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Impact of the restrictions on community activities policy during the COVID‐19 on psychological health in Indonesia's urban and rural residents: A cross‐sectional study

  • Universitas Qomaruddin, Gresik, Indonesia


Background and aims: Although extensive research has been conducted on the psychological impact after exposure to the COVID-19 pandemic, very few studies simultaneously investigated the negative and positive impacts on urban and rural residents. This study aims to compare the extent of psychological impact on Indonesian living in urban and rural areas a year after the first case of COVID-19 was reported. Design methodology and approach: We employed a cross-sectional study design. A total of 428 participants completed a set of web-based questionnaires from February to March 2021, consisting of the Impact of Event Scale-Revised (IES-R), the Perceived Social-Support (PSS), the mental health-related lifestyle (MHLS), and 6-item negative impacts, and the Jenkins' Sleep Scale (JSS). Findings: Over 40% of the participants reported moderate to severe trauma-related distress; 30%-40% increased stress at work, home, and financial stress, and 50% more social support gained from their family and friends. Although 62.1% of participants paid more attention to their mental health, only 30% engaged in a healthier lifestyle, and 36.7% had sleep problems. No significant differences were found between urban and rural residents on psychological impact, changes in mental health and related lifestyles, and sleep quality. Urban residents perceived more negative impacts, in parallel with increased social support, compared to rural residents. We also found a significant correlation between psychological impact, sleep disturbance, and increased social support. However, there was no significant association between mental health-related lifestyles and other scales. Originality and value: This is among the first studies that examine the urban-rural disparity on the positive and negative impact of the COVID-19 in the later stage of the pandemic. Our findings offer insights to provide equal effort to mitigate the negative impacts of the COVID-19 crisis as well as promote healthy lifestyle behaviors in both urban and rural residencies.
Received: 21 March 2022
Revised: 23 June 2022
Accepted: 26 June 2022
DOI: 10.1002/hsr2.725
Impact of the restrictions on community activities policy
during the COVID19 on psychological health in Indonesia's
urban and rural residents: A crosssectional study
Desdiani Desdiani
|Auditya P. Sutarto
Department of Pulmonology and Respiratory
Medicine, Occupational Medicine, Faculty of
Medicine, Universitas Sultan Ageng Tirtayasa,
Serang, Banten, Indonesia
Department of Pulmonology and Respiratory
Medicine, Bhayangkara Brimob Hospital,
Cimanggis, Depok, Indonesia
Department of Industrial Engineering,
Universitas Qomaruddin, Gresik, Indonesia
Desdiani Desdiani, Faculty of Medicine,
Universitas Sultan Ageng Tirtayasa,
Jalan Raya Jakarta Km. 4 Pakupatan, Serang,
Banten 42124, Indonesia.
Background and Aims: Although extensive research has been conducted on the
psychological impact after exposure to the COVID19 pandemic, very few studies
simultaneously investigated the negative and positive impacts on urban and rural
residents. This study aims to compare the extent of psychological impact on Indonesian
living in urban and rural areas a year after the first case of COVID19 was reported.
Design, Methodology and Approach: We employed a crosssectional study design.
A total of 428 participants completed a set of webbased questionnaires from
February to March 2021, consisting of the Impact of Event ScaleRevised (IESR), the
Perceived SocialSupport (PSS), the mental healthrelated lifestyle (MHLS), and
6item negative impacts, and the Jenkins' Sleep Scale (JSS).
Findings: Over 40% of the participants reported moderate to severe traumarelated
distress; 30%40% increased stress at work, home, and financial stress, and 50%
more social support gained from their family and friends. Although 62.1% of
participants paid more attention to their mental health, only 30% engaged in a
healthier lifestyle, and 36.7% had sleep problems. No significant differences were
found between urban and rural residents on psychological impact, changes in mental
health and related lifestyles, and sleep quality. Urban residents perceived more
negative impacts, in parallel with increased social support, compared to rural
residents. We also found a significant correlation between psychological impact,
sleep disturbance, and increased social support. However, there was no significant
association between mental healthrelated lifestyles and other scales.
