A psychoacoustical approach to resolving office noise distraction

Nigel Oseland (Workplace Unlimited, Berkhamsted, UK)
Paige Hodsman (Department of Concept Development, Saint-Gobain Ecophon, Ramsdell, UK)

Journal of Corporate Real Estate

ISSN: 1463-001X

Publication date: 12 November 2018

Abstract

Purpose

The purpose of this paper is to determine whether noise is affected by psychological factors rather than simply by physical metrics. For example, personality type, age, perceived control and screening ability were explored, as well as the choice of primary workplace.

Design/methodology/approach

An online survey was conducted which resulted in 517 valid responses. The survey included the personality profiling along with questions related to noise and personal circumstances. The key noise metrics were perceived performance, ability to work, well-being and stress plus three noise indices: concentration, distraction and speech interference.

Findings

The survey revealed that personality type does affect noise perception, in particular extroversion and neuroticism. Perceived control, screening ability, age, workplace, design and focused work are also factors. Personal variables accounted for 25 per cent of the variance in the ability to carry out work, and for 40 per cent of the variance in concentration and speech interference.

Research limitations/implications

Whilst statistically significant differences were found for most of the psychological and personal variables, the size of effect was smaller than anticipated. This is likely because the survey was carried out across a range or workplaces, rather than in a laboratory, with a number of uncontrolled extraneous factors.

Practical implications

The research has resulted in the development of a design guidance document for controlling noise distractions based on more psychoacoustic, people-centred, principles than purely physical ones.

Originality value

Most acoustics research is conducted in the laboratory and focuses on the physical sound properties. This research took a psychoacoustic approach focusing more on psychological and personal factors, and was carried out in the real world.

Keywords

Citation

Oseland, N. and Hodsman, P. (2018), "A psychoacoustical approach to resolving office noise distraction", Journal of Corporate Real Estate, Vol. 20 No. 4, pp. 260-280. https://doi.org/10.1108/JCRE-08-2017-0021

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Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited


Introduction

Traditional approaches to resolving office noise

It is widely recognised that acoustics is an interdisciplinary science; however, many architectural acousticians have a physics or engineering background and their approach to mitigating noise is mostly, but not entirely, focused on physical solutions.

This paper presents a combined psychological and physiological approach to resolving noise distraction in the workplace and is based on a three-year programme, including a literature review, original research and development of a practical toolkit. The paper details a psychoacoustic, people-centred approach to noise, focusing on perception, attitudes, mood, personality and behaviour. It reflects an emphasis on psychophysical rather than purely physical acoustic parameters.

Acoustic issues in offices

We, the authors, have already published a detailed literature review (Oseland and Hodsman, 2017a). Our review draws on the studies from the fields of psychology, health, interior design and business management, as well as acoustics, and clearly highlights that noise is a major problem in the modern office. For example, we referred to Jensen et al. (2005) who conducted an extensive survey of 142 buildings, with 23,450 participants, and found that acoustics are the highest cause of dissatisfaction. Similarly, in their worldwide survey with circa 103,000 responses, Oldman and Rothe (2017) found noise to be the second biggest cause of dissatisfaction, after temperature control.

Furthermore, Abbot (2004) concludes that not only is noise a nuisance and disturbance in offices, but it is a primary cause of reduction in productivity and can contribute to stress and illness, which in turn can also contribute to absenteeism and turnover of staff. Oseland and Burton (2012) conducted a meta-analysis of 21 noise studies and reported that the impact of noise on office worker performance is 1.7 per cent. Whilst this figure appears low, it is estimated that a change in productivity of just 5 per cent may cover annual property operating costs (Oseland, 2017).

Our previous literature review also refers to Perham et al. (2007) who commented that “The acoustic design of offices often does not receive the attention that most other architectural systems would. However, unwanted levels of ambient noise […] can cause difficulties with communication as well as with concentration at work”. Similarly, Treasure (2010) concludes that “Despite huge advances in almost every area of architecture and interior design […] sound and acoustics, for the most part, have remained secondary concerns”. So, it appears that, despite noise remaining a significant problem in office environments and affecting worker satisfaction and productivity, the problem of poor acoustics is often ignored.

Measuring sound and noise

Acoustics is a complex subject, even measuring the sound level is not as simple as it may first appear and a major challenge is simply identifying what to measure. Common metrics used are sound pressure level, reverberation time and speech transmission, but there does not appear to be collective agreement on which parameters should be adhered to. This may explain why acoustic solutions are often under-valued or ignored altogether. Horowitz (2012) explains that, whilst frequency, amplitude and phase can be used to characterise and produce a pure sound, using them to describe a complex sound outside of the laboratory “is like asking a physicist to describe the motion of a herd of cows – the behaviour can be modelled as long as the cows are spherical and moving on a frictionless surface in a vacuum”.

Measuring sound is difficult enough, but a further complication is that noise is defined as “unwanted sound”, implying that it is humans, not physics, who actually determine whether a sound is a noise. Noise detection begins when sound pressure waves reach the eardrum and our physiology converts the pressure waves into a sound (perception); the brain then interprets the sound applying meaning to it (cognition) and then determines whether the sound is considered a noise.

Thus, determination of “unwanted sound” is totally subjective, and our reaction to noise is not simply related to perceived loudness – psychological and other personal factors play a key role. Based on our literature review, there appears to be four key non-physical factors relevant to offices that affect noise perception and performance:

  1. Task and work activity – the nature of the task in hand or work activity; whether it involves cognition or memory; the complexity of the task; whether it involves multi-tasking; and whether the task requires quiet (e.g. for concentration or sleep).

  2. Context and attitude – feelings towards those creating the noise; the perceived need for the noise; the meaning attached to the noise; and whether the noise source (e.g. conversation) is perceived as being useful.

  3. Perceived control and predictability – whether the noise source is intermittent or steady; whether it is predictable; and whether those exposed to the noise believe they can control it.

  4. Personality and mood – differences in those who are more noise sensitive, and in those who seek stimulation versus those that prefer solitude; and the effect of moods such as anger and anxiety.

Reported ratings of noise annoyance do correlate with sound level measurement, but it is generally accepted that the sound level only accounts for 25 per cent of the variance in annoyance. For example, Borsky (1969) suggests that sound level is only a minor factor in noise perception, accounting for less than one-quarter of the variance in ratings of noise annoyance. Job (1988) concurs, writing “Even with the full range of exposure covered and very accurate noise and reaction measurements, noise exposure may only account for 25-40 per cent of the variation in reaction”. Furthermore, Smith and Jones (1992) proposed that noise intensity only accounts for 25 per cent of variance in annoyance, whereas psychological factors account for 50 per cent, and they concluded that perceived control of noise is more important than the physical component.

