) for BDD. The Perspectives app covers core treatment components: psychoeducation, cognitive restructuring, exposure with response prevention, mindfulness, attention retraining, and relapse prevention. METHODS: A randomized waitlist-controlled trial was conducted. Adults (N = 80) with primary BDD were assigned to 12 weeks of Perspectives or waitlist. Coaches promoted engagement and answered questions via in-app messaging and phone calls. BDD severity was measured at baseline, mid-treatment, and end of treatment by blinded independent evaluators (Yale-Brown Obsessive Compulsive Scale Modified for BDD; BDD-YBOCS). Secondary outcomes included BDD-related insight, depression, quality of life, and functioning. RESULTS: App uptake and satisfaction were high. In intent-to-treat analyses, Perspectives app-based CBT was associated with significantly lower BDD-YBOCS severity at end of treatment (M [SD]: 16.8 [7.5]) compared to the waitlist (26.7 [6.2]; p < 0.001, d = 1.44). App-based CBT was associated with greater improvements across all secondary measures, with medium to large effects. CONCLUSIONS: Perspectives, supported by a bachelor's-level coach, is an efficacious, scalable treatment for adults with BDD.

Human Support in App-Based Cognitive Behavioral Therapies for Emotional Disorders: Scoping Review.

BACKGROUND: Smartphone app-based therapies offer clear promise for reducing the gap in available mental health care for people at risk for or people with mental illness. To this end, as smartphone ownership has become widespread, app-based therapies have become increasingly common. However, the research on app-based therapies is lagging behind. In particular, although experts suggest that human support may be critical for increasing engagement and effectiveness, we have little systematic knowledge about the role that human support plays in app-based therapy. It is critical to address these open questions to optimally design and scale these interventions. OBJECTIVE: The purpose of this study is to provide a scoping review of the use of human support or coaching in app-based cognitive behavioral therapy for emotional disorders, identify critical knowledge gaps, and offer recommendations for future research. Cognitive behavioral therapy is the most well-researched treatment for a wide range of concerns and is understood to be particularly well suited to digital implementations, given its structured, skill-based approach. METHODS: We conducted systematic searches of 3 databases (PubMed, PsycINFO, and Embase). Broadly, eligible articles described a cognitive behavioral intervention delivered via smartphone app whose primary target was an emotional disorder or problem and included some level of human involvement or support (coaching). All records were reviewed by 2 authors. Information regarding the qualifications and training of coaches, stated purpose and content of the coaching, method and frequency of communication with users, and relationship between coaching and outcomes was recorded. RESULTS: Of the 2940 titles returned by the searches, 64 (2.18%) were eligible for inclusion. This review found significant heterogeneity across all of the dimensions of coaching considered as well as considerable missing information in the published articles. Moreover, few studies had qualitatively or quantitatively evaluated how the level of coaching impacts treatment engagement or outcomes. Although users tend to self-report that coaching improves their engagement and outcomes, there is limited and mixed supporting quantitative evidence at present. CONCLUSIONS: Digital mental health is a young but rapidly expanding field with great potential to improve the reach of evidence-based care. Researchers across the reviewed articles offered numerous approaches to encouraging and guiding users. However, with the relative infancy of these treatment approaches, this review found that the field has yet to develop standards or consensus for implementing coaching protocols, let alone those for measuring and reporting on the impact. We conclude that coaching remains a significant hole in the growing digital mental health literature and lay out recommendations for future data collection, reporting, experimentation, and analysis.

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

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

Unique and predictive relationships between components of cognitive vulnerability and symptoms of depression.

