| Literature DB >> 35567688 |
Song Pu1, Jamshid Ali Turi2, Wang Bo3,4, Chen Zheng5, Dandan Tang3, Wasim Iqbal6.
Abstract
History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.Entities:
Keywords: COVID-19 pandemic; Environmentalism; Financial consideration; Financial impact; Naturalism; Psychological ffects; Sustainability
Year: 2022 PMID: 35567688 PMCID: PMC9107217 DOI: 10.1007/s11356-022-20387-8
Source DB: PubMed Journal: Environ Sci Pollut Res Int ISSN: 0944-1344 Impact factor: 5.190
Fig. 1Virus’s exponential increase during its outbreak in Dec 2019 to its peak in May 2020 .
Source: World Health Organization (WHO)
Fig. 2Theoretical framework. Note: Health consciousness (HCON), naturalism (NATU), meditation and self-development (MESD), environmentalism (ENVS), sustainability (SUST), compassion (COMP), gregariousness (GREG), sympathy (SYMP), and cooperation (CPRT), COVID-19 prevention (COVIDP)
Demographic details of encompassing the pragmatic approach COVID-19
| Sample characteristics | Frequency | Percentage |
|---|---|---|
| Gender | ||
| Female | 168 | 40.9% |
| Male | 243 | 59.1% |
| Age | ||
| 30–40 years | 103 | 25.1% |
| 41–50 years | 185 | 45% |
| 51–60 years | 123 | 29.9% |
| Education level | ||
| BS | 174 | 42.3% |
| MS | 36 | 8.8% |
| Diploma | 201 | 48.9% |
| Marital status | ||
| Married | 298 | 72.5% |
| Unmarried | 113 | 27.5% |
| Respondent’s domain expertise | ||
| Technical person | 213 | 51.8% |
| Medical Sciences | 62 | 15.1% |
| Engineering Sciences | 102 | 34.8% |
| Other | 34 | 8.3% |
Source: Authors’ calculation
Descriptive statistics of the data
| Variables | Items | Observations | Coefficient of variation (CV) | Mean | Std. dev |
|---|---|---|---|---|---|
| HCON | 5 | 411 | 0.139 | 3.52 | 0.489 |
| NATU | 4 | 411 | 0.555 | 2.701 | 1.498 |
| MESD | 4 | 411 | 0.076 | 3.213 | 0.243 |
| ENVS | 3 | 411 | 0.122 | 3.808 | 0.465 |
| SUST | 2 | 411 | 0.212 | 2.592 | 0.55 |
| COMP | 3 | 411 | 0.571 | 2.895 | 1.652 |
| GREG | 2 | 411 | 0.479 | 3.672 | 1.760 |
| SYMP | 7 | 411 | 0.638 | 3.052 | 1.947 |
| CPRT | 7 | 411 | 0.287 | 3.048 | 0.874 |
| COVIDP | 7 | 411 | 0.551 | 3.036 | 1.674 |
Health consciousness (HCON), naturalism (NATU), meditation and self-development (MESD), environmentalism (ENVS), sustainability (SUST), compassion (COMP), gregariousness (GREG), sympathy (SYMP), cooperation (CPRT), COVID-19 prevention (COVIDP)
Correlation and discriminant validity analysis
| Variables | HCON | NATU | MESD | ENVS | SUST | COMP | GREG | SYMP | CPRT | COVIDP | AVE | MSV |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HCON | (0.715) | 0.512 | 0.122 | |||||||||
| NATU | 0.267 | (0.821) | 0.674 | 0.292 | ||||||||
| MESD | 0.349 | 0.54 | (0.802) | 0.643 | 0.292 | |||||||
| ENVS | 0.304 | 0.16 | 0.352 | (0.844) | 0.712 | 0.124 | ||||||
| SUST | 0.155 | 0.354 | 0.259 | 0.227 | (0.824) | 0.678 | 0.445 | |||||
