Author info: Correspondence should be sent to: Dr. Joseph R. Ferrari, Dept. of
Psychology, DePaul University, 2219 North Kenmore Avenue, Chicago, IL,
North American Journal of Psychology, 2020, Vol. 22, No. 3, 441-454.
The Negative Side of Office Clutter:
Impact on Work-Related Well-Being and Job
Trina N. Dao and Joseph R. Ferrari
Clutter in the home negatively influences a person’s well-being, but this
tendency has not been investigated in workplace settings. The present
study addressed whether office clutter impacted work-place well-being
(job satisfaction, job tension, employee engagement, burnout, and
occupational stress) using a crowd-sourced sample of U.S. adults (n =
290; 177 male, 113 female) employed full-time in office and/or home
settings. It was hypothesized that office clutter would negatively impact
job satisfaction and employee engagement, positively impact emotional
exhaustion and occupational stress, and job-related tension would
moderate the relationship between office clutter and job satisfaction.
Multiple hierarchical linear regressions and a moderated hierarchical
regression analyzed the data and tested the hypotheses. Results showed
that office clutter did predict emotional exhaustion and stress.
KEY WORDS: office clutter, work-place well-being, crowd source
Clutter’s impact is a research topic of interest to psychologists (cf,
Crum & Ferrari, 2019a; Crum & Ferrari, 2019b: Roster, Ferrari, & Jurkat,
2016), extending into the corporate world (Roster & Ferrari, 2020). In
fact, organizations initiated “clean desk policies” of paper and
digitalizing data (Parviainen, Tihinen, Kääriäinen, & Teppola, 2017).
Clutter in the workplace seems innocuous but may impact employee
performance. The National Association of Professional Organizers
(NAPO, 2009) claimed that about 27% of adults feel disorganized while
at work and believe they would save over an hour per day in productivity
if their workspaces were more organized. The Kelton Research for Office
Max found that over half of workers (53%) believed that their motivation
was negatively affected by their own workspace disorganization. A fifth
of the participants also stated that clutter impacted their relationships
with peers and coworkers, and 53% admitted that they have negative
impressions of their coworkers with messy workspaces. Despite these
442 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
statistics and the potential consequences of office clutter, few published
psychological studies supported or challenged survey results.
Clutter is defined as the over-accumulation of material items that
create a chaotic and disorderly space (Roster, Ferrari, & Jurkat, 2016),
and may include possessions that are either commonly used or unused.
Clutter, however, is not to be confused with hoarding, a psychological
disorder recognized by the DSM-5 and ICD-10. Hoarding is an
obsessive-compulsive disorder that involves over-accumulation of the
same types of items, often of little or no worth to the average person, and
in turn leads to unsanitary or dangerous living spaces (American
Psychological Association, 2013). Clutter is not as severe as hoarding
and often involves a wide breadth of items without hygiene implications.
Clutter may also appear outside of the home, particularly in office spaces.
It may even act as a physical stressor in work environments (Roster &
Ferrari, 2020). The present study was an initial step toward
understanding the impact of office clutter among adults employed in
Clutter’s Negative Side
Roster et al. (2016) found that clutter was a result of indecision
(decisional procrastination: see Ferrari, 2010), such that a person
developed clutter because they did not decide which items to keep or
remove. These scholars hypothesized that an over-accumulation of items
may actually impede an individual’s well-being and their connection with
their home environment because of the stress and negative stigma
associated with clutter. Roster et al. found that self-extension tendencies
regarding possessions (a person’s need to self-identify with their material
possessions), and place attachment (how emotionally dependent a person
is on their physical location) had a positive relationship with
psychological home (a person’s desire to self-identify with their home
and physical environment), while clutter had a negative influence on
psychological home and sense of well-being. These findings are the first
to connect physical clutter with a person’s health and well-being,
providing support for their claim that material items may have a profound
impact on a person and their reactions to other stressors.
