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.

Investigating child self-report capacity: a systematic review and utility analysis.

PURPOSE: To identify and evaluate methods for assessing pediatric patient-reported outcome (PRO) data quality at the individual level. METHODS: We conducted a systematic literature review to identify methods for detecting invalid responses to PRO measures. Eight data quality indicators were applied to child-report data collected from 1780 children ages 8-11 years. We grouped children with similar data quality patterns and tested for between-group differences in factors hypothesized to influence self-report capacity. RESULTS: We identified 126 articles that described 494 instances in which special measures or statistical techniques were applied to evaluate data quality at the individual level. We identified 22 data quality indicator subtypes: 9 direct methods (require administration of special items) and 13 archival techniques (statistical procedures applied to PRO data post hoc). Application of archival techniques to child-report PRO data revealed 3 distinct patterns (or classes) of the data quality indicators. Compared to class 1 (56%), classes 2 (36%) and 3 (8%) had greater variation in their PRO item responses. Three archival indicators were especially useful for differentiating plausible item response variation (class 2) from statistically unlikely response patterns (class 3). Neurodevelopmental conditions, which are associated with a range of cognitive processing challenges, were more common among children in class 3. CONCLUSION: A multi-indicator approach is needed to identify invalid PRO responses. Once identified, assessment environments and measurement tools should be adapted to best support these individuals' self-report capacity. Individual-level data quality indicators can be used to gauge the effectiveness of these accommodations.

Beliefs about depression relate to active and avoidant coping in high-symptom adolescents.

BACKGROUND: Perceptions of personal attributes as less malleable are associated with more severe depression symptoms and less active coping in youth. Perceptions of depression itself as relatively fixed have been linked to more severe depression symptoms; however, it is not known how beliefs about depression relate to active and avoidant coping behaviors in particular. METHODS: We gathered information about beliefs about depression and activation and avoidance behaviors among 104 adolescents with high depression symptoms. The primary depression belief examined was prognostic pessimism, or the belief that depression is relatively permanent. We calculated correlations between this belief and activation and avoidance/rumination behaviors. RESULTS: Prognostic pessimism was negatively correlated with behavioral activation scores (r = -0.31; p = .001), and was positively correlated with behavioral avoidance/rumination scores (r = 0.30; p = .002). LIMITATIONS: This data was cross-sectional, and relied on self-report measures of depression beliefs and behaviors. CONCLUSIONS: Adolescents who believe that depression is relatively permanent might feel less motivated to engage in effortful activation behaviors, instead favoring avoidance. These results may help elucidate the ways in which malleability beliefs relate to mental health outcomes among adolescents, and highlight prognostic pessimism as a potential treatment target for reducing depressogenic behaviors.

Depression self-labeling in U.S. college students: Associations with perceived control and coping strategies.

BACKGROUND: Research on mental illness labeling has demonstrated that self-labeling (identifying with a mental illness label, e.g., "I have depression") is associated with internalized stigma, maladaptive responses to that stigma, and lower quality of life. However, research has not yet examined the link between self-labeling and how individuals cope with emotional distress. It is important to understand this relationship because adaptive and maladaptive methods of coping can lead to positive and negative mental illness outcomes. METHODS: This cross-sectional study examined the link between depression self-labeling, depression symptoms, and three constructs related to depression self-management (perceived control over depression, cognitive emotion regulation strategies, and help-seeking beliefs) in a large (N = 1423) sample of U.S. college students. RESULTS: Approximately one-fifth of students (22.2 %) self-labeled as having depression, while 39.0 % were estimated to meet diagnostic criteria for MDD. After controlling for depression symptom severity, self-labeling was associated with lower levels of perceived control over depression (p = .002), more catastrophizing (p = .013), less perspective taking, refocusing, reappraisal, and planning (ps < 0.05), and more positive help-seeking attitudes towards medication (p < .001) but not therapy. LIMITATIONS: Results are non-causal and may not generalize to non-college populations. CONCLUSIONS: Self-labeling may inform how individuals cope with emotional distress, with the potential for positive and negative effects on clinical outcomes. This is consistent with well-established research on self-labeling with regards to stigma, but extends this research in important new directions.

