Internet addiction belief, but not Internet use time, is independently associated with menstrual pain severity and interference to social life among adolescents: a cross-sectional study
Bibliographic record
Abstract
INTRODUCTION: Problematic Internet use is a serious health issue for modern adolescents who have developed and matured in a global Internet environment. This study aimed to examine whether Internet use time and Internet addiction beliefs were independently associated with menstrual pain severity and its interference among Japanese adolescents. METHODS: We recruited 1166 adolescents at two high schools to complete questionnaires on Internet use and menstrual pain. The explanatory variable was self-reported average Internet use time per day and Internet addiction beliefs ('none' (reference) 'somewhat', 'moderate' and 'severe'). The outcome variables were moderate-to-severe menstrual pain and interference. A multivariable logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for moderate-to-severe menstrual pain and interference. Adjustment variables were age, body mass index, belonging to a community or school sports club, sleep duration and Internet addiction beliefs/Internet use time. RESULTS: Internet addiction belief, but not Internet use time, was independently associated with menstrual pain severity and interference to social life in a dose-response manner. ORs (95% CIs) of moderate-to-severe menstrual pain for slight, moderate and severe Internet addition beliefs were 1.43 (1.02-1.99), 1.89 (1.31-2.74) and 1.88 (1.10-3.23), respectively. ORs of moderate-to-severe disability due to menstrual pain for slight, moderate and severe Internet addition beliefs were 1.25 (0.75-1.82), 1.72 (1.01-2.92) and 2.21 (1.11-4.40), respectively, after adjusting for average Internet use time. CONCLUSION: Internet addiction belief was associated with higher prevalence of moderate-to-severe menstrual pain among adolescents, beyond the variance accounted for by Internet use time.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".