Sex Differences in Adolescent Depression Trajectory Before and Into the Second Year of COVID-19 Pandemic

OBJECTIVE

Evidence on the impact of the COVID-19 pandemic on adolescent mental health is mixed and does not disentangle natural age-related changes. We compared depressive symptoms among 16-year-olds surveyed, at a fourth wave, before or during the pandemic, while accounting for expected trajectories of within-person change based on 3 prior waves.

METHOD

In this longitudinal cohort of 3,171 adolescents in Tokyo, Japan, adolescents were grouped based on their age 16 survey timing: pre-pandemic (February 2019 to February 2020) and during-pandemic (March 2020 to September 2021). Depressive symptoms were self-reported using the Short Mood and Feelings Questionnaire. Mixed-effect models were fitted to assess group differences while controlling for previous trends. Variations by sex, household income, and pandemic phase (early, late first-year, and second-year) were examined.

RESULTS

Of 2,034 eligible adolescents, 960 (455 girls) were assessed before and 1,074 (515 girls) during the pandemic. Overall, depressive symptoms increased by 0.80 points (95% CI 0.28-1.31, 0.15 SD of the population average). This increase varied by sex and pandemic phase. For boys the increase emerged in the late first-year phase and enlarged in the second-year phase (mean difference from pre-pandemic: 1.69, 0.14-3.24), whereas for girls it decreased in the early school-closure phase (mean difference: -1.98, -3.54 to -0.41) and returned to the pre-pandemic level thereafter, with no additional increases during the pandemic.

CONCLUSION

Into the second year of the COVID-19 pandemic, depressive symptoms of 16-year-olds worsened above the expected age-related change only in boys. Continuous monitoring and preventive approaches for adolescents at the population level are warranted.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure that the study questionnaires were prepared in an inclusive way. We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

The short and long-term efficacy of nurse-led interventions for improving blood pressure control in people with hypertension in primary care settings: a systematic review and meta-analysis

BACKGROUND

Previous systematic reviews suggest that nurse-led interventions improve short-term blood pressure (BP) control for people with hypertension. However, the long-term effects, adverse events, and appropriate target BP level are unclear. This study aimed to evaluate the long-term efficacy and safety of nurse-led interventions.

METHODS

We conducted a systematic review and meta-analysis. We searched the Cochrane Central Register of Controlled Trials, PubMed, and CINAHL, as well as three Japanese article databases, as relevant randomized controlled trials from the oldest possible to March 2021. This search was conducted on 17 April 2021. We did an update search on 17 October 2023. We included studies on adults aged 18 years or older with hypertension. The treatments of interest were community-based nurse-led BP control interventions in addition to primary physician-provided care as usual. The comparator was usual care only. Primary outcomes were long-term achievement of BP control goals and serious adverse events (range: 27 weeks to 3 years). Secondary outcomes were short-term achievement of BP control goals and serious adverse events (range: 4 to 26 weeks), change of systolic and diastolic BP from baseline, medication adherence, incidence of hypertensive complications, and total mortality.

RESULTS

We included 35 studies. Nurse-led interventions improved long-term BP control (RR 1.10, 95%CI 1.03 to 1.18). However, no significant differences were found in the short-term effects of nurse-led intervention compared to usual care about BP targets. Little information on serious adverse events was available. There was no difference in mortality at both terms between the two groups. Establishing the appropriate target BP from the extant trials was impossible.

CONCLUSIONS

Nurse-led interventions may be more effective than usual care for achieving BP control at long-term follow-up. It is important to continue lifestyle modification for people with hypertension. We must pay attention to adverse events, and more studies examining appropriate BP targets are needed. Nurse-led care represents an important complement to primary physician-led usual care.

Utility of RAND/UCLA appropriateness method in validating multiple-choice questions on ECG

OBJECTIVES

This study aimed to investigate the utility of the RAND/UCLA appropriateness method (RAM) in validating expert consensus-based multiple-choice questions (MCQs) on electrocardiogram (ECG).

METHODS

According to the RAM user's manual, nine panelists comprising various experts who routinely handle ECGs were asked to reach a consensus in three phases: a preparatory phase (round 0), an online test phase (round 1), and a face-to-face expert panel meeting (round 2). In round 0, the objectives and future timeline of the study were elucidated to the nine expert panelists with a summary of relevant literature. In round 1, 100 ECG questions prepared by two skilled cardiologists were answered, and the success rate was calculated by dividing the number of correct answers by 9. Furthermore, the questions were stratified into "Appropriate," "Discussion," or "Inappropriate" according to the median score and interquartile range (IQR) of appropriateness rating by nine panelists. In round 2, the validity of the 100 ECG questions was discussed in an expert panel meeting according to the results of round 1 and finally reassessed as "Appropriate," "Candidate," "Revision," and "Defer."

RESULTS

In round 1 results, the average success rate of the nine experts was 0.89. Using the median score and IQR, 54 questions were classified as " Discussion." In the expert panel meeting in round 2, 23% of the original 100 questions was ultimately deemed inappropriate, although they had been prepared by two skilled cardiologists. Most of the 46 questions categorized as "Appropriate" using the median score and IQR in round 1 were considered "Appropriate" even after round 2 (44/46, 95.7%).

CONCLUSIONS

The use of the median score and IQR allowed for a more objective determination of question validity. The RAM may help select appropriate questions, contributing to the preparation of higher-quality tests.

Prevalence of hazardous drinking and suspected alcohol dependence in Japanese primary care settings

OBJECTIVE

We aimed to assess the prevalence of hazardous drinking and potential alcohol dependence among Japanese primary care patients, and their readiness to change and awareness of others' concerns.

METHODS

From July to August 2023, we conducted a multi-site cross-sectional study as a screening survey for participants in a cluster randomized controlled trial. The trial included outpatients aged 20-74 from primary care clinics. Using the Alcohol Use Disorders Identification Test (AUDIT) alongside a self-administered questionnaire, we evaluated the prevalence of hazardous drinking and suspected alcohol dependence, patients' readiness to change, and their awareness of others' concerns.

RESULTS

Among the 1388 participants from 18 clinics, 22% (95% confidence interval (CI): 20% to 24%) were identified as engaging in hazardous drinking or suspected of being alcohol dependent. As the AUDIT scores increased, so did their readiness to change. However, only 22% (95%CI: 16% to 28%) of those with scores ranging from 8 to 14 reported that others, including physicians, had expressed concerns about their drinking during the past year. For those with scores of 15 or higher, the figure was 74%.

CONCLUSIONS

This study underscores the need for universal or high-risk alcohol screening and brief intervention in Japanese primary care settings. Trial registry UMIN-CTR (https://www.umin.ac.jp/ctr/) (UMIN000051388).

Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review

Research waste occurs when randomised controlled trial (RCT) outcomes are heterogeneous or overlook domains that matter to patients (eg, relating to symptoms or functions). In this systematic review, we reviewed the outcome measures used in 450 RCTs of adult unipolar and bipolar depression registered between 2018 and 2022 and identified 388 different measures. 40% of the RCTs used the same measure (Hamilton Depression Rating Scale [HAMD]). Patients and clinicians matched each item within the 25 most frequently used measures with 80 previously identified domains of depression that matter to patients. Seven (9%) domains were not covered by the 25 most frequently used outcome measures (eg, mental pain and irritability). The HAMD covered a maximum of 47 (59%) of the 80 domains that matter to patients. An interim solution to facilitate evidence synthesis before a core outcome set is developed would be to use the most common measures and choose complementary scales to optimise domain coverage. TRANSLATIONS: For the French and Dutch translations of the abstract see Supplementary Materials section.

Components and Delivery Formats of Cognitive Behavioral Therapy for Chronic Insomnia in Adults: A Systematic Review and Component Network Meta-Analysis

Importance

Chronic insomnia disorder is highly prevalent, disabling, and costly. Cognitive behavioral therapy for insomnia (CBT-I), comprising various educational, cognitive, and behavioral strategies delivered in various formats, is the recommended first-line treatment, but the effect of each component and delivery method remains unclear.

Objective

To examine the association of each component and delivery format of CBT-I with outcomes.

Data Sources

PubMed, Cochrane Central Register of Controlled Trials, PsycInfo, and International Clinical Trials Registry Platform from database inception to July 21, 2023.

Study Selection

Published randomized clinical trials comparing any form of CBT-I against another or a control condition for chronic insomnia disorder in adults aged 18 years and older. Insomnia both with and without comorbidities was included. Concomitant treatments were allowed if equally distributed among arms.