Crum and Ferrari (2019a) expanded this research by analyzing
whether clutter impacts overall life satisfaction among persons of
different demographic profiles. For instance, they explored whether self-
identified race reported by 99 women of color (M age = 55.33 years old)
might predict how strongly clutter affects their perception of home and
satisfaction. Results showed that psychological home was a significant
predictor of life satisfaction, without place attachment being a moderator
for the relationship between psychological home and life satisfaction. In
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 443
a separate study, Crum and Ferrari (2019b) analyzed the effects of clutter
on psychological home in a sample of young adults (242 women, 82
men; M age = 19 years). They found that the perception of clutter was a
significant predictor of psychological home; young persons who were
less affected by clutter reported a higher sense of psychological home.
Roster and Ferrari (2020) believed that the negative effects of clutter
occurred in work settings. In the first study to look at office clutter, these
researchers crowd-sourced 290 employed adults (109 females; 177
males; M age range = 25 - 35), finding that a heavy workload at a quick
pace was positively related to emotional exhaustion. Emotional
exhaustion depleted energy and made decisional delays more likely.
Indecision then predicted the negative impact of office clutter. Roster and
Ferrari found the relationship between workload and office clutter
partially mediated by the effects of emotional exhaustion and its
consequential impact on decisional delay, as related to clutter.
If clutter in the home influenced a person’s general well-being, then it
may be possible that office clutter affects work outcomes. People spend a
large amount of time at work and in their organization, so their well-
being is not just dependent on their home environments, but their work
life as well. Organizations suffer when their employees are unhealthy,
unmotivated, or performing at a lower level. Identifying a relationship
between office clutter and decreased well-being might potentially inform
practitioners of how to approach the issue of clutter and reduce their
impact on workplace outcomes that may affect profit, employee
motivation, the buildup of slack/extraneous resources, interpersonal
conflict, attitudes about work, and employee behavior. An individual’s
work-related well-being not only impacts their success as an employee,
but it may influence their home life and health as well. Higher levels of
stress or emotional exhaustion may directly harm persons’ health and
make them more susceptible to illnesses, which will also impact
absenteeism and turnover (House, Wells, Landerman, McMichael, &
The present study explored several work-related variables and the
impact of clutter. For instance, employees’ well-being is particularly
important to address in corporate settings (Jackson, Rothmann, & van de
Vijver, 2006; Rothmann, 2008; Warr, 2002). Rothmann (2008)
developed and tested a four-part model of work-related well-being.
Results supported his model; stress and burnout negatively affected well-
being in the workplace while engagement and job satisfaction were found
to positively impact it. Together, job satisfaction, employee engagement,
occupational stress, and burnout are first order factors that create the
construct of work-related well-being (Rothmann, 2008). In the present
study we assessed these employee-related variables impacting office
444 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
clutter, and predicted a positive relationship between office clutter and
emotional exhaustion and stress. We also predicted a negative
relationship between office clutter and job engagement and satisfaction.
Finally, we predicted that job-related tension would moderate the
relationship between office clutter and job satisfaction. Specifically, the
more job-related tension, the stronger the relationship.
Data were previously collected and used in one previous study
(Roster & Ferrari, 2019); however, no previous analyses were repeated;
the present study focused on different variables. Participants were adults
living in the United States, recruited through on-line crowdsourcing
outlet (Prolific Academic: https://prolific.ac), designed to connect
researchers with a quality group of participants based on certain selection
criteria. The number of participants was 290, after excluding ten persons
who did not pass a qualifier and did not pass the attention trap question.
Participants answered “yes” or “no” to a qualifier item, namely: Do you
spend at least 20 hours per week working in an “office” workspace,
meaning a space allocated specifically for you to conduct either self-
employed or employer-related (either profit or non-profit) business
activities? While ‘office’ workspaces might take many forms, we
referred to a traditional office space as at least a desk and a chair
designated for use to conduct work-related activities, whether it be
located in your home or in an office building. Only individuals who
spend at least 20 hours per week in an office workspace were included in
the present study.
