Speech-in-Speech Listening on the LiSN-S Test by Older Adults With Good Audiograms Depends on Cognition and Hearing Acuity at High Frequencies
Notice bibliographique
Résumé
OBJECTIVES: The main objective was to investigate age-related differences on the listening in spatialized noise-sentences (LiSN-S) test in adults with normal audiometric thresholds in most of the speech range. A second objective was to examine the contributions of auditory, cognitive, and linguistic abilities to LiSN-S outcomes. DESIGN: The LiSN-S test was administered to participants in an older group (M(Age) = 72.0, SD = 4.3 years) and a younger group (M(Age) = 21.7, SD = 2.6 years) with N = 26 per group. All the participants had clinically normal audiometric thresholds at frequencies up to and including 3000 Hz. The LiSN-S test yields a speech reception threshold (SRT) in each of the four speech-in-speech listening conditions that differ in the availability of voice difference cues and/or spatial separation cues. Based on these four SRTs, the scores were calculated for the talker advantage, the spatial advantage, and the total advantage as a result of both the types of cues. Additionally, the participants completed four auditory temporal-processing tests, a cognitive screening test, a vocabulary test, and tests of linguistic closure for high- and low-context sentences. The contributions of these predictor variables and measures of pure-tone hearing acuity to LiSN-S outcomes were analyzed for both the groups using regression analyses. RESULTS: Younger listeners outperformed the older listeners on all four LiSN-S SRTs and all the three LiSN-S advantage measures. Age-related differences were larger for conditions involving the use of spatial cues. For the younger group, all LiSN-S SRTs were predicted by the measure of linguistic closure in low-context sentences; in addition, the SRT for the condition with voice difference cues but without spatial separation cues was predicted by vocabulary, and the SRT for the condition with both voice difference cues and spatial separation cues was predicted by temporal resolution at low frequencies. Vocabulary also contributed to the talker advantage in the younger group, whereas the spatial advantage was predicted by high-frequency pure-tone hearing acuity in the range 6,000 to 10,000 Hz (pure-tone average [PTA](HIGH)). For the older group, the LiSN-S SRT in the condition with neither voice difference cues nor spatial separation cues was predicted by age; their other three LiSN-S SRTs and all advantage measures were predicted by PTA(HIGH). In addition, for the older group, cognition predicted LiSN-S SRT outcomes in three of the four conditions. Measures of auditory temporal processing, linguistic abilities, or hearing acuity up to and including 4000 Hz did not predict LiSN-S outcomes in this group. CONCLUSIONS: LiSN-S outcomes were poorer for adults aged 65 years or older, even those with good audiograms, compared with younger adults and also compared with people up to the age of 60 years from a previous study. In the present study, regardless of the types of cues, auditory and cognitive interactions were reflected by the combined influences on LiSN-S outcomes of high-frequency hearing acuity and measures of linguistic and cognitive processing. The data also suggest a hierarchy in the deployment of processing resources, which would account for the observed shift from linguistic abilities in the younger group to general cognitive abilities in the older group.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».