Translating basic psychopathology research to preventive interventions: a tribute to john R. Z. Abela

The development and validation of an algorithm to predict future depression onset in unselected youth

BACKGROUND

Universal depression screening in youth typically focuses on strategies for identifying current distress and impairment. However, these protocols also play a critical role in primary prevention initiatives that depend on correctly estimating future depression risk. Thus, the present study aimed to identify the best screening approach for predicting depression onset in youth.

METHODS

Two multi-wave longitudinal studies (N = 591, AgeM = 11.74; N = 348, AgeM = 12.56) were used as the 'test' and 'validation' datasets among youth who did not present with a history of clinical depression. Youth and caregivers completed inventories for depressive symptoms, adversity exposure (including maternal depression), social/academic impairment, cognitive vulnerabilities (rumination, dysfunctional attitudes, and negative cognitive style), and emotional predispositions (negative and positive affect) at baseline. Subsequently, multi-informant diagnostic interviews were completed every 6 months for 2 years.

RESULTS

Self-reported rumination, social/academic impairment, and negative affect best predicted first depression onsets in youth across both samples. Self- and parent-reported depressive symptoms did not consistently predict depression onset after controlling for other predictors. Youth with high scores on the three inventories were approximately twice as likely to experience a future first depressive episode compared to the sample average. Results suggested that one's likelihood of developing depression could be estimated based on subthreshold and threshold risk scores.

CONCLUSIONS

Most pediatric depression screening protocols assess current manifestations of depressive symptoms. Screening for prospective first onsets of depressive episodes can be better accomplished via an algorithm incorporating rumination, negative affect, and impairment.

Screening for and Personalizing Prevention of Adolescent Depression

Depression is a prevalent, distressing, often recurrent, disorder. Adolescence represents a vulnerable developmental period when rates of depression surge and many experience their first episode. Some professional agencies now recommend universal screening starting at age 12. This paper advocates for a risk-based approach to screening for adolescent depression that can improve upon current approaches to screening and facilitate more seamless connections to enable personalizing prevention of depression based on risk group classification. Empirical examples are reviewed for screening based on established risk factors that predict later depression. Evidence is provided that risk groups can reliably and validly classify adolescents at risk for future development of depression based on cognitive and interpersonal vulnerabilities. These risk groups inform one approach to personalizing prevention of depression by matching youths' risk to established, evidence-based prevention programs (cognitive or interpersonal). Promising data from a randomized trial suggest that this personalized depression prevention strategy can reduce depression better than a "one size fits all" approach.

Translating Cognitive Vulnerability Theory Into Improved Adolescent Depression Screening: A Receiver Operating Characteristic Approach

Traditionally, screening research tests how well a given symptom inventory can identify a concurrent depressive episode. Although developmental psychopathology could inform screening protocols for a myriad of depression outcomes (e.g., prospective depressive episodes), approaches typically used in research make it difficult to translate these findings. Using a translational analytic approach and multiwave longitudinal study design, we examined how screening for cognitive vulnerabilities (rumination, dysfunctional attitudes, and attributional style) may improve our ability to identify concurrent depressive episodes, prospective depressive episodes, first lifetime episodes of depression, and recurrent major depressive episodes. There were 473 sixth-grade (early adolescents) and ninth-grade (middle adolescents; AgeM = 13.15, AgeSD = 1.62) students who completed baseline self-report cognitive vulnerability and depressive symptom measures. At baseline and every 6 months for 3 years, pediatric depression interviews were completed by the caregiver and youth. A receiver operating characteristic (ROC) approach was utilized to test our aims. Distinct algorithms best forecasted our depression outcomes. Rumination and attributional style emerged as unique and incrementally valid predictors for prospective episodes after controlling for baseline depressive symptoms. Rumination was the only unique predictor for first lifetime depressive episodes. For recurrent major depression, rumination in early adolescence and attributional style in middle adolescence served as incremental predictors beyond baseline depressive symptoms. Proposed cutoffs and diagnostic likelihood ratios are offered for algorithms for each depression outcome. Assessing cognitive vulnerability represents a feasible method to improve depression screening initiatives. Using an ROC-informed approach can help prevention initiatives better leverage the considerable gains made within developmental psychopathology research.

