ArticleFrontiers in psychology2019
Machine Learning in Psychometrics and Psychological Research.
Article in Frontiers in psychology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
66 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Exploring Adaptive Virtual Reality Systems Used in Interventions for Children With Autism Spectrum Disorder: Systematic Review.Journal of medical Internet research · 2024Pooled it
- How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.Cadernos de saude publica · 2024Pooled it
- Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review.Journal of autism and developmental disorders · 2022Pooled it
- Mindfulness, Compassion, and Self-Compassion Among Health Care Professionals: What's New? A Systematic Review.Frontiers in psychology · 2020Pooled it
- Predicting longitudinal post-traumatic stress disorder symptoms using psychological measures and heart rate variability: a machine-learning approach.European journal of psychotraumatology · 2026Article
- Predicting suicidal ideation in academic communities using machine learning methods: a cross-sectional study.Lancet regional health. Americas · 2026Article
- Profiles of Smartphone Addiction Risk Among Middle School Students: The Roles of Childhood Neglect and Materialism Using Latent Profile Analysis, Network Analysis, and Machine Learning.European journal of investigation in health, psychology and education · 2026Article
- Machine Learning Approach for Predicting Older Adults' Responsiveness to Cognitive Training Interventions: Data from the ACTIVE Study.Journal of Intelligence · 2026Article
- Factors associated with psychological distress among family caregivers of preschool children with autism: an analysis.Frontiers in psychiatry · 2026Article
- Behavioral profile predicts ethanol preference in adolescent mice, but not in adults: A machine learning approach.Alcohol, clinical & experimental research · 2026Article
- Machine learning clustering of psychological response trajectories across the first and second waves of the COVID-19 pandemic.Frontiers in psychiatry · 2026Article
- Machine learning-optimized perinatal depression screening: Maximum impact, minimal burden.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Sleep disturbances predict nine-year panic disorder chronicity: The sleep-panic nexus theory with machine learning insights.Journal of anxiety disorders · 2025Article
- A Machine-Learning-Based Approach to Informing Student Admission Decisions.Behavioral sciences (Basel, Switzerland) · 2025Article
- Beyond the hot flashes: how machine learning is uncovering the complexity of menopause-related depression.CNS spectrums · 2025Article
- Behavioral science of voting in hypothetical utopia and dystopia scenarios: a predictive modeling approach.Frontiers in psychology · 2025Article
- Predicting depression among men who have sex with men in Ghana using machine learning algorithms.PLOS mental health · 2025Article
- Comparing chatbots to psychometric tests in hiring: reduced social desirability bias, but lower predictive validity.Frontiers in psychology · 2025Article
- Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent controversies about the level of replicability of behavioral research analyzed using statistical inference have cast interest in developing more efficient techniques for analyzing the results of psychological experiments. Here we claim that complementing the analytical workflow of psychological experiments with Machine Learning-based analysis will both maximize accuracy and minimize replicability issues. As compared to statistical inference, ML analysis of experimental data is model agnostic and primarily focused on prediction rather than inference. We also highlight some potential pitfalls resulting from adoption of Machine Learning based experiment analysis. If not properly used it can lead to over-optimistic accuracy estimates similarly observed using statistical inference. Remedies to such pitfalls are also presented such and building model based on cross validation and the use of ensemble models. ML models are typically regarded as black boxes and we will discuss strategies aimed at rendering more transparent the predictions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.