Evaluating a treatment selection approach for online single-session interventions for adolescent depression.

BACKGROUND: The question 'what works for whom' is essential to mental health research, as matching individuals to the treatment best suited to their needs has the potential to maximize the effectiveness of existing approaches. Digitally administered single-session interventions (SSIs) are effective means of reducing depressive symptoms in adolescence, with potential for rapid, large-scale implementation. However, little is known about which SSIs work best for different adolescents. OBJECTIVE: We created and tested a treatment selection algorithm for use with two SSIs targeting depression in high-symptom adolescents from across the United States. METHODS: Using data from a large-scale RCT comparing two evidence-based SSIs (N = 996; ClinicalTrials.gov: NCT04634903), we utilized a Personalized Advantage Index approach to create and evaluate a treatment-matching algorithm for these interventions. The two interventions were Project Personality (PP; N = 482), an intervention teaching that traits and symptoms are malleable (a 'growth mindset'), and the Action Brings Change Project (ABC; N = 514), a behavioral activation intervention. RESULTS: Results indicated no significant difference in 3-month depression outcomes between participants assigned to their matched intervention and those assigned to their nonmatched intervention. The relationship between predicted response to intervention (RTI) and observed RTI was weak for both interventions (r = .39 for PP, r = .24 for ABC). Moreover, the correlation between a participants' predicted RTI for PP and their predicted RTI for ABC was very high (r = .79). CONCLUSIONS: The utility of treatment selection approaches for SSIs targeting adolescent depression appears limited. Results suggest that both (a) predicting RTI for SSIs is relatively challenging, and (b) the factors that predict RTI for SSIs are similar regardless of the content of the intervention. Given their overall effectiveness and their low-intensity, low-cost nature, increasing youths' access to both digital SSIs may carry more public health utility than additional treatment-matching efforts.

Predicting Mental Health Treatment Access Among Adolescents With Elevated Depressive Symptoms: Machine Learning Approaches.

A large proportion of adolescents experiencing depression never access treatment. To increase access to effective mental health care, it is critical to understand factors associated with increased versus decreased odds of adolescent treatment access. This study used individual depression symptoms and sociodemographic variables to predict whether and where adolescents with depression accessed mental health treatments. We performed a pre-registered, secondary analysis of data from the 2017 National Survey of Drug Use and Health (NSDUH), a nationally representative sample of non-institutionalized civilians in the United States. Using four cross-validated random forest models, we predicted whether adolescents with elevated past-year depressive symptoms (N = 1,671; ages 12-17 years) accessed specific mental health treatments in the previous 12 months ("yes/no" for inpatient, outpatient, school, any). 53.38% of adolescents with elevated depressive symptoms accessed treatment of any kind. Even with depressive symptoms and sociodemographic factors included as predictors, pre-registered random forests explained < 0.00% of pseudo out-of-sample deviance in adolescent access to inpatient, outpatient, school, or overall treatments. Exploratory elastic net models explained 0.80-2.50% of pseudo out-of-sample deviance in adolescent treatment access across all four treatment types. Neither individual depressive symptoms nor any socioeconomic variables meaningfully predicted specific or overall mental health treatment access in adolescents with elevated past-year symptoms. This study highlights substantial limitations in our capacity to predict whether and where adolescents access mental health treatment and underscores the broader need for more accessible, scalable adolescent depression treatments.

Embracing Scientific Humility and Complexity: Learning "What Works for Whom" in Youth Psychotherapy Research.

Clinical psychological scientists have spent decades attempting to understand "what works for whom" in the context of youth psychotherapy, toward the longstanding goal of personalizing psychosocial interventions to fit individual needs and characteristics. However, as the articles in this Special Issue jointly underscore, more than 50 years of psychotherapy research has yet to help us realize this goal. In this introduction to the special issue, we outline how and why "aspiration-method mismatches" have hampered progress toward identifying moderators of youth psychotherapy; emphasize the need to embrace etiological complexity and scientific humility in pursuing new methodological solutions and propose individual and structural strategies for better-aligning clinical research methods with the goal of personalizing mental health care for youth with diverse identities and treatment needs.

Network analyses reveal which symptoms improve (or not) following an Internet intervention (Deprexis) for depression.