Originality and Value: This is among the first studies that examine the urbanrural
disparity on the positive and negative impact of the COVID19 in the later stage of
the pandemic. Our findings offer insights to provide equal effort to mitigate the
negative impacts of the COVID19 crisis as well as promote healthy lifestyle
behaviors in both urban and rural residencies.
COVID19, Indonesia, mental health, psychological impact, rural, urban
Health Sci. Rep. 2022;5:e725.
This is an open access article under the terms of the Creative Commons AttributionNonCommercial License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited and is not used for commercial purposes.
© 2022 The Authors. Health Science Reports published by Wiley Periodicals LLC.
The new coronavirus SARSCoV2 first emerged in late December
2019 in Wuhan, China, and was quickly spreading around the
world, forcing the World Health Organization (WHO) to proclaim a
worldwide pandemic on March 11, 2020.
Since the declaration of
the first case in Indonesia on March 2, 2020, Indonesia was struggling
with COVID19 which has not shown any signs of slowing down.
Indonesia is among the highest cases in the world, with over
1,322,866 confirmed cases with a total of 35,876 deaths by February
26, 2021.
In response to the COVID19 crisis, governments around the
world have taken a wide range of measures including border
shutdowns, travel restrictions, complete and partial lockdowns, and
public activities restrictions. These measures have profoundly affected
people's economy, livelihood, and physical, and mental wellbeing
To balance tackling COVID19 and saving the economy,
Indonesian Government has not imposed a complete lockdown
policy, rather, implemented the LargeScale Social Restriction Policy
(Pembatasan Sosial Berskala Besar/PSBB) in several provinces that
restricted nonessential businesses, encourage telework, distance
learning, and still allowed people to carry out social activities such
as doing religious prayer with certain limitations. About 10 months
after the PSBB implementation, although fluctuating, the curve of
daily new cases and deaths continues to rise. Accordingly, the
Indonesian Government has implemented the Policy for Enforcement
of Restrictions on Community Activities (Pemberlakuan Pembatasan
Kegiatan Masyarakat/PPKM) that restricts community mobility at the
While the PSBB was issued by the Health of Ministry,
the decision to implement the PPKM was the regional leaders'
responsibility. Under the PPKM policy, for the badly affected area,
access to public places is restricted, for example, by limiting people
working at the office by 25% of the maximum capacity, conducting
online teaching and learning activities, allowing the restaurant to
serve dinein customers at only 25% of the total venue capacity, and
instructing places of worship to reduce visitor capacity to 50 percent.
Essential sectors can continue to operate normally and must adhere
to health protocols. In addition, during this microscale restriction, the
implementation of 3 T (tracing, testing, treatment) in the villages has
been strengthened.
Although these measures are less stringent than the requirements
under the PSBB or complete lockdown, the PPKM implementation
is also likely to pose adverse impacts on Indonesian physical and
mental health, and significantly affect everyday life with psychosocial
In the early stage of the pandemic, studies on the
mental health impact in Indonesia showed a high prevalence of
depression, anxiety, and other worse psychological symptoms.
survey on 2364 people from 34 provinces also revealed the most
prevalent complaints were worrying too much, getting irritated easily,
having difficulty relaxing, fatigue, and sleep problems.
On the other hand, such a crisis offers an opportunity to enhance
family bonds and provide assistance.
In collectivist cultures such as
Indonesia, the extended family system is considered a pillar of the
society which shall act as a protective factor concerning mental
health difficulties and other negative impacts during times of crisis.
Meanwhile, the Indonesian government has launched the Sejiwa
program (meaning healthy mind) to provide free psychological
consultation services, volunteered by hundreds of psychologists.
During 12 days from its launching date on April 29, 2020, Sejiwa
received more than 7500 calls and has responded to 14,916 calls
until the end of May,
indicating people paid more attention to their
mental health, a favorable behavior that raises the likelihood of early
intervention and fast recovery.
Furthermore, to deal with the
activities' restrictions during the PPKM, people were obligated to
modify their living conditions, sleep hygiene, and daily activities.