Personality and acoustics

Psychologists propose that introverts and extroverts have different innate levels of arousal, which in turn affects how noise affects their performance, as explained by Oseland (2009):

[…] people can perform better if they are stimulated or motivated (which increases their level of arousal), but there is a limit, as too much stimulation can lead to stress and thus reduce performance […] individuals have a different base level of arousal and therefore need different magnitudes of stimulation for optimal performance […] extroverts have a low natural level of arousal and enjoy thrill-rides whereas introverts who have a higher level of arousal might find such rides distressing.

Sound is a stimulus, and so it follows that extroverts should perform, or cope, better than introverts in noisy environments. Much of the earlier research on the impact of noise on task performance, notably by Broadbent (1958), generated results in support of arousal theory.

Eysenck’s (1967) original super-traits model and the Eysenck Personality Inventory, measuring extraversion and neuroticism, underpin many of the current theories of personality. For example, the Big Five Inventory (BFI) includes Eysenck’s extroversion and neuroticism dimensions along with openness, conscientiousness and agreeableness (John et al., 1991; John and Srivastava, 1999). The BFI is often referred to as OCEAN:

  1. openness – refers to being open to new experiences and is a trait of those who are creative, curious, with broad interests, are imaginative and artistically sensitive;

  2. conscientiousness – relates to those who are more responsible, hard-working, organised, dependable, self-disciplined and persistent;

  3. extraversion – refers to those who are more sociable in nature and prefer keeping company; they are also more impulsive, gregarious, assertive, talkative and are thrill-seekers;

  4. agreeableness – is seen in those who are more cooperative, affectionate, good-natured, helpful, forgiving, caring and trusting; and

  5. neuroticism – refers to emotional instability, the tendency to experience negative emotions and to experience anxiety and apprehension.

Research has shown that, in noisy conditions, extroverts perform better than introverts at cognitive tasks (Morgenstern et al., 1974), comprehension tasks (Standing et al., 1990) and mental arithmetic (Belojevic et al., 2001). Furthermore, Campbell and Hawley (1982) demonstrated that, when studying in a library, introverts tended to choose a place to work away from the “buzz and bustle”, whereas extroverts were more attracted to the latter as their primary place of work.

More anxious (neurotic) personality types performed poorer when exposed to noise than those more emotionally stable in complex mental tasks (von Wright and Vauras, 1980) or learning prose (Nurmi and von Wright, 1983). Eysenck and Graydon (1989) also suggest that neurotic introverts are more adversely affected by noise than emotionally stable extroverts when carrying out work–life tasks. Matthews et al. (2004) propose that the performance of those with a more neurotic disposition is degraded because of a “reduced availability of attentional resources or working memory, due to diversion of attention to processing internal worries”. It seems that people emotionally unstable are overly concerned with the source of the unwanted sound and respond to it more negatively, resulting in stress.

Franklin et al. (2013) examined the relationship between acceptable noise level and personality. The analysis revealed a correlation between acceptable noise and openness or conscientious personality dimensions. They suggest that people who are more open to new experiences may accept more noise, while those who are of the more conscientious personality type, who generally desire fewer distractions when focusing on a task, accept less background noise. The impact of noise on the agreeableness personality scale is less well documented.

Other researchers have noted that some individuals are better able to cope with the excessive stimulation in the open-plan office. Mehrabian (1977) proposed that such individual differences in coping are due to an innate ability to “screen” out noise. He distinguishes between screeners, who effectively reduce over-stimulation by attending to information on a priority basis, and non-screeners who become over-stimulated. It is unclear whether screening is inherent, like personality, or a learned coping strategy.

Hypotheses for testing

Based on the above research, it appears that different office workers will react differently to the same acoustic conditions in their workplace. Therefore, actions to resolve noise distraction need to account for individual differences and not assume that a single physical acoustic solution will work for all the office occupants. A psychoacoustic approach to understanding noise distraction indicates that other, people-centred, solutions are required. Such solutions are more behavioural, educational, managerial and organisational rather than purely physical.

The literature review uncovered how factors, such as personality, impact the perception of noise and performance. The majority of evidence is based on laboratory studies or office simulations. Nevertheless, as mentioned earlier, noise in offices is a major cause of dissatisfaction and impeded performance. As a consequence, we developed several hypotheses for testing:

  • Extroverted offices workers can cope better with noisy environments, whereas introverts will perform better under quieter conditions.

  • Perceived control over noise in the office, ability to screen or learned coping mechanisms will help reduce the problem of poorer performance caused by noise distraction.

  • Occasional working from home reduces noise distraction and will improve performance.

An online survey was developed and conducted to test the above hypotheses. The primary objective of the survey was to test whether personality types, in particular extroversion and introversion, affect noise perception and distraction in the office.

Methodology

Survey questions

The core methodology was a new online survey developed to explore the relationship between noise distraction and key variables such as personality, work activities, primary workplace, acoustic design, ability to screen noise and demographics. The survey included approximately 100 questions distributed across seven sections/screens.

The first question included 44 sub-questions used to determine the respondents’ personality profile on the BFI developed by the University of California, Berkeley (John et al., 1991). As discussed, the BFI, also known as OCEAN, determines the strength of five personality factors: openness (O), conscientiousness (C), extroversion (E), agreeableness (A) and neuroticism (N).

The main noise questions or metrics (dependent variables) are as follows:

  1. Approximately how much is your performance at work increased or decreased by the noise levels in your primary workspace?

  2. How do the noise levels in your primary workspace affect your ability to carry out work?

  3. Do you believe that the noise levels in your primary workspace are affecting your …

    • […] well-being?

    • […] stress levels?

    • […] productivity?

  4. Over the last working week in your primary workspace, have you […]

    • […] had problems concentrating?C

    • […] found it difficult to make decisions?C

    • […] had memory lapses?C

    • […] found it difficult to think clearly?C

    • […] found it difficult to hear when colleagues talk to you?

    • […] found yourself listening in to nearby conversations?S

  5. Over the last working week in your primary workspace, to what extent have you been distracted by […]

    • ‘[…] nearby colleagues’ conversations and laughter?S

    • […] conversations taking place in other teams?S

    • […] talking and laughter in communal areas (breakout, kitchen)?S

    • […] conversations taking place outside of meeting rooms?S

    • […] nearby colleagues’ telephone calls?S

    • […] individuals with loud voices, on the phone or talking to their colleagues?S

    • […] people moving around the office?