BACKGROUND: Depression is a heterogeneous collection of symptoms. Prior meta-analyses using symptom sum scores have shown the Internet intervention, Deprexis, to be an efficacious treatment for depression. However, no prior research has investigated how Deprexis (or any other Internet intervention for depression) impacts specific symptoms of depression. The current study utilizes symptom-level analyses to examine which symptoms are directly, indirectly, or minimally influenced by treatment. METHODS: Network analysis and mean-level approaches examined which symptoms, assessed by the Quick Inventory of Depression Symptoms, were affected by an 8-week course of Deprexis compared with a waitlist in a nationally recruited sample from the United States (N = 295). RESULTS: Deprexis directly improved the symptoms of sadness and indecision. Changes in these symptoms, in turn, was associated with a change in early insomnia, middle insomnia, self-dislike, fatigue, anhedonia, suicidality, slowness, and agitation. All of these symptoms (except for agitation and early insomnia) show decreases with Deprexis compared with a waitlist after correcting for multiple comparisons. Six additional symptoms, particularly the somatic symptoms, were not impacted by Deprexis compared with a waitlist. CONCLUSIONS: In this sample, the efficacy of Deprexis was due to its direct impact on sadness and indecision. Examining the treatment-related change in specific symptoms may facilitate a more nuanced understanding of how a treatment works compared with examining symptom sum scores. Symptom-level approaches may also identify symptoms that do not improve and provide important direction for future treatment development.

Getting Fewer "Likes" Than Others on Social Media Elicits Emotional Distress Among Victimized Adolescents.

Three studies examined the effects of receiving fewer signs of positive feedback than others on social media. In Study 1, adolescents (N = 613, Mage  = 14.3 years) who were randomly assigned to receive few (vs. many) likes during a standardized social media interaction felt more strongly rejected, and reported more negative affect and more negative thoughts about themselves. In Study 2 (N = 145), negative responses to receiving fewer likes were associated with greater depressive symptoms reported day-to-day and at the end of the school year. Study 3 (N = 579) replicated Study 1's main effect of receiving fewer likes and showed that adolescents who already experienced peer victimization at school were the most vulnerable. The findings raise the possibility that technology which makes it easier for adolescents to compare their social status online-even when there is no chance to share explicitly negative comments-could be a risk factor that accelerates the onset of internalizing symptoms among vulnerable youth.

Future Directions in Single-Session Youth Mental Health Interventions.

The United States spends more money on mental health services than any other country, yet access to effective psychological services remains strikingly low. The need-to-access gap is especially wide among children and adolescents, with up to 80% of youths with mental health needs going without services, and the remainder often receiving insufficient or untested care. Single-session interventions (SSIs) may offer a promising path toward improving accessibility, cost-effectiveness, and completion rates for youth mental health services. SSIs are structured programs that intentionally involve only one visit or encounter with a clinic, provider, or program; they may serve as stand-alone or adjunctive clinical services. A growing body of evidence supports the capacity of SSIs to reduce and prevent youth psychopathology of multiple types. Here, we provide a working definition of SSIs for use in future research and practice; summarize the literature to date on SSIs for child and adolescent mental health; and propose recommendations for the future design, evaluation, and implementation of SSIs across a variety of settings and contexts. We hope that this paper will serve as an actionable research agenda for gauging the full potential of SSIs as a force for youth mental health.

Does trauma-focused exposure therapy exacerbate symptoms among patients with comorbid PTSD and substance use disorders?

BACKGROUND: Although exposure-based therapy is a well-established, effective treatment for post-traumatic stress disorder (PTSD), some practitioners report reluctance to implement it due to concerns that it may exacerbate symptoms of PTSD and commonly comorbid disorders, such as substance use disorders (SUD). AIM: This study compared the exacerbation of psychological symptoms among participants with comorbid PTSD and SUD who received either SUD treatment alone or SUD treatment integrated with exposure therapy for PTSD. METHOD: Participants (N = 71) were treatment-seeking, military Veterans with comorbid PTSD and SUD who were randomized to 12 individual sessions of either (1) an integrated, exposure-based treatment (Concurrent Treatment of PTSD and Substance Use Disorders using Prolonged Exposure; COPE); or (2) a non-exposure-based, SUD-only treatment (Relapse Prevention; RP). We examined between-group differences in the frequency of statistically reliable exacerbations of PTSD, SUD and depression symptoms experienced during treatment. RESULTS: At each of the 12 sessions, symptom exacerbation was minimal and generally equally likely in either treatment group. However, an analysis of treatment completers suggests that RP participants experienced slightly more exacerbations of PTSD symptoms during the course of treatment. CONCLUSIONS: This study is the first to investigate symptom exacerbation throughout trauma-focused exposure therapy for individuals with comorbid PTSD and SUD. Results add to a growing literature which suggests that trauma-focused, exposure-based therapy does not increase the risk of symptom exacerbation relative to non-exposure-based therapy.

