This meta-analysis investigates the efficacy of exercise as a treatment for DSM-IV diagnosed anxiety disorders.
We searched PubMED and PsycINFO for randomized, controlled trials comparing the ...anxiolytic effects of aerobic exercise to other treatment conditions for DSM-IV defined anxiety disorders. Seven trials were included in the final analysis, totaling 407 subjects. The control conditions included non-aerobic exercise, waitlist/placebo, cognitive-behavioral therapy, psychoeducation and meditation. A fixed-effects model was used to calculate the standardized mean difference of change in anxiety rating scale scores of aerobic exercise compared to control conditions. Subgroup analyses were performed to examine the effects of (1) comparison condition; (2) whether comparison condition controlled for time spent exercising and (3) diagnostic indication.
Aerobic exercise demonstrated no significant effect for the treatment of anxiety disorders (SMD=0.02 (95%CI: −0.20–0.24), z=0.2, p=0.85). There was significant heterogeneity between trials (χ2 test for heterogeneity=22.7, df=6, p=0.001). The reported effect size of aerobic exercise was highly influenced by the type of control condition. Trials utilizing waitlist/placebo controls and trials that did not control for exercise time reported large effects of aerobic exercise while other trials report no effect of aerobic exercise.
Current evidence does not support the use of aerobic exercise as an effective treatment for anxiety disorders as compared to the control conditions. This remains true when controlling for length of exercise sessions and type of anxiety disorder. Future studies evaluating the efficacy of aerobic exercise should employ larger sample sizes and utilize comparison interventions that control for exercise time.
•Seven trials using exercise as a treatment for anxiety disorders were compared.•Treatment with CBT and pharmacotherapy is much more effective than exercise.•Exercise is more effective than placebo or wait-list conditions.•Exercise is not significantly better than controls for treating anxiety disorders.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Tourette syndrome (TS) is a neuropsychiatric disorder involving multiple motor and phonic tics. Tics, which usually begin between the ages of 6 and 8, are sudden, rapid, stereotyped, and apparently ...purposeless movements or sounds that involve discrete muscle groups. Individuals with TS experience a variety of different sensory phenomena, including premonitory urges prior to tics and somatic hypersensitivity due to impaired sensorimotor gating. In addition to other conditions, stress, anxiety, fatigue, or other heightened emotional states tend to exacerbate tics, while relaxation, playing sports, and focused concentration on a specific task tend to alleviate tic symptoms. Ninety percent of children with TS also have comorbid conditions, such as attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), or an impulse control disorder. These disorders often cause more problems for the child both at home and at school than tics do alone. Proper diagnosis and treatment of TS involves appropriate evaluation and recognition, not only of tics, but also of these associated conditions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Epidemiological studies of excoriation disorder have reported different prevalence estimates for this condition, limiting our understanding of its public health impact. We performed a systematic ...review and meta-analysis to collate epidemiological studies of excoriation disorder. We aimed to estimate the pooled prevalence and the female-to-male ratio of excoriation disorder in the general population. We searched Embase, PsycInfo, and PubMed up to May 2020 and updated the PubMed search in October 2021. Studies which reported the frequency of excoriation disorder in a sample from the general population were included in our meta-analyses. We made no restrictions regarding the definition or assessment of excoriation disorder. Data were pooled through random-effects meta-analyses. Of the 677 records identified through database searches, 19 studies involving 38,038 participants met our inclusion criteria. Meta-analyses demonstrated that excoriation disorder has an overall prevalence of 3.45% (95% CI 2.55, 4.65%) and impacts women more than men (female-to-male OR = 1.45; 95% CI 1.15, 1.81, p = 0.001). These findings underscore the public health impact of excoriation disorder, which will hopefully motivate future research focused on advancing our understanding and management of this condition.
•Systematic review of epidemiological studies of excoriation disorder identified 19 studies containing 38,038 individuals.•Excoriation disorder has an estimated pooled prevalence of 3.45% in the general population (95% CI 2.55%–4.65%).•Excoriation disorder has a female preponderance (female-to-male OR = 1.45; 95% CI 1.15–1.81, p = 0.001).
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this issue, we read with interest Research Review: Developmental origins of depression – a systematic review and meta‐analysis (Su et al., 2021). Su et al. (2021) conducted a systematic review and ...meta‐analysis examining prenatal, perinatal and postnatal exposures and their association with depression in offspring. Su et al. (2021) evaluated twenty‐eight potential exposures and determined that 12 were associated with increased risk of depression in the offspring. These risk factors included low birth weight, premature birth, being small gestational age, maternal education, socioeconomic status, parental age, parental smoking, maternal stress, maternal anxiety and prenatal depression (Su et al., 2021). Strikingly, each of these developmental risk factors for depression in the offspring is known to be associated with poverty.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Few data exist to help clinicians predict likelihood of treatment response in individual patients with major depressive disorder (MDD). Our aim was to identify subgroups of MDD patients with ...differential treatment outcomes based on presenting clinical characteristics. We also sought to quantify the likelihood of treatment success based on the degree of improvement and side effects after 2 and 4 weeks of selective serotonin reuptake inhibitor (SSRI) pharmacotherapy.
We analyzed data from the first treatment phase of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, in which subjects with a DSM-IV diagnosis of MDD were treated for 8-14 weeks with open-label citalopram. A receiver operating characteristic (ROC) analysis was conducted to determine homogenous subgroups with different rates of response and remission in depressive symptoms. Included predictor variables were initial clinical characteristics, initial improvement, and side effects after 2 and 4 weeks of SSRI treatment. The primary outcome measures were treatment response (defined as a greater than 50% reduction in 17-item Hamilton Depression Rating Scale HDRS-17 score from baseline) and remission (defined as an HDRS-17 score ≤ 17).
