Relationships Between Burnout and Resilience: Experiences of Physical Therapists and Occupational Therapists During the COVID-19 Pandemic

Abstract

Objective

Research on burnout among physical therapists and occupational therapists in the context of the coronavirus disease 2019 (COVID-19) pandemic is limited. Resilience may be important for reducing burnout and promoting well-being among rehabilitation specialists, especially during periods of elevated occupational demand and stress. The purpose of this study was to investigate experiences of burnout, COVID-19 pandemic–related distress, and resilience among physical therapists and occupational therapists during the first year of the COVID-19 pandemic.

Methods

Physical therapists and occupational therapists working in a university-affiliated health system were invited to complete an online survey assessing burnout, COVID-19 pandemic–related distress, state- and trait-like resilience, physical activity, sleep disturbance, and financial concerns. Multiple linear regressions were used to examine variables associated with burnout as well as the contribution of specific aspects of resilience to burnout.

Results

Greater COVID-19 pandemic–related distress was associated with greater emotional exhaustion and depersonalization, whereas state-like resilience at work was associated with lower emotional exhaustion, greater personal accomplishment, and lower depersonalization. Analyses examining the impact of specific components of resilience at work suggested that several components are associated with less burnout, with finding one’s calling being particularly relevant for all 3 domains of burnout.

Conclusion

Symptoms of burnout were reported by many physical therapists and occupational therapists. COVID-19–related distress and state-like resilience at work, particularly the perception of finding one’s calling, emerged as consistently being associated with burnout in the context of the COVID-19 pandemic.

Impact

These findings can inform the development of interventions to reduce burnout among physical therapists and occupational therapists amid the continuing COVID-19 pandemic.

Resilience, Physical Therapists, Occupational Therapists, COVID-19, Burnout

Introduction

High occupational stress is associated with burnout, a syndrome characterized by emotional exhaustion (EE), depersonalization (DP), and feelings of ineffectiveness at work.^1–8 Burnout negatively impacts nearly every aspect of health care, with significant consequences for patients, health care professionals, and health systems.⁹ Patients treated by health care professionals with higher levels of burnout experience an increased prevalence of major medical errors, lower patient satisfaction, decreased quality of care, and worse health outcomes.⁹ Providers reporting burnout experience diminished productivity, an increased risk of major motor vehicle crashes, and a greater prevalence of mental health disorders, substance abuse, and suicide.⁹ Health systems experience increased staff turnover, lower workplace morale, and a shift in time and resources toward recruiting, hiring, and training staff.⁹

Burnout experienced by rehabilitation specialists (ie, physical therapists and occupational therapists) has received increased attention in the media and by professional organizations (eg, American Physical Therapy Association) in the past several years, yet research regarding burnout among rehabilitation specialists has remained limited.¹⁰ Studies conducted prior to the coronavirus disease 2019 (COVID-19) pandemic indicate that aspects of burnout are common, with 58% of rehabilitation specialists reporting high levels of EE.¹¹ Among rehabilitation specialists, EE is the most commonly reported aspect of burnout and is mostly associated with occupational stress.^4,7,12 The degree of burnout experienced by rehabilitation specialists is present across health care settings, caseload expectations, and patient populations.¹¹ For example, levels of burnout in hospitals, home health facilities, rehabilitation settings, private practice, and skilled nursing ranged from low to moderate.¹³ Rehabilitation specialists report feeling stressed at work because of a variety of issues including lack of autonomy, excessive workloads, workplace disorganization, lack of supervisor support, and time constraints.^2,14–18 Current trends contributing to burnout among rehabilitation specialists include considerable increases in tuition costs, student loan debt, productivity expectations, and documentation requirements.^19,20

The COVID-19 pandemic placed increased occupational stress on health care professionals by adding uncertainty, fear, potential threat, and stigmatization to an already challenging work environment.²¹ Many health care professionals have reported trauma-like symptoms, including emotional numbing and intrusive, vivid, and traumatic thoughts.²² For rehabilitation specialists, increased stressors included the transition to telehealth, pressure to discharge patients without COVID-19 rapidly, providing care to a lonely or isolated patient population, and for some, managing staffing needs, childcare, and school closures.^23–27 Physical therapists described negative critical events as a result of COVID-19, such as witnessing the death of patients who died alone and providing manual ventilator support for hours until exhaustion.²⁸ Despite these documented stressors, research has not explored the psychological burden experienced by occupational therapists during the COVID-19 pandemic and research focused on physical therapists has been limited.^21,22,28,29 A comparison of studies published before and during the pandemic suggests that rates of burnout among physical therapists significantly increased during the COVID-19 pandemic,¹² with 1 study of physical therapists in Portugal finding 42% reporting personal burnout, 42% reporting work-related burnout, and 25% reporting patient-related burnout.³⁰

