Exploring symptom-level associations between anxiety and depression across developmental stages of adolescence: a network analysis approach
Bibliographic record
Abstract
BACKGROUND: Anxiety and depression often co-occur during adolescence, but the associations between symptoms of these two disorders in this developmental period are not yet fully understood. Network analysis provides a valuable approach to uncover meaningful associations among symptoms and offers insights for prevention and intervention strategies. This study aimed to investigate symptom-level associations between anxiety and depression using network analysis and to identify core symptoms, bridge symptoms, and differences in network structure across different stages of adolescence. METHODS: The cross-sectional study was conducted in March 2022 in Shenzhen, China. Participants completed the Generalized Anxiety Disorder Scale-7 and Patient Health Questionnaire Depression Scale, along with demographic questionnaires assessing age and gender. Chinese adolescents aged 10 to 17 who were in Grades 5 or 6 of elementary school, Grades 1 or 2 of middle school, or Grades 1 or 2 of high school, and who could comprehensively understand and read Chinese were recruited as participants. Students in Grade 3 of middle and high schools were excluded due to their upcoming high school or college entrance examinations. Based on age, participants were categorized into early, middle, and late developmental stages of adolescence. RESULTS: "Loss of control" was among the most central symptoms in the comorbidity network throughout all three developmental stages; "excessive worry" and "anhedonia" emerged as the core symptoms in early adolescence, and "restlessness" as the core symptom in late adolescence. "Anhedonia," "sad mood," and "fatigue" were identified as bridge symptoms between anxiety and depression across all three developmental stages of adolescence. The global strength of the network in middle adolescence was significantly higher compared to the other two stages. CONCLUSION: These findings highlight the core and bridge symptoms that require special attention and intervention at each stage of adolescence. Moreover, significantly higher network connectivity in middle adolescence suggests this is a critical period for intervention to prevent the development of comorbid mental disorders.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".