Data Extraction and Synthesis

Two independent reviewers identified components, extracted data, and assessed trial quality. Random-effects component network meta-analyses were performed.

Main Outcomes and Measures

The primary outcome was treatment efficacy (remission defined as reaching a satisfactory state) posttreatment. Secondary outcomes included all-cause dropout, self-reported sleep continuity, and long-term remission.

Results

A total of 241 trials were identified including 31 452 participants (mean [SD] age, 45.4 [16.6] years; 21 048 of 31 452 [67%] women). Results suggested that critical components of CBT-I are cognitive restructuring (remission incremental odds ratio [iOR], 1.68; 95% CI, 1.28-2.20) third-wave components (iOR, 1.49; 95% CI, 1.10-2.03), sleep restriction (iOR, 1.49; 95% CI, 1.04-2.13), and stimulus control (iOR, 1.43; 95% CI, 1.00-2.05). Sleep hygiene education was not essential (iOR, 1.01; 95% CI, 0.77-1.32), and relaxation procedures were found to be potentially counterproductive(iOR, 0.81; 95% CI, 0.64-1.02). In-person therapist-led programs were most beneficial (iOR, 1.83; 95% CI, 1.19-2.81). Cognitive restructuring, third-wave components, and in-person delivery were mainly associated with improved subjective sleep quality. Sleep restriction was associated with improved subjective sleep quality, sleep efficiency, and wake after sleep onset, and stimulus control with improved subjective sleep quality, sleep efficiency, and sleep latency. The most efficacious combination-consisting of cognitive restructuring, third wave, sleep restriction, and stimulus control in the in-person format-compared with in-person psychoeducation, was associated with an increase in the remission rate by a risk difference of 0.33 (95% CI, 0.23-0.43) and a number needed to treat of 3.0 (95% CI, 2.3-4.3), given the median observed control event rate of 0.14.

Conclusions and Relevance

The findings suggest that beneficial CBT-I packages may include cognitive restructuring, third-wave components, sleep restriction, stimulus control, and in-person delivery but not relaxation. However, potential undetected interactions could undermine the conclusions. Further large-scale, well-designed trials are warranted to confirm the contribution of different treatment components in CBT-I.

When does the placebo effect have an impact on network meta-analysis results?

The placebo effect is the 'effect of the simulation of treatment that occurs due to a participant's belief or expectation that a treatment is effective'. Although the effect might be of little importance for some conditions, it can have a great role in others, mostly when the evaluated symptoms are subjective. Several characteristics that include informed consent, number of arms in a study, the occurrence of adverse events and quality of blinding may influence response to placebo and possibly bias the results of randomised controlled trials. Such a bias is inherited in systematic reviews of evidence and their quantitative components, pairwise meta-analysis (when two treatments are compared) and network meta-analysis (when more than two treatments are compared). In this paper, we aim to provide red flags as to when a placebo effect is likely to bias pairwise and network meta-analysis treatment effects. The classic paradigm has been that placebo-controlled randomised trials are focused on estimating the treatment effect. However, the magnitude of placebo effect itself may also in some instances be of interest and has also lately received attention. We use component network meta-analysis to estimate placebo effects. We apply these methods to a published network meta-analysis, examining the relative effectiveness of four psychotherapies and four control treatments for depression in 123 studies.

Multicomponent Intervention for Overactive Bladder in Women: A Randomized Clinical Trial

Importance

Although the cognitive components of behavioral therapy for overactive bladder (OAB) are widely recognized, there is a lack of studies evaluating the effectiveness of multicomponent interventions that include cognitive components as a treatment for OAB.

Objective

To examine the efficacy of a multicomponent intervention in improving health-related quality of life (HRQOL) for women with moderate to severe OAB.

Design, Setting, and Participants

This multicenter, open-label, randomized clinical trial was conducted in Japan among women aged 20 to 80 years who had moderate to severe OAB. Participants were recruited from 4 institutions between January 16, 2020, and December 31, 2022, through self-referral via advertisement or referral from the participating institutions.

Interventions

Participants were randomized 1:1 by minimization algorithm using an internet-based central cloud system to four 30-minute weekly sessions of a multicomponent intervention or waiting list. Both groups continued to receive baseline treatment throughout the study period.

Main Outcomes and Measures

The primary outcome was the least-squares mean changes from baseline through week 13 in HRQOL total scores of the OAB questionnaire between 2 groups. Secondary outcomes included OAB symptom score and frequency volume chart.

Results

A total of 79 women were randomized to either the intervention group (39 participants; mean [SD] age, 63.5 [14.6] years) or the waiting list control group (40 participants; mean [SD] age, 63.5 [12.9] years). One participant from each group dropped out from the allocated intervention, while 5 participants in the intervention group and 2 in the control group dropped out from the primary outcome assessment at week 13. Thirty-six participants (92.3%) in the intervention group and 35 (87.5%) in the control group had moderate OAB. The change in HRQOL total score from baseline to week 13 was 23.9 points (95% CI, 18.4-29.5 points) in the intervention group and 11.3 points (95% CI, 6.2-16.4 points) in the waiting list group, a significant difference of 12.6 points (95% CI, 6.6-18.6 points; P < .001). Similar superiority of the intervention was confirmed for frequency of micturition and urgency but not for OAB symptom score.

Conclusions and Relevance

These findings demonstrate that a multicomponent intervention improves HRQOL for women with moderate to severe OAB and suggest that the cognitive component may be an effective treatment option for women with OAB.

Trial Registration

UMIN Clinical Trials Registry Identifier: UMIN000038513.

Three types of university students with subthreshold depression characterized by distinctive cognitive behavioral skills

Subthreshold depression impairs young people's quality of life and places them at greater risk of developing major depression. Cognitive behavioral therapy (CBT) is an evidence-based approach for addressing such depressive states. This study identified subtypes of university students with subthreshold depression and revealed discrete profiles of five CBT skills: self-monitoring, cognitive restructuring, behavioral activation, assertive communication, and problem solving. Using data from the Healthy Campus Trial (registration number: UMINCTR-000031307), a hierarchical clustering analysis categorized 1,080 students into three clusters: Reflective Low-skilled, Non-reflective High-skilled, and Non-reflective Low-skilled students. Non-reflective Low-skilled students were significantly more depressed than other students (p < .001). The severity of depression seemed to be related to the combination of self-monitoring skills and other CBT skills. Considering the high prevalence of poor self-monitoring skills in persons with autism, the most severe depression was observed in the significant association between Non-reflective Low-skilled students and autistic traits (p = .008). These findings suggest that subthreshold depression can be categorized into three subtypes based on CBT skill profiles. The assessment of autistic traits is also suggested when we provide CBT interventions for Non-reflective Low-skilled students.

Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies

BACKGROUND

Major depressive disorder (MDD) is a heterogeneous condition; multiple underlying neurobiological and behavioral substrates are associated with treatment response variability. Understanding the sources of this variability and predicting outcomes has been elusive. Machine learning (ML) shows promise in predicting treatment response in MDD, but its application is limited by challenges to the clinical interpretability of ML models, and clinicians often lack confidence in model results. In order to improve the interpretability of ML models in clinical practice, our goal was to demonstrate the derivation of treatment-relevant patient profiles comprised of clinical and demographic information using a novel ML approach.

METHODS

We analyzed data from six clinical trials of pharmacological treatment for depression (total n = 5438) using the Differential Prototypes Neural Network (DPNN), a ML model that derives patient prototypes which can be used to derive treatment-relevant patient clusters while learning to generate probabilities for differential treatment response. A model classifying remission and outputting individual remission probabilities for five first-line monotherapies and three combination treatments was trained using clinical and demographic data. Prototypes were evaluated for interpretability by assessing differences in feature distributions (e.g. age, sex, symptom severity) and treatment-specific outcomes.

RESULTS

A 3-prototype model achieved an area under the receiver operating curve of 0.66 and an expected absolute improvement in remission rate for those receiving the best predicted treatment of 6.5% (relative improvement of 15.6%) compared to the population remission rate. We identified three treatment-relevant patient clusters. Cluster A patients tended to be younger, to have increased levels of fatigue, and more severe symptoms. Cluster B patients tended to be older, female, have less severe symptoms, and the highest remission rates. Cluster C patients had more severe symptoms, lower remission rates, more psychomotor agitation, more intense suicidal ideation, and more somatic genital symptoms.

