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|Year : 2014
: 16 | Issue : 69 | Page
|Cognitive skills and the effect of noise on perceived effort in employees with aided hearing impairment and normal hearing
Håkan Hua1, Magnus Emilsson1, Rachel Ellis1, Stephen Widén2, Claes Möller3, Björn Lyxell1
1 Linnaeus Centre HEAD, Swedish Institute for Disability Research; Department of Behavioural Sciences and Learning, Linköping University, Sweden
2 Linnaeus Centre HEAD, Swedish Institute for Disability Research, Linköping University; School of Health and Medical Sciences and Örebro University, Örebro, Sweden
3 Linnaeus Centre HEAD, Swedish Institute for Disability Research, Linköping University; School of Health and Medical Sciences and Örebro University; Audiological Research Centre, Örebro University Hospital, Örebro, Sweden
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|Date of Web Publication||7-May-2014|
The aim of the following study was to examine the relationship between working memory capacity (WMC), executive functions (EFs) and perceived effort (PE) after completing a work-related task in quiet and in noise in employees with aided hearing impairment (HI) and normal hearing. The study sample consisted of 20 hearing-impaired and 20 normally hearing participants. Measures of hearing ability, WMC and EFs were tested prior to performing a work-related task in quiet and in simulated traffic noise. PE of the work-related task was also measured. Analysis of variance was used to analyze within- and between-group differences in cognitive skills, performance on the work-related task and PE. The presence of noise yielded a significantly higher PE for both groups. However, no significant group differences were observed in WMC, EFs, PE and performance in the work-related task. Interestingly, significant negative correlations were only found between PE in the noise condition and the ability to update information for both groups. In summary, noise generates a significantly higher PE and brings explicit processing capacity into play, irrespective of hearing. This suggest that increased PE involves other factors such as type of task that is to be performed, performance in the cognitive skill required solving the task at hand and whether noise is present. We therefore suggest that special consideration in hearing care should be made to the individual's prerequisites on these factors in the labor market.
Keywords: Adverse conditions, cognitive skills, hearing impairment, labor market, normal hearing, perceived effort
|How to cite this article:|
Hua H, Emilsson M, Ellis R, Widén S, Möller C, Lyxell B. Cognitive skills and the effect of noise on perceived effort in employees with aided hearing impairment and normal hearing. Noise Health 2014;16:79-88
|How to cite this URL:|
Hua H, Emilsson M, Ellis R, Widén S, Möller C, Lyxell B. Cognitive skills and the effect of noise on perceived effort in employees with aided hearing impairment and normal hearing. Noise Health [serial online] 2014 [cited 2020 Jul 5];16:79-88. Available from: http://www.noiseandhealth.org/text.asp?2014/16/69/79/132085
| Introduction|| |
Statistics Sweden  reports that people with hearing impairment (HI) have an unfavorable position at the labor market. This group report bad health more frequently and estimate their own health to be worse than peers in their age group. Increased unemployment, early health-related retirement and sick leave are also more common for people with HI compared to the population at large. Research has confirmed these disadvantages in the labor market ,,, and Danermark and Gellerstedt  demonstrated that neck problems are most frequently reported by employees with HI. Furthermore, previous studies have shown that listening and participating in noisy sound environments is more cognitively demanding for people with HI ,,, and one could speculate that physical tension might originate from these situations as more cognitive effort is required from this population.