Resilience refers to the capacity to manage stress, adapt to adverse situations, and rebound and learn from unexpected setbacks while remaining healthy.^31,32 Resilience can be enhanced and considered a changeable state versus a fixed trait. State-like resilience may be important for reducing burnout and promoting well-being among health care professionals, especially during periods of elevated occupational demand and stress such as the COVID-19 pandemic.^33–37 One recent study of physical therapists in Brazil during the COVID-19 pandemic found that therapists with low levels of resilience experienced significantly greater depression, anxiety, stress, and COVID-19 pandemic–related (COVID-related) traumatic stress symptoms compared to those with high levels of resilience.³⁸ In a study of resilience among health care professionals, including rehabilitation specialists, during the COVID-19 pandemic, work environment factors associated with greater resilience included having positive perceptions about the health care organization’s understanding of health care professionals’ emotional support needs, having educational resources regarding the care of patients with COVID-19, having positive perceptions of leadership support from direct managers, believing that staff redeployment to critical areas was necessary, and having greater psychological safety.³⁵

This study investigates the experiences of burnout, COVID-related distress, and resilience among rehabilitation specialists during the COVID-19 pandemic. The 3 aims of this study are to describe levels of burnout and COVID-related distress among rehabilitation specialists; examine factors associated with burnout, including COVID-related distress; and explore the relationships between different aspects of resilience and burnout. Resilience has been conceptualized as both trait- and state-like. The current study examines the role of trait-like resilience (ie, individuals’ ability to bounce back or recover from stressful circumstances) and state-like resilience (ie, behaviors, attitudes, and states that underpin personal resilience) in the workplace.

Methods

Participants

From July to December 2020, physical therapists and occupational therapists working in a university-affiliated health system were invited to complete an online survey. Inclusion criteria were physical or occupational therapist, providing patient care in an outpatient or inpatient setting, and age of ≥18 years. Exclusion criteria included inability to speak or read English and inability to provide meaningful informed consent (eg, cognitive impairment). This study was approved by the Duke University Health System Institutional Review Board (protocol number 00104215) and complies with the Declaration of Helsinki.

Procedures

Emails inviting study participation were sent to physical therapists and occupational therapists working in the university-affiliated health system. The invitation email described the study, provided contact information for the study team, and included an option to opt out of receiving future emails about the study. For those interested in study participation, informed consent was completed online via Research Electronic Data Capture (REDCap). After completing informed consent, participants completed the study questionnaires online via a REDCap survey.

Measures

Demographic and Background Information

Participants demographic and background characteristics were assessed by self-report including gender education, partner status, area of training and practice, years of experience, and years of employment in their current health system.

Work-Related Burnout

The Maslach Burnout Inventory (MBI)³⁹ is a well-validated 22-item questionnaire assessing 3 dimensions of burnout: EE (9 items), DP (5 items), and personal accomplishment (PA; 8 items). Each item is rated using a 7-point frequency response scale ranging from 0 (never) to 6 (every day). Items are summed to create a score for each burnout dimension. Higher EE and DP scores indicate higher levels of burnout, whereas higher PA scores reflect lower levels of burnout. In the present sample, the Cronbach α ranged from 0.80 to 0.93 for the subscales.

COVID-Related Distress

The Impact of Event Scale–Revised (IES-R)⁴⁰ is a 22-item self-report measure assessing subjective distress related to a specific event. The event of interest for this study was the COVID-19 pandemic. The IES-R assesses symptoms of intrusion (8 items), avoidance (8 items), and hyperarousal (6 items), with participants rating how distressing each item has been during the past 7 days from 0 (not at all) to 4 (extremely). Items are summed to yield a total score, with higher scores indicating greater distress. The Cronbach α was 0.88.

Resilience

The Resilience at Work Scale⁴¹ is a 20-item measure assessing behaviors, attitudes, and states that underpin personal resilience in the workplace in 7 domains: living authentically (3 items), finding one’s calling (4 items), maintaining perspective (3 items), managing stress (4 items), interacting cooperatively (2 items), staying healthy (2 items), and building networks (2 items). Items are rated on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). Items are summed to create a total score, with higher scores indicating higher resilience at work. For each domain, items can be summed to create a subscale score. The Cronbach α was 0.86 for the total score and ranged from 0.61 to 0.86 for the subscales.

The Brief Resilience Scale⁴² is a 6-item measure assessing individuals’ abilities to “bounce back” or recover from stressful circumstances. Items are rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). Three items are positively worded, and 3 items are negatively worded. Negatively worded items are reverse scored, and items are then summed to create a total score, with higher scores indicating greater resilience. The Cronbach α was 0.90.