CONCLUSION

It is possible to produce novel treatment-relevant patient profiles using ML models; doing so may improve interpretability of ML models and the quality of precision medicine treatments for MDD.

Psychotherapies for Generalized Anxiety Disorder in Adults: A Systematic Review and Network Meta-Analysis of Randomized Clinical Trials

Importance

Generalized anxiety disorder (GAD) is one of the most common mental disorders in adults. Psychotherapies are among the most recommended treatments for GAD, but which should be considered as first-line treatment needs to be clarified.

Objective

To use a network meta-analysis to examine the short- and long-term associations of different psychotherapies with outcomes of effectiveness and acceptability in adults with GAD.

Data Sources

MEDLINE, Embase, PsycINFO, and the Cochrane Register of Controlled Trials were searched from database inception to January 1, 2023, to identify randomized clinical trials (RCTs) of psychotherapies for adults with GAD.

Study Selection

RCTs comparing any type of psychotherapy against another or with a control condition for the treatment of adults (≥18 years, both sexes) with a primary diagnosis of GAD were eligible for inclusion.

Data Extraction and Synthesis

This study followed Cochrane standards for extracting data and assessing data quality and used the PRISMA guideline for reporting. Risk of bias of individual studies was assessed using the second version of the Cochrane risk of bias tool, and the Confidence in Network Meta-Analysis was used to rate the certainty of evidence for meta-analytical results.

Main Outcomes and Measures

Eight psychotherapies were compared against one another and with 2 control conditions. Primary outcomes were severity of GAD symptoms and acceptability of the psychotherapies. Random-effects model pairwise and network meta-analyses were conducted. For effectiveness, standardized mean differences (SMDs) were pooled, and for acceptability, relative risks with 95% CIs were calculated.

Results

Data from 65 RCTs were included. Effect size estimates on data from 5048 participants (mean [SD], 70.9% [11.9%] women; mean [SD] age, 42.2 [12.5] years) suggested that third-wave cognitive behavior therapies (CBTs) (SMD, -0.76 [95% CI, -1.15 to -0.36]; certainty, moderate), CBT (SMD, -0.74 [95% CI, -1.09 to -0.38]; certainty, moderate), and relaxation therapy (SMD, -0.59 [95% CI, -1.07 to -0.11]; certainty, low) were associated with reduced GAD symptoms vs treatment as usual. Relative risks for all-cause discontinuation (indication of acceptability) signaled no differences compared with treatment as usual for all psychotherapies (eg, relative risk, 1.04 [95% CI, 0.64-1.67] for CBT vs treatment as usual). When excluding studies at high risk of bias, relaxation therapy lost its superiority over treatment as usual (SMD, -0.47; 95% CI, -1.18 to 0.23). When considering anxiety severity at 3 to 12 months after completion of the intervention, only CBT remained significantly associated with greater effectiveness than treatment as usual (SMD, -0.60; 95% CI, -0.99 to -0.21).

Conclusions and Relevance

Given the evidence in this systematic review and network meta-analysis for its associations with both acute and long-term effectiveness, CBT may represent the first-line therapy of GAD. Third-wave CBTs and relaxation therapy were associated with short-term effectiveness and may also be offered.

Understanding effect size: an international online survey among psychiatrists, psychologists, physicians from other medical specialities, dentists and other health professionals

BACKGROUND AND OBJECTIVE

Various ways exist to display the effectiveness of medical treatment options. This study examined various psychiatric, medical and allied professionals' understanding and perceived usefulness of eight effect size indices for presenting both dichotomous and continuous outcome data.

METHODS

We surveyed 1316 participants from 13 countries using an online questionnaire. We presented hypothetical treatment effects of interventions versus placebo concerning chronic pain using eight different effect size measures. For each index, the participants had to judge the magnitude of the shown effect, to indicate how certain they felt about their own answer and how useful they found the given effect size index.

FINDINGS

Overall, 762 (57.9%) participants fully completed the questionnaire. In terms of understanding, the best results emerged when both the control event rate (CER) and the experimental event rate (EER) were presented. The difference in minimal importance difference units (MID unit) was understood worst. Respondents also found CER and EER to be the most useful presentation approach while they rated MID unit as the least useful. Confidence in the risk ratio ranked high, even though it was rather poorly understood.

CONCLUSIONS AND CLINICAL IMPLICATIONS

For dichotomous outcomes, presenting the effects in terms of the CER and EER could lead to the most correct interpretation. Relative measures including the risk ratio must be supplemented with absolute measures such as the CER and EER. Effects on continuous outcomes were better understood through standardised mean differences than mean differences. These can also be supplemented by dichotomised CER and EER.

Are the results of open randomised controlled trials comparing antipsychotic drugs in schizophrenia biased? Exploratory meta- and subgroup analysis

A recent meta-epidemiological study did not reveal major differences between the results of blinded and open randomised-controlled trials (RCTs). Fewer patients may consent to double-blind RCTs than to open RCTs, compromising generalisability, making this question very important. However, the issue has not been addressed in schizophrenia. We used a database of randomised, acute-phase antipsychotic drug trials. Whenever at least one open and one blinded RCT was available for a comparison of two drugs, we contrasted the results by random-effects meta-analysis with subgroup tests. The primary outcome was overall symptoms as measured by the Positive and Negative Syndrome Scale, supplemented by seven secondary efficacy and side-effect outcomes. We also examined whether open RCTs were biased in favour of more recently introduced antipsychotics, less efficacious or more prone to side-effects antipsychotics, and pharmaceutical sponsors. 183 RCTs (155 blinded and 28 open) with 34715 participants comparing two active drugs were available. The results did not suggest general differences between open and blinded RCTs, which examined two active drugs. Only 12 out of 122 subgroup tests had a p-value below 0.1, four below 0.05, and if a Bonferroni correction for multiple tests had been applied, only one would have been significant. There were some exceptions which, however, did not always confirm the originally hypothesized direction of bias. Due to the relatively small number of open RCTs, our analysis is exploratory, but this fundamental question should be given more scientific attention. Currently, open RCTs should be excluded from meta-analyses, at least in sensitivity analyses.

Guided versus unguided chatbot-delivered cognitive behavioral intervention for individuals with moderate-risk and problem gambling: A randomized controlled trial (GAMBOT2 study)

BACKGROUND

Internet-based interventions can be a promising option for individuals with problem gambling facing barriers to seeking help. This study aimed to directly compare the effects of therapist-guided Internet interventions with unguided ones on gambling-related behavior, cognition, and stage of change including help-seeking intention.

METHODS

We conducted a participant-blinded randomized controlled trial of therapist-guided versus unguided groups with a 12-week follow-up. Both groups received self-help chatbot-delivered cognitive behavioral therapy. Additionally, at baseline and weeks 1, 2, 3, and 4, the guided group received personalized feedback messages from therapists based on their gambling diary and questionnaire responses. The unguided group received reminders of assessments from research assistants. The primary outcome was the change in scores on the Gambling Symptoms Assessment Scale (G-SAS) over 12 weeks. Secondary outcomes included the stage of change including help-seeking intention, money wagered, gambling frequency, and gambling-related cognitions.

RESULTS

We included 139 participants with a mean Problem Gambling Severity Index total score of 14.6 and a mean G-SAS total score of 27.0 who sought information about gambling problems. Both groups demonstrated substantial decreases in their G-SAS scores from baseline to week 12 (-10.2, 95% CI: -7.67 to -12.7 for the guided group, and 11.7, 95% CI: -9.05 to -14.3 for the unguided group). However, we did not find a significant between-group difference (1.49, 95% CI: -2.20 to 5.17). Regarding the stage of change including help-seeking intention, there were also no between-group differences.

CONCLUSIONS

Minimum therapist support did not have an additive effect on the self-help chatbot intervention on gambling symptoms, behavior, and the stage of change including help-seeking intention.

Treatment Outcomes With Licensed and Unlicensed Stimulant Doses for Adults With Attention-Deficit/Hyperactivity Disorder: A Systematic Review and Meta-Analysis

Importance

Stimulants (methylphenidate and amphetamines) are often prescribed at unlicensed doses for adults with attention-deficit/hyperactivity disorder (ADHD). Whether dose escalation beyond US Food and Drug Administration recommendations is associated with positive risk benefits is unclear.

Objective

To investigate the impact, based on averages, of stimulant doses on treatment outcomes in adults with ADHD and to determine, based on averages, whether unlicensed doses are associated with positive risk benefits compared with licensed doses.

