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Psychiatric disorders are categorized on the basis of presence and absence of diagnostic criteria using classification systems such as the international classification of diseases (ICD) and the diagnostic and statistical manual for mental disorders (DSM). The research domain criteria (RDoC) initiative provides an alternative dimensional framework for conceptualizing mental disorders. In the present paper, we studied neural and behavioral effects of central stimulant (CS) medication in adults with attention deficit hyperactivity disorder (ADHD) and healthy controls using categorical and dimensional stratifications. AX-Continuous Performance Task (AX-CPT) was utilized for the later purpose, and participants were classified as "reactive" or "proactive" based on their baseline proactive behavioral index (PBI). Out of the 65 individuals who participated (33 healthy controls and 32 patients with ADHD), 53 were included in the final analysis that consisted of 31 healthy controls and 22 ADHD patients. For the dimensional stratification, a median split of PBI scores divided participants into "reactive" and "proactive" groups irrespective of whether they had ADHD or not. Participants performed AX-CPT in conjunction with functional magnetic resonance imaging (fMRI) before and after CS medication. We found no significant within or between group CS effect when participants were categorically assigned as healthy controls and ADHD patients. For the dimensional stratification, however, CS selectively increased activation in frontoparietal cognitive areas and induced a shift towards proactive control mode in the reactive group, without significantly affecting the proactive group. In conclusion, the neural and behavioral effects of CS were more clear-cut when participants were stratified into dimensional groups rather than diagnostic categories. [ABSTRACT FROM AUTHOR]

Treating depression in adolescents is a significant challenge, and major depressive disorder (MDD) with suicidal ideation and treatment-resistant depression (TRD) are common and potentially devastating to optimal psychological and physical development in this age group. Suicide is among the leading causes of youth mortality, and TRD occurs in up to 40% of adolescents with MDD. TRD involves severe, persistent symptoms that are hard to treat, significantly reducing functioning and quality of life. We conducted a literature search focusing on key terms related to ketamine and esketamine for MDD with suicidal ideation and TRD in adolescents, aiming to review the potential utility of these molecules in adolescents for these conditions. Ketamine has shown efficacy in reducing depressive symptoms in adolescents with TRD. Esketamine has shown efficacy in reducing depressive symptoms and treating suicidal ideation in adolescents. Both ketamine and esketamine have demonstrated favorable safety and tolerability profiles. Using these drugs for serious conditions like adolescent MDD with suicidal thoughts and TRD can effectively treat symptoms, reduce self-harm and suicide risks, and provide a window for longer-term therapeutic interventions. The prompt and effective treatment of TRD could improve adolescents' quality of life. However, more research is needed to optimize treatment protocols and evaluate long-term effects. [ABSTRACT FROM AUTHOR]

Systematic reviews are a cornerstone for synthesizing the available evidence on a given topic. They simultaneously allow for gaps in the literature to be identified and provide direction for future research. However, due to the ever‐increasing volume and complexity of the available literature, traditional methods for conducting systematic reviews are less efficient and more time‐consuming. Numerous artificial intelligence (AI) tools are being released with the potential to optimize efficiency in academic writing and assist with various stages of the systematic review process including developing and refining search strategies, screening titles and abstracts for inclusion or exclusion criteria, extracting essential data from studies and summarizing findings. Therefore, in this article we provide an overview of the currently available tools and how they can be incorporated into the systematic review process to improve efficiency and quality of research synthesis. We emphasize that authors must report all AI tools that have been used at each stage to ensure replicability as part of reporting in methods. [ABSTRACT FROM AUTHOR]

To increase the number of pre‐registered observational studies, Journal of Child Psychology and Psychiatry (JCPP) Advances is delighted to now invite Registered Reports. Registered Reports are a format of article in which the study protocol is pre‐registered and peer‐reviewed before the research is conducted. If the protocol is of high quality and the proposed research topic is important, JCPP Advances will commit to publishing the study regardless of the results. This article format crucially addresses publication bias, as decisions on publication are entirely independent of the results. [ABSTRACT FROM AUTHOR]

