| Literature DB >> 33462563 |
Roy Rillera Marzo1, Akansha Singh2, Roushney Fatima Mukti3.
Abstract
INTRODUCTION: Previous studies conducted on the psychological impact of infectious outbreaks have found heavy psychological burdens among general population with more severe affect in the current pandemic. The main aim of this study is to examine the level of psychological distress during COVID-19 in Bangladesh and explore factors associated with higher psychological distress.Entities:
Keywords: COVID-19; Peritraumatic distress index; Psychological distress
Year: 2021 PMID: 33462563 PMCID: PMC7806495 DOI: 10.1016/j.cegh.2020.100693
Source DB: PubMed Journal: Clin Epidemiol Glob Health ISSN: 2213-3984
Presence of Covid19 peri-traumatic distress index (CPDI), Bangladesh.
| Symptoms | Never n,(%) | Occasionally n,(%) | Sometimes n,(%) | Often n,(%) | Always n,(%) |
|---|---|---|---|---|---|
| S1 | 35(7.0) | 76(15.1) | 215(42.7) | 111(22.1) | 66(13.1) |
| S2 | 263(52.3) | 107(21.3) | 77(15.3) | 40(8.0) | 16(3.2) |
| S3 | 39(7.8) | 103(20.5) | 150(29.8) | 116(23.1) | 95(18.9) |
| S4 | 148(29.4) | 101(20.1) | 129(25.6) | 78(15.5) | 47(9.3) |
| S5 | 5(1.0) | 10(2.0) | 28(5.6) | 67(13.3) | 393(78.1) |
| S6 | 59(11.7) | 91(18.1) | 148(29.4) | 126(25.0) | 79(15.7) |
| S7 | 144(28.6) | 114(22.7) | 113(22.5) | 89(17.7) | 43(8.5) |
| S8 | 138(27.4) | 118(23.5) | 105(20.9) | 70(13.9) | 72(14.3) |
| S9 | 433(86.1) | 33(6.6) | 14(2.8) | 12(2.4) | 11(2.2) |
| S10 | 373(74.2) | 52(10.3) | 46(9.1) | 14(2.8) | 18(3.6) |
| S11 | 340(67.6) | 75(14.9) | 50(9.9) | 28(5.6) | 10(2.0) |
| S12 | 252(50.1) | 95(18.9) | 100(19.9) | 40(8.0) | 16(3.2) |
| S13 | 213(42.3) | 126(25.0) | 93(18.5) | 52(10.3) | 19(3.8) |
| S14 | 105(20.9) | 121(24.1) | 130(25.8) | 97(19.3) | 50(9.9) |
| S15 | 122(24.3) | 118(23.5) | 126(25.0) | 107(21.3) | 30(6.0) |
| S16 | 118(23.5) | 118(23.5) | 123(24.5) | 107(21.3) | 37(7.4) |
| S17 | 158(31.4) | 125(24.9) | 118(23.5) | 71(14.1) | 31(6.2) |
| S18 | 269(53.5) | 99(19.7) | 73(14.5) | 53(10.5) | 9(1.8) |
| S19 | 275(54.7) | 119(23.7) | 69(13.7) | 31(6.2) | 9(1.8) |
| S20 | 259(51.5) | 96(19.1) | 79(15.7) | 46(9.1) | 23(4.6) |
| S21 | 281(55.9) | 84(16.7) | 65(12.9) | 51(10.1) | 22(4.4) |
| S22 | 403(80.1) | 52(10.3) | 26(5.2) | 18(3.6) | 4(0.8) |
| S23 | 164(32.6) | 130(25.8) | 91(18.1) | 76(15.1) | 42(8.3) |
| S24 | 344(68.4) | 77(15.3) | 37(7.4) | 29(5.8) | 16(3.2) |
Descriptive statistics and internal consistency of OVID19 Peri-traumatic distress index (CPDI), Bangladesh.
