ArticleComprehensive psychiatry2017
Mental disorder comorbidity and treatment utilization.
Article in Comprehensive psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Association between comorbid anxiety and depression symptomatology, quality of life, social support and use of mental health services in youth from Bogota, Buenos Aires, and Lima.Journal of affective disorders · 2026Article
- Mental health care utilization among middle-aged and older U.S. adults: Findings from the National Health Interview Survey.PLOS mental health · 2026Article
- Is there evidence that emotional reasoning processing underlies emotional disorders in adults? A systematic review.Current psychology (New Brunswick, N.J.) · 2022Article
- Integrating the Hierarchical Taxonomy of Psychopathology (HiTOP) into clinical practice.Journal of consulting and clinical psychology · 2019Article
- A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research.Perspectives on psychological science : a journal of the Association for Psychological Science · 2019Review
- Prevalence and predictors of no lifetime utilization of mental health treatment among people with mental disorders in France: findings from the 'Mental Health in General Population' (MHGP) survey.Social psychiatry and psychiatric epidemiology · 2018Article
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
Abstract
objectiveEffective interventions have been developed for myriad common psychological and substance use disorders, though they remain highly underutilized. Previous research has shown that the likelihood of treatment utilization varies across disorder diagnosis. However, studies that focus on individual disorders have resulted in a large, piecemeal literature that neglects the high rates of multivariate comorbidity. The current study investigated the association between treatment utilization and transdiagnostic comorbidity factors.
methodsIn a nationally representative sample of the United States adult population (N=34,653), we applied the internalizing-externalizing latent comorbidity model to examine its association with lifetime utilization of various treatments for mood, anxiety, and substance use disorders.
resultsBoth internalizing and externalizing transdiagnostic factors were positively associated with all forms of treatment utilization. Stronger within-domain domain (e.g., internalizing's association with mood or anxiety treatment) than between-domain (e.g., internalizing's association with substance use disorder treatment) associations were found. Significant antagonistic internalizing-by-externalizing interactions were also observed.
conclusionsThese results underscore the importance of applying a nuanced approach to modeling comorbidity when predicting treatment utilization. Clinical implications are discussed.
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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.