The influence of individual noise sensitivity on mobile phone attitudes and behavior

Abstract

Research in psychoacoustics and public health reveals that individuals respond differently to noise, with some being more sensitive to noise than others. Given the prevalence of mobile technology and that noise sensitivity appears to be a relatively stable individual difference, it is possible that noise sensitivity may distinguish individual mobile phone use. This study investigates the relationship between noise sensitivity and mobile phone attitudes and behaviors. Study results suggest that noise sensitive bystanders find mobile phone conversations more annoying, that they differ in their assessment of the distraction level of ambient noise when making and receiving calls, are more likely to report mobile phones as distracting, and are more likely to seek privacy from others when receiving a call.

Keywords

Listening mobile phone noise mobile phone privacy noise sensitivity sensory processing sensitivity

In many respects, mobile technology has made the world a noisier place. Chimes, rings, vibration, and chirps have become commonplace in public and private spaces. Their noise appears to be a new normal in our social interactions with others. It is clear, however, that not everyone responds the same to the sounds associated with mobile devices. Whether their sounds are considered noise can vary, with some individuals being more sensitive than others (Smith, 2003).

Focus on the role of mobile telephony as a noise source is growing. For example, engineers have begun developing building materials designed to block or reduce mobile phone pollution in public areas such as theatres (“Cell Phone Noise,” 2005), while business owners and others have designated quiet spaces (e.g., libraries, doctor offices, etc.). Even cities are addressing cellular phone noise. The New York City Department of Environmental Protection’s Guide to New York City’s Noise Code discusses keeping cell-phone conversations “to a minimum in public spaces, especially confined areas like public transit” (“A Guide to York City’s,” 2014, p. 7), while the city of LaPorte, Indiana, suggests residents keep their cell-phone ringer at its lowest volume to reduce noise pollution (“Playing Your Part,” 2010). Traditionally, researchers in noise sensitivity have focused on annoyance associated with airplanes, traffic, railways, factories, etcetera (e.g., Marks & Griefahn, 2007; Ouis, 2002). Mobile devices, in contrast, have received little attention (for an exception, see Benfield et al., 2012).

If, as suggested by researchers, attitudes and behaviors are affected by sensitivity to noise, then noise sensitivity may inform our understanding of individual mobile phone behavior. Cell-phone noise can possibly affect the moods and emotions of users and proximate others, and may negatively influence message processing, especially among those who are more noise sensitive. This article reports results of a study examining the impact of individual noise sensitivity on attitudes toward and use of mobile phones.

Noise sensitivity

Miedema (2007) outlines several factors that can lead noise to be classified as annoying. Noise may be judged as irritating when it masks other sounds, begins to interfere with intellectual activities, reduces attention and the ability to focus or concentrate, and leads to physiological arousal resulting in negative affect or reaction.

Noise irritation, one of the most examined reactions to sound, has been referred to in a number of ways (i.e., unpleasant, annoying, disturbing, etc.; Guski, 1997) and has been studied by a number of researchers (see e.g., Baird, Harder, & Preis, 1997; Schreiber & Kahneman, 2000; Västfjäll, 2002). As an element of environmental noise and the annoyance people experience, research in psychoacoustics and public health reveals that individuals respond differently to noise (for a review, see Hill, 2012). Saarinen (2013) suggests that noise sensitivity is not only an individual, but also an organizational and societal dilemma. While many definitions (and types) of noise sensitivity exist (see Mulgrew, 2013, for a review), Mulgrew (2013) suggests a definition that “provides sufficient specificity to allow testing” while at the same time addressing both the stimulus and psychological elements of noise sensitivity (NS). He defines noise sensitivity as

A relatively stable trait that mediates an individual’s tolerance and subsequent reaction to both ambient sound in general and to specific sounds, and can be expressed on a continuum with highly noise reactive (i.e., high noise sensitivity) and highly noise resilient (i.e., low noise sensitivity) as poles. (2013, p. 10)

One of the seminal studies in noise sensitivity and its measurement was conducted by Weinstein (1978). His longitudinal investigation is noteworthy for several reasons. First, as part of his study, Weinstein developed the first comprehensive self-report measure of noise sensitivity. His study also encouraged researchers to begin examining noise sensitivity as an individual difference and introduced the study of noise sensitivity to nontransportation contexts. Using a student population, Weinstein examined differences in individual reactions to noise in a college dormitory context. More specifically, he examined initial reactions to noise as well as a subject’s ability to adapt to noise over time. Weinstein found a significant positive relationship between sensitivity and need for privacy, with noise sensitive students reporting a stronger need for privacy (r = .41; p < .01). Sensitive subjects were also more critical of noise in their surroundings and were quicker to express their displeasure when faced with noise disturbances. Other results found higher sensitivity to be inversely related to extraversion, social desirability, sociability, and social presence. Based on these and related findings, Weinstein claimed that noise reactive individuals are less comfortable and effective in social situations.

