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Record W2035458557 · doi:10.1159/000288104

Validation of the Toronto Alexithymia Scale with Substance Abusers

2010· article· en· W2035458557 on OpenAlexaboutno aff
Mark G. Haviland, Dale G. Shaw, James P. MacMurray, Michael A. Cummings

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaPsychologyToronto Alexithymia ScaleClinical psychologyBeck Depression InventorySubstance abusePsychometricsBeck Hopelessness ScalePsychiatryNormativeAnxiety

Abstract

fetched live from OpenAlex

The purposes of this paper were to complete factor and item analyses of the Toronto Alexithymia Scale (TAS) in a sample of mixed substance abusers and to examine the correlations between patients' TAS scores and other variables. Results indicate that the TAS is a reliable, valid measure of alexithymia for substance abusers. The factor structure we found is congruent with the theoretical construct and is similar to those published in the normative studies; coefficient alpha reliability was 0.68. Additionally, a high percentage of the subjects (50.4%) scored in the alexithymic range while 24% had scores in the nonalexithymic range. Patients' TAS scores were positively associated with Beck Depression Inventory scores, with a reported paternal history of alcoholism, and with attempted suicide; TAS scores were negatively associated with being Black.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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 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

Citations114
Published2010
Admission routes1
Has abstractyes

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