Socio-Demographic, Economic and Psychological Correlates of Risky Sexual Behaviour Among Sexually Active Young People in Nigeria
Bibliographic record
Abstract
This study sought to identify the socio-demographic, economic, and psychological factors associated with risky sexual behaviour among sexually active youths in Nigeria with the view to providing more empirical information for the development of more effective interventions to improve safe-sex practices and the sexual health of the young people in Nigeria. The study analyzed the male and female datasets extracted from the 6th round of the Nigeria Multiple Indicator Cluster Survey data (MICS) (n=7,909) using descriptive statistics and multiple binary logistic regression to achieve the study objectives and test hypothesis. The results showed that 66% of the youths have had sex before reaching 18 years, 77% had unprotected sex, and 32% have had more than one-lifetime sexual partner. The significance of the association between socio-demographic (age, sex, marital status, ever fathered/mothered, awareness of AIDS, ethnicity, residence, and region), economic factors (employment status and wealth index), and risky sexual behaviour differ by the category of risky sexual behaviour. Overall psychological factor (satisfaction with life) was a significant correlate of the lifetime number of sexual partners. This study concludes that socio-demographic, economic, and psychological factors were predictive of risky sexual behaviour among young people in Nigeria. However, the significance of these predictors differs by type of risky sexual behaviour. The study recommends that more effective sexual health interventions must also address the prevalent psychological risk factors among young people in Nigeria- apart from different background characteristics- which could predispose them to risky sexual practices.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".