More recent studies have found that noise reactive individuals are more aware of sound, rate it more negatively, and generally have a stronger affective response to it (Mulgrew, 2013; Zimmer & Ellermeier, 1999). While noise sensitivity appears to be independent of noise level, it does, however, reduce the threshold at which individuals report sounds as annoying (Miedema & Vos, 1999). In other words, sensitive individuals tend to report greater levels of annoyance than their noise resilient counterparts, no matter the actual noise level (see e.g., Ellermeier, Eigenstetter, & Zimmer, 2001; Heinonen-Guzejev et al., 2007; Nordin, Ljungberg, Claeson, & Neely, 2013; Raw & Griffiths, 1988).

Mobile phone noise

Annoyance with noise from telephones, mobile phones, and related electronic devices has been documented. As part of a larger study, Benfield and his colleagues (2012) explored visitor reactions to possible noise (e.g., airplane, automotive, visitors talking, visitor electronic devices, park operations) in a U.S. national park setting (Yosemite National Park). They note that noise levels in parks can be a source of conflict, but that the level of annoyance can vary with the individual. Benfield et al. (2012) found that as individual noise sensitivity rose, evaluations of the acceptability of using personal electronic devices fell.

Kjellberg, Landstroè, Tesarz, Èoderberg, and Èakerlund (1996), examining individual responses to noise in a work environment, report two findings applicable to this study. First, participants found it easier to deal with constant noise rather than variable noise. Second, telephone noise, in particular, was identified by noise sensitive workers as annoying and distracting. These findings reflect those of other studies reporting that people find constant, predictable noise (i.e., ongoing background noise) less annoying than variable noise (Gearhart, 2012; Kuwano, Namba, & Nakajima, 1980; Vanderhei & Loeb, 1977).

The results of these studies are limited in at least two ways. First, both studies were conducted in a specialized context (i.e., a national park and office environment) and the expectations associated with the context may affect the generalizability of the findings. Second, the findings may or may not be indicative of a general negative attitude toward the public use of mobile phones.

However, related research suggests the findings may still apply to mobile phone use. For example, sensory processing sensitivity has also been linked to increased processing errors. Gearhart (2012) found sensitive persons to be more distracted by audio stimulation, particularly intermittent audio sounds. His findings support suggestions by Luz (2005) and others (Aron, 1996; Aron & Aron, 1997) that as arousal increases for these individuals so do problems with cognitive and social processing. Gearhart’s study results echo those of Kjellberg et al. (1996) and others (Kuwano et al., 1980; Vanderhei & Loeb, 1977), who found noise sensitivity to be associated with increased annoyance with variable noise.

Luz (2005) suggests that people who are hypersensitive to noise may have a more active orienting response or reflex (p. 15). Such a response likely makes it more difficult for noise sensitive individuals to become accustomed to repeated sounds. In contrast, noise resilient individuals should be better able to tune out the noise as they become used to it (e.g., once habituated to living near train tracks, they no longer “hear” trains going by). Luz notes that our orienting response readies us to take in and process new information. However, if this response is overactive, it can make it more difficult to concentrate. Support for this suggestion is seen in noise and sound studies that found that highly sensitive individuals have more difficulty focusing and that, as a result, make more errors during assigned tasks (Sandrock, Schutte, & Griefahn, 2009; Smith & Stansfeld, 1986).

Aron (1996) suggests that these individuals focus greater attention on both external sensory activities and internal events to the extent that it may result in being less adept in social situations (e.g., extended pauses, poorer listening, inaccurate or failed evaluations of verbal/nonverbal cues). Gearhart (2012) found support for claims that sensitive individuals process information more deeply and thus may experience a cognitive backlog when exposed to multiple or intense stimuli, resulting in reduced performance when engaged in cognitive processing tasks.

Mobile devices provide yet another level of stimulus for sensitive individuals. This stimulation is further compounded by multiple disruptions caused by their own device as well as those in their proximate area. In such instances, noise reactive individuals may focus their attention on the phone and their internal response to the device to the detriment of their interactions with others.

