ArticleJournal of attention disorders2023
Screening for Adulthood ADHD and Comorbidities in a Tertiary Mental Health Center Using EarlyDetect: A Machine Learning-Based Pilot Study.
Article in Journal of attention disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- An in-depth exploration of machine learning methods for mental health state detection: a systematic review and analysis.Frontiers in digital health · 2025Pooled it
- Accurate and efficient data-driven psychiatric assessment using machine learning.BMC medical informatics and decision making · 2026Article
- Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review.Journal of medical Internet research · 2025Article
- The Inaccuracy of the Mood Disorder Questionnaire for Bipolar Disorder in a Community Sample: From the "DYMERS" Construct Toward a New Instrument for Detecting Vulnerable Conditions.Journal of clinical medicine · 2025Article
- Urgency to treat and early optimized treatment in major depressive disorder: consequences of delayed treatment, barriers to implementation, and practical strategies for clinicians.CNS spectrums · 2025Review
- Interpretable machine learning approaches for children's ADHD detection using clinical assessment data: an online web application deployment.BMC psychiatry · 2025Article
- Machine learning on a smartphone-based CPT for ADHD prediction.Frontiers in psychiatry · 2025Article
- Ethical trade-offs in AI for mental health.Frontiers in psychiatry · 2024Article
- Identifying neurodevelopmental disabilities from nationalised preschool health check.The Australian and New Zealand journal of psychiatry · 2023Article
- Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms.Translational psychiatry · 2023Review
- Screening for Adulthood ADHD and Comorbidities in a Tertiary Mental Health Center Using EarlyDetect: A Machine Learning-Based Pilot Study.Journal of attention disorders · 2023Article
- Practical pathway for the management of depression in the workplace: a Canadian perspective.Frontiers in psychiatry · 2023Review
- Resting-state functional connectivity does not predict individual differences in the effects of emotion on memory.Scientific reports · 2022Article
- Individualized identification of sexual dysfunction of psychiatric patients with machine-learning.Scientific reports · 2022Article
- Prediction of Probable Major Depressive Disorder in the Taiwan Biobank: An Integrated Machine Learning and Genome-Wide Analysis Approach.Journal of personalized medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Screening for adult Attention-Deficit/Hyperactivity Disorder (ADHD) and differentiating ADHD from comorbid mental health disorders remains to be clinically challenging. A screening tool for ADHD and comorbid mental health disorders is essential, as most adult ADHD is comorbid with several mental health disorders. The current pilot study enrolled 955 consecutive patients attending a tertiary mental health center in Canada and who completed EarlyDetect assessment, with 45.2% of patients diagnosed with ADHD. The best ADHD classification model using composite scoring achieved a balanced accuracy of 0.788, showing a 2.1% increase compared to standalone ADHD screening, detecting four more patients with ADHD per 100 patients. The classification model including ADHD with comorbidity was also successful (balanced accuracy = 0.712). The results suggest the novel screening method can improve ADHD detection accuracy and inform the risk of ADHD with comorbidity, and may further inform specific comorbidity including MDD and BD.
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.