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Record W2160435594 · doi:10.1037/a0021729

Implicit measures of association in psychopathology research.

2011· review· en· W2160435594 on OpenAlexaff
Anne Roefs, Jorg Huijding, Fren T.Y. Smulders, Colin M. MacLeod, Peter J. de Jong, Reínout W. Wiers, Anita Jansen

Bibliographic record

VenuePsychological Bulletin · 2011
Typereview
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologyPanic disorderPsychopathologyDysfunctional familyClinical psychologyPredictive validityAssociation (psychology)Specific phobiaComorbidityPsychiatryAnxietyPsychotherapist

Abstract

fetched live from OpenAlex

Studies obtaining implicit measures of associations in Diagnostic and Statistical Manual of Mental Disorders (4th ed., Text Revision; American Psychiatric Association, 2000) Axis I psychopathology are organized into three categories: (a) studies comparing groups having a disorder with controls, (b) experimental validity studies, and (c) incremental and predictive validity studies. In the first category, implicit measures of disorder-relevant associations were consistent with explicit beliefs for some disorders (e.g., specific phobia), but for other disorders evidence was either mixed (e.g., panic disorder) or inconsistent with explicit beliefs (e.g., pain disorder). For substance use disorders and overeating, expected positive and unexpected negative associations with craved substances were found consistently. Contrary to expectation, implicit measures of self-esteem were consistently positive for patients with depressive disorder, social phobia, and body dysmorphic disorder. In the second category, short-term manipulations of disorder-relevant states generally affected implicit measures as expected. Therapeutic interventions affected implicit measures for one type of specific phobia, social phobia, and panic disorder, but not for alcohol use disorders or obesity. In the third category, implicit measures had predictive value for certain psychopathological behaviors, sometimes moderated by the availability of cognitive resources (e.g., for alcohol and food, only when cognitive resources were limited). The strengths of implicit measures include (a) converging evidence for dysfunctional beliefs regarding certain disorders and consistent new insights for other disorders and (b) prediction of some psychopathological behaviors that explicit measures cannot explain. Weaknesses include (a) that findings were inconsistent for some disorders, raising doubts about the validity of the measures, and (b) that understanding of the concept "implicit" is incomplete.

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 imitation

Not 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.

metaresearch head score (Codex)0.063
metaresearch head score (Gemma)0.187
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.187
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.012
Science and technology studies0.0010.003
Scholarly communication0.0040.009
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.373
GPT teacher head0.505
Teacher spread0.132 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations227
Published2011
Admission routes1
Has abstractyes

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