Given the prevalence of mobile technology, its variable sound, and that noise sensitivity appears to be a relatively stable individual difference, it is possible that noise sensitivity may distinguish individual mobile phone users’ attitudes and behaviors. The previously reviewed studies suggest that sensitive individuals may hold more negative attitudes toward mobile devices and that their interactions with others may be negatively affected. Thus, this study investigates what relationship, if any, exists between noise sensitivity and individual mobile phone use and behaviors.

Method

Participants

A total of 236 (115 women, 121 men) undergraduate students attending a large Southeastern university constituted the convenience sample for this study. Students ranged from 18 to 44 years of age (M = 22.9, SD = 7.3) and represented the freshman (n = 104), sophomore (n = 55), junior (n = 47) and senior (n = 28) ranks, with two respondents indicating postgraduate status. The majority of participants were Caucasian (78%; n = 185), followed by African Americans (n = 28), those of Asian descent (n = 10), Hispanics/Latinos (n = 6), and other (n = 7).

Procedures

Students were recruited for the study via an online scheduling system. They were able to select from a variety of research credit opportunities to fulfil a required research participation component that counted for 1.5% of their course grade. Students provided informed consent, and the appropriate Institutional Review Board approved all procedures. Students who chose to participate in this study were directed to an external and secure universal resource locator (URL) where they completed surveys on noise sensitivity, general listening, general cell-phone use, and cell-phone use in social settings.

Measures

Noise sensitivity

Noise sensitivity was measured using the revised unidimensional 10-item version of Weinstein’s Noise Sensitivity Scale (Kishikawa et al., 2006). This version differs from the WNSS-21 in that academic/dorm-related items have been removed, resulting in a scale that is more global in its assessment of listening sensitivity.

Cell-phone behaviors

To measure cell-phone behaviors, a series of questions were given to the participants on general listening (e.g., “Communicating with someone using email or instant messaging/texting uses the same listening skills as face-to-face interaction”), and general cell-phone use (e.g., “While on the mobile phone, have you ever had someone indicate to you [verbally or nonverbally] that your mobile phone use was unacceptable?”). Some items were original to this study, while others were inspired by or adapted from previous mobile phone studies (see Banjo, Hu, & Sundar, 2008; Campbell, 2007; Przybylski & Weinstein, 2012; Worthington, Fitch-Hauser, Välikoski, Imhof, & Kim, 2012).

Results

Preliminary analyses

All measurement scales were assessed for dimensionality and ability to represent current data. Commonly used fit indexes and comparison thresholds were utilized. The comparative fit index (CFI) above .90 and the root mean square error of approximation (RMSEA) below .08 (e.g., Byrne, 2010; Hoyle, 2000; Hu & Bentler, 1999; Kline, 2005; Raykov & Marcoulides, 2006). Internal consistency was estimated using Cronbach’s α.

As noted previously, noise sensitivity was measured using the revised unidimensional 10-item version of Weinstein’s Noise Sensitivity Scale (Kishikawa et al., 2006). This proposed 10-item structure was not represented in these data, χ²(35) = 206.88, p < .001, CFI = .00, RMSEA = .15, CI 90% = [.13, .17]. Subsequently, we tested a shorter five-item version that had been used successfully in previous research (Benfield et al., 2012). However, this version also failed to exhibit satisfactory internal consistency (α = .60) or model fit, χ²(5) = 47.11, p < .001, CFI = .85, RMSEA = .15, CI 90% = [.11, .19], with two of the items accounting for less than 1% of the variance in the proposed model (“I get annoyed when my neighbors are noisy” and “I find it hard to relax in a place that’s noisy”).

Therefore, a new model was identified after deleting low-loading items from the 10-item version. This process resulted in five items that achieved model fit, χ²(5) = 8.77, p < .12, CFI = .97, RMSEA = .06, CI 90% = [.00, .12], although a reliability estimate was not exemplary (α = .65).¹ The consequences of low reliability include increased possibility of Type II error (the factor is underpowered). Consequently, this limitation is acknowledged.

Statistical power

A post hoc power analysis was conducted using G*Power software (Faul, Erdfelder, Lang, & Buchner, 2007). The sample size (N = 236) was used to conduct the analysis for recommended small (r = .10), medium (r = .30), and large (r = .50) correlations at the p < .05 level (see, Cohen, 1988). The evaluation showed that the statistical power for this sample was .46 to detect small effects and exceeded .99 for medium and large effects. The sample meets moderate expectations to detect small effects and high expectations to detect medium to large effect sizes for correlational model estimations.