Physical Activity

The well-validated International Physical Activity Questionnaire–Short Form⁴³ calculates the metabolic equivalent value, and considers the frequency, duration (minutes), and intensity of physical activities performed for at least 10 minutes over the past 7 days. The questionnaire considers vigorous-intensity activity, moderate-intensity activity, walking (slow, moderate, and fast paces), and time spent for sitting. The total volume of physical activity accumulated over the past 7 days is calculated by multiplying the duration of the reported category by its assigned metabolic equivalent value.

Sleep Disturbance

The 4-item PROMIS Sleep Disturbance–Short Form⁴⁴ was used to assess the severity of sleep disturbance in the past 7 days. Items are rated on a 5-point scale, with 1 sleep quality item rated from 1 (very good) to 5 (very poor) and 3 items assessing sleep disturbance rated from 1 (not at all) to 5 (very much). Items are summed to create a total score, and a standardized T score is obtained. Higher scores represent a more severe sleep disturbance. The Cronbach α was 0.82.

Financial Concerns

Two items developed for this study were used to assess the impact of student debt on and worry about finances. Participants were asked the degree to which they agreed with each of the following statements on a 5-point scale from 1 (strongly disagree) to 5 (strongly agree): “Student debt has negatively impacted my financial situation” and “I often worry about my financial situation.”

Data Analysis

Descriptive statistics were computed. Bivariate analyses (ie, independent t tests or Pearson correlations, as appropriate) were conducted to examine associations between study variables and participant characteristics. Pearson correlations also examined associations among study variables. Multiple linear regression analyses were conducted to examine variables associated with burnout (ie, EE, PA, and DP). Variables associated with 1 or more of the MBI scales in bivariate analyses (P < .05) were included in regression models. Separate regression models were conducted for each burnout scale. Subsequent regression models were conducted to examine the relationships between different components of resilience and each of the burnout scales. For each regression model, variance inflation factor and tolerance tests determined the degree of multicollinearity in models. A variance inflation factor value of 10 or more and a tolerance test value of 0.10 or less was used to identify problems with multicollinearity.⁴⁵ No multicollinearity problems were identified, as regression models had variance inflation factor values of ≤2.20 and tolerance test values of ≥0.46. Analyses were conducted using SPSS 25 (IBM SPSS, Chicago, IL, USA).

Table 1

Sample Description (n = 125)

Characteristic	% (No.) of Participants	Mean (SD)	Range
Age, y	a	36.30 (9.44)	26.00–64.00
Gender
Male	24.0 (30)
Female	76.0 (95)
Type of professional
Occupational therapist	24.8 (31)
Physical therapist	75.2 (94)
Practice setting
Outpatient	64.0 (80)
Inpatient	22.4 (28)
Both outpatient and inpatient	13.6 (17)
Years of professional experience		9.84 (9.60)	0.50–43.00
Highest level of training
Bachelor’s degree	4.0 (5)
Master’s degree	31.2 (39)
Doctorate	51.2 (64)
Residency	6.4 (8)
Fellowship	7.2 (9)
Area of practice  b
Subacute	1.6 (2)
Acute	16.0 (20)
Sports	18.4 (23)
Pediatric	13.6 (17)
Cardiopulmonary	10.4 (13)
Pelvic floor	10.4 (13)
Oncology	11.2 (14)
Neurology	15.2 (19)
Orthopedic	36.8 (46)
Other	12.0 (15)
Treat individuals with chronic pain	59.2 (74)
Training in psychosocial aspects of patient care  b
Occasional lectures	71.2 (89)
Semester course	37.6 (47)
Informal teaching	58.4 (73)
Role playing	39.2 (49)
Cognitive-behavioral based	46.4 (58)
Organized course or workshop	15.2 (19)
No formal training	4.0 (5)
Other	4.8 (6)
Maslach Burnout Inventory
Emotional exhaustion		21.52 (11.35)	0.00–52.00
Personal accomplishment		38.07 (4.75)	22.00–46.00
Depersonalization		5.06 (4.99)	0.00–24.00
Impact of Event Scale–Revised (COVID-19 pandemic–related distress)		19.91 (12.01)	1.00–55.00
Resilience at Work Scale		85.92 (13.13)	57.00–111.00
Brief Resilience Scale		20.90 (4.48)	11.00–30.00
International Physical Activity Questionnaire–Short Formc		939.51 (947.48)	0.00–4808.20
PROMIS Sleep Disturbance–Short Form (T score)		49.33 (6.76)	32.00–68.80
Student debt has negatively affected my financial situation		3.43 (1.55)	1.00–5.00
I often worry about my financial situation		3.48 (1.26)	1.00–5.00

^a

Although the total number of respondents was 125, the system was missing age for 1 participant.

^b

Because participants may provide care/receive training in more than 1 area, they indicated all areas that applied.

^c

Measured in metabolic equivalent min/wk.

