Psychosocial correlates of risky sexual behaviour amongst students in Niger Delta University, Bayelsa
Bibliographic record
Abstract
globally young people constitute one quarter of the population. They are the most vibrant and productive sector, but they are also prone to more risky sexual behaviour (RSB) with attendant negative consequences. In the Niger Delta Region of Nigeria, persistent conflicts and socioeconomic difficulty predisposes young people to risky conducts including RSB. The aim of this study is to explore the psychosocial correlates of risky sexual behaviour amongst students in the Niger Delta University, Bayelsa.we undertook a descriptive cross-sectional survey of students in the university. A multistage random sampling technique was used to recruit 400 students who completed a self-administered questionnaire. The data collected was analyzed using SPSS version 20.0.out of the 400 students, 64.3% (257) engaged in RSB and 46.8% (187) were currently engaging in RSB. Rates of self-reported depression, suicidal ideation and attempt were 62.3% (249), 18.0% (72) and 14.3% (54) respectively. Independent correlates of RSB include being older than 19 years (aOR. 2.82; 95% C.I. 1.44 -5.51), male gender (aOR. 1.70; 95% C.I. 1.08-2.66), having depression (aOR. 1.83; 95% C.I. 1.15-2.92), being diagnosed with a sexually transmitted disease (STD)/HIV (aOR. 2.08; 95% C.I. 1.12-3.86), and having been taught about condoms (aOR. 1.80; 95% C.I. 1.13-2.86).risky sexual behaviours have negative psychosocial and health implications. Regular and continuous health education targeted at young people is essential to reduce the social and health effects associated with RSB.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".