Causal beliefs about mental illness: A scoping review.

Research on causal beliefs about mental illness-the beliefs people hold about what causes a particular mental illness, or mental illnesses in general-is split across a number of theories and disciplines. Although research on this subject has provided a number of insights and practical applications, the diversity of theories, terminology, and keywords makes it challenging for a new reader to gain a comprehensive understanding. We sought to address this by conducting a systematic scoping review of research on causal beliefs. This review included English-language articles from any year that mentioned causal beliefs for mental illness in their title or abstract. We identified articles in two stages. In the first stage, we used a narrow set of search terms referring specifically to causal beliefs (1227 records identified, 417 included). In the second stage, we used a comprehensive set of terms relevant to research on causal beliefs (10,418 records identified, 3838 included). We analyzed articles qualitatively, organizing them into one of five theories or categories: the common-sense model of self-regulation, explanatory models, mental health literacy, biogenetic causal beliefs, and other research on causal beliefs. We provide a comprehensive summary of these literatures in terms of their history, typical research questions and study design, findings, and practical applications. These theories differ in their theoretical orientation towards causal beliefs, research methods, findings, and applications. However, they broadly share a view of causal beliefs as multifaceted, culturally determined, and relevant for additional psychosocial variables such as mental illness stigma and help-seeking. We conclude by making recommendations for researchers, clinicians, public health messaging, and for individuals with mental illness.

Brief School-Based Interventions Targeting Student Mental Health or Well-Being: A Systematic Review and Meta-Analysis.

Brief, school-based mental health interventions hold promise for reducing barriers to mental health support access, a critical endeavor in light of increasing rates of mental health concerns among youth. However, there is no consensus on whether or not brief school-based interventions are effective at reducing mental health concerns or improving well-being. This systematic review and meta-analysis aims to provide consensus and determine directions for future work. Articles were included if they examined a brief (≤ four sessions or 240 min of intervention time) psychosocial intervention, were conducted within a Pre-K through 12th-grade school setting, included at least one treatment outcome evaluating mental health or well-being, and were published since 2000. A total of 6,702 papers were identified through database searching, of which 81 papers (k studies = 75) were ultimately selected for inclusion. A total of 40,498 students were included across studies and a total of 75 unique interventions were examined. A total of 324 effect sizes were extracted. On average, interventions led to statistically significant improvements in mental health/well-being outcomes versus control conditions up to one-month (g = .18, p = .004), six-month (g = .15, p = .006), and one-year (g = .10, p = .03) post-intervention. There may be benefits to brief school-based interventions from a preventative public health standpoint; future research may focus on how to optimize their real-world utility. Prospero pre-registration: CRD42021255079.

Population mental health science: Guiding principles and initial agenda.

A recent American Psychological Association Summit provided an urgent call to transform psychological science and practice away from a solely individual-level focus to become accountable for population-level impact on health and mental health. A population focus ensures the mental health of all children, adolescents, and adults and the elimination of inequities across groups. Science must guide three components of this transformation. First, effective individual-level interventions must be scaled up to the population level using principles from implementation science, investing in novel intervention delivery systems (e.g., online, mobile application, text, interactive voice response, and machine learning-based), harnessing the strength of diverse providers, and forging culturally informed adaptations. Second, policy-driven community-level interventions must be innovated and tested, such as public efforts to promote physical activity, public policies to support families in early life, and regulation of corporal punishment in schools. Third, transformation is needed to create a new system of universal primary care for mental health, based on models such as Family Connects, Triple P, PROmoting School-community-university Partnerships to Enhance Resilience, Communities That Care, and the Early Childhood Collaborative of the Pittsburgh Study. This new system must incorporate valid measurement, universal screening, and a community-based infrastructure for service delivery. Addressing tasks ahead, including scientific creativity and discovery, rigorous evaluation, and community accountability, will lead to a comprehensive strategic plan to shape the emergent field of public mental health. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Adolescents' beliefs about what symptoms constitute depression: Are more expansive definitions helpful or harmful?

