Psychosocial and pharmacologic interventions for methamphetamine addiction: protocol for a scoping review of the literature
Bibliographic record
Abstract
BACKGROUND: Methamphetamine use and harms are rising rapidly. Management of patients with methamphetamine use disorder (MUD) and problematic methamphetamine use (PMU) is challenging, with no clearly established best approach; both psychosocial and pharmacologic interventions have been described. Furthermore, given the diversity of individuals that use methamphetamines, there is a need to assess evidence for treatments for subgroups including youths; gay, bisexual, and other men who have sex with men; individuals with mental health comorbidities; and individuals in correction services. Establishing awareness of the messages regarding treatment from recent clinical practice guidelines (CPG) in the field is also of value. The first study objective will be to establish a greater understanding of the methods, populations, and findings of controlled studies for psychosocial and pharmacologic treatments for MUD and PMU. Investigation of this information can help establish the potential for advanced syntheses of the evidence (such as network meta-analysis) to compare therapies for this condition and to identify gaps related to key populations where more primary research is needed. Summarizing the recommendations regarding treatment of MUD/PMU from recent CPGs and systematic reviews will be an important secondary objective. METHODS: A scoping review will be performed. Using the OVID platform, MEDLINE, Embase, PsycINFO, and relevant Cochrane databases from EBM Reviews will be searched (from databases' inception onwards). Eligibility criteria will include individuals described as having MUD or PMU, with designs of interest including randomized trials, non-randomized trials, and controlled cohort studies with three or more months of follow-up; systematic reviews and CPGs will also be sought. Two reviewers (with support from automation tools) will independently screen all citations, full-text articles, and chart data. Different approaches to handling and summarizing the data will be implemented for each type of study design. Tables and graphics will be used to map evidence sources and identify evidence gaps. DISCUSSION: This research will enhance awareness of evidence addressing the effects of psychosocial and pharmacologic interventions for MUD/PMU overall and in sub-populations, both in terms of recent CPGs/reviews and primary studies; inspection of the latter will also help establish the feasibility of future syntheses to compare treatments, such as network meta-analysis. SYSTEMATIC REVIEW PROTOCOL REGISTRATION: Open Science Framework ( https://osf.io/9wy8p ).
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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 | 0.063 | 0.057 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.018 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.099 | 0.014 |
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".