Data Sources

Twelve databases, including published (PubMed, Cochrane Library, Embase, Web of Sciences) and unpublished (ClinicalTrials.gov) literature, up to February 22, 2023, without language restrictions.

Study Selection

Two researchers independently screened records to identify double-blinded randomized clinical trials of stimulants against placebo in adults (18 years and older) with ADHD.

Data Extraction and Synthesis

Aggregate data were extracted and synthesized in random-effects dose-response meta-analyses and network meta-analyses.

Main Outcome Measures

Change in ADHD symptoms and discontinuations due to adverse events.

Results

A total of 47 randomized clinical trials (7714 participants; mean age, 35 (SD, 11) years; 4204 male [56%]) were included. For methylphenidate, dose-response curves indicated additional reductions of symptoms with increments in doses, but the gains were progressively smaller and accompanied by continued additional risk of adverse events dropouts. Network meta-analyses showed that unlicensed doses were associated with greater reductions of symptoms compared with licensed doses (standardized mean difference [SMD], -0.23; 95% CI, -0.44 to -0.02; very low certainty of evidence), but the additional gain was small and accompanied by increased risk of adverse event dropouts (odds ratio, 2.02; 95% CI, 1.19-3.43; moderate certainty of evidence). For amphetamines, the dose-response curve approached a plateau and increments in doses did not indicate additional reductions of symptoms, but there were continued increments in the risk of adverse event dropouts. Network meta-analysis did not identify differences between unlicensed and licensed doses for reductions of symptoms (SMD, -0.08; 95% CI, -0.24 to 0.08; very low certainty of evidence).

Conclusions and Relevance

Based on group averages, unlicensed doses of stimulants may not have positive risk benefits compared with licensed doses for adults with ADHD. In general, practitioners should consider unlicensed doses cautiously. Practitioners may trial unlicensed doses if needed and tolerated but should be aware that there may not be large gains in the response to the medication with those further increments in dose. However, the findings are averages and will not generalize to every patient.

The definition of treatment resistance in anxiety disorders: a Delphi method-based consensus guideline

Anxiety disorders are very prevalent and often persistent mental disorders, with a considerable rate of treatment resistance which requires regulatory clinical trials of innovative therapeutic interventions. However, an explicit definition of treatment-resistant anxiety disorders (TR-AD) informing such trials is currently lacking. We used a Delphi method-based consensus approach to provide internationally agreed, consistent and clinically useful operational criteria for TR-AD in adults. Following a summary of the current state of knowledge based on international guidelines and an available systematic review, a survey of free-text responses to a 29-item questionnaire on relevant aspects of TR-AD, and an online consensus meeting, a panel of 36 multidisciplinary international experts and stakeholders voted anonymously on written statements in three survey rounds. Consensus was defined as ≥75% of the panel agreeing with a statement. The panel agreed on a set of 14 recommendations for the definition of TR-AD, providing detailed operational criteria for resistance to pharmacological and/or psychotherapeutic treatment, as well as a potential staging model. The panel also evaluated further aspects regarding epidemiological subgroups, comorbidities and biographical factors, the terminology of TR-AD vs. "difficult-to-treat" anxiety disorders, preferences and attitudes of persons with these disorders, and future research directions. This Delphi method-based consensus on operational criteria for TR-AD is expected to serve as a systematic, consistent and practical clinical guideline to aid in designing future mechanistic studies and facilitate clinical trials for regulatory purposes. This effort could ultimately lead to the development of more effective evidence-based stepped-care treatment algorithms for patients with anxiety disorders.

A chatbot to improve adherence to internet-based cognitive-behavioural therapy among workers with subthreshold depression: a randomised controlled trial

BACKGROUND

Internet-based cognitive-behavioural therapy (iCBT) is effective for subthreshold depression. However, iCBT has problems with adherence, especially when unaccompanied by human guidance. Knowledge on how to enhance adherence to iCBT without human involvement can contribute to improving the effectiveness of iCBT.

OBJECTIVE

This is an implementation study to examine the effect of an automated chatbot to improve the adherence rate of iCBT.

METHODS

We developed a chatbot to increase adherence to an existing iCBT programme, and a randomised controlled trial was conducted with two groups: one group using iCBT plus chatbot (iCBT+chatbot group) and one group not using the chatbot (iCBT group). Participants were full-time employees with subthreshold depression working in Japan (n=149, age mean=41.4 (SD=11.1)). The primary endpoint was the completion rate of the iCBT programme at 8 weeks.

FINDINGS

We analysed data from 142 participants for the primary outcome. The completion rate of the iCBT+chatbot group was 34.8% (24/69, 95% CI 23.5 to 46.0), that of the iCBT group was 19.2% (14/73, 95% CI 10.2 to 28.2), and the risk ratio was 1.81 (95% CI 1.02 to 3.21).

CONCLUSIONS

Combining iCBT with a chatbot increased participants' iCBT completion rate.

CLINICAL IMPLICATIONS

Encouraging messages from the chatbot could improve participation in an iCBT programme. Further studies are needed to investigate whether chatbots can improve adherence to the programme in the long term and to assess their impact on depression, anxiety and well-being.

TRIAL REGISTRATION NUMBER

UMIN000047621.

Estimating the smallest worthwhile difference of antidepressants: a cross-sectional survey

BACKGROUND

Approximately 30% of patients experience substantial improvement in depression after 2 months without treatment, and 45% with antidepressants. The smallest worthwhile difference (SWD) refers to an intervention's smallest beneficial effect over a comparison patients deem worthwhile given treatment burdens (harms, expenses and inconveniences), but is undetermined for antidepressants.

OBJECTIVE

Estimating the SWD of commonly prescribed antidepressants for depression compared to no treatment.

METHODS

The SWD was estimated as a patient-required difference in response rates between antidepressants and no treatment after 2 months. An online cross-sectional survey using Prolific, MQ Mental Health and Amazon Mechanical Turk crowdsourcing services in the UK and USA between October 2022 and January 2023 garnered participants (N=935) that were a mean age of 44.1 (SD=13.9) and 66% women (n=617).

FINDINGS

Of 935 participants, 124 reported moderate-to-severe depressive symptoms but were not in treatment, 390 were in treatment and 495 reported absent-to-mild symptoms with or without treatment experiences. The median SWD was a 20% (IQR=10-30%) difference in response rates for people with moderate-to-severe depressive symptoms, not in treatment, and willing to consider antidepressants, and 25% (IQR=10-35%) for the full sample.

CONCLUSIONS

Our observed SWDs mean that the current 15% antidepressant benefit over no treatment was sufficient for one in three people to accept antidepressants given the burdens, but two in three expected greater treatment benefits.

IMPLICATIONS

While a minority may be satisfied with the best currently available antidepressants, more effective and/or less burdensome medications are needed, with more attention given to patient perspectives.

Correction: Electronic Health Record-Nested Reminders for Serum Lithium Level Monitoring in Patients With Mood Disorder: Randomized Controlled Trial

[This corrects the article DOI: 10.2196/40595.].

Evaluating the substance use disorder treatment gap in the United States, 2016-2019: A population health observational study

BACKGROUND AND OBJECTIVES

Only 10% of Americans with substance use disorders (SUDs) receive treatment with insufficient treatment access and screening practices proposed and potential contributing factors.

METHODS

This retrospective cross-sectional study used National Survey on Drug Use and Health (NSDUH) data to assess individuals with SUDs receiving treatment between 2016 and 2019 (survey n = 12,111; weighted n = 12,394,214). Demographic, access, and screening characteristics were investigated as predictors of treatment receipt using time-series logistic regression analyses to test trends and assessed treatment receipt odds, controlling for demographic and treatment characteristics.

RESULTS

For those with past-year SUDs, 13.0% reported receiving past-year SUD treatment (survey n = 1605; weighted n = 1,612,154). The SUD treatment receipt rate remained statistically stable from 2016 to 2019, with a nonsignificant treatment receipt trend declining from 14% to 12%. Treatment changes were notable among Native Americans (+53.80%), Pacific Islanders (+94.10%), multiracial (-59.96%), ages 65+ (-70.18%), and ages 12-17 (-50.70%). In the regression model, race, sex, age, insurance status, and receiving mental health treatment were associated with SUD treatment receipt.

DISCUSSION AND CONCLUSIONS

The treatment gap remains substantial and stable. Annually, about 87% of Americans with SUDs are not receiving the treatment they need. Asian Americans were less likely and those attending general mental health services were more likely to receive treatment.