BACKGROUND: Cognitive vulnerability theories of depression outline multiple, distinct inferential biases constitutive of cognitive vulnerability to depression. These include attributing negative events to internal, stable, and global factors, assuming that negative events will lead to further negative consequences, and inferring that negative events reflect negative characteristics about the self. Extant research has insufficiently examined these biases as distinct, limiting our understanding of how the individual cognitive vulnerability components interrelate and confer risk for depression symptoms. Thus, we conducted exploratory network analyses to examine the relationships among the five components of negative cognitive style and explore how components may differentially relate to depressive symptoms in adolescents. METHODS: Participants completed measures of negative cognitive style twice over a two-year period. We estimated Graphical Gaussian Models using contemporaneous data and computed a cross-lagged panel network using temporal data from baseline and 2-year follow-up. RESULTS: Results reveal interesting structural dynamics among facets of negative cognitive style and depressive symptoms. For example, results point to biases towards stable and future-oriented inferences as highly influential among negative cognitive style components. The temporal model revealed the internal attributions component to be heavily influenced by depressive symptoms among adolescents, whereas stable and global attributions most influenced future symptoms. CONCLUSIONS: This study presents novel approaches for investigating cognitive style and depression. From this perspective, perhaps more precise predictions can be made about how cognitive risk factors will lead to the development or worsening of psychopathology.

Less is more? Effects of exhaustive vs. minimal emotion labelling on emotion regulation strategy planning.

Previous research suggests that labelling emotions, or describing affective states using emotion words, facilitates emotion regulation. But how much labelling promotes emotion regulation? And which emotion regulation strategies does emotion labelling promote? Drawing on cognitive theories of emotion, we predicted that labelling emotions using fewer words would be less confusing and would facilitate forms of emotion regulation requiring more cognitively demanding processing of context. Participants (N = 82) mentally immersed themselves in an emotional vignette, were randomly assigned to an exhaustive or minimal emotion labelling manipulation, and then completed an emotion regulation strategy planning task. Minimal (vs. exhaustive) emotion labelling promoted higher subjective emotional clarity. Furthermore, in terms of specific emotion regulation strategies, minimal emotion labelling prompted more plans for problem solving and marginally more plans for reappraisal, but did not affect plans for behavioural activation or social support seeking. We discuss implications for the cognitive mechanisms supporting the generation of emotion regulation strategies.

Acute aerobic exercise helps overcome emotion regulation deficits.

Although colloquial wisdom and some studies suggest an association between regular aerobic exercise and emotional well-being, the nature of this link remains poorly understood. We hypothesised that aerobic exercise may change the way people respond to their emotions. Specifically, we tested whether individuals experiencing difficulties with emotion regulation would benefit from a previous session of exercise and show swifter recovery than their counterparts who did not exercise. Participants (N = 80) completed measures of emotion response tendencies, mood, and anxiety, and were randomly assigned to either stretch or jog for 30 minutes. All participants then underwent the same negative and positive mood inductions, and reported their emotional responses. Analyses showed that more perceived difficulty generating regulatory strategies and engaging in goal-directed behaviours after the negative mood induction predicted more intense and persistent negative affect in response to the stressor, as would be expected. Interactions revealed that aerobic exercise attenuated these effects. Moderate aerobic exercise may help attenuate negative emotions for participants initially experiencing regulatory difficulties. This study contributes to the literature on aerobic exercise's therapeutic effects with experimental data, specifically in the realm of emotional processing.

Medical burden in bipolar disorder: findings from the Clinical and Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study (Bipolar CHOICE).

OBJECTIVES: Individuals with bipolar disorder have high rates of other medical comorbidity, which is associated with higher mortality rates and worse course of illness. The present study examined common predictors of medical comorbidity. METHODS: The Clinical and Health Outcomes Initiative in Comparative Effectiveness for Bipolar Disorder study (Bipolar CHOICE) enrolled 482 participants with bipolar I or bipolar II disorder in a six-month, randomized comparative effectiveness trial. Baseline assessments included current and lifetime DSM-IV-TR diagnoses, demographic information, psychiatric and medical history, severity of psychiatric symptoms, level of functioning, and a fasting blood draw. Medical comorbidities were categorized into two groups: cardiometabolic (e.g., diabetes, hyperlipidemia, and metabolic syndrome) and non-cardiovascular (e.g., seizures, asthma, and cancer). Additionally, we looked at comorbid substance use (e.g., smoking and drug dependence). RESULTS: We found that 96.3% of participants had at least one other medical comorbidity. Older age predicted a greater likelihood of having a cardiometabolic condition. Early age of onset of bipolar symptoms was associated with a lower chance of having a cardiometabolic condition, but a greater chance of having other types of medical comorbidity. Additional predictors of other medical comorbidities in bipolar disorder included more time spent depressed, less time spent manic/hypomanic, and longer duration of illness. Medications associated with weight gain were associated with low high-density lipoprotein and abnormal triglycerides. CONCLUSIONS: There appears to be a substantial medical burden associated with bipolar disorder, highlighting the need for collaborative care among psychiatric and general medical providers to address both psychiatric and other medical needs concomitantly in this group of patients.