From the 290-total number of participants, 51.4% (n = 149) of
participants were aged 25 to 35. Most participants (n = 226; 77.9%) were
Caucasian and male (n = 177; 61.0%). Participants frequently self-
identified (n = 116; 40%) their highest degree earned as a bachelor’s
degree. Just more than half of participants (53.8%) classified their current
job as part of the “professional” or “office manager” sector. The most
commonly reported income was $50,000 to $74,999 (n = 76; 26.2%),
followed by $35,000 to $49,999 (n = 62; 21.4%). In terms of number of
years employed, 98 (27.2%) participants claimed employment for 5 to 10
years, 26.9% for 3 to 4 years, and 24.8% for 1 to 2 years. Most
participants (n = 80; 27.6%) indicated that they held a staff/
administrative position within their organization or worked as an
individual contributor (n = 76; 26.2%). In total, 202 (69.7%) participants
spent most of their time in an office building workspace while the rest
used a home office. Power analyses determined the minimum sample size
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 445
needed to reach a large effect size of f
> 0.35; the present study’s
sample size (n = 290) was sufficient.
Demographic and Work Characteristic Items
All participants completed a set of demographic questions, namely:
age, state of residence, race, income level, level of education, length of
employment, and gender. Participants also indicated whether they did
most of their work from a home office or office building workspace, the
size of their workspace, how cluttered their workspace is, and what types
of clutter they have in their workspace. In addition, respondents
completed general questions about their work, including their position
within the organization, how many hours they work in a typical week,
and their job classification.
Office clutter. All participants completed the 11-item, unidimensional
Office Clutter Impact scale, adapted from the Clutter Quality of Life
Scale (Roster, Ferrari, & Jurkat, 2016) examining the negative impact of
workplace clutter on the individual’s workability of space, emotional
well-being, and social aspect of work. Initial reliability conducted by
Roster et al. on the Clutter Quality of Life Scale showed a Cronbach’s
alpha of .88 (M = 31.55, SD = 15.40) and was validated with the original
sample of 1,349 adults using both exploratory and confirmatory factor
analyses. Reliability analysis conducted for the present study showed an
Omega Hierarchical score of .88 and an Omega Total of .96. Omega
Hierarchical and Omega Total scores test the reliability of scales while
taking into account its multidimensionality. Example items from this
scale include, “I have to move things in order to accomplish tasks in my
office,” and “I feel overwhelmed by the clutter in my office.” Participants
responded by selecting a number on a 7-point Likert scale, from 1
(strongly disagree) to 7 (strongly agree).
Engagement in work. Participants completed the 4-item,
unidimensional Engagement in Work Scale (Britt & Bliese, 2003,
adapted from Britt, 1999). Initial reliability studies conducted by Britt
and Bliese (2003) showed a Cronbach’s alpha of .56 (M = 16.94, SD =
2.44). Reliability analysis conducted for the present study showed an
Omega Hierarchical score of .74 and an Omega Total of .87. Sample
items from this scale include “I feel responsible for my job
performance,” and “I am committed to my job.” Participants responded
by selecting a number on a 5-point Likert scale, from 1 (strongly
disagree) to 5 (strongly agree).
Job-related tension. In addition, participants responded to the revised
Job-Related Tension Index (Wooten, Fakunmoju, Kim, & LeFevre, 2010,
446 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
adapted from Kahn et al., 1964), a 12-item, multidimensional scale
examining job tension related to role ambiguity across three factors –
performance, workload, and organizational design (Wooten et al., 2010).
Initial reliability studies conducted by Wooten showed a Cronbach’s
alpha of .87 (M = 25.06, SD = 9.03). Reliability analysis conducted for
the present study showed an Omega Hierarchical score of .77 and an
Omega Total of .93. Participants responded by selecting a number on a 5-
point Likert scale, from 1 (never) to 5 (nearly all the time).
Emotional exhaustion – burnout. Participants also responded to the 8-
item, unidimensional Emotional Exhaustion subscale from the Maslach
Burnout Inventory (Maslach & Jackson, 1981), which measures how
tired, frustrated, and close to burnout the individual is. Initial reliability
studies by the authors showed a Cronbach’s alpha of .86 (M = 29.70, SD
= 11.93) and internal consistency of the subscale was supported when
tested across occupational groups (Schaufeli, & Bakker, 2004).
Reliability analysis conducted for the present study showed an Omega
Hierarchical score of .88 and an Omega Total of .95. Example items
include “I feel fatigued when I get up in the morning and have to face
another day on the job,” and “I feel used up at the end of the workday.”
