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Psychological Effects of Classroom Noise on
Early Childhood Teachers
Leonid Grebennikov and Mark Wiggins
University of Western Sydney
Abstract
The aim of this research was to examine the relationship between exposure to
classroom noise and the psychological well-being of full-time teaching staff in 14
preschool settings located across Western Sydney. The participants comprised 25
teachers, each of whom was administered a range of instruments. The results
indicated that 40% of teachers were subjected to daily or peak noise exposures beyond
the maximum permissible levels according to the Australian Occupational Health and
Safety (OH&S) standard. Further, the unique contribution of daily noise dose received
by the staff to the prediction of their vocational strain, interpersonal strain, and
defensive functioning was evident through multiple regression analyses. It was
concluded that vocational strain amongst preschool teachers may be related, in part,
to a combination of elevated daily doses of noise, and years of teaching experience.
Introduction
A number of contemporary studies concerning noise in early childhood educational
settings have established its detrimental effects on both students and teaching staff
(e.g., Baxter 2000, Maxwell & Evans 1999, Nelson & Soli 2000, Sorkin 2000).
Understandably most of these projects have focused on children, as they are more
vulnerable to long-term health, psychological, and educational impairments created
by classroom noise than are adults (Evans & Lepore 1993, Evans & Maxwell 1997,
Nelson & Soli 2000). However, McLaren and Dickinson (2002) have found that
exposure to noise is also a problem amongst early childhood teachers with 30% being
exposed to noise in excess of the maximum permissible level under New Zealand
standards.
•35
The Australian Educational Researcher,Volume 33, Number 3, December 2006
The Australian standard for exposure to noise in the occupational environment is
consistent with that enacted in New Zealand: An average of 85 decibels (dB) for an
eight-hour day, and 140 dB for peak noise level. Comparable common noise sources
falling within the range of 85-140 decibels are: A handsaw – 85; A subway – 90-110;
A rock concert – 110-120; Noisy squeeze toys – 135; An ambulance siren – 140. It is
important to note that these levels specify maximum permissible exposure within the
workplace. Repeated exposure to lower levels of noise may also cause hearing
damage over the longer term (American Speech-Language-Hearing Association 2004,
National Code of Practice for Noise Management and Protection of Hearing at Work
2000).
In addition to the physical damage caused by exposure to excessive noise, continued
exposure has been associated with elevated levels of stress, high anxiety, increased
annoyance, depression, and fatigue (Doherty 1999, Evans & Johnson 2000, Glass &
Singer 1972, Kalveram 2000, Kryter 1994). Stress, in turn, has been observed as
contributing to a number of psychosomatic conditions, including asthma, digestive
tract disorders, heart diseases, migraines, chest and back pain (Bacon et al. 1994,
Barsky 1988, Doherty 1999, Donoghue & Siegel 1994, Galloway, Panckurst, Boswell,
Boswell & Green 1984b, Maddi & Kobasa 1984, Romanova & Grebennikov 1996,
Wilder & Plutchik 1984). Hans Selye, whose research first demonstrated that the
continuing presence of stressors modified the immune system, labelled these
conditions “diseases of adaptation” (Selye 1956). Unsurprisingly, stress has been
shown to disrupt both workers’ performance (Evans & Johnson 2000) and their job
satisfaction (Galloway, Panckurst, Boswell, Boswell & Green 1984a).
While teaching, in general, is currently considered a very stressful occupation (Finlay-
Jones 1986, Hodge, Jupp & Taylor 1994, Jarvis 2002, Pithers & Fogarty 1995, Smith,
Brice, Collins, Matthews & McNamara 2000, Wilhelm, Dewhurst-Savellis & Parker
2000), an analysis of the literature reveals that little or no attention has been
specifically directed towards early childhood teachers’ stress and its sources.
Anecdotal evidence appears to suggest that much of employee “burnout” and
turnover in the Australian early childhood workforce can be attributed, at least in part,
to job strains and the nature of the working environment. For example, working
conditions and the intensity of the workplace were cited by the respondents to a New
South Wales (NSW) Childcare Workers’ survey as their second most significant
concern following wages (Warrilow, Fisher, Cummings, Sumsion & Beckett 2002).
Many teachers appear worried about the impact of noise on their hearing, as they
often report going home with “ringing ears”. Indeed, school boards are becoming
increasingly concerned about the relationship between noise and the performance of
both teachers and their students.
