The International Perspectives on Internalizing Disorders in Children and Adolescents
Bibliographic record
Abstract
This paper reviews the experiences of researchers from Western and Eastern countries, including the USA, Germany, Canada, the United Kingdom, China, and others, in studying internalized disorders in children and adolescents. The diversity of countries with different public health systems in the review broadened the perspective on a diagnostic paradigm based on the transdiagnostic model of mental disorder classification. The paper examines various approaches to conceptualizing internalizing disorders in overseas research. It introduces the concept of "internalized disorders" and contrasts it with "externalized disorders", with a focus on the symptoms, diagnosis, and interventions for internalized disorders in childhood and adolescence. It also presents data on the epidemiology and aetiology of internalized disorders, analyzing their prevalence in populations, which vary by age, gender, and region of residence. The paper also includes a discussion on the comorbidity of internalized disorders in children and adolescents. This scope of information provides a comprehensive understanding of the essence of "internalized disorders" and their key characteristics, creating a foundation for developing effective diagnostic and therapeutic strategies in national psychological practice.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".