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Record W2087417674 · doi:10.1080/15374416.2012.710163

Depression in China: Integrating Developmental Psychopathology and Cultural-Clinical Psychology

2012· review· en· W2087417674 on OpenAlexafffund
Andrew G. Ryder, Jiahong Sun, Xiongzhao Zhu, Shuqiao Yao, Yulia Chentsova-Dutton

Bibliographic record

VenueJournal of Clinical Child & Adolescent Psychology · 2012
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsConcordia UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsPsycINFOPsychologyPsychopathologyDepression (economics)ChinaMental healthDevelopmental psychopathologyClinical psychologyPsychiatryDevelopmental psychologyMEDLINE

Abstract

fetched live from OpenAlex

With a starting point in John Abela's groundbreaking developmental psychopathology research on adolescent depression in China, we aimed to review the state of the literature on Chinese depression across the lifespan. We began with Dr. Abela's published studies relevant to depression in China and our own research with adults before turning to the reference lists of these articles to find additional sources. Then we conducted literature searches using PsycINFO and PubMed to find other relevant studies published between April 2001 and April 2011 . There are two distinct literatures on depression in China. Developmental psychopathology research has emphasized adolescent samples and cognitive models of causation; cultural-clinical psychology and cultural psychiatry research have emphasized adult samples and the meanings associated with emotions, symptoms, and syndromes. Both approaches to the study of depression in China have yielded important findings but have also highlighted issues that could be better addressed by incorporating the other approach. Beyond depression in China, the psychological study of culture and mental health more generally would benefit from greater exchange between developmental psychopathology and cultural-clinical psychology.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.184
GPT teacher head0.506
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations41
Published2012
Admission routes2
Has abstractyes

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