However, it is unclear whether people are more or less likely to adopt
healthier lifestyles. When people need to maintain their physical
health or prevent diseases and reduce the risk of COVID19 hospital
they might spend more time resting and relaxing and
engaged in more physical activities.
Conversely, they might also
act toward the opposite, become physically inactive, and develop
other poor behavior lifestyles.
A great deal of previous research has focused on the psychological
impact and sleep disturbance amid the COVID19 pandemic in the
general population as summarized in recent systematic reviews.
The authors found the presence of substantial heterogeneity between
the included studies, suggesting different social groups, contexts, and
countries may have different impacts on psychological health due to
the COVID19 pandemic.
Researchers also attempted to assess the possible positive impacts
including favorable lifestyle changes
and increased social
So far, however, there has been a lack of studies
simultaneously that investigated the negative and positive impacts of
the COVID19 pandemic. A pioneer epidemic study showed a
moderate to a severe disturbance caused by the SARS outbreak,
accompanied by other positive and negative behaviors.
the novel SARSCoV2 was much more contagious and infectious,
resulting in more devastating effects. Other studies have been
undertaken in Egypt,
and the Middle East and
North Africa region
which found mild to severe posttraumatic stress
symptoms and other negative impacts such as an increased feeling of
fear, amplified stress at work and home, financial burden, difficulties
with sleep, and somatic complaints.
While research on the psychological impact has been emerging,
the disparities between residence types are less studied. There is a
need to explore how the psychological distress caused by a traumatic
life event affects residents in urban and rural settings considering the
differences in the status of health literacy, health infrastructure, and
risk of infection with SARSCoV2.
A better understanding of the
psychological and behavioral responses of the general public would
contribute to controlling the pandemic and promote psychological
preparedness for emerging infectious diseases.
Research shows
inconsistent findings on the effect of the COVID19 pandemic on
mental health among urban and rural residents across countries.
While psychological distress in the United Kingdom
and China
living in urban areas was greater compared to rural areas, the overall
life satisfaction and mental health of US rural populations have been
severely affected by the pandemic.
Therefore, we aimed to examine whether any differences in
the psychological impact as measured by traumarelated distress,
changes in lifestyle, social support, and sleep quality among urban
and rural Indonesian residents at the later stage of the pandemic. This
study also assesses to what extent the correlation between all the
psychological impact variables. People from different countries have
been experiencing varying degrees of traumarelated distress, based
on the rate of coronavirus spread, the laws imposed by governments,
and prior experience. We expect to provide insights into evidence
based public health policies and resource allocation.
2.1 |Participants and study design
A total of 428 out of 434 (98.6%) from 25 of 34 provinces in
Indonesia completed a crosssectional webbased survey from
February 27 to March 30, 2021. The study inclusion criteria were
living in Indonesia, age 18 years. Those who were known to have
any psychiatric illness, a history of COVID19, or were diagnosed
with COVID19 were excluded. Participants were invited to partici-
pate in the study using convenience and snowball sampling methods
through social media and authors' networks. Sociodemographic
characteristics were collected including age, gender, education level,
employment status, and marital status. The study was approved by
the Ethics Committee of the Bhayangkara Brimob Hospital (No KET/
EC16/VII/2021/RS.BHAY.TK.I) and followed the STROBE reporting
guidelines for crosssectional studies to ensure accuracy, transpar-
ency of results, and quality of observational research. The partici-
pants were informed about the purpose of this study, and before
participation in the survey, all of them provided informed consent.
Anonymity, confidentiality, and voluntary participation with no
monetary benefits were ensured, meaning that respondents could
withdraw their data at any time from the study.
2.2 |Measures
The Indonesian version of the impact event scale revised (IESR) was
used to assess the psychological impact after traumatic and/or
stressful experiences.
The questionnaire consists of 22 items with
three subscales measuring avoidance, intrusion, and hyperarousal,
and are rated on a 5point Likerttype scale, ranging from 0 (not at
all)to4(completely agree). The total IESR scores were summed
(range 088) to perform the inferential statistics. For descriptive
purposes, the total scores were divided into normal (023), mild
(2432), moderate (3336), and severe psychological distress (>37).
