Depressive and mobile phone addiction symptoms in Chinese adolescents with major depressive disorder: the mediating effect of alexithymia
Bibliographic record
Abstract
BACKGROUND: Mobile phone addiction (MPA) is associated with depression, yet the underlying mechanisms are not clear. This study aimed to explore the socio-demographic and clinical correlates of MPA symptoms, the associations between depressive and MPA symptoms, and whether the associations are mediated by alexithymia among adolescents with major depressive disorder (MDD). METHODS: This cross-sectional study was conducted from January to July 2021 in seven hospitals across the northern, central, and southern regions of Anhui Province, China. MPA symptoms, depressive symptoms, and alexithymia were assessed using the Mobile Phone Addiction Scale (MPAS), the Center for Epidemiologic Studies of Depression Symptom Scale (CES-D) and the 20-item Toronto Alexithymia Scale (TAS-20), respectively. RESULTS: A total of 286 adolescents with MDD were included. Univariate analyses revealed that adolescents with abnormal parental marriage, poorer academic performance, higher total scores of CES-D and TAS-20, and higher subscale scores of difficulty identifying feeling (DIF) and externally oriented thinking (EOT) were likely to have more severe MPA symptoms (all P < 0.05). Multivariate linear regression analyses showed that depressive symptoms were positively correlated with the severity of MPA symptoms in adolescents with MDD (all P < 0.05). Alexithymia and EOT partially mediated the associations between depressive and MPA symptoms. CONCLUSION: MPA symptoms are common in adolescents with MDD, and the effect of depressive symptoms on the severity of MPA symptoms is mediated partially through alexithymia. Therefore, effective identification and intervention for alexithymia may be important strategies to help clinical staff reduce the risk of MPA among adolescents with MDD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".