Evidence map›Paper›PMID 40129493›Full record

ArticleDrug and alcohol dependence reports2025

Protocol for a new family history of addiction density score to aid in the treatment of alcohol and substance use disorders.

Jessica L Bourdon, Jordan Wright, Sabrina Verdecanna, Mer W Francis, Vivia V McCutcheon

Abstract read
In one paragraph

Article in Drug and alcohol dependence reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jessica L BourdonDepartment of Psychology, University of Richmond, 114 UR Drive, Richmond, VA 23173, USA.
Jordan WrightCenter for Addiction Science, Wellbridge Addiction Treatment and Research, 525 Jan Way, Calverton, NY 11933, USA.
Sabrina VerdecannaCenter for Addiction Science, Wellbridge Addiction Treatment and Research, 525 Jan Way, Calverton, NY 11933, USA.
Mer W FrancisSchool of Social Work, Virginia Commonwealth University,1000 Floyd Avenue, Box 842027,Richmond,VA 23284,USA.
Vivia V McCutcheonDepartment of Psychiatry, Washington University School of Medicine,4560 Clayton Avenue,St. Louis,MO 63110,USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: While molecular and non-molecular genetic testing are the gold standard for assessing a person's familial liability for substance use disorders, such testing is often inaccessible. Family history information collected at intake is an alternative, but tools to effectively utilize this information are excessively complex. The aims of the study are threefold: 1) Describe a protocol for the collection of family history in a thorough and straightforward manner. 2) Provide an algorithm to convert family history information to numerical scores. 3) Present the aggregated results from the pilot testing of the protocol. Methods: All patients ( Results: The protocol asked patients four key questions about 1st and 2nd degree relatives while completing a family pedigree. Answers were transferred into an algorithm to output a score for each patient. This score took affectedness and relatedness of each family member into account. The average number of affected relatives was 5.24 (SD=3.17), and there were significant sex, race, and primary substance score differences. Conclusions: This study provides the addiction field with a novel, freely available, and easily implementable family history protocol that has several potential clinical applications. While more research is needed, pilot results provide a valuable research tool, insight into a typical family history for those at an inpatient addiction treatment center, and steps toward closing the research-to-practice gap in this field.

Indexed as

AddictionDensity scoreFamily historyGeneticsProtocol

Identifiers

PMID40129493
PMCPMC11930440

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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.