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Article
Different Responses to Stress, Health Practices and Self-care
during COVID-19 Lockdown: A Stratified Analysis
Elena Bermejo-Martins1,2; Elkin O. Luis*2,3; Ainize Sarrionandia4; Martín Martínez2,3; María Sol Garcés5; Edwin Y.
Oliveros6; Cristian Cortés-Rivera7; Maider Belintxon1,2 and Pablo Fernández-Berrocal8
1 School of Nursing, University of Navarra. Spain. ebermejo@unav.es (E.B.M) and mbelintxon@unav.es (M.B)
2 Navarra Institute for Health Research, IdiSNA. Spain
3 School of Education and Psychology, University of Navarra. Spain. eoswaldo@unav.es (E.O.L) and mmvil-
lar@unav.es (M.M)
4 Faculty of Psychology, University of the Basque Country. Spain. ainize.sarrionandia@ehu.eus (A.S)
5 Neuroscience Institute, Universidad San Francisco de Quito. Ecuador. sgarces@usfq.edu.ec (M.S.G)
6 Faculty of Psychology, University of San Buenaventura, Bogotá. Colombia eoliveros@usbbog.edu.co (E.Y.O)
7 Faculty of Psychology, Universidad del Desarrollo. Chile. crcortesr@udd.cl (C.C)
8 Faculty of Psychology, University of Málaga. Spain. berrocal@uma.es (P.F.B)
* Correspondence: eoswaldo@unav.es; Tel.: +34 948425600 ext 802903
Abstract: The aim of the present cross-sectional study was to analyze the differential impact of the
first COVID-19 lockdown (3rd April 2020) on stress, health practices, and self-care activities across
different Hispanic countries, age range and gender groups. One thousand and eigthy-two partici-
pants from Spain, Chile, Colombia, and Ecuador took part in this study. Irrespective of the country,
and controlling for income level, young people, especially females, suffered a greater level of stress,
perceived the situation as more severe, showed less adherence to health guidelines and reported
lower levels of health consciousness, in comparison to their male peers and older groups. However,
in the case of self-care, it seems that older and female groups are generally more involved in self-
care activities and adopt more healthy daily routines. These results are mostly similar between Co-
lombia, Ecuador, and Spain. However, Chile showed some different tendencies, as males reported
higher levels of healthy daily routines and better adherence to health guidelines compared to fe-
males and people over the age of 60. Differences between countries, genders and age ranges should
be considered in order to improve health recommendations and adherence to guidelines. Moreover,
developing community action and intersectoral strategies with a gender-based approach could help
to reduce health inequalities and increase the success of people ́s adherence to health guidelines and
self-care-promoting interventions. Future studies should be addressed to explore the possible cau-
sations of such differences in more cultural-distant samples and at later stages of the current out-
break.
Keywords: COVID-19; health practices; stress; self-care; cross-cultural study
1. Introduction
As of 14st April 2020, more than 18056 people had died as a result of the coro-
navirus disease 2019 (COVID-19) in Spain; more than 127 in Colombia; more than 92 in
Chile; and more than 369 in Ecuador [1]. This led to unprecedented efforts to institute the
practice of "social distancing" in most countries around the world, resulting in a strict na-
tional lockdown and affecting the population’s usual functioning and daily lives. Alt-
hough these measures are crucial to mitigating the spread of this disease, they are un-
doubtedly affecting people’s health and well-being in the short and long term. As a con-
sequence, people from different countries have suffered (and continue to suffer) several
psychological symptoms and health problems [2–6].
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© 2021 by the author(s). Distributed under a Creative Commons CC BY license.
In contrast, this situation can offer the opportunity to progress in terms of health pro-
motion and prevention strategies [7]. In this sense, from a salutogenic perspective, it is
important to move beyond individual risk factors such as tobacco use, to social and struc-
tural forces on health, and to “salutary” factors such as education or people’s capability
to remain healthy [8]. The salutogenic approach highlights the importance of promoting
health assets and the active role of people in creating health. Given that health arises from
the interplay between people and their context, it must be considered that people have a
critical role in bringing about change [9]. According to Morgan and Ziglio [10], these
health assets represent any factor or resource that enhances the ability of individuals, com-
munities, and populations to maintain and sustain health and well-being and to help to
reduce health inequalities. Therefore, these assets can operate at the level of the individ-
ual, family or community, and population as protective and promoting factors to buffer
against life's stressors.
From a health-assets approach, promoting self-care activities could be key to bolster-
ing physical and mental health at the individual level [11]. In fact, during the current pan-
demic, it has been widely advised to engage in self-care activities to reduce stress, along
with maintaining a healthy lifestyle as a protective factor against the virus complications
[12,13]. In the same vein, people who suffered a higher impact of quarantine on their phys-
ical activities tend to have higher prevalence of anxiety and depression symptoms and
keeping active can play a very important protective factor of mental and physical health
[14,15].
However, stress responses, self-care or health behaviour changes during COVID-19
lockdown can differ by age, gender, ethnicity, and socioeconomic position. This situation
seems particularly stressful for younger adults (< 35 years), women, people without work
and with low incomes [16]. Moreover ethnic minorities showed to undertake less exercise
and consume lower amounts of fruit and vegetables during lockdown. Regarding coun-
tries differences, it has been found that living in a high-income country during the pan-
demic is a risk factor for depression and anxiet and countries belonging to the Latin Amer-
ica and Caribbean cluster showed a lower prevalence of mental health symptoms com-
pared to countries belonging to North America, Europe and Central Asia, and Sub-Sa-
haran Africa clusters [17].
