Background
There are few studies exploring the social context of controlled drug use amongst young people in Indonesia. This qualitative study examines the experience of young people in a slum area (lorong) in Makassar, eastern Indonesia, who use drugs but are not drug dependent and who employ various forms of self regulation to control their use.Methods
Semi-structured interviews were conducted with eight controlled drug users.Results
The study found that whilst controlled drug users lived in a drug risk environment, they were not deeply embedded in the street culture, risk-taking practises and drug scene within their locality. Their employment, albeit in the informal economy and in low-paid jobs, facilitated their perspective that the status of rewa (a local construct of masculinity) and gaul (being sociable and up-to-date) could and should be accomplished through conventional means such as jobs and halal (legitimate) income. Their employment generated both direct benefit (legitimate income) and indirect benefit, including meaningful activities, structured time, positive identity and wider social networks (bridging social capital). This enabled them to have a stake in mainstream society and provided an incentive to control drug use. All factors which are protective against escalation into problematic drug use.Conclusion
The study showed the importance of sociological concepts of direct and indirect benefits of employment and of social capital in understanding the social context of controlled drug use amongst young people in the lorong. Additionally, drug policy should be more cognizant of the social vulnerability in the lorong and of the need to increase access to employment amongst young people in order to potentially decrease the likelihood of problematic drug use. 相似文献Electroencephalography (EEG) is a diagnostic test that records and measures the electrical activity of the human brain. Research investigating human behaviors and conditions using EEG has increased from year to year. Therefore, an efficient approach is vital to process the EEG dataset to improve the output signal quality. The wavelet is one of the well-known approaches for processing the EEG signal in time–frequency domain analysis. The wavelet is better than the traditional Fourier Transform because it has good time–frequency localized properties and multi-resolution analysis where the transient information of an EEG signal can be extracted efficiently. Thus, this review article aims to comprehensively describe the application of the wavelet method in denoising the EEG signal based on recent research. This review begins with a brief overview of the basic theory and characteristics of EEG and the wavelet transform method. Then, several wavelet-based methods commonly applied in EEG dataset denoising are described and a considerable number of the latest published EEG research works with wavelet applications are reviewed. Besides, the challenges that exist in current EEG-based wavelet method research are discussed. Finally, alternative solutions to mitigate the issues are recommended.
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