    • […] brief sounds of ring tones, text signals, computers, etc.?

    • […] sounds from the ventilation system?E

    • […] traffic noise from outside the office?E

  6. Over the last working week, how often have you […]

    • […] been so distracted that you could not fully concentrate on the task in front of you?C

    • […] not been able to fully concentrate due to the noise levels in your primary workspace?C

    • […] been interrupted midway through completing an important task?D

    • […] had to leave the workspace to avoid distractions and finish off work tasks?D

    • […] missed a work deadline due to continuous distractions or noise?D

    • […] stayed late or come in early to avoid noise and distractions?D

  7. How good are you at screening out noise and distractions in your primary workspace?

The performance at work question (item 1 above) is based on that administered as part of the office environment survey (Wilson and Hedge, 1987) and uses a similar nine-point response scale, but ranging from 1 = “−20 per cent” to 5 = “0 per cent” to 9 = “+20 per cent”.

The ability to work question (item 2) was rated on a five-point scale where 1 =“makes work impossible” (poor), 2 = “makes work very difficult”, 3 = “makes work difficult”, 4 = “makes work slightly difficult” and 5 = “has no effect” (good).

In contrast, the well-being, stress and productivity questions (item 3) were rated using a scale of 1 = “definitely not” (good), 2 = not really”, 3 = a little, 4 = “mostly” and 5 = very much so” (poor). In hindsight, these questions could have also been interpreted as a more positive effect with 1 = poor and 5 = good, but we believe that the interpretation was the former, as it followed the other questions on noise distraction, as described below.

The three sets of questions on noise distraction and concentration (items 4 to 6) were all answered on the scale: 1 =“never” (good), 2 = “rarely”, 3 = “sometimes”, 4 = often” and 5 = “all the time” (poor). The intention of using the same rating scale was to allow simple indices to be created based on factor analysis. In practice, a principal component analysis (PCA), with varimax rotation, was carried on all the three sets of dependent variables.

The PCA produced four components. Based on selecting questions with a component loading (weighting) greater than 0.5, the four components appear to be related to: concentration (C), distraction (D), speech (S) and extraneous sounds (E). The superscripts, written next to each of the questions in items 4 to 6 on the variable list, indicate the principal component on which the question was weighted above 0.5. The responses to the questions selected in each component were then simply averaged to form the concentration, distraction and speech indices, with six, seven and four questions included, respectively.

Statistical analysis

All analysis in this paper was conducted using the statistics package for social scientists (SPSS). The findings presented in the results section of this paper are mostly statistically significant (p < 0.05), but some non-significant (N/S) results are included for completeness.

The size of the effect when comparing groups (tests of difference) was measured by η2, and when comparing relationships (correlations), the variance (r2) was used as the measure. According to Cohen (1988), η2 of 0.01 is considered small, whereas 0.06 is medium and 0.14 is large. For r2, 1 per cent is considered small, 9 per cent is medium and 25 per cent is large.

Survey sample

Merlin Events and Marketing, who organise the Workplace Trends series of conferences, invited their database of potential conference delegates to participate in the survey. Saint-Gobain Ecophon also sent emails requesting their clients to take part in the study. Calls to participate were also made via social media, including relevant LinkedIn groups such as Acoustic Bulletin and Workplace Trends, along with corresponding Twitter feeds.

Some 547 responses were received, but 31 came after the deadline, so were excluded them, resulting in 516 valid responses. Because of using social media, the number of invitations to participate is not certain, but we estimate a response rate in the region of 15-20 per cent. Whilst this is not high, the number of responses and survey sample characteristics are sufficient to offer worthwhile, statistically valid, analysis.

Half of the responses came from the UK (50.2 per cent), with a further 18.6 per cent coming from The Netherlands. The sample included a range of occupations, but there is a higher proportion of architects, designer and engineers (17.4 per cent) and consultants or advisors (16.1 per cent). So, the sample is mostly from the construction industry, and therefore probably more informed in acoustics matters.

The respondents were asked to identify their primary place of work. Over one-half (53.9 per cent) primarily work at an open-plan desk, with one-third of them (17.3 per cent of the total sample) working at a hot/flexi desk. A further 17.8 per cent worked primarily from home; these are likely to be home-offices rather than ad hoc arrangements. One-quarter of the sample work in a private (12.2 per cent) or shared (14.8 per cent) office, and the remaining 1.3 per cent use a co-working space. For simplicity and to ensure sufficient numbers in each group, the primary workplace was regrouped into: home, office, open-plan.

Personality profiles

The primary objective of the survey was to test whether different personality types affect noise perception and distraction. It is, therefore, important that the sample includes a range of personality types. Figure 1 shows that our sample is normally distributed across each of the Big Five (OCEAN) personality types; the mean (-x) rating and standard deviation (σ) are shown for each personality factor.

The developers of the BFI recommend that the respondents are sub-grouped into three categories, on each personality factor, to represent those with low, medium and high scores relative to the other respondents in the sample. So, those with a rating below 1 standard deviation (–1σ) of the mean average were considered low (L), scoring and representing one end of the personality scale; they represent around 16 per cent of the respondents. Those with a rating above 1σ of the average were considered high (H) scoring and representing the other end of the personality scale; they also represent around 16 per cent of the respondents. The majority (68 per cent) of the respondents fit into the mid-range (M), with a personality score within ±1σ of the mean. Figure 2 illustrates the three groupings on the extroversion dimension. This grouping into three broad categories allowed a comparison of the preferences of those at extreme ends of the five personality factors.

Results

Noise metrics

When asked “How do the noise levels in your primary workspace affect your ability to work?”, three-quarters (77.8 per cent) of the respondents reported that noise in their workplace makes it difficult or very difficult to work, see Figure 3. So, it appears that, for our sample, noise in the workplace is indeed an issue and affects perceived performance.

The survey respondents were asked to estimate approximately how much their performance at work is increased or decreased by the noise levels in their primary workspace. The percentage responses on the nine-point scale were converted into negative, zero and positive groups. Figure 4 shows that two-thirds (64.9 per cent) of the respondents believe that the noise level in their workplace is having a negative effect on their performance, and more importantly, only 10.1 per cent say it has a positive effect, which is a low proportion. Using the same question, the mean estimated impact of noise on work performance is calculated to be a –5.1 per cent decrease in productivity.

The survey included a series of questions asking how the workplace affected concentration and distraction, etc. For brevity, only the most significant results are presented here. Some 42.4 per cent of the sample found themselves listening into conversations and one-third (33.0 per cent) of the respondents are distracted (all the time or often) by nearby colleagues’ conversations.

