As the introduction to this thesis stated, life does not happen at hearing threshold levels. Nor does it happen in a steady background noise of 65 dB SPL. Both the FDTT and FINSIMAT use a speech-shaped background noise of 65 dB SPL, which will effectively mask speech (Wagener and Kollmeier, 2005; Buss et al., 2019). Unlike real-life background noises from variable and changing sources, steady speech-shaped noise provides no
informational masking or opportunities for glimpsing for those with good enough hearing, cognition, and linguistic skills. More realistic sound environments are needed for speech perception tests in noise to better capture HI listeners’ everyday struggles and the small but significant benefits that well-fitted HAs or CIs, updated technology, and assistive listening devices can provide. Realistic, individualizable, virtual sound environments that can be combined with the test materials of the FMST, FINSIMAT, and FDTT are currently being developed at KUH.
Even though the FINSIMAT is in active use in multiple large clinics in Finland, we still lack age-specific normative reference values for school-age children. A large, age-stratified results database for HI children with
different degrees of HL would serve as a valuable reference for realistic rehabilitation expectations for clinicians and families. Slope estimates, test- retest values, and estimates of learning effects in repeated use would increase the reliability of the FINSIMAT.
Based on our clinical experience, we suspect that FINSIMAT provides more reliable SRT estimates than the FMST for some elderly listeners. The FMST’s adaptive procedure is long, and listening fatigue may lead to lapses in concentration towards the end of test run and produce, in turn,
unreliable results. However, shorter adaptive procedures (such as
FINSIMAT’s) may lead to unreliable results if the test track is too short and
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does not have time to stabilize to the range of the true SRT. We did not observe any signs of listening fatigue with the FMST in our elderly study population, but our participants had good cognition and only mild-to- moderate HL. Another evaluation study with older and more severely HI listeners and more data, i.e., slope estimates and learning effect data, would provide valuable information on the reliability of the FMST and FINSIMAT in this growing patient population. As DTTs are emerging in hearing rehabilitation monitoring, the same data should be obtained also for the FDTT and compared with that of FMST and FINSIMAT.
In the clinic the focus is often on speech perception, even though, in real life, speech is only one of the sounds we need to attend to and interpret.
Testing patients in a standard clinical setting, where the source of the sound and background are clearly defined, or at least limited to a certain number of options, completely ignores the auditory scene analysis that our brains perform all the time in our everyday surroundings. Auditory scene analysis refers to the process of constructing and constantly upkeeping a mental auditory image of our surroundings. Auditory scene analysis involves recognizing the quiet hum as the dishwasher in the kitchen, the muffled high-pitched squeals as the sounds coming from the neighbor’s children playing outside, and the swoosh and thud followed by a metal clank as your spouse returning home, opening the door, and leaving their keys on the table by the door. For a HI listener, auditory scene analysis is particularly demanding, since all its essential components (i.e., spectral and temporal resolution, sound localization) are impaired (Shinn-Cunningham and Best, 2008). In the complex listening situations of everyday life, the upkeep of a mental auditory image can take up some of the resources (i.e., working memory capacity, selective auditory attention) needed for speech perception (Shinn-Cunningham and Best, 2008; Shinn-Cunningham, Best and Lee, 2017) and lead to poorer speech perception than in a
standardized, restricted clinical test setting.
Effective everyday communication is more than just listening. Successful communication requires comprehension, processing, retrieving memories
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and experiences, synthesizing new concepts and ideas, coming up with arguments to contradict the ones being presented, and packaging and delivering one’s formulated responses as convincingly, wittily, or kindly as the occasion calls for. The more effort is needed for listening, the less there is left to spend for all the other areas of communication (Peelle, 2018;
Rönnberg, Holmer and Rudner, 2019, 2021). Listening effort is defined as
“the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a task, with listening effort applying more specifically when tasks involve listening” (Pichora-Fuller et al., 2016).
Listening effort is the price we pay for listening, and as important a measure of functional hearing as SRT, but still not routinely discussed when reporting rehabilitation outcomes. FDTT and FINSIMAT will provide data on listening performance, but we need to adopt other measures, such as pupillometry (Alhanbali et al., 2019; Lunner et al., 2020; McGarrigle, Rakusen and Mattys, 2021) or patient reported outcome measures (Allen, Hickson and Ferguson, 2022) for a comprehensive hearing evaluation.
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8 CONCLUSIONS
No speech test alone can capture or quantify the ubiquitous and complex effects of HL in everyday life. Whichever test is used, its characteristics, strengths, and shortcomings in different patient populations should be known to provide accurate speech perception assessments. This research has extended the speech audiometry test selection in Finnish and provided internationally unprecedented information on long-term reliability of speech perception testing in noise. Based on the results, the following conclusions can be drawn:
1. The Finnish digit triplet test provides reliable and internationally comparable results in normal hearing listeners.
2. The Finnish simplified matrix sentence test provides reliable results in normal hearing listeners and in elderly hearing-impaired listeners.
3. No significant long-term learning effects were detected for the Finnish digit triplet test, but improvements were detected between the first and second test lists during all test sessions. A statistically and clinically significant long-term learning effect was detected for the Finnish matrix sentence test, but the effect plateaued.
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