Working memory refers to a system that processes and stores information over a period of time. When working with complex cognitive tasks, working memory capacity (WMC) is often of crucial importance because it determines the resources available to the individual to process the information necessary for the task at hand and to temporarily store and handle the needed information.  Studies have confirmed that performance declines if a task is performed in competing background noise. , Baddeley's  multi-component model includes a central control called the central executive, which is considered to be responsible for the control and regulation of cognitive processes called executive functions (EFs). Executive functioning refers to inhibition of unwanted responses, updating with new incoming information and shifting between different sources of information. It has been demonstrated that it is possible to distinguish between the different subcomponents of EF according their relative contribution to performance in different cognitive tasks. ,
Moreover, studies have shown that perceived effort (PE) increases in challenging listening conditions and that noise affect working memory (WM) in different ways. ,,, For example, Larsby et al.  have examined how different speech noises interfere with cognitive processing in individuals with HI and normal hearing. Four study groups were included in the study and the sample consisted of both young/elderly with normal hearing and young/elderly with HI. Cognitive speech understanding tests (presented either as text, auditory or visual-auditory) and PE were administered and rated, respectively, in four background conditions: Quiet and three types of speech or speech-like noise. The results demonstrated that the presence of noise compared with quiet clearly had a negative effect on accuracy, speed of performance in the speech processing tasks and PE for the group with HI compared to the group with normal hearing.
In another study by Jahncke et al.,  cognitive, emotional and physiological effects of two open-plan office noises (low and high noise levels at 39 dBA and 51 dBA) were examined during work in a simulated open-plan office. The study sample comprised of 47 participants with normal hearing. In each session, the participants were instructed to work for 2 h on tasks involving basic WM processes. Physiological measures of stress (cortisol and catecholamine) and self-reported ratings of fatigue and mood were also obtained. The results showed that short-term exposure to the high level noise negatively affected WM performance, tiredness and motivation to a greater extent than the low level noise and reduction of noise level can reduce the negative effects of background noise. However, there was no effect of noise on the physiological measures. The authors concluded that the effect of short-term noise exposure on cognitive performance might not be mediated by change in physiology. In a follow-up study, the same procedure and tasks were used to test participants with aided HI.  The results showed that participants with HI were more affected by high noise than participants with normal hearing. Participants with HI reported higher levels of fatigue and tended to have a higher stress hormone levels in the high noise level. The authors concluded that the impact of noise varied with the hearing characteristics of the study participants.
Taken together, studies indicate that it might be important to examine the effects of background noise and hearing loss on measures reflecting the effort required during the performance of different cognitive tasks. To date, only a few studies have investigated cognitive abilities and PE in noise in employees with HI. Therefore, the aim of the present study was to examine the possible relationship between WMC, EFs and PE after completing a work-related task in quiet and in traffic noise in employees with aided HI and normal hearing.
| Methods|| |
Data were collected in 2010-2012 and is a part of a larger study about working life and hearing loss and participants in this study are the same individuals reported in Hua et al.  Forty participants (21 men and 19 women) with a mean age of 44.3 years old (18-64 years old) were recruited to take part in the study. The study sample consisted of both hearing-impaired (n = 20) and normally hearing (n = 20) participants. All participants were either students, part-time or full-time employees in Örebro County, Sweden. The hearing-impaired participants were recruited from the Department of Audiology, Örebro University Hospital. They were selected based on the following criteria: 18-65 years old, mild to moderate binaural sensorineural hearing loss, undergone aural rehabilitation and frequent hearing aid (HA) users with at least 3 months HA experience. Exclusion criteria were: Retirement, long-term sick leave, moderate-severe tinnitus, hyperacusis, psychiatric illnesses, dyslexia and/or other diseases/disabilities. Air and bone conduction thresholds were measured using standard audiological procedures in a sound-treated booth. Pure tone averages (PTA) were calculated for the 0.5, 1, 2 and 4 kHz for each ear. [Table 1] gives the demographic information of the participants. The two study groups were matched according to age and education level and did not differ significantly on these two variables (P > 0.05).
In order to control for background factors a demographic questionnaire was used. This questionnaire included questions regarding the respondents' age, sex, education, profession, employment status and working tasks. The participants were also instructed to identify all types of disabilities (including physical, psychological and sensory) and medication that they were currently using. If they had HI they were instructed to answer questions regarding etiology, duration of hearing loss, HA experience, uni- or bi-lateral fitting and current HA model.
