scholarly journals A Sequential Multiple Assignment Randomized Trial (SMART) study of medication and CBT sequencing in the treatment of pediatric anxiety disorders

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bradley S. Peterson ◽  
Amy E. West ◽  
John R. Weisz ◽  
Wendy J. Mack ◽  
Michele D. Kipke ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Randomized Trial ◽  
The Other ◽  
Smart Study ◽  
Main Effect ◽  
Multiple Assignment ◽  
Stage 1 ◽  
Main Effects ◽  
Treatment Sequences

Abstract Background Treatment of a child who has an anxiety disorder usually begins with the question of which treatment to start first, medication or psychotherapy. Both have strong empirical support, but few studies have compared their effectiveness head-to-head, and none has investigated what to do if the treatment tried first isn’t working well—whether to optimize the treatment already begun or to add the other treatment. Methods This is a single-blind Sequential Multiple Assignment Randomized Trial (SMART) of 24 weeks duration with two levels of randomization, one in each of two 12-week stages. In Stage 1, children will be randomized to fluoxetine or Coping Cat Cognitive Behavioral Therapy (CBT). In Stage 2, remitters will continue maintenance-level therapy with the single-modality treatment received in Stage 1. Non-remitters during the first 12 weeks of treatment will be randomized to either [1] optimization of their Stage 1 treatment, or [2] optimization of Stage 1 treatment and addition of the other intervention. After the 24-week trial, we will follow participants during open, naturalistic treatment to assess the durability of study treatment effects. Patients, 8–17 years of age who are diagnosed with an anxiety disorder, will be recruited and treated within 9 large clinical sites throughout greater Los Angeles. They will be predominantly underserved, ethnic minorities. The primary outcome measure will be the self-report score on the 41-item youth SCARED (Screen for Child Anxiety Related Disorders). An intent-to-treat analysis will compare youth randomized to fluoxetine first versus those randomized to CBT first (“Main Effect 1”). Then, among Stage 1 non-remitters, we will compare non-remitters randomized to optimization of their Stage 1 monotherapy versus non-remitters randomized to combination treatment (“Main Effect 2”). The interaction of these main effects will assess whether one of the 4 treatment sequences (CBT➔CBT; CBT➔med; med➔med; med➔CBT) in non-remitters is significantly better or worse than predicted from main effects alone. Discussion Findings from this SMART study will identify treatment sequences that optimize outcomes in ethnically diverse pediatric patients from underserved low- and middle-income households who have anxiety disorders. Trial registration This protocol, version 1.0, was registered in ClinicalTrials.gov on February 17, 2021 with Identifier: NCT04760275.

scholarly journals Spoilage Microbiota of Beef Throughout Various Phases of Processing

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
C. G. Bower ◽  
S. C. Fernando ◽  
G. A. Sullivan
Keyword(s):  
Storage Time ◽  
Distance Matrix ◽  
The Other ◽  
Unifrac Distance ◽  
Β Diversity ◽  
Time Interaction ◽  
Main Effect ◽  
Unweighted Unifrac ◽  
Plate Counts ◽  
Main Effects

ObjectivesThis study aimed to evaluate the spoilage microbiota of beef throughout various processing steps and identify key differences in the microbiome associated with each phase of processing.Materials and MethodsIn each of three replicates, products representing each phase of processing were made from the same uniform meat block (beef shoulder clods): T1-ground beef; T2-fresh sausage; T3-cooked links; T4-beef franks; T5-sliced bologna; T6-bologna with HPP treatment; T7-bologna with lactate/diacetate. Raw treatments were evaluated every 3 d for 21 d, and cooked treatments were evaluated every 14 d for 112 d. Heat treated products were cooked to an internal temperature of 71°C and chilled overnight at 4°C. Parameters for HPP were 600 MPa for 3 min. Aerobic (APC), anaerobic (AnPC), lactic acid bacteria (LAB), and psychrotrophic (PPC) plate counts were measured. Microbial communities were evaluated using high throughput 16S rRNA gene sequencing on the Illumina MiSeq platform. Reads were processed using QIIME, binned into operational taxonomic units (OTUs) at 97% similarity, and assigned taxonomy using the Greengenes database as reference. Alpha and β diversity of bacterial communities were analyzed using QIIME and R. Alpha diversity was estimated using observed OTUs and Chao1 estimates, and β diversity was determined using the weighted and unweighted UniFrac distance matrices (Fig. 2). Raw and cooked samples were analyzed independently for plate counts and α diversity.ResultsThere was a treatment by storage time interaction for AnPC in cooked samples (P = 0.003), where T3, T4, and T7 increased from Day 28 and 42. In raw samples, there was a main effect of storage time on APC, AnPC, LAB, and PPC (P < 0.001), where growth increased over time. In cooked samples, there was a main effect of storage time on APC, LAB, and PPC, and a main effect of treatment for APC and LAB (P < 0.030). Higher APC and LAB counts were observed in T5, while a general increase in APC, LAB, and PPC was seen throughout storage time. There were main effects of treatment and storage time on Chao1 and Observed OTUs in raw samples (P < 0.023) and a main effect of treatment in cooked samples (P < 0.009). In raw samples, bacterial richness was greater in T2 compared to T1, and generally decreased throughout storage time. In cooked samples, richness was the greatest in T3 and T4, the least in the T5, and T6 and T7 were intermediate. There were main effects for treatment and storage time on the bacterial community structure according to the weighted UniFrac distance matrix (P < 0.004) and a treatment by storage time interaction for the unweighted UniFrac distance matrix (P = 0.031). For the weighted UniFrac, T1 and T5 samples formed a cluster relatively separate from the other treatments, while T2 formed an additional cluster by itself. For the unweighted UniFrac, T1, T2, and T5 formed a cluster separate from the other samples, with increased storage times being further separated from the other samples.ConclusionResults from this study indicate that the microbiota of cooked, sliced, bologna is somewhat similar to that of raw ground beef, whereas fresh sausage, cooked links, and bologna with HPP and antimicrobial treatments are different from the former. Treatments where microbial growth was reduced had a significantly different microbial composition compared to those with greater amounts of growth.Figure 2PCoA Plot of Weighted (a) and Unweighted (b) UniFrac Distance Matrices.