SCIENTIFIC SIGNIFICANCE

We present an updated SUD treatment gap evaluation, and identify access and screening characteristics associated with SUD treatment receipt. Policymakers, clinicians, and researchers must continue improving access and identification of those in need of care.

Pharmacological treatments in panic disorder in adults: a network meta-analysis

BACKGROUND

A panic attack is a discrete period of fear or anxiety that has a rapid onset and reaches a peak within 10 minutes. The main symptoms involve bodily systems, such as racing heart, chest pain, sweating, shaking, dizziness, flushing, churning stomach, faintness and breathlessness. Other recognised panic attack symptoms involve fearful cognitions, such as the fear of collapse, going mad or dying, and derealisation (the sensation that the world is unreal). Panic disorder is common in the general population with a prevalence of 1% to 4%. The treatment of panic disorder includes psychological and pharmacological interventions, including antidepressants and benzodiazepines.

OBJECTIVES

To compare, via network meta-analysis, individual drugs (antidepressants and benzodiazepines) or placebo in terms of efficacy and acceptability in the acute treatment of panic disorder, with or without agoraphobia. To rank individual active drugs for panic disorder (antidepressants, benzodiazepines and placebo) according to their effectiveness and acceptability. To rank drug classes for panic disorder (selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), mono-amine oxidase inhibitors (MAOIs) and benzodiazepines (BDZs) and placebo) according to their effectiveness and acceptability. To explore heterogeneity and inconsistency between direct and indirect evidence in a network meta-analysis.

SEARCH METHODS

We searched the Cochrane Common Mental Disorders Specialised Register, CENTRAL, CDSR, MEDLINE, Ovid Embase and PsycINFO to 26 May 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of people aged 18 years or older of either sex and any ethnicity with clinically diagnosed panic disorder, with or without agoraphobia. We included trials that compared the effectiveness of antidepressants and benzodiazepines with each other or with a placebo.

DATA COLLECTION AND ANALYSIS

Two authors independently screened titles/abstracts and full texts, extracted data and assessed risk of bias. We analysed dichotomous data and continuous data as risk ratios (RRs), mean differences (MD) or standardised mean differences (SMD): response to treatment (i.e. substantial improvement from baseline as defined by the original investigators: dichotomous outcome), total number of dropouts due to any reason (as a proxy measure of treatment acceptability: dichotomous outcome), remission (i.e. satisfactory end state as defined by global judgement of the original investigators: dichotomous outcome), panic symptom scales and global judgement (continuous outcome), frequency of panic attacks (as recorded, for example, by a panic diary; continuous outcome), agoraphobia (dichotomous outcome). We assessed the certainty of evidence using threshold analyses.

MAIN RESULTS

Overall, we included 70 trials in this review. Sample sizes ranged between 5 and 445 participants in each arm, and the total sample size per study ranged from 10 to 1168. Thirty-five studies included sample sizes of over 100 participants. There is evidence from 48 RCTs (N = 10,118) that most medications are more effective in the response outcome than placebo. In particular, diazepam, alprazolam, clonazepam, paroxetine, venlafaxine, clomipramine, fluoxetine and adinazolam showed the strongest effect, with diazepam, alprazolam and clonazepam ranking as the most effective. We found heterogeneity in most of the comparisons, but our threshold analyses suggest that this is unlikely to impact the findings of the network meta-analysis. Results from 64 RCTs (N = 12,310) suggest that most medications are associated with either a reduced or similar risk of dropouts to placebo. Alprazolam and diazepam were associated with a lower dropout rate compared to placebo and were ranked as the most tolerated of all the medications examined. Thirty-two RCTs (N = 8569) were included in the remission outcome. Most medications were more effective than placebo, namely desipramine, fluoxetine, clonazepam, diazepam, fluvoxamine, imipramine, venlafaxine and paroxetine, and their effects were clinically meaningful. Amongst these medications, desipramine and alprazolam were ranked highest. Thirty-five RCTs (N = 8826) are included in the continuous outcome reduction in panic scale scores. Brofaromine, clonazepam and reboxetine had the strongest reductions in panic symptoms compared to placebo, but results were based on either one trial or very small trials. Forty-one RCTs (N = 7853) are included in the frequency of panic attack outcome. Only clonazepam and alprazolam showed a strong reduction in the frequency of panic attacks compared to placebo, and were ranked highest. Twenty-six RCTs (N = 7044) provided data for agoraphobia. The strongest reductions in agoraphobia symptoms were found for citalopram, reboxetine, escitalopram, clomipramine and diazepam, compared to placebo. For the pooled intervention classes, we examined the two primary outcomes (response and dropout). The classes of medication were: SSRIs, SNRIs, TCAs, MAOIs and BDZs. For the response outcome, all classes of medications examined were more effective than placebo. TCAs as a class ranked as the most effective, followed by BDZs and MAOIs. SSRIs as a class ranked fifth on average, while SNRIs were ranked lowest. When we compared classes of medication with each other for the response outcome, we found no difference between classes. Comparisons between MAOIs and TCAs and between BDZs and TCAs also suggested no differences between these medications, but the results were imprecise. For the dropout outcome, BDZs were the only class associated with a lower dropout compared to placebo and were ranked first in terms of tolerability. The other classes did not show any difference in dropouts compared to placebo. In terms of ranking, TCAs are on average second to BDZs, followed by SNRIs, then by SSRIs and lastly by MAOIs. BDZs were associated with lower dropout rates compared to SSRIs, SNRIs and TCAs. The quality of the studies comparing antidepressants with placebo was moderate, while the quality of the studies comparing BDZs with placebo and antidepressants was low.

AUTHORS' CONCLUSIONS

In terms of efficacy, SSRIs, SNRIs (venlafaxine), TCAs, MAOIs and BDZs may be effective, with little difference between classes. However, it is important to note that the reliability of these findings may be limited due to the overall low quality of the studies, with all having unclear or high risk of bias across multiple domains. Within classes, some differences emerged. For example, amongst the SSRIs paroxetine and fluoxetine seem to have stronger evidence of efficacy than sertraline. Benzodiazepines appear to have a small but significant advantage in terms of tolerability (incidence of dropouts) over other classes.

Detection bias in open-label trials of anticancer drugs: a meta-epidemiological study

OBJECTIVES

In anticancer clinical trials, particularly open-label trials, central reviewers are recommended to evaluate progression-free survival (PFS) and objective response rate (ORR) to avoid detection bias of local investigators. However, it is not clear whether the bias has been adequately identified, or to what extent it consistently distorts the results. Therefore, the objective of this study was to evaluate the detection bias in oncological open-label trials by confirming whether local investigators overestimate the PFS and ORR compared with the findings of central reviewers.

DESIGN

Meta-epidemiological study.

DATA SOURCES

MEDLINE via PubMed from 1 January 2010 to 30 June 2021.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Open-label, parallel-group superiority, randomised trials of anticancer drugs that adjudicated PFS or ORR by both central reviewers and local investigators.

REVIEW METHODS

We assessed the values for the same outcome (PFS and ORR) adjudicated by both central reviewers and local investigators. A random-effects model was used to estimate the ratio of HR (RHR) for PFS and the ratio of OR (ROR) for ORR between central reviewers and local investigators. An RHR lower than 1 and an ROR higher than 1 indicated an overestimation of the effect estimated by local investigators.

RESULTS

We retrieved 1197 records of oncological open-label trials after full-text screening. We identified 171 records (PFS: 149 records, ORR: 136 records) in which both central reviewers and local investigators were used, and included 114 records (PFS: 92 records, ORR: 74 records) for meta-analyses. While the RHR for PFS was 0.95 (95% CI 0.91 to 0.98), the ROR of ORR was 1.00 (95% CI 0.91 to 1.09). The results remained unchanged in the prespecified sensitivity analysis.

CONCLUSIONS

This meta-epidemiological study found that overestimation of local investigators has a small impact on evaluating PFS and ORR in oncological open-label trials. However, a limitation of this study is that it did not include data from all trials; hence, the results may not fully evaluate detection bias. The necessity of central reviewers in oncological open-label trials needs to be assessed by further studies that overcome this limitation.

TRIAL REGISTRATION NUMBER

CTR-UMIN000044623.

Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis

BACKGROUND

The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been proposed in the literature to account for multiple outcomes and individual preferences, such as the coverage area inside a spie chart, that, however, does not account for a trade-off between efficacy and safety outcomes. We present the net-benefit standardised area within a spie chart, [Formula: see text] to explore the changes in treatment performance with different trade-offs between benefits and harms, according to a particular set of preferences.