A score 26 was used as a cutoff to represent moderatetosevere
The internal consistency Cronbach αwas 0.94 in our
Six questions were used to measure other negative mental health
impacts because of the COVID19 pandemic, adapted from Lay
et al.
Respondents were asked whether they experienced increased
stress at work or study, at home, and in financial status as compared
to the prepandemic period. Three other questions asked to what
extent the respondents felt horrified, apprehensive, and helpless due
to the pandemic. The response options range from much decreased
(1) to much increased(5). These questions had a Cronbach α
of 0.83.
A perceived support scale was used to assess the impact of
the COVID19 pandemic on the support received from family or
Participants were asked about: support from friends,
support from family members, sharing feelings with a family member,
sharing feelings with others when in blue, and caring for family
members' feelings. The response options were much decreased(1)
to much increased(5). The Cronbach αfor this study was 0.87.
Participants were also asked to rate to what extent the changes in
their lifestyle might have affected them due to the COVID19
pandemic using the Mental Health Lifestyle Scale (MHLS)
comprised of four items: attention to mental health, spending enough
time to rest, relax, and exercise. The response options range from
much decreased(1) to much increased(5). The internal consistency
value of this study was 0.74.
The Jenkins Sleep Scale (JSS) was used to assess sleep efficiency
during the previous month about difficulty falling asleep, awakening
during the night, trouble remaining asleep, and feeling tired and
sleepiness when awaking from sleep.
The respondents were asked
to rate on a sixpoint Likert scale from 0 not at allto 5 2228
days.The scores were summed (020) with higher scores being
related to more severe sleep disturbance. The cutoff score (>6 as
poor sleep quality) was used for descriptive and further analysis.
The Cronbach αvalue for our sample was 0.86.
2.3 |Data analysis
Numeric variables were represented by the mean and standard
deviation (SD) for normally distributed data, and medians and ranges
or interquartile ranges (IQRs) for nonnormally distributed data.
Categorical variables were represented by absolute (n) and relative
frequency (%). The original fivepoint Likert scores of negative mental
health, social support, and mental healthrelated lifestyle were
calculated as the composite score by taking the average of the total
scores on each scale. These scales were also dichotomized by
collapsing responses for much decreased (1), decreased (2), and same
as before (3) into the decrease or similar category, while increased (4),
and much increased (5) were collapsed into an increased category.
To examine the differences between total IESR and sleep scores
by residential location, the nonparametric MannWhitney test was
used. The association between each indicator of other measures
(negative mental health, social support, attention to mental health,
lifestyle changes) and residency was calculated using Phi and Cramer
V statistics. We further conducted a Spearman analysis to evaluate
the correlation between IESR, JSS, and the composite scores of the
other three scales because data were not normally distributed. All
analysis was performed using SPSS 23.0 (IBM) at twotailed a
significance level of 0.05.
The majority of respondents were female (54.2%), more than 30
years (52.8%), and married (55.1%) (see Table 1). More than 65% of
respondents lived in urban areas, 43.93% had college or university
degrees, and 17.30% worked as health care workers.
3.1 |Differences between outcome variables by
Table 2presents the total sample scores and frequencies for all
measured variables and their differences statistics between rural
and urban respondents. The overall mean IESR score was 29.92
(SD = 18.45), indicating that the COVID19 pandemic had a mildly
stressful effect on the surveyed subjects. About 44% of respondents
reported indicating significant psychological impact (mean IESR
scores 33). There are no significant differences in IESR total scores
and IESR categories according to the residencies.
About 31%40% of the participants perceived an increased level
of stress at home, in financial matters, and at work or study. Those
who live in urban areas significantly experienced a greater level of
stress as compared to rural residents. More than 44% of participants
felt horrified due to the COVID19 even after 1 year, 49.3% felt
apprehensive, and 25.8% felt helpless. However, the difference
between such feelings and those who live in urban or rural areas was
not observed.
Furthermore, more than half of the sample perceived increased
support from family and friends, shared feeling with family, and
caring for family members' feelings, while about 40% reported
increased shared feelings with others when blue. These increases
were much higher among urban than rural respondents.
