Evidence map›Paper›PMID 40988992›Full record

ArticleComplex psychiatry

Development of the Comprehensive Addiction Risk Evaluation System: Initial Participant Response to an Online Personalized Feedback Program Integrating Genomic, Behavioral, and Environmental Risk Information.

Danielle M Dick, Maia Choi, Emily Balcke, Fazil Aliev, Diya Patel, Kennedy Borle, Jehannine Austin

Abstract read
In one paragraph

Article in Complex psychiatry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

7 authors.

Danielle M DickDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
Maia ChoiDepartment of Psychology, School of Arts and Sciences, Rutgers University, Piscataway, NJ, USA.
Emily BalckeDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
Fazil AlievDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
Diya PatelDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
Kennedy BorleDepartment of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
Jehannine AustinDepartment of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.

Funding

Rutgers Training in Addiction Research ProgramT32DA055569 · NIDA · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI Robert Christopher Pierce · 2023 to 2026
$1.6M
NIDA NIH HHS T32 DA055569
6 · The paper itself

Abstract

Introduction: We have made tremendous advances in understanding the etiology of substance use disorders (SUDs). Despite these advances, screening for SUDs has remained largely unchanged. In this paper, we describe an effort to build a program that integrates advances across genomics, developmental psychology, and epidemiology to provide individuals with personalized information about their addiction risk profile. Methods: The program was developed based on foundational work from a NIDA-funded project that conducted multivariate analyses of externalizing phenotypes to advance gene identification for SUDs and then characterized how polygenic scores (PGS) and early life behavioral and environmental factors predicted SUDs in diverse longitudinal samples. Based on this work, we created PGS and a behavioral and environmental risk index to generate personalized risk profiles. We carefully considered ethical concerns when developing the program. Results: We created a user-friendly, self-directed online platform that provides personalized risk information, including overall risk for developing an SUD based on an individual's combination of genetic, behavioral, and environmental risk, and specific information about genetic risk, based on PGS, and behavioral/environmental risk. Data from the first 188 participants enrolled in an ongoing study to evaluate the platform indicate high satisfaction and low distress at receiving genetic information. Conclusion: Provision of personalized feedback about addiction risk factors, including genetic information along with behavioral and environmental feedback, may be a viable way to promote earlier screening and intervention with the goal of preventing substance use problems before they start.

Indexed as

Addiction riskDistressGenetic feedbackPersonalized feedbackPrecision medicinePrecision psychiatrySatisfactionUnderstanding

Identifiers

PMID40988992
PMCPMC12453580

What Socratic holds

Textmetadata
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 Socratic graph.