The survey included further questions about how noise distraction affects work activities, see Figure 5. Over one-quarter (28.4 per cent) of the respondents said they are interrupted mid-way through completing an important task often or all of the time. One-fifth (22.2 per cent) also said they stay late or arrive early (all the time or often) to avoid noise and distractions. In contrast, fewer of the respondents miss a deadline due to noise distraction. Perhaps, they are adapting to the noise in their workspace, or they work extra hours to compensate for any lost productivity, as work tasks need to be completed, regardless of distractions.

Noise and personality type

Table I shows the ratings of noise distraction and the three noise indices (on the five-point scales where 1 is better) for each personality type. The table also shows the estimated percentage of performance affected by the noise and also the ability to work (where 5 is better).

The table shows that the more introverted respondents (L) are more affected by noise than the extroverts (H). The estimated impact on performance of introverts is more negative than extroverts, and stress well-being, concentration and productivity are all rated more poorly. Unexpectedly, there is no significant effect on speech index, distraction or the ability to carry out work. Noise is clearly a complicated subject producing some results that do not always match our predictions. In this case, it appears that the distraction from colleagues talking and other factors is not the main source of difference between introverts and extroverts, but nevertheless the concentration, productivity, performance, stress and well-being of introverts is affected.

The largest range of effect on the noise metrics is for neuroticism. The emotionally stable (L) respondents are slightly less affected by the effect of noise than the more neurotic ones (H). The ability to carry out work, well-being, stress, productivity, distraction and speech interference are all affected, and the largest effect size is found for the concentration index.

Similarly, the less conscientious (L) are slightly more affected by noise than their more conscientious colleagues (H). In particular, performance, ability to carry out work, productivity, concentration and well-being are negatively affected. It was anticipated that the less conscientious would be less affected by noise, as possibly less bothered by the impact on work, but perhaps, they are more easily distracted from work.

Table I also shows that there are a few small effects for the agreeableness personality type. Noise had a more negative impact on stress, concentration and speech interference for those less agreeable (L). However, no statistically significant (N/S) effects were found for openness.

On further examination of the 22 individual questions that make up the three noise indices (concentration, distraction and speech), a number of statistically significant differences were found across the five personality types. For openness, one question (on conversation) produced significant results, conscientiousness had nine significantly different responses, extroversion had four, agreeableness eight and neuroticism 12. Of further interest is that some personality types are more likely to miss a work deadline due to noise distraction, in particular the more neurotic (p < 0.01, F = 4.9, η2 = 0.02) and less conscientious (p < 0.01, F = 6.1, η2 = 0.02).

Primary workspace and noise distraction

The respondents who primarily work from home rate the effectiveness of the design of their workspace in reducing noise better than those who primarily work at open-plan desks (p < 0.001, F = 8.52, η2 = 0.04). Similarly, home-workers perceive they have more control over the noise on their workplace than those at open-plan desks (p < 0.001, F = 28.8, η2 = 0.11). The key question is whether the primary workplace also affects the perception of noise distraction and corresponding performance.

Table II shows the ratings (on a five-point scale where 1 is better) in response to the key noise metrics and three noise indices. The table shows that, in general, those who primarily work from home rate noise distraction as slightly more positive than those working in private/shared offices, who in turn rate it more positive than those in open-plan. The largest effect was shown for the speech index.

A number of individual questions also produced significantly different results with medium-sized effects due to the primary workplace: listening in to nearby conversations (p < 0.001, F = 29.6, η2 = 0.11) and distraction from colleague conversations (p < 0.001, F = 29.8, η2 = 0.11), conversations in other teams (p < 0.001, F = 14.4, η2 = 0.06), loud voices (p < 0.001, F = 18.8, η2 = 0.08) and telephone calls (p < 0.001, F = 13.2, η2 = 0.06).

Perceived control and acoustic design

The respondents who considered themselves to have more perceived control over noise (“mostly” or “very much so”) were less distracted by noise than those with little perceived control (“definitely not”, “not really”, “a little”). Table III shows that the noise variables were all statistically significant, with the size of effect largest for the concentration and speech indices. So, perceived control is mostly related to reduced distraction from talking and improved concentration.

Figure 6 shows that the respondents who primarily work from home rate the effectiveness of the design of their workspace in reducing noise better than those who primarily work at open-plan desks (p < 0.001, F = 8.52, η2 = 0.04). Similarly, home-workers perceive they have more control over the noise in their workplace than those at open-plan desks (p < 0.001, F = 28.8, η2 = 0.11).

Those working primarily at home not only have less noise distraction than their colleagues (Table II) but also have more perceived control. So, perceived control appears to be the key variable rather than the primary workplace per se. The design challenge is, therefore, to create office environments that have the same level of perceived control as the home.

Focus and concentration

The psychological literature reports very strong links between work requiring concentration and the impact of noise distraction. So, the survey participants were asked what percentage of their work time they carry out tasks that require focus and concentration. The responses were recoded as 1-40 per cent, 41-59 per cent and 60 per cent+.

Table IV shows that there were only two significant differences in noise distraction for those spending their time in focus and concentration. Furthermore, the size of the effect was small (η2 < 0.1) which was not expected for such a key variable. This result was not affected by filtering for those who spend most of their time in the office or for those who use headphones.

Screening ability and coping mechanisms

The survey participants were asked to select the main coping mechanisms they use to deal with noise distraction. Figure 7 shows that moving away from the source of noise, by working outside the office or at home (46.1 per cent) is a primary coping mechanism. Following on from the previous section, this is likely because the respondents have more perceived control in the home. However, given the provision, moving to a quiet area (40.5 per cent) is also a readily adopted coping mechanism, but few say they move to another desk (14.1 per cent). The proportion of respondents who say they come in early or work late to avoid noise (38.8 per cent) and the numbers that wear headphones at work (37.8 per cent) was higher than expected. Interestingly, fewer respondents say they raise the issue with colleagues (14.7 per cent), so would rather change their own behaviour than challenge that of others.

The respondents were asked how good they are at screening out noise and distractions in their primary workplace. As shown in Table V, there are medium to large effects across all the noise metrics for high (“good”, “very good”) and low (“very poor”, “poor”, “okay”) screening ability.

Research studies have found the ability to screen out noise to be a key variable, but it is unclear what underlines the ability or whether it is a separate personality factor. Weak correlations were found between the ability to screen and the five personality factors: open (r = 0.11, p < 0.05), conscientiousness (r = 0.21, p < 0.001), extroversion (r = 0.11, p < 0.05), agreeableness (r = 0.11, p < 0.001) and neuroticism (r = −0.34, p < 0.001). However, no one specific personality type was found to be strongly associated with screening ability. If screening is a learned skill, then perhaps natural screeners can educate their less-fortunate colleagues.