A year after the first case was confirmed, about twothirds of the
participants paid more attention to their mental health which was
reported similar by those living in the rural and urban regions. In
contrast, only 35%36% of the sample took more time to rest, relax,
and do exercise. No significant differences were found in the lifestyle
changes between the urban and rural residents. For sleep quality,
about a third of the sample reported sleep disturbance and urban
residents experienced slightly higher sleep scores, indicating worse
sleep problems. Nevertheless, the difference between the two
residency groups was not statistically significant.
3.2 |Correlation analysis
Table 3displays the Spearman rho's coefficient of correlation among
all scales The IESR scores were significantly correlated with the JSS
(sleep disturbance), negative mental health impacts, and increased
PSS (social support) (p< 0.05, Table 3). However, the association
between IESR scores and the composite score of mental health
related lifestyles was not observed. Similar findings were also found
for the correlation between sleep disturbance and other variables of
We found that a year after the first case was confirmed, urban and
rural residents reported moderate levels of psychological impact, and
more than onethird reported increased stress at home, work,
and financial stress. Although almost half of the reported felt
horrified and apprehensive, only 25% felt helpless. While the majority
of participants reported more attention devoted to their mental
health, only 34%40% spent more time resting, relaxing, or doing
exercise. The prevalence rate of sleep problems accounted for 36.1%.
There were no differences between urban and rural areas on
residents' psychological impact, mental health and related lifestyle,
and sleep disturbance. On the other hand, differences were observed
in some indicators of negative impacts and perceived social support.
Compared to other countries, using the same instrument in the
general population, we found that our IESR mean score was higher
than people from China,
relatively similar to Middle East regions,
and Italy,
but lower than Egypt,
and Portugal.
This result
corroborates the finding of prior metaanalysis studies that found the
TABLE 1 Descriptive statistics of sample
characteristics (n= 428)
Variable Categories Count Percentage
Age <30 202 47
>30 226 53
Gender Female 232 54
Male 196 46
Residency Urban 278 65
Rural 150 35
Education High School or less 172 40
College/University 188 44
Postgraduate 68 16
Occupation NonHCW 226 53
HC workers 74 17
Students 68 16
Unemployment 60 14
Marital status Single 182 42.5
Married 236 55.1
Widow/divorced 10 2.4
TABLE 2 Psychological impact, negative mental health impacts, changes of family and social support of the sample, attention to mental
health, and lifestyle changes by residency types
All Urban Rural
N= 428 N= 278 N= 150
Response n(%) n(%) n(%)
impact IESR
Total IESR Scores Mean (SD) 29.92 (18.45) 29.87 (30) 30.00 (20) 0.891
Median (IQR) 30.0 (15.043.0) 30.0 (16.042.0) 29.5 (1345.3)
Intrusion Mean (SD) 10.01 (7.38) 10.25 (7.16) 9.55 (7.77) 0.199
Median (IQR) 9.0 (4.015.0) 10.0 (4.015.0) 9.0 (2.015.0)
Hyperarousal Mean (SD) 7.63 (5.63) 7.56 (5.48) 7.76 (5.92) 0.934
Median (IQR) 7.0 (3.011.0) 7.0 (3.011.0) 7.0 (3.012.0)
Avoidance Mean (SD) 12.28 (7.33) 12.05 (6.88) 12.69 (8.10) 0.424
Median (IQR) 12.0 (7.017.5) 12 (7.017.0) 13 (6.018.2)
Normal 160 (37.4%) 100 (36%) 60 (40%) 0.425
Mild 79 (18.5%) 56 (20%) 23 (15%)
Moderate 39 (9.1%) 28 (10%) 11 (7%)
Severe 150 (35%) 94 (34%) 56 (37%)
Negative mental
Composite scores Mean (SD) 3.2 (0.69) 3.2 (0.72) 3.1 (0.61) 0.002
Median (IQR) 3.2 (3.03.7) 3.3 (3.03.7) 3.0 (2.80.35
Increased Stress from work/
Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 171 (40.0%) 135 (48.6%) 36 (24.0%) <0.001
