| Literature DB >> 33035219 |
Most Zannatul Ferdous1,2, Md Saiful Islam1,3, Md Tajuddin Sikder1, Abu Syed Md Mosaddek2,4, J A Zegarra-Valdivia5, David Gozal6.
Abstract
In Bangladesh, an array of measures have been adopted to control the rapid spread of the COVID-19 epidemic. Such general population control measures could significantly influence perception, knowledge, attitudes, and practices (KAP) towards COVID-19. Here, we assessed KAP towards COVID-19 immediately after the lock-down measures were implemented and during the rapid rise period of the outbreak. Online-based cross-sectional study conducted from March 29 to April 19, 2020, involving Bangladeshi residents aged 12-64 years, recruited via social media. After consenting, participants completed an online survey assessing socio-demographic variables, perception, and KAP towards COVID-19. Of the 2017 survey participants, 59.8% were male, the majority were students (71.2%), aged 21-30 years (57.9%), having a bachelor's degree (61.0%), having family income >30,000 BDT (50.0%), and living in urban areas (69.8). The survey revealed that 48.3% of participants had more accurate knowledge, 62.3% had more positive attitudes, and 55.1% had more frequent practices regarding COVID-19 prevention. Majority (96.7%) of the participants agreed 'COVID-19 is a dangerous disease', almost all (98.7%) participants wore a face mask in crowded places, 98.8% agreed to report a suspected case to health authorities, and 93.8% implemented washing hands with soap and water. In multiple logistic regression analyses, COVID-19 more accurate knowledge was associated with age and residence. Sociodemographic factors such as being older, higher education, employment, monthly family income >30,000 BDT, and having more frequent prevention practices were the more positive attitude factors. More frequent prevention practice factors were associated with female sex, older age, higher education, family income > 30,000 BDT, urban area residence, and having more positive attitudes. To improve KAP of general populations is crucial during the rapid rise period of a pandemic outbreak such as COVID-19. Therefore, development of effective health education programs that incorporate considerations of KAP-modifying factors is needed.Entities:
Mesh:
Year: 2020 PMID: 33035219 PMCID: PMC7546509 DOI: 10.1371/journal.pone.0239254
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Demographic characteristics of participants (N = 2,017).
| Variables | n | (%) |
|---|---|---|
| Male | 1206 | (59.8) |
| Female | 811 | (40.2) |
| 12–20 | 671 | (33.3) |
| 21–30 | 1168 | (57.9) |
| >30 | 178 | (8.8) |
| Secondary (6–10) | 20 | (1.0) |
| Intermediate (11–12) | 226 | (11.2) |
| Bachelor | 1230 | (61.0) |
| Higher education (above bachelor) | 541 | (26.8) |
| Unmarried | 1630 | (80.8) |
| Married | 379 | (18.8) |
| Divorced | 8 | (0.4) |
| Student | 1437 | (71.2) |
| Housewife | 64 | (3.2) |
| Govt. employee | 122 | (6.0) |
| Non-govt. employee | 315 | (15.6) |
| Businessman | 52 | (2.6) |
| Unemployment | 27 | (1.3) |
| Nuclear | 1572 | (77.9) |
| Join | 445 | (22.1) |
| <5 | 1449 | (71.8) |
| ≥5 | 568 | (28.2) |
| <20,000 BDT | 512 | (25.4) |
| 20,000–30,000 BDT | 497 | (24.6) |
| >30,000 BDT | 1008 | (50.0) |
| Rural area | 610 | (30.2) |
| Urban area | 1407 | (69.8) |
Perception towards COVID-19 about the mode of transmission, incubation period, symptoms, risk factors, treatments, prevention initiatives, and challenges.