Bivariate analysis

General cell-phone use

Noise sensitivity was negatively related to only one question pertaining to general cell-phone use: A negative association with a Likert response into how distracting other’s cell-phone use is to them (“Do you find mobile conversations going on around you to be…” r = −.16, p < .002). In other words, the higher a respondent’s NS, the more distracting s/he found others’ cell-phone usage (see Table 1).

Table 1.

Standardized discriminant function coefficients and loadings for general cell-phone use.

Item	Standardized coefficient	Function loading
Do you find mobile phone conversations going on around you to be…^a	.25	.12
Please rate the following locations based on your general willingness to make/return a mobile phone call while in that location:
Private car	−.08	−.16
Public transit	−.24	−.13
Park	−.13	.08
Public sidewalk	.31	.22
Restaurant	−.14	.01
Coffee store	.24	.23
Classroom	−.06	−.01
Church/chapel	.12	.02
Restroom	.45	.23
Theater	−.06	.01
Please rate the following individuals based on your comfort level in ignoring an incoming mobile phone call from them:
Close/best friend	−.04	−.19
Other friend	.13	−.15
Business colleague or classmate	−.31	−.37
Parent	−.96	−.54
Sibling	.61	−.15
Supervisor or boss	−.19	−.37
Stranger	.37	.28

Note. Standardized loadings of note (> .30) are in boldface along with their function loadings.

Response categories were measured on a 5-point scale ranging from extremely distracting to not at all distracting.

Cell-phone use in social settings

For cell-phone use in social settings, individuals higher in noise sensitivity were more likely to engage in privacy behaviors such as moving to a more private area (r = .31; p < .001), turning their backs to others in the area (r = .14; p < .03), and getting off the phone and texting the person back (r = .15; p < .02).

Multivariate analysis of noise sensitivity

To further assess differences between those with higher and lower NS, participants were organized into high and low levels of noise sensitivity using a tertile split. Separate canonical linear discriminant analyses were estimated to examine the between-class variation (i.e., multivariate group differences) concerning linear combinations of items for general cell-phone use, cell-phone use in social settings, and general SMS use.

General cell-phone use

There was one significant canonical dimension in this model, F(36, 410) = 2.12, p < .001; the canonical root was moderate r_canonical = .44 in effect. As presented in Table 1, there were five items with at least moderate strength in potentially distinguishing the levels of NS. Three of the variables were positively associated with the end of the discriminant continuum associated with low noise sensitivity (Table 2). In other words, these participants were more comfortable making or returning a phone call in public places such as public sidewalks or restrooms, and were comfortable ignoring calls from strangers. Two of the variables were associated with individuals exhibiting moderate noise sensitivity, those comfortable ignoring calls from business colleagues, classmates, and parents.

Table 2.

Group centroids on discriminant functions.

Groups	Group centroids for general cell-phone use	Group centroids for cell-phone use in social situations (Dimension 1)	Group centroids for cell-phone use in social situations (Dimension 2)
Low NS	.98	1.56	−.05
Moderate NS	−.45	−.33	−.55
High NS	.08	−.27	.57

Cell-phone use in social settings

The model did an adequate job at distinguishing between high and low noise sensitive participants in regard to mobile phone use in mobile settings, and there were two significant canonical dimensions. In the first dimension, F(60, 372) = 2.27, p < .001, the canonical root was moderate r_canonical = .57 in effect. Fifteen items with standardized coefficients were strong enough to be noteworthy (> .30; see Table 3); however, only one was even moderately associated with either high or low NS. Examining the group centroids (Table 2), we see that one item (“We will develop a closer relationship without our mobile phones on the table”) was associated with the positive end of the canonical continuum, which are those categorized as low noise sensitive.

Table 3.

Standardized discriminant function coefficients and loadings for cell-phone use in social settings.