METHODS

We combine the standardised areas within spie charts for efficacy and safety/acceptability outcomes with a value λ specifying the trade-off between benefits and harms. We derive absolute probabilities and convert outcomes on a scale between 0 and 1 for inclusion in the spie chart.

RESULTS

We illustrate how the treatments in three published network meta-analyses perform as the trade-off λ varies. The decrease of the [Formula: see text] quantity appears more pronounced for some drugs, e.g. haloperidol. Changes in treatment performance seem more frequent when SUCRA is employed as outcome measures in the spie charts.

CONCLUSIONS

[Formula: see text] should not be interpreted as a ranking metric but it is a simple approach that could help identify which treatment is preferable when multiple outcomes are of interest and trading-off between benefits and harms is important.

Dismantling and personalising task-sharing psychosocial interventions for common mental disorders: a study protocol for an individual participant data component network meta-analysis

INTRODUCTION

Common mental disorders, including depression, anxiety and related somatic health symptoms, are leading causes of disability worldwide. Especially in low-resource settings, psychosocial interventions delivered by non-specialist providers through task-sharing modalities proved to be valid options to expand access to mental healthcare. However, such interventions are usually eclectic multicomponent interventions consisting of different combinations of evidence-based therapeutic strategies. Which of these various components (or combinations thereof) are more efficacious (and for whom) to reduce common mental disorder symptomatology is yet to be substantiated by evidence.

METHODS AND ANALYSIS

Comprehensive search was performed in electronic databases MEDLINE, Embase, PsycINFO and the Cochrane Register of Controlled Trials-CENTRAL from database inception to 15 March 2023 to systematically identify all randomised controlled trials that compared any single component or multicomponent psychosocial intervention delivered through the task-sharing modality against any active or inactive control condition in the treatment of adults suffering from common mental disorders. From these trials, individual participant data (IPD) of all measured outcomes and covariates will be collected. We will dismantle psychosocial interventions creating a taxonomy of components and then apply the IPD component network meta-analysis (IPD-cNMA) methodology to assess the efficacy of individual components (or combinations thereof) according to participant-level prognostic factors and effect modifiers.

ETHICS AND DISSEMINATION

Ethics approval is not applicable for this study since no original data will be collected. Results from this study will be published in peer-reviewed journals and presented at relevant conferences.

Improved methods to construct prediction intervals for network meta-analysis

Network meta-analysis has played an important role in evidence-based medicine for assessing the comparative effectiveness of multiple available treatments. The prediction interval has been one of the standard outputs in recent network meta-analysis as an effective measure that enables simultaneous assessment of uncertainties in treatment effects and heterogeneity among studies. To construct the prediction interval, a large-sample approximating method based on the t-distribution has generally been applied in practice; however, recent studies have shown that similar t-approximation methods for conventional pairwise meta-analyses can substantially underestimate the uncertainty under realistic situations. In this article, we performed simulation studies to assess the validity of the current standard method for network meta-analysis, and we show that its validity can also be violated under realistic situations. To address the invalidity issue, we developed two new methods to construct more accurate prediction intervals through bootstrap and Kenward-Roger-type adjustment. In simulation experiments, the two proposed methods exhibited better coverage performance and generally provided wider prediction intervals than the ordinary t-approximation. We also developed an R package, PINMA (https://cran.r-project.org/web/packages/PINMA/), to perform the proposed methods using simple commands. We illustrate the effectiveness of the proposed methods through applications to two real network meta-analyses.

Comprehensive validation of early diagnostic algorithms for myocardial infarction in the emergency department

OBJECTIVE

To comprehensively evaluate diagnostic algorithms for myocardial infarction using a high-sensitivity cardiac troponin I (hs-cTnI) assay.

PATIENTS AND METHODS

We prospectively enrolled patients with suspected myocardial infarction without ST-segment elevation from nine emergency departments in Japan. The diagnostic algorithms evaluated a) based on hs-cTnI alone, such as the European Society of Cardiology (ESC) 0/1-h or 0/2-h and High-STEACS pathways; or b) used medical history and physical findings, such as the ADAPT, EDACS, HEART, and GRACE pathways. We evaluated the negative predictive value (NPV), sensitivity as safety measures, and proportion of patients classified as low or high-risk as an efficiency measure for a primary outcome of type 1 myocardial infarction or cardiac death within 30 days.

RESULTS

We included 437 patients, and the hs-cTnI was collected at 0 and 1 hours in 407 patients and at 0 and 2 hours in 394. The primary outcome occurred in 8.1% (33/407) and 6.9% (27/394) of patients, respectively. All the algorithms classified low-risk patients without missing those with the primary outcome, except for the GRACE pathway. The hs-cTnI-based algorithms classified more patients as low-risk: the ESC 0/1-h 45.7%; the ESC 0/2-h 50.5%; the High-STEACS pathway 68.5%, than those using history and physical findings (15-30%). The High-STEACS pathway ruled out more patients (20.5%) by hs-cTnI measurement at 0 hours than the ESC 0/1-h and 0/2-h algorithms (7.4%).

CONCLUSIONS

The hs-cTnI algorithms, especially the High-STEACS pathway, had excellent safety performance for the early diagnosis of myocardial infarction and offered the greatest improvement in efficiency.

Dynamics of depressive states among university students in Japan during the COVID-19 pandemic: an interrupted time series analysis

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic was reported to have increased depression among university students which was associated with impairments in their campus lives. This study examined changes in depressive states among Japanese university students during the COVID-19 pandemic.

METHODS

A secondary data analysis from a factorial randomized controlled trial involving smartphone-based cognitive-behavioral therapy was performed. Six cohorts (N = 1626) underwent an 8-week intervention during the spring or autumn of 2019-2021, with a 9-month follow-up. We evaluated participants' depressive states weekly using the Patient Health Questionnaire-9 (PHQ-9) during the intervention, with monthly evaluations thereafter. The follow-up periods included Japan's four states of emergency (SOEs) to control COVID-19. Hypothesizing that SOEs caused a sudden worsening of depressive states, Study 1 compared the cohorts' PHQ-9 scores, and Study 2 employed time series analysis with a mixed-effects model to estimate identified changes in PHQ-9 scores.

RESULTS

Although no changes in depressive states were observed in relation to the SOEs, Study 1 identified sudden increases in PHQ-9 scores at the 28-week evaluation point, which corresponded to the beginning of the new academic year for the three autumn cohorts. In contrast, the three spring cohorts did not exhibit similar changes. Study 2 showed that, for all three autumn cohorts (n = 522), the 0.60-point change was significant (95% CI 0.42-0.78; p < .001) at 28 weeks; that is, when their timeline was interrupted.

CONCLUSIONS

While the results do not indicate any notable impact of the SOEs, they highlight the influence of the new academic year on university students' mental health during COVID-19. Trial registration UMIN, CTR-000031307. Registered on February 14, 2018.

Tool to assess risk of bias in studies estimating the prevalence of mental health disorders (RoB-PrevMH)

OBJECTIVE

There is no standard tool for assessing risk of bias (RoB) in prevalence studies. For the purposes of a living systematic review during the COVID-19 pandemic, we developed a tool to evaluate RoB in studies measuring the prevalence of mental health disorders (RoB-PrevMH) and tested inter-rater reliability.

METHODS

We decided on items and signalling questions to include in RoB-PrevMH through iterative discussions. We tested the reliability of assessments by different users with two sets of prevalence studies. The first set included a random sample of 50 studies from our living systematic review. The second set included 33 studies from a systematic review of the prevalence of post-traumatic stress disorders, major depression and generalised anxiety disorder. We assessed the inter-rater agreement by calculating the proportion of agreement and Kappa statistic for each item.

RESULTS

RoB-PrevMH consists of three items that address selection bias and information bias. Introductory and signalling questions guide the application of the tool to the review question. The inter-rater agreement for the three items was 83%, 90% and 93%. The weighted kappa scores were 0.63 (95% CI 0.54 to 0.73), 0.71 (95% CI 0.67 to 0.85) and 0.32 (95% CI -0.04 to 0.63), respectively.

CONCLUSIONS

RoB-PrevMH is a brief, user-friendly and adaptable tool for assessing RoB in studies on prevalence of mental health disorders. Initial results for inter-rater agreement were fair to substantial. The tool's validity, reliability and applicability should be assessed in future projects.