Results

Sample Description

Table 1 displays the participant characteristics and descriptive statistics for study measures. The participants’ (n = 125) average age was 36.30 (SD = 9.44) years, and 76.0% (n = 95) were female. Race was not collected for this sample; among all rehabilitation specialists approached for study participation (N = 419), 77.1% (n = 323) identified as white. Therapists had an average of 9.84 (SD = 9.60) years of professional experience. The sample included occupational therapists (24.8%; n = 31) and physical therapists (75.2%; n = 94), with 64.0% (n = 80) of providers working in outpatient settings, 22.4% (n = 28) working in inpatient settings, and 13.6% (n = 17) working in both outpatient and inpatient settings.

Average MBI scores were 21.52 (SD = 11.35) for EE, 38.07 (SD = 4.75) for PA, and 5.06 (SD = 4.99) for DP. The presence of burnout is suggested by EE scores of ≥27, PA scores of ≤33, and DP scores of ≥10.^39,46 In this study, 32.8% (n = 41) reported elevated EE scores, 13.6% (n = 17) reported low PA scores, and 15.2% (n = 19) reported high DP scores. Only 4.0% (n = 5) of participants reported significant symptoms of burnout on all 3 MBI scales.

The average IES-R score was 19.9 (SD = 12.0). IES-R scores of ≥24 indicate elevated symptoms of distress, whereas scores of ≥33 suggest more severe symptoms consistent with a probable diagnosis of posttraumatic stress disorder.^47,48 Of participants, 31.2% (n = 39) reported IES-R scores of 24 or higher, with 16.8% (n = 21) reporting scores of 33 or higher.

Table 2

Correlations Between Study Variables^a

Variable	Pearson Correlation, r (95% CI) for:
	MBI Emotional Exhaustion	MBI Personal Accomplishment	MBI Depersonalization	Impact of Event Scale–Revised	PROMIS	IPAQ-SF	Negative Impact of Student Debt	Worry About Financial Situation	Resilience at Work Scale	Brief Resilience Scale
MBI emotional exhaustion
MBI personal accomplishment	0.01 (−0.16 to 0.19)
MBI depersonalization	0.60b (0.47 to 0.70)	−0.24c (−0.40 to −0.07)
Impact of Event Scale–Revised	0.44b (0.28 to 0.57)	−0.19c (−0.36 to −0.02)	0.28c (0.11 to 0.44)						.
PROMIS	0.40b (0.24 to 0.54)	−0.24c (−0.40 to −0.06)	0.20c (0.02 to 0.36)	0.38b (0.22 to 0.52)
IPAQ-SF	−0.10 (−0.27 to 0.08)	0.04 (−0.13 to 0.22)	−0.07 (−0.24 to 0.11)	−0.02 (−0.19 to 0.16)	−0.04 (−0.21 to 0.14)
Negative impact of student debt	0.12 (−0.06 to 0.29)	−0.05 (−0.22 to 0.13)	0.25c (0.07 to 0.40)	0.03 (−0.15 to 0.21)	−0.03 (−0.21 to 0.14)	−0.19c (−0.36 to −0.02)
Worry about financial situation	0.32b (0.16 to 0.47)	−0.08 (−0.25 to 0.10)	0.24c (0.07 to 0.40)	0.19c (0.01 to 0.36)	0.25c (0.08 to 0.41)	−0.10 (−0.27 to 0.08)	0.61b (0.48 to 0.71)
Resilience at Work Scale	−0.59b (−0.70 to −0.46)	0.31c (0.14 to 0.46)	−0.41b (−0.54 to −0.25)	−0.28c (−0.44 to −0.11)	−0.36b (−0.50 to −0.19)	0.27c (0.12 to 0.44)	−0.11 (−0.28 to 0.07)	−0.27c (−0.42 to −0.09)
Brief Resilience Scale	−0.32b (−0.47 to −0.16)	0.28c (0.11 to 0.43)	−0.23c (−0.39 to −0.05)	−0.33b (−0.48 to −0.16)	−0.32b (−0.47 to −0.15)	−0.15 (−0.24 to 0.11)	−0.06 (−0.23 to 0.12)	−0.15 (−0.32 to 0.02)	0.55b (0.42 to 0.66)

^a

IPAQ-SF = International Physical Activity Questionnaire–Short Form; MBI = Maslach Burnout Inventory; PROMIS = PROMIS Sleep Disturbance–Short Form.

^b

P < .001.

^c

P < .05.