No 257 (60.0%) 143 (51.4%) 114 (76.0%)
Increased Stress from home Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 133 (31.1%) 104 (37.4%) 29 (19.3%) <0.001
No 295 (68.9%) 174 (62.6%) 121 (80.7%)
Increased Financial Stress Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (2.04.0)
Yes 151 (35.35%) 112 (40.3%) 39 (26.0%) 0.003
No 277 (64.7%) 166 (59.7%) 111 (74%)
Feel horrified due to the
Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 191 (44.6%) 130 (46.8%) 61 (40.7%) 0.226
No 237 (55.4%) 148 (53.2%) 89 (59.3%)
Feel apprehensive due to
Median (IQR) 3.0 (3.04.0) 4.0 (3.04.0) 3.0 (3.04.0)
Yes 211 (49.3%) 147 (52.9%) 64 (42.7%) 0.044
No 217 (50.7%) 131 (47.1%) 86 (57.3%)
Feel helpless due to the
Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 110 (25.75) 78 (28.1%) 32 (21.3%) 0.129
No 318 (74.3%) 200 (71.9%) 118 (78.7%)
Social support Composite scores 3.6 (0.70) 3.7 (0.71) 3.6 (0.68) 0.042
3.6 (3.00 3.8 (3.24.0) 3.5 (3.04.0)
Increased support from
Median (IQR) 4.0 (3.04.0) 4.0 (3.04.0) 4.0 (3.05.0)
Yes 267 (62.4%) 186 (66.90%) 81 (54.0%) 0.009
No 161 (37.6%) 92 (33.10%) 69 (46.0%)
pooled prevalence of psychological problems in the general popula-
tion from the Asia region accounted for more than 30%
larger than of the European, North American, and Oceanian.
Moreover, no significant differences in psychological impact were
observed between citizens living in urban and rural areas. Prior
studies were conducted mostly at the early stage of the pandemic
(March to July 2020), while our study was carried out about a year
after discovering the first case. This implied Indonesian continued to
experience higher posttraumatic event symptoms.
We found that increased perceived social support was larger
than reported in UAE
and Egypt,
implying families and friends
were highly valued in times of stress event. Such behaviors provide
psychological advantages for people who encountered negative
feelings during the pandemic.
Compared to rural citizens, urban
TABLE 2 (Continued)
All Urban Rural
N= 428 N= 278 N= 150
Response n(%) n(%) n(%)
Increased support from
Median (IQR) 4.0 (3.04.0) 4.0 (3.04.0) 3.0 (3.04.0)
Yes 229 (53.5%) 160 (57.60%) 69 (46.0%) 0.022
No 199 (46.5%) 118 (42.4%) 81 (54.0%)
Increased shared feeling
with family members
Median (IQR) 4.0 (3.04.0) 4.0 (3.04.0) 3.0 (3.04.0)
Yes 229 (53.50%) 160 (57.60%) 69 (46.0%) 0.016
No 199 (46.5%) 118 (42.4%) 81 (54.0%)
Increased shared feeling
with others when blue
Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 182 (42.5%) 130 (46.8%) 52 (34.70%) 0.016
No 246 (57.5%) 148 (53.2%) 98 (65.30%)
Increased caring for family
members' feeling
Median (IQR) 4.0 (3.04.0) 4.0 (3.04.0) 4.0 (3.04.0)
Yes 302 (70.6%) 206 (74.1%) 96 (64.0%) 0.029
No 126 (29.4%) 72 (25.9%) 549 (36.0%)
Mental health &
Composite scores 3.3 (0.71) 3.3 (0.72) 3.4 (0.70) 0.135
3.2 (3.03.8) 3.3 (3.03.8) 3.3 (3.04.0)
Increased mental health Median (IQR) 4.0 (3.04.0) 4.0 (3.04.0) 4.0 (3.04.0)
Yes 266 (62.1%) 173 (62.2%) 93 (62.0%) 0.963
No 162 (37.9%) 105 (37.8%) 57 (38.05)
Increased relax Median (IQR) 3.0 (3.04.0) 3.0 (2.84.0) 3.0 (3.04.0)
Yes 147 (34.3%) 92 (33.1%) 55 (36.7%) 0.458
No 281 (65.7% 186 (66.9%) 95 (63.3%)
Increased rest Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 158 (36.9%) 100 (36.0%) 58 (38.7%) 0.422
No 270 (63.1%) 178 (64.0%) 92 (61.3%)
Increased workout Median (IQR) 3.0 (3.04.0) 3.0 (3.04.0) 3.0 (3.04.0)
Yes 153 (35.7%) 94 (33.8%) 59 (39.7%) 0.256
No 275 (64.3%) 184 (66.2%) 91 (60.7%)
Sleep Total JSS scores Mean (SD) 4.00 (4.13) 4.21 (4.28) 3.60 (3.82) 0.193
Median (IQR) 3.0 (0.06.0) 3.0 (0.06.0) 3.0 (0.06.0)
Poor 157 (36.7%) 105 (37.8%) 52 (34.7%) 0.525
Good 271 (63.3%) 173 (62.2%) 98 (65.3%)
Abbreviations: IESR, impact event scale revised; IQR, interquartile range; JSS, Jenkins' Sleep Scale.