Participants responded by selecting a number from a 7-point Likert scale
from 1 (strongly disagree) to 7 (strongly agree). High scores suggest that
the person is experiencing much emotional exhaustion and is close to
Job satisfaction. Ferguson and Weisman’s (1986) unidimensional Job
Satisfaction scale was completed by all participants; a 5-item measure
examining how much an individual likes their job and is satisfied. Initial
reliability studies showed a Cronbach’s alpha of .85 (M = 17.29, SD =
4.46). Reliability analysis conducted for the present study showed an
Omega Hierarchical score of .74 and an Omega Total of .91. Sample
items include “I am satisfied with my daily job routine,” and “In general
I like my job.” Participants responded by selecting a number from a 5-
point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly
Perceived life stress. The 10-item Perceived Stress Scale (Cohen,
Kamarck, & Mermelstein, 1983) measures self-perception of stress.
Initial reliability studies showed a Cronbach’s alpha of .84 (M = 30.11,
SD = 4.62). Reliability analysis conducted for the present study showed
an Omega Hierarchical score of .51 and an Omega Total of .80. Validity
of the scale is evidenced by the association of PSS scores with increased
colds, less control over blood sugar levels in diabetics, more depressive
symptoms elicited by stressful life events, and failure to quit smoking
cigarettes (Cohen et al., 1983). Example items include “In the last month,
how often have you felt that you were unable to control the important
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 447
things in your life?” and “In the last month, how often have you found
that you could not cope with all the things that you had to do?”
Participants responded by selecting a number from a 5-point frequency
scale (1 = Never and 5 = Very Often).
The self-report survey was created on Qualtrics with each scale
placed in counterbalanced order and posted on Prolific Academic for one
day (target sample size = 300 participants). Participants were notified
ahead of time that they would be compensated for completing the survey.
Participants earned $2.60 for filling out the entire survey, and must have
been at least 21 years old and a United States resident. The survey began
with the qualifier question (if the individuals spend at least 20 hours
working in an office), followed by office space questions, the scales, and
lastly, demographic items.
The 130-item survey contained a total of 14 scales but only six key
scales were included in the present study. It took participants
approximately 20-25 minutes to complete the full survey. Once data were
collected, it was examined and cleaned. Individuals with mostly missing
data or failed attention trap questions were deleted.
A hierarchical linear regression assessed whether office clutter
predicted emotional exhaustion, controlling for gender, age, and length of
Table 1: Regression analysis predicting emotional exhaustion from office
Age -0.65 0.52 -0.54 -0.05 0.82 - - -
0.48 0.63 0.34 0.03 0.72 - - -
Model 2 1, 283 13.05 0.16
Gender -0.22 0.82 -0.29 -0.01 1.30 - - -
Age -0.90 0.37 -0.68 -0.06 0.76 - - -
0.38 0.70 0.25 0.03 0.66 - - -
Office Clutter 7.16 0.001 0.30 0.39 0.04 - - -
= 0.15, ΔF = 51.31, p < 0.001; n = 290
448 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
employment. Table 1 showed that gender, age, and length of employment
did not significantly influence levels of emotional exhaustion, but office
clutter did significantly predict emotional exhaustion scores, b = 0.39, t
(283) = 7.16, p < .001. For every one-unit change in office clutter
impact, there was a 0.39 unit increase in emotional exhaustion. Office
clutter also explained a significant proportion of variance in emotional
exhaustion scores, R
= .16, F (1, 283) = 13.05, p < .001. A hierarchical
linear regression assessed whether office clutter predicted perceived
Table 2: Regression analysis predicting stress from office clutter.
Age -0.34 0.73 -0.11 -0.02 0.32 - - -
-0.19 0.85 -0.05 -0.01 0.28 - - -
Model 2 1, 283 14.38 0.17
Gender 0.62 0.54 0.31 0.03 0.50 - - -
Age -0.58 0.56 -0.17 -0.04 0.29 - - -
-0.35 0.73 -0.90 -0.02 0.25 - - -
Office Clutter 7.55 0.001 0.12 0.41 0.02 - - -
= 0.17, ΔF = 57.05, p < 0.001; n = 290
stress, controlling for gender, age, and length of employment. Table 2
showed that stress levels were not significantly impacted by gender, age,
or employment length. However, office clutter significantly predicted
stress scores, b = 0.41, t (283) = 7.55 p < .001. Therefore, for every one-
unit change in office clutter impact, there was a 0.41 unit increase in
stress. Office clutter also explained a significant proportion of variance in
stress scores, R
= .17, F (1, 283) = 14.38, p < .001.