Global Trends in Highly Cited Studies in COVID-19 Research

Importance

Since the onset of the COVID-19 outbreak, an extremely high number of studies have been published worldwide, with variable quality. Research trends of highly cited papers may enable identification of influential research, providing insights for new research ideas; it is therefore important to investigate trends and focus on more influential publications in COVID-19-related studies.

Objective

To examine research trends of highly cited studies by conducting a bibliometric analysis of highly cited studies in the previous 2 months about COVID-19.

Design, Setting, and Participants

In this cross-sectional study, Essential Science Indicators (ESI) and Web of Science (WOS) Core Collection were used to find studies with a focus on COVID-19 that were identified as highly cited studies from Clarivate Analytics. Highly cited studies were extracted from the ESI database bimonthly between January 2020 and December 2022. Bibliographic details were extracted from WOS and combined with ESI data using unique accession numbers. The number of highly cited studies was counted based on the fractional counting method. Data were analyzed from January through July 2023.

Main Outcomes and Measures

The number of publications by research field, country, and institutional affiliation.

Results

The number of published COVID-19-related highly cited studies was 14 studies in January to February 2020, peaked at 1292 studies in November to December 2021, and showed a downward trend thereafter, reaching 649 studies in November to December 2022. China had the highest number of highly cited studies per 2-month period until July to August 2020 (138.3 studies vs 103.7 studies for the US, the second highest country), and the US had the greatest number of highly cited studies afterward (159.9 studies vs 157.6 studies for China in September to October 2020). Subsequently, the number of highly cited studies per 2-month period published by China declined (decreasing from 179.7 studies in November to December 2020 to 40.7 studies in September to October 2022), and the UK produced the second largest number of such studies in May to June 2021 (171.3 studies). Similarly, the top 5 institutional affiliations in May to June 2020 by highly cited studies per 2-month period were from China (Huazhong University: 14.7 studies; University of Hong Kong: 6.8 studies; Wuhan University: 4.8 studies; Zhejiang University: 4.5 studies; Fudan University: 4.5 studies), while in November to December 2022, the top 5 institutions were in the US and UK (Harvard University: 15.0 studies; University College London: 11.0 studies; University of Oxford: 10.2 studies; University of London: 9.9 studies; Imperial College London: 5.8 studies).

Conclusions and Relevance

This study found that the total number of highly cited studies related to COVID-19 peaked at the end of 2021 and showed a downward trend until the end of 2022, while the origin of these studies shifted from China to the US and UK.

Prevalence of gambling disorder and its correlates among homeless men in Osaka city, Japan

Internationally, the prevalence of gambling disorder has been reported to be higher among homeless people than the general population; however, little is known about the factors associated with gambling disorder in this population. The present study aimed to investigate the prevalence of gambling disorder and its associated factors among homeless men using shelters in Osaka City. A cross-sectional survey was conducted from 30 to 2018 to 4 January 2019, using the 2017 Japanese National Survey of Gambling (JNSG) questionnaire, supplemented with questions about homeless experiences, drinking, and smoking. Using the South Oaks Gambling Screen, the presence of gambling disorder was determined by a score ≥ 5 out of 20. Multivariate logistic regression was conducted to explore factors associated with lifetime gambling disorder. Lifetime and past-year prevalence of gambling disorder among 103 participants was 43.7% (95% confidence interval [CI]: 34.5-53.3) and 3.9% (95% CI: 1.5-9.6), respectively, which are higher than the 6.7% and 1.5% found among men in the 2017 JNSG. Reasons reported for currently gambling less were primarily financial. Factors associated with lifetime GD included "more than 20 years since the first incidence of homelessness" (adjusted odds ratio [AOR]: 4.97, 95% CI: 1.50-16.45) and "more than five incidences of homelessness" (AOR: 4.51, 95% CI: 1.06-19.26). When homeless individuals with gambling disorder try to rebuild and stabilize their lives, the presence or resurgence of gambling disorder may hinder the process and pose a risk of recurring homelessness. Comprehensive support services for homeless individuals with gambling disorder are required. (250 words).

An open competition involving thousands of competitors failed to construct useful abstract classifiers for new diagnostic test accuracy systematic reviews

There are currently no abstract classifiers, which can be used for new diagnostic test accuracy (DTA) systematic reviews to select primary DTA study abstracts from database searches. Our goal was to develop machine-learning-based abstract classifiers for new DTA systematic reviews through an open competition. We prepared a dataset of abstracts obtained through database searches from 11 reviews in different clinical areas. As the reference standard, we used the abstract lists that required manual full-text review. We randomly splitted the datasets into a train set, a public test set, and a private test set. Competition participants used the training set to develop classifiers and validated their classifiers using the public test set. The classifiers were refined based on the performance of the public test set. They could submit as many times as they wanted during the competition. Finally, we used the private test set to rank the submitted classifiers. To reduce false exclusions, we used the Fbeta measure with a beta set to seven for evaluating classifiers. After the competition, we conducted the external validation using a dataset from a cardiology DTA review. We received 13,774 submissions from 1429 teams or persons over 4 months. The top-honored classifier achieved a Fbeta score of 0.4036 and a recall of 0.2352 in the external validation. In conclusion, we were unable to develop an abstract classifier with sufficient recall for immediate application to new DTA systematic reviews. Further studies are needed to update and validate classifiers with datasets from other clinical areas.

Kenward-Roger-type corrections for inference methods of network meta-analysis and meta-regression

Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average treatment effect parameters in random-effects models can seriously underestimate statistical errors; that is, the actual coverage probability of a true parameter cannot retain the nominal level (e.g., 95%). In this article, we provided improved inference methods for the network meta-analysis and meta-regression models using higher-order asymptotic approximations based on the approach of Kenward and Roger (Biometrics 1997;53:983-997). We provided two corrected covariance matrix estimators for the REML estimator and improved approximations for its sample distribution using a t-distribution with adequate degrees of freedom. All of the proposed procedures can be implemented using only simple matrix calculations. In simulation studies under various settings, the REML-based Wald-type confidence intervals seriously underestimated the statistical errors, especially in cases of small numbers of trials meta-analyzed. By contrast, the proposed Kenward-Roger-type inference methods consistently showed accurate coverage properties under all the settings considered in our experiments. We also illustrated the effectiveness of the proposed methods through applications to two real network meta-analysis datasets.

Major depressive disorder

Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and physical and cognitive symptoms. People with MDD can have reduced quality of life owing to the disorder itself as well as related medical comorbidities, social factors, and impaired functional outcomes. MDD is a complex disorder that cannot be fully explained by any one single established biological or environmental pathway. Instead, MDD seems to be caused by a combination of genetic, environmental, psychological and biological factors. Treatment for MDD commonly involves pharmacological therapy with antidepressant medications, psychotherapy or a combination of both. In people with severe and/or treatment-resistant MDD, other biological therapies, such as electroconvulsive therapy, may also be offered.

Development and validation of a prediction model for rehospitalization among people with schizophrenia discharged from acute inpatient care

Objective

Relapses and rehospitalization prevent the recovery of individuals with schizophrenia or related psychoses. We aimed to build a model to predict the risk of rehospitalization among people with schizophrenia or related psychoses, including those with multiple episodes.

Methods

This retrospective cohort study included individuals aged 18 years or older, with schizophrenia or related psychoses, and discharged between January 2014 and December 2018 from one of three Japanese psychiatric hospital acute inpatient care ward. We collected nine predictors at the time of recruitment, followed up with the participants for 12 months, and observed whether psychotic relapse had occurred. Next, we applied the Cox regression model and used an elastic net to avoid overfitting. Then, we examined discrimination using bootstrapping, Steyerberg's method, and "leave-one-hospital-out" cross-validation. We also constructed a bias-corrected calibration plot.

Results

Data from a total of 805 individuals were analyzed. The significant predictors were the number of previous hospitalizations (HR 1.42, 95% CI 1.22-1.64) and the current length of stay in days (HR 1.31, 95% CI 1.04-1.64). In model development for relapse, Harrell's c-index was 0.59 (95% CI 0.55-0.63). The internal and internal-external validation for rehospitalization showed Harrell's c-index to be 0.64 (95% CI 0.59-0.69) and 0.66 (95% CI 0.57-0.74), respectively. The calibration plot was found to be adequate.

Conclusion

The model showed moderate discrimination of readmission after discharge. Carefully defining a research question by seeking needs among the population with chronic schizophrenia with multiple episodes may be key to building a useful model.

