investigate the moderating role of mobile phone dependency in the model of predicting subjective vitality based on perceived social support and Alexithymia mediated by academic procrastination
Bibliographic record
Abstract
Introduction:The purpose of this study was to investigate the moderating role of mobile phone dependency in the model of predicting subjective vitality based on perceived social support and alexithymia mediated by academic procrastination in adolescent girls. Materials and Methods: The statistical population included the Bandar Imam Khomeini high school girl students, in 2019. 352 of them were selected by multistage cluster random sampling. They responded to these questionnaires: smartphone addiction scale, Multidimensional Scale of Perceived Social Support, Alexithymia Questionnaire, academic procrastination Scale, and subjective vitality questionnaire. Data were analyzed by structural equation modeling Findings:The results showed that in both groups of addicted students to mobile and non-mobile addicted, the direct path of social support and alexithymia was not significant with subjective vitality, but the direct path of academic procrastination to subjective vitality was negative and significant and social support had a negative and significant relationship with academic procrastination and alexithymia had a positive and significant relationship with academic procrastination. Academic procrastination also mediated the relationship between social support and alexithymia with subjective vitality. Dependence on mobile phones moderated this mediation model. Conclusion:By increasing social support and treating alexithymia, it is possible to reduce academic procrastination in adolescents and thereby improve subjective vitality. And by teaching the correct use of mobile phones, the intensity of the impact of factors on reducing subjective vitality decreased.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".