Prevalence and Correlates of Alexithymia and Its Relationship With Life Events in Chinese Adolescents With Depression During the COVID-19 Pandemic
Bibliographic record
Abstract
Objectives: The incidence of psychological and behavioral problems and depression among adolescents is increasing year by year, which has become an important public health problem. Alexithymia, as an important susceptible factor of adolescent depression, may continue to develop and strengthen under the stimulation of COVID-19-related stressors. However, no studies have focused on alexithymia in adolescent depression during the pandemic in China. This study aims to investigate the incidence and related factors of alexithymia in adolescent depression during the pandemic. Methods: Three hundred adolescent patients were enrolled from October 2020 to May 2021. The general demographic information of all participants was collected, and the clinical characteristics were assessed by the 20-item Toronto Alexithymia Scale (TAS-20), the Adolescent Self-Rating Life Events Check (ASLEC) List, the Childhood Trauma Questionnaire (CTQ), and the Positive and Negative Suicide Ideation (PANSI) Inventory. Results: The incidence of alexithymia was significantly higher among adolescents with depression (76.45%) during the pandemic. There were significant differences in school bullying, disease severity, ASLEC score, CTQ score and PANSI score between adolescents with and without alexithymia. In addition, learning stress, health and adaptation problems during the pandemic may be influential factors in alexithymia of adolescent depression ( P < 0.05). Conclusions: According to the results, we found a high incidence of alexithymia in adolescent depression during the pandemic. More support and attention from families, schools and society is needed to develop preventive and targeted psychological interventions as early as possible.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".