Using Network Analysis to Identify Central Symptoms of Adolescent Depression.

Experiencing depression symptoms, even at mild to moderate levels, is associated with maladaptive outcomes for adolescents. We used network analysis to evaluate which symptoms (and associations between symptoms) are most central to adolescent depression. Participants were part of a large, diverse community sample (N = 1,409) of adolescents between 13 and 19 years of age. Network analysis was used to identify the most central symptoms (nodes) and associations between symptoms (edges) assessed by the Children's Depression Inventory. We also evaluated these centrality indicators for network robustness using stability and accuracy tests, associated symptom centrality with mean levels of symptoms, and examined potential differences between the structure and connectivity of depression networks in boys and girls. The most central symptoms in the network were self-hatred, loneliness, sadness, and pessimism. The strongest associations between symptoms were sadness-crying, anhedonia-school dislike, sadness-loneliness, school work difficulty-school performance decrement, self-hatred-negative body image, sleep disturbance-fatigue, and self-deprecation-self-blame. The network was robust to stability and accuracy tests. Notably, symptom centrality and mean levels of symptoms were not associated. Boys and girls' networks did not differ in levels of connectivity, though the link between body image and self-hatred was stronger in girls than boys. Self-hatred, loneliness, sadness, and pessimism were the most central symptoms in adolescent depression networks, suggesting that these symptoms (and associations between symptoms) should be prioritized in theoretical models of adolescent depression and could also serve as important treatment targets for adolescent depression interventions.

Conversational assessment using artificial intelligence is as clinically useful as depression scales and preferred by users.

BACKGROUND: Depression is prevalent, chronic, and burdensome. Due to limited screening access, depression often remains undiagnosed. Artificial intelligence (AI) models based on spoken responses to interview questions may offer an effective, efficient alternative to other screening methods. OBJECTIVE: The primary aim was to use a demographically diverse sample to validate an AI model, previously trained on human-administered interviews, on novel bot-administered interviews, and to check for algorithmic biases related to age, sex, race, and ethnicity. METHODS: Using the Aiberry app, adults recruited via social media (N = 393) completed a brief bot-administered interview and a depression self-report form. An AI model was used to predict form scores based on interview responses alone. For all meaningful discrepancies between model inference and form score, clinicians performed a masked review to determine which one they preferred. RESULTS: There was strong concurrent validity between the model predictions and raw self-report scores (r = 0.73, MAE = 3.3). 90 % of AI predictions either agreed with self-report or with clinical expert opinion when AI contradicted self-report. There was no differential model performance across age, sex, race, or ethnicity. LIMITATIONS: Limitations include access restrictions (English-speaking ability and access to smartphone or computer with broadband internet) and potential self-selection of participants more favorably predisposed toward AI technology. CONCLUSION: The Aiberry model made accurate predictions of depression severity based on remotely collected spoken responses to a bot-administered interview. This study shows promising results for the use of AI as a mental health screening tool on par with self-report measures.

A randomized trial of online single-session interventions for adolescent depression during COVID-19.