Nevertheless, to our knowledge, none have explored these differences in a well-bal-
anced sample by age, gender and country and neither on variables such as, people’s ad-
herence to Public Health guidelines, stress perception, and the adoption of self-care activ-
ities. Therefore, in this study we hypothesized the existence of differences in responses to
stress, health practices and self-care activities depending on country, age and gender due
to mandatory COVID-19 confinement.
2. Materials and Methods
2.1. Study Sample
The sample was obtained by an online survey shared on social media from 31th
March to 14th April of 2020. Participation was voluntary, anonymous, no compensation
was offered, and the administration of the instruments (Perceived Stress Scale: PSS-10,
COVID-19 Health Practices, and Self-Care Activities Screening Scale: SASS-14) took ap-
proximately 15 minutes. Approval was obtained from the Research Ethics Committee of
the university responsible for the study (Project ID: 2020.058). The estimation of the
sample size was based on the application of the central limit theorem, which states that
when a sample exceeds 30 individuals, whatever the sample mean, it will approximately
follow a normal distribution. Given that the statistical analyzes respond to the general
linear model, the estimation of the sample would be calculated as follows: number of sub-
jects (30) * number of age groups (5) * number of genders (2) * number of countries (4) =
1200. Out of 3452 respondents, a stratified sample was extracted by randomizing cases by
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 2 February 2021 doi:10.20944/preprints202102.0092.v1
the four countries, gender, and age groups. The final sample was comprised of 1082 par-
ticipants.
2.2. Measures
2.2.1. Perceived Stress
The Spanish version of the PSS-10 evaluates perceived stress during the last month
[18]. It is composed of 10 items ranging from 0= Never to 4= Very often. The instrument
provides a total score; the higher the total score, the greater the level of perceived stress.
The scale has good reliability (internal consistency, α = .81), concurrent validity, sensitiv-
ity, and Cronbach’s alpha for this sample was α =.85 [18]. Studies have been published
that report in relation to PSS-10, optimal psychometric properties, both in the general pop-
ulation and people exposed to confinement [19,20] and specifically in health professionals
who attend the emergency situation [21].
2.2.2. COVID-19 Health Practices
A short ad hoc scale was used to examine three preventive health indicators during
COVID-19 lockdown. A single item examined COVID-19 seriousness perception: “How
serious do you consider this pandemic situation?” The response scale ranged from 1= Not se-
rious at all to 4=Very serious. Two items ranging from 1= Do not agree at all to 6= Totally
agree examined healthy daily routines and adherence to Public Health guidelines: “I do
follow Public Health guidelines” and “I am keeping a healthy routine with balanced schedules and
different places to work and rest”, respectively.
2.2.3. Self-Care Activities
The SASS-14 is a brief self-report instrument to screen self-care activities in the gen-
eral population [14]. This screening tool measures four dimensions: health consciousness,
nutrition and physical activity, sleep quality and inter and intrapersonal coping strategies.
The SASS-14 is composed of 14 items ranging from 1= Never to 6= Always. The higher the
total score, the more self-care activities the person engages in. The SASS-14 has adequate
psychometric properties with high internal consistency and convergent validity with psy-
chological well-being and stress measures. For this sample, Cronbach’s alpha was α = .77.
2.3. Statistical Analysis
SPSS version 24 was used for data entry and analyses. Descriptive statistics analysis
was used to summarize the socio-demographic data. Preliminary multiple regression
analyses were conducted to determine whether socio-economic variables were associated
with the main variables (i.e., stress, health practices, and self-care). Such analyses did not
show significant influences of any socio-demographic variables on health practices indi-
cators and self-care. On the other hand, educational level, income level, changes in the
employment situation, being accompanied during lockdown, or having community re-
sources showed a significant influence on stress (R² = .10; p < .001). Finally, only the income
level variable had a significant influence in a preliminary univariate on stress. Therefore,
analyses of the relationship between the main variables and factors were conducted using
multivariate analysis (MANOVA), where health practices and self-care variables were in-
cluded as dependent variables, and country, gender and age were included as independ-
ent variables. Stress, controlling for income level, was analyzed with a univariate analysis
of covariance (ANCOVA).
When significant interactions were found, the file was split by the responsible factors
of the interaction and, subsequently, independent ANOVAs were conducted with each
dependent variable. Bonferroni adjusted all multiple comparisons and partial eta square
(ηp2) was used for test effect size.
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3. Results
3.1. Socio-Demographic Characteristics
Data was obtained from 1,082 participants recruited in four countries: Spain (n = 271,
with a ratio of the sample participation relation to the population of legal age of 0,0007%,
source: INE), Ecuador (n = 282, 0,0024%, source: INEC), Chile (n = 261, 0,0024%, source:
INE) and Colombia (n = 268, 0,00081%, source: DANE). Participants’ age ranged from 18
to 95 with a mean age of 43.9 (SD = 15.2); 50.9% (551) of the sample was female and 49.1%
(531) male. Socio-demographic characteristics were similar across countries with very few
differences between genders, most participants having a high educational level and me-
dium and high-income level, as shown in Table 1..
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1
Table 1. Sample age–range distribution and socio–demographics characteristics by country and gender.