36 •
LEONID GREBENNIKOV AND MARK WIGGINS
It is reasonable to assume that the relationship between classroom noise and teachers’
stress is a complex interaction of factors (including, for example, teaching experience
or age), rather than a single causal link. If this is the case, then it is important to
investigate whether and, to what extent, these factors contribute to employees’
perception of stress in the targeted industry sector.
Since noise in early childhood settings is a potentially continuous stressor, and there
is little opportunity to mitigate either the sources of noise or its impact, teachers have
to reconcile themselves to it if they wish to remain within the industry. We supposed
that a so-called “buffer” or “ostrich” psychological adaptation strategy would be
mainly in use. This strategy implies the creation of a mental “barrier” between the
individual and the stressful environment to prevent the full effects of the stressor
being experienced. The perceptual defence mechanism of denial is one possible
psychological technique to implement this strategy (e.g., Conte & Apter 1995, Plutchik
1995, Plutchik, Kellerman & Conte 1979). Denial is presumed to assist an individual
avoid awareness of unwelcome reality and, in this sense, it is likely to be used to
“block out” both recognition of being under stress and the awareness of its source.
Plutchik, Kellerman, & Conte (1979) found an interesting difference between denial
and other defence mechanisms. The use of denial correlated negatively with
perceived stress and anxiety, while all other defence mechanisms showed positive
correlations with stress. Therefore, on the one hand, the stressful environment can
enhance the use of denial alongside other defence mechanisms. On the other hand,
denial is the only defence with a “back action”, such that it can considerably dampen
one’s conscious perception of the stressor (Evans & Johnson 2000, Plutchik,
Kellerman & Conte 1979). On the basis of this perspective, two models were
proposed for evaluation. First, we sought to test whether the set of the objective
variables: Noise exposure, age, and length of service plus denial contributed to a
prediction of perceived stress. It was expected that denial would be negatively related
to self-reported measures of stress, while the objective variables would be positively
related to the stress parameters. Second, we tested the combination of the objective
variables and stress measures as the basis of a prediction of the overall use of defence
mechanisms.
In summary, the present research was designed to examine: (1) The level of
occupational noise, to which early childhood teachers are exposed, and (2)
employees’ perceived stress and the defence strategies they implement, if any, to
manage the situation. Our principal concern was to examine an under-studied group
of professionals at potential risk, with a focus on their exposure to noise,
psychological well-being, and possible exposure-outcome relationship. It was
hypothesized that a statistically significant, positive linear relationship would be
evident between the level of noise to which early childhood teachers were exposed
•37
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
and their scores on various psychological measures, including personal strain, chronic
and recent distress, and the use of defence mechanisms.
Method
Participants
Data were collected from 25 full-time teaching staff located at 14 preschools across
Western Sydney and operated under the auspices of the New South Wales
Department of Education and Training. Full-time employees were selected for testing,
since it was assumed that this group would experience noise over relatively longer
periods than other staff (McLaren & Dickinson 2002). All the participants were female.
Their mean age was 42.7 years (SD = 9.7), and they had accumulated an average of
13.9 years (SD = 8.5) of teaching experience. The student to teacher ratios were 10:1
for 16 participants (64%), 11:1 for two participants (8%), and 12:1 for seven
participants (28%).
Noise Assessment
The initial stage of the study involved an assessment of the daily noise exposure for
full-time teaching staff members, taken as an average eight-hour equivalent sound
pressure level, and peak sound pressure level. The ambient noise level was
monitored using a high-quality personal sound exposure meter “Casella”, model CEL-
310/K1, which is designed to meet the standards of the National Code of Practice
(2000). The data collected included:
• The average sound pressure level throughout a trial period;
• An eight-hour equivalent sound level (i.e. average level throughout a trial period
projected over eight hours);
• The dose% (the amount of actual exposure relative to the amount of allowable
exposure for which 100% and above are hazardous);
• The peak sound pressure exceedence; and
• Event and time history.
The estimation of noise level, projected over eight hours, was used as it standardized
the exposure received by participants during the approximately six hours of actual
working time, assuming that the remainder of the eight-hour reference period was
quiet. This enabled comparisons between individual exposure rates and with the
OH&S eight-hour standard (see Figure1).