| Variables | Total | Male | Female | |||
|---|---|---|---|---|---|---|
| N = 2017 | ||||||
| n | (%) | n | (%) | n | (%) | |
| Direct transmission during coughing | 1339 | (66.4) | 816 | (60.9) | 523 | (39.1) |
| Touching contaminated surfaces | 1236 | (61.3) | 773 | (62.5) | 463 | (37.5) |
| Contact with infected animals | 622 | (30.8) | 396 | (63.7) | 226 | (36.3) |
| Through eating infected animal products (e.g., meat, milk) | 431 | (21.4) | 276 | (64.0) | 155 | (36.0) |
| Close contact with an infected person | 1889 | (93.7) | 1129 | (59.8) | 760 | (40.2) |
| Don't know | 11 | (0.5) | 7 | (63.6) | 4 | (36.4) |
| 2–5 days | 126 | (6.2) | 82 | (65.1) | 44 | (34.9) |
| 2–14 days | 1842 | (91.3) | 1092 | (59.3) | 750 | (40.7) |
| Don't know | 49 | (2.4) | 32 | (65.3) | 17 | (34.7) |
| Fever, dry cough, difficulty of breathing | 2004 | (99.4) | 1199 | (59.8) | 805 | (40.2) |
| Sore throat, blocked nose | 1032 | (51.2) | 614 | (59.5) | 418 | (40.5) |
| Headache | 3 | (0.1) | 0 | (0.0) | 3 | (100.0) |
| Diarrhea | 14 | (0.7) | 10 | (71.4) | 4 | (28.6) |
| Don't know | 8 | (0.4) | 5 | (62.5) | 3 | (37.5) |
| Old aged persons | 1737 | (86.1) | 1056 | (60.8) | 681 | (39.2) |
| Pregnant women | 427 | (21.2) | 249 | (58.3) | 178 | (41.7) |
| Children | 511 | (25.3) | 305 | (59.7) | 206 | (40.3) |
| Individuals with cancer, diabetes, chronic respiratory diseases | 1505 | (74.6) | 878 | (58.3) | 627 | (41.7) |
| Migrants from other parts of the world having COVID-19 | 903 | (44.8) | 525 | (58.1) | 378 | (41.9) |
| Don't know | 17 | (0.8) | 15 | (88.2) | 2 | (11.8) |
| Supportive treatment | 1627 | (80.7) | 967 | (59.4) | 660 | (40.6) |
| Vaccine | 20 | (1.0) | 11 | (55.0) | 9 | (45.0) |
| Don't know | 370 | (18.3) | 228 | (61.6) | 142 | (38.4) |
| Wash hands with water and soap | 1885 | (93.5) | 1136 | (60.3) | 749 | (39.7) |
| Avoid touching the eyes andnose with hands | 1823 | (90.4) | 1102 | (60.4) | 721 | (39.6) |
| Avoid contacts with infected people | 1709 | (84.7) | 1035 | (60.6) | 674 | (39.4) |
| Using masks | 1759 | (87.2) | 1054 | (59.9) | 705 | (40.1) |
| Maintaining social distance | 1886 | (93.5) | 1140 | (60.4) | 746 | (39.6) |
| Maintaining self-quarantine | 1551 | (76.9) | 945 | (60.9) | 606 | (39.1) |
| Takingall family members in home quarantine | 1575 | (78.1) | 931 | (59.1) | 644 | (40.9) |
| Strengthening to health care | 1283 | (63.6) | 765 | (59.6) | 518 | (40.4) |
| Creating a strong voluntary force to fight against COVID-19 | 539 | (26.7) | 346 | (64.2) | 193 | (35.8) |
| Temporary closure of outside people coming inside the home | 1769 | (87.8) | 1037 | (58.6) | 732 | (41.4) |
| Arrange for handwashing with soap inside or outside the home | 1723 | (85.5) | 1039 | (60.3) | 684 | (39.7) |
| Wash hands with soap after touching pets | 794 | (39.4) | 501 | (63.1) | 293 | (36.9) |
| Negligence about the severity of the disease | 810 | (40.3) | 531 | (65.6) | 279 | (34.4) |
| Reluctance to use masks | 512 | (25.5) | 335 | (65.4) | 177 | (34.6) |
| Not being able to stop going out of the house | 1147 | (57.1) | 695 | (60.6) | 452 | (39.4) |
| Don't face the problem | 395 | (19.7) | 225 | (57.0) | 170 | (43.0) |
aindicates multiple responses.
