Convergent Validity and Test–Retest Reliability of the Swedish Version of the Empowerment Audiology Questionnaire
Bibliographic record
Abstract
Purpose: Hearing loss affects communication and participation. Empowerment initiatives support individuals to manage their condition and facilitate patient-centered care. The Empowerment Audiology Questionnaires (EmpAQ-15/5), recently translated and validated in Swedish (EmpAQ SWE), were evaluated for convergent validity, internal consistency, and test–retest reliability. This study evaluates the convergent validity, internal consistency, and test–retest reliability of EmpAQ SWE. Method: A total of 136 adults with hearing loss completed an online survey twice. The survey consisted of EmpAQ-SWE and five measures assessing hearing disability, everyday functioning, hearing aid benefit, and general disability. For analysis, Spearman's correlation coefficient and Cronbach's alpha were used. Results: There were significant correlations between the EmpAQ SWE and measures of hearing disability ( r = −.389), everyday functioning ( r = −.350), and hearing aid benefit ( r = .542 and r = −.326). There were no significant correlations between the EmpAQ and general disability. The test–retest results for the EmpAQ-SWE indicated strong reliability ( r = .760) and moderate internal consistency (α = .678). Conclusions: EmpAQ SWE demonstrated positive associations with everyday functioning and hearing aid benefit and negative associations with hearing disability. Although causality cannot be established, the findings support the convergent validity and reliability of EmpAQ SWE, underscoring its potential utility in clinical and research contexts.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".