scholarly journals Using a Sequential Multiple Assignment Randomized Trial (SMART) to Develop an Adaptive K–2 Literacy Intervention With Personalized Print Texts and App-Based Digital Activities

AERA Open ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 233285841987270 ◽  
Author(s):  
James S. Kim ◽  
Catherine A. Asher ◽  
Mary Burkhauser ◽  
Laura Mesite ◽  
Diana Leyva
Keyword(s):  
Reading Comprehension ◽  
Randomized Trial ◽  
Text Messages ◽  
Literacy Intervention ◽  
Digital Content ◽  
Adaptive Intervention ◽  
Multiple Assignment ◽  
Stage 1 ◽  
To Receive

This study employs a sequential multiple assignment randomized trial (SMART) design to develop an adaptive intervention with personalized print and digital content for kindergarten to Grade 2 children (n = 273). In Stage 1, we ask whether it is better for children to receive an adaptive intervention based on (a) 10 conceptually coherent texts or (b) 10 leveled texts on a range of topics. In Stage 2, we ask how best to encourage nonresponding children. Findings indicate that children who received either conceptually coherent texts or leveled texts performed similarly on reading comprehension posttests, while augmenting and intensifying follow-up with gamification of the app and text messages to parents improved comprehension outcomes for nonresponders. Descriptively, we find that only 26% (n = 71) of parents accessed the app, highlighting the need for better implementation procedures to increase take up of app-based digital activities.

Anxiety and the Spectrum of Obsessive-Compulsive Disorder

CNS Spectrums ◽  
2008 ◽  
Vol 13 (S14) ◽  
pp. 4-5 ◽  
Author(s):  
Donald W. Black
Keyword(s):  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Obsessive Compulsive Disorder ◽  
Selective Serotonin Reuptake Inhibitors ◽  
Age Of Onset ◽  
The Other ◽  
Specific Response ◽  
Obsessive Compulsive ◽  
Important Place ◽  
Compulsive Disorder

This supplement to CNS Spectrums focuses on the obsessive-compulsive spectrum of disorders and their relationship to anxiety. Hollander and others pioneered the concept of the obsessive-compulsive spectrum in the early 1990s, and have described its breadth and overlap with other psychiatric disorders. While its place in the psychiatric nomenclature is uncertain, the obsessive-compulsive spectrum is intertwined with the anxiety disorders in both its symptoms and biologic substrates.Obsessive-compulsive disorder (OCD) has an important place at the center of the spectrum. While currently classified in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition as an anxiety disorder, OCD is distinct from these conditions in the International Classification of Diseases. There is a strong rationale for its separation from the anxiety disorders. First, OCD often begins in childhood, whereas other anxiety disorders typically have a later age of onset. OCD has a nearly equal gender distribution, unlike the other anxiety disorders, which are more common in women. Studies of psychiatric comorbidity show that, unlike the other anxiety disorders, persons with OCD generally tend not to have elevated rates of substance misuse. Family studies suggest that first-degree relatives of persons with OCD have an elevated prevalence of OCD-related disorders including body dysmorphic disorder, hypochondriasis, and grooming disorders, but not other anxiety disorders except for generalized anxiety disorder. The brain circuitry that mediates OCD appears to be different from that involved in other anxiety disorders. Lastly, OCD is unique with regard to its specific response to selective serotonin reuptake inhibitors, while noradrenergic medications, effective in the anxiety and mood disorders, are largely ineffective. On the other hand, the benzodiazepines, which have little effect on OCD, are often effective for the other anxiety disorders.