The COVID-19 pandemic has potentially increased the risk for adolescent depression. Even pre-pandemic, <50% of youth with depression accessed care, highlighting needs for accessible interventions. Accordingly, this randomized controlled trial (ClinicalTrials.gov: NCT04634903 ) tested online single-session interventions (SSIs) during COVID-19 in adolescents with elevated depression symptoms (N = 2,452, ages 13-16). Adolescents from all 50 US states, recruited via social media, were randomized to one of three SSIs: a behavioural activation SSI, an SSI teaching that traits are malleable and a supportive control. We tested each SSI's effects on post-intervention outcomes (hopelessness and agency) and three-month outcomes (depression, hopelessness, agency, generalized anxiety, COVID-19-related trauma and restrictive eating). Compared with the control, both active SSIs reduced three-month depressive symptoms (Cohen's d = 0.18), decreased post-intervention and three-month hopelessness (d = 0.16-0.28), increased post-intervention agency (d = 0.15-0.31) and reduced three-month restrictive eating (d = 0.12-17). Several differences between active SSIs emerged. These results confirm the utility of free-of-charge, online SSIs for high-symptom adolescents, even in the high-stress COVID-19 context.

Symptom centrality and infrequency of endorsement identify adolescent depression symptoms more strongly associated with life satisfaction.

Although depression symptoms are often treated as interchangeable, some symptoms may relate to adolescent life satisfaction more strongly than others. To assess this premise, we first conducted a network analysis on the Mood and Feelings Questionnaire (MFQ) in a large (N = 1,059), cross-sectional sample of community adolescents (age M = 14.72 ± 1.79). The most central symptoms of adolescent depression, as indexed by strength, were self-hatred, loneliness, sadness, and worthlessness while the least frequently endorsed symptoms were self-hatred, anhedonia, feeling like a bad person, and feeling unloved. Moreover, the more central a depression symptom was in the network (i.e., higher strength), the more variance it shared with life satisfaction (r = 0.59, 95% CI: 0.27, 0.76). How frequently a symptom was endorsed was negatively associated with the variance symptoms shared with life satisfaction (r = -0.48, 95% CI: -0.63, -0.21). Cross-validated, prediction focused models found central symptoms were expected to predict more out of fold variance in life satisfaction than peripheral symptoms and frequently endorsed symptoms, but not the least frequently endorsed symptoms. These findings show certain depression symptoms may be more strongly associated with life satisfaction in adolescence and these symptoms can be identified by multiple symptom-level metrics. Limitations include use of cross-sectional data and utilizing a community sample. Better understanding which symptoms of depression share more variance with important outcomes like life satisfaction could help us develop a more fine-grained understanding of adolescent depression.

Harnessing Wise Interventions to Advance the Potency and Reach of Youth Mental Health Services.

Despite progress in research on evidence-based treatments (EBTs) for youth psychopathology, many youths with mental health needs do not receive services, and EBTs are not always effective for those who access them. Wise interventions (WIs) may help address needs for more disseminable, potent youth mental health interventions. WIs are single-component, social-psychological interventions designed to foster adaptive meaning-making. They have improved health-related and interpersonal youth outcomes, yet their potential to reduce youth psychopathology has not been systematically explored. Accordingly, we conducted a systematic, descriptive review characterizing WIs' potential to reduce youth mental health problems. Across 25 RCTs (N = 9219 youths, ages 11-19) testing 13 intervention types, 7 WIs qualified as "Well-Established," "Probably Efficacious," or "Possibly Efficacious" for reducing one or more types of youth psychopathology, relative to controls. Among these, 5 WIs significantly reduced youth depressive symptoms; 3, general psychological distress; and 1 each, eating problems, anxiety, and substance use. Three of these 7 WIs were self-administered by youths, and four by trained interventionists; collectively, they were 30-168 min in length and targeted clinic-referred and non-referred samples in clinical, school, and laboratory settings. Overall, certain WIs show promise in reducing mild-to-severe youth psychopathology. Given their brevity and low cost relative to traditional (i.e., therapist-delivered, 12- to 16-week, clinic-based) EBTs, WIs may represent beneficial additions to the youth mental healthcare ecosystem. Priorities for future research are proposed, including testing WIs for parents, younger children, and externalizing problems; as EBT adjuncts; and in schools and primary care clinics to increase access to brief, effective supports.

Contributions of fixed mindsets and hopelessness to anxiety and depressive symptoms: A commonality analysis approach.

