Alcohol use among sexual minority women: Methods used and lessons learned in the 20-Year Chicago Health and Life Experiences of Women Study
Bibliographic record
Abstract
Background: Two decades ago, there was almost no research on alcohol use among sexual minority women (SMW, e.g., lesbian, bisexual). Since then, a growing body of scientific literature documents substantial sexual orientation-related disparities in alcohol use and alcohol-related problems. Research has identified multiple risk factors associated with high-risk/hazardous drinking among SMW. However, this research has almost exclusively used cross-sectional designs, limiting the ability to draw conclusions about processes through which sexual minority status affects alcohol use. Longitudinal designs, although very rare in research on alcohol use among SMW, are important for testing mediational mechanisms and necessary to understanding how changes in social determinants impact alcohol use. Aim: To describe the processes and lessons learned in conducting a 20-year longitudinal study focused on alcohol use among SMW. Methods: The Chicago Health and Life Experiences of Women (CHLEW) study includes five waves of data collection (2000-present) with an age and racially/ethnically diverse sample of 815 SMW (ages 18-83) originally recruited in the Chicago Metropolitan Area in Illinois, a midwestern state in the United States (U.S.). Measures and focus have evolved over the course of the study. Results: The CHLEW study is the longest-running and most comprehensive study of SMW's drinking in the U.S. or elsewhere. Findings reported in more than 50 published manuscripts have contributed to understanding variations in SMW's risk for hazardous/harmful drinking based on sexual identity, age, race/ethnicity, sex/gender of partner, and many other factors. Conclusions: By describing the process used in conducting this long-term study, its major findings, and the lessons learned, we hope to encourage and support other researchers in conducting longitudinal research focused on SMW's health. Such research is critically important in understanding and ultimately eliminating sexual orientation-related health disparities.
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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 | 0.064 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".