| Literature DB >> 33571838 |
Charissa Millevert1, Stijn Van Hees2, Joseph Nelson Siewe Fodjo3, Veerle Wijtvliet4, Edlaine Faria de Moura Villela5, Barbara Rosso6, Antonio Gil-Nagel7, Sarah Weckhuysen1, Robert Colebunders8.
Abstract
OBJECTIVE: To evaluate the impact of the coronavirus disease 2019 (COVID-19) measures on the lives and psychosocial well-being of persons with epilepsy (PWE) during the third trimester of the COVID-19 pandemic.Entities:
Keywords: COVID-19; Epilepsy; HADS; Mental health; Telemedicine
Mesh:
Year: 2021 PMID: 33571838 PMCID: PMC8803628 DOI: 10.1016/j.yebeh.2021.107800
Source DB: PubMed Journal: Epilepsy Behav ISSN: 1525-5050 Impact factor: 3.337
Characteristics of persons with epilepsy.
| Total | |
|---|---|
| Age (years) | |
| Mean (±SD) | 34.52 ± 14.03 |
| Gender | |
| Male (%) | 102 (25.1%) |
| Female (%) | 304 (74.7%) |
| Country of residence | |
| Europe (%) | 245 (60.2%) |
| South America (%) | 157 (38.6%) |
| Canada (%) | 5 (1.2%) |
| Relationship status | |
| Single (%) | 198 (48.6%) |
| In a relationship/married (%) | 209 (51.4%) |
| Maximum educational level | |
| Primary (%) | 36 (8.8%) |
| Secondary (%) | 159 (39.1%) |
| University undergraduate degree (%) | 129 (31.7%) |
| University postgraduate degree (%) | 73 (17.9%) |
| Housemates | |
| Parents (%) | 138 (33.9%) |
| Spouse/partner (%) | 173 (42.5%) |
| Child(ren) (%) | 122 (30.0%) |
| Siblings or other family relatives (%) | 56 (13.8%) |
| Friend(s) (%) | 7 (1.7%) |
| None, i.e. living alone (%) | 63 (15.5%) |
| Job status | |
| Self-employed (%) | 33 (8.1%) |
| Employee (%) | 169 (41.5%) |
| Retired (%) | 28 (6.9%) |
| Unemployed (%) | 85 (20.9%) |
| Student (%) | 75 (18.5%) |
| Other (%) | 16 (3.9%) |
| Financial situation | |
| Financial difficulties | 135 (33.2%) |
| To feed properly (%) | 54 (13.3%) |
| To pay for housing/bills (%) | 81 (19.9%) |
| To pay for ASM (%) | 58 (14.3%) |
| No financial difficulties (%) | 272 (66.8%) |
ASM: anti-seizure medication; N: number; SD: standard deviation.
Fig. 1HADS scores of anxiety and depression among PWE during the different months of follow-up survey.
Fig. 2Overview of reported items discussed during telephone or video consult.
Comparisons between the first and second online surveys among PWE.
| Second respondents | Round 1 ( | Round 2 ( | ||
|---|---|---|---|---|
| Financial problems | Yes; | 16 (29.1%) | 7 (12.7%) | 0.039 |
| Problems to obtain ASM | Yes; | 9 (16.4%) | 5 (9.1%) | 0.259 |
| Taking ASM | Yes; | 54 (98.2%) | 53 (96.4%) | 0.491 |
| Number of ASM | >1; | 27 (49.1%) | 33 (60.0%) | 0.202 |
| Seizure frequency | Increased; | 8 (14.5%) | 10 (18.2%) | 0.607 |
| HADS-Anxiety | Positive; | 21 (38.2%) | 25 (45.5%) | 0.440 |
| HADS-A score | Mean (±SD) | 6.65 ± 3.99 | 7.27 ± 4.01 | 0.418 |
| HADS-Depression | Positive; | 15 (27.3%) | 19 (34.5%) | 0.410 |
| HADS-D score | Mean (±SD) | 5.84 ± 4.43 | 6.60 ± 4.45 | 0.371 |
ASM: anti-seizure medication; HADS: Hospital anxiety and depressions scale; N: number; SD: standard deviation.
Impact of COVID-19 on daily life and finances.
| Total | 407 |
|---|---|
| Impact of COVID-19 on daily life | |
Yes (%) | 351 (86.2%) |
Job loss (%) | 19 (4.7%) |
Work from home (%) | 111 (27.3%) |
Temporary jobless (%) | 32 (7.9%) |
Not allowed to go outside (except to go to the supermarket) (%) | 186 (45.7%) |
Not allowed to see people other than housemates (%) | 207 (50.9%) |
Care for children during the day (%) | 55 (13.5%) |
Other (%) | 75 (18.4%) |
No (%) | 56 (13.8%) |
| Impact of COVID-19 on income | |
Increased (%) | 47 (11.5% |
Decreased (%) | 76 (18.7%) |
No change (%) | 216 (53.1%) |
Not applicable (%) | 68 (16.7%) |
| Impact of COVID-19 on expenditure | |
Increased (%) | 124 (30.5%) |
Decreased (%) | 81 (19.9%) |
No change (%) | 146 (35.9%) |
Not applicable (%) | 56 (13.8%) |
N: number.