Eating behavior and obesity in bipolar disorder.

OBJECTIVES: Individuals with bipolar disorder are more frequently overweight or obese than the general population, but the reasons for this association are unknown. The aim of this study is to further understand the etiology of overweight and obesity in bipolar disorder. METHODS: We invited patients in a specialty outpatient bipolar clinic to complete the Eating Inventory. Patients provided self-reported restraint, disinhibition, and perceived hunger as well as general perceptions of dietary intake. RESULTS: Sixty-two individuals (37 female) between the ages of 18 and 67 (M = 41.5, SD = 13.38) and with an average body mass index (BMI) of 27.18 (SD = 5.71) completed the survey. Disinhibition and perceived hunger were positively correlated with BMI and self-reported difficulty eating healthy foods. Restraint was positively correlated with healthy eating (ps < .05). Stepwise linear regressions revealed that hunger was the most significant predictor of BMI (F(1) = 8.134, p = .006). Those participants with bipolar I or II disorder reported greater hunger scores (p < .01) and difficulty eating healthily (p < .05) than those without a full diagnosis. CONCLUSIONS: These results suggest that disinhibition and perception of hunger may be linked to the disproportionately high rate of obesity in bipolar disorder.

Lessons and Untapped Potential of Smartphone-Based Physical Activity Interventions for Mental Health: Narrative Review.

BACKGROUND: Physical activity has well-known and broad health benefits, including antidepressive and anxiolytic effects. However, only approximately half of Americans meet even the minimum exercise recommendations. Individuals with anxiety, depression, or related conditions are even less likely to do so. With the advent of mobile sensors and phones, experts have quickly noted the utility of technology for the enhanced measurement of and intervention for physical activity. In addition to being more accessible than in-person approaches, technology-driven interventions may uniquely engage key mechanisms of behavior change such as self-awareness. OBJECTIVE: This study aims to provide a narrative overview and specific recommendations for future research on smartphone-based physical activity interventions for psychological disorders or concerns. METHODS: In this paper, we summarized early efforts to adapt and test smartphone-based or smartphone-supported physical activity interventions for mental health. The included articles described or reported smartphone-delivered or smartphone-supported interventions intended to increase physical activity or reduce sedentary behavior and included an emotional disorder, concern, or symptom as an outcome measure. We attempted to extract details regarding the intervention designs, trial designs, study populations, outcome measures, and inclusion of adaptations specifically for mental health. In taking a narrative lens, we drew attention to the type of work that has been done and used these exemplars to discuss key directions to build on. RESULTS: To date, most studies have examined mental health outcomes as secondary or exploratory variables largely in the context of managing medical concerns (eg, cancer and diabetes). Few trials have recruited psychiatric populations or explicitly aimed to target psychiatric concerns. Consequently, although there are encouraging signals that smartphone-based physical activity interventions could be feasible, acceptable, and efficacious for individuals with mental illnesses, this remains an underexplored area. CONCLUSIONS: Promising avenues for tailoring validated smartphone-based interventions include adding psychoeducation (eg, the relationship between depression, physical activity, and inactivity), offering psychosocial treatment in parallel (eg, cognitive restructuring), and adding personalized coaching. To conclude, we offer specific recommendations for future research, treatment development, and implementation in this area, which remains open and promising for flexible, highly scalable support.

Impact of sleep disruption on BDD symptoms and treatment response.

