A sex- and gender-based analysis of alcohol treatment intervention research involving youth: A methodological systematic review
Bibliographic record
Abstract
BACKGROUND: While there is widespread consensus that sex- and gender-related factors are important for how interventions are designed, implemented, and evaluated, it is not currently known how alcohol treatment research accounts for sex characteristics and/or gender identities and modalities. This methodological systematic review documents and assesses how sex characteristics, gender identities, and gender modalities are operationalized in alcohol treatment intervention research involving youth. METHODS AND FINDINGS: We searched MEDLINE, Embase, Cochrane Central Registry of Controlled Trials, PsycINFO, CINAHL, LGBT Life, Google Scholar, Web of Science, and grey literature from 2008 to 2023. We included articles that reported genders and/or sexes of participants 30 years of age and under and screened participants using AUDIT, AUDIT-C, or a structured interview using DSM-IV criteria. We limited the inclusion to studies that enrolled participants in alcohol treatment interventions and used a quantitative study design. We provide a narrative overview of the findings. Of 8,019 studies screened for inclusion, 86 articles were included in the review. None of the studies defined, measured, and reported both sex and gender variables accurately. Only 2 studies reported including trans participants. Most of the studies used gender or sex measures as a covariate to control for the effects of sex or gender on the intervention but did not discuss the rationale for or implications of this procedure. CONCLUSIONS: Our findings identify that the majority of alcohol treatment intervention research with youth conflate sex and gender factors, including terminologically, conceptually, and methodologically. Based on these findings, we recommend future research in this area define and account for a spectrum of gender modalities, identities, and/or sex characteristics throughout the research life cycle, including during study design, data collection, data analysis, and reporting. It is also imperative that sex and gender variables are used expansively to ensure that intersex and trans youth are meaningfully integrated. TRIAL REGISTRATION: Registration: PROSPERO, registration number: CRD42019119408.
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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 | 0.109 | 0.255 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.038 | 0.030 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".