MannWhitney test.
citizens perceived significantly increased stress at work, at home, and
financially. However, they also reported more support from their
friends and family as well as more shared feeling and caring which
might explain why the psychological distress of both groups of
residencies is relatively similar. One of the crucial factors to cope
with difficulties and develop resilience in times of crisis is a feeling of
Furthermore, the majority of urban and rural residents paid
more attention to their mental health which might help participants
to overcome other negative impacts. Unfortunately, only a third of
participants reported increased healthier lifestyles which might be
due to the restriction of outdoor activities during the PPKM. No
significant differences in mental health awareness, time spent on
rest, relaxation, and exercise were found according to residency
type which supports a prior study from China.
It seems that family
members of urban residents devoted more time together and were
more concerned about their health and family, rather than leisure
activities. According to the current findings, less time spent on rest,
relaxation, and physical activity was parallel with higher scores on
the IESR scale, implying that such unfavorable behaviors might
exacerbate the event's negative impact. JiménezPavón, et al.,
suggested that physical activity is an effective therapy to combat
In terms of sleep, our result was consistent with a recent
systematic review that summarized the prevalence of sleep problems
during the COVID19 affected more than onethird of people in the
general population.
Another study in Turkey during the 3month
lockdown also reported a somewhat similar JSS score.
This level
was found to be 18% higher than that of pooled estimated from the
general population in 39 countries.
Similar to posttraumarelated
stress symptoms, we were unable to demonstrate the differences in
sleep problems between residential groups. Nevertheless, Spear-
man's correlation reveals the positive association between IESR,
other negative impacts, and JSS scores. Increased negative feelings
due to the COVID19 pandemic (e.g., increased stress at work) was
significantly associated with more posttraumatic stress symptoms
and worse sleep quality which are in accord with recent systematic
review studies.
These results implied potential interrelationships
among all three variables which need more complex path analysis to
quantify these pathways in future studies.
Furthermore, we also found a positive correlation between
psychological impact, sleep disturbance, and increased family and
social support. Those who reported greater levels of traumarelated
distress and poorer sleep quality were likely to receive more social
support during the COVID19 pandemic. This result highlights the
protective factor of social support against developing mental health
difficulties and sleep disturbances.
Interestingly, in contrast to previous findings,
neither trauma
related distress nor the quality of sleep was significantly related to
mental healthrelated lifestyle concerns. This result may partly be
explained by the association between psychological impact and
sleep quality with the intensity of lifestyle behaviors. Studies have
demonstrated that more intensive physical activity was needed to
achieve greater psychological health.
Our findings should be considered in light of some limitations.
Using a webbased questionnaire with a convenience sampling
technique raises the generalizability issue while the crosssectional
study design hinders us to infer causality. These limitations were
mainly due to the intention to avoid possible infection during the
activities restriction policy as well as constraints on time and
resources. Future research requires a more rigorous design. Secondly,
the data were selfreported that could not rule out social and
memory recall biases. Nevertheless, the use of online platforms and
emphasis on anonymity and confidentiality reduce the impact of the
biases. Lastly, we extended the use of a 6item scale to measure
other negative impacts in the SARS epidemic context into the
COVID19 pandemic.
