| Literature DB >> 35319444 |
Jacqueline Limoges1, Jesse Mclean2, Daniel Anzola3, Nathan J Kolla4.
Abstract
BACKGROUND: Notably higher rates of mental health issues have been reported among healthcare providers (HCPs) during the COVID-19 pandemic. Concerns over the impact of policy decisions on the well-being of HCPs is growing, yet it remains underexplored in the literature.Entities:
Mesh:
Year: 2022 PMID: 35319444 PMCID: PMC8935928 DOI: 10.12927/hcpol.2022.26728
Source DB: PubMed Journal: Healthc Policy ISSN: 1715-6572
Participant demographics
| Variable | Questionnaire | Interviews | Total | |||
|---|---|---|---|---|---|---|
| RVH (Community hospital) | Waypoint (Psychiatric hospital) | RVH (General hospital) | Waypoint (Psychiatric hospital) | |||
|
| Nursing | 36 (76.6%) | 34 (82.9%) | 11 (73.3%) | 9 (60.0%) | 90 (76.3%) |
| Physician | 2 (4.3%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 2 (1.7%) | |
| Other | 3 (6.4%) | 4 (9.8%) | 1 (6.7%) | 0 (0.0%) | 8 (6.8%) | |
| Allied health | 6 (12.8%) | 3 (7.3%) | 3 (20.0%) | 6 (40.0%) | 18 (15.3%) | |
| Total | 47 (100%) | 41 (100%) | 15 (100%) | 15 (100%) | 118 (100%) | |
|
| <30 | 13 (27.7%) | 14 (34.1%) | 0 (0.0%) | 1 (6.7%) | 28 (23.7%) |
| 31–50 | 29 (61.7%) | 15 (36.6%) | 9 (60.0%) | 6 (40.0%) | 59 (50.0%) | |
| 51–65 | 5 (10.6%) | 12 (29.3%) | 6 (40.0%) | 8 (53.3%) | 31 (26.3%) | |
| Total | 47 (100%) | 41 (100%) | 15 (100%) | 15 (100%) | 118 (100%) | |
|
| <5 | 16 (34.0%) | 14 (34.1%) | 1 (6.7%) | 2 (13.3%) | 33 (28.0%) |
| 6–10 | 11 (23.4%) | 12 (29.3%) | 3 (20.0%) | 1 (6.7%) | 27 (22.9%) | |
| 11–15 | 7 (14.9%) | 5 (12.2%) | 4 (26.7%) | 4 (26.7%) | 20 (16.9%) | |
| 16–20 | 8 (17.0%) | 6 (14.6%) | 4 (26.7%) | 2 (13.3%) | 20 (16.9%) | |
| >20 | 5 (10.6%) | 4 (9.8%) | 3 (20.0%) | 6 (40.0%) | 18 (15.3%) | |
| Total | 47 (100%) | 41 (100%) | 15 (100%) | 15 (100%) | 118 (100%) | |
|
| <5 | 24 (51.1%) | 16 (39.0%) | 4 (26.7%) | 2 (13.3%) | 46 (39.0%) |
| 6–10 | 14 (29.8%) | 10 (24.4%) | 3 (20.0%) | 1 (6.7%) | 28 (23.7%) | |
| 11–15 | 2 (4.3%) | 1 (2.4%) | 4 (26.7%) | 4 (26.7%) | 11 (9.3%) | |
| 16–20 | 5 (10.6%) | 8 (19.5%) | 2 (13.3%) | 2 (13.3%) | 17 (14.4%) | |
| <20 | 2 (4.3%) | 6 (14.6%) | 2 (13.3%) | 6 (40.0%) | 16 (13.6%) | |
| Total | 47 (100%) | 41 (100%) | 15 (100%) | 15 (100%) | 118 (100%) | |
|
| White | 42 (89.4%) | 36 (90.0%) | 14 (93.3%) | 12 (92.3%) | 104 (90.4%) |
|
| 88 | 30 | 118 | |||
Small numbers in race/ethnicity have not been presented to protect identity.