Meeting Sexual Partners Through Internet Sites and Smartphone Apps in Australia: National Representative Study
Bibliographic record
Abstract
BACKGROUND: Studies have reported on the proportion of the population looking for potential sexual partners using internet sites and smartphone apps, but few have investigated those who have sex with these partners, arguably a more important target group for health promotion. OBJECTIVE: This study aimed to determine the proportion of people who have had sex with someone they met on an internet site or a smartphone app in the previous year. METHODS: We analyzed data from the 2012-2013 Second Australian Study of Health and Relationships, a nationally representative telephone survey of Australian residents aged 16-69 years (N=20,091). The participation rate for the telephone survey was 66.22%. The prevalence of looking for a potential partner, physically meeting, and having sex with someone first met through an internet site or a smartphone app was estimated. Multivariate logistic regression was used for men and women separately to determine demographic and behavioral factors associated with having had sex with someone met on an internet site or a smartphone app in the last year. RESULTS: Overall, 12.09% of respondents had looked for potential partners using these technologies and 5.40% had done so in the last year. In the last year, 2.98% had met someone in person and 1.95% reported having had sex with someone first met on an internet site or a smartphone app. The prevalence of all behaviors was greater in men than in women and in younger respondents than in older respondents. Among sexually active men, factors associated with having had sex with someone met using internet sites or smartphone apps included identifying as gay or bisexual (adjusted odds ratio, AOR: 15.37, 95% CI 8.34-28.35), having either 2-3 or >3 sexual partners in the last year (AOR: 9.20, 95% CI 9.20-34.68 and AOR: 35.77, 95% CI 18.04-70.94, respectively), having had a sexually transmissible infection (STI) test in the past year (AOR: 2.02, 95% CI 1.21-3.38), or an STI in the last year (AOR: 3.15, 95% CI 1.25-7.97). Among sexually active women, factors associated with having had sex with someone met on an internet site or a smartphone app were as follows: having either 2-3 or >3 sexual partners in the last year (AOR: 32.01, 95% CI 13.17-77.78 and AOR: 71:03, 95 % CI 27.48-183.57, respectively), very low and low income (vs very high AOR: 3.40, 95% CI 1.12-10.35), and identifying as lesbian or bisexual (AOR: 2.27, 95% CI 1.04-4.49). CONCLUSIONS: More than a third of adults who had looked for potential partners using websites and apps each year had sex with such partners, and those who had done so were more sexually active, suggesting that dating and hookup websites and applications are suitable settings for targeted sexual health interventions.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".