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Developing an Algorithm for Temporary Bans on New Psychoactive Substances: A Delphi Consensus Study

delete2025-11-01
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PRE
AI
M
Min Hwang
J
J. Park
J
Jung, Hyun Sil
J
Jeong Min Go
J
Jae Hoon Cheong
H
Ha‐Lim Jeon *
DOI:10.1177/29767342251380375delete
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摘要

摘要

En 中文
Background: To develop a valid algorithm for temporary bans on new psychoactive substances (NPSs) to minimize the intervention of the subjective opinions of experts in the temporary scheduling process.Methods: This study consisted of a preliminary survey, a 2-phase Delphi survey, and a final consensus survey. In Phase 1 of the Delphi survey, the importance of 7 criteria for designating subjects of temporary bans, as confirmed through a preliminary survey, was evaluated. Phase 2 survey was conducted to investigate the suitability of detailed questions representing the key criteria to be included in the algorithm. In the final phase, the final algorithm was selected, and several questions regarding the expert evaluation of the algorithm were asked. The mean scores of importance and the content validity ratio were calculated for consistency.Results: Nineteen panelists participated in a Delphi survey. The experts agreed on 5 criteria and 22 detailed questions for designating subjects of temporary bans. The finally selected algorithm involves primary evaluation of 'Abuse potential and dependence', 'Social risks', and 'Regulatory cases in reference countries' and secondary considerations about 'Pharmacological effects on the central nervous system' and 'Toxicity and harmfulness'. For expert evaluation, the preferred number of participating experts was 7. Many participants (77.8%) responded that the average expert evaluation score for temporary bans was 2 or higher.Conclusions: We developed a valid algorithm for temporary bans on NPS that can effectively regulate NPS and prevent the spread of addictive substances.
Keyword:
new psychoactive substances
Delphi study
algorithm
temporary bans

期刊

S
SUBSTANCE USE & ADDICTION JOURNAL
IF:
0
论文数:
77
被引数:
0

机构

J
jeonbuk national university
学者数:
2.1K
论文数: 913
被引数: 0
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