Gambling disorder is a severe mental health and behavioural problem with harmful consequences, including financial, relationship and mental health problems. The present paper initiates discussion on the use of psychedelics combined with psychotherapeutic support as a potential treatment option for people living with a gambling disorder. Recent studies have shown promising results using psychedelic-assisted therapy (PAT) to treat anxiety, depression, post-traumatic stress disorder, and various substance use disorders. Considering the similarities in the underlying psychosocial and neurobiological mechanisms of gambling disorder and other addictive disorders, the authors suggest that psychedelic-assisted therapy could be effective in treating gambling disorder. The paper also underscores the need for further research into the viability and effectiveness of psychedelic-assisted therapy for gambling disorder. [ABSTRACT FROM AUTHOR]

Background: Depression is a public health problem and common amongst adolescents. Cognitive behavioural therapy (CBT) is widely used to treat adolescent depression but existing research does not provide clear conclusions regarding the relative effectiveness of different delivery modalities. Objectives: The primary aim is to estimate the relative efficacy of different modes of CBT delivery compared with each other and control conditions for reducing depressive symptoms in adolescents. The secondary aim is to compare the different modes of delivery with regard to intervention completion/attrition (a proxy for intervention acceptability). Search Methods: The Cochrane Depression, Anxiety and Neurosis Clinical Trials Register was searched in April 2020. MEDLINE, PsycInfo, EMBASE, four other electronic databases, the CENTRAL trial registry, Google Scholar and Google were searched in November 2020, together with reference checking, citation searching and hand‐searching of two databases. Selection Criteria: Randomised controlled trials (RCTs) of CBT interventions (irrespective of delivery mode) to reduce symptoms of depression in young people aged 10–19 years with clinically relevant symptoms or diagnosis of depression were included. Data Collection and Analysis: Screening and data extraction were completed by two authors independently, with discrepancies addressed by a third author. CBT interventions were categorised as follows: group CBT, individual CBT, remote CBT, guided self‐help, and unguided self‐help. Effect on depressive symptom score was estimated across validated self‐report measures using Hedges' g standardised mean difference. Acceptability was estimated based on loss to follow‐up as an odds ratio. Treatment rankings were developed using the surface under the cumulative ranking curve (SUCRA). Pairwise meta‐analyses were conducted using random effects models where there were two or more head‐to‐head trials. Network analyses were conducted using random effects models. Main Results: Sixty‐eight studies were included in the review. The mean age of participants ranged from 10 to 19.5 years, and on average 60% of participants were female. The majority of studies were conducted in schools (28) or universities (6); other settings included primary care, clinical settings and the home. The number of CBT sessions ranged from 1 to 16, the frequency of delivery from once every 2 weeks to twice a week and the duration of each session from 20 min to 2 h. The risk of bias was low across all domains for 23 studies, 24 studies had some concerns and the remaining 21 were assessed to be at high risk of bias. Sixty‐two RCTs (representing 6435 participants) were included in the pairwise and network meta‐analyses for post‐intervention depressive symptom score at post‐intervention. All pre‐specified treatment and control categories were represented by at least one RCT. Although most CBT approaches, except remote CBT, demonstrated superiority over no intervention, no approaches performed clearly better than or equivalent to another. The highest and lowest ranking interventions were guided self‐help (SUCRA 83%) and unguided self‐help (SUCRA 51%), respectively (very low certainty in treatment ranking). Nineteen RCTs (3260 participants) were included in the pairwise and network meta‐analyses for 6 to 12 month follow‐up depressive symptom score. Neither guided self‐help nor remote CBT were evaluated in the RCTs for this time point. Effects were generally attenuated for 6‐ to 12‐month outcomes compared to posttest. No interventions demonstrated superiority to no intervention, although unguided self‐help and group CBT both demonstrated superiority compared to TAU. No CBT approach demonstrated clear superiority over another. The highest and lowest ranking approaches were unguided self‐help and individual CBT, respectively. Sixty‐two RCTs (7347 participants) were included in the pairwise and network meta‐analyses for intervention acceptability. All pre‐specified treatment and control categories were represented by at least one RCT. Although point estimates tended to favour no intervention, no active treatments were clearly inferior. No CBT approach demonstrated clear superiority over another. The highest and lowest ranking active interventions were individual CBT and group CBT respectively. Pairwise meta‐analytic findings were similar to those of the network meta‐analysis for all analyses. There may be age‐based subgroup effects on post‐intervention depressive symptoms. Using the no intervention control group as the reference, the magnitudes of effects appear to be larger for the oldest age categories compared to the other subgroups for each given comparison. However, they were generally less precise and formal testing only indicated a significant difference for group CBT. Findings were robust to pre‐specified sensitivity analyses separating out the type of placebo and excluding cluster‐RCTs, as well as an additional analysis excluding studies where we had imputed standard deviations. Authors' Conclusions: At posttreatment, all active treatments (group CBT, individual CBT, guided self‐help, and unguided self‐help) except for remote CBT were more effective than no treatment. Guided self‐help was the most highly ranked intervention but only evaluated in trials with the oldest adolescents (16–19 years). Moreover, the studies of guided self‐help vary in the type and amount of therapist support provided and longer‐term results are needed to determine whether effects persist. The magnitude of effects was generally attenuated for 6‐ to 12‐month outcomes. Although unguided self‐help was the lowest‐ranked active intervention at post‐intervention, it was the highest ranked at follow‐up. This suggests the need for further research into whether interventions with self‐directed elements enable young people to maintain effects by continuing or revisiting the intervention independently, and whether therapist support would improve long‐term outcomes. There was no clear evidence that any active treatments were more acceptable to participants than any others. The relative effectiveness of intervention delivery modes must be taken into account in the context of the needs and preferences of individual young people, particularly as the differences between effect sizes were relatively small. Further research into the type and amount of therapist support that is most acceptable to young people and most cost‐effective would be particularly useful. [ABSTRACT FROM AUTHOR]

