The Influence of Neurotic Personality Traits on Excessive Short Video Usage
Bibliographic record
Abstract
This study focuses on the influence of neuroticism on the tendency to consume a high amount of short videos, revealing the internal flow as well as paths that lead to it. The study used a cohort of 513 undergraduates and employed tools such as the Chinese Big Five Personality Inventory (in the brief form), the Short Video Addiction Scale, the Flow Experience Scale, and the Brief Self-Control Scale. Findings from this research underscore that: - The loading of neuroticism on the overuse of short videos are significantly positive; - The effect of neuroticism on the overindulgence of short video content acts through two routes: First, an indirect path of self-control and flow, and second, a serial mediation path between self-control and flow. The comprehensive analysis explains excessive consumption of short video content that gives birth to the guidance on strategies of prevention and correction that will be aimed at college students. This thoughtful analysis adds value to the discussion related to digital behaviors and their psychological roots.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".