(PP1611) Exploring the Role of Different Attention Domains in Understanding Speech-in-Noise

Hearing in noise is a challenging listening task. It demands a large cognitive load and engages various cognitive capacities such as working memory and attention. Numerous studies reported an association between cognition and speech recognition in noise (Billings et al., 2018; Anderson et al., 2013). However, the literature is relatively limited on examining how various attention domains may influence speech-in-noise performance. This current study investigates the relationship between speech-in-noise performance and the five attention domains – proposed by the hierarchical model of attention (Sohlberg & Mateer 1987). Specifically, this model categorizes attention into focused, sustained, selective, alternating, and divided attention.

 

Summary: 

Background: Speech understanding in noisy environments engages several cognitive abilities including attention – the specific cognitive interest of this study. Attention involves a complex system that includes “paying attention, concentrating, focusing, dealing with distraction, and effectively allocating attentional resources” (Sohlberg & Mateer, 2005). In particular, this study focuses on the hierarchical model of attention proposed by Sohlberg and Mateer (1987), which divides attention into five domains (or modes): focused, sustained, selective, alternating, and divided attention.

Objective: The purpose of this study is to evaluate the relative contribution of the different attention domains to listening in noise. Specifically, this study aims to examine the relationship between the five attention domains and speech-in-noise performance in both auditory-only (AO) and audiovisual (AV) modalities.

Participants: Ten normal-hearing young adults (18-25 years) and ten normal-hearing older adults (45-65 years) participated in this study. Participants completed a case history, an audiometric evaluation, a cognitive screen (Mini Mental State Exam ‘MMSE’), and a vision screen using Snellen chart. All participants had normal hearing (i.e. pure-tone thresholds ≤ 25 dB HL for the octave frequencies 0.25 – 8 kHz in both ears), and normal visual acuity (or normal corrected visual acuity) (i.e. Snellen acuity of 20/20), and passed the MMSE. 

Procedures: This study included the following three behavioral measures. The Multimodal Lexical Sentence Test for Adults (MLST-A) (Kirk et al., 2012) was used to evaluate speech-in-noise performance in AO and AV modalities. Two lists of 12 sentences were presented at a fixed 0 dB signal-to-noise ratio for each of the AO and AV conditions. The Attention Processing Training Test (APT) (Sohlberg & Mateer, 2005) was used to assess the five attention domains and is comprised of five subtests, each designed to measure a specific attention domain (I-IV). The subtests are as follows: sustained attention (I), complex sustained attention (II), selective attention (III), divided attention (IV), and alternating attention (V). The APT-Test material was presented bilaterally at 60 dB HL via insert earphones. The Comprehensive Trail-Making Test, Second Edition (CTMT2) (Reynolds, 2019) was used to assess participants’ inhibitory control and cognitive flexibility which are heavily influenced by attention.

Additionally, questionnaires that measure self-perceived attention (i.e. Everyday Life Attention Scale ‘ELAS’) and self-perceived hearing ability (i.e. The Speech, Spatial, and Quality of Hearing Scale ‘SSQ’) were also included.

Anticipated Findings: Data collection is currently ongoing. Once complete, statistical analyses will be performed on all of the test variables for each of the subject groups (e.g. percent correct of MLST-A key words for both modalities, APT-Test scores, CTMT2 indices and the responses on the questionnaires).

Given the reported links between cognition and speech-in-noise performance, we expect that attention metrics will correlate with speech-in-noise scores. We anticipate that selective attention will show the strongest links. We also hypothesize that speech-in-noise performance will be generally constrained by poor attentional skills, especially for the challenging AO modality.

Clinical Relevance: Anticipated findings may encourage the use of attention-specific tests in audiological assessments alongside other global cognitive screeners (e.g. the Mini-Cog Test, and the Montreal Cognitive Screening Assessment).