| Literature DB >> 34911708 |
Elkin Luis1,2, Elena Bermejo-Martins3,4, Martín Martinez1,2, Ainize Sarrionandia5, Cristian Cortes6, Edwin Yair Oliveros7, María Sol Garces8, José Victor Oron9, Pablo Fernández-Berrocal10.
Abstract
OBJECTIVES: To examine the mediation role of self-care between stress and psychological well-being in the general population of four countries and to assess the impact of sociodemographic variables on this relationship.Entities:
Keywords: COVID-19; mental health; preventive medicine; primary care; public health
Mesh:
Year: 2021 PMID: 34911708 PMCID: PMC8678542 DOI: 10.1136/bmjopen-2020-048469
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Descriptive values of the sociodemographic variables, stress, well-being and self-care scores in the four countries and of the total sample
| Spain | Chile | Colombia | Ecuador | Total | ANOVA p value | |
| Sample size | 271 | 261 | 268 | 282 | 1082 | |
| Age, mean (SD) | 43.8 (15.7) | 43.9 (14.5) | 44 (14.8) | 44 (14.8) | 43.8 (15.1) | 0.99 |
| Gender, n (%) | ||||||
| Female | 136 (50.2) | 127 (48.7) | 131 (48.9) | 137 (48.6) | 531 (49.1) | |
| Male | 135 (49.8) | 134 (51.4) | 137 (51.1) | 145 (51.4) | 551 (50.9) | |
| Psychological variables, mean (SD) | ||||||
| Stress | 17.0 (6.1) | 17 (6.2) | 15.3 (6.3) | 16.2 (6.3) | 16.4 (6.4) | 0.001 |
| Well-being | 30.6 (5.8) | 31.5 (5.9) | 32.6 (5.4) | 32.2 (5.7) | 31.7 (5.7) | 0.33 |
| Self-care | 58.5 (9.1) | 58.2 (11) | 59.9 (9.3) | 59.1 (10.1) | 58.9 (9.9) | 0.22 |
| Income level, n (%) | ||||||
| No salary | 45 (16.6) | 27 (10.3) | 43 (16) | 43 (15.2) | 158 (14.6) | |
| One mw | 9 (3.3) | 22 (8.4) | 37 (13.8) | 19 (6.7) | 87 (8) | |
| Two mw | 30 (11) | 36 (13.8) | 37 (13.8) | 42 (15) | 145 (13.4) | |
| Three mw | 50 (18.5) | 35 (13.4) | 68 (25.3) | 36 (12.7) | 189 (17.5) | |
| Four mw | 59 (21.7) | 34 (13) | 30 (12) | 52 (18.4) | 175 (16.2) | |
| Five mw | 78 (28.8) | 107 (41) | 53 (19.7) | 90 (32) | 328 (30.3) | |
| Educational level, n (%) | ||||||
| Elementary | 4 (1.48) | 4 (1.53) | 1 (0.4) | 2 (0.7) | 11 (1) | |
| High school | 42 (15.5) | 28 (7.0) | 35 (13.5) | 48 (17.0) | 153 (14.1) | |
| Technical | 37 (13.7) | 33 (12.7) | 40 (15.3) | 12 (4.3) | 122 (11.3) | |
| University | 188 (69.3) | 196 (75.1) | 192 (74.5) | 220 (78) | 796 (73.6) | |
| COVID-19 variables, n (%) | ||||||
| Confinement days | 21 (4.6) | 17.5 (6.5) | 17 (4.0) | 25 (0.6) | 20.24 (5.51) | |
| Front-line workers (yes) | 80 (29.5) | 80 (30.7) | 131 (48.9) | 76 (27) | 367 (33.9) | |
| Health risk (yes) | 89 (32.8) | 84 (32.2) | 77 (28.7) | 87 (30.9) | 337 (31.1) | |
| Employment changes (yes) | 46 (17) | 51 (19.5) | 87 (32.4) | 87 (31) | 271 (25) | |
| Accompanied during lockdown (yes) | 231 (85.2) | 237 (91) | 266 (99.2) | 248 (88) | 982 (90.8) | |
| Community resources (yes) | 245 (90.4) | 233 (89.2) | 225(84) | 251 (89) | 936 (85.5) | |
| Children in charge (yes) | 63 (23.2) | 86 (33) | 93 (34.7) | 95 (33.6) | 337 (31.1) | |
| Older people in charge (yes) | 29 (10.5) | 57 (22) | 106 (39.5) | 95 (33.6) | 287 (26.5) | |
Age, stress, well-being and self-care were coded as continuous variables, gender was coded as nominal variable, and income and educational levels were coded as ordinal variables. All COVID-19 variables were nominal with the exception of the number of confinement days, which was continuous.