All tasks were administered through a computer and the instructions were presented in written form and complemented with oral instructions by the test leader. Three of the cognitive tests, lexical decision-making, rhyme-judgment and reading span, are part of a cognitive test battery. The test battery has previously been described in detail in Rönnberg et al.  and the tests included in the test-battery are all well-established in the literature of cognitive psychology. ,,,, A condensed description follows below:
Lexical decision-making: The lexical decision-making test was used as a measure of lexical access. The task was to decide whether a combination of three letters constituted a real word or not. Six items were initially presented for practice and after that 40 items in total were presented and used for scoring. Half of the items were real words and they were all familiar Swedish three-letter words.
Rhyme-judgment: A rhyme-judgment test was used as a measure of phonologic ability. The task was to decide whether two simultaneously presented words rhymed or not. Words were presented lexically on the computer screen. Four items were used for practice and after that 32 items were presented and used for scoring of the measurement. The outcome measures of the lexical decision-making and rhyme-judgment were the proportion of correct responses.
Reading span: The reading span test was used as a measure of WMC. The test used in the current study was a short version of the reading span test created by Rönnberg et al.  based on the original test created by Daneman and Carpenter.  The task was to read 24 sentences and to decide whether the sentences were absurd or not and after reading sets of three, four or five sentences, to recall either the first or the final words of the sentences in correct serial order. The sets were always presented in the ascending order and the participants were cued to recall the first/last words post-stimulus presentation. The outcome measure was the proportion of correctly recalled items.
The keep track task: The keep track task, adapted from Miyake et al.,  was used as a measure of updating of information. Each trial began with the presentation of four target categories at the top of the computer screen. After this, 15 (mono- or disyllabic) words including 1-4 exemplars from each of six possible categories (countries, colors, metals, fruits, relatives and animals) were presented one at a time. Words were presented for 3000 ms with an interstimulus interval of 500 ms. At the end of each trial, the participants were asked to type in (in a dialogue box appearing on the screen) the last item from each of the four target categories. The target categories remained on the screen during the whole of each trial. Each trial required three updates for one of the categories (for example, four exemplars of this category were presented) and two, one and no update for the remaining three categories, respectively. By the presentation of the seventh word in each trial, at least one exemplar of each of the four target categories had been presented (i.e., during the presentation of words 8-15, the participants were required to hold four items active in working memory). Two practice trials were followed by six main trials. The outcome measure was the proportion of correctly recalled items.
The sustained attention to response test (SART): SART was used as a measure of inhibition.  One digit at a time was presented at the center of the computer screen. The task was to press the space bar as fast as possible when a digit was detected. However, if the digit was "3", the participants were to withhold their response and await the next stimuli. Each digit remained on the screen until a response had been given or until 1000 ms had passed. Trials were separated by an interstimulus interval of 500 ms. Of the 120 presented digits, 21 were the digit "3". The outcome measure was the number of failures to withhold a response.
The number-letter task: The number-letter task, adapted from Miyake et al.,  was used as a measure of shifting ability. In this task, pairs consisting of one digit and one letter (for example: 7G) were presented in one of the four corners of the computer screen. The pairs were presented one at a time and in a clockwise manner. The task was to decide whether the digit was odd or even when a pair was presented in the upper half of the screen and whether the letter was a lower case or upper case when a pair was presented in the lower half of the screen. The participants responded by pressing one of four buttons marked with the words "odd", "even", "lower" and "upper". Stimuli remained on the screen until a response had been given or until 10 s had passed. Twelve practice trials were followed by 38 main trials. Scoring was based upon the difference in reaction time between two consecutive trials:
- When the present trial was a shift trial and the preceding trial was a no-shift trial and
- when the present trial was a no-shift trial and the preceding trial was a shift trial. The outcome variable reported to as "shifting" was thus the mean difference between trials 1 and 2.