BACKGROUND: Body dysmorphic disorder (BDD) is severe, undertreated, and relatively common. Although gold-standard cognitive behavioral therapy (CBT) for BDD has strong empirical support, a significant number of patients do not respond. More work is needed to understand BDD's etiology and modifiable barriers to treatment response. Given its high prevalence and impact on the development, maintenance, and treatment of related, frequently comorbid disorders, sleep disruption is a compelling, but not-yet studied factor. METHODS: Data were drawn from a randomized controlled trial of guided smartphone app-based CBT for BDD. Included participants were offered 12-weeks of treatment, immediately (n = 40) or after a 12-week waitlist (n = 37). Sleep disruption and BDD symptom severity were assessed at baseline, week-6, and week-12. RESULTS: Hypotheses and analysis plan were pre-registered. Two-thirds of patients reported significant insomnia symptoms at baseline. Baseline severity of sleep disruption and BDD symptoms were not related (r = 0.02). Pre-treatment sleep disruption did not predict BDD symptom reduction across treatment, nor did early sleep improvements predict greater BDD symptom improvement. Early BDD symptom improvement also did not predict later improvements in sleep. LIMITATIONS: Limitations include the small sample, restricted ranges of BDD symptom severity and treatment response, and few metrics of sleep disruption. CONCLUSIONS: Although insomnia was disproportionately high in this sample and both BDD symptoms and sleep improved in treatment, results suggest sleep and BDD symptoms may function largely independent of one another. More work is encouraged to replicate and better understand findings as well as potential challenges and benefits of addressing sleep in BDD.

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

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

The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder.

Background: Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions. However, little is known about how different patients may use coaching, what patterns correspond to meaningful outcomes, and how to match coaching to patient needs. Methods: Participants were 77 adults who received a 12-week guided smartphone CBT-BDD. Bachelor's-level coaches were available via asynchronous messaging. We analyzed the 400 messages sent by users to coaches during treatment. Message content was coded using the efficiency model of support (i.e., usability, engagement, fit, knowledge, and implementation). We aimed to clarify when and for what purposes patients with BDD used coaching, and if we can meaningfully classify patients by these patterns. We then assessed potential baseline predictors of coach usage, and whether distinct patterns relate to clinical outcomes. Results: Users on average sent 5.88 messages (SD = 4.51, range 1-20) and received 9.84 (SD = 5.74, range 2-30). Regarding frequency of sending messages, latent profile analysis revealed three profiles, characterized by: (1) peak mid-treatment (16.88 %), (2) bimodal/more communication early and late in treatment (10.39 %), and (3) consistent low/no communication (72.73 %). Regarding content, four profiles emerged, characterized by mostly (1) engagement (51.95 %), (2) fit (15.58 %), (3) knowledge (15.58 %), and (4) miscellaneous/no messages (16.88 %). There was a significant relationship between frequency profile and age, such that the early/late peak group was older than the low communication group, and frequency profile and adherence, driven by the mid-treatment peak group completing more modules than the low contact group. Regarding content, the engagement and knowledge groups began treatment with more severe baseline symptoms than the fit group. Content profile was associated with dropout, suggesting higher dropout rates in the miscellaneous/no contact group and reduced rates in the engagement group. There was no relationship between profile membership and other outcomes. Discussion: The majority of participants initiated little contact with their coach and the most common function of communications was to increase engagement. Results suggest that older individuals may prefer or require more support than younger counterparts early in treatment. Additionally, whereas individuals using coaching primarily for engagement may be at lower risk of dropping out, those who do not engage at all may be at elevated risk. Findings can support more personalized, data-driven coaching protocols and more efficient allocation of coaching resources.

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

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

One-carbon metabolism and bipolar disorder.

OBJECTIVE: Folate is one of the most widely used nutraceuticals for the treatment of mood disorders. In this article, we review folate metabolism, its relationship with bipolar disorder, and its therapeutic potential. METHODS: We searched PubMed and the Cochrane Library for relevant articles up to and including the year 2012. Background information, proposed mechanisms of action, and results from clinical trials were reviewed. RESULTS: Folate is an essential cofactor involved in methylation reactions, which are critical for monoamine synthesis and homocysteine regulation. Folate level is thought to be associated with mood disorders and limited response to antidepressants. Functional deficiency, due to a common genetic variant of the methylenetetrahydrofolate reductase (NAD(P)H) (MTHFR) gene, could also affect the presentation of bipolar disorder. Sodium valproate and lamotrigine, commonly used mood stabilizers for the treatment of bipolar disorder, can potentially interfere with folate and homocysteine metabolism. Previous studies consistently support the efficacy of folate in the treatment of depression; one study showed efficacy in the treatment of mania. Biologically active forms of folate formulations, which do not require biochemical conversion, could be beneficial in the treatment of bipolar disorder. CONCLUSIONS: Folate augmentation could be effective for the treatment of bipolar disorder. A common genetic variant of the MTHFR gene might impact the treatment effect of folate augmentation. The biologically active form of folate could potentially correct mood stabilizer-associated functional folate deficiency, help normalize monoamine synthesis, and improve outcomes.

