Evidence map›Paper›PMID 27663984›Full record

ArticleSubstance abuse treatment, prevention, and policy2016

Comparison of illegal drug use pattern in Taiwan and Korea from 2006 to 2014.

Ling-Yi Feng, Wen-Jing Yu, Wei-Ting Chang, Eunyoung Han, Heesun Chung, Jih-Heng Li

Open access · goldAbstract read
In one paragraph

Article in Substance abuse treatment, prevention, and policy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 49 citations in OpenAlex.

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4 · The record

Corrections and comments

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

6 authors at 3 institutions in 2 countries.

Ling-Yi FengSchool of Pharmacy and Ph.D. Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung City, 80708, Taiwan.
Wen-Jing YuSchool of Pharmacy and Ph.D. Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung City, 80708, Taiwan.
Wei-Ting ChangSchool of Pharmacy and Ph.D. Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung City, 80708, Taiwan.
Eunyoung HanCollege of Pharmacy, Duksung Women's University, Seoul, Korea.
Heesun ChungGraduate School of Analytical Science and Technology(GRAST), Chungnam National University, 99- Daehak-ro, Yuseongk-gu, Daejeon, 305-764, Korea. hschung@cnu.ac.kr.
Jih-Heng LiSchool of Pharmacy and Ph.D. Program in Toxicology, College of Pharmacy, Kaohsiung Medical University, 100 Shih-Chuan 1st Road, Kaohsiung City, 80708, Taiwan. jhlitox@kmu.edu.tw.ORCID http://orcid.org/0000-0003-4712-9517
Kaohsiung Medical University · TWChungnam National University · KRDuksung Women's University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIllegal drug use has long been a global concern. Taiwan and Korea are geographically adjacent and both countries have experienced the illegal use problems of methamphetamine, a predominant prototype of New Psychoactive Substances (NPS). NPS, a term coined by the United Nations Office on Drugs and Crime (UNODC) in recent years, have not been scrutinized for their safety and may become a new threat to public health and security worldwide. To conduct evidence-based drug policy, it is imperative to estimate the trend and pattern of illegal drug use. Therefore, this study aims to analyze and compare the current status of drug-related seizures, arrests and illegal drug use, with a focus on methamphetamine and NPS, between Taiwan and Korea.

methodsData of illegal drug (including NPS)-related seizures and arrests were collected via anti-drug related agencies of both countries from 2006 through 2014.Since listing of NPS as controlled substances was a result of NPS abuse liability through official evaluation, the items of controlled NPS were used as an indicator of emerging use. These data obtained from Taiwan and Korea was then compared.

resultsThe results showed that while methamphetamine remained as a predominant drug in both Taiwan and Korea for decades, different illegal drug use patterns have been observed in these two countries. In Taiwan, the major illegal drugs were methamphetamine, heroin, and ketamine, whereas in Korea those were methamphetamine and cannabis. By comparison of per capita illicit drug seizures, the illegal drug use situation in Taiwan was at a higher stake than that in Korea. In terms of NPS use, ketamine has been a major drug in Taiwan, but it was seldom found in Korea. Besides ketamine, the major type of NPS was synthetic cathinones in Taiwan whereas it was synthetic cannabinoids and phenethylamines in Korea. The difference in the numbers of controlled NPS items between Taiwan (23) and Korea (93) may be due to the implementation of temporary control on NPS in Korea since 2011.

conclusionWhile the problem of methamphetamine still lingers, NPS have emerged as a new issue in both countries. However, the NPS pattern was different between Taiwan and Korea. Although the controlled NPS items in Taiwan were far less than those in Korea, the quantity of total NPS seizures, especially with ketamine, was much larger in Taiwan than in Korea. Different NPS pattern may also imply they were from different sources. Factors other than geographical proximity, such as drug policy and availability and accessibility to drugs, should be taken into account for the current status of illegal drug use in Korea and Taiwan.

Indexed as

Drug seizuresKetamineKoreaMethamphetamineNew Psychoactive Substances (NPS)Taiwan

Identifiers

PMID27663984
PMCPMC5034652
OpenAlexW2521937248

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.