SAS macro programme for Bang's Blinding Index to assess and visualise the success of blinding in randomised controlled trials.

This paper aims to present a Statistical Analysis Software (SAS) macro %BBIplus, offering estimation and visualisation methods for the Bang's Blinding Index (BBI) for randomised controlled trials (RCTs) with various designs. We developed the SAS macro programme %BBIplus to facilitate the implementation of BBI. This user-friendly programme allows for easy and rapid estimation and visualisation of BBI across different scenarios, including pairwise comparison RCTs with two arms, double-dummy design RCTs with three arms and factorial design RCTs with four arms.

Initial treatment choices for long-term remission of chronic insomnia disorder in adults: a systematic review and network meta-analysis.

Background: We aimed to evaluate the comparative efficacy and acceptability of cognitive behavioral therapy for insomnia (CBT-I), pharmacotherapy, and their combination in the long and short terms among adults with chronic insomnia disorder.

Methods: We searched multiple databases to December 27, 2023. We included trials in hypnotic-free adults with chronic insomnia comparing at least two of CBT-I, pharmacotherapy, or their combination.

Association of Problematic Internet Use With Psychotic Experiences and Depression in Adolescents: A Cohort Study.

Background And Hypothesis: Problematic internet use (PIU) is prevalent among adolescents. Past research suggested cross-sectional associations between PIU and psychotic experiences, but little information is available on the longitudinal association. We hypothesized that PIU in adolescence may be longitudinally associated with psychotic experiences, adjusting for confounders.

Shortening the Alzheimer's disease assessment scale cognitive subscale.

Background: A short yet reliable cognitive measure is needed that separates treatment and placebo for treatment trials for Alzheimer's disease. Hence, we aimed to shorten the ' (ADAS-Cog) and test its use as an efficacy measure.

Methods: Secondary data analysis of participant-level data from five pivotal clinical trials of donepezil compared with placebo for Alzheimer's disease (N = 2,198).

Development of a model to predict antidepressant treatment response for depression among Veterans.

Background: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA).

Methods: A 2018-2020 national sample of = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment.

Relationship between Clinical Severity and Cross-sectional Area of Ultrasonographic Examinations in Ulnar Neuropathy at the Elbow.

Objectives: This study explored the relationship between clinical severity of ulnar neuropathy at the elbow (UNE) and ulnar nerve cross-sectional area (CSA) by ultrasound examination to identify appropriate measurement sites for UNE diagnosis and evaluation.

Methods: In this retrospective analysis, we examined the arms of 37 patients diagnosed with UNE and those of 34 individuals as controls. The ulnar nerve CSAs were measured at 2 cm distal to the tip of the medial epicondyle (dME), the tip of the medial epicondyle (ME), 2 cm proximal to the tip of the medial epicondyle (pME), and any site showing the maximum CSA between the dME and pME (largest dpME).

Optimization of smartphone psychotherapy for depression and anxiety among patients with cancer using the multiphase optimization strategy (MOST) framework and decentralized clinical trial system (SMartphone Intervention to LEssen depression/Anxiety and GAIN resilience: SMILE AGAIN project): a protocol for a randomized controlled trial.

Background: Cancer patients experience various forms of psychological distress. Their distress, mainly in the form of depression and anxiety, leads to poor quality of life, increased medical spending due to frequent visits, and decrease in treatment adherence. It is estimated that 30-50% among them would require support from mental health professionals: in reality, much less actually receive such support partly due to a shortage of qualified professionals and also due to psychological barriers in seeking such help.

Behavioral change stage might moderate the impact of multifaceted interventions on non-attendance from medical care among patients with type 2 diabetes: The Japan Diabetes Outcome Intervention Trial-2 Large-Scale Trial 007 (J-DOIT2-LT007).

Aims/introduction: Non-attendance from regular medical care is a major problem in diabetes patients. This study aimed to examine the impact of a multifaceted lifestyle intervention by face-to-face approach (FFA) on non-attendance from regular medical care in comparison with that by telephone from the technical support center (TSC).

Materials And Methods: This was secondary analysis from a 1-year, prospective, cluster randomized, intervention study.

Development of a model to predict combined antidepressant medication and psychotherapy treatment response for depression among veterans.

Background: Although research shows that more depressed patients respond to combined antidepressants (ADM) and psychotherapy than either alone, many patients do not respond even to combined treatment. A reliable prediction model for this could help treatment decision-making. We attempted to create such a model using machine learning methods among patients in the US Veterans Health Administration (VHA).

Measuring the performance of prediction models to personalize treatment choice.

