The Internet administration version of the 20-item Toronto Alexithymia Scale.
Bibliographic record
Abstract
Researchers are increasingly administering tests developed and validated in paper format via the Internet. Yet, the equivalence between paper and Internet concerning administration of tests is not typically demonstrated. We evaluated the reliability, factorial and external validity, and measurement equivalency of the Internet version of the 20-item Toronto Alexithymia Scale (TAS-20; Bagby, Parker, & Taylor, 1994; Bagby, Taylor, & Parker, 1994; Lumley et al., 2007) vis-à-vis the paper version. Participants (N = 621) completed the TAS-20 either on the Internet or on paper. Reliability and item-to-scale homogeneity were evaluated for each format. We used confirmatory factor analyses (CFAs) to evaluate factorial validity and used CFA-based factorial invariance procedures to determine measurement equivalency. Alpha coefficients and mean interitem correlations (MICs) were adequate for the full-scale TAS-20 Internet and paper versions and the difficulty identifying feelings (DIF) and difficulty describing feelings (DDF) factor scale test scores; in both formats, alpha and MICs were poorer for externally oriented thinking (EOT) factor test scores compared to scores for the DIF and DDF. The fit of the 3-factor structure of the TAS-20 was adequate for both formats. Factorial invariance across formats was also demonstrated; mean scores for the total scale and each factor scale were not different across formats. Correlations with the domain and facet scales of the Revised NEO Personality Inventory (Costa & McCrae, 1992b) were mostly similar across formats. The Internet and paper versions of the TAS-20 are comparably reliable and valid. An Internet version of the TAS-20 expands opportunities to collect data and permits generalizing of results across studies using the different modes of administration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".