Article in The American journal on addictions, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
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.
Yan WangDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Katelyn F RommTSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.ORCID 0000-0002-9552-0732
Mark C EdbergDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Jeffrey B BingenheimerDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Cassidy R LoParcoDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Yuxian CuiDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Carla J BergDepartment of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.ORCID 0000-0001-8931-1961
Funding
Tissue Pathology Shared ResourceP30CA225520 · NCI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI ROBERT S. MANNEL · 2018 to 2026
$27.1M
Recreational Marijuana Marketing and Young Adult Consumer Behavior - Administrative SupplementR01DA054751 · NIDA · GEORGE WASHINGTON UNIVERSITY · PI Carla J Berg, Patricia A Cavazos-Rehg · 2022 to 2026
$4.3M
Regulatory Impact on Vape Shops and Young Adults' Use of ENDS - Diversity SupplementR01CA215155 · NCI · GEORGE WASHINGTON UNIVERSITY · PI BERG, CARLA J · 2018 to 2022
$3.4M
Implementing a Scalable Smoke-free Home Intervention in Armenia and GeorgiaR01CA278229 · NCI · GEORGE WASHINGTON UNIVERSITY · PI Carla J Berg, MICHELLE C KEGLER · 2023 to 2026
$2.3M
Effects of State Preemption of Local Tobacco Control Legislation on Disparities in Tobacco Use, Exposure and RetailR01CA275066 · NCI · GEORGE WASHINGTON UNIVERSITY · PI Carla J Berg, Y. Tony Yang · 2023 to 2026
$2.0M
Smoke-free Air Coalitions in Georgia and Armenia: A Community Randomized TrialR01TW010664 · FIC · EMORY UNIVERSITY · PI BERG, CARLA J, KEGLER, MICHELLE C · 2017 to 2021
$1.5M
Emory-Georgia Clean Air Research & Education (CARE) ProgramD43ES030927 · NIEHS · EMORY UNIVERSITY · PI BERG, CARLA J, CAUDLE, WILLIAM MICHAEL · 2019 to 2025
$1.2M
Assessing IQOS Marketing Influences and Consumer Behavior in Israel: Implications for the USR01CA239178 · NCI · GEORGE WASHINGTON UNIVERSITY · PI BERG, CARLA J, LEVINE, HAGAI · 2019 to 2021
$1.2M
Helping Everyone Achieve a LifeTime of Health - Future Addiction Scientist TrainingR25DA054015 · NIDA · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI OBASI, EZEMENARI M., REITZEL, LORRAINE R · 2021 to 2025
$1.0M
Armenia-US Collaboration to Address Chronic Disease via Education in Social Determinants Science (ACCESS)D43TW012456 · FIC · GEORGE WASHINGTON UNIVERSITY · PI Carla J Berg, Nino Paichadze · 2023 to 2026
$974k
An mHealth Positive Psychology Intervention to Reduce Cancer Burden in Young Adult Cancer SurvivorsR21CA261884 · NCI · GEORGE WASHINGTON UNIVERSITY · PI AREM, HANNAH, BERG, CARLA J · 2022 to 2023
objectivesLimited longitudinal research has examined differential interpersonal and intrapersonal correlates of young adult use and use frequency of cigarettes, e-cigarettes, and cannabis. This study aimed to address these limitations.
methodsWe analyzed five waves of longitudinal data (2018-2020) among 3006 US young adults (M
resultsRegarding baseline past-month use (27% cigarettes, 38% e-cigarettes, 39% cannabis), depressive symptoms, ACEs, and parental substance use predicted use outcomes (i.e., likelihood, frequency) for each product; extraversion predicted cigarette and e-cigarette use outcomes; openness predicted e-cigarette and cannabis use outcomes; conscientiousness negatively predicted cigarette and cannabis use outcomes; and agreeableness negatively predicted cannabis use frequency. Regarding longitudinal changes, conscientiousness predicted accelerated increase of cigarette use frequency at later timepoints; depressive symptoms predicted increases in likelihood of e-cigarette use but the association weakened over time; and parental cannabis use predicted decreased cannabis use frequency but the association weakened over time. DISCUSSION AND
conclusionsYoung adult substance use interventions should target high-risk subgroups and focus on distinct factors impacting use, including chronic, escalating, and decreasing use. SCIENTIFIC SIGNIFICANCE: This study advances the literature regarding distinct predictors of different substance use outcomes and provides unique data to inform interventions targeting young adult cigarette, e-cigarette, and cannabis use.
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.
Two-part models identifying predictors of cigarette, e-cigarette, and cannabis use and change in use over time among young adults in the US. · full record | OpenQuestion