38 •
LEONID GREBENNIKOV AND MARK WIGGINS
Figure 1: Individual recorded and projected noise exposure
Peak noise exceedence
•39
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
110
108
106
104
102
100
98
96
94
92
90
88
86
84
82
80
78
76
10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM
Time hh:mm
LAeq dB
Peak noise exceedence
9:45am
Recorded exposure
over 6 hrs = 85.8 dB
Projected exposure
over 8 hrs = 84.6 dB
Instruments
The second stage of the study involved the distribution of a series of psychological
instruments, including the Personal Strain Questionnaire (PSQ), which was a part of
the Occupational Stress Inventory revised edition (Osipow 1998); the General Health
Questionnaire (GHQ-60) (Goldberg & Williams 1991); and the Life Style Index (LSI)
defence mechanisms test (Plutchik, Kellerman & Conte 1979).
The PSQ consists of four subscales. According to Osipow (1998), the vocational strain
scale assesses job attitudes and perceived performance; the psychological strain scale
assesses the degree of one’s psychological adjustment and mood problems; the
interpersonal strain scale assesses the extent to which interpersonal relationships are
disrupted; and the physical strain scale assesses worries about one’s health and poor
self-care habits. Each scale contains 10 items. A five-point (1-5) Likert-style scale is
used by respondents to rate their level of agreement with a given statement
(rarely/never, occasionally, often, usually, most of the time). Normative data obtained
from samples of 364 female and 619 male adults is available as T-scores with a mean
of 50 and a standard deviation of 10. A mean value for Cronbach’s alpha of .94 is
reported for this instrument.
The GHQ-60 is an unscaled, single-score screening test that focuses on emotional
distress and social dysfunction. Goldberg and Williams (1991) suggest that these
dimensions should be examined through an emergence of various minor somatic
symptoms and changes in social behaviour. The questionnaire contains 60 items,
which respondents are asked to rate, using a four-point scale, as applying to their
perception of their current condition (better than usual, same as usual, worse than
usual, much worse than usual). Three types of scoring can be used to interpret the
scale: Likert (0-1-2-3), GHQ (0-0-1-1), understood as a recent distress score, and
CGHQ (0-1-1-1) for negative items and (0-0-1-1) for positive items, understood as a
chronic distress score. The thresholds identifying respondents with severe
psychological distress not only vary with the scoring method, but also across
populations. The GHQ and CGHQ scoring methods were employed in the present
research. The GHQ scoring method was selected because it had been used in various
studies reporting a stable cut-score of 11/12 (Goldberg and Williams 1991). A score >
12 identified individuals who were likely to have experienced distress of late. The
CGHQ scoring method was used, as it tends to produce a less skewed distribution.
This is useful for parametric analyses and, as some studies have shown, it also tends
to increase sensitivity of the instrument (Goldberg & Williams 1991, Finlay-Jones
1986).
The LSI defence mechanisms measure was developed on the basis of psychoanalytic
theory and empirical research (Conte & Apter 1995, Plutchik, Kellerman & Conte
40 •
LEONID GREBENNIKOV AND MARK WIGGINS
1979). Its 97 items are grouped into eight scales: compensation (including
identification and fantasy), denial, displacement, intellectualisation (including
sublimation, undoing, and rationalization), projection, reaction formation, regression
(including acting out), and repression (including isolation and introjection). Each
scale contains from 10 to 14 items describing feelings, ideas, and behaviours that are
presumed to represent the eight defence mechanisms. For each item, respondents are
asked to indicate whether it is usually true for them by checking “Yes” (1) or “No”
(0)”. A total score on the use of defences can also be calculated. Normative data
derived from a sample of 147 adults is available as both percentiles and T-scores with
a mean of 50 and a standard deviation of 15. The variation in Cronbach’s alphas for
the scales (range = .30 to .86) the authors explain by the fact that some scales are, by
design, multidimensional as are the defences they represent. In order to combine
several concepts or clusters of items into a single scale a certain amount of internal
consistency for that scale had to be sacrificed.
The three standardized self-report instruments represent methodologically different
approaches to the assessment of perceived stress. While the PSQ items are mainly
unambiguous statements relating to feelings and behaviour under stress (“I make
errors or mistakes at my work”; “Lately I am easily irritated”; “I have troubles falling
and staying asleep”), the GHQ and LSI items are less explicit. Respondents are not
always consciously aware that they are under stress. For example, Evans & Johnson
(2000) have found that individuals in noisy settings do not necessarily report greater
levels of stress than those in relatively quiet settings, while physiological tests suggest
that there is a stress-related response.