Work-related task and rating of PE
An information extraction task was used as a work-related task. In this task, tables of 15 numbered items belonging to a semantic category (for example fruits) and both categorical (for example place of origin) and continuous (for example price) information about the items were presented on a computer screen. In each trial, the participants were asked to identify one target item based on a question presented below the table. The participants responded by typing the number (1-15) corresponding to the target item in a box appearing at the bottom of the screen. The tables remained on the screen until a response had been given, or until 60 s had passed. The level of difficulty was manipulated by using one constraint in the easy condition ("Which fruit has the highest price per kilogram?") and three constraints in the difficult condition ("Which Portuguese fruit of which at least 14,000 kg has been sold has the highest price per kilogram?"). There were 16 easy and 16 difficult trials in total and proportions of correct responses were used as outcome measures of performance.
After the extraction of information task was completed, the participants were immediately asked to rate how effortful they found the task to be using the Borg CR-10 scale on the computer.  This scale is a combination of ratio and category scaling where verbal expressions and numbers are used congruently on a scale ranging from 0 (none at all) to 10 (extremely great). The scale was given on a sheet of paper next to the computer to help the participants with ratings and the participants had to type in the number corresponding to the degree of effort perceived in the work-related task. One question was asked for each level of difficulty of the working task. The Borg CR-10 scale was used as a measure of PE because this measure has shown to be sensitive enough to identify differences between different background conditions in a previous study where it has been used (c.f., Larsby et al.  ).
The noise used in the experiment was recorded at a crossroads in Örebro during morning traffic using a microphone employing the Ambisonics surround sound technique.  From the original recording, 19.6 min of traffic noise was extracted, edited and reproduced in an anechoic chamber (5.5 m × 5.5 m × 4.5 m). Six loudspeakers were used to reproduce the noise and they were placed in the circle around the participants (sitting in the middle of the room with a computer performing the work-related task) with a spread of 60° between each speaker. To ensure a realistic noise level, the sound was reproduced with an equivalent A-weighted sound pressure level of 73 dBA, matching the level of the original recording location. In order to avoid dynamic variation of the noise level, quiet parts of the recording file were removed so that a consistent traffic noise was played in every test trial. The final output of the noise was also looped and hence that it could be played continuously until the work-related task was completed by each participant. [Figure 1] shows the experimental set up in the anechoic chamber.
|Figure 1: The experimental set-up. The participants were seated in the middle of an anechoic chamber with a computer and there were six loudspeakers surrounding them in a circle. The loudspeakers reproduced the traffic noise at 73 dBA and had a spread of 60° between them|
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Data collection occurred on two separate sessions. Sessions were completed within 4 weeks of each other. At the first appointment, the demographic questionnaire, auditory and cognitive tests were administrated. As the data is part of a larger project, several other work-related tasks were included in the project in a counterbalanced order meaning that the extraction of information task could be performed either in the first or second session. The task was always performed in quiet or in noise in the anechoic chamber and the group with HI always wore their HAs during this task.
The SPSS software was used for statistical analysis. A Kolmogorov-Smirnov test for normality was first conducted to ensure a normal distribution and the results of the test showed that the variables were non-significant (P > 0.05). Initially, a one-way analysis of variance (ANOVA) was performed on the results of all the cognitive tasks between the two groups (normally hearing vs. hearing impaired). The reason for this was to check whether both study groups went into the quiet and noise conditions on similar cognitive level when performing the work-related task. Secondly, Pearson's correlation coefficients between each of the cognitive scores and demographic variables were calculated for the total sample. Thirdly, to analyze for within-group and between-groups differences in performance on the work-related task and PE, two-way ANOVA with repeated measures was performed. This was followed with Bonferroni-adjusted post-hoc pairwise comparisons. Finally, Pearson's correlation coefficients were used to examine the possible relationship between cognitive abilities and PE after completing the work-related task in quiet and in noise. All tests were two tailed and conducted at a 5% significance level.
Participants received vouchers for cinema tickets or flowers for taking part in the study. The study was approved by the Regional Ethics Committee in Uppsala (Dnr: 2010/072).
| Results|| |
In the first part, we will report the test results of the cognitive measurements between the two study groups. In the second part, the correlational analyzes between the cognitive tasks and the demographic variables are described. In the third part, we examined the performance of the work-related task and PE after completing the task in quiet and in noise, between and within-group. Finally, correlational analyzes between the cognitive tasks and PE in the two conditions are reported.
