Dissociating self reported interoceptive accuracy and attention: Evidence from a Portuguese community sample
Bibliographic record
Abstract
The 2x2 factorial model has been recently proposed as a promising framework to measure individual differences in interoception. The first factor addresses which domain is being measured (interoceptive accuracy vs. attention), while the second distinguishes how it is being measured (self-report beliefs vs. objective performance). The current study examined the association between self-reported interoceptive accuracy and attention. We hypothesized no linear association between these constructs, although a quadratic U-shaped association was expected. Furthermore, alexithymia should be differentially related to interoceptive accuracy and attention. An online community sample (*n *= 515) completed the Interoceptive Accuracy Scale (IAS), the Body Perception Questionnaire (BPQ) *ndexing self-reported interoceptive attention, and the Toronto Alexithymia Scale (TAS). Pearson correlations, Steiger’s Z-test, polynomial regression analysis, and two-lines testing were used for statistical analysis. IAS was positively correlated with BPQ, r = .204, p < .001. In the polynomial regression analysis, the linear model indicated a positive association between IAS and BPQ (4.2%), but the quadratic term explained an additional 12.7% of the variance. Two-lines testing indicated a U-shaped association between self-report interoceptive accuracy and attention. IAS was negatively correlated with TAS, r = -.291, p < .001, while there was no significant association between BPQ and TAS, r = -.030, p = .500, as these correlations were statistically different. These results suggest that interoceptive accuracy and attention can be dissociated using self-report measures and may display a quadratic U-shaped association, providing further evidence for the 2x2 factorial model. Future studies should explore the non-linear relationship between interoceptive accuracy and attention using alternative questionnaires and performance-based measures.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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; both teacher heads agree on what is shown here.
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".