| Literature DB >> 34918181 |
Rebecca C Hendrickson1,2, Roisín A Slevin3, Katherine D Hoerster4,5,6, Bernard P Chang7, Ellen Sano7, Catherine A McCall4,5,8, Gillian R Monty6, Ronald G Thomas9, Murray A Raskind3,4.
Abstract
BACKGROUND: The COVID-19 pandemic has greatly affected front-line health care workers (HCW) and first responders (FR). The specific components of COVID-19 related occupational stressors (CROS) associated with psychiatric symptoms and reduced occupational functioning or retention remain poorly understood.Entities:
Keywords: COVID-19; Insomnia; Occupational trauma; PTSD; Professional retention
Mesh:
Year: 2021 PMID: 34918181 PMCID: PMC8675543 DOI: 10.1007/s11606-021-07252-z
Source DB: PubMed Journal: J Gen Intern Med ISSN: 0884-8734 Impact factor: 5.128
Fig. 1Factor analysis of COVID-19-related occupational stressors (CROS). Results of a 3-factor analysis of COVID-19 exposure items into 3 factors, termed volume, demoralization, and risk, based on an interpretation of their most highly weighted items. Color shading is proportional to the numeric weight on each cell, and indicates the weight that item contributes to the factor below. See Appendix A for complete wording of CROS items
Sample Demographics, COVID-19-Related Occupational Stressors (CROS), Psychiatric Symptoms, and Functional Outcome Measures
| All | Health Care Workers | First Responders | HCW vs FR | Physician vs nurse | LEO/ fire vs EMS | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| All HCW | Physician | Nurse | All FR | LEO or fire | EMS | |||||
| Demographics | ||||||||||
| Age, years (mean + SD) | 41.3 ± 10 | 42.3 ± 10 | 42.0 ± 6.6 | 42.9 ± 11 | 39.6 ± 11 | 44.0 ± 11 | 36.8 ± 10 | 0.03 | 0.52 | < 0.01 |
| Education, years (mean + SD) | 15.8 ± 3.1 | 16.6 ± 3.2 | 20.4 ± 2.0 | 15.5 ± 2.5 | 14.4 ± 2.4 | 14.1 ± 3.1 | 14.6 ± 1.9 | < 0.01 | < 0.01 | 0.25 |
| Married, % | 57.8% (208/360) | 63.2% (139/220) | 86.3% (44/51) | 56.7% (76/134) | 50% (68/136) | 69.2% (36/52) | 39.7% (31/78) | 0.02 | < 0.01 | < 0.01 |
| Veteran, % | 9.1% (33/362) | 5% (11/221) | 2% (1/51) | 7.4% (10/135) | 16.1% (22/137) | 26.4% (14/53) | 9% (7/78) | < 0.01 | 0.29 | 0.01 |
| COVID-19 exposure assessment* | ||||||||||
| Had Covid | 35.6% (160/449) | 30.2% (81/268) | 14% (8/57) | 34.8% (57/164) | 44% (77/175) | 32.3% (21/65) | 50% (51/102) | < 0.01 | < 0.01 | 0.03 |
| Family member Covid | 30.2% (136/450) | 24.5% (66/269) | 8.8% (5/57) | 27.3% (45/165) | 38.9% (68/175) | 35.4% (23/65) | 44.1% (45/102) | < 0.01 | < 0.01 | 0.33 |
| Close death from Covid | 22% (99/449) | 21.9% (59/269) | 8.8% (5/57) | 26.1% (43/165) | 22.4% (39/174) | 21.5% (14/65) | 20.8% (21/101) | 0.91 | < 0.01 | 1.00 |
| Medical condition increasing risk | 41.1% (180/438) | 39.8% (104/261) | 15.8% (9/57) | 45.6% (73/160) | 42.1% (72/171) | 37.1% (23/62) | 42.6% (43/101) | 0.69 | < 0.01 | 0.52 |
| Caring for mild cases | 1.6 ± 1.2 | 1.6 ± 1.2 | 1.0 ± 1.1 | 1.8 ± 1.2 | 1.6 ± 1.1 | 1.1 ± 1.2 | 2.0 ± 0.9 | 0.80 | < 0.01 | < 0.01 |
| Caring for critically ill | 1.1 ± 1.2 | 1.2 ± 1.2 | 0.5 ± 0.9 | 1.4 ± 1.2 | 1.0 ± 1.1 | 0.8 ± 1.1 | 1.2 ± 1.0 | 0.12 | < 0.01 | < 0.01 |
| Longer hours for Covid | 1.1 ± 1.1 | 1.2 ± 1.1 | 0.6 ± 0.9 | 1.3 ± 1.1 | 1.1 ± 1.1 | 0.8 ± 1.0 | 1.2 ± 1.1 | 0.33 | < 0.01 | < 0.01 |
| Deaths to Covid | 0.8 ± 0.9 | 0.8 ± 1.0 | 0.3 ± 0.6 | 0.9 ± 1.0 | 0.7 ± 0.9 | 0.6 ± 0.8 | 0.8 ± 0.9 | 0.68 | < 0.01 | 0.04 |
| Deaths in isolation | 0.7 ± 1.0 | 0.8 ± 1.0 | 0.2 ± 0.6 | 1.0 ± 1.1 | 0.6 ± 0.8 | 0.4 ± 0.7 | 0.7 ± 0.8 | 0.03 | < 0.01 | 0.04 |
| Covid without PPE | 0.5 ± 0.8 | 0.5 ± 0.8 | 0.2 ± 0.4 | 0.6 ± 0.9 | 0.5 ± 0.9 | 0.3 ± 0.6 | 0.6 ± 0.9 | 0.56 | < 0.01 | 0.01 |