ANOVA, analysis of variance; mw, minimun wage.
Data on the multiple linear regression models of stress, well-being and self-care based on sociodemographics and COVID-19-related variables
| Variable | 1. Stress | 2. Well-being | 3. Self-care | ||||||||||||
| ß | SE | 95% CI | P value | ß | SE | 95% CI | P value | ß | SE | 95% CI | P value | ||||
| LL | UL | LL | UL | LL | UL | ||||||||||
| Age | −0.134 | 0.01 | −0.08 | −0.03 | <0.001 | 0.10 | 0.42 | 0.05 | 0.21 | <0.001 | 0.07 | 0.02 | 0.01 | 0.09 | <0.02 |
| Educational level | −0.107 | 0.27 | 1.42 | −0.35 | <0.001 | 0.07 | 0.87 | 0.30 | 3.7 | <0.01 | |||||
| Income level | −0.114 | 0.12 | −0.66 | −0.16 | <0.001 | 0.14 | 0.30 | 0.91 | 2.48 | <0.001 | 0.07 | 0.18 | 0.04 | 0.77 | <0.02 |
|
|
|
|
|
|
| ||||||||||
| Gender | 0.91 | <0.01 | 2.47 | <0.01 | −1.84 | <0.002 | |||||||||
| Country | −0.169 | <0.001 | 1.52 | <0.02 | |||||||||||
| Accompaniment in confinement | −2.042 | <0.001 | 5.21 | <0.01 | |||||||||||
| Work situation changes | 0.99 | <0.01 | |||||||||||||
|
| |||||||||||||||
|
|
|
|
|
| |||||||||||
| Age | 0.16 | 0.04 | 0.13 | 0.30 | <0.001 | ||||||||||
| Stress | −0.62 | 0.07 | −2.12 | −1.84 | <0.001 | ||||||||||
| Self-care | 0.22 | 0.04 | 0.37 | 0.54 | <0.001 | ||||||||||
ß: standardised coefficients are reported for continuous and ordinal variables; b: unstandardised coefficients are reported for nominal variables.
LL, lower limit CI; UL, upper limit CI.
Pearson’s correlations between the variables included in the mediation analyses
| Variables | 1 | 2 | 3 | 4 | |
| 1. Stress | r | ||||
| P value | |||||
| 2. Well-being | r | −0.677 | |||
| P value | <0.001 | ||||
| 3. Self-care | r | −0.213 | 0.359 | ||
| P value | <0.001 | <0.001 | |||
| 4. Age | r | −0.182 | 0.153 | 0.092 | |
| P value | <0.001 | <0.001 | 0.014 | ||
Figure 1Mediation model of self-care in the relationship between stress and well-being controlled with standardised coefficients.
