Prescription Psychostimulant Use Among Young Adults: A Narrative Review of Qualitative Studies
Bibliographic record
Abstract
BACKGROUND: Within the last decade, the nonmedical use of prescription drugs has raised concern, particularly among young adults. Psychostimulants, that is to say amphetamine and its derivatives, are pharmaceuticals, which contribute to what has come to be known in Canada and the United States as the "prescription drug crisis." Research in the fields of public health, addiction studies, and neuroethics has attempted to further understand this mounting issue; however, there is a paucity of data concerning the underlying social logics related to the use of these substances. OBJECTIVES: The objective of this article is to provide an overview of the current literature related to the social context of prescription psychostimulant use among young adults, and to discuss theoretical considerations as well as implications for future research. METHODS: A narrative review of the literature was performed. RESULTS: We found that research efforts have chiefly targeted college students, yet there is a lack of knowledge concerning other social groups likely to use these pharmaceuticals nonmedically, such as persons with high strain employment. Three main emerging patterns related to prescription psychostimulant use were identified: (1) control of external stressors, (2) strategic use toward the making of the self, and (3) increasing one's performance. CONCLUSIONS: Prescription psychostimulant use among young adults is anchored in contemporary normativity and cannot be separated from the developing performance ethic within North-American and other Western societies. We suggest that pharmaceuticalization and Actor-Network Theory are useful conceptual tools to frame future research efforts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".