Exploring Deeper Causes Linking Adolescents’ Mental Disorders to Mobile Phone Use Problems: Grounded Theory Approach
Bibliographic record
Abstract
BACKGROUND: Evidence from a variety of studies link mobile phone use with an increase in mental health problems, with the situation being particularly prevalent in China and exacerbated by the COVID-19 quarantine. OBJECTIVE: This study aims to reveal underlying connections between mobile phone use and mental disorders of adolescents, and to develop a theory to help parents and counseling psychologists better understand and intervene in future cases. METHODS: A total of 37 teenagers having both mental health and mobile phone use problems, along with their parents, were included for individual interviews. These interviews were transcribed, coded, and analyzed using qualitative methods of grounded theory. RESULTS: The grades-ranking-first mentality is one of the main factors causing problems such as defective family bonding and peer influences, pushing teenagers with mental disorders to seek comfort in the virtual world through their cellphones. CONCLUSIONS: The idea proposed in this study is not only inspiring for psychological counseling and therapy on adolescents with mental problems but also beneficial for school educators and parents to better understand the adolescents. The findings of the study are also particularly noteworthy in the postpandemic age, where parents whose work locations and schedules are substantially affected due to any emergencies should try to build a relaxing and cozy atmosphere at home to avoid possible conflicts with adolescents.
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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 | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".