Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach-Reference-Cited by-同舟云学术

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Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach

Published:2024-06-19 Issue:11 Volume:59 Page:1620-1628
ISSN:1082-6084
Container-title:Substance Use & Misuse
language:en
Short-container-title:Substance Use & Misuse

Author:

Huang Siyuan¹²^ORCID,Wahlquist Amy³,Dahne Jennifer¹²^ORCID

Affiliation:

1. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina (MUSC), Charleston, South Carolina, USA

2. Hollings Cancer Center, MUSC, Charleston, South Carolina, USA

3. Center for Rural Health Research, East Tennessee State University, Johnson City, Tennessee, USA

Funder

National Institute on Drug Abuse

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10826084.2024.2369155

Reference69 articles.

1. Disparity in Depression Treatment Among Racial and Ethnic Minority Populations in the United States

2. A Randomized Trial Evaluating Whether Topiramate Aids Smoking Cessation and Prevents Alcohol Relapse in Recovering Alcohol-Dependent Men

3. Quitting Smoking Among Adults — United States, 2000–2015

4. Patterns of Use of an Automated Interactive Personalized Coaching Program for Smoking Cessation

5. Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory-II (BDI-II). Psychological Corporation.

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