Determination of the Profile of New Psychoactive Substances Among Users from the Homeless Population: A Mixed-Methods Approach.
Bibliographic record
Abstract
The emergence of new psychoactive substances (NPS) among the homeless population has been highlighted as a growing concern in the recent years. NPS have plagued the homeless population in recent years creating a number of associated economic and social issues. The majority of previous research have focused on using either qualitative or quantitative techniques; however, few studies have used mixed-methods approach. Therefore, this thesis has complemented the gap in previous research by using a mixed method approach to determine the profile of NPS among the homeless population. \n \nTwo quantitative studies, including a systematic review and semi-structured questionnaire that enabled to understand the prevalence of NPS in the UK and worldwide, were conducted. Additionally, one qualitative study was performed and comprised Twitter analysis that confirmed NPS encountered among the homeless and their effects from the views of the public and service providers. The aforementioned three studies determined NPS used among the homeless population and flagged the impurities in them. NPS and impurities were further confirmed by chemical analysis conducted using Fourier transform infrared and Raman spectroscopy. \n \nSubstantial information obtained in this thesis, not reported in previous literature, demonstrated the potential for mixed-method approach in giving a greater insight into experience of NPS among the homeless. The systematic review highlighted the surge in synthetic cannabinoid receptor agonists (SCRAs) among the homeless in the UK, USA and Canada that occurred after 2016; whereas alcohol, cocaine and heroin had been more prevalent prior to 2016. Continued SCRAs use contributed to long-term adverse events especially anxiety, depression and psychosis. In this respect, the findings of the questionnaire confirmed the latter findings related to SCRAs use in the homeless population. Homeless in the UK reported short and long-term adverse events linked to SCRAs use that were readily accessible to them but not always as pure substances. Hence, they had access to SCRAs in different matrices including herbal, e-liquids and paper. The variable effects experienced upon SCRAs use further flagged their unknown purity. This was further explored in the Twitter study that reported variable effects experienced to drugs in different geographical area. Subsequently, the spectroscopic chapters identified the different concentrations of SCRAs impregnated into paper matrices. \n \nIn summary, the findings from this thesis contributed to the scientific literature by informing policy makers, law enforcement, medical practitioners and homeless service providers about the profile of NPS use among the homeless population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".