| Covid care futile | 0.9 ± 1.0 | 1.0 ± 1.1 | 0.4 ± 0.7 | 1.2 ± 1.2 | 0.9 ± 0.9 | 0.6 ± 0.8 | 1.0 ± 0.8 | 0.50 | < 0.01 | < 0.01 |
| Not quality care to all | 1.1 ± 1.1 | 1.3 ± 1.1 | 0.8 ± 1.0 | 1.5 ± 1.1 | 0.9 ± 1.0 | 0.5 ± 0.9 | 1.0 ± 1.0 | < 0.01 | < 0.01 | < 0.01 |
| Personal increased risk | 2.0 ± 1.1 | 1.9 ± 1.1 | 1.4 ± 1.0 | 2.0 ± 1.1 | 2.1 ± 1.0 | 1.8 ± 1.1 | 2.4 ± 0.8 | 0.03 | < 0.01 | < 0.01 |
| Family increased risk | 1.9 ± 1.1 | 1.8 ± 1.2 | 1.3 ± 1.1 | 1.9 ± 1.2 | 2.1 ± 1.1 | 1.8 ± 1.2 | 2.2 ± 1.0 | 0.04 | < 0.01 | 0.02 |
| Unsupportive workplace | 1.4 ± 1.2 | 1.4 ± 1.2 | 1.0 ± 1.0 | 1.5 ± 1.2 | 1.3 ± 1.2 | 1.2 ± 1.3 | 1.3 ± 1.2 | 0.21 | < 0.01 | 0.38 |
| Separation from family | 1.0 ± 1.1 | 0.9 ± 1.2 | 0.5 ± 1.0 | 0.9 ± 1.1 | 1.0 ± 1.1 | 0.7 ± 1.0 | 1.2 ± 1.1 | 0.63 | < 0.01 | < 0.01 |
| Unnecessary risk | 1.0 ± 1.1 | 1.0 ± 1.2 | 0.5 ± 0.9 | 1.1 ± 1.2 | 0.9 ± 1.1 | 0.8 ± 1.0 | 1.0 ± 1.1 | 0.24 | < 0.01 | 0.30 |
| Total Exposure Score | 14.2 ± 8 | 14.4 ± 9 | 8.4 ± 6 | 15.9 ± 9 | 13.7 ± 8 | 10.6 ± 8 | 15.7 ± 7 | 0.39 | < 0.01 | < 0.01 |
| Psychiatric Symptoms and Functional Outcomes** | ||||||||||
| PTSD (PCL5 total) | 27.7 ± 18.4 | 28.2 ± 18 | 19.5 ± 15.2 | 30.4 ± 17.5 | 26.6 ± 19 | 24.3 ± 20 | 28.1 ± 18.9 | 0.42 | < 0.01 | 0.25 |
| % clinical range (≥ 31) | 37.8% (152/402) | 38.8% (94/242) | 20.8% (11/53) | 42.3% (63/149) | 36.4% (56/154) | 36.1% (22/61) | 36% (31/86) | 0.67 | < 0.01 | 1.00 |
| Depression (PHQ9 Total) | 9.9 ± 6.6 | 9.6 ± 6.2 | 6.1 ± 4.7 | 10.5 ± 6.2 | 10.2 ± 7.1 | 7.9 ± 7.1 | 11.7 ± 6.7 | 0.39 | < 0.01 | < 0.01 |
| % clinical range (≥ 5) | 73.9% (264/357) | 74.1% (160/216) | 51% (26/51) | 80.2% (105/131) | 73% (100/137) | 56.6% (30/53) | 83.3% (65/78) | 0.90 | < 0.01 | < 0.01 |
| Insomnia (ISI total) | 12.3 ± 5.6 | 12.2 ± 5.5 | 9.0 ± 5.3 | 12.9 ± 5.1 | 12.3 ± 5.7 | 11.5 ± 6.1 | 12.7 ± 5.5 | 0.90 | < 0.01 | 0.17 |
| % clinical range (≥ 15) | 35.1% (174/496) | 35% (103/294) | 13.6% (8/59) | 39.6% (72/182) | 34.4% (67/195) | 33.3% (24/72) | 34.8% (40/115) | 0.92 | < 0.01 | 0.88 |
| GAD7 total | 9.3 ± 6.1 | 9.6 ± 6.0 | 7.9 ± 5.6 | 9.7 ± 6.0 | 8.8 ± 6.3 | 7.6 ± 6.5 | 9.7 ± 6.2 | 0.28 | 0.07 | 0.06 |
| % clinical range (≥ 5) | 74.7% (274/367) | 75.8% (169/223) | 70.6% (36/51) | 75.9% (104/137) | 72.7% (101/139) | 61.1% (33/54) | 79.7% (63/79) | 0.54 | 0.46 | 0.03 |
| Thoughts of suicide or self-harm (PHQ #9) | 15.3% (55/359) | 12.4% (27/218) | 3.9% (2/51) | 15.8% (21/133) | 19% (26/137) | 13.2% (7/53) | 24.4% (19/78) | 0.09 | 0.04 | 0.13 |
| Decreased likelihood remaining in field | 49.3% (215/436) | 55% (143/260) | 46.4% (26/56) | 59% (95/161) | 40.6% (69/170) | 35.9% (23/64) | 43.9% (43/98) | < 0.01 | 0.12 | 0.33 |
| Trouble completing work tasks | 18.5% (80/433) | 21.2% (55/259) | 17.9% (10/56) | 22% (35/159) | 14.3% (24/168) | 15.9% (10/63) | 12.2% (12/98) | 0.08 | 0.57 | 0.64 |
* Responses are indicated as the percent responding positively (the 4 binary response items) or the mean ± SD (the 13 individual Likert scale items, range 0–3); total exposure score represents the sum of the 13 Likert scale items (range 0–39)
** Psychiatric symptom and functional outcome characterization: mean ± SD of measure totals for PCL5 PTSD Checklist for DSM5, PHQ9 Patient Health Questionnaire 9-item (depression symptoms), ISI Insomnia Severity Index, GAD7 Generalized Anxiety Disorder 7-item
Fig. 2COVID-19-related occupational exposure (CROS total score) is strongly related to increased burden of psychiatric symptoms. A Bivariate relationships between demographic variables, exposure scores, and psychiatric symptom scores are represented by Spearman’s correlation coefficients. Scatter plots are provided for the relationship of CROS total to PTSD symptoms (B), depression symptoms (C), insomnia symptoms (D), and anxiety symptoms (E). *p < .05, **p < .01, ***p < .001, ****p < .0001. “Close death” = death of a family member or close colleague from COVID-19, “Inc risk” = medical condition associated with increased risk from COVID-19 infection