2
Spain
Chile
Colombia
Ecuador
18–28
29–39
40–49
50–59
<60
18–28
29–39
40–49
50–59
<60
18–28
29–39
40–49
50–59
<60
18–28
29–39
40–49
50–59
<60
57(21)
55(20)
54(20)
50(18)
55(20)
56(21.5)
53(20.3)
56(21.5)
45(17)
51(19.5)
56(21)
54(20)
56(21)
51(19)
51(19)
64(23)
55(19.5)
57(20)
54(19.1)
52(18)
Spain
Chile
Colombia
Ecuador
Female
Male
Total
Female
Male
Total
Female
Male
Total
Female
Male
Total
Full sample
N (%)
136(50.2)
135(49.8)
271
127(48.7)
134(51.4)
261
131(48.9)
147(51.1)
268
137(48.6)
145(51.4)
282
1082
Income n (%)
No salary
22(16.2)
23(17)
45(16.6)
19(15.0)
8(6.0)
27(10.3)
21(16)
22(16.1)
43(16.0)
23(16.8)
20(13.8)
43(15.2)
158 (14.6)
One mw
4(2.9)
5(3.7)
9(3.3)
13(10.2)
9(6.7)
22(8.4)
21(16)
16(11.7)
37(13.8)
12(8.8)
7(4.8)
19(6.7)
87(8)
Two mw
20(14.7)
10(7.4)
30(11)
21(16.5)
15(11.2)
36(13.8)
19(14.5)
18(13.1)
37(13.8)
26(19.0)
16(11.0)
42(15)
145(13.4)
Three mw
28(20.7)
22(16.3)
50(18.5)
14(11.0)
21(15.7)
35(13.4)
34(26.0)
34(24.8)
68(25.3)
26(19.0)
10(6.9)
36(12.7)
189(17.5)
Four mw
30(22.1)
29(21.6)
59(21.7)
15(11.8)
19(14.2)
34(13)
14(10.7)
16(11.7)
30(12.0)
26(19.0)
26(17.9)
52(18.4)
175(16.2)
Five mw
32(23.5)
46(34.1)
78(28.8)
45(35.4)
62(46.3)
107(41)
22(16.8)
31(22.6)
53(19.7)
24(17.5)
66(45.6)
90(32)
328(30.3)
Educational Level n (%)
Elementary
1(0.7)
3(2.2)
4(1.48)
2(1.6)
2(1.5)
4(1.53)
0(0.0)
1(0.7)
1(0.4)
2(1.5)
0(0)
2(0.7)
11(1)
High School
20(14.7)
22(16.3)
42(15.5)
12(9.4)
16(11.9)
28(7.0)
14 (10.7)
21 (15.3)
35 (13.5)
20(14.6)
28(19.3)
48(17.0)
153(14.1)
Technical
18(13.2)
19(14.1)
37(13.7)
18(14.2)
15(11.2)
33(12.7)
16 (12.2)
24 (17.5)
40(15.3)
7(5.1)
5(3.4)
12(4.3)
122(11.3)
University
97(71.3)
91 (67.4)
188(69.3)
95(74.8)
101(75.4)
196(75.1)
101(77.1)
91 (66.4)
192(74.5)
108(78.8)
112(77.2)
220(78.0)
796(73.6)
COVID–19 variables n
(%)
Front–line workers (yes)
34 (25)
46(34.1)
80(29.5)
36(28.3)
44(32.8)
80(30.7)
70(53.4)
61(44.5)
131(48.9)
35(25.5)
41(28.3)
76(27)
367(33.9)
Health risk factors (yes)
39 (28.7)
50 (37)
89(32.8)
33(26)
51(38.1)
84(32.2)
44(33.6)
33(24.1)
77(28.7)
31(22.6)
56(38.6)
87(30.9)
337(31.1)
Employment changes (yes)
21(15.4)
25(18.5)
46(17)
32(25.2)
19(14.2)
51(19.5)
41(31.3)
46(33.6)
87(32.4)
41(30)
46(31.7)
87(31)
271(25)
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Note: mw = minimun wage.
3
Accompanied during
lockdown (yes)
114(83.8)
117(86.7)
231(85.2)
117(92.1)
120(89)
237(91)
130(95)
136(94)
266(99.2)
121(92.4)
127(92.7)
248(88)
982(90.8)
Community resources (yes)
120(88.2)
125(92.6)
245(90.4)
102(80.3)
113(84.3)
233(89.2)
109(83.2)
116(85)
225(84)
118(86.1)
133(91.7)
251(89)
936(85.5)
Children in charge (yes)
32(23.5)
31(23)
63(23.2)
48(37.8)
38(28.4)
86(33)
37(28.2)
56(41)
93(34.7)
47(34.3)
48(33.1)
95(33.6)
337(31.1)
Older people in charge (yes)
15(11)
14(10.4)
29 (10,7)
37(30)
20(15)
57(22)
53(40.5)
53(38.7)
106(39.5)
47(34.3)
48(33.1)
95(33.6)
287(26.5)
Confinement days
M (SD)
21 (4.6)
17.5(6.5)
17(4.0)
25 (0.6)
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3.2. Perceived Stress
4
After correcting for income level, the univariate ANCOVA analysis showed no sig-
5
nificant interactions among country, gender and age group (F(12) = .75; p = .70). However,
6
a significant interaction was found between gender and age group (F(4) = 2.76; p = .03; ηp2
7
= .01) due to the fact that females from the youngest group showed significantly higher
8
levels of stress compared to females from older groups (p = .02; p = .005; p = .001). Females
9
from the 29–39 age group showed significantly higher stress levels than those over 60 (p =
10
.01). These differences are also significant between females and males from the youngest
11
age groups (18–28 years old) as young females reported higher levels of stress compared
12
to young males (p = .002). Main effects analysis shows that differences in terms of per-
13
ceived stress across countries are significant (F(3) = 6.92; p < .001; ηp2 = .02), those from
14
Chile and Spain having higher stress levels compared to Colombian people (p = .001; p <
15
.001), as shown in Figure 1A.
