Measuring Misophonia: Assessing the Psychometric Properties of the MisoQuest and Its Ability to Predict Cognitive Impacts of Triggering Sounds
Bibliographic record
Abstract
OBJECTIVES: Misophonia is characterized by an aversion to specific sounds, such as chewing and breathing. These "trigger" sounds can elicit negative emotional reactions, physiological stress, and cognitive impairments in people with misophonia. Despite its impact, misophonia lacks formal diagnostic classification, largely due to challenges in conceptualization and assessment. One of the few psychometrically robust self-report measures for misophonia (the MisoQuest) was originally developed and evaluated in Polish. The current study evaluated the utility of the English language version of the MisoQuest, including assessment of its criterion validity using cognitive performance as an outcome. METHODS: A total of 139 participants (44 people with misophonia and 95 controls) completed the MisoQuest, the Selective Sound Sensitivity Syndrome Scale (S-Five), the Generalized Anxiety Disorders Scale, and the Sensory Hypersensitivity Scale. Participants then completed either a Stroop task or reading comprehension task in the presence/absence of triggering sounds. A subset of participants retook the MisoQuest after 5 weeks. RESULTS: The MisoQuest showed excellent internal consistency and strong test-retest reliability. Additionally, MisoQuest scores strongly correlated with S-Five scores, supporting convergent validity, and moderately correlated with measures of generalized anxiety and sensory hypersensitivity, indicating some overlap while supporting discriminant validity. Higher MisoQuest scores predicted poorer reading comprehension performance when trigger sounds were present, supporting criterion validity. However, MisoQuest scores showed no significant relationship with Stroop task performance. CONCLUSION: These findings support the MisoQuest as a reliable and useful measure of misophonia in English-speaking individuals and suggest its scores may relate to clinically relevant outcomes.
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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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".