In comparison to the PSQ, the GHQ tends to focus, to a greater extent, on somatic
symptoms associated with psychological disturbance (“Have you recently been
getting a feeling of tightness or pressure in your head?”; “Have you recently been
sweating a lot?”). Scores on a shortened version of GHQ have been predicted by
teachers’ distress and job dissatisfaction (Galloway et al. 1984a, Finlay-Jones 1986).
If stress is constant and it is not possible for a person to exercise control over it, there
is evidence to suggest that they need excessive recourse to psychological mechanisms
to ward off unacceptable feelings (Conte & Apter 1995, Doherty 1999, Evans &
Johnson 2000, Plutchik 1995). Items of the LSI test are constructed allowing for the
fact that “most individuals can report their own feelings and can describe behaviour
that reflects their own ego defences, even though they cannot interpret the dynamic
meanings of such behaviour” (Plutchik, Kellerman & Conte 1979, p.236). (For
example, “I am free of prejudice”, representing denial; “I believe people will take
advantage of you if you are not careful”, representing projection; “I get irritable when
I don’t get attention”, representing regression.)
•41
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
Participants also completed a background data sheet that, apart from the demographic
details, contained a multiple-response, open-ended question concerning the main
sources of noise in their classroom(s). The respondents were not asked to rate these
sources.
Procedure
The preschools were visited to monitor participants’ noise exposure, to keep a log to
relate the data to actual sounds and activities, and to administer the questionnaires.
Measurements of noise exposure were conducted by fitting a personal sound
exposure meter (dose badge) to staff members for the duration of their working day.
Staff noise exposures were automatically logged by these means starting from 8.45-
9.00am when direct supervision began, throughout morning sessions (9.00am to
11.30am), lunch breaks, afternoon sessions (12.30pm to 3.00pm), and ending at
approximately 3.15pm when all students were picked up. This totalled 5-5.5 contact
hours and about 6 hours of monitoring time overall. The monitoring was conducted
on regular, ordinary days in the absence of any special events or outings, and the
questionnaires were administered out of hours. All responses were treated
confidentially.
Results
Noise Exposure
Of the 25 preschool teaching staff monitored, the highest individual noise exposure
levels were 85.0, 85.1, 85.8, and 86.1 dB during the six-hour workday. These values
were projected over eight hours, assuming that the remainder of the eight-hour
reference period was quiet, and resulted in daily equivalent exposures of 84.1, 84.2,
84.6, and 85.3 dB respectively. Thus, one teacher exceeded the Australian OH&S limit
of 85 dB and three staff approached this limit. These exposures corresponded to 70-
103% of the noise dose that is considered harmful. Nine staff recorded peak noise rates
that exceeded the maximum permissible level of 140 dB for peak noise. In total, 10 of
the staff evaluated were subjected to noise beyond the maximum acceptable levels
under Australian standards. Twenty-three teachers were subjected to daily noise
exposure over 75 dB. In the process of data screening, it was found that the peak noise
recorded by the badge was, in some cases, an artifact due to knocking the microphone.
Consequently, we disregarded five of the fourteen peak noise cases where the data
were inconsistent with the nature of the activities being observed or recorded at the
time. The other nine cases were considered accurate reflections of the actual noise
being experienced at the time, for example, while a staff member was comforting a
distressed student screaming close to the ear of the teacher (see Figure 1).
42 •
LEONID GREBENNIKOV AND MARK WIGGINS
The lowest levels of noise exposure recorded amongst all of the preschools were 73.9
and 74.3 dB over an eight-hour equivalent period, or 6% and 8% of the maximum
noise dose respectively. In each case, the students were put to sleep for 1-1.5 hours
after lunch, while the teachers moved to another room, completing paperwork and
overseeing the students through a window. Table 1 summarises the descriptive
statistics relating to the daily noise exposure for the overall sample, and for the sub-
samples of teachers whose average daily noise exposures were under or above 80 dB.
The distinction of 80 dB was made based on the principle that sounds louder that 80
dB are potentially hazardous (American Speech-Language-Hearing Association 2004).