Data on the estimated mediation models (corresponding to the indirect and direct paths) for the total sample and differentiated by country
| Variables | Stress (X) and self-care (M) | Self-care (M) and well-being (Y) | Stress (X) and well-being (Y) | |||||||||
| Coef* | SE | 95% CI | P value | Coef* | SE | 95% CI | P value | Coef* | SE | 95% CI | P value | |
| Total sample | ||||||||||||
| a | −0.32 | 0.05 | −0.41 to −0.22 | <0.001 | ||||||||
| b | 0.46 | 0.04 | 0.37 to 0.55 | <0.001 | ||||||||
| c | −1.98 | 0.07 | −2.13 to −1.85 | <0.001 | ||||||||
| c’ | −2.13 | 0.07 | −2.27 to −1.99 | <0.001 | ||||||||
| Age | 0.04 | 0.01 | −0.01 to 0.08 | <0.06 | 0.01 | 0.02 | −0.03 to 0.08 | <0.39 | ||||
| Stress and self-care as predictors of well-being, R2/ | 0.51/370.01 | Stress as a predictor of well-being, R2/ | 0.46/223.34 | |||||||||
| Spanish sample | ||||||||||||
| a | −0.21 | 0.09 | −0.39 to −0.34 | <0.01 | ||||||||
| b | 0.33 | 0.09 | 0.14 to 0.53 | <0.001 | ||||||||
| c | −1.73 | 0.14 | −2.02 to −1.45 | <0.001 | ||||||||
| c’ | −1.81 | 0.14 | −2.10 to −1.52 | <0.001 | ||||||||
| Age | −0.03 | 0.03 | −0.10 to 0.04 | <0.34 | −0.04 | 0.65 | −0.15 to 0.07 | <0.49 | ||||
| Stress and self-care as predictors of well-being, R2/ | 0.39/56.6 | Stress as a predictor of well-being, R2/ | 0.36/75.76 | |||||||||
| Chilean sample | ||||||||||||
| a | −0.48 | 0.09 | −0.67 to −0.28 | <0.001 | ||||||||
| b | 0.50 | 0.08 | 0.33 to 0.67 | <0.001 | ||||||||
| c | −1.84 | 0.07 | −2.12 to −1.56 | <0.001 | ||||||||
| c’ | −2.08 | 0.14 | −2.37 to −1.80 | <0.001 | ||||||||
| Age | 0.11 | 0.04 | 0.03 to 0.20 | <0.01 | 0.03 | 0.06 | −0.08 to −0.15 | <0.59 | ||||
| Stress and self-care as predictors of well-being, R2/ | 0.52/96.45 | Stress as a predictor of well-being, R2/ | 0.46/112.47 | |||||||||
| Colombian sample | ||||||||||||
| a | −0.25 | 0.08 | −0.43 to −0.07 | <0.001 | ||||||||
| b | 0.55 | 0.09 | 0.36 to 0.74 | <0.001 | ||||||||
| c | −2.16 | 0.14 | −2.44 to −1.88 | <0.001 | ||||||||
| c’ | −2.30 | 0.14 | −2.60 to −2.01 | <0.001 | ||||||||
| Age | 0.06 | 0.04 | −0.01 to 0.14 | <0.09 | 0.03 | 0.06 | −0.09 to −0.15 | <0.61 | ||||
| Stress and self-care as predictors of well-being, R2/ | 0.54/105.09 | Stress as a predictor of well-being, R2/ | 0.48/125.88 | |||||||||
| Ecuadorian sample | ||||||||||||
| a | −0.26 | 0.09 | −0.45 to −0.06 | <0.001 | ||||||||
| b | 0.44 | 0.08 | 0.29 to 0.60 | <0.001 | ||||||||
| c | −2.25 | 0.13 | −2.51 to −1.98 | <0.001 | ||||||||
| c’ | −2.36 | 0.13 | −2.63 to −2.09 | <0.001 | ||||||||
| Age | 0.02 | 0.04 | −0.05 to 0.10 | <0.55 | 0.04 | 0.05 | −0.06 to 0.15 | <0.43 | ||||
| Stress and self-care as predictors of well-being, R2/ | 0.58/131.12 | Stress as a predictor of well-being, R2/ | 0.54/163.78 | |||||||||
X= Independent variable; M= mediator; Y= Dependent variable.
*Unstandardised coefficients.