Cognitive performance between groups
[Table 2] shows the performance of the cognitive tests for each group. As can be seen, both groups scored relatively high in recall and accuracy. A one-way ANOVA conducted on the mean scores showed no significant differences (P > 0.05) between the groups, indicating that both groups performed similarly on the cognitive tasks.
|Table 2: Mean performance and SDs of the cognitive tasks for the normally hearing group and the hearing-impaired group|
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Correlations between cognitive tasks and demographic variables
A series of Pearson product-moment correlation coefficients were computed to assess the relationship between the background demographic variables and performance on the cognitive tasks [Table 3]. The strongest correlation was found between education and rhyme-judgment accuracy (r = 0.63, P < 0.001). WMC correlated negatively with age (r = −0.34, P = 0.04) and positively with education (r = 0.37, P = 0.02). A positive correlation also emerged between updating and education (r = 0.44, P = 0.005). This means that decreased cognitive performance was observed with increasing age and increased performance was related to higher education.
|Table 3: Pearson correlation coefficients between demographic variables and cognitive skills in the total group of participants (n = 40)|
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Performance in the work-related task and PE
[Figure 2] shows the mean performance on the work-related task for both groups in quiet and in noise. Both groups scored relatively highly in the easy tasks in quiet, 90% (SD = 0.1) for the group with HI and 92% (SD = 0.1) for the group with normal hearing. A similar level of performance was seen in the noise condition, where the hearing-impaired group scored 89% (SD = 0.1) and the normally hearing group 91% (SD = 0.1) in the easy task. In the difficult task, the groups differed in performance. The group with HI scored 67% (SD = 0.2) and 68% (SD = 0.2) and the group with normal hearing scored 80% (SD = 0.2) and 82% (SD = 0.1) in the quiet and the noise condition, respectively. A two-way repeated measures ANOVA revealed a statistical significant main effect of condition (F(3, 114) = 27.0, P = 0.001, ηp2 = 0.4) and between-group effect (F(1, 38) = 5.5, P = 0.02, ηp2 = 0.13). However, no significant interaction effect between condition and the group was observed (F(3, 114) = 3.3, P = 0.23). Post-hoc analysis showed that both groups performed significantly lower in the difficult task (P < 0.05) compared with the easy task in both conditions, meaning that task difficulty and not the presence of noise, affected their performance.
|Figure 2: Mean performance in the work-related task in quiet and in traffic noise for each group (error bars denote the 95% confidence interval)|
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[Figure 3] shows the mean PE scores for both groups in the quiet and the noise conditions. A higher rating indicates higher PE. The normally hearing group reported a mean PE score of 2.1 points (SD = 1.3) and 4.1 points (SD = 1.5) for the easy and difficult task in quiet, respectively, whereas the group with HI showed a mean score of 2.7 points (SD = 1.4) for the easy and 4.1 (SD = 1.3) points for the difficult task. In noise, the group with normal hearing reported a mean score of 2.7 points (SD = 1.3) for easy and 5.0 points (SD = 1.8) for the difficult task and group with HI reported 3.5 points (SD = 1.5) for the easy and 5.3 points (SD = 1.5) for the difficult task. A two-way repeated measures ANOVA revealed a statistical significant main effect of condition (F(3, 114) = 65.4, P = 0.001, ηp2 = 0.6). No significant main effect between groups (F(1, 38) = 1.3, P = 0.27) and interaction effect between condition and group (F(3, 114) = 1.4, P = 0.25) were observed, meaning that no significant differences in PE were observed between groups in all conditions. Post-hoc analysis revealed however, that both groups reported a statistical significantly higher PE (P < 0.001) when noise was present when compared with the quiet condition and this effect was observed for both the easy and difficult task. These findings demonstrate that the presence of noise generated a significantly higher PE for both groups, regardless of task difficulty.