| Symptoms | Mean | SD | Corrected Item-Total Correlation | Cronbach's Alpha if Item Deleted |
|---|---|---|---|---|
| S1 | 2.2 | 1.1 | .509 | .869 |
| S2 | 0.9 | 1.1 | .283 | .875 |
| S3 | 2.2 | 1.2 | .438 | .871 |
| S4 | 1.6 | 1.3 | .654 | .863 |
| S5 | 3.7 | 0.8 | .047 | .879 |
| S6 | 2.1 | 1.2 | .396 | .872 |
| S7 | 1.5 | 1.3 | .398 | .872 |
| S8 | 1.6 | 1.4 | .315 | .875 |
| S9 | 0.3 | 0.8 | .192 | .876 |
| S10 | 0.5 | 1.0 | .228 | .876 |
| S11 | 0.6 | 1.0 | .281 | .875 |
| S12 | 1.0 | 1.1 | .273 | .875 |
| S13 | 1.1 | 1.2 | .558 | .867 |
| S14 | 1.7 | 1.3 | .681 | .863 |
| S15 | 1.6 | 1.2 | .683 | .863 |
| S16 | 1.7 | 1.3 | .664 | .863 |
| S17 | 1.4 | 1.2 | .650 | .864 |
| S18 | 0.9 | 1.1 | .528 | .868 |
| S19 | 0.8 | 1.0 | .503 | .869 |
| S20 | 1.0 | 1.2 | .531 | .868 |
| S21 | 0.9 | 1.2 | .493 | .869 |
| S22 | 0.3 | 0.8 | .381 | .872 |
| S23 | 1.4 | 1.3 | .397 | .872 |
| S24 | 0.6 | 1.1 | .414 | .871 |
| Overall | 31.5 | 14.0 | .875 |
Fig. 1Prevalence of physiological distress in COVID-19, Bangladesh.
Prevalence of CPDI by socioeconomic and demographic characteristics, Bangladesh.
| Normal | mild to moderate distress | severe distress | Sample size | Chi-square test | P-value | ||
|---|---|---|---|---|---|---|---|
| Overall | 46.1 | 44.3 | 9.5 | 503 | |||
| Gender | Male | 54.6 | 41.2 | 4.1 | 291 | 33.596 | 0.000 |
| Female | 34.4 | 48.6 | 17.0 | 212 | |||
| Religion | Others | 44.9 | 53.1 | 2.0 | 49 | 4.152 | 0.125 |
| Islam | 46.3 | 43.4 | 10.4 | 454 | |||
| Age | 18–30 year | 46.5 | 43.8 | 9.6 | 447 | .385 | 0.825 |
| 30+ years | 42.9 | 48.2 | 8.9 | 56 | |||
| Education | School | 45.8 | 38.9 | 15.3 | 72 | 3.460 | 0.177 |
| College | 46.2 | 45.2 | 8.6 | 431 | |||
| Employment | Not Employed | 52.7 | 40.7 | 6.6 | 91 | 3.057 | 0.548 |
| Employed | 41.9 | 47.1 | 11.0 | 136 | |||
| Student | 46.0 | 44.2 | 9.8 | 276 | |||
| House Income | BDT less than 25,000 | 49.6 | 41.9 | 8.5 | 129 | 1.162 | 0.884 |
| BDT 25,000 to less than 50,000 | 44.7 | 46.0 | 9.3 | 215 | |||
| BDT More than 50,000 | 45.3 | 44.0 | 10.7 | 159 | |||
| Region | Dhaka/Mymensing | 47.2 | 42.9 | 10.0 | 371 | 6.562 | 0.363 |
| Rajshahi/Rangpur | 56.8 | 38.6 | 4.5 | 44 | |||
| Barisal/Khulna | 38.2 | 52.9 | 8.8 | 34 | |||
| Chittagong/Sylhet | 35.2 | 53.7 | 11.1 | 54 | |||
Predictors of CPDI through bivariate logistic regression, Bangladesh.
| Odds Ratio | 95% C.I. for Odds ratio | |||||||
|---|---|---|---|---|---|---|---|---|
| Lower | Upper | p-value | ||||||
| Male | Reference | |||||||
| Female | 2.435 | 1.662 | 3.568 | .000** | ||||
| Others | Reference | |||||||
| Islam | 0.861 | 0.463 | 1.600 | .635 | ||||
| 18–30 year | Reference | |||||||
| 30+ years | 0.975 | 0.503 | 1.889 | .941 | ||||
| School | Reference | |||||||
| College | 1.016 | 0.596 | 1.732 | .954 | ||||
| Not Employed | Reference | |||||||
| Employed | 1.772 | 0.988 | 3.178 | .055 | ||||
| Student | 1.260 | 0.767 | 2.070 | .361 | ||||
| BDT less than 25,000 | Reference | |||||||
| BDT 25,000 to less than 50,000 | 1.048 | 0.656 | 1.674 | .844 | ||||
| BDT More than 50,000 | 1.015 | 0.614 | 1.676 | .955 | ||||
| Dhaka/Mymensing | Reference | |||||||
| Rajshahi/Rangpur | 0.812 | 0.417 | 1.583 | .541 | ||||
| Barisal/Khulna | 1.436 | 0.685 | 3.011 | .338 | ||||
| Chittagong/Sylhet | 1.945 | 1.047 | 3.612 | .035* | ||||
**p < 0.01, *p < 0.05.