16
3.3. COVID-19 Health Practices
17
3.3.1. COVID-19 Seriousness Perception
18
The interaction found with regards to COVID-19 seriousness perception among
19
country, gender and age groups (F(12) = 0.83; p = .62) was not significant. However, a
20
significant interaction between gender and age groups was found in relation to this indi-
21
cator (F(4) = 5.04; p < .001; ηp2 = .20). Male participants from the youngest group (18–28
22
years old) reported greater seriousness perception than males from the 50–59 (p = .003)
23
and >60 age groups (p = .009). Similarly, males from the middle age group (40–49) showed
24
greater seriousness perception than those aged from 50–59 and >60 (p < .001; p < .001).
25
Females from the youngest group reported less seriousness perception compared to males
26
of the same age (p = .01). However, females from the older group (50–59) reported higher
27
scores than males from this age group (p = .002), as shown in Figure 1B.
28
3.3.2. Adherence to Public Health guidelines
29
A significant interaction was found among country, gender and age groups in the
30
case of adherence to health guidelines (F(12) = 2.74; p = .001; ηp2 = .30). Inter-gender by age
31
and country analysis showed significant differences for Colombian females in the 40-49
32
age group, who showed less adherence than their male peers (p = .03). In contrast, Colom-
33
bian females in the 50-59 age group reported greater adherence than males of the same
34
age (p = .01). Meanwhile, Ecuadorian females from the youngest and middle age groups
35
(18–59) showed less adherence than males of the same age (p = .01; p = .01; p = .04). Spanish
36
females aged between 29–39 also reported lower scores than males (p = .02). Similar to
37
Colombian participants, Ecuadorian females in the 50-59 age group reported higher scores
38
than their male peers (p = .04). Chilean females over the age of 60 showed lower scores
39
than males (p = .02) while Spanish females over the age of 60 reported greater adherence
40
(p = .02).
41
Inter-age by gender and country analysis showed that Ecuadorian females aged be-
42
tween 18-28 obtained lower adherence scores than those from the 40–49 and 50–59 age
43
groups in the same country (p = .04; p = .003). Similarly, 40–49 year old Spanish females
44
reported higher scores than those from the 50–59 age group (p = .02). This last group
45
showed lower scores compared to females over the age of 60 (p = .03). Regarding males,
46
those aged over 60 in Spain reported lower adherence scores than those from the 29–39
47
and 40–49 age groups (p = .01; p = .02). Inter-country by gender and age analysis showed
48
that 50-59 year old females from Colombia reported higher levels of adherence than Span-
49
ish females (p = .01). Similarly, Ecuadorian females from the same age group showed
50
higher scores than Spaniards (p = .004). Colombian males in the 50–59 age group reported
51
lower scores than Chilean males of the same age (p = .04). For males over 60, results
52
showed that Spanish males reported lower scores than Chilean males of the same age (p =
53
.04), as shown in Figure 1C.
54
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55
Figure 1. Values for A) perceived stress, B) seriousness perception, and C) health guidelines
56
adherence differentiated by gender, age group and country.
57
3.3.3. Healthy Daily Routines
58
Regarding the practice of healthy daily routines, a three-factor interaction was found
59
among country, gender and age group (F(12) = 3.71; p < .001; ηp2 = .40). In the case of inter-
60
gender by age and country analysis, results showed that 29–39 and 50–59 year old females
61
from Colombia reported higher levels of healthy daily routines than males (p < .001; p =
62
.02). In contrast, 50–59 and >60 year old Chilean males showed higher scores than females
63
(p = .01; p = .006). Spanish females over the age of 60 reported higher levels than males (p
64
= .008).
65
Inter-age by gender and country analysis showed that young females from Colombia
66
reported lower levels than those from the 50–59 age group (p = .05). These differences were
67
also detected in Spain but in the middle age group, where 40–49 year old females reported
68
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healthier routines than those from the 50–59 group (p = .03). This last group showed a
69
significantly higher level than females over 60 (p = .004). However, young Spanish males
70
(29–39) reported higher scores than those aged between 50–59 (p = .05).
71
Inter-country by age and gender analysis showed that 29–39 year old Colombian fe-
72
males reported higher levels than Ecuadorian females of the same age (p = .03). Colombian
73
females aged between 50–59 showed higher levels than Spanish and Chilean females (p =
74
.02; p = .02). Spanish females over 60 reported higher levels than Chileans (p = .02). Re-
75
garding males, Chilean and Spanish males from the 29–39 age group reported higher
76
scores than Colombians (p = .04; p < .001), as shown in Figure 2A.
77
3.4. Self-Care Activities
78
With regards to the total score of self-care activities, the univariate analysis showed
79
no interactions among country, gender and age range for this variable (F(12) = 1,19; p =
80
.29; ηp2 = .01). However, a main effect was detected for gender (F(1) = 7.00; p = .008; ηp2 =
81
.01), which can be explained by the fact that females in general scored higher in self-care
82
activities than males (p = .008), as shown in Figure 2B.
83
84
Figure 2. Values for A) healthy daily routine, and B) self-care differentiated by gender, age group
85
and country.
86
To further examine differences between groups, a second multivariate analysis was
87
conducted on the health consciousness dimension as a key element of self-care.
88
3.4.1. Health Consciousness
89
An interaction was detected for this indicator between gender and country (F(3) =
90
3.08; p = .02; ηp2 = .01). Differences were found for Colombian and Ecuadorian females,
91
who showed a lower level of health consciousness compared to males (p = .007; p < .001).
