Mental Distress during the Coronavirus Pandemic in Israel: Who Are the Most Vulnerable?
Abstract
:1. Introduction
1.1. Mental Distress and Associated Factors
1.2. Theoretical Background
1.3. The Current Study
2. Materials and Methods
2.1. Sample
2.2. Process
2.3. Measurement
2.3.1. Mental Distress
2.3.2. SES Variables
2.3.3. Changes in Economic Situation following the COVID-19 Outbreak
2.3.4. The Number of Areas in Which They Needed Support
2.3.5. Sociodemographic Variables
2.4. Data Analysis
2.5. Ethical Considerations
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | N | %/Mean (SD) |
---|---|---|
Sociodemographic | ||
Age | ||
20–24 | 29 | 10.6 |
25–35 | 90 | 33 |
36–54 | 119 | 43.6 |
55–68 | 35 | 12.8 |
Female (=1) | 187 | 68.5% |
Immigrant (=1) | 44 | 16.3% |
Married (=1) | 168 | 61.5% |
Children (=1) | 179 | 65.6% |
Education (post high school =1) | 146 | 53.5% |
Health problem in the household (=1) | 60 | 20.0% |
SES Monthly household income | ||
Less than 3000 NIS | 26 | 9.5% |
3000–7000 NIS | 94 | 36.3% |
7000–15,000 NIS | 64 | 23.4% |
15,000–22,000 NIS | 49 | 17.9% |
22,000 and above | 34 | 12.5% |
Housing density * (=1) | 27.5% | |
Economic effects of COVID-19 | ||
Employment | ||
Employed | 94 | 34.4% |
Reduced employment | 44 | 16.1% |
Unemployed ** | 112 | 41.0% |
Increase in expenses (=1) | 164 | 60.1% |
Negative change in economic situation (=1) | 150 | 54.9% |
Took out loans (=1) | 32 | 11.7% |
Needs for support (0–6) | 0.61 (1.03) | |
Received informal support (=1) | 121 | 44.3% |
Mental Distress (7–42) | 20.34 (8.47) |
Sociodemographic | Mental Distress Mean (SD) | F/t-Test/Pearson Correlation |
---|---|---|
Age | ||
20–24 | 22.52 (8.81) | F = 1.56 |
25–35 | 19.18 (7.31) | |
36–54 | 20.25 (8.85) | |
55–68 | 22.09 (9.49) | |
Gender | ||
Male | 19.38 (8.92) | t = 1.25 |
Female | 20.80 (8.23) | |
Birth country | ||
Israel | 19.83 (8.15) | t = 3.09 ** |
Other | 24.02 (9.23) | |
Marital status | ||
Married | 19.21 (7.90) | t = 2.67 ** |
Other | 22.07 (9.04) | |
Have kids | ||
Yes | 20.23 (8.49) | t = 0.30 |
No | 20.56 (8.48) | |
Education | ||
High school or below | 22.96 (9.01) | t = 4.79 *** |
Post high school | 17.99 (7.29) | |
Health problem in the household | ||
Yes | 23.79 (8.51) | t = 5.72 *** |
No | 17.97 (7.60) | |
SES before COVID-19 | ||
Income | r = −0.33 *** | |
Housing density | ||
Yes | 20.51 (8.34) | t = 0.41 |
No | 20.02 (8.49) | |
Economic effects of COVID-19 | ||
Employment | ||
Continued | 16.17 (6.40) | F= 17.57 *** |
Unemployed | 20.90 (8.09) a | |
Reduced employment | 22.70 (8.50) a | |
Increase in expenses | ||
Yes | 23.79 (8.52) | t = 5.72 *** |
No | 17.97 (7.60) | |
Loans | ||
Yes | 26.57 (8.58) | t = 4.44 *** |
No | 19.51 (8.12) | |
Worsened economic situation | ||
Yes | 23.64 (8.58) | t = 8.69 *** |
No | 15.79 (5.80) | |
Needs for support (0–6) | r = 0.42 *** | |
Received informal support | ||
Yes | 23.91 (8.21) | t = 6.85 *** |
No | 17.17 (7.38) |
Variables | Model 1 | Model 2 | Model 3 | ||||||
---|---|---|---|---|---|---|---|---|---|
B | S.E.B | β | B | S.E.B | β | B | S.E.B | β | |
Sociodemographic | |||||||||
Gender (female = 1) | 2.68 | 1.07 | 0.15 | 2.11 | 1.05 | 0.12 | 1.09 | 0.09 | 0.06 |
Country of birth (immigrant = 1) | 2.24 | 1.38 | 0.10 | 2.07 | 1.34 | 0.09 | 1.92 | 1.13 | 0.09 |
Marital status (married = 1) | 0.18 | 1.13 | 0.01 | −0.56 | 1.11 | −0.03 | −0.73 | 0.93 | −0.04 |
Education (post high school = 1) | −2.75 | 1.23 | −0.17 * | −2.27 | 1.20 | −0.14 | −1.20 | 1.01 | −0.07 |
Income (1–5) | −1.48 | 0.56 | −0.20 ** | −0.95 | 0.56 | −0.13 | −0.07 | 0.48 | −0.01 |
Health problems (yes = 1) | 4.43 | 1.25 | 0.21 *** | 4.24 | 1.21 | 0.20 *** | 3.68 | 1.01 | 0.18 *** |
Employment | |||||||||
Unemployed (=1) | 4.58 | 1.13 | 0.28 *** | 0.88 | 1.10 | 0.05 | |||
Reduced employment (=1) | 3.89 | 1.43 | 0.17 ** | 2.29 | 1.32 | 0.10 | |||
Economic effects of COVID-19 | |||||||||
Increase in expenses (yes = 1) | −0.99 | 0.94 | −0.06 | ||||||
Loans (yes = 1) | 3.05 | 1.32 | 0.12 * | ||||||
Worsened economic situation (yes = 1) | 3.62 | 1.08 | 0.22 *** | ||||||
Needs for support (0–6) | 1.94 | 0.43 | 0.25 *** | ||||||
Received informal support (yes = 1) | 4.39 | 0.88 | 0.26 *** | ||||||
R2 | 0.21 *** | 0.26 *** | 0.50 *** | ||||||
ΔR2 | - | 0.06 *** | 0.24 *** |
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Refaeli, T.; Krumer-Nevo, M. Mental Distress during the Coronavirus Pandemic in Israel: Who Are the Most Vulnerable? Int. J. Environ. Res. Public Health 2022, 19, 124. https://doi.org/10.3390/ijerph19010124
Refaeli T, Krumer-Nevo M. Mental Distress during the Coronavirus Pandemic in Israel: Who Are the Most Vulnerable? International Journal of Environmental Research and Public Health. 2022; 19(1):124. https://doi.org/10.3390/ijerph19010124
Chicago/Turabian StyleRefaeli, Tehila, and Michal Krumer-Nevo. 2022. "Mental Distress during the Coronavirus Pandemic in Israel: Who Are the Most Vulnerable?" International Journal of Environmental Research and Public Health 19, no. 1: 124. https://doi.org/10.3390/ijerph19010124