Socio-demographics

A few basic background questions were asked. For example, statistically significant differences were found for some of the noise metrics across age groups. Table VI shows that, unexpectedly, the older respondents perceive noise to be slightly less of an issue than the younger ones.

Some minor effects of organisation size were found. Those in smaller organisations (1-14 people) rated their concentration (p < 0.05, F = 3.4, η2 = 0.02) and speech interference (p < 0.001, F = 9.6, η2 = 0.06) better than those larger organisations.

Small but significant differences in some of the noise metrics across job roles were found. Senior management and acousticians rate the effect of noise on their concentration (p < 0.05, F = 2.0, η2 = 0.04) and stress (p < 0.01, F = 2.6, η2 = 0.05) better than those working in project management, cost consulting, sales or business development or research.

Combined noise factors

The previous sections describe the various factors (independent variables) that were tested for an effect on various noise metrics (dependent variables). Multiple (stepwise) regression analysis was used to test which of the independent variables had the biggest impact on noise and contributed the most to explaining the variation in the various metrics of noise distraction.

Table VII shows that the variables that repeatedly predict noise distraction are: the ability to screen noise, design effectiveness, time working at home and perceived control. Personality types such as extroversion, openness and neuroticism also contribute to noise distraction. In addition, the time in heads-down (focussed) work influenced distraction and age affected ratings of productivity. These variables account for 12.9 per cent of the variance in the self-assessed impact on performance, and they contributed to 27.3 per cent of the variance in ratings of productivity. Furthermore, these variables contribute to 40.1 per cent of the variance in how the respondents believe noise affects their concentration, and 39.6 per cent of the variance in speech interference is explained by some of the noise metrics. The effect size was found to be large (> 25 per cent) for all the multiple regression analysis.

Discussion

Summary of findings

When asked how noise affects the ability to work, only 8.4 per cent of the respondents reported that the noise in their workplace does not make their work difficult. Similarly, the survey participants were asked to estimate approximately how much their performance at work is increased or decreased by the noise levels in their primary workplace. Only 10.1 per cent of the respondents believed that their workplace had a positive effect on their self-assessed performance, which is low, and in line with previous research (Abbot, 2004; Jensen et al., 2005; Oseland and Burton, 2012). The survey participants are mostly distracted by nearby colleagues’ conversations, listening to those conversations and individuals with loud voices. Another quarter of respondents said they are interrupted mid-way through completing an important task often or all of the time. It should be noted that all these distractions are fundamentally behavioural issues.

Furthermore, the mean estimated impact of noise on work performance is –5.1 per cent. Whilst this figure appears low, it should be noted that just a 5 per cent increase in employee performance can offset the cost of building and operating an office property (Oseland, 2017). So, it appears that for the survey sample, noise in the workplace is indeed an issue and affects their performance.

Personality type had an effect on perceived noise distraction, in line with previous research (Franklin et al., 2013). The more introverted respondents are more negatively affected by noise than extroverts. Self-assessed performance, stress, well-being, concentration and productivity are all rated slightly worse by introverts. The largest effect on the noise metrics is for the neuroticism personality trait. The less neurotic respondents are less affected by noise, as reflected in the majority of noise metrics with the largest effect size shown for concentration. Statistically significant, but mostly small, effects were also found for conscientiousness and agreeableness. Furthermore, the more neurotic and less conscientious respondents believe they are also likely to miss a work deadline due to noise distraction. The reason for the small, but nevertheless significant effects, are explored in the next section.

Those who primarily work from home perceive they have more control over the noise in their workplace than those at open-plan desks. The key question is whether the primary workplace affects the perception of noise distraction and corresponding performance. Indeed, it was found that those who primarily work from home rate noise distraction as more positive than those working in open-plan or private/shared offices. The largest effect was shown for speech interference.

Whilst the results show that working from home is good for minimising noise distraction and speech interference, it does not necessarily mean that the only solution to noise is working from home. Indeed, the survey respondents preferred office work-settings for team-working and face-to-face meetings; see the original report by Oseland and Hodsman (2015). Furthermore, the office is generally considered to facilitate collaboration and mentoring, provide supporting equipment and facilities, offer a showcase for clients and foster staff loyalty. Whilst the survey showed that those in private and shared offices were less distracted by noise than those in the open-plan spaces, we are not suggesting to replacing open-plan environments with cellular spaces. The open-plan office is being adopted across the world, and is likely, here to stay. The challenge is, therefore, to create open-plan offices which minimise noise distraction, which is achievable with well-considered acoustic design, management and use of the space.

On further inspection, the survey revealed no significant differences across the primary workspaces between the ratings of productivity and performance. This may be due to the respondents adapting to “get the job done” or their views on what they consider is productive work may vary. For example, for some workers, meeting colleagues, sharing ideas and delegating work may be considered key deliverables; for others, it may be analysis, processing or written outputs that are the main deliverables. Nevertheless, we suspect that, as elements of concentration and distraction are affected, then performance efficiency will also be degraded, perhaps resulting in earlier fatigue, regardless of whether output is maintained.

There were few significant differences in noise distraction for those spending their time in focus and concentration; the size of the effect was also smaller than expected for such a key variable. It may be possible that people who need to focus and concentrate have learned to cope with or adapt to the surrounding noise levels. It may also be that the people who need to focus are more diligent and just “get the job done”, regardless of the distractions. Overall, this is an unexpected result worthy of further investigation. However, our results imply that, in terms of noise, factors such as personality are more important than the task or work activity.

The respondents who perceived they have more control over noise were less distracted by noise, irrespective of their personality type. Those working primarily at home had more perceived control than their colleagues and also had less noise distraction. So, perceived control appears to be the key variable rather than the place of work per se. The design challenge is to create office environments that have the same level of perceived control as the home.

Our respondents were asked how good they are at screening out noise and distractions in their primary workplace. There are good correlations with all the noise metrics and screening ability, accounting for up to 26 per cent of the variance in responses. The noise variables are all significantly affected by the ability to screen, and the size of effect is one of the strongest we found. Screening was also weakly correlated with all personality factor ratings, but not related strongly with any one personality type. The ability to screen out noise requires further investigation to understand whether it is learnt or innate, and if learned, then can all workers acquire this valuable skill.

