DEPRESSION AMONG CHINESE CHILDREN AND ADOLESCENTS: A REVIEW OF THE LITERATURE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p><span style="font-family: Times New Roman; font-size: small;">The purpose of this review is to explore, identify, and discuss the predisposing factors and associated outcomes of depression in Chinese children and adolescents. <span style="font-family: Times New Roman; color: #262626;">For inclusion in the review, studies had to meet our objectives, be original peer-reviewed articles, conducted among Chinese children and adolescents in China. Articles were sourced through MEDLINE, EMBASE, </span></span><span style="font-family: Times New Roman; color: #262626; font-size: small;">Wan Fang Data</span><span style="font-family: Times New Roman; color: #262626; font-size: small;">,</span><span style="font-family: Times New Roman; color: #262626; font-size: small;"> </span><span style="font-family: Times New Roman; font-size: small;">PsycINFO,</span><span style="font-family: Times New Roman; color: #262626; font-size: small;"> and DOAJ databases. The results of the review indicate that the prevalence of depression symptoms in Chinese children and adolescents is high. The following factors are related to depression in Chinese children and adolescents: family, social factors, peer relations, gender, age, obesity, body image, and ethnicity. The outcomes of depression are poor academic performance, psychosocial retardation, conduct problems, cognitive distortion, and suicide. Depression is a major mental health problem among Chinese children and adolescents. This points to the need for longitudinally designed and controlled studies to establish effective preventive strategies.</span></p>
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.
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) | 0.001 | 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 | 0.001 |
| 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 it