Table 1
Descriptive Statistics on Staff Daily Noise Exposure: Overall Sample, Higher
and Lower Exposure Rates Subsamples
The log of events and activities associated with the measurements indicated that the
highest levels of noise were recorded when a large number of students were located
in a confined space such as the free-play area, when they were fighting over
playthings, or when the students were involved in rough play. High levels of noise
were also evident when students were distressed, when they dropped heavy play
equipment, and during music time, when the students were playing instruments.
From the teachers’ perspective, the main causes or sources of noise (most teachers
noted more than one source) in their classrooms included:
• Poor weather, which kept students indoors (10, 20.8% of all responses);
• Insufficient space, such as a confined indoor area (8, 16.6%);
• A resonant floor, furniture, and/or play equipment (e.g., wooden blocks) (6,
12.5%);
•43
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
Overall group
(
N
= 25)
High exposure
subsample (
n
= 12)
Low exposure
subsample (
n
= 13)
Noise parameters
Recorded dB
Projected (standardized) dB
Dose %
Peak sound
exceedence cases (%)
SD
3.24
3.22
25.72
SD
3.46
1.89
23.79
SD
4.31
1.69
6.12
M
80.48
79.41
33.28
9 (36.00)
M
83.65
82.17
53.25
6 (50.00)
M
77.75
76.87
14.85
3 (23.07)
• Distressed students (6, 12.5%);
• Outside noises from traffic or a nearby school (5, 10.4%);
• Over-exuberant students or those with behavioural problems (4, 8.3%);
• Noisy indoor activities (e.g., assemblies, music, bells) (4, 8.3%);
• Air conditioners (4, 8.3%); and
• Alarms sounding on exit doors (1, 2.1%).
The time histories also suggested that afternoon sessions were generally as noisy as
morning sessions, and that noise levels did not always decrease during lunchtime.
Anecdotal reports from two staff revealed that the staff rooms in which they had lunch
were as noisy as the classrooms (e.g., see Figure 1).
Psychological Instruments
Table 2 lists the mean scores and standard deviations for the four scales, distributed
across all participants, and across high and low exposure subsamples (defined as
above or below 80 decibels). In the case of the Personal Strain Questionnaire (PSQ)
and the eight scales of the Life Style Index (LSI), the data are expressed in terms of
T-scores (female normative sample and generic norms respectively). In the case of the
General Health Questionnaire (GHQ), two scoring methods were used (chronic
distress and recent distress). The GHQ (recent distress) scoring method was used to
determine the number of participants per group who exceeded the cut-score of 11/12.
Data for the remaining instruments were distributed normally.
To determine whether differences between participants’ scores were evident on the
basis of noise exposure, an independent t test was conducted with high and low
levels of noise exposure as the independent variable. Although the sample sizes were
limited, the t test was still considered more informative than a simple visual display
of the mean scores. The results indicated that, in comparison with participants in the
low noise exposure subgroup, participants in the high exposure subgroup obtained
significantly higher scores on the interpersonal strain dimension of the PSQ (t(23) =
2.12, p = .04), and the regression and displacement dimensions of the LSI (t(23) =
2.17, p = .04; t(23) = 2.56, p = .02). No significant differences were evident for the
remaining dimensions of the instruments. The participants in the high noise exposure
subgroup recorded higher scores on the chronic distress dimension of the GHQ than
those in the low exposure subgroup, although it should be noted that the difference
was not statistically significant (t(23) = 1.76, p = .09).
44 •
LEONID GREBENNIKOV AND MARK WIGGINS
Table 2
Descriptive Statistics: Overall Sample, Higher vs. Lower Exposure Rates
Subsamples. Participants Exceeding the GHQ Threshold
On 11 of the 13 variables, the scores pertaining to the high exposure subsample were
greater than those of the low exposure subsample. Effect sizes were from .46 to .67
for the strain indicators, and from -.11 to .76 for the defence mechanism indicators.