Knowledge and gender difference of participants (N = 2017).
| Variables | Total N = 2017 | Male | Female | χ2 | df | ||||
|---|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | ||||
| Yes | 1951 | (96.7) | 1160 | (96.2) | 791 | (97.5) | 2.988 | 2 | 0.224 |
| No | 40 | (2.0) | 27 | (2.2) | 13 | (1.6) | |||
| Don't know | 26 | (1.3) | 19 | (1.6) | 7 | (0.9) | |||
| Yes | 1210 | (60.0) | 735 | (60.9) | 475 | (58.6) | 1.161 | 2 | 0.560 |
| No | 567 | (28.1) | 330 | (27.4) | 237 | (29.2) | |||
| Don't know | 240 | (11.9) | 141 | (11.7) | 99 | (12.2) | |||
| Yes | 1013 | (50.2) | 612 | (50.7) | 401 | (49.4) | 4.690 | 2 | 0.096 |
| No | 578 | (28.7) | 358 | (29.7) | 220 | (27.1) | |||
| Don't know | 426 | (21.1) | 236 | (19.6) | 190 | (23.4) | |||
| Yes | 1013 | (50.2) | 612 | (50.7) | 401 | (49.4) | 4.690 | 2 | 0.096 |
| No | 578 | (28.7) | 358 | (29.7) | 220 | (27.1) | |||
| Don't know | 426 | (21.1) | 236 | (19.6) | 190 | (23.4) | |||
| Yes | 509 | (25.2) | 300 | (24.9) | 209 | (25.8) | 0.406 | 2 | 0.816 |
| No | 1017 | (50.4) | 615 | (51.0) | 402 | (49.6) | |||
| Don't know | 491 | (24.3) | 291 | (24.1) | 200 | (24.7) | |||
| Yes | 53 | (2.6) | 35 | (2.9) | 18 | (2.2) | 3.859 | 2 | 0.145 |
| No | 1821 | (90.3) | 1076 | (89.2) | 745 | (91.9) | |||
| Don't know | 143 | (7.1) | 95 | (7.9) | 48 | (5.9) | |||
Distribution and risk factors of knowledge, attitude and practice among participants.
| Variables | Knowledge | Attitudes | Practices | |||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Less accurate | More accurate | χ2 | OR | 95%CI | Less positive | More positive | χ2 | OR | 95%CI | Less frequent | More frequent | χ2 | OR | 95%CI | ||||||||||
| N | (%) | N | (%) | N | (%) | N | (%) | N | (%) | N | (%) | |||||||||||||
| Male | 626 | (51.9) | 580 | (48.1) | 0.046 | 0.981 | 0.821–1.172 | 0.829 | 472 | (39.1) | 734 | (60.9) | 2.715 | 0.856 | 0.712–1.030 | 0.100 | 572 | (47.4) | 634 | (52.6) | 8.583 | 0.764 | 0.638–0.915 | 0.003 |
| Female | 417 | (51.4) | 394 | (48.6) | Ref. | 288 | (35.5) | 523 | (64.5) | Ref. | 331 | (40.8) | 480 | (59.2) | Ref. | |||||||||
| 12–20 | 340 | (50.7) | 331 | (49.3) | 7.100 | 1.538 | 1.098–2.155 | 0.012 | 301 | (44.9) | 370 | (55.1) | 25.841 | 0.467 | 0.325-.671 | <0.001 | 345 | (51.4) | 326 | (48.6) | 20.474 | 0.530 | 0.377–0.746 | <0.001 |
| 21–30 | 594 | (50.9) | 574 | (49.1) | 1.527 | 1.106–2.108 | 0.010 | 410 | (35.1) | 758 | (64.9) | 0.702 | 0.495-.997 | 0.048 | 494 | (42.3) | 674 | (57.7) | 0.766 | 0.552–1.063 | 0.110 | |||
| >30 | 109 | (61.2) | 69 | (38.8) | Ref. | 49 | (27.5) | 129 | (72.5) | Ref. | 64 | (36.0) | 114 | (64.0) | Ref. | |||||||||