When data are available from individual patients receiving either a treatment or a control intervention in a randomized trial, various statistical and machine learning methods can be used to develop models for predicting future outcomes under the two conditions, and thus to predict treatment effect at the patient level. These predictions can subsequently guide personalized treatment choices. Although several methods for validating prediction models are available, little attention has been given to measuring the performance of predictions of personalized treatment effect.

Personalized Prediction of Alzheimer's Disease and Its Treatment Effects by Donepezil: An Individual Participant Data Meta-Analysis of Eight Randomized Controlled Trials.

Background: Patient characteristics may predict the progression of Alzheimer's disease (AD) and may moderate the effects of donepezil.

Objective: To build a personalized prediction model for patients with AD and to estimate patient-specific treatment effects of donepezil, using individual patient characteristics.

Methods: We systematically searched for all double-masked randomized controlled trials comparing oral donepezil and pill placebo in the treatment of AD and requested individual participant data through its developer, Eisai.

Development and validation of the Japanese version of the uMARS (user version of the mobile app rating system).

Background: Although the global market of Mobile Health Apps (mHealth apps) continues to grow dramatically, most mHealth apps still not only lack evidence base but have even not been evaluated for the basic usability or functionality. The User Version of the Mobile App Rating Scale (uMARS) was developed to allow end users to assess mHealth apps objectively and subjectively. However, there is no Japanese version of uMARS to date.

Early- and subsequent- response of cognitive functioning in Alzheimer's disease: Individual-participant data from five pivotal randomized clinical trials of donepezil.

The association between early improvement and subsequent change in cognition is unexamined in antidementia clinical trials. We aimed to examine the consequences of early-response to antidementia medication in Alzheimer's disease. Participant-level data were analyzed from five pivotal clinical trials of donepezil for Alzheimer's disease lasting up to 24 weeks (N = 1917).

Cognitive impairment networks in Alzheimer's disease: Analysis of three double-blind randomized, placebo-controlled, clinical trials of donepezil.

Psychometric network analysis is an alternative theoretically-driven analytic approach that has the potential to conceptualize cognitive impairment in Alzheimer's disease differently than was previously assumed and consequently detect unknown treatment effects. Based on individual participant data, extracted from three double-blind, randomized placebo-controlled clinical trials, psychometric networks were computed on observed Alzheimer's Disease Assessment Scale Cognitive Subscale scores at baseline (N=1,554) and on predicted change scores at 24 weeks of follow-up for participants who received donepezil (N=797) or placebo (N=484). A novel conceptualization of cognitive impairment in Alzheimer's disease was displayed through the baseline network, that had 90% (n=27) positive statistically significant (p<0.

Association of Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder Traits with Depression and Empathy Among Medical Students.

Purpose: This study aimed to investigate the associations of the traits of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) with depression and empathy among medical students.

Patients And Methods: A cross-sectional survey was conducted with 202 fifth-year students at a Japanese medical school for 10 months during their clinical clerkship. The survey included sociodemographic questions and validated tools to measure depressive symptoms (Hospital Anxiety and Depression Scale [HADS]), medical students' empathy for patients (Jefferson Scale of Empathy-Student version [JSE]), ADHD traits (ADHD Self-Report Scale Screener [ASRS Screener]), and ASD traits (Autism-Spectrum Quotient Japanese version-21 [AQ-J-21]).

Utility of a novel tablet computer software for memory impairment in participants with brain injuries: A randomized control trial.

This study examined the effectiveness of a novel information and communication technology (ICT) tool developed for external memory compensation to improve memory function in participants with brain injuries. In this 3-month randomized control study, participants with memory impairment secondary to brain injury were randomly assigned on a 1:1 basis to either intervention (the ICT tool [ARATA]) or 3-month waitlist control groups. This study's primary outcome measure was memory-related difficulties in everyday life, assessed using the Everyday Memory Checklist (EMC).

The GAD-7 and the PHQ-8 exhibit the same mathematical pattern of item responses in the general population: analysis of data from the National Health Interview Survey.

Background: Recent studies have shown that, among the general population, responses to depression-rating scales follow a common mathematical pattern. However, the mathematical pattern among responses to the items of the Generalized Anxiety Disorder-7 (GAD-7) is currently unknown. The present study investigated whether item responses to the GAD-7, when administered to the general population, follow the same mathematical distribution as those of depression-rating scales.

Fingertip advanced glycation end products and psychotic symptoms among adolescents.

Case control studies have suggested that advanced glycation end products play a key role in the pathophysiology of chronic schizophrenia. However, the longitudinal association between advanced glycation end products and psychotic symptoms among drug-naïve adolescents remains unclear. This study examined whether advanced glycation end products could predict the trajectory of psychotic symptoms in drug-naive adolescents using data from prospective population-based biomarker subsample study of the Tokyo Teen Cohort.