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Cross‐cultural equivalence in depression assessment: Japan–Europe–North American study

2005· article· en· W2108975105 on OpenAlexaff
Toshi A. Furukawa, David L. Streiner, Hideki Azuma, Teruhiko Higuchi, Kunitoshi Kamijima, Shigenobu Kanba, Norio Ozaki, A. Aoba, M. Murasaki, Satoshi Miura

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2005
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of Toronto
FundersEli Lilly and Company
KeywordsAnhedoniaHamilton Rating Scale for DepressionConfirmatory factor analysisPsychologyDepression (economics)Clinical psychologyRating scalePsychiatryStructural equation modelingDevelopmental psychologyMajor depressive disorderStatisticsMood

Abstract

fetched live from OpenAlex

OBJECTIVE: Worldwide use of the Hamilton Rating Scale for Depression (HRSD) presupposes that depression symptomatology can be measured the same way across countries but no empirical study has yet examined this issue. We therefore examined cross-cultural consistency of factor structure of HRSD. METHOD: A 17-item HRSD data were sought for 5,185 individuals diagnosed with major depression in Japan, Europe and North America. Candidate factor structures were obtained with simultaneous component analysis (SCA) across the three cultures. They were then submitted to multiple-group confirmatory factor analysis (CFA). RESULTS: According to SCA, 3-, 4- or 5-factor solutions were found to optimally and adequately summarize the variables for all the three populations. When submitted to CFA, the 5-factor solution was the best fitting and the most parsimonious: they were 'anhedonia/retardation,''guilt/agitation,''bodily symptoms,''insomnia' and 'appetite.' CONCLUSION: Common underlying factors exist for HRSD among Japanese, European and American patients with major depression.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.366
Teacher spread0.347 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations45
Published2005
Admission routes1
Has abstractyes

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