| COMP | 0.284 | 0.493 | 0.429 | 0.216 | 0.667 | (0.744) | 0.554 | 0.445 | ||||
| GREG | 0.187 | 0.632 | 0.599 | 0.205 | 0.189 | 0.583 | (0.740) | 0.977 | 0.371 | |||
| SYMP | 0.1526 | 0.771 | 0.769 | 0.194 | 0.381 | 0.956 | 0.531 | (0.706) | 0.531 | 0.106 | ||
| CPRT | 0.1182 | 0.91 | 0.939 | 0.183 | 0.573 | 0.329 | 0.085 | 0.841 | (0.797) | 0.585 | 0.841 | |
| COVIDP | 0.0838 | 0.049 | 0.109 | 0.172 | 0.765 | 0.702 | 0.639 | 0.576 | 0.513 | (0.845) | 0.639 | 0.576 |
Diagonal values in parentheses represent the root square of AVEs
The results of reliability analysis and factor loadings
| Variables | Items | Standard loadings | Cronbach-α | CR |
|---|---|---|---|---|
| Health consciousness | 0.813 | 0.807 | ||
| HCON 1 | 0.737 | |||
| HCON 2 | 0.802 | |||
| HCON 3 | 0.92 | |||
| HCON 4 | 0.866 | |||
| HCON 5 | 0.88 | |||
| Naturalism | 0.916 | 0.935 | ||
| NATU 1 | 0.719 | |||
| NATU 2 | 0.731 | |||
| NATU 3 | 0.731 | |||
| NATU 4 | 0.675 | |||
| Meditation and self-development | 0.91 | 0.915 | ||
| MESD 1 | 0.88 | |||
| MESD 2 | 0.959 | |||
| MESD 3 | 0.709 | |||
| MESD 4 | 0.695 | |||
| Environmentalism | 0.903 | 0.925 | ||
| Sustainability | ENVS 1 | 0.634 | ||
| ENVS 2 | 0.841 | |||
| ENVS 3 | 0.802 | |||
| ENVS 4 | 0.869 | |||
| ENVS 5 | 0.833 | |||
| ENVS 6 | 0.835 | |||
| ENVS 7 | 0.893 | |||
| 0.832 | 0.893 | |||
| SUST 1 | 0.851 | |||
| SUST 2 | 0.736 | |||
| SUST 3 | 0.661 | |||
| SUST 4 | 0.914 | |||
| SUST 5 | 0.907 | |||
| SUST 6 | 0.657 | |||
| Compassion | 0.809 | 0.832 | ||
| COMP 1 | 0.746 | |||
| COMP 2 | 0.71 | |||
| COMP 3 | 0.762 | |||
| COMP 4 | 0.609 | |||
| Gregariousness | 0.916 | 0.935 | ||
| GREG 1 | 0.719 | |||
| GREG 2 | 0.731 | |||
| GREG 3 | 0.731 | |||
| GREG 4 | 0.675 | |||
| Sympathy | 0.91 | 0.915 | ||
| SYMP 1 | 0.88 | |||
| SYMP 2 | 0.959 | |||
| SYMP 3 | 0.709 | |||
| Cooperation | 0.903 | 0.925 | ||
| CPRT 1 | 0.751 | |||
| CPRT 2 | 0.634 | |||
| CPRT 3 | 0.841 | |||
| CPRT 4 | 0.802 | |||
| COVID-19 prevention | 0.832 | 0.893 | ||
| COVIDR 1 | 0.869 | |||
| COVIDR 2 | 0.833 | |||
| COVIDR 3 | 0.835 | |||
| COVIDR 4 | 0.893 | |||
Rotation method: promax with Kaiser normalization; extraction method: maximum likelihood
The results of the collinearity diagnostics test
| Variables | Statistics for collinearity | |
|---|---|---|
| Tolerance | VIF | |
| HCON | 0.84447 | 1.16028 |
| NATU | 0.92763 | 1.05633 |
| MESD | 0.79299 | 1.23552 |
| ENVS | 0.82764 | 1.18404 |
| SUST | 0.93654 | 1.04643 |
| COMP | 0.78498 | 1.22304 |
| GREG | 0.81928 | 1.17208 |
| SYMP | 0.78498 | 1.22304 |
| CPRT | 0.81928 | 1.17208 |
| COVIDP | 0.92708 | 1.03586 |
Dependent variable: COVIDP
Bartlett’s test and Kaiser–Meyer–Olkin (KMO)
| KMO and Bartlett's test | ||
|---|---|---|
| Kaiser–Meyer–Olkin measure of sampling adequacy | 0.908 | |
| 6,874.96 | ||
| 435 | ||
| 0.000 | ||