|Figure 3: Means scores of perceived effort in quiet and in traffic noise for each group (error bars denote the 95% confidence interval)|
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Correlations between cognitive tasks, performance in the work-related task and PE
A series of Pearson product-moment correlation coefficient tests were used to analyze the relationship between performance on each of the cognitive tasks and PE in quiet and in noise after performing the work-related task for each group [Table 4]. In general, no significant correlations were found between the cognitive tasks and PE in quiet and in noise. Only updating was found to correlate significantly with PE in noise for both groups, with PE being negatively correlated with the easy task (r = −0.55, P = 0.02) for the group with normal hearing and with the difficult task (r = −0.46, P = 0.04) for the group with HI [Figure 4]. That is, the updating skill of both groups was significantly correlated with PE in noise, where lower performance in the updating task generated a higher PE. Interestingly, a difference between groups emerged where the updating skill was only correlated in the easy task for people with normal hearing and in the difficult task for people with HI. Nonetheless, it is important to point out that PE in noise was trending toward statistical significant correlation with updating for the group with HI (r = −0.44, P = 0.057) in the easy task as well.
|Figure 4: Scatter plots showing the significant relationship between the keep track task performance and perceived effort in noise for both groups|
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|Table 4: Pearson correlation coefficients between cognitive skills and perceived effort in the different conditions for both groups|
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In order to rule out the possibility that the participants rated their performance instead of PE, an additional correlation analysis was performed between the performance of the work-related task and PE for both groups. The analysis showed no significant correlations between performance and rated PE in the group with HI in quiet (easy: r = −0.18, P = 0.46; difficult: r = −0.18, P = 0.45) and noise (easy: r = 0.07, P = 0.76; difficult: r = −0.25, P = 0.29). Likewise, no significant correlations were observed in the group with normal hearing in the quiet (easy: r = −0.13, P = 0.60; difficult: r = −0.12, P = 0.62) and noise (easy: r = −0.10, P = 0.68; difficult: r = −0.20, P = 0.41) condition.
| Discussion|| |
The present results show that both groups performed at a similar cognitive level and this finding was expected since there was no indication to as why both groups were to differ on cognitive performance (c.f., Hällgren et al.  ). Significant correlations between some of the demographic variables and cognitive tasks emerged in line with previous research. That is, decreasing cognitive performance (WMC) with increasing age, ,, and increased performance (WMC, rhyme-judgment and updating) with higher education.  No significant group differences were found when comparing PE in quiet and in noise in the easy and difficult task, meaning that both groups rated PE similarly in both conditions, although there was a tendency for listeners with HI to rate PE slightly higher in the easy conditions. When analyzing for within-group differences, significant differences emerged between the quiet and the noise condition for each level of difficulty of the task, meaning that the presence of noise yielded a significantly higher PE for both groups, regardless of task difficulty. Performance in the work-related task further showed that the noise did not affect performance for both groups. Interestingly, significant correlations were found between PE in noise and updating ability, but not in quiet, where the ability to update information and PE in noise was significantly correlated with the easy task for the group with normal hearing and difficult task for the group with HI.
PE in quiet and in noise
The current results demonstrate no statistical significant differences between groups in PE in quiet and in noise. Previous studies have shown, however, that people with HI usually do report a higher PE than normally hearing controls. ,, There are a number of possible explanations for the difference between our results and previous studies. Firstly, the exclusion criteria in the present study had a wide range of conditions that had to be fulfilled (early retirement, sick leave and other diseases/disabilities) for participation in the study and this resulted in two relatively healthy groups with the main difference being the mild-moderate HI. Secondly, the present study recruited relatively young employees that were group matched on age and education and the group with HI had already undergone aural rehabilitation with at least 3 months of HA experience and this might have contributed to the similar ratings in PE. This finding clearly demonstrates that employees with aided HI with no other diseases/disabilites perceive the task to be as effortful to perform as their normally hearing peers, irrespective of hearing and task difficulty. Noise does generate a higher PE for both groups, but here we can extend this finding showing that young and healthy employees with mild-moderate HI using HAs report a similar PE in noise and in quiet as their normally hearing peers.