Associations With Participant Characteristics

Relationships between participant characteristics and study measures were examined. Compared with female participants, male participants reported significantly higher MBI DP scores (mean = 7.70 [SD = 5.58] vs mean = 4.42 [SD = 4.64]; 95% CI for mean difference = 0.62 to 4.67; t₁₂₃ = 2.59; P = .01; d = 0.54) and significantly greater negative impact of student debt (mean = 3.97 [SD = 1.30] vs mean = 3.26 [SD = 1.59]; 95% CI for mean difference = 0.07 to 1.35; t₁₂₂ = 2.22; P = .03; d = 0.47). Older age and more years of professional experience were associated with having a lower negative impact of student debt (r = −0.39 [P < .001; 95% CI = −0.53 to −0.23] and r = −0.43 [P < .001; 95% CI = −0.56 to −0.27], respectively) and less worry about finances (r = −0.24 [P = .008; 95% CI = −0.40 to −0.06] and r = −0.33 [P < .001; 95% CI = −0.48 to −0.16], respectively). There were no other statistically significant (P < .05) associations between participant characteristics and study variables.

Correlational Analysis

Table 2 displays associations (ie, Pearson correlations with 95% CIs) between study variables. Higher EE was significantly correlated with higher DP (r = 0.60; P < .001), IES-R COVID-related distress (r = 0.44; P < .001), sleep disturbance (r = 0.40; P < .001), and worry about finances (r = 0.32; P < .001), and with lower resilience at work (r = −0.59; P < .001). EE and PA scores were not related (r = 0.01; P = .89). Higher PA was significantly correlated with lower DP (r = −0.24; P = .007), IES-R COVID-related distress (r = −0.19; P = .03), and sleep disturbance (r = −0.24; P = .008), and with higher resilience at work (r = 0.31; P = .001). Higher DP was also significantly associated with greater IES-R COVID-related distress (r = 0.28; P = .002), sleep disturbance (r = 0.20; P = .03), negative impact of student debt (r = 0.25; P = .006), and worry about finances (r = 0.24; P = .006), and with lower resilience at work (r = −0.41; P < .001). In addition to significant associations with the MBI scales, greater IES-R COVID-related distress was also significantly associated with greater sleep disturbance (r = 0.38; P < .001) and worry about finances (r = 0.19; P = .04), and with lower resilience at work (r = −0.28; P = .002).

Multiple-Regression Analysis

Table 3 displays the results of multiple-regression analyses examining variables associated with burnout. The regression model for EE was significant (total R² = 0.48; F_7,114 = 14.86; P < .001). Higher IES-R COVID-related distress was significantly associated with higher EE (β = 0.25; 95% CI = 0.10 to 0.38; t₁₁₄ = 3.35; P = .001; squared semipartial correlation coefficient [sr²] = 0.05), whereas higher resilience at work was significantly associated with lower EE (β = −0.50; 95% CI = −0.58 to −0.29; t₁₁₄ = −5.85; P < .001; sr² = 0.16). The regression model for PA was significant (total R² = 0.15; F_7,114 = 2.79; P = .01). Resilience at work was the only variable significantly associated with PA, with greater resilience being associated with higher PA (β = 0.23; 95% CI = 0.01 to 0.16; t₁₁₄ = 2.09; P = .04; sr² = 0.03). The regression model for DP was also significant (total R² = 0.30; F_7,114 = 6.81; P < .001). Higher COVID-related distress (β = 0.18; 95% CI = 0.002 to 0.15; t₁₁₄ = 2.02; P = .046; sr² = 0.03) and male gender (β = −0.22; 95% CI = −4.42 to −0.69; t₁₁₄ = −2.71; P = .008; sr² = 0.05) were significantly associated with higher DP. Higher resilience at work was significantly associated with lower DP (β = −0.37; 95% CI = −0.22 to −0.07; t₁₁₄ = −3.71; P < .001; sr² = 0.08).

Table 3

Multiple-Regression Analysis Examining Associations With MBI Scales^a

Variable	β	95% CI for β	t114	P	sr2
Emotional exhaustion
Gender (0 = male, 1 = female)	−0.13	−7.08 to 0.21	−1.87	.07	0.02
IES-R COVID-19 pandemic–related distress	0.25	0.10 to 0.38	3.35	.001	0.05
PROMIS Sleep Disturbance–Short Form (T score)	0.12	−0.06 to 0.46	1.50	.14	0.01
Negative impact of student debt	−0.03	−1.56 to 1.05	−0.38	.71	0.001
Worry about finances	0.14	−0.41 to 2.86	1.49	.14	0.01
Resilience at Work Scale	−0.50	−0.58 to −0.29	−5.85	<.001	0.16
Brief Resilience Scale	0.08	−0.24 to 0.62	0.89	.37	0.004
Personal accomplishment
Gender (0 = male, 1 = female)	−0.03	−2.32 to 1.58	−0.38	.71	0.001
IES-R COVID-19 pandemic–related distress	−0.06	−0.10 to 0.05	−0.62	.54	0.003
PROMIS Sleep Disturbance–Short Form (T score)	−0.14	−0.24 to 0.04	−1.41	.16	0.01
Negative impact of student debt	−0.09	−0.97 to 0.42	−0.79	.43	0.005
Worry about finances	0.08	−0.56 to 1.18	0.71	.48	0.004
Resilience at Work Scale	0.23	0.01 to 0.16	2.09	.04	0.03
Brief Resilience Scale	0.09	−0.13 to 0.33	0.85	.40	0.005
Depersonalization
Gender (0 = male, 1 = female)	−0.22	−4.42 to −0.69	−2.71	.008	0.05
IES-R COVID-19 pandemic–related distress	0.18	0.002 to 0.15	2.02	.05	0.03
PROMIS Sleep Disturbance–Short Form (T score)	0.03	−0.11 to 0.16	0.34	.73	0.001
Negative impact of student debt	0.17	−0.12 to 1.22	1.63	.11	0.02
Worry about finances	−0.005	−0.86 to 0.82	−0.05	.96	0.00
Resilience at Work Scale	−0.37	−0.22 to −0.07	−3.71	<.001	0.08
Brief Resilience Scale	0.02	−0.20 to 0.24	0.21	.83	0.00