Sig significance, df degree of freedom
Communalities findings
| Variables | Communalities | |
|---|---|---|
| Initial | Extraction | |
| HCON | 1 | 0.560 |
| NATU | 1 | 0.699 |
| MESD | 1 | 0.890 |
| ENVS | 1 | 0.592 |
| SUST | 1 | 0.649 |
| COMP | 1 | 0.791 |
| GREG | 1 | 0.946 |
| SYMP | 1 | 0.558 |
| CPRT | 1 | 0.674 |
| COVIDP | 1 | 0.745 |
Maximum likelihood: extraction method
Cumulative variance and eigenvalues
| Variables | Eigenvalues (initial) | Squared loadings extraction sums | ||||
|---|---|---|---|---|---|---|
| Total | Variance % | % Cumulative | Total | Variance % | % Cumulative | |
| 1 | 9.669 | 32.229 | 32.229 | 9.28 | 30.935 | 30.935 |
| 2 | 3.746 | 12.487 | 44.716 | 3.418 | 11.394 | 42.329 |
| 3 | 3 | 10 | 54.715 | 2.635 | 8.784 | 51.114 |
| 4 | 2.083 | 6.942 | 61.658 | 1.695 | 5.65 | 56.764 |
| 5 | 1.983 | 6.611 | 68.269 | 1.65 | 5.499 | 62.263 |
| 6 | 1.141 | 3.804 | 72.073 | 0.8 | 2.667 | 64.93 |
| 7 | 8.79879 | 29.32839 | 29.32839 | 8.4448 | 28.15085 | 28.15085 |
| 8 | 3.40886 | 11.36317 | 40.69156 | 3.11038 | 10.36854 | 38.51939 |
| 9 | 2.73 | 9.1 | 49.79065 | 2.39785 | 7.99344 | 46.51374 |
| 10 | 1.89553 | 6.31722 | 56.10878 | 1.54245 | 5.1415 | 61.65524 |
Rotation method: promax with Kaiser normalization, cumulative variance: 61.65524%
Fig. 3Hypothesis path analysis
Hypotheses’ results
| Hypotheses | Structural paths | Description | ||
|---|---|---|---|---|
| H1 | HCON → COVIDP | 0.042*** | 2.042 | Not different |
| H2 | NATU → COVIDP | 0.742 | 7.963 | Not different |
| H3 | MESD → COVIDP | 0.501*** | 5.236 | Not different |
| H4 | ENVS → COVIDP | 0.043*** | 2.163 | Not different |
| H5 | SUST → COVIDP | 0.354** | 3.168 | Not different |
| H6 | COMP → COVIDP | 0.654*** | 6.688 | Not different |
| H7 | GREG → COVIDP | 0.068*** | 2.636 | Not different |
| H8 | SYMP → COVIDP | 0.509*** | 5.123 | Not different |
| H9 | CPRT → COVIDP | 0.687** | 6.816 | Not different |
***p < 0.01, **p < 0.05, *p < 0.1
Endogeneity test
| Hypotheses | Structural paths | Description | ||
|---|---|---|---|---|
| H1 | HCON ® COVIDP | 0.132*** | 2.953 | Not different |
| H2 | NATU ® COVIDP | 0.354 | 8.702 | Not different |
| H3 | MESD ® COVIDP | 0.471*** | 2.171 | Not different |
| H4 | ENVS ® COVIDP | 0.383*** | 3.265 | Not different |
| H5 | SUST ® COVIDP | 0.186** | 6.761 | Not different |
| H6 | COMP ® COVIDP | 0.354 | 8.702 | Not different |
| H7 | GREG ® COVIDP | 0.471*** | 2.171 | Not different |
| H8 | SYMP ® COVIDP | 0.383*** | 3.265 | Not different |
| H9 | CPRT ® COVIDP | 0.186** | 6.761 | Not different |
***p < 0.00, **p < 0.01, *p < 0.05
Fig. 4Word cloud of the data
Fig. 5word count of the data. Note: Health consciousness (HCON), naturalism (NATU), meditation and self-development (MESD), environmentalism (ENVS), sustainability (SUST), compassion (COMP), gregariousness (GREG), sympathy (SYMP), and cooperation (CPRT)