Prescription psychostimulants as a harm reduction and treatment intervention for methamphetamine use disorder and the implications for nursing clinical practice: A scoping review of the literature
Bibliographic record
Abstract
The global rise in methamphetamine use and its negative effects warrants the need for research exploring harm reduction and treatment interventions for individuals with methamphetamine use disorder. Agonist medications have been utilized for years for the treatment of heroin and opioid addiction, but have yet to be incorporated into mainstream Canadian practice for methamphetamine dependence. This review aims to provide an overview of the current trends of prescription psychostimulant usage for individuals with methamphetamine use disorder from a Canadian perspective, identifies the barriers to accessing prescription psychostimulants for methamphetamine use disorder and highlights the nursing clinical practice implications in caring for individuals with the disorder. Discourse on the sustained abstinence and harm reduction debate is presented from the perspective of methamphetamine abuse is provided along with the neuropsychiatric complications of chronic methamphetamine use. The impacts of specific prescription psychostimulants on cognition are discussed as is the use of neuroimaging techniques to assess neuronal damage in methamphetamine users. Sign of toxicity, overdose and the contraindications for use of these prescription psychostimulants is also presented. The implications to nursing clinical practice in caring for this population is provided, touching on the clinical presentation of methamphetamine use, completing thorough assessment and screening and patient education. The findings of this review indicate the need for further research in this area exploring the benefits of prescription psychostimulants as a harm reduction and treatment intervention for the global problem of methamphetamine dependence.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".