The Emotional Communication in Hearing Questionnaire (EMO-CHeQ): Development and Evaluation
Bibliographic record
Abstract
OBJECTIVES: The objectives of this research were to develop and evaluate a self-report questionnaire (the Emotional Communication in Hearing Questionnaire or EMO-CHeQ) designed to assess experiences of hearing and handicap when listening to signals that contain vocal emotion information. DESIGN: Study 1 involved internet-based administration of a 42-item version of the EMO-CHeQ to 586 adult participants (243 with self-reported normal hearing [NH], 193 with self-reported hearing impairment but no reported use of hearing aids [HI], and 150 with self-reported hearing impairment and use of hearing aids [HA]). To better understand the factor structure of the EMO-CHeQ and eliminate redundant items, an exploratory factor analysis was conducted. Study 2 involved laboratory-based administration of a 16-item version of the EMO-CHeQ to 32 adult participants (12 normal hearing/near normal hearing (NH/nNH), 10 HI, and 10 HA). In addition, participants completed an emotion-identification task under audio and audiovisual conditions. RESULTS: In study 1, the exploratory factor analysis yielded an interpretable solution with four factors emerging that explained a total of 66.3% of the variance in performance the EMO-CHeQ. Item deletion resulted in construction of the 16-item EMO-CHeQ. In study 1, both the HI and HA group reported greater vocal emotion communication handicap on the EMO-CHeQ than on the NH group, but differences in handicap were not observed between the HI and HA group. In study 2, the same pattern of reported handicap was observed in individuals with audiometrically verified hearing as was found in study 1. On the emotion-identification task, no group differences in performance were observed in the audiovisual condition, but group differences were observed in the audio alone condition. Although the HI and HA group exhibited similar emotion-identification performance, both groups performed worse than the NH/nNH group, thus suggesting the presence of behavioral deficits that parallel self-reported vocal emotion communication handicap. The EMO-CHeQ was significantly and strongly (r = -0.64) correlated with performance on the emotion-identification task for listeners with hearing impairment. CONCLUSIONS: The results from both studies suggest that the EMO-CHeQ appears to be a reliable and ecologically valid measure to rapidly assess experiences of hearing and handicap when listening to signals that contain vocal emotion information.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".