Young people’s condom use during the COVID-19 pandemic: Cross-cultural differences and what predict them
Bibliographic record
Abstract
According to the Behavioural Immune System (BIS) theory, humans are motivated to avoid exposureto harmful pathogens. However, most sources of infection are impossible to avoid completely, leadingto the development of tools to reduce pathogen threat. Condoms are one example of an effective toolthat can be used to avoid exposure to sexually transmitted infections (STIs). Within this framework, itwould be expected that condom use would increase after the spread of a novel coronavirus (i.e.,COVID-19), but the evidence to date is inconsistent. The present study aimed to clarify theseinconsistencies by examining changes in condom use cross-culturally. First, Study 1 aimed to uncoverwhether condom use after the initial outbreak period was consistent with the BIS theory among anAustralian sample (N1 = 129). Contrary to the BIS, but inline with other findings in Australia, therewas a general decline of condom use. Second, Study 2 aimed to examine whether cross-culturalcondom use was consistent with the BIS. Sexually active participants (N2 = 3843) across 17 countrieswere asked about their condom use. Results revealed a significant decline in Canada, Portugal,Vietnam, Uganda, and Taiwan. Vaccination percentage and lockdown stringency were associatedwith this decline cross-culturally. In sum, there was no evidence supporting the BIS theory, and thesefindings continue to add concerns about the spread of STIs among young people during the pandemic.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".