The alternative to being able to naturally screen out noise, or to adapt to noise, is to cope with it in some other way. Moving away from the source of noise distraction, either by working outside the office at home or elsewhere, or by moving to a quiet area appears to be the primary coping mechanisms. Unexpectedly, there was also a high proportion of respondents who say they come in early or work late to avoid noise and who wear headphones at work. Interestingly, fewer respondents say they raise the issue with colleagues, so they learn to cope by changing their own behaviours, rather than challenging others.

Unexpectedly, the older respondents perceive noise to be slightly less of an issue than the younger ones. It was anticipated that the younger respondents coped better in noisy environments, whereas it appears the older ones may have adapted to their acoustic environment or have more choice over their work-settings. A more cynical view might be that the older respondents have poorer hearing so are less affected by noise, but this is not general consensus in the literature. A more recognised problem with the hearing abilities of older workers’ is distinguishing speech in noisy environments, but this was not supported in these data.

When considering all the variables in our survey, the ones that repeatedly predict noise distraction are: the ability to screen noise, design effectiveness, time working at home and perceived control. Personality types such as extroversion, openness and neuroticism also contribute to noise distraction. In addition, the time in focused work had an effect on distraction, and age affected the ratings of productivity. These variables account for 13 per cent of the variance in the self-assessed impact on performance, and they contribute to 27 per cent of the variance in the ratings of productivity. Furthermore, these variables contribute to 40 per cent of the variance in how the respondents believe noise affects their concentration and speech interference, and 25 per cent of the variance in the ability to carry out work. So, whilst our analysis does not account for the 75 per cent variation in noise distraction that we anticipated, it has highlighted some key factors psychological and personal factors that affect noise perception.

Interpretation of results

The analysis clearly shows that noise is an issue that affects performance at work, in particular concentration and speech interference. Many statistically significant results were found, but in some cases, the size of the effect (measured by η2) was not as great as expected based on those effects observed in the studies reported in our literature review. This smaller-than-anticipated effect of noise may be for several reasons:

  • The study involved “real world” research. People were asked to complete the survey about their primary place of work, possibly completed in that place, rather than carrying out a controlled laboratory experiment. The sound levels in the respondent’s offices were not actually controlled, and the study was dependent on the responses coming from a range of acoustic environments. Furthermore, in controlled experiments, the subjects are generally focusing on one specific task, away from distractions and interfering factors, and often motivated (financially or otherwise) to complete that task. In contrast, in the real world, there are many confounding variables such that noise becomes one of the many factors rather than the one focused on. For example, the productivity theory has shown that motivational factors, such as reward and recognition, have a larger impact on performance than hygiene factors, such as the physical environment. That noise distraction is registering as a concern amongst other variables indicates its importance, but the subtleties of other factors such as personality may be lost amongst the general office melee.

  • The effect of noise on concentration and distraction was stronger than on self-assessed performance and productivity. It may be that, despite the distractions from noise and speech interference, with all the associated inefficiencies, people still have to complete their work duties and complete tasks. So, their perceived performance (based on daily/weekly output) is not as greatly affected as might be expected, i.e. they have to “get the job done”, regardless of the distractions. However, distractions causing inefficiencies will result in the work taking longer to ensure the output is delivered; these extra working hours will have an impact on fatigue, stress and possibly absenteeism.

  • The survey respondents were found to adopt a number of coping strategies to deal with or adapt to noise distractions. The natural ability to screen out noise is also a key factor. If the respondents are adapting to noise, then the effect of noise on distraction and performance will be less noticeable. Nevertheless, it may mean that unnecessary effort, physical and mental, is being wasted daily to deal with noise. Such effort can affect both stress and well-being, as well as work efficiency.

Practical implications

The ability to screen noise, design effectiveness, time working at home, perceived control, age, time doing focused work and personality types (such as extroversion, openness and neuroticism) all contributed to perceived noise distraction. So, as originally proposed in the literature review, there is a need to consider and resolve the psychological and behavioural factors that impact on noise, as well as the physical.

Therefore, the people-centred acoustic solution we offered in the previous literature review still stands. The solution to noise distraction is as much to do with the management of the space and guidance on behaviour as it is about the design and acoustic properties. A choice of different types of space with different acoustic properties and agreed behaviours is essential for reducing noise distraction.

Since the survey was conducted, the authors have produced design guidance using people-centred acoustic solutions (Oseland and Hodsman, 2017b) along with a practical toolkit, which includes an evaluation and workshops techniques. The core guidance is summarised using the DARE acronym, as follows:

  • Displace – remove the noise distraction by providing a range of work-settings designed to accommodate, and separate, noisy activities from quieter ones.

  • Avoid – minimise generating noise distractions, for example, by not providing meeting tables near workstations where people are carrying out quiet work, and by locating noisy teams together away from the more subdued ones.

  • Reduce – limit the noise distraction by controlling the desk size and density and using good acoustic design to reduce speech intelligibility across open-plan areas and noise transference between rooms.

  • Educate – introduce some form of office etiquette which reinforces consideration towards colleagues and expected behaviours in shared working environments.

Conclusions

Our research supports our hypothesis and builds on previous findings that distraction from noise is a key issue in offices and affects performance, in particular, concentration and speech interference. The impact of noise on performance is not as clear as expected, possibly due to the respondents using coping strategies and adapting to noise. The survey sample size was, nevertheless, constraining and additional research is needed to further test the hypothesis. This research has commenced, including intervention studies, to explore the reduction of noise distractions by applying a combination of physical and behavioural solutions in real-world offices.

Figures

Distribution of scores on the OCEAN personality types

Figure 1.

Distribution of scores on the OCEAN personality types

Calculating extreme scores

Figure 2.

Calculating extreme scores

Effect of noise on the ability to work

Figure 3.

Effect of noise on the ability to work

Rating of how much performance is affected by noise levels

Figure 4.

Rating of how much performance is affected by noise levels

Over the last working week, to what extent have you

Figure 5.

Over the last working week, to what extent have you

Rating of design and control by workspace

Figure 6.

Rating of design and control by workspace

Noise-coping mechanisms

Figure 7.

