Prevalence and correlates of problematic pornography use among undergraduate medical students in Egypt
Bibliographic record
Abstract
ObjectivePornography use can become addictive when a person loses control of watching sexual materials, such as sex graphic images and movies, and is unable to stop doing so despite negative consequences. Pornography addiction is a disorder that can impair mental health, behavior, and performance. The purpose of this study was to determine the prevalence and correlates of problematic pornography use among medical students in Egypt.MethodsThis cross-sectional study included 614 undergraduate medical students selected from each of the 6 academic years at a faculty of medicine in Egypt. The short version of the problematic pornography consumption scale (PPCS-6) was used to determine problem pornography use. Sociodemographic information and academic performance data were collected, and the Depression Anxiety Stress Scale-21 (DASS-21) was administered to assess depression, anxiety, and stress symptoms.ResultsNearly one-quarter (23.3%) of students had problematic pornography use. Problematic pornography use was associated with older age and male sex. Students with problematic pornography use reported fewer hours studying and had lower test scores in the previous year than those without problematic pornography use. Medical students with problematic pornography had significantly higher levels of depression, anxiety and stress symptoms compared to those without.ConclusionsProblematic pornography use is a common problem among medical students at a university in Egypt, is present in nearly one-quarter of students, and is significantly associated with older age, male sex, and depression, anxiety, and stress symptoms, as well as poorer academic performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".