I am what I am: A meta-analysis of the association between substance user identities and substance use-related outcomes.
Bibliographic record
Abstract
OBJECTIVE: Research indicates that a substance user identity (i.e., drinking, smoking, and marijuana identity) is positively correlated with substance use-related outcomes (e.g., frequency, quantity, consequences, and disorder symptoms). The current study aimed to meta-analytically derive single, weighted effect size estimates of the identity-outcome association as well as to examine moderators (e.g., substance use type, explicit/implicit assessment, demographic characteristics, and research design) of this association. METHOD: Random effects meta-analysis was conducted on 70 unique samples that assessed substance user identity and at least one substance use-related outcome (frequency, quantity, consequences, and/or disorder symptoms), and provided the necessary information for effect size calculations. RESULTS: (tobacco or marijuana). In terms of moderators of the identity-outcome association, the link between explicit drinking identity and alcohol use-related outcomes appeared to be stronger in magnitude than the relationship between implicit drinking identity and alcohol use-related outcomes; however, this difference appears to be largely due to the finding that implicit measures have lower reliability. The strongest identity-outcome association was observed among younger individuals. CONCLUSIONS: Substance user identity is clearly an important correlate of substance use-related outcomes and this association is stronger among younger individuals. Additional theoretical, empirical, and intervention research is needed to utilize knowledge gleaned from the current study on the identity-outcome association. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".