^a

IES-R = Impact of Event Scale–Revised; MBI = Maslach Burnout Inventory.

Multiple linear regression analyses examined associations between different components of resilience at work and burnout (Tab. 4). Because gender and IES-R COVID-related distress were significantly associated with 1 or more of the MBI scales in multiple-regression analyses, these variables were included in models examining associations between resilience components and MBI scales. The regression model for EE was significant (total R² = 0.58; F_9,113 = 17.01; P < .001). Higher scores for finding one’s calling (β = −0.36; 95% CI = −7.37 to −2.50; t₁₁₃ = −4.01; P < .001; sr² = 0.06), maintaining perspective (β = −0.28; 95% CI = −4.35 to −1.33; t₁₁₃ = −3.73; P < .001), and managing stress (β = −0.23; t₁₁₃ = −3.12; P = .002; sr² = 0.04) were significantly associated with lower EE. Higher scores on the staying healthy component were significantly associated with higher EE (β = 0.15; 95% CI = 0.10 to 2.99; t₁₁₃ = 2.12; P = .0014; sr² = 0.02). The regression model for PA was significant (total R² = 0.28; F_9,113 = 4.96; P < .001). Higher scores for findings one’s calling (β = 0.37; 95% CI = 0.79 to 3.42; t₁₁₃ = 3.16; P = .002; sr² = 0.06), interacting cooperatively (β = 0.22; 95% CI = 0.17 to 2.32; t₁₁₃ = 2.30; P = .02; sr² = 0.03), and staying healthy (β = 0.27; 95% CI = 0.37 to 1.93; t₁₁₃ = 2.91; P = .004; sr² = 0.05) were significantly associated with higher PA. Having a higher score on the building networks component was significantly associated with lower PA (β = −0.25; 95% CI = −1.79 to −0.21; t₁₁₃ = −2.51; P = .01; sr² = 0.04). The regression model for DP was significant (total R² = 0.39; F_9,113 = 8.16; P < .001). Higher scores for findings one’s calling were significantly associated with lower DP (β = −0.38; 95% CI = −3.57 to −1.00; t₁₁₃ = −3.53; P = .001; sr² = 0.07).

Table 4

Multiple-Regression Analysis Examining Relationships Between Components of Resilience at Work and MBI Scales^a

Variable	β	95% CI for β	t113	P	sr2
Emotional exhaustion
Gender (0 = male, 1 = female)	−0.14	−7.09 to −0.40	−2.22	.03	0.02
IES-R COVID-19 pandemic–related distress	0.24	0.11 to 0.35	3.64	<.001	0.05
Living authentically	0.03	−1.85 to 2.81	0.41	.68	0.00
Finding one’s calling	−0.36	−7.37 to −2.50	−4.01	<.001	0.06
Maintaining perspective	−0.28	−4.35 to −1.33	−3.73	<.001	0.05
Managing stress	−0.23	−3.65 to −0.81	−3.12	.002	0.04
Interacting cooperatively	0.04	−1.47 to 2.49	0.51	.61	0.00
Staying healthy	0.15	0.10 to 2.99	2.12	.04	0.02
Building networks	−0.05	−1.94 to 0.96	−0.68	.50	0.002
Personal accomplishment
Gender (0 = male, 1 = female)	−0.09	−2.75 to 0.87	−1.03	.31	0.01
IES-R COVID-19 pandemic–related distress	−0.08	−0.10 to 0.04	−0.93	.36	0.01
Living authentically	−0.01	−1.32 to 1.21	−0.09	.93	0.00
Finding one’s calling	0.37	0.79 to 3.42	3.17	.002	0.06
Maintaining perspective	−0.02	−0.91 to 0.72	−0.23	.82	0.00
Managing stress	−0.05	−0.96 to 0.57	−0.50	.62	0.002
Interacting cooperatively	0.22	0.17 to 2.32	2.30	.02	0.03
Staying healthy	0.27	0.37 to 1.93	2.91	.004	0.05
Building networks	−0.25	−1.79 to −0.21	−2.51	.01	0.04
Depersonalization
Gender (0 = male, 1 = female)	−0.22	−4.34 to −0.82	−2.90	.004	0.04
IES-R COVID-19 pandemic–related distress	0.13	−0.01 to 0.12	1.64	.10	0.01
Living authentically	−0.07	−1.68 to 0.78	−0.73	.47	0.003
Finding one’s calling	−0.38	−3.57 to −1.00	−3.53	.001	0.07
Maintaining perspective	−0.15	−1.46 to 0.14	−1.65	.10	0.01
Managing stress	−0.01	−0.78 to 0.72	−0.08	.93	0.00
Interacting cooperatively	−0.16	−1.97 to 0.11	−1.76	.08	0.02
Staying healthy	0.11	−0.26 to 1.27	1.32	.19	0.009
Building networks	0.08	−0.43 to 1.09	0.86	.39	0.004