Sex Differences in Anxiety Disorders

2019 ◽  
pp. 404-432
Author(s):  
Teresa A. Piggott ◽  
Alexandra N. Duran ◽  
Isha Jalnapurkar ◽  
Tyler Kimm ◽  
Stephanie Linscheid ◽  
...  
Keyword(s):  
Sex Differences ◽  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Stress Disorder ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Considerable Research ◽  
Psychosocial Influences ◽  
Psychiatric Conditions ◽  
The Impact

Women are more likely than men to meet lifetime criteria for an anxiety disorder. Moreover, anxiety is a risk factor for the development of other psychiatric conditions, including major depression. Numerous studies have identified evidence of sex differences in anxiety disorders, and there is considerable research concerning factors that may contribute to vulnerability for anxiety in females. In addition to psychosocial influences, biological components such as the female reproductive hormone cycle have also been implicated. Although psychotropic medication is more likely to be prescribed to women, there is little controlled data available concerning sex differences in the efficacy and/or tolerability of pharmacotherapy in anxiety disorders. This chapter provides an overview of the impact of gender in the epidemiology, phenomenology, course, and treatment response in generalized anxiety disorder (GAD), social anxiety disorder (SAD), posttraumatic stress disorder (PTSD), panic disorder (PD), and obsessive-compulsive disorder (OCD).

scholarly journals Understanding the nature of association between anxiety phenotypes and anorexia nervosa: a triangulation approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
E. Caitlin Lloyd ◽  
Hannah M. Sallis ◽  
Bas Verplanken ◽  
Anne M. Haase ◽  
Marcus R. Munafò
Keyword(s):  
Anorexia Nervosa ◽  
Longitudinal Study ◽  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Causal Effect ◽  
Causal Effects ◽  
Observational Research ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Depressed Affect

Abstract Background Evidence from observational studies suggests an association between anxiety disorders and anorexia nervosa (AN), but causal inference is complicated by the potential for confounding in these studies. We triangulate evidence across a longitudinal study and a Mendelian randomization (MR) study, to evaluate whether there is support for anxiety disorder phenotypes exerting a causal effect on AN risk. Methods Study One assessed longitudinal associations of childhood worry and anxiety disorders with lifetime AN in the Avon Longitudinal Study of Parents and Children cohort. Study Two used two-sample MR to evaluate: causal effects of worry, and genetic liability to anxiety disorders, on AN risk; causal effects of genetic liability to AN on anxiety outcomes; and the causal influence of worry on anxiety disorder development. The independence of effects of worry, relative to depressed affect, on AN and anxiety disorder outcomes, was explored using multivariable MR. Analyses were completed using summary statistics from recent genome-wide association studies. Results Study One did not support an association between worry and subsequent AN, but there was strong evidence for anxiety disorders predicting increased risk of AN. Study Two outcomes supported worry causally increasing AN risk, but did not support a causal effect of anxiety disorders on AN development, or of AN on anxiety disorders/worry. Findings also indicated that worry causally influences anxiety disorder development. Multivariable analysis estimates suggested the influence of worry on both AN and anxiety disorders was independent of depressed affect. Conclusions Overall our results provide mixed evidence regarding the causal role of anxiety exposures in AN aetiology. The inconsistency between outcomes of Studies One and Two may be explained by limitations surrounding worry assessment in Study One, confounding of the anxiety disorder and AN association in observational research, and low power in MR analyses probing causal effects of genetic liability to anxiety disorders. The evidence for worry acting as a causal risk factor for anxiety disorders and AN supports targeting worry for prevention of both outcomes. Further research should clarify how a tendency to worry translates into AN risk, and whether anxiety disorder pathology exerts any causal effect on AN.

Growth of prefrontal and limbic brain regions and anxiety disorders in children born very preterm

2021 ◽  
pp. 1-12
Author(s):  
Courtney P. Gilchrist ◽  
Deanne K. Thompson ◽  
Bonnie Alexander ◽  
Claire E. Kelly ◽  
Karli Treyvaud ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Orbitofrontal Cortex ◽  
Developmental Trajectories ◽  
Brain Regions ◽  
Social Risk ◽  
Intracranial Volume ◽  
Total Brain Volume ◽  
Very Preterm ◽  
The Right