Performance in the work-related task
No statistical significant differences between groups were observed in performance in the work-related task regardless of task difficulty and whether noise was present. This was somewhat expected as both groups performed on a similar cognitive level, rated effort equally in all conditions and that cognitive performance showed statistical significant correlations with some of the demographic variables according to our expectations. However, it should be noted that there was a larger difference between the groups in the difficult task, where employees with HI scored, although not statistical significant, slightly lower in quiet and in noise. One reason for this larger difference between-group might be due to the updating ability as the performance of the keep track task [Table 2] was trending toward statistical significant difference (P = 0.06) and that the extraction of information task was highly dependent on one's ability to update new information. The additional correlation analysis between PE and performance of the work-related task further showed that these two outcome variables were dissociated, meaning that a larger difference in performance does not necessarily generate a significantly higher PE. Moreover, the trending difference in performance in the difficult work-related task could also be due to differences in performance in other cognitive skills that were not examined with the cognitive test battery used in the present study. Future research focusing on additional cognitive skills and their contribution to performance in different working tasks would be of interest.
Correlations between PE in noise and updating
Statistical significant negative correlations were found, but not in quiet, between updating ability and PE of the work-related task in noise for both groups. This demonstrates that with lower ability to update new information, a higher PE in noise is generated regardless of hearing ability. Previous studies have shown that in challenging situations, such as in noise, people with HI have to rely more on cognitive skills. , Further, both objective and subjective measures indicate that background noise forces hearing-impaired individuals to exert more effort in different listening tasks. ,, However, it is important to remember that the current study employed a non-auditory extraction of information task and it is not apparent whether the detrimental effects from background noise also applies to visual tasks for people with HI. The current findings suggest that there is a correlation between PE and cognitive skills in noise in both employees with HI and with normal hearing, even when the task is visual.
Interestingly, the current results showed that updating skill was only negatively correlated with the PE in the easy task for people with normal hearing. By itself, one might think that a more difficult work-related task would generate a higher PE for the group with normal hearing. This might not be the case according to Lavie's  perceptual load theory. This theory postulates that distractor perception can be prevented when processing of task-relevant stimuli involves high perceptual load. In other words, when high perceptual load engages full capacity in relevant processing this would leave no spare capacity for perception of the noise. Conversely, in situations of low perceptual load, any capacity not taken up in perception of task-relevant stimuli would involuntarily "spill over" to the perception of task-relevant distractors. This means that the easy task left more room for processing of noise and based upon the assumption that explicit processing capacity are brought into play in noise, updating skills were therefore involved in the easy task instead of the difficult task that yielded a higher perceptual load. These predictions have previously been tested in a series of experiments that assessed the effect of varying perceptual load in task-relevant processing. , If this theory were to apply to employees with aided HI, a significant correlation should have emerged between PE in the easy task in noise and updating and not between the difficult task and updating observed in the current results. There might be some explanations as to why there was a group difference in this finding and why the perceptual load theory does not apply on employees with aided HI. From an audiological perspective, a HI may be advantageous when performing visual tasks in noise, as the noise is not as intelligible for the group with HI. Moreover, all participants in our study were frequent HA users and they always wore their HAs when performing the work-related task, which could have amplified the noise to a normal hearing level. However, Jahncke and Halin  have proposed that the HAs may still distort incoming signals which may lead to an even greater distraction for people with HI as more cognitive resources are required to process the input. The authors further propose that recruitment of the HI may also lead to the perception of sharp onsets of sound that capture attention away from focal tasks. Therefore, for participants with aided HI there could still be an additional demand of resisting attention capture that causes disruption or less efficient focal task processing when noise is present. If this argument was true, disruption of task processing should still have been observed between PE in the easy task in noise and updating, as the HAs were worn in both levels of difficulty. In the present study, a trending, but non-significant, correlation (r = −0.44, P = 0.057) was indeed observed in our results between the PE in the easy task in noise and updating for the group with HI. This means that participants with HI could still be distracted by the noise in the easy task due to HA and that explicit processing capacity could still be involved in noise for this group even when performing an easy task. The current statistical significant correlations should however be interpreted with caution as the strength of the correlation was relatively small when judged against the standard criteria proposed by Cohen.  Future studies replicating the present findings would therefore be of interest to conduct.