| Secondary (6–10) | 8 | (40.0) | 12 | (60.0) | 4.347 | 1.419 | 0.571–3.527 | 0.451 | 9 | (45.0) | 11 | (55.0) | 47.791 | 0.427 | 0.173–1.051 | 0.064 | 13 | (65.0) | 7 | (35.0) | 23.415 | 0.308 | 0.121–0.786 | 0.014 |
| Intermediate (11–12) | 117 | (51.8) | 109 | (48.2) | 0.881 | 0.646–1.202 | 0.426 | 108 | (47.8) | 118 | (52.2) | 0.381 | 0.276–0.528 | <0.001 | 110 | (48.7) | 116 | (51.3) | 0.604 | 0.441–0.827 | 0.002 | |||
| Bachelor | 655 | (53.3) | 575 | (46.7) | 0.830 | 0.678–1.017 | 0.072 | 503 | (40.9) | 727 | (59.1) | 0.505 | 0.404–0.631 | <0.001 | 583 | (47.4) | 647 | (52.6) | 0.636 | 0.516–0.782 | <0.001 | |||
| Higher education (above bachelor) | 263 | (48.6) | 278 | (51.4) | Ref. | 140 | (25.9) | 401 | (74.1) | Ref. | 197 | (36.4) | 344 | (63.6) | Ref. | |||||||||
| Single | 835 | (51.2) | 795 | (48.8) | 1.659 | 0.571 | 0.136–2.398 | 0.444 | 643 | (39.4) | 987 | (60.6) | 14.932 | 2.558 | 0.609–10.742 | 0.199 | 751 | (46.1) | 879 | (53.9) | 5.854 | 0.702 | 0.167–2.948 | 0.629 |
| Married | 205 | (54.1) | 174 | (45.9) | 0.509 | 0.120–2.161 | 0.360 | 112 | (29.6) | 267 | (70.4) | 3.973 | 0.934–16.909 | 0.062 | 149 | (39.3) | 230 | (60.7) | 0.926 | 0.218–3.933 | 0.917 | |||
| Divorced | 3 | (37.5) | 5 | (62.5) | Ref. | 5 | (62.5) | 3 | (37.5) | Ref. | 3 | (37.5) | 5 | (62.5) | Ref. | |||||||||
| Student | 733 | (51.0) | 704 | (49.0) | 5.584 | 1.633 | 0.743–3.590 | 0.223 | 601 | (41.8) | 836 | (58.2) | 40.508 | 0.397 | 0.159–0.991 | 0.048 | 687 | (47.8) | 750 | (52.2) | 20.203 | 0.873 | 0.406–1.879 | 0.729 |
| Housewife | 40 | (62.5) | 24 | (37.5) | 1.020 | 0.402–2.587 | 0.967 | 14 | (21.9) | 50 | (78.1) | 1.020 | 0.345–3.016 | 0.971 | 20 | (31.3) | 44 | (68.8) | 1.760 | 0.698–4.438 | 0.231 | |||
| Govt. employee | 59 | (48.4) | 63 | (51.6) | 1.815 | 0.770–4.281 | 0.173 | 38 | (31.1) | 84 | (68.9) | 0.632 | 0.236–1.691 | 0.360 | 46 | (37.7) | 76 | (62.3) | 1.322 | 0.569–3.070 | 0.517 | |||
| Non-govt. employee | 165 | (52.4) | 150 | (47.6) | 1.545 | 0.686–3.480 | 0.293 | 82 | (26.0) | 233 | (74.0) | 0.812 | 0.317–2.082 | 0.664 | 118 | (37.5) | 197 | (62.5) | 1.336 | 0.605–2.951 | 0.474 | |||
| Businessman | 29 | (55.8) | 23 | (44.2) | 1.348 | 0.519–3.499 | 0.539 | 19 | (36.5) | 33 | (63.5) | 0.496 | 0.170–1.445 | 0.199 | 20 | (38.5) | 32 | (61.5) | 1.280 | 0.499–3.285 | 0.608 | |||
| Unemployedt | 17 | (63.0) | 10 | (37.0) | Ref. | 6 | (22.2) | 21 | (77.8) | Ref. | 12 | (44.4) | 15 | (55.6) | Ref. | |||||||||
