Anxiety and type 1 diabetes management: guardian and child report in a pediatric endocrinology clinic

Background: Childhood anxiety prevents optimal diabetes management yet may be underrecognized by guardians. Objective: We aimed to investigate associations among anxiety, diabetes treatment adherence, and diabetes symptom control through child and guardian report. Methods: Cross-sectional pilot study surveying a convenience sample of children (ages 2–21) in a pediatric endocrinology clinic. Behavior Assessment System for Children, Second Edition 2, Self-Care Inventory Report, and Pediatric Quality of Life measured anxiety, diabetes treatment adherence, and diabetes symptom control. Analyses were performed with Spearman correlations. Results: Prevalence of anxiety and related behaviors was higher when reported by children (13% and 24%) vs. guardians (5% and 13%). Child-reported anxiety was associated with worse symptom control in all ages (Pediatric Quality of Life [r = −0.55, P 12 (rho = 0.686, P = 0.003)—although not significantly for children ≤ 12 (rho = 0.201, P = 0.473). Conclusion: Anxiety in children with type 1 diabetes varies with the domain of diabetes management (treatment adherence vs. symptom control) and reporting source (child vs. guardian). Children aged ≤12 exhibited a stronger relationship between higher anxiety and worse diabetes management with worse treatment adherence and symptom control in the presence of higher anxiety. Guardians of younger children were less effective at recognizing symptoms. Challenges identifying anxiety and its detrimental effects on diabetes management suggest routine screening of anxiety in pediatric endocrinology clinics is especially salient

Effects of Problem-Solving Therapy and Clinical Case Management on Disability in Low-Income Older Adults

ObjectiveTo test the following hypotheses: (1) Clinical case management integrated with problem-solving therapy (CM-PST) is more effective than clinical case management alone (CM) in improving functional outcomes in disabled, impoverished patients and (2) improvement in depression, self-efficacy, and problem-solving skills mediates improvement of disability.MethodsUsing a randomized controlled trial with a parallel design, 271 individuals were screened and 171 were randomized to 12 weekly sessions of either CM or CM-PST at 1:1 ratio. Raters were blind to patients' assignments. Participants were at least age 60 years with major depression, had at least one disability, were eligible for home-based meals services, and had income no more than 30% of their counties' median. The WHO Disability Assessment Scale was used.ResultsBoth interventions resulted in improved functioning by 12 weeks (t = 4.28, df = 554, p = 0.001), which was maintained until 24 weeks. Contrary to hypothesis, CM was noninferior to CM-PST (one-sided p = 0.0003, t = -3.5, df = 558). Change in disability was not affected by baseline depression severity, cognitive function, or number of unmet social service needs. Improvements in self efficacy (t = -2.45, df = 672, p = 0.021), problem-solving skill (t = -2.44, df = 546, p = 0.015), and depression symptoms (t = 2.25, df = 672, p = .025) by week 9 predicted improvement in function across groups by week 12.ConclusionCM is noninferior to CM-PST for late-life depression in low-income populations. The effect of these interventions occur early, with benefits in functional status maintained as long as 24 weeks after treatment initiation (clinicaltrials.gov; NCT00540865)

Effects of Problem-Solving Therapy and Clinical Case Management on Disability in Low-Income Older Adults

ObjectiveTo test the following hypotheses: (1) Clinical case management integrated with problem-solving therapy (CM-PST) is more effective than clinical case management alone (CM) in improving functional outcomes in disabled, impoverished patients and (2) improvement in depression, self-efficacy, and problem-solving skills mediates improvement of disability.MethodsUsing a randomized controlled trial with a parallel design, 271 individuals were screened and 171 were randomized to 12 weekly sessions of either CM or CM-PST at 1:1 ratio. Raters were blind to patients' assignments. Participants were at least age 60 years with major depression, had at least one disability, were eligible for home-based meals services, and had income no more than 30% of their counties' median. The WHO Disability Assessment Scale was used.ResultsBoth interventions resulted in improved functioning by 12 weeks (t = 4.28, df = 554, p = 0.001), which was maintained until 24 weeks. Contrary to hypothesis, CM was noninferior to CM-PST (one-sided p = 0.0003, t = -3.5, df = 558). Change in disability was not affected by baseline depression severity, cognitive function, or number of unmet social service needs. Improvements in self efficacy (t = -2.45, df = 672, p = 0.021), problem-solving skill (t = -2.44, df = 546, p = 0.015), and depression symptoms (t = 2.25, df = 672, p = .025) by week 9 predicted improvement in function across groups by week 12.ConclusionCM is noninferior to CM-PST for late-life depression in low-income populations. The effect of these interventions occur early, with benefits in functional status maintained as long as 24 weeks after treatment initiation (clinicaltrials.gov; NCT00540865)

