Latent Heterogeneity of Online Sexual Experiences and Associations With Sexual Risk Behaviors and Behavioral Health Outcomes in Chinese Young Adults: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Online sexual experiences (OSEs) are becoming increasingly common in young adults, but existing papers have reported only on specific types of OSEs and have not shown the heterogeneous nature of the repertoire of OSEs. The use patterns of OSEs remain unclear, and the relationships of OSEs with sexual risk behaviors and behavioral health outcomes have not been evaluated. OBJECTIVE: This study aimed to examine the latent heterogeneity of OSEs in young adults and the associations with sexual risk behaviors and behavioral health outcomes. METHODS: The 2021 Youth Sexuality Study of the Hong Kong Family Planning Association phone interviewed a random sample of 1205 young adults in Hong Kong in 2022 (male sex: 613/1205, 50.9%; mean age 23.0 years, SD 2.86 years) on lifetime OSEs, demographic and family characteristics, Patient Health Questionnaire-4 (PHQ-4) scores, sex-related factors (sexual orientation, sex knowledge, and sexual risk behaviors), and behavioral health outcomes (sexually transmitted infections [STIs], drug use, and suicidal ideation) in the past year. Sample heterogeneity of OSEs was analyzed via latent class analysis with substantive checking of the class profiles. Structural equation modeling was used to examine the direct and indirect associations between the OSE class and behavioral health outcomes via sexual risk behaviors and PHQ-4 scores. RESULTS: The data supported 3 latent classes of OSEs with measurement invariance by sex. In this study, 33.1% (398/1205), 56.0% (675/1205), and 10.9% (132/1205) of the sample were in the abstinent class (minimal OSEs), normative class (occasional OSEs), and active class (substantive OSEs), respectively. Male participants showed a lower prevalence of the abstinent class (131/613, 21.4% versus 263/592, 44.4%) and a higher prevalence of the active class (104/613, 17.0% versus 28/592, 4.7%) than female participants. The normative class showed significantly higher sex knowledge than the other 2 classes. The active class was associated with male sex, nonheterosexual status, higher sex desire and PHQ-4 scores, and more sexual risk behaviors than the other 2 classes. Compared with the nonactive (abstinent and normative) classes, the active class was indirectly associated with higher rates of STIs (absolute difference in percentage points [Δ]=4.8%; P=.03) and drug use (Δ=7.6%; P=.001) via sexual risk behaviors, and with higher rates of suicidal ideation (Δ=2.5%; P=.007) via PHQ-4 scores. CONCLUSIONS: This study provided the first results on the 3 (abstinent, normative, and active) latent classes of OSEs with distinct profiles in OSEs, demographic and family characteristics, PHQ-4 scores, sex-related factors, and behavioral health outcomes. The active class showed indirect associations with higher rates of STIs and drug use via sexual risk behaviors and higher rates of suicidal ideation via PHQ-4 scores than the other 2 classes. These results have implications for the formulation and evaluation of targeted interventions to help young adults.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".