Item	Dimension 1		Dimension 2
	Standardized coefficient	Function loading	Standardized coefficient	Function loading
If I thought the conversation would lead to a positive business relationship, I would place my phone on the table.	.42	.21	.15	−.21
I would worry about missing a message if my mobile phone was out of sight while we were talking.	−.08	−.12	.05	.03
Having a mobile phone on the table would make it difficult for me to get to know the other person well.	−.40	−.23	−.35	−.16
If I felt the conversation was not going to develop into a friendship, I would place my phone out of sight.	−.19	−.21	−.08	−.14
It would be more difficult to accurately understand my partner if a mobile phone was on the table.	.26	−.02	.42	.08
Placing our mobile phones out of sight would encourage more conversation between the two of us.	.06	.02	−.23	.14
It will be more difficult to become friends if a mobile phone was on the table.	−.30	−.07	.15	.10
It would be easier to build a trusting relationship with the person if my mobile phone was on the table between us.	−.23	−.02	−.39	−.17
My conversational partner would be more likely to accurately understand me if his/her mobile phone was on the table.	.01	.00	.15	−.18
We will develop a closer relationship without our mobile phones on the table.	.43	.31	−.13	.13
If I thought the conversation could lead to a romantic relationship, I would be more likely to put my phone on the table.	.05	−.02	−.10	−.06
Of the following responses, which comes closest to describing your daily mobile phone use in each of the following areas?
Receive text messages	−.63	.07	−.04	.45
Send text messages	.45	.10	.41	.47
Receive tweets	.49	.07	−.27	−.18
Send tweets	−.37	−.00	−.07	−.03
Send pictures/video	−.84	−.06	.23	.40
Receive pictures/video	.99	.09	.36	.41
Play electronic games	−.05	.09	.19	.09
Listen to music	−.08	−.13	−.16	−.15
Download music or other applications	−.42	−.15	−.06	.01
Read online news	.29	.15	−.58	−.38
Seek information via Google or a similar search engine	−.08	−.04	.35	.04
When individuals are on the mobile phone, they sometimes feel a need for privacy. Please indicate how the following behaviors reflect what you would do to indicate that you need privacy during a mobile phone call:
Move to a more private area/place	−.37	−.19	.41	.35
Turn your back to people in the area/your group	−.10	.16	.03	.15
Lower your voice	.48	.16	.15	.27
Tell the person you’ll call them back later	.30	.18	−.10	.22
Try to cover your mouth and/or phone together	−.23	.01	−.09	−.03
Signal that the call will be over in a few moments	.31	.19	.13	.10
Get off the phone and text the person back	.01	.06	−.02	.24
How distracting do you find conversations going on around you when talking on the mobile phone?	−.50	−.18	.02	−.00

Note. Standardized loadings of note (> .30) are in boldface along with their function loadings.

In the second dimension, F(29, 187) = 1.71, p < .01, the canonical root was moderate r_canonical = .46 in effect. There were eight items with standardized coefficients strong enough to be noteworthy (> .30; see Table 3). Five of them were moderately associated with those categorized as highly noise sensitive. In other words, the second dimension suggests that higher tendencies to send and receive text messages and videos, along with having a tendency to move to a private location when receiving phone calls, is associated with those who are highly noise sensitive.

Discussion

Mobile phone use permeates all aspects of our lives—whether at home, at work, or in public. Because noise sensitivity appears to be a stable personality trait associated with a range of attitudes and responses to environmental sounds (Ellermeier et al., 2001), and because mobile phones represent a specialized variable noise source, we chose to address the relationship between noise sensitivity and mobile phone use and behaviors. It appears that cell-phone use does indeed vary according to one’s level of sensitivity, supporting the notion that cell-phone sounds can be considered variable noise along with other environmental sounds such as construction or traffic.

More specifically, primary results suggest that those with higher noise sensitivity are more likely to report mobile phones as distracting, and are more likely to seek privacy from others when receiving a call by moving to a private area, turning their backs to others, or ending the call and texting rather than talking. In addition, it appears that those with higher noise reactivity are more likely to use their phones in general.

While almost everyone reports being occasionally irritated by mobile phone use in public spaces (Rainie & Keeter, 2006), our results suggest that noise sensitive bystanders find mobile phone conversations annoying. As a social interaction, mobile phone conversations result in a complex communication situation for callers, receivers, and for those around them. Additional stress is added to the situation when attempting to balance the needs of the caller against those of proximate others, while at the same time attempting to balance privacy concerns of all the parties involved (Banjo et al., 2008). The increased need for privacy by sensitive mobile phone users reflects findings from earlier noise sensitivity studies. As previously noted, Weinstein (1978) also reported a relationship between level of noise sensitivity and need for privacy. The relationship here is not as strong as that found in Weinstein’s study. However, our study focused on a more general context, while at the same time attempting to identify specific behaviors more sensitive individuals may utilize when using their mobile phone.

