ArticleFrontiers in psychiatry2019
Introducing Machine Learning to Detect Personality Faking-Good in a Male Sample: A New Model Based on Minnesota Multiphasic Personality Inventory-2 Restructured Form Scales and Reaction Times.
Article in Frontiers in psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 41 citations in OpenAlex.
- Article
- Human-like problem-solving abilities in large language models using ChatGPT.Frontiers in artificial intelligence · 2023Article
- Reconstructing individual responses to direct questions: a new method for reconstructing malingered responses.Frontiers in psychology · 2023Article
- Article
- Article
- Automatic Decision-Making Style Recognition Method Using Kinect Technology.Frontiers in psychology · 2022Article
- Detecting faking-good response style in personality questionnaires with four choice alternatives.Psychological research · 2021Article
- Detecting suicidal risk using MMPI-2 based on machine learning algorithm.Scientific reports · 2021Article
- Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning Methods.Neuropsychiatric disease and treatment · 2021Article
- Translational Application of a Neuro-Scientific Multi-Modal Approach Into Forensic Psychiatric Evaluation: Why and How?Frontiers in psychiatry · 2021Article
- Facial Emotion Recognition Predicts Alexithymia Using Machine Learning.Computational intelligence and neuroscience · 2021Article
- Article
- Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models.Journal of clinical medicine · 2020Article
- How to Improve Compliance with Protective Health Measures during the COVID-19 Outbreak: Testing a Moderated Mediation Model and Machine Learning Algorithms.International journal of environmental research and public health · 2020Article
- Interrogative suggestibility in the elderly.PloS one · 2020Article
- MMPI-2-RF Profiles in Child Custody Litigants.Frontiers in psychiatry · 2019Article
- Machine Learning in Psychometrics and Psychological Research.Frontiers in psychology · 2019Article
- Observational
- Machine Learning Increases Diagnosticity in Psychometric Evaluation of Alexithymia in Fibromyalgia.Frontiers in medicine · 2019Article
- The Detection of Malingered Amnesia: An Approach Involving Multiple Strategies in a Mock Crime.Frontiers in psychiatry · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
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.