92
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An interaction was also found between gender and age group (F(4) = 2.92; p = .02; ηp2 =
93
.01). Females from the youngest group reported a significantly lower level of health con-
94
sciousness than the older group (50–59 and above 60) (p = .05; p < .001). Meanwhile, males
95
from the youngest groups reported lower scores than the older groups (29–59) (p = .05; p
96
= .002; p = .03). Inter-gender analysis showed significant differences, as 18 to 59 year old
97
females reported lower levels than their male peers (p = .03; p = .02; p = .003; p = .05). In
98
contrast, no significant differences were found between females and males over 60, as
99
shown in Table 2.
100
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Table 2. ANOVA´s for pair means comparison of main variables interaction.
101
Variable (Likert
scale)
ANOVA
Mean comparison
Dif Mean
Error
P value
95% CI
Perceived stress (1–
6)
Inter–gender by age, F(4) = 2.88, p = .02
Female 18–28 vs male
2.96
.92
.002
1.34
4.78
F(4) = 6.71, p < .001
Female 18–28 vs 40–49
3.12
.89
.005
.62
5.62
Female 18–28 vs 50–59
3.47
.91
.002
.91
6.04
Female 18–28 vs <60
3.96
.92
.000
1.37
6.56
Female 29–39 vs <60
2.62
.86
.024
.19
5.04
F(4) = 6.83, p < .001
Colombia vs Chile
-2.03
.55
.001
-3.47
-.59
Colombia vs Spain
-2.17
.54
.000
-3.59
-.76
Seriousness percep-
tion of COVID–19
pandemic (1–4)
Age x gender
F(4) = 8.14, p < .001
Males 18–28 vs 50–59
.29
.81
.003
.07
.53
Males 18–28 vs > 60
.28
.004
.009
.04
.49
Males 40–49 vs 50–59
.37
.08
< .001
.14
.61
Male 40–49 vs >60
.34
.08
< .001
.12
.57
F(1) = 6.44, p = .01
Female 18–28 vs Male
-.20
.07
.012
-.34
-.04
F(1) = 10.15, p = .002
Female 50–59 vs Male
.27
.08
.002
.10
.43
Public health guide-
lines (1–6)
Inter–gender by age and country
F(4) = 6.48, p = .01
40–49 Colombian females vs males
-.29
.13
.029
-.54
-.03
50–59 Colombian females vs males
.53
.21
.014
.11
.95
F(4) = 7.05, p = .01
18–28 Ecuadorian females vs males
-.63
.24
.010
-1.11
-.16
29–39 Ecuadorian females vs males
-.43
.17
.012
-.77
-.10
50–59 Ecuadorian females vs males
.29
.13
.036
.02
.56
F(4) = 6.27, p = .01
> 60 Chilean females vs males
-.39
.16
.016
-.70
-.08
F(4) = 5.90, p = .01
29–39 Spanish females vs males
-.30
.12
.018
-.55
-.05
F(4) = 5.43, p = .24
> 60 Spanish females vs males
.53
.23
.024
.07
.09
Inter–age by gender and country
F(4) = 4.24, p = .003
Ecuadorian females de 18–28 vs 40–49
-.62
.21
.035
-1.22
-0.03
Ecuadorian females de 18–28 vs 50–59
-.81
.22
.003
-1.42
-.19
F(4) = 3.98, p = .004
Spanish females 40–49 females 50–59
-.56
.17
.017
-1.06
-.06
Spanish females 40–49 females 50–59
-.54
.18
.031
-1.05
-.03
F(4) = 4.50, p = .002
Spanish males 29–39 vs males > 60
.61
.19
.012
.08
1.14
Spanish males 40–49 vs males > 60
.60
.19
.017
.06
1.14
Inter–country by gender and age
F(4) = 5.17, p = .002
50–59 Ecuadorian female vs Spanish
.57
.16
.004
.13
1.01
50–59 Chilean males vs Colombian
.56
.20
.035
.03
1.10
> 60 Chilean males vs Spanish
.59
.21
.036
.02
1.16
Healthy daily rou-
tines (1–6)
Inter–gender by age and country
F(1) = 15.32, p < .001
29–39 Colombian females vs males
1.39
.36
< .001
.68
2.11
F(1) = 6.42, p = .02
50–59 Colombian females vs males
.94
.37
.015
.20
1.69
F(1) = 6.63, p = .01
50–59 Chilean females vs males
-1.10
.43
.014
-1.95
-.24
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F(1) = 8.35, p = .006
> 60 Chilean females vs males
-1.01
.35
.006
-1.72
-.31
F(1) = 7.56, p = .008
> 60 Spanish females vs males
.74
.27
.008
.20
1.28
Inter–age by gender a country, F(4) = 6.42, p = .02
Colombian females 18–28 vs 50–59
-1.12
.39
.046
-2.23
-.01
F(4) = 3.92, p = .005
Spanish females 40–49 vs 50–59
.93
.31
.032
0.05
1.82
Spanish females 50–59 vs > 60
-1.15
.32
.004
-2.07
-.24
F(4) = 3.09, p = .02
Spanish males 29–39 vs 50–59
.97
.34
.046
.01
1.93
Inter–country by age and gender
F(1) = 4.08, p = .009
29–39 Colombian females vs Ecuadorian
1.06
.37
.028
.07
2.05
F(4) = 4.57, p = .005
50–59 Colombian females vs Spanish
1.21
.41
.022
.11
2.31
50–59 Colombian females vs Chilean
1.28
.43
.022
.12
2.44
F(3) = 3.44, p = .02
Spanish females > 60 vs Chilean
1.18
.40
.023
.11
2.24
F(3) = 8.44, p < .001
Colombian males 29–39 vs Chilean
-.93
.32
.024
-1.78
-.08
Colombian males 29–39 vs Spanish
-1.59
.32
.000
-2.45
-.74
Health consciousness
(1–6)
Inter–gender by country, F(1) = 7.36, p = .007
Colombian females vs Colombian
-1.60
.59
.007
-2.76
-.44
F(1) = 13.80, p < .001
Ecuadorian females vs males
-2.11
