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

Lina Homman; Henrik Danielsson; Jerker Rönnberg

doi:10.3389/fpsyg.2023.1015227

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

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

Authors

Lina Homman^{1

2}, Henrik Danielsson^{1

2}, Jerker Rönnberg^{1

2}

Affiliations

¹ Disability Research Division (FuSa), Department of Behavioural Sciences and Learning (IBL), Linköping University, Linköping, Sweden.
² Linnaeus Centre HEAD, The Swedish Institute for Disability Research, Linköping University, Linköping, Sweden.

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 via 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.

Keywords: ELU model; cognitive hearing science; mediation model; phonology; processing speed; working memory.