Page 25 - JCBP-3-2
P. 25
Journal of Clinical and
Basic Psychosomatics Alcohol use disorder relapse: Tools and factors
information technology, digitization, big data, and References
artificial intelligence. Through these diverse channels, we 1. Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol
aim to investigate the current situation of relapse among use disorders. Lancet. 2019;394(10200):781-792.
AUD patients and identify key factors that contribute to
relapse, ultimately providing insights into the pathological doi: 10.1016/S0140-6736(19)31775-1
mechanisms of AUD. In addition, we will mobilize and 2. Peacock A, Leung J, Larney S, et al. Global statistics on
integrate resources from various sectors to develop new alcohol, tobacco and illicit drug use: 2017 status report.
drugs, instruments, and nursing therapies, and create Addiction. 2018;113:1905-1926.
personalized treatment plans to help AUD patients fully quit doi: 10.1111/add.14234
drinking. Finally, it is necessary for families and society to
collaborate in creating a safe and supportive environment 3. Experts Group of the National Key R & D Program.
for AUD patients, providing necessary supervision and “Research on the Promotion and Application of Key Diagnosis
and Treatment Technologies for Alcohol and Morphine
emotional support, and improving their compliance with Dependence”. Chinese Diagnosis and Treatment Guidelines
alcohol cessation. This collaboration would help reduce for Chronic Alcohol-Related Brain Damage. Neurology
relapse rates, improve patients’ quality of life, and alleviate Branch of Chinese Medical Association; 2024. p. 1-17.
the pressure on both families and society.
4. Tucker JA, Chandler SD, Witkiewitz K. Epidemiology of
Acknowledgments recovery from alcohol use disorder. Alcohol Res. 2020;40(3):2.
Our team is deeply grateful to three institutions: Huzhou doi: 10.35946/arcr.v40.3.02.
University, Huzhou Third Municipal Hospital, and Sir 5. Chou SP, Lee HK, Cho MJ, Park JI, Dawson DA, Grant BF.
Run Run Shaw Hospital, Zhejiang University School of Alcohol use disorders, nicotine dependence, and
Medicine, as well as the individuals within these institutions co-occurring mood and anxiety disorders in the United
who have assisted us. States and South Korea-A Cross-national comparison.
Alcohol Clin Exp Res. 2012;36:654-662.
Funding doi: 10.1111/j.1530-0277.2011.01639.x
None. 6. Forouzanfar MH, Alexander L, Anderson HR, et al. Global,
regional, and national comparative risk assessment of
Conflict of interest 79 behavioural, environmental and occupational, and
Shen Xinhua is an Editorial Board Member of this metabolic risks or clusters of risks in 188 countries, 1990-
journal but was not involved in any way in the editorial 2013: A systematic analysis for the Global Burden of Disease
or peer-review process for this paper, either directly or Study 2013. Lancet. 2015;386:2287-2323.
indirectly. Separately, the other authors declare that they doi: 10.1016/S0140-6736(15)00128-2
have no known competing financial interests or personal 7. Zhou XH, Liu XJ, Hao W. Research progress on influencing
relationships that could have influenced the work reported factors related to relapse of alcohol dependence. Chin J Drug
in this paper. Abuse Prev Treat. 2015;21(5):307-310.
Author contributions 8. Shield K, Manthey J, Rylett M, et al. National, regional, and
global burdens of disease from 2000 to 2016 attributable to
Conceptualization: Hongqiang Lu alcohol use: A comparative risk assessment study. Lancet
Writing–original draft: Hongqiang Lu Public Health. 2020;5:e51-e61.
Writing–review & editing: Xinhua Shen, Beibei Hu, Liping doi: 10.1016/S2468-2667(19)30231-2
Zhou
9. Tang YL, Xiang XJ, Wang XY, Cubells JF, Babord TF, Hao W.
Ethics approval and consent to participate Alcohol and alcohol-related harm in China: Policy changes
needed. Bull World Health Organ. 2013;91(4):270-276.
Not applicable.
doi: 10.2471/BLT.12.107318
Consent for publication 10. Huang YQ, Wang Y, Wang H, et al. Prevalence of mental
Not applicable. disorders in China: A cross-sectional epidemiological study.
Lancet Psychiatry. 2019;6:211-224.
Availability of data doi: 10.1016/S2215-0366(18)30511-X
All data presented in this review are available within the 11. Heinz A, Deserno L, Zimmermann US, Smolka MN, Beck A,
manuscript. Schlagenhauf F. Targeted intervention: Computational
Volume 3 Issue 2 (2025) 19 doi: 10.36922/jcbp.6559

