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结构方程中介模型捕捉了语言理解模型参数之间的预测关系。

A structural equation mediation model captures the predictions amongst the parameters of the ease of language understanding model.

作者信息

Homman Lina, Danielsson Henrik, Rönnberg Jerker

机构信息

Disability Research Division (FuSa), Department of Behavioural Sciences and Learning (IBL), Linköping University, Linköping, Sweden.

Linnaeus Centre HEAD, The Swedish Institute for Disability Research, Linköping University, Linköping, Sweden.

出版信息

Front Psychol. 2023 Mar 3;14:1015227. doi: 10.3389/fpsyg.2023.1015227. eCollection 2023.

Abstract

OBJECTIVE

The aim of the present study was to assess the validity of the Ease of Language Understanding (ELU) model through a statistical assessment of the relationships among its main parameters: processing speed, phonology, working memory (WM), and dB Speech Noise Ratio (SNR) for a given Speech Recognition Threshold (SRT) in a sample of hearing aid users from the n200 database.

METHODS

Hearing aid users were assessed on several hearing and cognitive tests. Latent Structural Equation Models (SEMs) were applied to investigate the relationship between the main parameters of the ELU model while controlling for age and PTA. Several competing models were assessed.

RESULTS

Analyses indicated that a mediating SEM was the best fit for the data. The results showed that (i) phonology independently predicted speech recognition threshold in both easy and adverse listening conditions and (ii) WM was not predictive of dB SNR for a given SRT in the easier listening conditions (iii) processing speed was predictive of dB SNR for a given SRT mediated WM in the more adverse conditions.

CONCLUSION

The results were in line with the predictions of the ELU model: (i) phonology contributed to dB SNR for a given SRT in all listening conditions, (ii) WM is only invoked when listening conditions are adverse, (iii) better WM capacity aids the understanding of what has been said in adverse listening conditions, and finally (iv) the results highlight the importance and optimization of processing speed in conditions when listening conditions are adverse and WM is activated.

摘要

目的

本研究旨在通过对n200数据库中助听器使用者样本的给定言语识别阈值(SRT)下其主要参数(处理速度、语音学、工作记忆(WM)和dB语音噪声比(SNR))之间的关系进行统计评估,来评估语言理解简易度(ELU)模型的有效性。

方法

对助听器使用者进行了多项听力和认知测试。应用潜在结构方程模型(SEM)来研究ELU模型主要参数之间的关系,同时控制年龄和纯音平均听阈(PTA)。评估了几种竞争模型。

结果

分析表明,一个中介SEM最适合这些数据。结果显示:(i)语音学在轻松和不利的聆听条件下均能独立预测言语识别阈值;(ii)在较轻松的聆听条件下,对于给定的SRT,WM不能预测dB SNR;(iii)在更不利的条件下,处理速度通过介导WM来预测给定SRT下的dB SNR。

结论

结果与ELU模型的预测一致:(i)在所有聆听条件下,语音学对给定SRT的dB SNR有贡献;(ii)仅在聆听条件不利时才调用WM;(iii)更好的WM容量有助于在不利聆听条件下理解所讲内容;最后(iv)结果突出了在聆听条件不利且WM被激活时处理速度的重要性和优化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e2e/10020708/9f371faf7d9a/fpsyg-14-1015227-g001.jpg

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