.57
.000
-3.23
-.99
Intra–gender by age
F(4) = 6.57, p < .001
Female 18–28 vs female 50–59
-1.91
.67
.047
-3.80
-.02
Female 18–28 vs female > 60
-3.44
.67
< .001
-5.33
-1.54
F(4) = 4.09, p < .001
Males 18–28 vs males 29–39
-1.75
.62
.050
-3.49
.00
Males 18–28 vs males 40–49
-2.32
.63
.002
-4.09
-.55
Males 18–28 vs males 50–59
-1.89
.64
.031
-3.69
-.10
Inter–gender by age, F(1) = 4.69, p = .03
Females 18–28 vs males 18–28
-1.35
.62
.031
-2.58
-.12
F(1) = 5.58, p = .02
Females 29–39 vs males 29–39
-1.42
.60
.019
-2.61
-.24
F(1) = 9.18, p = .003
Females 40–49 vs males 40–49
-1.87
.62
.003
-3.09
-.66
F(1) = 3.96, p = .05
Females 50–59 vs males 50–59
-1.34
.67
.048
-2.66
-.01
Nutrition and physi-
cal activity (1–6)
Age main effect
F(4) = 4.66, p = .001
18–28 vs 29–39
1.21
.41
.029
-2.35
-.07
18–28 vs >60
1.39
.42
.009
.21
2.56
40–49 vs > 60
1.19
.42
.041
.03
2.37
Country main effect, F(3) = 4.16, p = .006
Ecuador vs Spain
-1.24
.37
.005
-2.21
-.27
Sleep (1–6)
Inter–age by country
F(4) = 3.55, p = .008
Chilean 29–39 vs 40–49
-1.35
.45
.031
-2.63
-.70
Chilean 29–39 vs >60
-1.41
.46
.025
-2.72
-.10
F(4) = 2.99, p = .02
Ecuadorian 18–28 vs 29–39
1.33
.43
.021
.12
2.54
Inter–country by age
F(3) = 4.66, p = .003
Ecuadorian 29–39 vs Spain 29–39
-1.53
.50
.005
-3.01
-.36
Chilean 29–39 vs Spain 29–39
-1.53
.50
.016
-2.87
-.18
Intra and interper-
sonal coping skills
(1–6)
Intra–gender by age, F(4) = 3.23, p = .01
Female 40–49 vs > 60
-1.57
.47
.008
-2.88
-.25
F(4) = 2.41, p = .05
Male 18–28 vs >60
1.40
.48
.034
.06
2.74
Inter–gender by age, F(1) = 10.94, p = .001
>60 Female vs male
1.62
.49
.001
-.65
2.58
Country main effect, F(3) = 2.98, p = .03
Ecuador vs Spain
-1.24
.37
.005
-2.21
-.27
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4. Discussion
103
104
As it was hypothesized, we found different responses to stress, health practices and
105
self-care according to country, age and gender. Our results suggest that regardless of the
106
country and controlling for income level, females from the youngest age group suffered
107
greater levels of stress, showed a lower level of adherence to health guidelines and re-
108
ported lower levels of health consciousness, in comparison to their male peers and older
109
groups. However, regarding self-care, it seems that females are generally more involved
110
in self-care activities and adopt healthier daily routines than males. Likewise, despite
111
young males perceiving this situation as more severe than their female peers, this result
112
is inverted for females over 50 who reported higher scores than males. The same hap-
113
pened in the case of adherence to health guidelines, as females from the age of 50 showed
114
higher levels than their male peers.
115
These results were mostly consistent among Colombia, Ecuador, and Spain. How-
116
ever, Chile showed some different tendencies as 29-39 year old males showed healthier
117
daily routines than females and better adherence to health guidelines than people from 50
118
to 60 years old. Similarly, females from Colombia and Ecuador aged over 50 showed
119
greater adherence to health guidelines than their Spanish peers. With regards to health
120
consciousness, significantly lower levels in young females were especially noticeable in
121
Colombia and Ecuador.
122
Our findings are in line with several studies conducted in Spain, Austria and UK,
123
which have found that this situation seems to have a higher impact on women and young
124
people, particularly stressful for those < 35 years, people without work, and low income
125
[16,17,23,24,25].
126
Regarding country differences, they could be explained by the fact that the average
127
number of days that people were confined in Spain and Ecuador was higher than in Co-
128
lombia and Chile at the time of the survey (March to April), which is in line with other
129
studies where Latin America and Caribbean clusters showed a lower prevalence of mental
130
health symptoms at that time [17].
131
It may be because of the impact of the coronavirus disease on South America was not
132
as severe as it was in Spain at that point according to epidemiological data from Johns
133
Hopkins University website [1]. In addition, Chile reported a lower percentage of males
134
in charge of children and older people, which may also be a factor in the lower levels of
135
stress suffered by this group, thus enabling them to maintain healthier daily routines and
136
report better adherence to health guidelines [2].