Background: Reactive balance is the last line of defense to prevent a fall when the body loses stability, and beneficial effects of various exercise-based interventions on reactive balance in older adults have been reported. However, their pooled evidence on the relative effects has yet to be described. Objective: To review and evaluate the comparative effectiveness of various exercise-based interventions on reactive balance in older adults. Methods: Nine electronic databases and reference lists were searched from inception to August 2021. Eligibility criteria according to PICOS criteria were as follows: (1) population: older adults with the mean age of 65 years or above; (2) intervention and comparison: at least two distinct exercise interventions or one exercise intervention with a no-exercise controlled intervention (NE) compared in each trial; (3) outcome: at least one measure of reactive balance; (4) study: randomized controlled trial. The main network meta-analysis was performed on data from the entire older adult population, involving all clinical conditions as well as healthy older adults. Subgroup analyses stratified by characteristics of participants (healthy only) and reactive balance outcomes (simulated slip or trip while walking, simulated forward falls, being pushed or pulled, and movable platform) were also conducted. Results: Thirty-nine RCTs (n = 1388) investigating 17 different types of exercise interventions were included in the network meta-analysis. Reactive balance training as a single intervention presented the highest probability (surface under the cumulative ranking (SUCRA) score) of being the best intervention for improving reactive balance and the greatest relative effects vs. NE in the entire sample involving all clinical conditions [SUCRA = 0.9; mean difference (95% Credible Interval): 2.7 (1.0 to 4.3)]. The results were not affected by characteristics of participants (i.e., healthy older adults only) or reactive balance outcomes. Summary/Conclusion: The findings from the NMA suggest that a task-specific reactive balance exercise could be the optimal intervention for improving reactive balance in older adults, and power training can be considered as a secondary training exercise. [ABSTRACT FROM AUTHOR]