Noise-coping mechanisms

Noise ratings for each personality type

Noise metric Open
(L, M, H)
Conscientious
(L, M, H)
Extroversion
(L, M, H)
Agreeable
(L, M, H)
Neurotic
(L, M, H)
Percentage performance N/S –7.2, –4.7, –4.6
(p = 0.05, F = 4.4, η2 = 0.02)
–8.5, –4.3, –5.5
(p = 0.01, F = 7.4, η2 = 0.03)
N/S N/S
Ability to carry out work
(5 = good)
N/S 3.6, 3.9, 3.8
(p < 0.01, F = 4.8, η2 = 0.02)
N/S N/S 4.1, 3.8, 3.7
(p < 0.01, F = 5.3, η2 = 0.02)
Well-being
(1 = good)
N/S 2.5, 2.1, 2.2
(p < 0.05, F = 3.7, η2 = 0.02)
2.5, 2.1, 2.2
(p < 0.05, F = 3.6, η2 = 0.02)
N/S 1.9, 2.2, 2.3
(p < 0.05, F = 4.0, η2 = 0.02)
Stress
(1 = good)
N/S N/S 2.8, 2.5, 2.5
(p < 0.05, F = 3.7, η2 = 0.02)
2.8, 2.5, 2.2
(p < 0.05, F = 5.1, η2 = 0.02)
2.1, 2.6, 2.7
(p < 0.001, F = 8.5, η2 = 0.04)
Productivity
(1 = good)
N/S 3.1, 2.8, 2.7
(p < 0.05, F = 4.4, η2 = 0.01)
3.1, 2.7, 3.0
(p < 0.05, F = 3.9, η2 = 0.02)
N/S 2.5, 2.9, 3.0
(p < 0.05, F = 4.1, η2 = 0.02)
Concentration index
(1 =good)
N/S 2.9, 2.5, 2.4
(p < 0.001, F = 9.9, η2 = 0.04)
2.8, 2.5, 2.5
(p < 0.01, F = 5.1, η2 = 0.02)
2.7, 2.5, 2.3
(p < 0.01, F = 5.0, η2 = 0.02)
2.2, 2.5, 2.9
(p < 0.001, F = 20.6, η2 = 0.08)
Distraction index
(1 = good)
N/S 2.7, 2.4, 2.6
(p < 0.05, F = 3.7, η2 = 0.02)
N/S N/S 2.4, 2.4, 2.8
(p < 0.01, F = 6.2, η2 = 0.03)
Speech index
(1 = good)
N/S N/S N/S 2.7, 2.7, 2.4
(p < 0.05, F = 4.0, η2 = 0.02)
2.6, 2.7, 2.8
(p < 0.05, F = 3.9, η2 = 0.02)

Ratings of noise distraction metrics by primary workplace

Noise metric Desk Office Home Statistics
Percentage performance –5.3 –5.1 –4.6 N/S
Ability to carry out work (5 = good) 3.8 3.9 3.9 N/S
Well-being (1 = good) 3.9 2.1 2.4 p < 0.05, F = 4.45, η2 = 0.02
Stress (1 = good) 2.4 2.6 2.6 N/S
Productivity (1 = good) 2.8 2.9 2.7 N/S
Concentration index (1 =good) 2.6 2.4 2.4 p < 0.01, F = 4.8, η2 = 0.02
Distraction index (1 = good) 2.6 2.3 2.3 p = 0.001, F = 7.3, η2 = 0.03
Speech index (1 = good) 2.9 2.6 2.2 p < 0.001, F = 22.0, η2 = 0.09

Noise distraction and perceived control

Noise metric Definitely not
or a little
Mostly or very
much so
Statistics
Percentage performance –5.8 –2.8 p < 0.001, t = 3.0, η2 = 0.02
Ability to carry out work (5 = good) 3.8 4.1 p < 0.001, t = 2.8, η2 = 0.02
Well-being (1 = good) 2.2 2.0 p < 0.001, t = 2.2, η2 = 0.01
Stress (1 = good) 2.6 2.3 p < 0.001, t = 2.2, η2 = 0.01
Productivity (1 = good) 3.0 2.3 p < 0.001, t = 5.0, η2 = 0.05
Concentration index (1 =good) 2.6 2.1 p < 0.001, t = 6.9, η2 = 0.10
Distraction index (1 = good) 2.6 2.1 p < 0.001, t = 4.8, η2 = 0.05
Speech index (1 = good) 2.9 2.0 p < 0.001, t = 9.5, η2 = 0.17

Noise metrics by work time concentrating

Noise metric < 41% 41-59% 60%+ Statistics
Percentage performance –5.1 –5.7 –5.2 N/S
Ability to carry out work (5 = good) 3.9 3.8 3.9 N/S
Wellbeing (1 = good) 2.2 2.2 2.2 N/S
Stress (1 = good) 2.5 2.5 2.5 N/S
Productivity (1 = good) 2.7 2.9 2.8 N/S
Concentration index (1 =good) 2.4 2.7 2.5 p < 0.05, F = 4.3, η2 = 0.02
Distraction index (1 = good) 2.5 2.6 2.3 p < 0.05, F = 3.5, η2 = 0.02
Speech index (1 = good) 2.7 2.8 2.6 N/S

Ability to screen out noise

Noise metric Very poor,
poor, okay
Good or
very good
Statistics
Percentage performance –7.0 –2.5 p < 0.001, t = –5.7, η2 = 0.07
Ability to carry out work (5 = good) 3.6 4.2 p < 0.001, t = –8.2, η2 = 0.13
Wellbeing (1 = good) 2.5 1.8 p < 0.001, t = 7.6, η2 = 0.12
Stress (1 = good) 2.8 2.1 p < 0.001, t = 8.2, η2 = 0.13
Productivity (1 = good) 3.2 2.3 p < 0.001, t = 8.6, η2 = 0.14
Concentration index (1 =good) 2.8 2.1 p < 0.001, t = 10.6, η2 = 0.20
Distraction index (1 = good) 2.7 2.2 p < 0.001, t = 6.5, η2 = 0.09
Speech index (1 = good) 2.9 2.4 p < 0.001, t = 7.1, η2 = 0.10

Noise metrics by age of respondent

Noise metric < 35 35-54 55+ Statistics
Percentage performance –6.8 –5.2 –3.3 p < 0.05, F = 4.1, η2 = 0.02
Ability to carry out work (5 = good) 3.8 3.8 4.1 p < 0.05, F = 3.8, η2 = 0.02
Well-being (1 = good) 2.7 2.3 1.9 p < 0.01, F = 5.8, η2 = 0.03
Stress (1 = good) 2.7 2.6 2.1 p < 0.001, F = 9.8, η2 = 0.04
Productivity (1 = good) 3.1 2.9 2.3 p < 0.001, F = 17.1, η2 = 0.08
Concentration index (1 =good) 2.7 2.6 2.3 p = 0.001, F = 7.0, η2 = 0.03
Distraction index (1 = good) 2.5 2.6 2.2 p = 0.001, F = 7.1, η2 = 0.03
Speech index (1 = good) 2.9 2.8 2.4 p < 0.001, F = 11.5, η2 = 0.05

Noise metrics by all independent variables

Noise metric Multiple regression entered variables Statistics
Percentage performance Screening, design r = 0.36, r2 = 12.9%, p < 0.001
Ability to carry out work Screening, design, home-working r = 0.50, r2 = 24.6%, p < 0.001
Well-being Screening, design, extroversion, openness r = 0.41, r2 = 16.7%, p < 0.001
Stress Screening, design, age, neuroticism, openness r = 0.50, r2 = 24.5%, p < 0.001
Productivity Screening, design, age r = 0.52, r2 = 27.3%, p < 0.001
Concentration index Screening, control, neuroticism r = 0.64, r2 = 40.1%, p < 0.001
Distraction index Screening, control, focussed, openness r = 0.43, r2 = 18.6%, p < 0.001
Speech index Screening, control, home-working r = 0.63, r2 = 39.6%, p < 0.001

References

Abbot, D. (2004), “Calming the office cacophony”, The Safety and Health Practitioner, Vol. 22 No. 1, pp. 34-36.