A hierarchical linear regression also assessed office clutter predicting
job engagement, controlling for gender, age, and employment length.
Results showed that office clutter did not significantly predict job
engagement, b = -0.02, t (283) = -0.34, p = .74 (see Table 3).
Subsequently, we examined whether the perception of office clutter
negatively predicted job satisfaction. We explored whether job-related
tension moderated the relationship between the impact of office clutter
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 449
and job satisfaction; that is, is it true that the more job-related tension
there is, the stronger the relationship? A moderated hierarchical
regression assessed whether office clutter predicted job satisfaction, and
Table 3: Regression analysis predicting work engagement from office
Age 0.11 0.91 0.01 0.01 0.17 - - -
-0.35 0.73 -0.02 -0.02 0.15 - - -
Model 2 1, 283 0.42 0.006
Gender 1.11 0.27 0.32 0.07 0.29 - - -
Age 0.12 0.90 0.02 0.01 0.17 - - -
-0.34 0.73 -0.05 -0.02 0.15 - - -
Office Clutter -0.34 0.74 -0.003 -0.02 0.01 - - -
= 0.001, ΔF = 0.11, p = 0.80
whether job-related tension moderated that relationship controlling for
gender, age, and length of employment. Results showed that office clutter
did not significantly predict job satisfaction scores, b = 0.04, t (280) =
0.66, p = 0.51 (see Table 4 at end of article). Results also found that there
was no significant interaction effect between office clutter and any of the
three job-related tension subscales. However, the organizational design
subscale did significantly predict job satisfaction scores, b = - 0.30, t
(280) = - 3.89, p < 0.001. This means that for every one-unit change in
the organizational design subscale, there was a 0.30 unit decrease in job
satisfaction. The organizational design subscale also explained a
significant proportion of variance in job satisfaction scores, R
= 0.21, F
(4, 280) = 10.58, p < 0.001.
The topic of clutter in the home showed a negative relationship
between clutter and a person’s well-being. However, this relationship had
never been studied in workplace clutter and occupational outcomes
(Crum & Ferrari, 2019a; Crum & Ferrari, 2019b; Roster et al., 2016).
There is a construct called work-related well-being (Narainsamy & Van
Der Westhuizen, 2013; Rothman, 2008), consisting of job satisfaction,
450 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
work engagement, burnout, and occupational stress. Previous research
showed that job-related tension may negatively impact job satisfaction
(Bateman & Strasser, 1983). Our study hypothesized that office clutter
negatively impacted job satisfaction and employee engagement,
positively impacted emotional exhaustion and occupational stress, and
job-related tension moderated the relationship between office clutter and
job satisfaction. Using multiple hierarchical linear regressions and a
moderated hierarchical regression (controlling for gender, age, and
employment length) showed that office clutter did predict emotional
exhaustion. As office clutter increased by one unit, so did a person’s
level of emotional exhaustion by 0.39 units. There was also a positive
relationship between office clutter impact and perceived stress levels, so
as office clutter impact increased by one unit, stress increased by 0.41.
Office clutter did not predict either work engagement or job satisfaction.
However, job-related tension scores predicted job satisfaction scores,
supporting previous research relating job-related tension and job
satisfaction (Bateman & Strasser, 1983; Jackson, 1983). In sum, the
presence of clutter positively predicted a person’s level of emotional
exhaustion and stress, but did not predict work-related well-being, nor
did it predict job related tension.
Our study had limitations, including a small sample size and the use
of only self-reported measures as opposed to actually assessing one’s
cluttered office. Future studies might analyze how office clutter impacts
other occupational outcomes, such as organizational commitment,
perceived control over time, or job performance. In addition,
demographic characteristics such as income level, management status,
gender, or education level might affect the impact of office clutter on
workplace outcomes. Future studies might determine if there are any
important differences between home office clutter and workplace office
clutter. Since our sample contained individuals working in a home office,
it is possible that clutter from their home environment may affect the
clutter within the office and its impact on the person. With technology
becoming more advanced and information and processes becoming more
digitalized, future studies might examine electronic and digital clutter.
