ArticleAssessment2020
Using Complete Enumeration to Derive "One-Size-Fits-All" Versus "Subgroup-Specific" Diagnostic Rules for Substance Use Disorder.
Article in Assessment, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Redundancy in the DSM-5 substance use disorder criterion set: Evidence from a national U.S. survey.Psychological assessment · 2026Article
- Conceptualization of Alcohol Use Disorder (AUD): Can Theoretical or Data Driven Approaches Improve the Construct Validity of AUD?Research on child and adolescent psychopathology · 2022Article
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
The use of fixed diagnostic rules, whereby the same diagnostic algorithms are applied across all individuals regardless of personal attributes, has been the tradition in the
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.