Objective: Children and adults with ADHD often report sleep disturbances that may form part of the etiology and/or symptomatology of ADHD. We review the evidence for sleep changes in children with ADHD.Methods: Systematic review with narrative synthesis assessing sleep and circadian function in children aged 5 to 13 years old with a diagnosis of ADHD.Results: 148 studies were included for review, incorporating data from 42,353 children. We found that sleep disturbances in ADHD are common and that they may worsen behavioral outcomes; moreover, sleep interventions may improve ADHD symptoms, and pharmacotherapy for ADHD may impact sleep.Conclusion: Sleep disturbance may represent a clinically important feature of ADHD in children, which might be therapeutically targeted in a useful way. There are a number of important gaps in the literature. We set out a manifesto for future research in the area of sleep, circadian rhythms, and ADHD. [ABSTRACT FROM AUTHOR]

Approval and prescription of psychotropic drugs should be informed by the strength of evidence for efficacy. Using a Bayesian framework, we examined (1) whether psychotropic drugs are supported by substantial evidence (at the time of approval by the Food and Drug Administration), and (2) whether there are systematic differences across drug groups. Data from short-term, placebo-controlled phase II/III clinical trials for 15 antipsychotics, 16 antidepressants for depression, nine antidepressants for anxiety, and 20 drugs for attention deficit hyperactivity disorder (ADHD) were extracted from FDA reviews. Bayesian model-averaged meta-analysis was performed and strength of evidence was quantified (i.e. BFBMA). Strength of evidence and trialling varied between drugs. Median evidential strength was extreme for ADHD medication (BFBMA = 1820.4), moderate for antipsychotics (BFBMA = 365.4), and considerably lower and more frequently classified as weak or moderate for antidepressants for depression (BFBMA = 94.2) and anxiety (BFBMA = 49.8). Varying median effect sizes (ESschizophrenia = 0.45, ESdepression = 0.30, ESanxiety = 0.37, ESADHD = 0.72), sample sizes (Nschizophrenia = 324, Ndepression = 218, Nanxiety = 254, NADHD = 189.5), and numbers of trials (kschizophrenia = 3, kdepression = 5.5, kanxiety = 3, kADHD = 2) might account for differences. Although most drugs were supported by strong evidence at the time of approval, some only had moderate or ambiguous evidence. These results show the need for more systematic quantification and classification of statistical evidence for psychotropic drugs. Evidential strength should be communicated transparently and clearly towards clinical decision makers. [ABSTRACT FROM AUTHOR]

The prevention of fetal growth restriction (FGR) is challenging in clinical practice. To date, no meta‐analysis summarized evidence on the relative benefits and harms of pharmacological interventions for FGR prevention. We performed a systematic review and network meta‐analysis (NetMA), searching PubMed, Embase, Cochrane Library, and ClinicalTrials.gov from inception until November 2019. We included clinical trials and observational studies on singleton gestating women evaluating antiplatelet, anticoagulant, or other treatments, compared between each other or with controls (placebo or no treatment), and considering the pregnancy outcome FGR (primary outcome of the NetMA). Secondary efficacy outcomes included preterm birth, placental abruption, and fetal or neonatal death. Safety outcomes included bleeding and thrombocytopenia. Network meta‐analyses using a frequentist framework were conducted to derive odds ratios (ORs) and 95% confidence intervals (CIs). Of 18,780 citations, we included 30 studies on 4,326 patients. Low molecular weight heparin (LMWH), alone or associated with low‐dose aspirin (LDA), appeared more efficacious than controls in preventing FGR (OR 2.00, 95% CI 1.27–3.16 and OR 2.67, 95% CI 1.21–5.89 for controls vs. LMWH and LDA + LMWH, respectively). No difference between active treatments emerged in terms of FGR prevention, but estimates for treatments other than LMWH +/‐ LDA were imprecise. Only the confidence in the evidence regarding LMWH vs. controls was judged as moderate, according to the Confidence in Network Meta‐Analysis framework. No treatment was associated with an increased risk of bleeding, although estimates were precise enough only for LMWH. These results should inform clinicians on the benefits of active pharmacological prophylaxis for FGR prevention. [ABSTRACT FROM AUTHOR]