•45
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
Overall group
(
N
= 25)
High exposure
subsample (
n
= 12)
Low exposure
subsample (
n
= 13)
Subscales
PSQ
Vocational strain
Psychological
strain
Interpersonal
strain
Physical strain
LSI
Denial
Repression
Regression
Compensation
Projection
Displacement
Intellectualisation
Reaction
formation
Defence total
GHQ
Chronic distress
score
Recent distress:
cut-score
exceedence
cases (%)
*
p
<.05
SD
8.68
7.31
8.48
8.61
12.70
11.64
14.14
14.87
14.12
7.33
15.68
15.91
6.59
11.54
SD
10.56
7.42
7.79
9.69
11.87
10.87
16.99
17.62
13.78
8.61
16.08
17.41
6.93
13.85
SD
6.11
6.11
8.04
7.05
13.84
12.74
8.19
12.38
14.99
3.96
15.91
15.06
6.27
7.66
M
44.92
46.00
45.76
46.04
60.72
42.88
36.88
39.88
43.64
30.48
48.88
53.96
44.64
15.52
4 (16)
M
47.33
47.92
49.25
48.58
59.83
43.42
42.83
41.42
44.00
34.00
49.67
53.08
46.01
19.58
2 (16.6)
M
42.69
42.69
42.54
43.69
61.54
42.38
31.38
38.46
43.31
27.23
48.15
54.77
43.37
11.77
2 (15.4)
t
1.36
1.28
2.12*
1.45
-.33
.22
2.17*
.49
.12
2.56*
.24
-.26
1.00
1.76
46 •
LEONID GREBENNIKOV AND MARK WIGGINS
Table 3
Correlations of All Study Variables
Variable
1. Noise dose
2. Age
3. Teaching
experience
4. Vocational strain
5. Psychological strain
6. Interpersonal strain
7. Physical strain
8. Chronic distress
9. Denial
10. Repression
11. Regression
12. Compensation
13. Projection
14. Displacement
15. Intellectualisation
16. Reaction formation
17. Defence total
*
p
<.05. **
p
<.01.
1
–
-.22
-.13
.35
.31
51**
.13
.31
-.13
.13
.54**
.13
.07
.45*
.11
.00
.30
2
–
.68**
.09
.23
-.16
-.05
.17
-.11
.06
-.25
-.16
-.00
-.15
.04
.24
-.08
3
–
.32
.25
-.10
-.01
.28
-.27
.07
-.23
-.28
.01
.01
-.35
.30
-.19
4
–
51**
.66**
.43*
.66**
-.24
.26
.41*
.16
.20
.27
-.24
.38
.29
5
–
.55**
.51**
.67**
-.04
.02
.50*
.23
.21
.31
-.13
.13
.29
6
–
.59**
.65**
.03
-.11
.60**
.24
.04
.45*
-.16
.19
.29
7
–
.82**
-.11
-.01
.62**
.59**
.43*
.61**
.19
.17
.61**
8
–
-.25
.13
.57**
.40*
.46*
.66**
.03
.33
.56**
9
–
.11
-.07
-.01
-.25
-.22
-.06
-.09
.10
10
–
-.18
-.08
.19
-.18
-.03
.31
.29
11
–
.61**
.36
.71**
.14
.05
.63**
12
–
.41*
.60**
.43*
-.21
.68**
13
–
.56**
.16
.31
.69**
14
–
.23
.10
.65**
15
–
.01
.51**
16
–
.41*
Effect size for the chronic distress indicator was substantial at .70. However, all scores
of both groups were within normal limits. Overall group T-scores on the PSQ
subscales did not reveal any differences between the teachers and the normative
sample, all being between 44.9T and 46.0T. Four (16%) of all participants exceeded
the GHQ threshold indicating serious psychological distress. The LSI results compared
with the norm group whose means would be around 50T, showed that the
participants in the present study scored higher on denial 60.7T (effect size of .71) and
considerably lower than the norm on displacement 30.4 T (effect size of -1.30).
Pearson product-moment correlations between the scores on the 13 dependent
variables, daily noise dose, age of participants, and years of work experience using
alpha levels of .01 and .05 are shown in Table 3. Statistically significant positive
correlations were evident between noise dose and interpersonal strain (r(23) = .51, p
< .01), the defences of regression (r(23) = .54, p < .01) and displacement (r(23) = .45,
p < .05). Age and teaching experience did not relate significantly to any variables
except to each other, and all measures of perceived stress correlated significantly with
each other. Physical strain and chronic distress also correlated positively and
significantly with four out of eight defence mechanisms: Regression, compensation,
projection and displacement, and with the use of defences overall. The defence
mechanisms of denial, repression, intellectualisation and reaction formation failed to
reach significance in relation to either of stress measures, with denial being the only
defence relating negatively to all stress measures except interpersonal strain.
