Development of the North American Listening in Spatialized Noise‐Sentences Test (NA LiSN-S): Sentence Equivalence, Normative Data, and Test‐Retest Reliability Studies
Notice bibliographique
Résumé
BACKGROUND: The Listening in Spatialized Noise-Sentences test (LiSN-S) was originally developed in Australia to assess auditory stream segregation skills in children with suspected central auditory processing disorder (CAPD). The software produces a three-dimensional auditory environment under headphones. A simple repetition-response protocol is utilized to determine speech reception thresholds (SRTs) for sentences presented from 0 degrees azimuth in competing speech. The competing speech (looped children's stories) is manipulated with respect to its location (0 degrees vs. +90 degrees and -90 degrees azimuth) and the vocal quality of the speaker(s) (same as, or different to, the speaker of the target stimulus). Performance is measured as two SRT and three advantage measures. The advantage measures represent the benefit in dB gained when either talker, spatial, or both talker and spatial cues combined are incorporated in the maskers. PURPOSE: The objective of this research was to develop a version of the LiSN-S suitable for use in the United States and Canada. The original sentences and children's stories were reviewed for unfamiliar semantic items and rerecorded by native North American speakers. RESEARCH DESIGN: In a descriptive design, a sentence equivalence study was conducted to determine the relative intelligibility of the rerecorded sentences and adjust the amplitude of the sentences for equal intelligibility. Normative data and test-retest reliability data were then collected. STUDY SAMPLE: Twenty-four children with normal hearing aged 8 years, 3 months, to 10 years, 0 months, took part in the sentence equivalence study. Seventy-two normal-hearing children aged 6 years, 2 months, to 11 years, 10 months, took part in the normative data study. Thirty-six children returned between two and three months after the initial assessment for retesting. Participants were recruited from sites in Cincinnati, Dallas, and Calgary. RESULTS: The sentence equivalence study showed that post-adjustment, sentence intelligibility increased by 18.7 percent for each 1 dB increase in signal-to-noise ratio. Analysis of the normative data revealed no significant differences on any performance measure as a consequence of data collection site or gender. Inter- and intra-participant variation was minimal. A trend of improved performance as a function of increasing age was found across performance measures, and cutoff scores, calculated as two standard deviations below the mean, were adjusted for age. Test-retest differences were not significant on any measure of the North American (NA) LiSN-S (p ranging from .080 to .862). Mean test-retest differences on the various NA LiSN-S performance measures ranged from 0.1 dB to 0.6 dB. One-sided critical difference scores calculated from the retest data ranged from 3 to 3.9 dB. These scores, which take into account mean practice effects and day-to-day fluctuations in performance, can be used to determine whether a child has improved on the NA LiSN-S on retest. CONCLUSIONS: The NA LiSN-S is a potentially valuable tool for assessing auditory stream segregation skills in children. The availability of one-sided critical difference scores makes the NA LiSN-S useful for monitoring listening performance over time and determining the effects of maturation, compensation (such as an assistive listening device), or remediation.
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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 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,004 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».