While our study did not show that office clutter impacts work-related
well-being, it did indicate that office clutter significantly impacted
certain occupational outcomes that are pertinent to employees’ health and
performance, such as stress and emotional exhaustion. Previous studies
have found that emotional exhaustion has been linked to physical health
issues such as colds, headaches, sleep problems, depression, and gastro-
intestinal problems; it has also been linked to workplace outcomes such
as job satisfaction, turnover intention, perceptions of workplace justice,
organizational commitment, and even job performance (Belcastro, 1982;
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 451
Cole, Bernerth, Walter, & Holt, 2010; Schaufeli & Bakker, 2004; Wright
& Cropanzano, 1998).
Previous research found that occupational stress may actually
increase physical and mental health issues, particularly depression
and anxiety (House, Wells, Landerman, McMichael, & Kaplan, 1979;
Jamal, 1990). Similarly to emotional exhaustion, stress also affects
turnover intention, absenteeism, occupational commitment, job
satisfaction, and job performance (Arsenault & Dolan, 1983; Jamal,
1990). These studies emphasize the importance of reducing
emotional exhaustion and occupational stress within employees as
much as possible. Now that the link between office clutter and these
variables have been found, this provides organizations with a more
tangible, physical way to reduce emotional exhaustion and stress.
Office clutter may be a real, physical aspect of the workplace that may
easily be changed to improve the way employees work and how they
feel. It may possibly be the link that allows organizations to tangibly
influence more complex worker characteristics. However, additional
studies might provide insights on how clutter in work settings may affect
Note: A portion of this study was the master’s thesis in I/O Psychology
by the first author supervised by the second author at DePaul University.
The authors express much gratitude to Dr. Catherine Roster (University
of New Mexico) for data collection and support for the crowd sourcing
American Psychiatric Association. (2013). Diagnostic and statistical manual of
mental disorders (DSM-5®). Arlington, VA: American Psychiatric
Arsenault, A., & Dolan, S. (1983). The role of personality, occupation and
organization in understanding the relationship between job stress,
performance and absenteeism. Journal of Occupational Psychology, 56(3),
Bateman, T. S., & Strasser, S. (1983). A cross-lagged regression test of the
relationships between job tension and employee satisfaction. Journal of
Applied Psychology, 68(3), 439.
Belcastro, P. A. (1982). Burnout and its relationship to teachers' somatic
complaints and illnesses. Psychological Reports, 50, 1045-1046.
Britt, T. W., & Bliese, P. D. (2003). Testing the stress‐buffering effects of self
engagement among soldiers on a military operation. Journal of
Personality, 71(2), 245-266.
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of
perceived stress. Journal of Health and Social Behavior, 385-396.
452 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
Cole, M. S., Bernerth, J. B., Walter, F., & Holt, D. T. (2010). Organizational
justice and individuals' withdrawal: Unlocking the influence of emotional
exhaustion. Journal of Management Studies, 47(3), 367-390.
Crum, K.P., & Ferrari, J.R., (2019a) Psychological home, clutter, and place
attachment predicting life satisfaction among women of color: Home is
beyond physical space. Journal of Contemporary Research in Social
Sciences, 1(1), 87-96.
Crum, K.P., & Ferrari, J.R., (2019b) Toward an understanding of psychological
home and clutter with emerging adults: Relationships over relics. North
American Journal of Psychology, 21(1), 45-56.
Ferrari, J.R. (2010). Still procrastinating? The no regrets guide to getting it done.
New York: John Wiley & Sons.
Ferguson, G.S. & Weisman, G.D. (1986). Alternative approaches to the
assessment of employee satisfaction with the office environment. In J.D.
Wineman, (Ed.), Behavior Issues in Office Design. New York: Van Nostrand
Reinhold, pp. 85 – 108.
House, J. S., Wells, J. A., Landerman, L. R., McMichael, A. J., & Kaplan, B. H.
(1979). Occupational stress and health among factory workers. Journal of
Health and Social Behavior, 139-160.