BACKGROUND: Fixed mindsets (beliefs that personal traits are unchangeable) show consistent associations with internalizing symptoms. However, the mindset-internalizing symptom link has previously been studied in isolation of other maladaptive cognitions that relate to internalizing symptoms. Thus, the unique contributions of mindsets to internalizing symptoms remains unclear. METHOD: We used commonality analysis (CA), which yields unique and shared effects of independent variables on an outcome, to assess unique contributions of emotion and anxiety mindsets to anxiety and depression symptoms, relative to the contributions of hopelessness. Participants in two online studies (Ns=200, 430) self-reported depression and anxiety symptoms, hopelessness, and emotion and anxiety mindsets. RESULTS: In Study 1, neither mindset type contributed unique variance to depression or anxiety beyond the contribution of hopelessness. In Study 2, emotion mindsets again explained no unique symptom variance. Anxiety mindsets uniquely contributed 2.0% and 6.5% of depression and anxiety variance, respectively-but far larger proportions of symptom variance (20.0%-60.9%) were contributed by hopelessness alone, variance shared by hopelessness and anxiety mindsets, and variance shared among hopelessness, anxiety mindsets, and emotion mindsets. LIMITATIONS: The cross-sectional design precludes causal conclusions, and the non-referred adult samples may limit generalizability. DISCUSSION: Mindsets contributed little unique variance to internalizing symptoms beyond hopelessness. Interventions teaching growth mindsets have been shown to reduce internalizing problem in past studies. However, these interventions might not necessarily operate by shaping mindsets; rather, they may affect symptom change by shaping closely-linked maladaptive cognitions-like hopelessness-with stronger ties to internalizing distress.

Acceptability and Utility of an Open-Access, Online Single-Session Intervention Platform for Adolescent Mental Health.

BACKGROUND: Many youths with mental health needs are unable to access care. Single-session interventions (SSIs) have helped reduce youth psychopathology across multiple trials, promising to broaden access to effective, low-intensity supports. Online, self-guided SSIs may be uniquely scalable, particularly if they are freely available for as-needed use. However, the acceptability of online SSI and their efficacy have remained unexamined outside of controlled trials, and their practical utility is poorly understood. OBJECTIVE: We evaluated the perceived acceptability and proximal effects of Project YES (Youth Empowerment & Support), an open-access platform offering three online SSIs for youth internalizing distress. METHODS: After selecting one of three SSIs to complete, participants (ages 11-17 years) reported pre- and post-SSI levels of clinically relevant outcomes that SSIs may target (eg, hopelessness, self-hate) and perceived SSI acceptability. User-pattern variables, demographics, and depressive symptoms were collected to characterize youths engaging with YES. RESULTS: From September 2019 through March 2020, 694 youths accessed YES, 539 began, and 187 completed a 30-minute, self-guided SSI. SSI completers reported clinically elevated depressive symptoms, on average, and were diverse on several dimensions (53.75% non-white; 78.10% female; 43.23% sexual minorities). Regardless of SSI selection, completers reported pre- to post-program reductions in hopelessness (dav=0.53; dz=0.71), self-hate (dav=0.32; dz=0.61), perceived control (dav=0.60; dz=0.72) and agency (dav=0.39; dz=0.50). Youths rated all SSIs as acceptable (eg, enjoyable, likely to help peers). CONCLUSIONS: Results support the perceived acceptability and utility of open-access, free-of-charge SSIs for youth experiencing internalizing distress. TRIAL REGISTRATION: Open Science Framework; osf.io/e52p3.

Virtual Reality and Web-Based Growth Mindset Interventions for Adolescent Depression: Protocol for a Three-Arm Randomized Trial.

