Is Smartphone Addiction Associated with a Younger Age at First Use in University Students?
Bibliographic record
Abstract
BACKGROUND: Recent evidence highlighted the potential of habitual smartphone use among youth to become an addiction analogous to established behavioral and substance-related addictions. While investigators revealed independent predictive effects of several sociodemographic factors, personality traits, psychological conditions, and smartphone usage patterns on smartphone addiction (SPA) in university students, none examined the independent effect of age at first smartphone use, a potential predictor variable, on subsequent development of SPA.OBJECTIVE: This study aims to examine the independent association between age at first smartphone use and SPA score in a sample of 688 Lebanese undergraduate university students.METHODS: A random sample of 688 undergraduate students selected from Notre Dame University, Lebanon filled out survey forms that included a) questions on socio-demographics, academics, smartphone use, personality type, depression, anxiety, and lifestyle habits; b) 26-item Smartphone Addiction Inventory (SPAI) Scale. Multiple linear regression analyses were used to examine the independent association between age at first use and SPA level.RESULTS: Mean age at first smartphone use was about 15 years. Younger age at first use of smartphone was found to be significantly associated with several SPA symptoms and correlated with higher total SPAI score. In the unadjusted regression model, higher total SPAI scores were found to be significantly associated with younger age at first smartphone use. This association remained significant in the partially adjusted model, but disappeared in the fully adjusted one when controlling additionally for smartphone use habits.CONCLUSION: Younger age at smartphone use did not independently predict SPA in this sample of students.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".