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

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

Credibility and expectancy of smartphone-based cognitive behavioral therapy among adults with body dysmorphic disorder.

BACKGROUND: Few patients receive cognitive behavioral therapy, the gold-standard for body dysmorphic disorder (CBT-BDD). Smartphones can make evidence-based interventions, like CBT-BDD, more accessible and scalable. A key question is: how do patients view it? Low credibility and expectancy would likely translate to low uptake and engagement outside of research settings, diminishing the impact. Thus, it is important to understand patients' beliefs about digital CBT-BDD. METHODS: We compared credibility and expectancy in a coach-guided app-based CBT-BDD trial (N=75) to a previous in-person CBT-BDD trial (N = 55). We further examined the relationship of perceptions of digital CBT-BDD to baseline clinical and demographic factors and dropout. RESULTS: Credibility did not differ between the in-person (M=19.3) and digital (M=18.3) trials, p=.24. Expectancy for improvement was moderately higher for in-person (M=58.4) than digital (M=48.3) treatment, p=.005. In the digital trial, no demographic variables were associated with credibility or expectancy. Better BDD-related insight and past non-CBT BDD therapy were associated with greater expectancy. Credibility was associated with lower likelihood of dropout. DISCUSSION: Digital CBT-BDD was regarded as similarly credible to in-person CBT-BDD but with lower expectancy. Tailored expectancy-enhancing strategies could strengthen this novel approach, particularly among those with poorer insight and without prior BDD treatment.

Response and ongoing skills use following a single-session virtual cognitive behavioral workshop for graduate students.

OBJECTIVE: Graduate students frequently experience anxiety, depression, and psychological distress. Counseling centers struggle to meet this need. Brief, skills-based treatments to mitigate burgeoning or mild mental health problems could alleviate this problem. PARTICIPANTS: Participants were 51 graduate students in years one through seven of their respective programs. METHODS: We examined a single-session virtual cognitive behavioral workshop and outcomes up to 6-months later. RESULTS: The program was feasible, acceptable, and beneficial for mood, anxiety, and emotion regulation, even during the COVID-19 pandemic. A majority of participants reported ongoing skills use at follow-up. Primary barriers to more frequent use were forgetting, time constraints, and difficulty when experiencing strong emotions. Few participants endorsed expecting that skills would not be helpful or forgetting how to use skills. CONCLUSIONS: This intervention may provide scalable, much needed aid to graduate schools. Moreover, results highlight opportunities for further enhancing brief interventions.

Early response to cognitive behavioral therapy for body dysmorphic disorder as a predictor of outcomes.

Individuals with body dysmorphic disorder (BDD) suffer from distressing or impairing preoccupations with perceived imperfections in their appearance. This often-chronic condition is associated with significant functional impairment and elevated rates of psychiatric comorbidity and morbidity, including depression, substance use disorders, and suicidality. Cognitive behavioral therapy (CBT) for BDD has been shown to be efficacious. However, this intervention is long (up to 24 weeks) relative to many manualized approaches for other related conditions, there is a significant shortage of clinicians trained in CBT for BDD, and some patients drop out of treatment and/or do not respond. Thus, there is great interest in understanding and predicting who is most likely to respond, to better allocate clinical resources. This secondary data analysis of participants enrolled in prior uncontrolled and controlled studies of CBT for BDD explored whether early response to CBT, operationalized as percentage change in symptom severity within the first four weeks and the first 12 weeks of this 24-week treatment, predicts clinical outcomes for patients with BDD (n = 90). The findings indicated that minimal early symptom change was not indicative of eventual non-response. This suggests that patients and clinicians should not be discouraged by limited early improvement but should instead continue with a full course of treatment before reevaluating progress and alternative interventions. Overall, the results support the view that treatment success is more likely if a longer CBT protocol is followed. More work is needed to understand mechanisms of change and thus match optimal interventions to patient characteristics.