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Record W4310054454 · doi:10.1177/21677026221122773

Examination of the Factor Structure of Psychopathology in a Mozambican Sample

2022· article· en· W4310054454 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Psychological Science · 2022
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsColumbia College
FundersFogarty International CenterNational Institute of Mental HealthNational Institute on Alcohol Abuse and Alcoholism
KeywordsPsychopathologyPsychologyComorbidityClinical psychologyConfirmatory factor analysisPsychiatryRisk factorChild psychopathologyStructural equation modelingMedicineInternal medicine

Abstract

fetched live from OpenAlex

Factor-analytic studies are needed in global samples to advance understanding of psychopathology. We aimed to examine the structure of psychopathology and a general psychopathology ('p') factor using data from a cross-sectional study of 971 adults (63% women) from Maputo City, Mozambique. We used confirmatory factor analyses of symptoms from 15 psychiatric disorders to test common models of the structure of psychopathology. Models including internalizing, substance use, and thought disorder factors as well as a general p-factor fit the data well. Measurement invariance testing revealed that factor loadings on p differed by gender. Higher levels of p, internalizing, and thought disorder factors were associated with greater suicide risk, psychiatric comorbidity, chronic medical illnesses, and poorer functioning. A general psychopathology ('p') factor and internalizing, substance use, and thought disorder factors are identifiable in this Mozambican sample. Understanding psychopathology dimensions is a step toward building more scalable mental health service approaches globally.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.167
GPT teacher head0.525
Teacher spread0.359 · 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