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Psychometrics

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A systematic review on the application of machine learning models in psychometric questionnaires for the diagnosis of attention deficit hyperactivity disorder.

The European journal of neuroscience
Attention deficit hyperactivity disorder is one of the most prevalent neurodevelopmental disorders worldwide. Recent studies show that machine learning has great potential for the diagnosis of attention deficit hyperactivity disorder. The aim of the ...

Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven shortened version from a machine learning approach.

Sleep medicine
BACKGROUND: The Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) is a widely used self-report instrument for identifying sleep-related cognition. However, its length can be cumbersome in clinical practice. This study aims to develop a ...

Cognitive diagnostic assessment: A Q-matrix constraint-based neural network method.

Behavior research methods
Cognitive diagnosis is a crucial element of intelligent education that aims to assess the proficiency of specific skills or traits in students at a refined level and provide insights into their strengths and weaknesses for personalized learning. Rese...

Data-driven shortened Insomnia Severity Index (ISI): a machine learning approach.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: The Insomnia Severity Index (ISI) is a widely used questionnaire with seven items for identifying the risk of insomnia disorder. Although the ISI is still short, more shortened versions are emerging for repeated monitoring in routine clin...

Using machine learning to develop a five-item short form of the children's depression inventory.

BMC public health
BACKGROUND: Many adolescents experience depression that often goes undetected and untreated. Identifying children and adolescents at a high risk of depression in a timely manner is an urgent concern. While the Children's Depression Inventory (CDI) is...

A neural network paradigm for modeling psychometric data and estimating IRT model parameters: Cross estimation network.

Behavior research methods
This paper presents a novel approach known as the cross estimation network (CEN) for fitting the datasets obtained from psychological or educational tests and estimating the parameters of item response theory (IRT) models. The CEN is comprised of two...

Instruments for Measuring Psychological Dimensions in Human-Robot Interaction: Systematic Review of Psychometric Properties.

Journal of medical Internet research
BACKGROUND: Numerous user-related psychological dimensions can significantly influence the dynamics between humans and robots. For developers and researchers, it is crucial to have a comprehensive understanding of the psychometric properties of the a...

Developing an Accumulative Assessment System of Upper Extremity Motor Function in Patients With Stroke Using Deep Learning.

Physical therapy
OBJECTIVE: The Fugl-Meyer assessment for upper extremity (FMA-UE) is a measure for assessing upper extremity motor function in patients with stroke. However, the considerable administration time of the assessment decreases its feasibility. This study...

Validating the AI-assisted second language (L2) learning attitude scale for Chinese college students and its correlation with L2 proficiency.

Acta psychologica
The positive impact of Artificial Intelligence (AI) on second language (L2) learning is well-documented. An individual's attitude toward AI significantly influences its adoption. Despite this, no specific scale has been designed to measure this attit...

Developing a machine learning-based instrument for subjective well-being assessment on Weibo and its psychological significance: An evaluative and interpretive research.

Applied psychology. Health and well-being
Demystifying machine learning (ML) approaches through the synergy of psychology and artificial intelligence can achieve a balance between predictive and explanatory power in model development while enhancing rigor in validation and reporting standard...