137
Regarding stress, our findings are in line with other studies that have found that
138
emotional well-being worsens during COVID-19 lockdown [6]. In particular, our results
139
on gender and age differences are similar to those that have demonstrated that stress has
140
increased during lockdown and that females and the youngest groups are the most af-
141
fected [4,26]. These findings could be related to the fact that young adults perceived this
142
situation as more severe than older people did. However, young adults reported a lower
143
level of adherence to health guidelines than the older groups. Therefore, this perception
144
of seriousness in young people might be more greatly associated with the impact of the
145
pandemic on their personal situation (i.e. working or studying situation, social life, or
146
changes to their lifestyle) rather than to their perception of the health risks. It may be crit-
147
ical to explore health and risk communications since, as a recent study has suggested,
148
people perceiving greater risks are more likely to implement protective behaviors—espe-
149
cially later (versus earlier) in time [27]. However, these risks may be perceived differently
150
across age ranges and may be different between women or men depending on their per-
151
sonal situation.
152
Concerning gender, the fact that women are reporting higher scores on perceived
153
stress was an expected outcome consistent with previous studies during lockdown [23].
154
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But this differential impact of gender on mental health outcomes goes beyond the pan-
155
demic situation, and could be argued to stem from women’s roles, mainly the burden of
156
both work and caring roles, as well as to the number of social roles women fulfil [31].These
157
gender differences may also contribute to a greater vulnerability for women, not only by
158
contracting the virus, given that the majority of workers in frontline sectors are women,
159
but also because of an overload of their caring role and therefore, an experience of greater
160
stress levels and mental health problems [34].
161
162
In relation to self-care, it has been considered either in clinical samples or general
163
population, as an important factor affecting one’s self-care abilities, perceived control, and
164
knowledge of self-care behaviors [28–30]. In this study, women from the middle age
165
groups onwards seemed to engage in more self-care activities and adopt healthier daily
166
routines than males. This result is in line with previous studies which have supported the
167
mediation role of stress in the relationship between gender and health-promoting behav-
168
iours. Whose results indicated that while women report a wider variety of health promot-
169
ing-behaviour than men, they might refrain from those behaviours because of their levels
170
of general stress, which could be the case of the current pandemic [31]. This fact may also
171
explain why in our study the youngest females whose stress levels were high, reported
172
also less self-care behaviours than older groups. This result is similar to other studies dur-
173
ing the confinement, indicating a direct relationship between physical activity, gender and
174
mental health outcomes [23,32]. Similar to stress and gender discussion, these results
175
might be likely embedded in gendered role behavior as women adopt more caregiving
176
behaviors and use a wider range of self-care activities than men [33]. Therefore, health
177
recommendations may need to focus on gender-informed approaches when health-pro-
178
moting behaviours or self-care.
179
.
180
Nevertheless, these differences went in the opposite direction for the health con-
181
sciousness dimension, as men seemed to be more health-conscious than women. Because
182
of the nature of this dimension, this result may be linked more to their seriousness per-
183
ception and adherence to health guidelines scores, rather than the adoption of self-care
184
activities. Thus, gender differences can vary depending on the dimension of self-care ex-
185
plored. Future research should further examine gender differences with regards to the
186
assessed variables to ascertain their nature.
187
Concerning age, the fact that older people showed better adherence to health guide-
188
lines, health consciousness, and other self-care activities (in comparison with the younger
189
groups) may be explained by two main reasons. On the one hand, the unavoidable differ-
190
ences in lifestyles across age. The daily lives of older adults are less diverse in terms of
191
their social interaction partners. Yet, older adults report greater diversity in activities com-
192
pared to younger adults as they must work or study [35]. These differences could be even
193
more acute within a lockdown experience since confinement has significantly affected the
194
social and studying/working habits and daily routines of young people.
195
On the other hand, health consciousness plays a key role in the adoption of health
196
behaviors in young adults [36]. According to a previous study, older adults (60–92) are
197
more likely to engage in more health-responsible behaviors and score higher in health-
198
promoting behaviors than middle-aged adults (40–59) and younger ones (18–39) [37].
199
These differences could also be explained by the fact that general health guidelines are not
200
being age-targeted in most countries. Most informative and mass media are not adapting
201
their messages to the worries, needs, and resources of young adults and adolescents. Thus,
202
they may not be as health conscious as older people are. Moreover, as a recent qualitative
203
study showed, self-care strategies within the young population are mostly based on social
204
media resources [38], whereas these resources are not being used enough to disseminate
205
adherence to health practices and self-care behavior in these age groups.
206
Therefore, it may be critical to increase health promotion and education through dig-
207
ital resources and social media [39]. Moreover, since young people are very influenced by
208
social norms, it would be essential to adapt health communication to their social identities,
209
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in order to promote social norms and behaviors based on accurate information [40]. How-
210
ever, it should be done without using fear appeals as a health communication strategy
211
[41]. An alternative way to do this might be to focus public messages on the positive health
212
behaviors that people are adopting, rather than focusing on the undesirable ones [42].
213
Nevertheless, some of these behaviors are also greatly influenced by trust in the govern-
214
ment [43]. Thus, differences in national attachment across age groups could influence
215
these results.
216
It is also noteworthy that this lack of adherence is often condemned as irresponsible
217
and selfish, however changing people’s behaviour is simply not as easy as just informing
218
them of the risks. As Van den Broucke [44] highlights, it is well-known in health promo-
219
tion models it is profoundly linked to the fact that people may not consider themselves at
220
risk (e.g. if they have not been in contact with others who have been contaminated), may
221
underestimate the seriousness of the condition (e.g. when they are told that most fatalities
222
are older people or people with pre-existing morbidity) or may not see themselves as ca-
223
pable to perform the preventive behaviours.
