Factorial Validity of the 32-Item World Health Organization Disability Assessment Schedule 2.0 in Persons With Stroke.

Background And Purpose: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-established tool for assessing disability.

Hypoactivity of the Prefrontal Cortex During Go/No-Go Task in Patients With Generalized Anxiety Disorder.

Generalized anxiety disorder (GAD) is a prevalent mental health condition affecting cognitive functions like response inhibition. The neural mechanisms underlying the interplay between inhibitory ability and anxiety regulation in GAD remain unclear. This study aimed to investigate the prefrontal cortex (PFC) alterations when anxiety regulation shares neural resources with response inhibition in patients with GAD compared to healthy controls and to explore the relationship between anxiety and PFC activity.

Increased body mass index may have more happiness, life satisfaction, and self-rated health in the aging process: A 10-year longitudinal study.

Understanding intricate relationships among various determinants of overall well-being is crucial for promoting healthy aging. The body mass index (BMI), happiness, life satisfaction, and self-rated health are key indicators of well-being in older adults. However, the dynamic interplay among these factors and the BMI was previously unclear.

Development of a Computerized Adaptive Testing System of the World Health Organization Disability Assessment Schedule 2.0 (CAT-WHODAS 2.0) for People With Dementia.

Importance: Widely used for assessing levels of disability, the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) provides informative profiles for six life perspectives.

Machine Learning-based World Health Organization Disability Assessment Schedule for persons with Parkinson's disease.

Introduction: The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a well-known measure to assess disability in persons with Parkinson's disease (PD).

Predicting Age and Visual-Motor Integration Using Origami Photographs: Deep Learning Study.

Background: Origami is a popular activity among preschool children and can be used by therapists as an evaluation tool to assess children's development in clinical settings. It is easy to implement, appealing to children, and time-efficient, requiring only simple materials-pieces of paper. Furthermore, the products of origami may reflect children's ages and their visual-motor integration (VMI) development.

eHealth Interventions of Health Literacy for Stroke Survivors: Systematic Review and Meta-Analysis.

Background: eHealth literacy interventions have emerged as a new approach in management of stroke survivors. Its effect on knowledge and clinical outcomes presents an inconsistent result in literature.

Objectives: We aim to evaluate the impact of eHealth interventions on health literacy, clinical metrics, adherence to healthy behaviors, stroke recurrence, mortality, and health-related quality of life in stroke survivors.

Quantifying Coloring Skills Among Preschoolers.

Importance: Coloring is popular with preschool children and reveals their developmental state. However, interpreting coloring performances is challenging because descriptive and subjective evaluations are commonly used with large variations.

Objective: To develop a scoring method to objectively quantify children's coloring skills.

Developing a machine learning-based short form of the positive and negative syndrome scale.

Background And Hypothesis: The Positive and Negative Syndrome Scale (PANSS) consists of 30 items and takes up to 50 minutes to administer and score. Therefore, this study aimed to develop and validate a machine learning-based short form of the PANSS (PANSS-MLSF) that reproduces the PANSS scores. Moreover, the PANSS-MLSF estimated the removed-item scores.

Leisure Participation for Mental Health Promotion in Later Life: A Six-Year Longitudinal Study.

Engaging in leisure activities is essential for mental health in older adults. This longitudinal study ( = 1,101, mean age = 69.20 ± 6.

Using Artificial Intelligence to Identify the Associations of Children's Performance of Coloring, Origami, and Copying Activities With Visual-Motor Integration.

Importance: Performance of coloring, origami, and copying activities reflects children's visual-motor integration (VMI), but the levels of association remain unclear.

Objective: To use artificial intelligence (AI) to investigate associations of performance of coloring, origami, and copying activities with VMI.

Design: Cross-sectional study.

Optical power degradation mechanisms in 271 nm AlGaN-based deep ultraviolet light-emitting diodes.

The degradation of AlGaN-based UVC LEDs under constant temperature and constant current stress for up to 500 hrs was analyzed in this work. During each degradation stage, the two-dimensional (2D) thermal distributions, I-V curves, optical powers, combining with focused ion beam and scanning electron microscope (FIB/SEM), were thoroughly tested and analyzed the properties and failure mechanisms of UVC LEDs. The results show that: 1) the opto-electrical characteristics measured before/during stress indicate that the increased leakage current and the generation of stress-induced defects increase the non-radiative recombination in the early stress stage, resulting in a decrease in optical power; 2) the increase of temperature caused by the deterioration of the Cr/Al layer of p-metal after 48 hrs of stress aggravates the optical power in UVC LEDs.

Development of a 13-item Short Form for Fugl-Meyer Assessment of Upper Extremity Scale Using a Machine Learning Approach.

