Objective Approximately 15–20 percent of young children can be classified as having a behaviorally inhibited (BI) temperament. Stable BI predicts the development of later anxiety disorders (particularly social anxiety), but not all inhibited children develop anxiety. Parenting characterized by inappropriate warmth/sensitivity and/or intrusive control predicts the stability of BI and moderates risk for anxiety among high-BI children. For these reasons, we developed and examined the preliminary efficacy of the Turtle Program: a multi-modal early intervention for inhibited preschool-aged children. Method Forty inhibited children between the ages of 42–60 months and their parent(s) were randomized to either the Turtle Program (n = 18) or a waitlist control condition (WLC; n = 22). Participants randomized to the Turtle Program condition received 8 weeks of concurrent parent and child group treatment. Participants were assessed at baseline and post-treatment with multi-source assessments, including parent and teacher report measures of child anxiety, diagnostic interviews, and observations of parenting behavior. Results The Turtle Program resulted in significant beneficial effects relative to the WLC condition on maternal-reported anxiety symptoms of medium to large magnitude; large effects on parent-reported BI; medium to large effects on teacher-rated school anxiety symptoms; and medium effects on observed maternal positive affect/sensitivity. Conclusions This study provides encouraging preliminary support for the Turtle Program for young behaviorally inhibited children. Importantly, the effects of the Turtle Program generalized to the school setting. Future studies should examine whether this early intervention program improves long-term developmental outcomes for these at-risk children.

This study examined differences in friendship quality between children with traumatic brain injury (TBI) and orthopedic injury (OI) and behavioral outcomes for children from both groups. Participants were 41 children with TBI and 43 children with OI (M age = 10.4). Data were collected using peer- and teacher-reported measures of participants’ social adjustment and parent-reported measures of children’s post-injury behaviors. Participants and their mutually nominated best friends also completed a measure of the quality of their friendships. Children with TBI reported significantly more support and satisfaction in their friendships than children with OI. Children with TBI and their mutual best friend were more similar in their reports of friendship quality compared to children with OI and their mutual best friends. Additionally, for children with TBI who were rejected by peers, friendship support buffered against maladaptive psychosocial outcomes, and predicted skills related to social competence. Friendship satisfaction was related to higher teacher ratings of social skills for the TBI group only. Positive and supportive friendships play an important role for children with TBI, especially for those not accepted by peers. Such friendships may protect children with TBI who are rejected against maladaptive psychosocial outcomes, and promote skills related to social competence.

The results underscore the importance of including peer reports of social behavior when developing interventions designed to improve the social, emotional, and behavioral outcomes of children with TBI.

BACKGROUND: Major depressive disorder (MDD) is a prevalent and debilitating condition. While numerous treatment options are available, low treatment response and high remission rates remain common, leading to the concept of treatment-resistant depression (TRD): a classification applied to patients who fail multiple courses of therapy. A patient with TRD can only be identified after repeated, and often prolonged, therapeutic efforts. OBJECTIVE: To use data readily available to integrated delivery networks to identify characteristics predictive of TRD among patients initiating pharmacotherapy for MDD. METHODS: Decision Resources Group Real-World Data, an integrated medical/pharmacy claims and electronic health record dataset, was used to conduct a retrospective, longitudinal cohort study of patients with MDD who initiated antidepressant treatment between July 1, 2014, and December 31, 2015. Individuals were followed for 24 months to determine treatment resistance. Eligible individuals had integrated claims and electronic health record data available, completed at least 1 course of therapy of adequate dose and duration to achieve response, and had 30 months of continuous benefits eligibility (6 months before and 24 months after treatment initiation). Stepwise logistic regression and demographic, health history, health care utilization, medication, provider, and related characteristics were used to predict onset of TRD. RESULTS: 35,246 people met eligibility and 7,098 (20.1%) met TRD criteria after an average of 402 days. Significant predictors of TRD included patient age, diagnosis of insomnia and hypertension, psychiatric office visits, nurse telephonic encounters, anticonvulsant medication use, suicidality, physician specialty associated with index prescription, total prescription drug claims, unique antidepressants attempted, and duration of untreated illness (the lag between diagnosis and index prescription). The final model achieved an area under the curve (AUC) = 0.83. Structured patient-generated health data, specifically, the Patient Health Questionnaire-2 and the Patient Health Questionnaire-9 were only reported for 542 patients (1.5%).CONCLUSIONS: TRD transition occurs after a prolonged treatment period, suggesting clinical inertia. Using data routinely available to integrated delivery networks and accountable care organizations, it is feasible to identify patients likely to qualify as treatment resistant. Monitoring risk factors may allow health systems to identify patients at risk for TRD earlier, potentially improving outcomes. Early identification of this at-risk population can allow for targeted resources for earlier intervention, more aggressive follow-up, and alternative treatment options. Furthermore, this model can be used to estimate future demand for specialized care resources, such as those delivered by mood disorder clinics.

No abstract