Development of the Word Auditory Recognition and Recall Measure: A Working Memory Test for Use in Rehabilitative Audiology
Notice bibliographique
Résumé
OBJECTIVES: The purpose of this study was to develop the Word Auditory Recognition and Recall Measure (WARRM) and to conduct the inaugural evaluation of the performance of younger adults with normal hearing, older adults with normal to near-normal hearing, and older adults with pure-tone hearing loss on the WARRM. DESIGN: The WARRM is a new test designed for concurrently assessing word recognition and auditory working memory performance in adults who may have pure-tone hearing loss. The test consists of 100 monosyllabic words based on widely used speech-recognition test materials. The 100 words are presented in recall set sizes of 2, 3, 4, 5, and 6 items, with 5 trials in each set size. The WARRM yields a word-recognition score and a recall score. The WARRM was administered to all participants in three listener groups under two processing conditions in a mixed model (between-subjects, repeated measures) design. The between-subjects factor was group, with 48 younger listeners with normal audiometric thresholds (younger listeners with normal hearing [YNH]), 48 older listeners with normal thresholds through 3000 Hz (older listeners with normal hearing [ONH]), and 48 older listeners with sensorineural hearing loss (older listeners with hearing loss [OHL]). The within-subjects factor was WARRM processing condition (no additional task or with an alphabet judgment task). The associations between results on the WARRM test and results on a battery of other auditory and memory measures were examined. RESULTS: Word-recognition performance on the WARRM was not affected by processing condition or set size and was near ceiling for the YNH and ONH listeners (99 and 98%, respectively) with both groups performing significantly better than the OHL listeners (83%). The recall results were significantly better for the YNH, ONH, and OHL groups with no processing (93, 84, and 75%, respectively) than with the alphabet processing (86, 77, and 70%). In both processing conditions, recall was best for YNH, followed by ONH, and worst for OHL listeners. WARRM recall scores were significantly correlated with other memory measures. In addition, WARRM recall scores were correlated with results on the Words-In-Noise (WIN) test for the OHL listeners in the no processing condition and for ONH listeners in the alphabet processing condition. Differences in the WIN and recall scores of these groups are consistent with the interpretation that the OHL listeners found listening to be sufficiently demanding to affect recall even in the no processing condition, whereas the ONH group listeners did not find it so demanding until the additional alphabet processing task was added. CONCLUSIONS: These findings demonstrate the feasibility of incorporating an auditory memory test into a word-recognition test to obtain measures of both word recognition and working memory simultaneously. The correlation of WARRM recall with scores from other memory measures is evidence of construct validity. The observation of correlations between the WIN thresholds with each of the older groups and recall scores in certain processing conditions suggests that recall depends on listeners' word-recognition abilities in noise in combination with the processing demands of the task. The recall score provides additional information beyond the pure-tone audiogram and word-recognition scores that may help rehabilitative audiologists assess the listening abilities of patients with hearing loss.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».