Evidence map›Paper›PMID 34450471›Full record

ArticleDrug and alcohol dependence2021

Agreement between DSM-5 and DSM-IV measures of substance use disorders in a sample of adult substance users.

Ofir Livne, Dvora Shmulewitz, Malka Stohl, Zachary Mannes, Efrat Aharonovich, Deborah Hasin

Open access · greenAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Ofir LivneDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Dvora ShmulewitzNew York State Psychiatric Institute, New York, NY, United States; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States.
Malka StohlNew York State Psychiatric Institute, New York, NY, United States.
Zachary MannesDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States.
Efrat AharonovichNew York State Psychiatric Institute, New York, NY, United States; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States.
Deborah HasinDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, United States; New York State Psychiatric Institute, New York, NY, United States; Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States. Electronic address: deborah.hasin@gmail.com.
Columbia University Irving Medical Center · USColumbia University · USNew York Psychoanalytic Society and Institute · US

Funding

Substance Abuse Epidemiology Training Program (SAETP) at Columbia UniversityT32DA031099 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEBORAH S HASIN, Silvia Saboia Martins · 2012 to 2026
$6.1M
Phenotypes for Drug Abuse:Epidemiologic-Genetic ApproachR01DA018652 · NIDA · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI HASIN, DEBORAH S · 2004 to 2018
$5.3M
NIDA NIH HHS R01 DA018652NIDA NIH HHS T32 DA031099
6 · The paper itself

Abstract

backgroundIn DSM-5, definitions of substance use disorders (SUD) were changed considerably from DSM-IV, yet little is known about how well DSM-IV and DSM-5 SUD diagnoses agree among substance users. Because data from many studies are based on DSM-IV diagnostic criteria, understanding the agreement between DSM-5 and DSM-IV SUD diagnoses and reasons for discordance between these diagnoses is crucial for comparing results across studies. MEASUREMENTS: Prevalences and chance-corrected agreement of DSM-5 SUD and DSM-IV substance dependence were evaluated in 588 substance users in a suburban inpatient addiction program and an urban medical center, using a semi-structured interview (PRISM-5). Alcohol, tobacco, cannabis, cocaine, heroin, opioid, sedative, and stimulant use disorders were examined. Cohen's kappa was used to assess agreement between DSM-5 and DSM-IV SUD (abuse or dependence), DSM-5 SUD and DSM-IV dependence, and DSM-5 moderate/severe SUD and DSM-IV dependence.

resultsAgreement between DSM-5 and DSM-IV SUD was excellent for all substances (κ = 0.84-0.99), except for cannabis and tobacco (κ = 0.75; 0.80, respectively). The most common reason for diagnostic discrepancies was a positive DSM-5 SUD diagnosis but no DSM-IV diagnosis, due to the lowered DSM-5 SUD threshold. Agreement between DSM-5 SUD and DSM-IV dependence was excellent for all substances (κ = 0.88-0.94), except for alcohol, tobacco, and cannabis (κ = 0.63-0.75). Agreement between moderate/severe DSM-5 SUD and DSM-IV dependence was excellent across all substances.

conclusionWhile care should be used in interpreting results of studies using different methods, studies relying on DSM-IV or DSM-5 SUD diagnostic criteria offer similar information and thus can be compared when accumulating a body of evidence.

Indexed as

CannabisCocaineDrug UsersSubstance-Related DisordersAdultDiagnostic and Statistical Manual of Mental DisordersHumansCocaineAddictionDSM-5 and DSM-IV agreementPRISM-5Substance use disorder

Identifiers

PMID34450471
PMCPMC8977110
OpenAlexW3194324131

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.