Fig. 3Relationships between different factors of COVID-19-related occupational stressors (CROS factors), psychiatric symptom expression, and functional outcomes. Results of multivariable regression models relating CROS factors and covariates to psychiatric symptom clusters (A) and functional outcome measures along with thoughts of suicide or self-harm (B). C Results of independent multivariable regression models relating symptom clusters as measured by total scores on the PCL5, PHQ9, GAD7, and ISI, along with covariates of age and gender, to functional outcome measures
Thematic Analysis of Free-Text Responses
• Leaders not listening to or respecting suggestions and needs of frontline staff; defensiveness; lack of transparency, proactive planning; confusing, inconsistent guidelines | “Higher management not recognizing that some of their staff are highly trained to respond […] Infection prevention department close minded to suggestions made by the bedside staff […].” |
• Insufficient PPE, safeguards, and protocols; general lack of caring or support from leaders | “Our hospital doesn't care about us. We're disposable.” |
• Increase in demands, more complex; significant changes in procedures; examples also included having to work longer hours without breaks and working outside one’s expertise and/or scope; nurses as “catch all” HCW | “Sudden schedule changes. Extensive work hours. The uncertainty of the disease and the continuous change and controversy of the treatments.” |
• Shortage of nurses, other essential HCW due to increased demands from patients; colleagues out with COVID-19 | “Severe understaffing and constantly feeling like I am being overworked and underappreciated.” |
• Patient care ethics; impact of COVID-19 on quality of care for COVID-19 patients and non-COVID-19 patients alike (due to overwhelming demands, short-staffing) | “People begging for your help. I feel so evil and dirty having to place a BiPap on a patient begging me not to. They don’t like it and cry and beg for me to let them die. I must put patients in restraints to keep them from pulling out their tubes. They cry for me to let them go. It's like a bad horror movie.” |
• Fear of or enacted retaliation for speaking out against workplace risks, hazards, and lack of safeguards; blackmail; threats to career and/or professional development for wanting to quit | “I was exposed to a confirmed COVID patient in April who was in respiratory distress. I only had my N95 on, no face shield or gown had been provided. I wanted to quarantine; I was accused of borderline patient abandonment. They threatened to report me to the board. I quit, then I couldn’t get unemployment because I quit.” |
• Failure of colleagues to follow guidelines/safeguards | “My coworkers are COVID deniers. I work in EMS and it makes it really hard.” |
• Public health guidelines disregarded by the general public; COVID-19 skepticism and/or denial often fueled by political and public health leaders; lack of accommodation from society for needs such as childcare | “The worst thing is dealing with incredible stress at work, and then realizing no one really cares… I separate from my kids at the first sign of symptoms because I'm heavily exposed at work, but then have to listen to people complaining about recommendations they don't have people over for Thanksgiving. It's very disheartening when the community doesn't do its part. I feel betrayed.” |
