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Record W3116185579 · doi:10.1002/cpp.2546

External correlates of the <i>SPECTRA</i>: Indices of psychopathology (<i>SPECTRA</i>) in a clinical sample

2021· article· en· W3116185579 on OpenAlexaff
Mark A. Blais, Samuel Justin Sinclair, Laura A. Richardson, Christina Massey, Michelle B. Stein

Bibliographic record

VenueClinical Psychology & Psychotherapy · 2021
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsPsychopathologyPsychologyClinical psychologyConstruct validitySuicide attemptPoison controlPsychometricsPsychiatryInjury preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

The SPECTRA: Indices of Psychopathology is a broadband assessment inventory compatible with contemporary hierarchical models of psychopathology (internalizing, externalizing, reality impairing dimensions and global psychopathology factor). This study explored the SPECTRA's construct validity using a wide range of life event (extra-test) variables in a clinical sample. The life event variables included the following: education level, school failure, childhood adversity, suicide attempts, psychiatric hospitalizations, depression, psychotic symptoms, self-injury, substance abuse, arrests, physical violence, marital status, employment status and current medications. Results showed that all SPECTRA clinical scales had significant life event correlations. For the higher-order Spectra scales, the global index of psychopathology had the greatest number and range of life event correlations. Correlations for the externalizing and reality impairing Spectra scales provided solid validity evidence, while correlations for the internalizing Spectra scale were more diffuse. These findings provide the first non-test-based evidence of construct validity for the SPECTRA.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.096
GPT teacher head0.459
Teacher spread0.363 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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