Cognitive strategies affecting recall of sexual behavior among high-risk men and women.
Bibliographic record
Abstract
OBJECTIVE: Most sexual health research depends on self-reported information, but little is known about the ways in which individuals arrive at their responses to sexual behavior questions. The purpose of the present research was to investigate the cognitive strategies and contextual cues used to recall sexual behaviors among men and women at high risk for HIV. DESIGN: 102 men and 106 women were recruited from a public health sexually transmitted disease clinic (mean age = 31 years; 45% African American, 50% White) and asked to think aloud as they responded to questions about number of lifetime sexual partners and frequency of vaginal and oral sex (in the past 2 weeks or 3 months). MAIN OUTCOME MEASURES: Transcripts of participant interviews were coded for the different types of cognitive strategies and contextual cues that were used to recall counts of sexual partners and behaviors. RESULTS: Multivariate logistic regressions indicated that respondents tended to enumerate each instance of behavior when recalling low frequencies of behavior and small numbers of partners and to use rate-based estimates or general impression strategies when recalling high frequencies and numbers. Most respondents did not use self-generated contextual cues. CONCLUSION: Results suggest that reports of high frequencies of sexual behavior or large numbers of partners are approximations. For valid and reliable assessment, researchers should direct respondents to recall sexual behavior in small, manageable chunks through the use of interviewer prompts.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".