CAN SELF-EFFICACY MEDIATE RELATIONS BETWEEN HELICOPTER PARENTING AND SOCIAL MEDIA ADDICTION AMONG TURKISH ADOLESCENTS?
Bibliographic record
Abstract
This study aimed to investigate the mediating role of self-efficacy (social, emotional, and academic) in the relationship between helicopter parenting and social media addiction (SMA) among Turkish adolescents. Previous studies examining the influences of helicopter parenting behaviors on mental health mostly studied college-age children and were conducted in Western cultures, while the current study focused on the association of helicopter parenting with the mental health of younger children and was conducted an Eastern country (Türkiye). The participants consisted of 326 adolescents (212 girls and 114 boys) who had at least one social media account. Data were collected through the Helicopter Parent Attitude Scale, the Self-Efficacy Scale for Children, the Social Media Addiction Scale for Adolescents, and a demographic information form. Data were analyzed with descriptive statistics, Pearson correlation analysis, and regression-based bootstrapping techniques. The results show that both maternal and paternal helicopter parenting had significant and direct positive associations with SMA. Emotional and academic self-efficacy had significant and direct associations with SMA, while social self-efficacy did not show such an association. In addition, it was found that the mediating effects of self–efficacy (social, emotional, and academic) in relations between helicopter parenting and SMA were not significant.
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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 | 0.003 |
| 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 | 0.001 |
| 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".