Validation of a Brief Internalized Sex-work Stigma Scale among Female Sex Workers in Kenya
Bibliographic record
Abstract
Female sex workers (FSW) often face severe stigma and discrimination and are extremely vulnerable to HIV and other sexually transmitted infections. In the fields of HIV and mental health, internalized stigma is associated with poor health care engagement. Due to the lack of valid, standardized measures for internalized sex work-related stigma, its dimensions and role are not well-understood. This study aimed to validate the six-item Internalized AIDS-Related Stigma Scale adapted to capture internalized sex work-related stigma by examining the scale's psychometric properties and performance among a cross-sectional, snowball sample of FSW (N = 497) in Kenya. While the original pre-hypothesized six-item model yielded acceptable CFI and SRMR values (CFI = 0.978 and SRMR = 0.038), the RMSEA was higher than desirable (RMSEA = 0.145). Our final four-item model demonstrated improved goodness of fit indices (RMSEA = 0.053; CFI = 0.999; and SRMR = 0.005). Both the pre-hypothesized six-item and reduced final four-item model demonstrated good internal consistency (Cronbach's alphas of 0.8162 and 0.8754, respectively). Higher levels of internalized stigma were associated with depression, riskier sexual behavior, and reduced condom use. This very brief measure will allow for reliable assessment of internalized stigma among FSW. Further investigation of internalized stigma among male sex workers, particularly the intersection of sex work-related and same-sex behavior-related stigmas, is needed.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".