A multimethod screening approach for pediatric depression onset: An incremental validity study

OBJECTIVE

Screening protocols that rely on a single informant are inadequate in predicting pediatric depression. Multi-informant and risk factor screening approaches are potentially more sensitive methods for identifying depression risk, but the incremental validity of these protocols has not been adequately tested. Using a translational analytic approach and multimethod, longitudinal study design, we simultaneously tested several multi-indicator approaches to depression screening to identify an optimal algorithm for predicting depression onset in youth.

METHOD

Participants were 222 never-depressed children and adolescents (M_age = 10.75 years old, SD_age = 1.85; female = 50.45%; 82.88% White), who completed baseline questionnaires for depressive symptoms and cognitive vulnerabilities, in addition to a morphed face task to assess pupil dilation. Mothers, meanwhile, completed baseline questionnaires and a semistructured interview to assess maternal and pediatric depression. Follow-up depression diagnostic assessments with both the mother and youth occurred every 6 months for 2 years. Receiver operating characteristics and reclassification analyses were used to test our aims.

RESULTS

Overall, we found moderate support for a multi-informant approach, and convincing evidence that individual differences in pupil dilation uniquely predicted depression onset. Youth with subthreshold depressive symptoms and elevated pupil dilation were over twice as likely to develop a first lifetime episode of depression compared to one's risk rate based on sex and age.

CONCLUSIONS

Our study provides one of the first screening batteries for detecting first lifetime episodes of depression in youth. The unique and incremental validity provided by pupil dilation suggests feasible biological indicators of depression risk can improve primary prevention efforts that target depression, such as universal pediatric depression screening. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Affective, biological, and cognitive predictors of depressive symptom trajectories in adolescence

Heterogeneity in the longitudinal course of depressive symptoms was examined using latent growth mixture modeling among a community sample of 382 U.S. youth from ages 11 to 18 (52.1 % female). Three latent trajectory classes were identified: Stable Low (51 %; displayed low depressive symptoms at all assessments), Increasing (37 %; reported low depressive symptoms at age 11, but then significantly higher depressive symptoms than the Stable Low class at ages 13, 15, and 18), and Early High (12 %; reported high early depressive symptoms at age 11, followed by symptoms that declined over time yet remained significantly higher than those of the Stable Low class at ages 13, 15, and 18). By age 15, rates of Major Depressive Disorder diagnoses among the Early High (25.0 %) and Increasing (20.4 %) classes were more than twice that observed among the Stable Low class (8.8 %). Affective (negative affectivity), biological (pubertal timing, sex) and cognitive (cognitive style, rumination) factors were examined as predictors of class membership. Results indicated general risk factors for both high-risk trajectories as well as specific risk factors unique to each trajectory. Being female and high infant negative affectivity predicted membership in the Increasing class. Early puberty, high infant negative affectivity for boys, and high rumination for girls predicted membership in the Early High class. Results highlight the importance of examining heterogeneity in depression trajectories in adolescence as well as simultaneously considering risk factors across multiple domains.

Genetic and environmental influences on adolescent rumination and its association with depressive symptoms

Rumination is an important cognitive vulnerability for adolescent and adult depression. However, little is known about the aetiological origins of rumination, as well as its association with depression. Adolescent rumination (self-report) and depressive symptoms (self- and parent-report) were assessed in 674 pairs of same-gender Chinese adolescent twins (11-17 years of age). Females accounted for 53.7 % of the sample. There were significant correlations between self-reported rumination and self-reported depression (r = 0.41), as well as parent-reported adolescent depression (r = 0.22). Genetic influences were significant and modest on all three measures, ranging from 24 % to 42 %. The three measures were also significantly influenced by shared environment, ranging from 20 % to 28 %, and non-shared environmental factors, ranging from 30 % to 56 %. Moreover, the genetic correlations between rumination and depression were significant (within-rater: r(g) = 0.99; cross-rater: r(g) = 0.59) and largely accounted for the phenotypic correlations (within-rater: 68 %; cross-rater: 77 %), while non-shared environmental correlations were also significant (within-rater: r(e) = 0.26; cross-rater: r(e) = 0.12) and accounted for the remainder of the phenotypic correlations (within-rater: 32 %; cross-rater: 23 %). The shared environmental correlations were non-significant. No significant gender and age differences were found in aetiological models. These findings suggest that rumination may be an endophenotype reflecting genetic risk for depression.