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Introduction: New psychoactive substances (NPS) pose a public health threat. Many studies have tried to identify the reasons of NPS use; however, none of them have so far used any standardised measures. The aim of this study was (i) to develop and cross-culturally validate the New Psychoactive Substance Use Motives Measure (NPSMM) and (ii) to compare motives of NPS use across countries and user types.Methods: Three subgroups (socially marginalised users, nightlife attendees and members of online communities) of NPS users (N = 3023) were recruited from six EU member countries. Demographics, motives and types of NPS used were assessed. NPS use motives were measured by adapting the extended six-factor version of the Marijuana Motives Measure.Results: Exploratory and confirmatory factor analysis resulted in a similar five-factor solution across most of the countries: coping, enhancement, social, conformity and expansion motives. Marginalised users scored higher on coping and conformity motives, nightlife groups showed higher endorsement of social motive, whereas online community users showed higher scores on expansion motives. Various types of NPS were also associated with different motives.Conclusion: NPS use motives might be associated with both the groups of users and the specific types of NPS being consumed. Expansion (psychedelics) and enhancement (stimulants) motives seemed to be linked to the chosen NPS product type, while coping, social and conformity motives were rather associated with user groups. NPSMM was found to be a valid instrument to measure NPS motives. [ABSTRACT FROM AUTHOR]

Aim: To compare characteristics of recreational vs. medical growers in a sample of small-scale cannabis cultivators from 12 countries. Methods: Six thousand eight hundred ninety six respondents who took part in an online survey were divided into three groups as: those who reported growing for recreational use, those cultivating for medical purposes who also reported use of other illegal drugs, and those who reported cultivation for medical use and didn't use other illegal substances. The groups were compared using multinomial logistic regression. Findings: In comparison to recreational growers, the two groups of medical growers included more females, consumed cannabis more frequently, and were more likely to cite health-related motivations for growing. The medical growers without other illicit drug use shared some of the same features with the medical growers with illicit drug use, but in comparison to both other groups, they were older, used less alcohol and tobacco, and were less likely to be involved in illicit activities other than drug crimes. Conclusions: Findings suggest that claims of medical use are not simply an attempt to justify personal cannabis consumption, but do at least partly reflect a genuine belief in medical benefit. However, those growing cannabis for medical reasons form a heterogeneous group of people. [ABSTRACT FROM AUTHOR]

It is common practice in survey questionnaires to include a general open and non-directive feedback question at the end, but the analysis of this type of data is rarely discussed in the methodological literature. While these open-ended comments can be useful, most researchers fail to report on this issue. The aim of this article is to illustrate and reflect upon the benefits and challenges of analyzing responses to open-ended feedback questions. The article describes the experiences of coding and analyzing data generated through a feedback question at the end of an international online survey with small-scale cannabis cultivators carried out by the Global Cannabis Cultivation Research Consortium. After describing the design and dataset of the web survey, the analytical approach and coding frame are presented. The analytical strategies chosen in this study illustrate the diversity and complexity of feedback comments which pose methodological challenges to researchers wishing to use them for data analyses. In this article, three types of feedback comments (political/policy comments, general comments of positive and negative appreciation, and methodological comments) are used to illustrate the difficulties and advantages of analyzing this type of data. The advantages of analyzing feedback comments are well known, but they seem to be rarely exploited. General feedback questions at the end of surveys are typically non-directive. If researchers want to use these data for research and analyses, they need a clear strategy. They ought to give enough thought to why they are including this type of question, and develop an analytical strategy at the design stage of the study. [ABSTRACT FROM AUTHOR]