• Stress (immediate and anticipated), burnout, anxiety, uncertainty, and/or feeling underappreciated | “I have never felt so helpless and devastated as well as traumatized in my career.” |
• Few explicitly said anything akin to “I’m afraid I’ll get COVID,” even when acknowledging infection risk. Health consequences focused more on effect of working long hours, wearing PPE for extensive amounts of time, etc | “Not having time to pee or drink water.” |
• Risk for family members or colleagues of COVID-19 infection, and impacts like stress for family members | “My [child] had severe anxiety due to my position and frequently had nightmares and panic attacks. She had previously not had anxiety problems.” |
• Insufficient pay relative to magnitude of demands and risks; lack of paid sick or vacation leave; job resignation, unemployment, loss of base pay; medical costs of COVID-19 | “Healthcare workers largely have not received hazard pay […] If you develop symptoms you are sent home for 3 days without pay.” |
We determined responses as being overrepresented when the proportions of respondents who endorsed the item deviated by > 5% from the occupational category’s representation in the open-ended text responses (i.e., 67% HCW, 31% FR, and 2% other). For example, if 73% of a theme was endorsed by HCW, it was considered overrepresented, and thereby uniquely relevant to that occupational group
Fig. 4Potential schematic framework for considering direct and contextual factors contributing to occupational stress from the COVID-19 pandemic, and potential mitigation strategies. Stressors (left) and potential mitigation strategies (right) are divided into direct and contextual factors. Direct factors result primarily from the volume of COVID-19-related care being provided by an individual or their institution and resources available for the system to respond to these demands. Contextual factors can be addressed independent of the volume of COVID-19-related care being provided, and include the responsiveness of the system to addressing and supporting HCW/FR’s needs, and ensuring they are not put at unnecessary risk. Stressors represent a synthesis of factors identified from the quantitative and qualitative analyses; mitigation strategies represent concrete examples of ways in which the identified stressors could be modified, minimized, or mitigated. Mitigation or intervention approaches may vary depending on the most relevant occupational stressors for a specific group. For example, the strong relationship between demoralization and both psychiatric symptoms and adverse occupational outcomes in FR, along with the emphasis in free-text responses of fear of or enacted reprisal from leaders and betrayal by colleagues, suggest interventions focused on responsiveness and clear communication from leadership and protections of job and financial security may be particularly important for many FR. The high rates of PTSD symptoms and the relationship of these symptoms to a high likelihood of leaving one’s current field for nurses may suggest that interventions focused on decreasing the risk of PTSD, and increasing the availability and utilization of treatment for PTSD, may be of particularly high priority for nurses. An alternative example of a conceptual framework for planning risk mitigation and interventions based on a literature review can be found in Schwartz et al[5]