Fear of Missing out, Social Media Engagement, Smartphone Addiction and Distraction: Moderating Role of Self-Help Mobile Apps-based Interventions in the Youth
Bibliographic record
Abstract
Smartphones offer high mobility and internet connectivity at the same time which has led to a substantial increase in the number of active social media users on the move, especially the ‘Millennials’. The excessive use of smartphone has been linked with several issues including mental well-being. Recently, different mobile applications have emerged to help users track their excessive use of smartphones and protect them from potential risks to mental health. This paper uses self-determination theory to examine the moderating role of such mobile applications (or self-help interventions) on inter-relationships between social media engagement, smartphone addiction and smartphone distractions. Survey responses from 284 college students reveal that mobile applications could prove to be quite effective self-help interventions that can help the young people in self-regulating their smartphone use. These results have substantial implications for designing effective mobile app-based interventions to save young people from potential risks to their mental health, productivity, and safety in performing their daily tasks. Future research directions have also been pointed out.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".