ArticleBMC psychiatry2017
Machine learning methods to predict child posttraumatic stress: a proof of concept study.
Article in BMC psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic literature review of AI-based digital decision support systems for post-traumatic stress disorder.Frontiers in psychiatry · 2022Pooled it
- Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors.Npj mental health research · 2026Article
- Posttraumatic stress in young children at risk for maltreatment: a causal data science analysis.Frontiers in health services · 2026Article
- Predicting Firearm Suicide among US Army Veterans Transitioning from Active Service.Nature. Mental health · 2026Article
- Predicting Maltreatment in Adolescents with Mentally Ill Parents: A Random Forest Tree Analysis.Child psychiatry and human development · 2025Article
- Behavioral outcome prediction among children using machine learning.Bioinformation · 2025Article
- Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.Journal of anxiety disorders · 2024Article
- Automatic screening for posttraumatic stress disorder in early adolescents following the Ya'an earthquake using text mining techniques.Frontiers in psychiatry · 2024Article
- Multi-omics approaches in psychoneuroimmunology and health research: Conceptual considerations and methodological recommendations.Brain, behavior, and immunity · 2023Article
- Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.Translational psychiatry · 2023Article
- A computational model for learning from repeated traumatic experiences under uncertainty.Cognitive, affective & behavioral neuroscience · 2023Article
- Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision.Annals of emergency medicine · 2023Article
- Superstorm Sandy exposureFrontiers in neuroscience · 2023Article
- Mental health progress requires causal diagnostic nosology and scalable causal discovery.Frontiers in psychiatry · 2022Review
- Can the adverse childhood experiences (ACEs) checklist be utilized to predict emergency department visits among children and adolescents?BMC medical research methodology · 2021Article
- Deep learning model of fMRI connectivity predicts PTSD symptom trajectories in recent trauma survivors.NeuroImage · 2021Article
- An Explainable Intelligence Driven Query Prioritization Using Balanced Decision Tree Approach for Multi-Level Psychological Disorders Assessment.Frontiers in public health · 2021Article
- Prospective prediction of PTSD diagnosis in a nationally representative sample using machine learning.BMC psychiatry · 2020Article
- Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health.Administration and policy in mental health · 2020Article
- Computational causal discovery for post-traumatic stress in police officers.Translational psychiatry · 2020Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe care of traumatized children would benefit significantly from accurate predictive models for Posttraumatic Stress Disorder (PTSD), using information available around the time of trauma. Machine Learning (ML) computational methods have yielded strong results in recent applications across many diseases and data types, yet they have not been previously applied to childhood PTSD. Since these methods have not been applied to this complex and debilitating disorder, there is a great deal that remains to be learned about their application. The first step is to prove the concept: Can ML methods - as applied in other fields - produce predictive classification models for childhood PTSD? Additionally, we seek to determine if specific variables can be identified - from the aforementioned predictive classification models - with putative causal relations to PTSD.
methodsML predictive classification methods - with causal discovery feature selection - were applied to a data set of 163 children hospitalized with an injury and PTSD was determined three months after hospital discharge. At the time of hospitalization, 105 risk factor variables were collected spanning a range of biopsychosocial domains.
resultsSeven percent of subjects had a high level of PTSD symptoms. A predictive classification model was discovered with significant predictive accuracy. A predictive model constructed based on subsets of potentially causally relevant features achieves similar predictivity compared to the best predictive model constructed with all variables. Causal Discovery feature selection methods identified 58 variables of which 10 were identified as most stable.
conclusionsIn this first proof-of-concept application of ML methods to predict childhood Posttraumatic Stress we were able to determine both predictive classification models for childhood PTSD and identify several causal variables. This set of techniques has great potential for enhancing the methodological toolkit in the field and future studies should seek to replicate, refine, and extend the results produced in this study.
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.