Abstract Background Children born very preterm (VP) display altered growth in corticolimbic structures compared with full-term peers. Given the association between the cortiocolimbic system and anxiety, this study aimed to compare developmental trajectories of corticolimbic regions in VP children with and without anxiety diagnosis at 13 years. Methods MRI data from 124 VP children were used to calculate whole brain and corticolimbic region volumes at term-equivalent age (TEA), 7 and 13 years. The presence of an anxiety disorder was assessed at 13 years using a structured clinical interview. Results VP children who met criteria for an anxiety disorder at 13 years (n = 16) displayed altered trajectories for intracranial volume (ICV, p < 0.0001), total brain volume (TBV, p = 0.029), the right amygdala (p = 0.0009) and left hippocampus (p = 0.029) compared with VP children without anxiety (n = 108), with trends in the right hippocampus (p = 0.062) and left medial orbitofrontal cortex (p = 0.079). Altered trajectories predominantly reflected slower growth in early childhood (0–7 years) for ICV (β = −0.461, p = 0.020), TBV (β = −0.503, p = 0.021), left (β = −0.518, p = 0.020) and right hippocampi (β = −0.469, p = 0.020) and left medial orbitofrontal cortex (β = −0.761, p = 0.020) and did not persist after adjusting for TBV and social risk. Conclusions Region- and time-specific alterations in the development of the corticolimbic system in children born VP may help to explain an increase in anxiety disorders observed in this population.

scholarly journals Effects of kinship correction on inflation of genetic interaction statistics in commonly used mouse populations

2021 ◽  
Author(s):  
Anna L Tyler ◽  
Baha El Kassaby ◽  
Georgi Kolishovski ◽  
Jake Emerson ◽  
Ann E Wells ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Genetic Interaction ◽  
Recombinant Inbred Lines ◽  
Test Statistics ◽  
Test Statistic ◽  
Kinship Matrix ◽  
Main Effect ◽  
Main Effects ◽  
Interaction Test

Abstract It is well understood that variation in relatedness among individuals, or kinship, can lead to false genetic associations. Multiple methods have been developed to adjust for kinship while maintaining power to detect true associations. However, relatively unstudied, are the effects of kinship on genetic interaction test statistics. Here we performed a survey of kinship effects on studies of six commonly used mouse populations. We measured inflation of main effect test statistics, genetic interaction test statistics, and interaction test statistics reparametrized by the Combined Analysis of Pleiotropy and Epistasis (CAPE). We also performed linear mixed model (LMM) kinship corrections using two types of kinship matrix: an overall kinship matrix calculated from the full set of genotyped markers, and a reduced kinship matrix, which left out markers on the chromosome(s) being tested. We found that test statistic inflation varied across populations and was driven largely by linkage disequilibrium. In contrast, there was no observable inflation in the genetic interaction test statistics. CAPE statistics were inflated at a level in between that of the main effects and the interaction effects. The overall kinship matrix overcorrected the inflation of main effect statistics relative to the reduced kinship matrix. The two types of kinship matrices had similar effects on the interaction statistics and CAPE statistics, although the overall kinship matrix trended toward a more severe correction. In conclusion, we recommend using a LMM kinship correction for both main effects and genetic interactions and further recommend that the kinship matrix be calculated from a reduced set of markers in which the chromosomes being tested are omitted from the calculation. This is particularly important in populations with substantial population structure, such as recombinant inbred lines in which genomic replicates are used.

scholarly journals How does music performance anxiety relate to other anxiety disorders?

2021 ◽  
pp. 030573562098860
Author(s):  
Anna Wiedemann ◽  
Daniel Vogel ◽  
Catharina Voss ◽  
Jana Hoyer
Keyword(s):  
Cluster Analysis ◽  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Graphical Model ◽  
Music Performance ◽  
Performance Anxiety ◽  
Separation Anxiety Disorder ◽  
Systematic Analysis ◽  
Music Performance Anxiety ◽  
Dsm 5

Music performance anxiety (MPA) is considered a social anxiety disorder (SAD). Recent conceptualizations, however, challenge existing MPA definitions, distinguishing MPA from SAD. In this study, we aim to provide a systematic analysis of MPA interdependencies to other anxiety disorders through graphical modeling and cluster analysis. Participants were 82 music students ( Mage = 23.5 years, SD = 3.4 years; 69.5% women) with the majority being vocal (30.5%), string (24.4%), or piano (19.5%) students. MPA was measured using the German version of the Kenny Music Performance Anxiety Inventory (K-MPAI). All participants were tested for anxiety-related symptoms using the disorder-specific anxiety measures of the Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5), including agoraphobia (AG), generalized anxiety disorder (GAD), panic disorder (PD), separation anxiety disorder (SEP), specific phobia (SP), SAD, and illness anxiety disorder (ILL). We found no evidence of MPA being primarily connected to SAD, finding GAD acted as a full mediator between MPA and any other anxiety type. Our graphical model remained unchanged considering severe cases of MPA only (K-MPAI ⩾ 105). By means of cluster analysis, we identified two participant sub-groups of differing anxiety profiles. Participants with pathological anxiety consistently showed more severe MPA. Our findings suggest that GAD is the strongest predictor for MPA among all major DSM-5 anxiety types.

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