Exploring Determinants and Factors Associated with Problematic Smartphone Use among Youth
Bibliographic record
Abstract
Background: Children and adolescents represent the population most susceptible to problematic smartphone use. This vulnerability is supported by developmental, behavioral, and epidemiological evidence. Objective: To provide a comprehensive synthesis of current evidence regarding the determinants and factors associated with problematic smartphone use (PSU) among youth. Methods: First, a systematized qualitative literature review was developed, and second, exploratory analyses were conducted using data from the SMARTKids Québec pilot study, which surveyed approximately 250 Canadian students aged 6–17. Main findings: The review shows that psychosocial vulnerabilities and sleep disruption stand out as the most consistent correlates with PSU. The exploratory findings highlight that higher levels of smartphone use were positively correlated with age and symptoms of depression, anxiety, and stress. Conversely, higher smartphone use was linked to poorer academic performance. Implications: The chapter emphasizes the importance of distinguishing between underlying psychosocial determinants and associated behavioral or mental health factors. Ultimately, these insights support the need for a balanced and preventive approach, one that avoids alarmism but acknowledges the potential risks of problematic smartphone use, a multifaceted issue with implications for youth development and well-being.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".