To test whether the stress parameters could be influenced by various possibly
explanatory variables, we regressed each stress measure on noise exposure, age,
length of service, and denial, using a stepwise procedure. This strategy was designed
to remove “weak” candidate predictors from the models and identify “stronger”
predictors, if any existed. Due to the limited sample size, two predictor variables at a
time were tested for their effect on each response variable consecutively. Table 4 lists
those stress measures which appeared to significantly relate to the predictors:
Vocational strain and interpersonal strain. The best prediction of vocational strain was
achieved by the combination of noise dose and teaching experience. Noise dose
emerged as the only significant predictor of interpersonal strain. Neither denial nor
age contributed to the prediction of the stress measures.
An analogical stepwise procedure was used to relate the overall use of defence
mechanisms to the objective variables and the measures of perceived stress. The best
sets of predictor variables were selected with the order of stepping specified by the
procedure. The results indicated that the combination of physical strain and noise
dose accounted for 42% of the variance in the total use of defence mechanisms (See
Table 4). Age, vocational strain, interpersonal strain, psychological strain, and chronic
•47
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
distress failed to contribute significantly to the prediction of the overall use of defence
mechanisms.
Table 4
Stepwise Regressions of Outcomes on Noise Dose, Teaching Experience,
and Stress Measures
Discussion
The initial aim of this study was to explore the extent of classroom noise in preschool
facilities of Western Sydney in relation to the Australian OH&S standard. The results
revealed that 10 of 25, or 40% of the monitored teaching staff were exposed to daily
or peak noise rates in excess of the Australian standard for exposure to noise in the
occupational environment. More particularly, one teacher exceeded the daily limit of
85 dB eight-hour equivalent, and nine staff exceeded the 140 dB limit for peak noise
level. Three staff recorded values that approached the OH&S daily limit, and 23 or
92% of teachers were subjected to daily noise exposure of over 75 dB eight-hour
equivalent. According to the National Code of Practice, if exposure to these noise
levels occurs repeatedly, it may have adverse effects on the health and well-being of
some workers.
Despite the evidence of excessive noise exposure, the outcomes of the present
research should not be considered conclusive, since a convenience sample of a
limited size was investigated. Nevertheless, two facts support extrapolation of the
findings to a sizeable proportion of Western Sydney early educational facilities. First,
the sample was derived from schools of diverse size and socio-economic
48 •
LEONID GREBENNIKOV AND MARK WIGGINS
R
2
.124
.260
.266
.372
.420
R
2
change
.124
.136
.266
.372
.048
F
3.252
3.875
8.332
13.618
7.952
p
.084
.036
.008
.001
.003
Criteria/Predictor variables entered stepwise
Vocational strain
1. Noise dose
2. Teaching experience
Interpersonal strain
1. Noise dose
Defence total
1. Physical strain
2. Noise dose
characteristics distributed across an area of approximately 160 square kilometres.
Second, anecdotal reports from many teachers revealed that the monitoring days were
quieter than usual and no-one suggested otherwise. Conducting more than one
monitoring session per participant may be useful in future studies as a more reliable
method of evaluation of typical noise exposure.
Importantly, the results pertaining to noise exposure that were obtained in the present
study were consistent with the results of a similar study in New Zealand (McLaren &
Dickinson 2002). Therefore, it might be argued that the results reflect a much broader
issue across developed nations in which early childhood education is an established
practice. Further research concerning noise in all types of early educational settings,
and across different nations, may be valuable in understanding both the scope of the
problem and possible remedies. For example, a larger per-person area in the
classroom might assist to avoid crowding and conflicts and, thereby, may reduce
noise. Sound-absorbing floor, acoustic ceilings and windows, sound dampers on
furniture legs, and the careful selection of low-noise play equipment may also reduce
exposure for both staff and students. Some of these measures would be less costly
than others and could easily be put into effect at the school level, while others may
require policy decisions.
The second aim of the present research was to investigate preschool teachers’
perceived stress and its relationship to classroom noise. No significant differences in
levels of personal strain were evident between the teachers and the PSQ normative
sample. The teachers’ mean scores (converted to T-scores) were similar to the norms
for all four subscales. Further, the PSQ mean scores obtained in the present research
showed no prevalence over the corresponding means of 37 Australian non-teaching
female professionals (Pithers & Fogarty 1995). This implies that, on the average, the
preschool teachers feel personal strain similarly or less than the community generally.