^a

IES-R = Impact of Event Scale–Revised; MBI = Maslach Burnout Inventory.

Discussion

Burnout represents a commonly experienced and understudied concern among rehabilitation specialists,¹¹ which has been further exacerbated by the COVID-19 pandemic.^12,30 This study examined experiences of burnout, COVID-related distress, and resilience among rehabilitation specialists during the COVID-19 pandemic. Resilience at work, which is characterized by behaviors, attitudes, and states that underpin one’s capacity for managing and adapting to difficult situations or unexpected setbacks,⁴¹ emerged as a potentially important protective factor for rehabilitation specialists. Higher resilience at work was significantly associated with lower EE, higher PA, and lower DP, even after accounting for associations between burnout and COVID-related distress. Examination of the relationships between burnout and specific domains of resilience at work found that maintaining perspective and managing stress were associated with lower EE, whereas interacting cooperatively and staying healthy were associated with higher PA. Finding one’s calling (ie, a sense of purpose and belonging at work) was significantly associated with all 3 domains of burnout including lower EE, higher PA, and lower DP. These findings suggest that finding one’s calling may be an especially important component of resilience for reducing burnout among rehabilitation specialists.

Surprisingly, the staying healthy and building networks components of resilience at work demonstrated relationships with burnout in unexpected directions: higher scores for staying healthy were associated with higher EE, and higher scores for building networks were associated with lower PA. These unexpected associations may reflect particular impacts of the COVID-19 pandemic. For many people, COVID-related restrictions limited access to exercise facilities, recreational activities, and other resources for staying healthy. In addition, individuals who value “staying healthy” may have experienced heightened health concerns relating to exposure or contraction of COVID-19. It is possible that restrictions on usual activities for staying healthy and fear of the virus contributed to individuals’ feelings of stress and EE. Similarly, COVID-related restrictions on social activities may have negatively impacted individuals’ abilities to build social networks and feelings of PA. In this study, the construct of “building networks” focused on social support from colleagues and did not examine institutional factors (eg, ineffectual communication and changes in work setting, expectations, and goals) that may affect building networks and further contribute to burnout.

This study examined both trait-like (ie, Brief Resilience Scale) and state-like resilience in the workplace (ie, Resilience at Work Scale). Although both trait- and state-like resilience were associated with burnout in bivariate analysis, only state-like resilience at work was associated with lower burnout in multiple-regression models. These findings suggest that the behaviors and attitudes that characterize state-like resilience in the workplace are more relevant for reducing burnout than the trait-like tendency to bounce back from stressful experiences. Strategies aimed at addressing burnout and enhancing resilience among rehabilitation specialists may be most beneficial when focused on enhancing the behaviors and attitudes associated with resilience in the work place (eg, helping therapists explicitly connect their daily work with meaningful patient outcomes). Interestingly, 1 recent review of interventions to improve resilience among health care workers found that studies using trait-like measures of resilience did not find pre- to post-intervention increases in resilience.⁴⁹

COVID-related distress symptoms were common and associated with higher EE and DP in this sample. One-third of participants reported high distress, and approximately 1 in 6 reported severe distress symptoms that would be consistent with posttraumatic stress disorder. The prevalence of severe distress in this sample is higher than the estimated prevalence of posttraumatic stress disorder in a sample of frontline workers during the COVID-19 pandemic in Australia,⁵⁰ where lockdowns have been more comprehensive and community transmission and mortality per capita have been consistently lower than in the United States. In contrast, severe distress was reported by 56% of participants in a study of frontline professionals directly involved in the care of patients with COVID-19 in Greece.⁵¹ The prevalence of severe COVID-related distress is impacted by the amount of time spent engaged in the care of patients with COVID-19.^52–54 Because our sample included professionals working in a range of care settings, the amount of exposure to the care of patients with COVID-19 and patient death varied across providers.