Twenty-year follow-up of promising clinical studies reported in highly circulated newspapers: a meta-epidemiological study

OBJECTIVES

Researchers have identified cases in which newspaper stories have exaggerated the results of medical studies reported in original articles. Moreover, the exaggeration sometimes begins with journal articles. We examined what proportion of the studies quoted in newspaper stories were confirmed.

METHODS

We identified newspaper stories from 2000 that mentioned the effectiveness of certain treatments or preventions based on original studies from 40 main medical journals. We searched for subsequent studies until June 2022 with the same topic and stronger research design than each original study. The results of the original studies were verified by comparison with those of subsequent studies.

RESULTS

We identified 164 original articles from 1298 newspaper stories and randomly selected 100 of them. Four studies were not found to be effective in terms of the primary outcome, and 18 had no subsequent studies. Of the remaining studies, the proportion of confirmed studies was 68.6% (95% CI 58.1% to 77.5%). Among the 59 confirmed studies, 13 of 16 studies were considered to have been replicated in terms of effect size. However, the results of the remaining 43 studies were not comparable.

DISCUSSION

In the dichotomous judgement of effectiveness, about two-thirds of the results were nominally confirmed by subsequent studies. However, for most confirmed results, it was impossible to determine whether the effect sizes were stable.

CONCLUSIONS

Newspaper readers should be aware that some claims made by high-quality newspapers based on high-profile journal articles may be overturned by subsequent studies within the next 20 years.

New living evidence resource of human and non-human studies for early intervention and research prioritisation in anxiety, depression and psychosis

In anxiety, depression and psychosis, there has been frustratingly slow progress in developing novel therapies that make a substantial difference in practice, as well as in predicting which treatments will work for whom and in what contexts. To intervene early in the process and deliver optimal care to patients, we need to understand the underlying mechanisms of mental health conditions, develop safe and effective interventions that target these mechanisms, and improve our capabilities in timely diagnosis and reliable prediction of symptom trajectories. Better synthesis of existing evidence is one way to reduce waste and improve efficiency in research towards these ends. Living systematic reviews produce rigorous, up-to-date and informative evidence summaries that are particularly important where research is emerging rapidly, current evidence is uncertain and new findings might change policy or practice. Global Alliance for Living Evidence on aNxiety, depressiOn and pSychosis (GALENOS) aims to tackle the challenges of mental health science research by cataloguing and evaluating the full spectrum of relevant scientific research including both human and preclinical studies. GALENOS will also allow the mental health community-including patients, carers, clinicians, researchers and funders-to better identify the research questions that most urgently need to be answered. By creating open-access datasets and outputs in a state-of-the-art online resource, GALENOS will help identify promising signals early in the research process. This will accelerate translation from discovery science into effective new interventions for anxiety, depression and psychosis, ready to be translated in clinical practice across the world.

Which psychotherapy is most effective and acceptable in the treatment of adults with a (sub)clinical borderline personality disorder? A systematic review and network meta-analysis

A broad range of psychotherapies have been proposed and evaluated in the treatment of borderline personality disorder (BPD), but the question which specific type of psychotherapy is most effective remains unanswered. In this study, two network meta-analyses (NMAs) were conducted investigating the comparative effectiveness of psychotherapies on (1) BPD severity and (2) suicidal behaviour (combined rate). Study drop-out was included as a secondary outcome. Six databases were searched until 21 January 2022, including RCTs on the efficacy of any psychotherapy in adults (⩾18 years) with a diagnosis of (sub)clinical BPD. Data were extracted using a predefined table format. PROSPERO ID:CRD42020175411. In our study, a total of 43 studies (N = 3273) were included. We found significant differences between several active comparisons in the treatment of (sub)clinical BPD, however, these findings were based on very few trials and should therefore be interpreted with caution. Some therapies were more efficacious compared to GT or TAU. Furthermore, some treatments more than halved the risk of attempted suicide and committed suicide (combined rate), reporting RRs around 0.5 or lower, however, these RRs were not statistically significantly better compared to other therapies or to TAU. Study drop-out significantly differed between some treatments. In conclusion, no single treatment seems to be the best choice to treat people with BPD compared to other treatments. Nevertheless, psychotherapies for BPD are perceived as first-line treatments, and should therefore be investigated further on their long-term effectiveness, preferably in head-to-head trials. DBT was the best connected treatment, providing solid evidence of its effectiveness.

Estimating Patient-Specific Relative Benefit of Adding Biologics to Conventional Rheumatoid Arthritis Treatment: An Individual Participant Data Meta-Analysis

Importance

Current evidence remains ambiguous regarding whether biologics should be added to conventional treatment of rheumatoid arthritis for specific patients, which may cause potential overuse or treatment delay.

Objectives

To estimate the benefit of adding biologics to conventional antirheumatic drugs for the treatment of rheumatoid arthritis given baseline characteristics.

Data Sources

Cochrane CENTRAL, Scopus, MEDLINE, and the World Health Organization International Clinical Trials Registry Platform were searched for articles published from database inception to March 2, 2022.

Study Selection

Randomized clinical trials comparing certolizumab plus conventional antirheumatic drugs with placebo plus conventional drugs were selected.

Data Extraction and Synthesis

Individual participant data of the prespecified outcomes and covariates were acquired from the Vivli database. A 2-stage model was fitted to estimate patient-specific relative outcomes of adding certolizumab vs conventional drugs only. Stage 1 was a penalized logistic regression model to estimate the baseline expected probability of the outcome regardless of treatment using baseline characteristics. Stage 2 was a bayesian individual participant data meta-regression model to estimate the relative outcomes for a particular baseline expected probability. Patient-specific results were displayed interactively on an application based on a 2-stage model.

Main Outcomes and Measures

The primary outcome was low disease activity or remission at 3 months, defined by 3 disease activity indexes (ie, Disease Activity Score based on the evaluation of 28 joints, Clinical Disease Activity Index, or Simplified Disease Activity Index).

Results

Individual participant data were obtained from 3790 patients (2996 female [79.1%] and 794 male [20.9%]; mean [SD] age, 52.7 [12.3] years) from 5 large randomized clinical trials for moderate to high activity rheumatoid arthritis with usable data for 22 prespecified baseline covariates. Overall, adding certolizumab was associated with a higher probability of reaching low disease activity. The odds ratio for patients with an average baseline expected probability of the outcome was 6.31 (95% credible interval, 2.22-15.25). However, the benefits differed in patients with different baseline characteristics. For example, the estimated risk difference was smaller than 10% for patients with either low or high baseline expected probability.

Conclusions and Relevance

In this individual participant data meta-analysis, adding certolizumab was associated with more effectiveness for rheumatoid arthritis in general. However, the benefit was uncertain for patients with low or high baseline expected probability, for whom other evaluations were necessary. The interactive application displaying individual estimates may help with treatment selection.

Protocol for development of an assessment tool for competency of ECG interpretation: expert consensus by the RAND/UCLA appropriateness method and cross-sectional testing using multidimensional item response theory

INTRODUCTION

Although the ECG is an important diagnostic tool in medical practice, the competency of ECG interpretation is considered to be poor. Diagnostic inaccuracy involving the misinterpretation of ECG can lead to inappropriate medical judgements and cause negative clinical outcomes, unnecessary medical testing and even fatalities. Despite the importance of assessing ECG interpretation skills, there is currently no established universal, standardised assessment tool for ECG interpretation. The current study seeks to (1) develop a set of items (ECG questions) for estimating competency of ECG interpretation by medical personnel by consensus among expert panels following a process based on the RAND/UCLA Appropriateness Method (RAM) and (2) analyse item parameters and multidimensional latent factors of the test set to develop an assessment tool.

METHODS AND ANALYSIS

This study will be conducted in two steps: (1) selection of question items for ECG interpretation assessment by expert panels via a consensus process following RAM and (2) cross-sectional, web-based testing using a set of ECG questions. A multidisciplinary panel of experts will evaluate the answers and appropriateness and select 50 questions as the next step. Based on data collected from a predicted sample size of 438 test participants recruited from physicians, nurses, medical and nursing students, and other healthcare professionals, we plan to statistically analyse item parameters and participant performance using multidimensional item response theory. Additionally, we will attempt to detect possible latent factors in the competency of ECG interpretation. A test set of question items for ECG interpretation will be proposed on the basis of the extracted parameters.

ETHICS AND DISSEMINATION

The protocol of this study was approved by the Institutional Review Board of Ehime University Graduate School of Medicine (IRB number: 2209008). We will obtain informed consent from all participants. The findings will be submitted for publication in peer-reviewed journals.