Journal article
Late positive potential as a candidate biomarker of motivational relevance in substance use: Evidence from a meta-analysis*
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, v 141, 104835
Oct 2022
PMID: 36031010
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The objective of the current meta-analysis was to assess the effect size of the Late Positive Potential (LPP) to drug and emotional cues in substance users compared to controls. The secondary objective was to test for moderation by: age, gender, years of use, use status, and substance type. Search was performed in August 2021 using PubMed. Inclusion criteria were: substance use disorder/dependence or validated self-report, LPP means, healthy control comparison, non-acute drug study, data available, peer-reviewed journal, English, and human participants. Selection bias was tested through modified Egger's regression and exploratory 3-parameter selection model tests. Results (k = 11) indicated LPP to drug cues was larger in substance use compared to control group, with a large effect size (Hedges' g=1.66, 95%CI [0.64,2.67], p = 0.005). There were no overall differences for emotional cues. Though threats of selection bias were not severe, inclusion of more studies with larger sample sizes in future meta-analyses will allow more robust tests of publication bias and more accurate measures of effect size.
Metrics
Details
- Title
- Late positive potential as a candidate biomarker of motivational relevance in substance use: Evidence from a meta-analysis*
- Publication Details
- NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, v 141, 104835
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD; OXFORD
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Drexel University
- Web of Science ID
- WOS:000864084600002
- Scopus ID
- 2-s2.0-85136706415
- Other Identifier
- 991021861191604721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Behavioral Sciences
- Neurosciences