BACKGROUND: Depression is the leading cause of disability in youth, with a global economic burden of US >$210 billion annually. However, up to 70% of youth with depression do not receive services. Even among those who do access treatment, 30% to 65% fail to respond and many dropout prematurely, demonstrating a need for more potent, accessible interventions. In a previous trial, a single-session Web-based growth mindset (GM) intervention significantly reduced depressive symptoms in high-symptom adolescents; however, this intervention did not benefit adolescents uniformly. For instance, the intervention reduced depression in adolescents who reported post intervention increases in perceived control, but it did not lead to significant depression reductions in adolescents who reported no significant post intervention increases in perceived control. OBJECTIVE: The goal of this project is to test the acceptability and efficacy of a novel, single-session, virtual reality (VR) depression intervention-the VR Personality Project-teaching GM, the belief that personal attributes are malleable rather than fixed. The VR Personality Project was designed to systematically target and increase adolescents' perceived control by offering a more immersive, engaging, user-directed intervention experience than the Web-based intervention can provide. By targeting an identified predictor of intervention response, the VR Personality Project may lead to larger reductions in depressive symptoms than existing Web-based mindset interventions. METHODS: Adolescents with elevated depressive symptoms or a recent history of depression (N=159; ages 12 to 16 years) will be randomized to one of 3 intervention conditions: the VR Personality Project; the Web-based GM intervention tested previously; or an active, Web-based control. Adolescents and their parents will report on the adolescents' depression symptoms, perceived control, and related domains of functioning at preintervention, postintervention, and at 3- and 9-month follow-up assessments. RESULTS: We predict that the VR and Web-based mindset interventions will both lead to larger reductions in adolescent symptoms than the control intervention. Additionally, we predict that the VR-based single session intervention will lead to larger reductions in depression than the online mindset intervention and that these symptom reductions will be mediated by increases in adolescents' perceived control from pre- to postintervention. CONCLUSIONS: The results may suggest an efficient strategy for reducing adolescent depressive symptoms: One that is mechanism-targeted, relatively affordable (less than US $200 for a commercially available VR headset, a fraction of the cost of long-term psychotherapy) and potentially engaging to adolescents experiencing mood-related distress. TRIAL REGISTRATION: ClinicalTrials.gov NCT0385881; https://clinicaltrials.gov/ct2/show/NCT03858881 (Archived by WebCite at http://www.webcitation.org/78C3roDgA). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13368.

Association between negative cognitive bias and depression: A symptom-level approach.

Cognitive models of depression posit that negatively biased self-referent processing and attention have important roles in the disorder. However, depression is a heterogeneous collection of symptoms and all symptoms are unlikely to be associated with these negative cognitive biases. The current study involved 218 community adults whose depression ranged from no symptoms to clinical levels of depression. Random forest machine learning was used to identify the most important depression symptom predictors of each negative cognitive bias. Depression symptoms were measured with the Beck Depression Inventory-II. Model performance was evaluated using predictive R-squared (Rpred2), the expected variance explained in data not used to train the algorithm, estimated by 10 repetitions of 10-fold cross-validation. Using the self-referent encoding task (SRET), depression symptoms explained 34% to 45% of the variance in negative self-referent processing. The symptoms of sadness, self-dislike, pessimism, feelings of punishment, and indecision were most important. Notably, many depression symptoms made virtually no contribution to this prediction. In contrast, for attention bias for sad stimuli, measured with the dot-probe task using behavioral reaction time (RT) and eye gaze metrics, no reliable symptom predictors were identified. Findings indicate that a symptom-level approach may provide new insights into which symptoms, if any, are associated with negative cognitive biases in depression. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Making Friends With Yourself: A Mixed Methods Pilot Study of a Mindful Self-Compassion Program for Adolescents.

The aims of this mixed-method pilot study were to determine the feasibility, acceptability, and preliminary psychosocial outcomes of "Making Friends with Yourself: A Mindful Self-Compassion Program for Teens" (MFY), an adaptation of the adult Mindful Self-Compassion program. Thirty-four students age 14-17 enrolled in this waitlist controlled crossover study. Participants were randomized to either the waitlist or intervention group and administered online surveys at baseline, after the first cohort participated in the intervention, and after the waitlist crossovers participated in the intervention. Attendance and retention data were collected to determine feasibility, and audiorecordings of the 6-week class were analyzed to determine acceptability of the program. Findings indicated that MFY is a feasible and acceptable program for adolescents. Compared to the waitlist control, the intervention group had significantly greater self-compassion and life satisfaction and significantly lower depression than the waitlist control, with trends for greater mindfulness, greater social connectedness and lower anxiety. When waitlist crossovers results were combined with that of the first intervention group, findings indicated significantly greater mindfulness and self-compassion, and significantly less anxiety, depression, perceived stress and negative affect post-intervention. Additionally, regression results demonstrated that self-compassion and mindfulness predicted decreases in anxiety, depression, perceived stress, and increases in life satisfaction post-intervention. MFY shows promise as a program to increase psychosocial wellbeing in adolescents through increasing mindfulness and self-compassion. Further testing is needed to substantiate the findings.