The Effect of Age on Human Immunodeficiency Virus Risk Related Behaviors among Undergraduate Students at a Historically Black College and University in the United States of America
Bibliographic record
Abstract
Objective: HIV infections have taken a heavy toll on young adults in the USA. Most undergraduate students fall within the age group who are at high risk of HIV infections. The effect of age on HIV risk related behaviors among African American undergraduate students has never been investigated before. Thus, this study assessed the effect of age on HIV risk related behaviors among African American undergraduate students at a Historically Black College and University. Methods: A total of 400 respondents were randomly selected from Jackson State University of the USA, a Historically Black College and University. A cross-sectional study design was utilized from January to September, 2016. Data were collected using a validated self-administered standardized questionnaire. Chi-square test was used to see the association between age and HIV risk related behaviors. Results: Over seventy five percent of the study participants have had at least one risk behavior related to HIV infection transmission and there was significant statistical difference between students aged 18-24 years and students aged 25 years and above (p<0.05). The students aged 18-24 years were more likely to participate in risk behaviors that could predispose them to HIV infections (P = 0.02). Conclusions: As the HIV related risk behaviors was higher among students aged 18-24 years old, age appropriate HIV preventive programs that are appealing to young people will be required to effectively prevent HIV infection among this vulnerable population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".