Jackson, S. E. (1983). Participation in decision making as a strategy for reducing
job-related strain. Journal of Applied Psychology, 68(1), 3.
Jackson, S. E., & Maslach, C. (1982). After‐effects of job‐related stress: Families
as victims. Journal of Organizational Behavior, 3(1), 63-77.
Jackson, L. T., Rothmann, S., & Van de Vijver, F. J. (2006). A model of
work‐related well‐being for educators in South Africa. Stress and Health:
Journal of the International Society for the Investigation of Stress, 22(4),
Jamal, M. (1990). Relationship of job stress and Type-A behavior to employees'
job satisfaction, organizational commitment, psychosomatic health problems,
and turnover motivation. Human Relations, 43(8), 727-738.
Maslach, C., & Jackson, S. E. (1981). The measurement of experienced
burnout. Journal of Organizational Behavior, 2(2), 99-113.
Parviainen, P., Tihinen, M., Kääriäinen, J., & Teppola, S. (2017). Tackling the
digitalization challenge: How to benefit from digitalization in practice.
International Journal of Information Systems and Project Management, 5(1),
Roster, C., & Ferrari, J.R. (2020). Does work stress lead to office clutter, and
how? Mediating influences of emotional exhaustion and indecision.
Environment & Behavior, 52, in press.
Roster, C. A., Ferrari, J. R., & Jurkat, M. P. (2016). The dark side of home:
assessing possession ‘clutter’ on subjective well-being. Journal of
Environmental Psychology, 46, 32-41.
Rothmann, S. (2008). Job satisfaction, occupational stress, burnout and work
engagement as components of work-related well-being. Sabinet African
Journal of Industrial Psychology, 34(3), 11-16.
Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their
relationship with burnout and engagement: A multi‐sample study. Journal of
Dao & Ferrari NEGATIVE SIDE OF OFFICE CLUTTER 453
Organizational Behavior: The International Journal of Industrial,
Occupational and Organizational Psychology and Behavior, 25(3), 293-315.
Warr, P. (2002). Psychology at work. Penguin UK.
Wooten, N. R., Fakunmoju, S. B., Kim, H., & LeFevre, A. L. (2010). Factor
structure of the job-related tension index among social workers. Research on
Social Work Practice, 20(1), 74-86.
Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a predictor of
job performance and voluntary turnover. Journal of Applied
Psychology, 83(3), 486.
Table 4: Regression analysis predicting job satisfaction from office
clutter, moderated by job-related tension.
Age -0.91 0.36 -0.28 -0.06 0.31 - - -
1.08 0.28 0.29 0.08 0.27 - - -
Model 2 4, 280 10.58 0.21
Gender 1.31 0.19 0.62 0.07 0.47 - - -
Age -1.82 0.07 -0.50 -0.11 0.28 - - -
1.51 0.13 0.37 0.10 0.24 - - -
Office Clutter 0.66 0.51 0.01 0.04 0.02 - - -
-1.28 0.20 -0.12 -0.11 0.09 - - -
-3.89 0.001 -0.52 -0.30 0.13 - - -
-1.39 0.17 -0.13 -0.10 0.10 - - -
Model 3 3, 277 7.70 0.22
Gender 1.24 0.22 0.59 0.07 0.48 - - -
Age -1.68 0.10 -0.50 -0.12 0.28 - - -
1.51 0.13 0.37 0.10 0.25 - - -
454 NORTH AMERICAN JOURNAL OF PSYCHOLOGY
Table 4 continued.
Office Clutter -0.46 0.65 -0.02 -0.07 0.04 - - -
0.66 0.51 0.14 0.13 0.22 - - -
-2.19 0.03 -0.67 -0.40 0.31 - - -
-2.08 0.04 -0.44 -0.35 0.21 - - -
-1.32 0.19 -0.01 -0.47 0.01 - - -
0.43 0.67 0.004 0.14 0.009 - - -
1.61 0.11 0.01 0.50 0.01 - - -
Note. Model 1 & 2: ΔR
= 0.20, ΔF = 17.25, p < 0.001; n = 290
Model 2 & 3: ΔR
= 0.01, ΔF = 1.00, p < 0.001; n = 290