It may raise a concern about its contextual
use because the current pandemic had more devastating economic,
social, and health consequences than the SARS outbreak. This scale,
however, has been used in COVID19related studies world-
which enables us to make comparisons across different
populations. Findings of this scale also helped us better interpret
results from other wellestablished instruments used in this study,
such as IESR and JSS. Further studies, yet, should consider several
measures developed specifically to study the psychosocial impact of
the COVID19 pandemic such as the Short Multidimensional
Inventory Lifestyle Evaluation tool
and the COVID19 Pandemic
Mental Health Questionnaire (CoPaQ).
Notwithstanding these limitations, our study also has strengths.
First, to the best of our knowledge, this is the first urbanrural
disparity study on the simultaneous positive and negative impact of
the COVID19 in the later stage of the pandemic in a developing
country. Second, the use of similar measures allows us to make cross
country comparisons in the general population.
4.1 |Implication
Since the prevalence of psychological impacts and sleep problems
among urban and rural residents did not differ significantly,
policies should focus on developing mitigation plans that are not
TABLE 3 Correlation between all acales
JSS 0.60** 1
Negative 0.33 0.31** 1
PSS 0.22** 0.14** 0.26** 1
MHLS 0.04 0.02 0.13** 0.36** 1
Abbreviations: IESR, Impact Event ScaleRevised; JSS, Jenkins' Sleep
Scale; MHLS, Mental HealthRelated Lifestyle; Negative, 6item other
negative impact; PSS, Perceived Social Support.
**Significant at p< 0.001.
urbancentric for the rural population to ensure a successful recovery
for all parts of the country. It is also important to promote adherence
to healthy lifestyle behavior as protective factors for worse
psychological impact and sleep disturbance. A more precise physical
activity recommendation is required to significantly improve indivi-
duals' mental health. This study has also contributed to the literature
on the prevalence of traumarelated distress symptoms simulta-
neously with positive impacts during the COVID19 pandemic not
only on urbanized areas but also on rural areas which have been paid
less attention.
Our study examined to what extent the psychological impact and
positive impacts of Indonesia's urban and rural residents at the
later stage of the COVID19 pandemic. In summary, regardless of
the residency areas, this study confirms that the prevalence of
psychological problems after 1 year of exposure to a COVID19
crisis remains substantial. This evidence reveals the need to
COVID19 crisis as well as promote healthy lifestyle behaviors.
Further studies need to explore other influencing factors in rural
Conceptualization: Desdiani Desdiani, Auditya Purwandini Sutarto.
Methodology: Desdiani Desdiani, Auditya Purwandini Sutarto. Data
Collection: Desdiani Desdiani. Formal analysis: Auditya P. Sutarto.
Supervision: Desdiani Desdiani. WritingOriginal draft: Auditya P.
Sutarto. WritingReview and Editing: Desdiani Desdiani. All authors
have read and approved the final version of the manuscript. Desdiani
Desdiani had full access to all of the data in this study and takes
complete responsibility for the integrity of the data and the accuracy of
the data analysis.
The authors would like to acknowledge all the respondents for their
voluntary participation. The present study did not receive any
financial supports from public agencies, private companies or non
profit entities for the research, authorship, and/or publication of this
manuscript. We would like to thanks the authorities of Faculty of
Medicine Universitas Sultan Ageng Tirtayasa and Bhayangkara
Brimob Hospital for their support with dissemination of the survey
through their network.
The author declares no conflict of interest.
Desdiani Desdiani affirms that this manuscript is an honest, accurate,
and transparent account of the study being reported; that no
important aspects of the study have been omitted.
The data are available from the corresponding author upon
reasonable request.
Desdiani Desdiani
Auditya P. Sutarto
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Additional supporting information can be found online in the
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How to cite this article: Desdiani D, Sutarto AP. Impact of the
restrictions on community activities policy during the COVID19
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a crosssectional study. Health Sci Rep. 2022;5:e725.
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