At the same time, 16% of respondents scored above the GHQ threshold, indicating
severe psychological distress. This compares with 9% for the general Australian
population cited by Finlay-Jones (1986). Finlay-Jones (1986) also reported that 17% of
Australian teachers, mainly from primary and secondary sectors, exceeded the GHQ
threshold, which is consistent with the outcome of the present research.
The apparent conflict between the PSQ and GHQ scores may have resulted from the
GHQ questions being less explicitly focused on supraliminal stress in comparison to
the questions in the PSQ. Participants may have felt less able to recognise and/or
admit that they were under stress when asked in a straightforward way, but may have
responded more sincerely to less direct questions concerning the subject. The higher
teachers’ T-scores on denial in comparison to the LSI normative sample supports, at
least in part, the assumption that some teachers may be unwilling to recognise that
•49
PSYCHOLOGICAL EFFECTS OF CLASSROOM NOISE
they are under stress. In other words, they may use denial to a greater extent to
control their perception of stress. Contrary to expectations, denial did not show a
significant moderating effect on any of the stress measures. Nevertheless, it was the
only variable of all of the defence mechanisms in which a negative correlation was
evident with the majority of stress parameters.
On 11 of the 13 dependent variables, the scores of the high exposure subsample were
greater than those of the low exposure subsample. Effect sizes indicated that the
strain measures showed larger deviations between groups than most of the defence
measures. Effect sizes may also suggest that the use of particular defence mechanisms
under elevated exposure to noise vary considerably across people, while their
perception of strain reliably increases with the higher exposure rate. Even though all
scores of both subgroups were within normal limits, the results of multiple regression
analyses indicated that the level of daily noise dose predicted subjective perceptions
of vocational strain, interpersonal strain, and overall defensive functioning.
These findings partially confirm the hypothesized relationship between the level of
preschool teachers’ exposure to classroom noise and their perceived stress.
Specifically, statistically significant positive relationship was evident between the
doses of noise to which staff were subjected and the level of interpersonal strain,
understood as a disruption in interpersonal relationships and a tendency to withdraw
from the social environment. Poor job satisfaction, attitudes, and performance, as
attributes of vocational strain, are significantly associated with higher levels of
classroom noise, in combination with longer periods of professional teaching. The
increase in noise dose also appears to be associated with regression and
displacement. These defence mechanisms imply tendencies to retreat under stress to
earlier or more immature patterns of behaviour, such as crying, displaying temper, or
blaming; and/or to discharge pent-up anger on irrelevant objects or people, including
oneself. The last interpretation, however, may not be a valid representation
considering the fact that both the high exposure and the low exposure subsamples
scored well below the norm on displacement. In general terms, the differences
between the high and low exposure subsamples on all defence mechanisms but one
and on their total score suggest that teachers, who are exposed to relatively higher
noise doses, may be more likely to be required to develop stress coping strategies.
It is important to note that noise dose emerged as the second most significant
predictor of total defensive functioning following physical strain. Therefore, it would
appear that the combination of the tiring job and classroom noise may aggravate
teachers’ worries about their physical well-being. This may explain, to some extent,
the relatively greater recourse to psychological defence mechanisms.
50 •
LEONID GREBENNIKOV AND MARK WIGGINS
The results of this study should be interpreted with caution due to a number of
limitations, not least of which is the small sample size. The small size and
convenience character of the sample limited the research power and may have
impacted the reliability of the outcomes. Further, the data on noise were obtained by
means of a single monitoring session per participant during one school term, and thus
may not reflect typical exposure. Finally, only one type of early educational facilities,
allegedly the “quietest” one, was investigated. Nevertheless, the research has
generated important pilot data suggesting a possible association between noise in
preschool settings and stress perceived by the teachers. The outcomes provide the
basis for a broader study to understand and manage classroom noise as an integral
issue in early childhood education. This may include regular monitoring of teaching
staff in all types of early educational settings, and further investigation of all aspects
of noise in these facilities including per-person space in the classroom, the design of
premises, furniture, ventilation, heating, and some educational trends.
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54 •