Our findings also reflect studies of noise sensitivity and sensory processing that suggest that those who are more sensitive are also more easily distracted (Gearhart, 2012; Smith & Stansfeld, 1986) as well as those suggesting that noise reactive individuals are predisposed to be more discriminating of environmental conditions and, subsequently, more likely to evaluate them negatively (Miedema & Vos, 2003). It appears, then, that people who are noise sensitive are personally more irritated but also are more conscious of (or sensitive to) the irritation of others. Moreover, research in noise sensitivity and in sensory processing suggests those who are more sensitive may be more affected by moderate and low levels of stimulation, more so than nonsensitives (Aron & Aron, 1997; Ellermeier et al., 2001; Gearhart, 2012, 2014). These individuals experience deficits in cognitive processing while aroused and are therefore less able to concentrate on immediate tasks or conversations (Smith & Stansfeld, 1986). Thus, seeking privacy may reflect the need of more sensitive interlocutors to remove themselves from an overly arousing situation.

Our findings suggest that noise reactive interlocutors are more attuned to mobile phones. Interruptions and distractions have the potential to negatively affect the natural or smooth flow of a conversation (Cegala, 1981). It may also negatively affect altercentrism (i.e., other-orientation; Cocker & Burgoon, 1987). Thus, mobile phone noise may adversely affect noise sensitive persons’ cognitive involvement, subsequently interfering with their mental participation in an interaction. In other words, mobile phone distractions may have a greater effect on the ability of a noise reactive individual to focus on a conversational partner. Notably, these individuals were more likely to seek privacy from others when receiving a call. Seeking privacy, as a general behavior, allows them to focus greater attention on the incoming call.

These behaviors suggest an additional area of study. Are those who are more sensitive to noise more likely to attempt to reduce the noise in their lives? Will they reduce the volume on their mobile phone? Be less likely to make voice calls and more likely to text? Our study was not designed to specifically address these questions. However, as seen in Table 3, the findings do suggest that noise sensitive respondents engaged in “quieter” activities.² Texting others reduces the ambient noise level that could make it more difficult to focus in conversations with others. Removing oneself to a more private area accomplishes the same goal.

Of course, the associations reported between noise sensitivity and the two variables measuring distraction were small in effect (i.e., r = −.16, p < .002 for both). These low associations suggest that while noise sensitivity may be a stable personality characteristic, context plays a greater role than previously believed in an individual’s evaluation of annoyance. Stronger relationships between sensitivity and annoyance levels were found in both the Kjellberg et al. (1996) and the Benfield et al. (2012) studies. Kjellberg et al. (1996) reported higher levels of annoyance with telephones in a work environment, while Benfield et al. (2012) reported that individuals with higher noise sensitivity were less accepting of personal electronic devices in a national park setting. In fact, Smith (2003) argues that context is key when assessing the influence of noise sensitivity. Thus, while those who are noise sensitive may have some level of negative affect in their general judgements of mobile phone noise, this negative attitude may be further emphasized by contextual cues.

Conclusion

As we conclude this article, we note three limitations and provide directions for future research. The first limitation is reliance on self-report data of mobile phone use. As a result, there may be some differences between individual survey responses and actual mobile phone behaviors. Second, as noted earlier, the reliability estimates of the noise sensitivity measure were less than desired. While a number of versions of noise sensitivity measures have been proposed and continue to be tested (see Benfield et al., 2012; Mulgrew, 2013), in many noise sensitivity studies results of reliability tests are not provided. We encourage researchers to provide reliability information on the instrument they choose to use. Our third limitation addresses the relationship between negative affect and noise sensitivity. Several studies have reported positive associations between noise sensitivity and individual characteristics such as introversion, anxiety, and negative affect (see Ellermeier et al., 2001; Miedema & Vos, 2003; Öhrsröm, Björkman, & Rylander, 1988). We suggest future studies assess these and related individual differences in order to better understand how each may uniquely contribute to mobile phone attitudes and behaviors. Such an understanding will aid in the development of more sophisticated theoretical models of mobile phone use. For example, the theoretical model of mobile phone use introduced by Banjo et al. (2008) suggests that our social interaction with proximate others are mediated by an obligation to others and a presumption of privacy. It is unclear, however, what effect individual differences may have on the choices mobile phone users make as they seek to balance privacy concerns and their obligations to others.

