The Development and Evaluation of a Brief Form of the Normative Male Alexithymia Scale (NMAS-BF) 1
Bibliographic record
Abstract
Chapter 6 presents a scale development study, adapted from a peer-reviewed journal article. The study extended prior work on the Normative Male Alexithymia Scale (NMAS), a unidimensional measure of some men&s;s limitations in expressing emotion that results from gender-based socialization informed by the masculine norm of restrictive emotionality. Data ( N = 505 men) were from Amazon Mechanical Turk participants. First, dimensionality was re-assessed using exploratory factor analysis, which supported the unidimensional structure. Second, based on these results, three six-item models of the NMAS-Brief Form (NMAS-BF) were developed, based on classical test theory (CTT), CTT optimized to avoid item redundancy, and item response theory (IRT). Third, the relative fits of these versions were assessed using confirmatory factor analysis (CFA) on a separate part of the sample, finding that IRT version was the best fitting model. Fourth, evidence for reliability for the NMAS-BF items (α = .80) and validity was found. Convergent evidence for validity was supported by a significant, moderate, positive correlation between the latent constructs of the NMAS-BF and Toronto Alexithymia Scale-20 (TAS-20), which measures clinical alexithymia. Concurrent evidence for validity of the latent factor of the NMAS-BF was assessed in a structural regression model which found that the NMAS-BF uniquely predicted Restrictive Emotionality scores when TAS-20 scores were included in the model. Finally, incremental evidence for validity was examined using hierarchical multiple regression, finding that NMAS-BF scores significantly predicted variance in Restrictive Emotionality scores above and beyond that predicted by TAS-20 scores. The results are discussed in relation to prior literature, future research directions, applications to counseling practice, and limitations.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".