In addition, despite the multiple correlations, a Bonferroni correction was not applied as it was felt that the increase in the risk of a Type 2 error occurring outweighed the potential benefits of reducing the risk of a Type 1 error. Exact P values are provided in order to enable the reader to evaluate whether applying a correction for multiple comparisons would have affected the outcome of the analyzes. We argue that the statistical significant correlations between PE in noise and updating skill are valid because: The task is highly based upon updating skills and no other statistical significant correlations emerged with the different cognitive tasks and the involvement of updating was only observed in the noise conditions for both groups. In other words, regardless of hearing ability, the employees at work have to actively think about the task and devote cognitive resources to it during the presence of noise, even if the task is non-auditory, which involves executive processes. The presence of noise does not affect performance, further confirmed by the additional analysis where no significant correlations were observed between PE and performance of the task, but it affected both groups differently due to the aided HI. More specifically, it affects how and when explicit processing capacity is engaged to solve the task at hand and that a decreased performance relying on that specific process may lead to a greater PE for the individual in adverse conditions. Furthermore, our results are also in agreement with those Jahncke and Halin  reported regarding visual tasks for people with HI in noise. An effect of noise was observed in their study where high noise affected the hearing-impaired participants' recall of semantic information and subjective effort negatively, whereas statistical significant correlations between PE in noise and updating skills were observed in our study for employees with aided HI and normal hearing.
The current results are important because they demonstrate that a higher PE is generated by noise and that it affects both employees with normal hearing and with HI. Practical implication on where the present results are applicable could be working environments at inventories where a lot of traffic noises are constantly present and where the employees need to update themselves with new information (e.g., fill out forms, check invoices, read documents, etc.). In addition, previous research has shown that neck problems are most frequently reported by hearing-impaired men and women with a mild to moderate HI and this might be due to listening and participating in general challenging communication situations at work.  This study further demonstrates that the effects of noise are highly influenced by which task that is to be performed and that the chosen task relies on specific aspects of cognitive skills, especially when noise is present. We therefore suggest that special consideration should be made in hearing care and occupational health services to the individual's prerequisites in the labor market, such as hearing ability, cognitive skills and the sound environments where the working tasks are being performed. At this stage, little is still known about the interaction between cognitive processes, hearing and PE and more research is needed to unravel this complex area of research for employees in the labor market. Future studies comparing different work-related noises and working tasks would add valuable knowledge for both study populations.
| Conclusion|| |
The results from the present study demonstrate that the presence of noise generated a significantly higher PE for employees with HI and normal hearing compared to quiet and that noise brings explicit processing capacity into play irrespective of hearing. However, a group difference was observed on how and when explicit processing capacity is involved to solve the work-related task in adverse condition and this difference might be due to the aided HI. We therefore suggest that special consideration in hearing health care and occupational health services should be made to the individual's prerequisites on these factors in the labor market. Future studies focusing on different tasks and comparing different work-related noises would add valuable knowledge for this study population.
| Acknowledgments|| |
The authors would also like to thank Jonas Birkelöf, Arvid Björndal, Kristina Ingvall, Jennie Hjaldahl, Johannes Olsson and Tobias Åslund who carried out some of the tests and recorded the different sound environments. Thanks are also due to Gitte Keidser for providing valuable comments on the manuscript.
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Department of Behavioural Sciences, Linköping University, SE-581 83, Linköping
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]