Purpose: What symptoms do people think constitute "depression"? In a mental health literacy framework, knowing more of depression's nine core symptoms (per formal psychiatric diagnostic criteria) is thought to help people identify and seek help for depression. However, the common-sense model of self-regulation suggests that more expansive beliefs about what symptoms constitute an illness may be maladaptive, whereby viewing more symptoms as characterizing a disorder predicts greater functional impairment. Methods: We collected data from N = 281 U.S. adolescents experiencing elevated depression symptoms, recruited via social media. Symptom beliefs were assessed descriptively and with a latent profile analysis to test associations with other variables. Results: Adolescents' beliefs about what symptoms constitute depression varied widely, and only 49% endorsed all DSM-5 depression symptoms as characterizing the disorder. Adolescents who identified more symptoms as belonging to depression had more severe depression symptoms (p = .004), reported more hopelessness (p = .021), and were more pessimistic about the permanence of depression (p = .007); they were also more likely to rate medication as potentially helpful (p = .001). Conclusion: These findings simultaneously support and challenge elements of both the common-sense model and the mental health literacy framework. Future research on mental health literacy may examine why adolescents with more psychiatrically-accurate understandings of depression experience worse clinical outcomes. Likewise, future research on the common sense model should explore whether more expansive depression symptom beliefs may be adaptive as well as maladaptive.

Loss of mental health support among college students during the COVID-19 pandemic.

Objective: The COVID-19 pandemic has simultaneously exacerbated mental health concerns among college students and made it more challenging for many students to access mental health support. However, little is known about the extent of mental health support loss among college students, or which students have lost support. Participants: 415 undergraduate students who reported receiving mental health support prior to the pandemic participated. Methods: Students completed an online questionnaire between March and May of 2020. Researchers examined the extent of support loss and how support loss differed by demographic and mental health variables. Methods pre-registered at https://osf.io/m83hz. Results: 62% of respondents reported loss of mental health support. Loss of support was associated with more severe depressive symptoms (p < .001), more severe anxiety symptoms (p < .001), suicidal ideation (p < .001), and sexual minority identity (p = .017). Conclusions: Loss of support was common, especially among more vulnerable students.

College student interest in teletherapy and self-guided mental health supports during the COVID-19 pandemic.

Objective The COVID-19 pandemic has worsened college students' mental health while simultaneously creating new barriers to traditional in-person care. Teletherapy and online self-guided mental health supports are two potential avenues for addressing unmet mental health needs when face-to-face services are less accessible, but little is known about factors that shape interest in these supports. Participants: 1,224 U.S. undergraduate students (mean age = 20.7; 73% female; 40% White) participated. Methods: Students completed an online questionnaire assessing interest in teletherapy and self-guided supports. Predictors included age, sex, race/ethnicity, sexual minority status, and anxiety and depression symptomatology. Results: Interest rates were 20% and 25% for at-cost supports (teletherapy and online self-help, respectively) and 70% and 72% for free supports (teletherapy and online self-help, respectively). Patterns emerged by age, anxiety symptom severity, and race/ethnicity. Conclusions: Results may inform universities' efforts to optimize students' engagement with nontraditional, digital mental health supports, including teletherapy and self-guided programs.The SARS-CoV2 (COVID-19) pandemic has taken a severe toll on public health, with effects reaching far beyond unprecedented illness and mortality. Levels of mental health difficulties appear to be rising broadly as the pandemic has progressed, both in the general U.S. population and among college students specifically.1,2 The COVID-19 pandemic and its repercussions may undermine college student mental health in myriad ways.2 Concurrently, students now face the potential for serious illness, loss of loved ones, financial strain, social isolation, loss of on-campus resources, and sudden disruption of routines-creating a "perfect storm" for the emergence or exacerbation of psychological distress.