| Nuclear | 809 | (51.5) | 763 | (48.5) | 0.175 | 1.046 | 0.847–1.291 | 0.676 | 612 | (38.9) | 960 | (61.1) | 4.753 | 0.782 | 0.626–0.976 | 0.029 | 707 | (45.0) | 865 | (55.0) | 0.121 | 0.963 | 0.779–1.190 | 0.728 |
| Joint | 234 | (52.6) | 211 | (47.4) | Ref. | 148 | (33.3) | 297 | (66.7) | Ref. | 196 | (44.0) | 249 | (56.0) | Ref. | |||||||||
| <5 | 746 | (51.5) | 703 | (48.5) | 0.106 | 1.033 | 0.850–1.254 | 0.745 | 553 | (38.2) | 896 | (61.8) | 0.514 | 0.929 | 0.760–1.136 | 0.473 | 631 | (43.5) | 818 | (56.5) | 3.108 | 1.191 | 0.981–1.447 | 0.078 |
| ≥5 | 297 | (52.3) | 271 | (47.7) | Ref. | 207 | (36.4) | 361 | (63.6) | Ref. | 272 | (47.9) | 296 | (52.1) | Ref. | |||||||||
| <20,000 BDT | 256 | (50.0) | 256 | (50.0) | 1.412 | 1.066 | 0.861–1.318 | 0.559 | 216 | (42.2) | 296 | (57.8) | 8.219 | 0.732 | 0.589–0.911 | 0.005 | 263 | (51.4) | 249 | (48.6) | 12.147 | 0.707 | 0.571–0.876 | 0.001 |
| 20,000–30,000 BDT | 267 | (53.7) | 230 | (46.3) | 0.918 | 0.740–1.138 | 0.436 | 193 | (38.8) | 304 | (61.2) | 0.842 | 0.674–1.051 | 0.128 | 209 | (42.1) | 288 | (57.9) | 1.029 | 0.828–1.279 | 0.795 | |||
| >30,000 BDT | 520 | (51.6) | 488 | (48.4) | Ref. | 351 | (34.8) | 657 | (65.2) | Ref. | 431 | (42.8) | 577 | (57.2) | Ref. | |||||||||
| Rural area | 288 | (47.2) | 322 | (52.8) | 7.083 | 1.295 | 1.070–1.566 | 0.008 | 238 | (39.0) | 372 | (61.0) | 0.665 | 0.922 | 0.758–1.121 | 0.415 | 322 | (52.8) | 288 | (47.2) | 22.733 | 0.629 | 0.520–0.762 | <0.001 |
| Urban area | 755 | (53.7) | 652 | (46.3) | Ref. | 522 | (37.1) | 885 | (62.9) | Ref. | 581 | (41.3) | 826 | (58.7) | Ref. | |||||||||
| More accurate | 0 | (.0) | 974 | (100.0) | — | — | — | — | 372 | (38.2) | 602 | (61.8) | 0.211 | 0.959 | 0.801–1.148 | 0.646 | 424 | (43.5) | 550 | (56.5) | 1.167 | 1.102 | 0.924–1.313 | 0.280 |
| Less accurate | 1043 | (100.0) | 0 | (0.0) | 388 | (37.2) | 655 | (62.8) | Ref. | 479 | (45.9) | 564 | (54.1) | Ref. | ||||||||||
| More positive | 655 | (52.1) | 602 | (47.9) | 0.211 | 0.959 | 0.801–1.148 | 0.646 | 0 | (0.0) | 1257 | (100.0) | — | — | — | — | 521 | (41.4) | 736 | (58.6) | 14.885 | 1.428 | 1.191–1.711 | <0.001 |
| Less Positive | 388 | (51.1) | 372 | (48.9) | Ref. | 760 | (100.0) | 0 | (0.0) | 382 | (50.3) | 378 | (49.7) | Ref. | ||||||||||
| More frequent | 564 | (50.6) | 550 | (49.4) | 1.167 | 1.102 | 0.924–1.313 | 0.280 | 378 | (33.9) | 736 | (66.1) | 14.885 | 1.428 | 1.191–1.711 | <0.001 | 0 | (0.0) | 1114 | (100.0) | — | — | — | — |
| Less frequent | 479 | (53.0) | 424 | (47.0) | Ref. | 382 | (42.3) | 521 | (57.7) | Ref. | 903 | (100.0) | 0 | (0.0) | ||||||||||
Attitude and gender difference of participants (N = 2017).