In addition to the previously proposed questions, we suggest that future studies examine the role of environmental control (Stansfeld, 1992). Does removing oneself from the immediate environment and use of SMS reflect an aspect of environmental control? Previous research suggests that perceived control over noise and the predictability of noise significantly contribute to the effects and after-effects of noise exposure (Glass & Singer, 1972; Smith, 2003). Thus, the privacy behaviors identified in this study may be an attempt by noise sensitive mobile phone users to have greater control over their environment.

Second, if, as suggested by Smith (2003), context plays a significant role in how sensitive individuals respond to noise, then a greater understanding of the role of context on assessment of noise is needed. Other mobile phone studies have found context affects perceived acceptability of mobile phone use (Campbell, 2007; Worthington et al., 2012). Does context affect perceptions of noise sensitivity? Will highly sensitive persons react differently depending on the context?

Finally, future study should expand on the relationship between noise sensitivity and communication behaviors such as sensory processing sensitivity and interaction involvement. For example, low interaction involvement and high noise sensitivity have been linked to negative affect. Sidelinger, Ayash, Godorhazy, and Tibbles (2008) suggest that low interaction involvement results in a self-centered focus, while high interaction involvement leads to proactive, other-oriented behaviors. Thus, individuals who are lower in interaction involvement may face greater conversational challenges if distracted by mobile phone use and noise around them. Similarly, Gearhart (2012) found highly sensitive individuals to be more distracted by audio stimulation, especially intermittent audio sounds. Intuitively, it would seem that noise sensitivity would be related to sensory processing sensitivity, but additional study is needed to confirm this possible relationship and to explore the potential association between noise sensitivity, interaction involvement, and other related communication measures.

Footnotes

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Notes

Author biography

Debra L. Worthington (PhD, University of Kansas) is Associate Director of Communication in the School of Communication & Journalism at Auburn University. Her research falls into two broad categories: psycho-social and communication processes that affect courtroom communication and individual factors that affect listening and information processing. She is a past president of the International Listening Association and previously served on the Board of Directors of the American Society of Trial Consultants. She is a past recipient of the Burton Award for Legal Achievement and has won numerous research awards from international and U.S. organizations including: the International Listening Association, the National Communication Association, the Southern States Communication Association, and the Eastern Communication Association. She has published numerous peer-reviewed articles, coauthored the textbook Listening: Processes, Functions & Competency, and is currently working on an edited volume—the Sourcebook of Listening Methods and Measures (anticipated in 2016).

Shaughan Keaton, PhD, is Assistant Professor of Communication Studies at Young Harris College. He specializes in social psychology and sport communication, listener goals and communicator styles, and intergenerational/intercultural communication. Broadly, his research profile can be described as interpersonal interaction and cognition and various aspects of intercultural interaction. Shaughan is a recent recipient of the Hewlett-Mellon Research Grant and is a co-editor of the book, The Influence of Communication in Physiology and Health. He is also a member of the editorial boards for the International Journal of Listening and Imagination, Cognition and Personality. Shaughan’s recent articles have appeared in journals such as Communication Quarterly, Southern Communication Journal, Sport Marketing Quarterly, and Educational Gerontology.

Margarete Imhof (PhD 1995, Bamberg, Germany) is full Professor for Educational Psychology at Johannes Gutenberg University, Mainz, Germany. Her research interests are – among others – in listening to both relevant and irrelevant sound.

Tuula-Riitta Välikoski (M.Sc.Admin., University of Tampere, 1979; Ph.D. University of Tampere, 2004), is Adjunct Professor of legal communication at the University of Eastern Finland and Assistant Professor of Speech Communication and Vice Chair of the Board in the School of Communication, Media and Theatre at the University of Tampere. Her research interests are in the areas of listening, social interaction and professional communication particularly in the legal context. Her articles have appeared in national and international journals including the Prologi (Speech Communication Yearbook), Oikeus (the Justice), Defensor Legis, the International Journal of Listening (IJL) and the Empedocles: European Journal for the Philosophy of Communication. She served as the first editor-in-chief of the Prologi, 2005–2007, and is current member of the editorial board of IJL 2012. She is a member of NCA, ICA, ILA and ECREA and has chaired the Research Committee of ILA. Currently, she is Vice Chair of the ECREA section of Interpersonal Communication and Social Interaction and of PROLOGOS (Finland’s Speech Communication Association).

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