We aimed to screen for depression among a sample of adolescents with type 1 Diabetes Mellitus (T1DM) and to determine the impact of obesity and poor diabetic control as potential risk factors. One hundred adolescents with T1DM (aged between 14 and 18 years) were randomly selected and subjected to detailed history, physical examination, and laboratory investigations. BMI and Glycated Hemoglobin (HbA1c) were measured. The "PHQ-9" questionnaire- Arabic version was used to screen for depression. We found that 51% of the sample was at moderate to severe risk for depression. There was a statistically significant association between the depression and older age and female gender. Depression severity was positively correlated with HbA1c, frequency of hospital admission, presence of diabetic complications and the degree of obesity. In this study, the best cut-off points that could predict depression in T1DM adolescent patients were: HbA1c of >10.1 or more, while the best cut-off point regarding BMI was found to be more than >22.3 Kg/m2. We can conclude adolescents with T1DM are at increased risk for depression especially females, with poor diabetic control and overweight problems. [ABSTRACT FROM AUTHOR]

Neuropharmacotherapy is substantially hindered by poor drug targeting, resulting in low specificity and efficacy. It is known that different behavioral tasks increase functional activity and cerebral blood flow (CBF), two key parameters controlling drug delivery and efficacy. Here, we tested a novel, non-invasive drug targeting approach (termed functional-pharmacological coupling), which couples drug administration with a task that is known to specifically activate the drug's sites-of-action in the brain. In two studies we administered Methylphenidate (MPH) to neurotypical adults and to subjects with attention deficit hyperactivity disorder (ADHD). In study 1 we employed a within-subject factorial design and found that only following MPH administration, subjects that performed better in the cognitive induction task showed greater improvements in N-back performance. Moreover, only under MPH-Cognitive induction condition, this improvement correlated with concurrent N-Back rDLPFC activation. In Study 2, subjects with ADHD performed better on sustained attention when MPH administration was followed by a cognitive challenge rather than a control task. Again, those who were more attentive to the cognitive challenge scored higher. Our results provide preliminary support for the feasibility of functional-pharmacological coupling concept, hence opening a new horizon for patient-tailored, context-driven drug therapy. [ABSTRACT FROM AUTHOR]

Network meta‐analysis (NMA) compares several interventions that are linked in a network of comparative studies and estimates the relative treatment effects between all treatments, using both direct and indirect evidence. NMA is increasingly used for decision making in health care, however, a user‐friendly system to evaluate the confidence that can be placed in the results of NMA is currently lacking. This paper is a tutorial describing the Confidence In Network Meta‐Analysis (CINeMA) web application, which is based on the framework developed by Salanti et al (2014, PLOS One, 9, e99682) and refined by Nikolakopoulou et al (2019, bioRxiv). Six domains that affect the level of confidence in the NMA results are considered: (a) within‐study bias, (b) reporting bias, (c) indirectness, (d) imprecision, (e) heterogeneity, and (f) incoherence. CINeMA is freely available and open‐source and no login is required. In the configuration step users upload their data, produce network plots and define the analysis and effect measure. The dataset should include assessments of study‐level risk of bias and judgments on indirectness. CINeMA calls the netmeta routine in R to estimate relative effects and heterogeneity. Users are then guided through a systematic evaluation of the six domains. In this way reviewers assess the level of concerns for each relative treatment effect from NMA as giving rise to "no concerns," "some concerns," or "major concerns" in each of the six domains, which are graphically summarized on the report page for all effect estimates. Finally, judgments across the domains are summarized into a single confidence rating ("high," "moderate," "low," or "very low"). In conclusion, the user‐friendly web‐based CINeMA platform provides a transparent framework to evaluate evidence from systematic reviews with multiple interventions. [ABSTRACT FROM AUTHOR]

This is the protocol for a Campbell review. The primary aim is to estimate the relative efficacy of different modes of CBT delivery compared with control conditions for reducing depressive symptoms in adolescents. The secondary aim is to compare the different modes of delivery with regards to intervention completion/attrition (used as a proxy for intervention acceptability). The review will provide relative effect estimates and ranking probabilities for each outcome based on intervention delivery. [ABSTRACT FROM AUTHOR]