224
4.1. Limitations
225
Firstly, this study included people with a similar high socio-economic situation in the
226
four countries that composed our sample. Therefore, these findings may not be repre-
227
sentative for more disadvantaged or vulnerable social groups. Secondly, self-report in-
228
struments were used, where social desirability may have influenced these results and also
229
these instruments were only in the spanish language so it may not capture the full lan-
230
guage diversity of each participant country. However, questions related to sociodemo-
231
graphic data, self-care and health activities sections, were adapted by 8 judges (two for
232
each country) to standardize into Spanish from each of the participating countries.
233
Thirdly, the study has a cross-sectional design, and thus, it is not possible to conclude
234
causal relations between the assessed variables. Lastly, the sample size of the factor age
235
groups could have been too small to detect bigger differences. Another limitation was that
236
due to the characteristics of the sample, there is a different percentage of participation of
237
the population by country, this percentage being higher in Chile and Ecuador.
238
5. Conclusions
239
240
Due to the unquestionable importance of promoting healthy behaviors and self-care
241
in general, especially during a lockdown, socio-economic, age and gender differences
242
should be considered when addressing health recommendations. Developing strategies
243
to get the most vulnerable groups involved in health behaviors, as well as reinforcing
244
those that serve as a role model, could increase the success of people´s adherence to health
245
guidelines and self-care. This would lead to improving the health, wellness, and well-
246
being of individuals, thus reducing the high costs of medical services.
247
248
Therefore, it is mandatory to optimize public policies to make them more health pro-
249
moting, taking into account the social determinants of health and by altering social norms
250
so that the health of all members and groups of society is a priority. In order to do so,
251
some implications for research, policy and practice are described below.
252
253
A more integrative health promotion approach
254
255
On one hand, in the same vein that research has noticeable increased on the impact
256
of the COVID-19 pandemic on mental health outcomes, more systematic research is
257
needed to understand the relationship between health behaviours and mental health out-
258
comes to better understand the short- and long-term consequences of this mental health
259
crisis and explore more comprehensives approaches to address it [45, 46]. On the other
260
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hand, health policies, measures and media are needed to promote greater health behav-
261
iours with a special emphasis on health consciousness and self-care. Enabling people to
262
increase control over their health and its determinants is at the core of health promotion,
263
which paradoxically is more important in this time of crisis than ever before [44]. This
264
health promotion approach can contribute at different levels [47] the downstream level
265
focusing on individual behaviour change and disease management, at the midstream
266
level through interventions affecting organizations and communities and at the upstream
267
level through informing policies affecting the population. As Van den Broucke [44] as
268
pointed out, the expertise with regard to health behaviour change is one of the core com-
269
petencies of health educators and promoters, and their advice may help governments to
270
achieve the required behaviour change.
271
272
A gender-based approach
273
274
Since the impact of COVID-19 pandemic and physical distancing measures on health
275
behaviours drive important health inequalities, especially in those disadvantaged groups,
276
further studies should monitor the differential impacts of the current pandemic across
277
age, gender, socioeconomic disadvantage (in early and adult life) and culture/ethnicity
278
and their possible implications to population health and the widening of health inequali-
279
ties [16]. But also, in order to reduce these health inequities and address immediate and
280
long-term consequences, it is urgent to establish strategies for public health emergencies
281
that take a gender-based approach into account [48,49].
282
283
Intersectionality and community action
284
285
While preventing the further spread of COVID-19 relies heavily on informing and
286
encouraging the population to adopt protective behaviours, these efforts may be more
287
successful if the advice from experts is combined with local community knowledge [44]
288
and intersectoral strategies [49]. According to The Ottawa Charter, it is crucial in health
289
promotion strategies to emphasize the importance of community action, in the sense of
290
needs assessments, setting priorities, joint planning, capacity building, strengthening lo-
291
cal partnerships, intersectoral working and enhancing public participation and social sup-
292
port [50]. All of these activities are aimed to create empowered communities, where indi-
293
viduals and organizations apply their skills and resources in collective efforts to address
294
health priorities and meet their respective health needs. Therefore, community engage-
295
ment can make a substantial difference in health outcomes, and strengthen the capacity
296
to deal with the negative consequences of the pandemic at individual, organizational and
297
community level.
298
299
Funding: This research received no external funding.
300
Acknowledgments: We would like to acknowledge the communication team from the School of
301
Nursing, and the School of Education and Psychology (University of Navarra), as well as Colegio
302
Colombiano de Psicólogos and Silvia Fernanda Maldonado Ormeño, for theirs support and contri-
303
bution to the dissemination of this project.
304
Author Contributions: Three researchers (EBM, EOL and PFB) participated in the first conceptual-
305
ization of the study and first drafting of the manuscript. All nine authors have contributed to the
306
following: the design of the study, data collection, analysis and interpretation of data, revision of
307
the paper for intellectual content and final approval of the version (EBM; EOL; AS; MM; MSG; EYO;
308
CCR; MB and PFB). Three researchers participated in methodology (EBM; EOL E.O and MM) and
309
five researchers participated in writing—review and editing (AS; MSG; CCR; EOL and EBM).
310
Institutional Review Board Statement: The study was conducted according to the guidelines of the
311
Declaration of Helsinki and approved by the Research Ethics Committee of The University of Na-
312
varra (Project ID: 2020.058, data of approval: 01/04/2020).
313
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Informed Consent Statement: Informed consent was obtained from all subjects involved in the
314
study.
315
Data Availability Statement: The data presented in this study are available on request from the
316
corresponding author. The data are not publicly available due to data privacy was agreed with
317
study participants through informed consent.
318
Conflicts of Interest: The authors declare no conflict of interest.
319
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