Belojevic, G., Slepcevic, V. and Jakovljevic, B. (2001), “Mental performance in noise: the role of introversion”, Journal of Environmental Psychology, Vol. 21 No. 2, pp. 209-213.

Borsky, P.N. (1969), “Effects of noise on community behaviour”, in Proceedings of the Third International Congress on Noise as a Public Health Hazard, ASHA Reports 4W, Speech-Language-Hearing Association, Washington, DC.

Broadbent, D.E. (1958), Perception and Communication, Pergamon Press, London.

Campbell, J.B. and Hawley, C.W. (1982), “Study habits and Eysenck’s theory of extraversion–introversion”, Journal of Research in Personality, Vol. 16 No. 2, pp. 139-146.

Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences, Routledge, Oxon.

Eysenck, H.J. (1967), The Biological Basis of Personality, Thomas Publishing, Springfield.

Eysenck, M.W. and Graydon, J. (1989), “Susceptibility to distraction as a function of personality”, Personality and Individual Differences, Vol. 10 No. 6, pp. 681-687.

Franklin, C., Johnson, L.V., White, L., Franklin, C. and Smith-Olinde, L. (2013), “The relationship between personality type and acceptable noise levels: a pilot study”, ISRN Otolaryngology, Vol. 2013.

Horowitz, S. (2012), The Universal Sense: How Hearing Shapes the Mind, Bloomsbury, London.

Jensen, K.L., Arens, E. and Zagreus, L. (2005), “Acoustical quality in office workstations, as assessed by occupant surveys”, Proceedings of Indoor Air 2005, Beijing, pp. 2401-2405.

John, O.P., Donahue, E.M. and Kentle, R.L. (1991), The Big Five Inventory - Versions 4a and 54, UC Berkeley, Berkeley, CA.

John, O.P. and Srivastava, S. (1999), “The big five trait taxonomy: history, measurement and theoretical perspectives”, in Pervin, L.A. and John, O.P. (Eds) Handbook of Personality: Theory and Research, Guilford Press, New York, NY, pp. 102-138.

Matthews, T., et al. (2004), “A toolkit for managing user attention in peripheral displays”, in Proceedings of the 17th Annual ACM Symposium on User Interface Software and Technology (UIST), pp. 247-256.

Mehrabian, A. (1977), “A questionnaire measure of individual difference in stimulus screening and associated differences in arousability”, Environmental Psychology and Nonverbal Behavior, Vol. 1 No. 2, pp. 89-103.

Morgenstern, S., Hodgson, R.J. and Law, L. (1974), “Work efficiency and personality”, Ergonomics, Vol. 17 No. 2, pp. 211-220.

Oldman, T. and Rothe, P. (2017), “2017 Q1 data summary”, Leesman Review, No. 23, pp. 6-7.

Oseland, N.A. (2009), “The impact of psychological needs on office design”, Journal of Corporate Real Estate, Vol. 11 No. 4, pp. 244-254.

Oseland, N.A. (2017), “Proving the productivity benefits of well-designed offices”, in Clement-Croome, D. (Ed.), Creating the Productive Workplace: Places to Work Creatively, Routledge, Oxon, pp. 148-159.

Oseland, N.A. and Burton, A. (2012), “Quantifying the impact of environmental conditions on worker performance for inputting to a business case to justify enhanced workplace design features”, Journal of Building Survey, Appraisal and Valuation, Vol. 1 No. 2, pp. 151-164.

Oseland, N.A. and Hodsman, P. (2015), Psychoacoustics Survey Results: Psychological Factors Affecting Noise Distraction, Workplace Unlimited, available at: http://workplaceunlimited.com/Psychoacoustics%20Final%20Report.pdf (accessed 1 August 2017).

Oseland, N.A. and Hodsman, P. (2017a), “Psychoacoustics: resolving noise distractions in the workplace”, in Hedge, A. (Ed.), Ergonomics Design for Healthy and Productive Workplaces, Taylor and Francis, Abingdon, pp. 73-102.

Oseland, N.A. and Hodsman, P. (2017b), Design Guidance on Eliminating Office Noise: A Psychoacoustic Approach, Saint-Gobain Ecophon, Tadley.

Nurmi, J. and von Wright, J. (1983), “Interactive effect of noise, neuroticism and state anxiety in the learning and recall of a textbook passage”, Human Learning, Vol. 2, pp. 119-125.

Perham, N., Banbury, S. and Jones, D.M. (2007), “Do realistic reverberation levels reduce auditory distraction?”, Applied Cognitive Psychology, Vol. 21 No. 7, pp. 839-847.

Smith, A.P. and Jones, D.M. (1992), “Noise and performance”, in Jones, D.M. and Smith, A.P. (Eds) Handbook of Human Performance. Volume 1: The Physical Environment, Harcourt Brace Jovanovich, London, pp. 1-28.

Standing, L., Lynn, D. and Moxness, K. (1990), “Effects of noise upon introverts and extroverts”, Bulletin of the Psychonomic Society, Vol. 28 No. 2, pp. 138-140.

Treasure, J. (2010), “Shh! sound health in 8 steps”, TEDGlobal 2010, available at: www.ted.com/talks/julian_treasure_shh_sound_health_in_8_steps (accessed 1 August 2017).

von Wright, J. and Vauras, M. (1980), “Interactive effects of noise and neuroticism on recall from semantic memory”, Scandinavian Journal of Psychology, Vol. 21 No. 1, pp. 97-101.

Wilson, S. and Hedge, A. (1987), “The office environment survey: a study of building sickness”, Building Use Studies, London.

Corresponding author

Paige Hodsman can be contacted at: paige.hodsman@ecophon.co.uk