Mediating Role of Smartphone Addiction on the Relationship Between Self-Efficacy and Psychological Escapism Among College Students: Structure Model Test
Bibliographic record
Abstract
The present work explores the potential role of smartphone addiction in mediating the correlation between self-efficacy and Psychological Escapism among university students. The paper’s stratified convenience sample comprised 195 students from the World Islamic Sciences and Education University. Validated scales measuring self-efficacy, psychological escapism, and smartphone addiction were utilized for data collection. The findings indicate that smartphone addiction, self-efficacy, and psychological escapism were all found at moderate levels. Moreover, the presence of smartphone addiction as a mediating variable resulted in a significant increase in the proportion of explained variance in the level of psychological escapism attributed to self-efficacy (31%), compared to the absence of this mediating variable (22%). Additionally, while gender and academic year have significant effects on psychological escapism, the demographic elements investigated did not demonstrate any significance with self-efficacy or smartphone addiction among college students. Accordingly, this research points out the importance of developing curative and preventive counseling programs aimed at reducing smartphone addiction and mitigating the level of psychological escapism by enhancing self-efficacy among college students.
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 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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".