Clinical Case Management versus Case Management with Problem-Solving Therapy in Low-Income, Disabled Elders with Major Depression: A Randomized Clinical Trial

ObjectiveTo test the hypotheses that (1) clinical case management integrated with problem-solving therapy (CM-PST) is more effective than clinical case management alone (CM) in reducing depressive symptoms of depressed, disabled, impoverished patients and that (2) development of problem-solving skills mediates improvement of depression.MethodsThis randomized clinical trial with a parallel design allocated participants to CM or CM-PST at 1:1 ratio. Raters were blind to patients' assignments. Two hundred seventy-one individuals were screened and 171 were randomized to 12 weekly sessions of either CM or CM-PST. Participants were at least 60 years old with major depression measured with the 24-item Hamilton Depression Rating Scale (HAM-D), had at least one disability, were eligible for home-based meals services, and had income no more than 30% of their counties' median.ResultsCM and CM-PST led to similar declines in HAM-D over 12 weeks (t = 0.37, df = 547, p = 0.71); CM was noninferior to CM-PST. The entire study group (CM plus CM-PST) had a 9.6-point decline in HAM-D (t = 18.7, df = 547, p <0.0001). The response (42.5% versus 33.3%) and remission (37.9% versus 31.0%) rates were similar (χ(2) = 1.5, df = 1, p = 0.22 and χ(2) = 0.9, df = 1, p = 0.34, respectively). Development of problem-solving skills did not mediate treatment outcomes. There was no significant increase in depression between the end of interventions and 12 weeks later (0.7 HAM-D point increase) (t = 1.36, df = 719, p = 0.17).ConclusionOrganizations offering CM are available across the nation. With training in CM, their social workers can serve the many depressed, disabled, low-income patients, most of whom have poor response to antidepressants even when combined with psychotherapy

Hybrid ICA-Seed-Based Methods for fMRI Functional Connectivity Assessment: A Feasibility Study

Brain functional connectivity (FC) is often assessed from fMRI data using seed-based methods, such as those of detecting temporal correlation between a predefined region (seed) and all other regions in the brain; or using multivariate methods, such as independent component analysis (ICA). ICA is a useful data-driven tool, but reproducibility issues complicate group inferences based on FC maps derived with ICA. These reproducibility issues can be circumvented with hybrid methods that use information from ICA-derived spatial maps as seeds to produce seed-based FC maps. We report results from five experiments to demonstrate the potential advantages of hybrid ICA-seed-based FC methods, comparing results from regressing fMRI data against task-related a priori time courses, with “back-reconstruction” from a group ICA, and with five hybrid ICA-seed-based FC methods: ROI-based with (1) single-voxel, (2) few-voxel, and (3) many-voxel seed; and dual-regression-based with (4) single ICA map and (5) multiple ICA map seed

Modifiable predictors of nonresponse to psychotherapies for late-life depression with executive dysfunction: a machine learning approach

The study aimed to: (1) Identify distinct trajectories of change in depressive symptoms by mid-treatment during psychotherapy for late-life depression with executive dysfunction; (2) examine if nonresponse by mid-treatment predicted poor response at treatment end; and (3) identify baseline characteristics predicting an early nonresponse trajectory by mid-treatment. A sample of 221 adults 60 years and older with major depression and executive dysfunction were randomized to 12 weeks of either problem-solving therapy or supportive therapy. We used Latent Growth Mixture Models (LGMM) to detect subgroups with distinct trajectories of change in depression by mid-treatment (6th week). We conducted regression analyses with LGMM subgroups as predictors of response at treatment end. We used random forest machine learning algorithms to identify baseline predictors of LGMM trajectories. We found that ~77.5% of participants had a declining trajectory of depression in weeks 0-6, while the remaining 22.5% had a persisting depression trajectory, with no treatment differences. The LGMM trajectories predicted remission and response at treatment end. A random forests model with high prediction accuracy (80%) showed that the strongest modifiable predictors of the persisting depression trajectory were low perceived social support, followed by high neuroticism, low treatment expectancy, and low perception of the therapist as accepting. Our results suggest that modifiable risk factors of early nonresponse to psychotherapy can be identified at the outset of treatment and addressed with targeted personalized interventions. Therapists may focus on increasing meaningful social interactions, addressing concerns related to treatment benefits, and creating a positive working relationship