Baseline clinical characteristics were able to identify subgroups from a low likelihood of response of 18% (income < $10,000, comorbid generalized anxiety disorder, < 16 years of education; P < .01) to a high likelihood of response of 68% (income ≥ $40,000, no comorbid posttraumatic stress disorder; P < .01). Among baseline clinical characteristics, employment status (N = 2,477; χ²₁ = 78.1; P < .001) and income level (N = 2,512; χ²₁ = 77.7; P < .001) were the most informative in predicting treatment outcome. For the models at weeks 2 and 4, treatment success was best predicted by early symptom improvement.
Socioeconomic data such as low income, education, and unemployment were most discriminative in predicting a poor response to citalopram, even with disparities in access to care accounted for. This finding implies that socioeconomic factors may be more useful predictors of medication response than traditional psychiatric diagnoses or past treatment history.
ClinicalTrials.gov identifier: NCT00021528.
Clinical course of Tourette syndrome Bloch, Michael H; Leckman, James F
Journal of psychosomatic research,
12/2009, Volume:
67, Issue:
6
Journal Article
Peer reviewed
Open access
Abstract Objective Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by multiple motor and vocal tics lasting at least a year in duration. Children with TS often ...experience comorbid conditions such as obsessive-compulsive disorder (OCD) and attention-deficit disorder. The goal of this article was to review the long-term clinical course of tics and comorbid conditions in children with TS. Method We conducted a traditional literature search to locate relevant articles regarding long-term outcome and prognosis in TS and tic disorders. Results Tics typically have an onset between the ages of 4 and 6 years and reach their worst-ever severity between the ages of 10 and 12 years. On average, tic severity declines during adolescence. By early adulthood, roughly three-quarters of children with TS will have greatly diminished tic symptoms and over one-third will be tic free. Comorbid conditions, such as OCD and other anxiety and depressive disorders, are more common during the adolescence and early adulthood of individuals with TS than in the general population. Conclusion Although tics are the sine qua non of TS, they are often not the most enduring or impairing symptoms in children with TS. Measures used to enhance self-esteem, such as encouraging strong friendships and the exploration of interests, are crucial to ensuring positive adulthood outcome in TS.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Our objective was to examine the association between antipsychotic receptor binding profiles and the magnitude of common side-effects. We used regression analysis to examine the association between ...the receptor binding affinities of antipsychotic agents (log Ki) and degree of specific antipsychotic side-effects. Data on magnitude of weight gain, prolactin increase and QTc prolongation (in Standardized Mean Difference) and risk of sedation and extrapyramidal symptoms (in Odds Ratio) between individual antipsychotic medications as compared to placebo was based on a recent network meta-analysis examining the treatment of schizophrenia. Receptor affinities (in log Ki) were examined for the D2, 5-HT1A, 5-HT2A, 5-HT2C, H1, alpha1, alpha2, M1, M3 and M4 receptors. Medications were weighted in the analysis using the generic inverse variance method utilizing variance estimates from the previous meta-analysis.
Magnitude of weight gain was significantly associated with the affinity of antipsychotic medications to M1, M3, 5-HT2C and H1 receptors. Risk of sedation was significantly associated with the affinity to the M1 and M4 receptors. Magnitude of hyperprolactinemia was significantly associated with the affinity to M1 and M4 receptors. Risk of extrapyramidal side effects was associated with the affinity to 5-HT2C and M1 receptors. QT prolongation was not significantly associated with antipsychotic receptor affinities. Our meta-analysis demonstrated that increased affinity of antipsychotics for certain receptors are significantly associated with higher risk of sedation, hyperprolactinemia, extrapyramidal side effects and weight gain.
•Increased M1 and M4 affinity of antipsychotics wereassociated with increased risk of sedation.•Increased H1, 5-HT2C, M1 and M3 affinity of antipsychotics were associated with increased risk of weight gain.•Decreased M1 and M4 affinity of antipsychotics were associated with increased prolactin levels.•Decreased 5-HT2C and M1 affinity of antipsychotics wereassociated with increased relative risk of extrapyramidal side effects.•We failed to demonstrate any significant association between the receptor affinities and QT prolongation among antipsychotic agents.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Background
Adolescent major depressive disorder (MDD) is a significant health problem, associated with substantial morbidity, cost, and mortality. Depression is a significant risk factor for suicide, ...which is now the second leading cause of death in young people. Up to twenty per cent of adolescents will experience MDD before adulthood, and while a substantial proportion will improve with standard‐of‐care treatments (psychotherapy and medication), roughly one third will not.
Methods
Here, we have reviewed the literature in order to discuss the concept of treatment‐resistant depression (TRD) in adolescence, examine risk factors, diagnostic difficulties, and challenges in evaluating symptom improvement, and providing guidance on how to define adequate medication and psychotherapy treatment trials.
Results
We propose a staging model for adolescent TRD and review the treatment literature. The evidence base for first‐ and second‐line treatments primarily derives from four large pediatric clinical trials (TADS, TORDIA, ADAPT, and IMPACT). After two medications and a trial of evidence‐based psychotherapy have failed to alleviate depressive symptoms, the evidence becomes quite thin for subsequent treatments. Here, we review the evidence for the effectiveness of medication switches, medication augmentation, psychotherapy augmentation, and interventional treatments (i.e., transcranial magnetic stimulation, electroconvulsive therapy, and ketamine) for adolescent TRD. Comparisons are drawn to the adult TRD literature, and areas for future pediatric depression research are highlighted.
Conclusions
As evidence is limited for treatments in this population, a careful consideration of the known risks and side effects of escalated treatments (e.g., mood stabilizers and atypical antipsychotics) is warranted and weighed against potential, but often untested, benefits.
Read the Commentary on this article at doi: 10.1111/jcpp.13207
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
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