Objective: To develop and validate a short form of the Fugl-Meyer Assessment of Upper Extremity Scale (FMA-UE) using a machine learning approach (FMA-UE-ML). In addition, scores of items not included in the FMA-UE-ML were predicted.

Design: Secondary data from a previous study, which assessed individuals post-stroke using the FMA-UE at 4 time points: 5-30 days post-stroke screen, 2-month post-stroke baseline assessment, 6-month post-stroke assessment, and 12-month post-stroke assessment.

Machine learning-based brief version of the Caregiver-Teacher Report Form for preschoolers.

Background: The Caregiver-Teacher Report Form of the Child Behavior Checklist for Ages 1½-5 (C-TRF) is a widely used checklist to identify emotional and behavioral problems in preschoolers. However, the 100-item C-TRF restricts its utility.

Aims: This study aimed to develop a machine learning-based short-form of the C-TRF (C-TRF-ML).

Development of a Short-Form Stroke Impact Scale Using a Machine Learning Algorithm for Patients at the Subacute Stage.

Importance: Several short forms of the Stroke Impact Scale Version 3.0 (SIS 3.0) have been proposed in order to decrease its administration time of about 20 min.

High levels of screen time were associated with increased probabilities of lagged development in 3-year-old children.

Aim: This study determined whether higher screen time was associated with the development of 3-year-old children in Taiwan. It also examined whether differences would be found between television and other screen-based media in the probability of lagged development.

Methods: We examined 2139 children aged 3 years and their parents.

Error patterns of facial emotion recognition in patients with schizophrenia.

Error patterns of facial emotion recognition (FER) indicate how individuals misinterpret others' facial expressions, which helps clinicians to manage related deficits. However, previous investigations are limited and may have been biased due to methodological issues (e.g.

Using Machine Learning to Develop a Short-Form Measure Assessing 5 Functions in Patients With Stroke.

Objective: This study aimed to develop and validate a machine learning-based short measure to assess 5 functions (the ML-5F) (activities of daily living [ADL], balance, upper extremity [UE] and lower extremity [LE] motor function, and mobility) in patients with stroke.

Design: Secondary data from a previous study. A follow-up study assessed patients with stroke using the Barthel Index (BI), Postural Assessment Scale for Stroke (PASS), and Stroke Rehabilitation Assessment of Movement (STREAM) at hospital admission and discharge.

Cross-Validation of the Factorial Validity of the Stroke Impact Scale 3.0 in Patients With Stroke.

Importance: The Stroke Impact Scale 3.0 appears to be a promising outcome measure of health-related quality of life (HRQOL) for clients with stroke. However, because the factorial validity of the Stroke Impact Scale 3.

A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

Objective: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of this study was to develop a short form of the FM for people with stroke using a machine-learning methodology (FM-ML) and compare the efficiency (ie, number of items) and psychometric properties of the FM-ML with those of other FM versions, including the original FM, the 37-item FM, and the 12-item FM.

Development of the CAT-FER: A Computerized Adaptive Test of Facial Emotion Recognition for Adults With Schizophrenia.

Importance: The most frequently used measures of facial emotion recognition (FER) are insufficiently comprehensive, reliable, valid, and efficient; moreover, the impact of gender on scoring has not been controlled.

Objective: To develop a computerized adaptive test of FER for adults with schizophrenia.

Design: First, we selected photographs from a published database.

Improving the utility of the European Health Literacy Survey Questionnaire: a computerized adaptive test for patients with stroke.

Purpose: Health literacy among patients is crucial for effective stroke management. The European Health Literacy Survey Questionnaire is a theory-based measure that comprehensively captures 12 domains of health literacy. We aimed to develop a computerized adaptive test of the European Health Literacy Survey Questionnaire to efficiently assess health literacy among patients with stroke.

Practice Effects and Test-Retest Reliability of the Continuous Performance Test, Identical Pairs Version in Patients with Schizophrenia over Four Serial Assessments.

Objective: The purposes of this study were to examine the practice effects and test-retest reliability of the Continuous Performance Test, Identical Pairs version (CPT-IP) over four serial assessments in patients with schizophrenia.

Method: Fifty-six patients with schizophrenia were assessed with the CPT-IP four times, once per week. The CPT-IP contains four indices: "2-digit score," "3-digit score," "4-digit score," and "total score.

A Comparison of the Responsiveness of the Postural Assessment Scale for Stroke and the Berg Balance Scale in Patients With Severe Balance Deficits After Stroke.

Background And Purpose: Previous evidence that the Postural Assessment Scale for Stroke (PASS) and the Berg Balance Scale (BBS) have similar responsiveness is doubtful. Compared with the BBS, the PASS has more items assessing basic balance abilities (such as postural transition during lying and sitting), so it should be more likely to detect changes in patients with severe balance deficits. We aimed to compare the responsiveness of the PASS and the BBS in patients with stroke who have severe balance deficits.