We conducted a meta-analysis on the effects of mobile technology on treatment outcome for psychotherapy and other behavioral interventions. Our search of the literature resulted in 26 empirical articles describing 25 clinical trials testing the benefits of smartphone applications, PDAs, or text messaging systems either to supplement treatment or substitute for direct contact with a clinician. Overall, mobile technology use was associated with superior treatment outcome across all study designs and control conditions, ES = .34, p < .0001. For the subset of 10 studies that looked specifically at the added benefit of mobile technology using a rigorous “Treatment” versus “Treatment + Mobile” design, effect sizes were only slightly more modest (ES = .27) and still significant (p < .05). Overall, the results support the role of mobile technology for the delivery of psychotherapy and other behavioral interventions.

Anxious youth are at heightened risk for subsequent development of depression; however, little is known regarding which anxious youth are at the highest prospective risk. Biased attentional patterns (e.g., vigilance and avoidance of negative cues) are implicated as key mechanisms in both anxiety and depression. Aberrant attentional patterns may disrupt opportunities to effectively engage with, and learn from, threatening aspects of the environment during development and/or treatment, compounding risk over time. Sixty-seven anxious youth (age 9–14; 36 female) completed a dot-probe task to assess baseline attentional patterns provoked by fearful-neutral face pairs. The time course of attentional patterns both during and after threat was assessed via eyetracking and pupilometry. Self-reported depressive and anxiety symptoms were assessed two years after the conclusion of a larger psychotherapy treatment trial. Eyetracking patterns indicative of threat avoidance predicted greater 2-year depression scores, over and above baseline and post-treatment symptoms. Sustained, post-threat pupillary avoidance (reflecting preferential neural engagement with the neutral relative to the previously threatening location) predicted additional variance in depression scores, suggesting sustained avoidance in the wake of threat further exacerbated risk. Identical eyetracking and pupil indices were not predictive of anxiety at 2 years. These biobehavioral markers imply that avoidant attentional processing in the context of anxiety may be a gateway to depression across a key maturational window. Excessive avoidance of threat could interfere with acquisition of adaptive emotion regulation skills during development, culminating in the broad behavioral deactivation that typifies depression. Prevention efforts explicitly targeting avoidant attentional patterns may be warranted.

Cognitive behavioral therapy (CBT) is an efficacious treatment for child anxiety disorders, but 40-50% of youth do not respond fully to treatment, and time commitments for standard CBT can be prohibitive for some families and lead to long waiting lists for trained CBT therapists in the community. SmartCAT 2.0 is an adjunctive mobile health program designed to improve and shorten CBT treatment for anxiety disorders in youth by providing them with the opportunity to practice CBT skills outside of session using an interactive and gamified interface. It consists of an app and an integrated clinician portal connected to the app for secure 2-way communication with the therapist. The goal of the present study was to evaluate SmartCAT 2.0 in an open trial to establish usability, feasibility, acceptability, and preliminary efficacy of brief (8 sessions) CBT combined with SmartCAT. We also explored changes in CBT skills targeted by the app. Participants were 34 youth (ages 9-14) who met DSM-5 criteria for generalized, separation, and/or social anxiety disorder. Results demonstrated strong feasibility and usability of the app/ portal and high satisfaction with the intervention. Youth used the app an average of 12 times between each therapy session (M = 5.8 mins per day). At post-treatment, 67% of youth no longer met diagnostic criteria for an anxiety disorder, with this percentage increasing to 86% at twomonth follow-up. Youth showed reduced symptom severity over time across raters and also improved from pre-to post-treatment in CBT skills targeted by the app, demonstrating better emotion identification and thought challenging and reductions in avoidance. Findings support the feasibility of combining brief CBT with SmartCAT. Although not a controlled trial, when benchmarked against the literature, the current findings suggest that SmartCAT may enhance the utility of brief CBT for childhood anxiety disorders.

Several methodological challenges affect the study of typical brain development based on resting state blood oxygenation level dependent (BOLD) functional MRI (fMRI). One such challenge is mitigating artifacts such as those from head motion, known to be more substantial in younger subjects than older subjects. Other challenges include controlling for potential age-dependence in cerebrospinal fluid (CSF) volume affecting anatomical-functional coregistration; in vascular density affecting BOLD contrast-to-noise; and in CSF pulsation creating time series artifacts. Historically, these confounds have been approached through incorporating artifact-specific temporal and/or spatial filtering into preprocessing pipelines. However, such paths often come with new confounds or limitations. In this study we take the approach of a bottom-up revision of fMRI methodology based on acquisition of multi-echo fMRI and comprehensive utilization of the information in the TE-domain to enhance several aspects of fMRI analysis in the context of a developmental study. We show in a cohort of 25 healthy subjects, aged 9 to 43 years, that the analysis of multi-echo fMRI data eliminates a number of arbitrary processing steps such as bandpass filtering and spatial smoothing, while enabling procedures such as [Formula: see text] mapping, BOLD contrast normalization and signal dropout recovery, precise anatomical-functional coregistration based on [Formula: see text] measurements, automatic denoising through removing subject motion, scanner-related signal drifts and physiology, as well as statistical inference for seed-based connectivity. These enhancements are of both theoretical significance and practical benefit in the study of typical brain development.

Age-related changes in human functional neuroanatomy are poorly understood. This is partly due to the limits of interpretation of standard fMRI. These limits relate to age-related variation in noise levels in data from different subjects, and the common use of standard adult brain parcellations for developmental studies. Here we used an emerging MRI approach called multiecho (ME)-fMRI to characterize functional brain changes with age. ME-fMRI acquires blood oxygenation level-dependent (BOLD) signals while also quantifying susceptibility-weighted transverse relaxation time (T*) signal decay. This approach newly enables reliable detection of BOLD signal components at the subject level as opposed to solely at the group-average level. In turn, it supports more robust characterization of the variability in functional brain organization across individuals. We hypothesized that BOLD components in the resting state are not stable with age, and would decrease in number from adolescence to adulthood. This runs counter to the current assumptions in neurodevelopmental analyses of brain connectivity that the number of BOLD signal components is a random effect. From resting-state ME-fMRI of 51 healthy subjects of both sexes, between 8.3 and 46.2 years of age, we found a highly significant ( = -0.55, ≪ 0.001) exponential decrease in the number of BOLD components with age. The number of BOLD components were halved from adolescence to the fifth decade of life, stabilizing in middle adulthood. The regions driving this change were dorsolateral prefrontal cortices, parietal cortex, and cerebellum. The functional network of these regions centered on the cerebellum. We conclude that an age-related decrease in BOLD component number concurs with the hypothesis of neurodevelopmental integration of functional brain activity. We show evidence that the cerebellum may play a key role in this process. Human brain development is ongoing from childhood to at least 30 years of age. Functional MRI (fMRI) is key for characterizing changes in brain function that accompany development. However, developmental fMRI studies have relied on reference maps of adult brain organization in the analysis of data from younger subjects. This approach may limit the characterization of functional activity patterns that are particular to children and adolescents. Here we used an emerging fMRI approach called multi-echo fMRI that is not susceptible to such biases when analyzing the variation in functional brain organization over development. We hypothesized an integration of the components of brain activity over development, and found that the number of components decreases exponentially, halving from 8 to 35 years of age. The brain regions most affected underlie executive function and coordination. In summary, we show major changes in the organization and integration of functional networks over development into adulthood, with both methodological and neurobiological implications for future lifespan and disease studies on brain connectivity.