Evidence map›Paper›PMID 42686305›Full record

ReviewChild and adolescent psychiatric clinics of North America2026

Digital Interventions to Facilitate Screening, Brief Interventions, and Referral to Treatment for Substance Use Among Adolescents.

Kammarauche Aneni, Elizabeth Ngarachu, Margaret R Kuklinski, Ross Shegog, Deepa Camenga

Abstract readReview
In one paragraph

Review in Child and adolescent psychiatric clinics of North America, 2026. 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
–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

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.

Kammarauche AneniChild Study Center, Yale School of Medicine, New Haven, CT, USA; Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA. Electronic address: uche.aneni@yale.edu.
Elizabeth NgarachuStudent, Division of Health and Behavioral Science, Seattle Pacific University, Seattle, WA, USA.
Margaret R KuklinskiSocial Development Research Group, School of Social Work, University of Washington, Seattle, WA, USA.
Ross ShegogDepartment of Health Promotion and Behavioral Sciences, UTHealth School of Public Health, Houston, TX, USA.
Deepa CamengaDepartment of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA; Department of Pediatrics, Yale School of Medicine, New Haven, CT, USA.

Funding

A Family-Based Digital Intervention to Address Early Substance Use Among Adolescents in Primary Care SettingsK23DA059638 · NIDA · YALE UNIVERSITY · PI Kammarauche Aneni · 2024 to 2026
$585k
NIDA NIH HHS K23 DA059638
6 · The paper itself

Abstract

Substance use in adolescence is linked to short-term and long-term morbidity and mortality, including risk of developing a substance use disorder, violence, poor academic and career achievement, impaired social functioning and relationships, homicides and suicides, and drug overdose deaths and poisonings. Screening, Brief Intervention, and Referral to Treatment (SBIRT) is a public health framework for addressing adolescent substance use, but challenges to implementation exist. Digital approaches can mitigate existing barriers to SBIRT. We provide an overview of the digital interventions used for SBIRT, discuss challenges with current digital approaches, and provide recommendations to enhance the digital SBIRT in routine practice.

Indexed as

Adolescent BehaviorMass ScreeningReferral and ConsultationSubstance-Related DisordersAdolescentDigital HealthDigital MediaHumansAdolescentBarriers to accessDigital interventionsSBIRTSubstance use

Identifiers

PMID42686305
PMCPMC13557742

What OpenQuestion 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 OpenQuestion graph.