Intestinal parasites affect millions of children globally. We aimed to assess effects of deworming children on nutritional and cognitive outcomes across potential effect modifiers using individual participant data (IPD). We searched multiple databases to 27 March 2018, grey literature, and other sources. We included randomised and quasi randomised trials of deworming compared to placebo or other nutritional interventions with data on baseline infection. We used a random-effects network meta-analysis with IPD and assessed overall quality, following a pre-specified protocol. We received IPD from 19 trials of STH deworming. Overall risk of bias was low. There were no statistically significant subgroup effects across age, sex, nutritional status or infection intensity for each type of STH. These analyses showed that children with moderate or heavy intensity infections, deworming for STH may increase weight gain (very low certainty). The added value of this review is an exploration of effects on growth and cognition in children with moderate to heavy infections as well as replicating prior systematic review results of small effects at the population level. Policy implications are that complementary public health strategies need to be assessed and considered to achieve growth and cognition benefits for children in helminth endemic areas. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is one of the most common reasons patients present for medical care worldwide. Nurses should be aware of the occurrence of and pharmacologic treatments for MDD and treatment-resistant depression (TRD). Holistic nursing plays a pivotal role in caring for patients with TRD. [ABSTRACT FROM AUTHOR]

Background: Amyotrophic Lateral Sclerosis (ALS) is a relentlessly progressive neurodegenerative condition with limited therapeutic options at present. Survival from symptom onset ranges from 3 to 5 years depending on genetic, demographic, and phenotypic factors. Despite tireless research efforts, the core etiology of the disease remains elusive and drug development efforts are confounded by the lack of accurate monitoring markers. Disease heterogeneity, late-stage recruitment into pharmaceutical trials, and inclusion of phenotypically admixed patient cohorts are some of the key barriers to successful clinical trials. Machine Learning (ML) models and large international data sets offer unprecedented opportunities to appraise candidate diagnostic, monitoring, and prognostic markers. Accurate patient stratification into well-defined prognostic categories is another aspiration of emerging classification and staging systems. Methods: The objective of this paper is the comprehensive, systematic, and critical review of ML initiatives in ALS to date and their potential in research, clinical, and pharmacological applications. The focus of this review is to provide a dual, clinical-mathematical perspective on recent advances and future directions of the field. Another objective of the paper is the frank discussion of the pitfalls and drawbacks of specific models, highlighting the shortcomings of existing studies and to provide methodological recommendations for future study designs. Results: Despite considerable sample size limitations, ML techniques have already been successfully applied to ALS data sets and a number of promising diagnosis models have been proposed. Prognostic models have been tested using core clinical variables, biological, and neuroimaging data. These models also offer patient stratification opportunities for future clinical trials. Despite the enormous potential of ML in ALS research, statistical assumptions are often violated, the choice of specific statistical models is seldom justified, and the constraints of ML models are rarely enunciated. Conclusions: From a mathematical perspective, the main barrier to the development of validated diagnostic, prognostic, and monitoring indicators stem from limited sample sizes. The combination of multiple clinical, biofluid, and imaging biomarkers is likely to increase the accuracy of mathematical modeling and contribute to optimized clinical trial designs. [ABSTRACT FROM AUTHOR]

Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains. This leaves much quantitative scaffolding literature not covered by existing meta-analyses. To address this gap, this study used Bayesian network meta-analysis to synthesize within-subjects (pre–post) differences resulting from scaffolding in 56 studies. We generated the posterior distribution using 20,000 Markov Chain Monte Carlo samples. Scaffolding has a consistently strong effect across student populations, STEM (science, technology, engineering, and mathematics) disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional models (exception: inquiry-based learning and modeling visualization) and educational levels (exception: secondary education). Results also indicate some promising areas for future scaffolding research, including scaffolding among students with learning disabilities, for whom the effect size was particularly large (ḡ = 3.13). [ABSTRACT FROM AUTHOR]