Limitations

This study has several limitations. First, because all participants belonged to the same academic health system, other types of organizations, settings, and geographical locations were not represented in the sample, which may have influenced results, particularly regarding the effects of the COVID-19 pandemic. Second, the degree of impact of the COVID-19 pandemic on health professionals has been associated with the amount of exposure to death and the care of patients with COVID-19 in prior studies.⁵⁴ This study included rehabilitation specialists providing care in a range of settings with variable amounts of exposure to direct care of patients with COVID-19; however, the degree of engagement in the direct care of patients with COVID-19 was not directly measured. Many of the clinicians in this sample who typically worked in outpatient settings were assigned to work partially or entirely in acute care during the first wave of COVID-19 hospitalizations, from April to May 2020. All survey results were collected prior to vaccines and may not reflect current provider experiences. Therefore, although the work-related exposure to COVID-19–related death varied, much of the sample was exposed to the acute care setting during the first wave of COVID-19 hospitalizations. Third, because of the cross-sectional design, causal relationships between burnout, resilience, or COVID-related distress could not be examined. Fourth, other important constructs such as moral injury or compassion fatigue have been identified in burnout literature but were not measured in our study. Further research is warranted that may highlight important insights relating to burnout and resilience. Moreover, this study did not address organizational support issues such as chaotic and unethical work climates, shifts toward fiscal sustainability, and decreased support for childcare services as other potential key contributors to EE.⁵⁵ Finally, because of the reliance on self-reported data, it is unclear whether the results would have been similar with objective measures (eg, minutes of physical activity, sleep disturbance, hours spent at work, amount of time exposed to stress or trauma at work).

Clinical Implications

This study suggests that COVID-related distress may contribute to burnout among rehabilitation specialists, and that resilience at work may be the most relevant factor for reducing burnout. Although several studies have detected associations between resilience and burnout, this study highlights that finding one’s calling may be the most salient aspect of resilience in addressing burnout. Interestingly, burnout may be less associated with specific health behaviors or financial concerns and instead may be more associated with whether professionals find a sense of belonging at their workplace, have work that aligns with their values and beliefs, or are able to participate in work that helps to fulfill a sense of purpose in life.

Interventions to improve resilience have historically included individual-level, organization-level, and combined approaches⁵⁶ that often aim to modify individual-level health behaviors such as physical activity, sleep habits, mindfulness practices, or diet.⁵⁷ This study suggests that the individual-level factors most associated with reducing burnout are related to state-like resilience rather than these often targeted health behaviors. Other research suggests that health care providers’ resilience, work satisfaction, and burnout are associated with workload, autonomy, effort-reward balance, and organizational support, all of which involve collaboration between organizations and clinicians.^58,59 Because of the importance of finding one’s calling, maintaining perspective, and managing stress, future interventions that aim to reduce burnout and enhance resilience should consider individual-level state-like resilience as well as organizational level factors such as increasing autonomy and improving the balance between effort and rewards.

Summary and Future Directions

Psychological distress in response to the COVID-19 pandemic and symptoms of burnout were reported by many rehabilitation specialists. Higher COVID-related distress and lower state-like resilience at work were both associated with higher EE and DP, and lower resilience at work was associated with lower PA. Resilience at work, particularly the perception of finding one’s calling, emerged as a consistent and significant factor associated with all 3 burnout domains. Yet, resilience at work and COVID-related distress explained only a portion of the variance in burnout suggesting that other factors should be considered. Future research is needed to continue to investigate the causes of burnout and to inform organizational initiatives, professional education, and the individual self-care of physical therapists and occupational therapists.

Authors’ Contributions

Concept/idea/research design: P.E. Roundy, Z.R. Stearns, J.J. Blevins, T.A. Linton, T.R. Medlin, J.G. Winger, R.A. Shelby

Writing: P.E. Roundy, Z.R. Stearns, J.J. Blevins, T.A. Linton, T.R. Medlin, J.G. Winger, C.S. Dorfman, R.A. Shelby

Data collection: M.W. Willis

Data analysis: Z.R. Stearns, M.W. Willis, R.A. Shelby

Project management: P.E. Roundy, M.W. Willis, R.A. Shelby

Clerical/secretarial support: M.W. Willis

Consultation (including review of manuscript before submitting): J.J. Blevins, T.R. Medlin, J.G. Winger, C.S. Dorfman, R.A. Shelby

Ethics Approval

This study was approved by the Duke University Health System Institutional Review Board (protocol no. 00104215).

Funding

There are no funders to report for this study.

Data Availability Statement

Descriptive statistics were computed. Bivariate analyses (ie, independent t tests or Pearson correlations, as appropriate) were conducted to examine associations between study variables and participant characteristics.

Disclosures

The authors completed the ICMJE Form for Disclosure of Potential Conflicts of Interest and reported no conflicts of interest.