Validation of the Japanese version of the Interoception Sensory Questionnaire (ISQ); part1
Bibliographic record
Abstract
The purpose of this study is to confirm the validation of the Japanese version of the Interoception Sensory Questionnaire (ISQ; Fiene et al., 2018) in adolescents and adults with autism spectrum disorder (ASD) participants. The ISQ is a self-report instrument developed to assess confusion about interoceptive bodily states in adolescents and adults with ASD (Fiene et al., 2018).. Scores on the ISQ are useful to investigate globally integrated sensory experience on interoception. Previous studies have shown that scores of ISQ is more appropriate to assess difficulties in interoception that people with ASD experience, compared to other subjective measures of interoception (e.g. the Body Perception Questionnaire-Body Awareness; BPQ-BA, Porges et al, 1993). Yet, no prior study has shown the validation of the ISQ in the Japanese sample. To address this, this study will attempt to validate the Japanese version of the ISQ by examining its psychometric properties. In this study, we will confirm score distribution, internal consistency, and factor structure of the ISQ in the Japanese sample. In addition, we will compare the scoress of ISQ between adolescents and adults with ASD participants and control participants. Furthermore, we also examine the relationships with some relevant individual traits; Toronto Alexithymia Scale (TAS-20; Bagby, Parker, et al., 1994; Bagby, Taylor, et al., 1994), Body Perception Questionnaire-Body Awareness (BPQ-BA; Porges et al, 1993) and multi-dimensional assessment of interoceptive awareness (MAIA; Mehling et al., 2012).
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".