Construct Validity of the Sensory Profile Interoception Scale: Measuring Sensory Processing in Everyday Life
Bibliographic record
Abstract
Scholars and providers are coming to realize that one’s ability to notice and respond to internal body sensations (i.e., interoception) contributes to an overall sense of wellbeing. Research has demonstrated a relationship between interoceptive awareness and anxiety, for example. Currently, however, tools for evaluating one’s interoception lack the conceptual foundation and clarity necessary to identify everyday behaviors that specifically reflect interoceptive awareness. Unlike existing interoceptive measures, the Sensory Profile Interoception (SPI) scale is participation-based and grounded in Dunn’s Sensory Processing framework. In this study we investigated concurrent validity by correlating the SPI with the Adolescent/Adult Sensory Profile (A/ASP); we investigated construct validity by correlating the SPI with the Perth Alexithymia Scale (PAS), the Body Awareness Scale (BAS), and the State-Trait Anxiety Inventory (STAI). Using the REDCAP online platform, 74 college-aged participants completed the measures. Using Spearman rank order correlations there were statistically significant relationships between the corresponding sensory pattern subscales on SPI and A/ASP (r = 0.277 to r = 0.582). The PAS was only weakly related to the registration subscale of the SPI (r = 0.260). The BAS had significant relationships with seeking and avoiding on the SPI (r = 0.496 and r = 0.385). The STAI had significant relationships with sensitivity and registrations of the SPI (r = 0.266 and r = 0.361 for state; r = 0.403 and r = 0.321 for trait). Taken together, these findings provide evidence of construct validity of the SPI to identify participation patterns associated with both high and low interoception. With the more precise information the SPI provides, professionals can design tailored interventions to support everyday life goals and researchers can study interoception within authentic activities.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".