Untangling Self-Reported Interoceptive Attention and Accuracy: Evidence from the European Portuguese Validation of the Body Perception Questionnaire and the Interoceptive Accuracy Scale
Bibliographic record
Abstract
Objectives: To explore the factor structure and psychometric properties of the European Portuguese versions of the Interoceptive Accuracy Scale (IAS) and the Body Perception Questionnaire (BPQ) - Body Awareness and Autonomic Reactivity; to examine the association between self-reported interoceptive attention and accuracy (BPQ Body Awareness and IAS, respectively).Method: A community-sample (n=515) completed an online survey comprising the IAS, BPQ, and Toronto Alexithymia Scale. Factor structure analyses followed a comprehensive pipeline (parallel analysis and EFA, to establish the number of factors and item loadings; CFA and ESEM, to compare different factor structures). Additional psychometric analyses included internal consistency and test-retest analyses. Correlational analyses examined the associations between alexithymia, interoceptive attention and accuracy. Polynomial regression and two-lines testing investigated the quadratic association between IAS and BPQ.Results: Parallel-analysis indicated a one-factor solution for BPQ Body Awareness. For IAS and BPQ Autonomic Reactivity, bifactor ESEM models were retained. Ancillary measures revealed that both scales were mainly unidimensional and presented reliable total scores. All scales displayed excellent internal consistency, although test-rest reliability was modest. IAS and BPQ Body Awareness were moderately correlated and further displayed a quadratic U-shaped association. Alexithymia was negatively correlated with IAS and unassociated with BPQ Body Awareness.Conclusions: The European Portuguese IAS and BPQ displayed good psychometric properties and can thus be used within clinical and research settings. These questionnaires were differentially related to alexithymia, suggesting that interoceptive attention and accuracy may be dissociated using self-reports, although future research should further examine their linear vs. quadratic association.
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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 | 0.020 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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; 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".