| Variables | Total N = 2017 | Male | Female | χ2 | df | ||||
|---|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | ||||
| Agree | 1993 | (98.8) | 1186 | (98.3) | 807 | (99.5) | 6.292 | 2 | 0.043 |
| Undecided | 12 | (0.6) | 11 | (0.9) | 1 | (0.1) | |||
| Disagree | 12 | (0.6) | 9 | (0.7) | 3 | (0.4) | |||
| Agree | 1991 | (98.7) | 1183 | (98.1) | 808 | (99.6) | 9.053 | 2 | 0.011 |
| Undecided | 11 | (0.5) | 10 | (0.8) | 1 | (0.1) | |||
| Disagree | 15 | (0.7) | 13 | (1.1) | 2 | (0.2) | |||
| Agree | 2006 | (99.5) | 1197 | (99.3) | 809 | (99.8) | 3.492 | 2 | 0.174 |
| Undecided | 5 | (0.2) | 5 | (0.4) | 0 | (0.0) | |||
| Disagree | 6 | (0.3) | 4 | (0.3) | 2 | (0.2) | |||
| Agree | 1829 | (90.7) | 1091 | (90.5) | 738 | (91.0) | 4.211 | 2 | 0.122 |
| Undecided | 109 | (5.4) | 60 | (5.0) | 49 | (6.0) | |||
| Disagree | 79 | (3.9) | 55 | (4.6) | 24 | (3.0) | |||
| Agree | 1158 | (57.4) | 686 | (56.9) | 472 | (58.2) | 1.995 | 2 | 0.369 |
| Undecided | 240 | (11.9) | 137 | (11.4) | 103 | (12.7) | |||
| Disagree | 619 | (30.7) | 383 | (31.8) | 236 | (29.1) | |||
| Agree | 1928 | (95.6) | 1148 | (95.2) | 780 | (96.2) | 1.805 | 2 | 0.406 |
| Undecided | 52 | (2.6) | 32 | (2.7) | 20 | (2.5) | |||
| Disagree | 37 | (1.8) | 26 | (2.2) | 11 | (1.4) | |||
Practice and gender difference of participants (N = 2017).
| Variables | Total N = 2017 | Male | Female | χ2 | df | ||||
|---|---|---|---|---|---|---|---|---|---|
| n | (%) | n | (%) | n | (%) | ||||
| Yes | 1549 | (76.8) | 886 | (73.5) | 663 | (81.8) | 23.392 | 2 | <0.001 |
| No | 74 | (3.7) | 59 | (4.9) | 15 | (1.8) | |||
| Sometimes | 394 | (19.5) | 261 | (21.6) | 133 | (16.4) | |||
| Yes | 1891 | (93.8) | 1116 | (92.5) | 775 | (95.6) | 7.570 | 2 | 0.023 |
| No | 14 | (0.7) | 10 | (0.8) | 4 | (0.5) | |||
| Sometimes | 112 | (5.6) | 80 | (6.6) | 32 | (3.9) | |||
| Yes | 1228 | (60.9) | 734 | (60.9) | 494 | (60.9) | 0.118 | 2 | 0.943 |
| No | 154 | (7.6) | 94 | (7.8) | 60 | (7.4) | |||
| Sometimes | 635 | (31.5) | 378 | (31.3) | 257 | (31.7) | |||
| Yes | 1831 | (90.8) | 1051 | (87.1) | 780 | (96.2) | 47.237 | 2 | <0.001 |
| No | 41 | (2.0) | 34 | (2.8) | 7 | (0.9) | |||
| Sometimes | 145 | (7.2) | 121 | (10.0) | 24 | (3.0) | |||
| Yes | 760 | (37.7) | 464 | (38.5) | 296 | (36.5) | 0.806 | 1 | 0.369 |
| No | 1257 | (62.3) | 742 | (61.5) | 515 | (63.5) | |||
| Sometimes | 0 | (0.0) | 0 | (0.0) | 0 | (0.0) | |||
| Yes | 1698 | (84.2) | 982 | (81.4) | 716 | (88.3) | 17.779 | 2 | <0.001 |
| No | 19 | (0.9) | 15 | (1.2) | 4 | (0.5) | |||
| Sometimes | 300 | (14.9) | 209 | (17.3) | 91 | (11.2) | |||
| Yes | 1784 | (88.4) | 1030 | (85.4) | 754 | (93.0) | 29.710 | 2 | <0.001 |
| No | 39 | (1.9) | 25 | (2.1) | 14 | (1.7) | |||
| Sometimes | 194 | (9.6) | 151 | (12.5) | 43 | (5.3) | |||