Factors associated with burnout among allied health professionals in the Post-COVID era in Singapore

Abstract

Background

The endemicity of COVID and resultant social upheaval can result in significant levels of burnout. In healthcare establishments already saddled with high workloads and heavy reliance on foreign-born staff, this may create even higher levels of burnout and worsen staff turnover.

Objectives

The aim of this study was to evaluate factors affecting burnout among Allied Health Professionals (AHPs) in a tertiary hospital in Singapore. We hypothesized that female gender, younger age, relative inexperience, singlehood, and lack of family locally is associated with higher odds of burnout and that perceived social support and satisfaction with use of leisure time would help mitigate against burnout.

Methods

An anonymized email survey of AHPs was conducted. Survey instruments used were the Oldenburg Burnout Inventory, Leisure Time Satisfaction Survey, Patient Health Questionnaire-4 items, Brief form of Perceived Social Support Questionnaire, and the Demand Control Support Questionnaire.

Results

We received 136 responses, of which 69.9% (n = 95) were female. Burnout was associated with younger personnel (20–29 years old), less social support at work, and those with shorter duration of residence in Singapore (≤15 years) (p < 0.05). Burnout was also associated with psychological distress, where those with higher PHQ scores had higher odds of experiencing burnout (p < 0.05). Contrary to hypothesis, gender, singlehood, work experience, lack of immediate family residing locally, social support outside of work and satisfaction with leisure time were not significantly associated with the odds of burnout.

Conclusion

Younger AHPs with less support at work and less time residing in Singapore have higher odds to experience burnout. There is a need to implement individual and organizational interventions that target those with the greatest risk factors for burnout.

Keywords

Covid-19 burnout allied health depression anxiety

Introduction

Burnout has been defined by the ICD-11 as an occupational and psychological syndrome comprising exhaustion, increased mental distance from one’s occupation and feelings of reduced efficacy and accomplishment.¹ This is associated with reduced job satisfaction, increased absenteeism, medical errors, sickness, injury, and accidents among healthcare providers.^2,3 Moreover, burnout may lead to reduced work quality, higher mortality levels among patients, and higher staff resignation rates, thus compounding manpower shortages and reducing staff morale.⁴

It is well established that during the COVID-19 pandemic, allied health professionals (AHPs) suffered high rates of burnout,⁵ with some even proposing that AHPs were more likely to report job burnout compared to other health care workers (HCWs).⁴

Many factors can influence the occurrence of burnout, such as increased self-reported workload, lesser work experience, and younger age.⁵ Younger staff experienced more burnout,⁶ whereas married personnel, and older workers were less so affected.⁷ Others have found that female staff reported higher emotional exhaustion and lower subjective well-being than their male counterparts.⁸ In addition, workplace-specific elements e.g., lack of organizational support and conflict with hierarchical structures are sources of stress which can predispose to burnout.³

Chan and colleagues found that those living apart from family were twice more likely to report being significantly stressed.⁹ The importance of family support was further upheld where a study of pharmacists found that those experiencing burnout were younger, single and did not stay with their family.¹⁰ Travel bans prevented foreign HCWs from visiting their families in their countries of origin. Not seeing one’s family for more than a year was significantly associated with higher risk of burnout.⁹ Moreover, HCWs from overseas (and thus not living with family) were independently associated with a risk for anxiety and depression.¹¹ Forced to choose between family and work, many foreign HCWs chose to leave the country, resulting in loss of professional capital.¹² This is relevant in the local context as Singapore’s healthcare system relies heavily on foreign HCWs with foreign-born staff comprising about 15% of AHPs.¹³

During the pandemic, many of the hospital’s elective services and procedures were temporarily halted. Following the easing of restrictions as hospitals resumed services and dealt with their backlog of cases, burnout was unfortunately observed to progressively increase.⁴

While much research has focussed on burnout experienced during the pandemic, few studies have assessed burnout in the post-pandemic era, much less examining factors affecting burnout among AHPs. Ours is one of such studies. We hypothesize that female gender, younger age, less work experience, single marital status, and lack of family locally is associated with higher odds of burnout. We also hypothesize that perceived social support, and satisfaction with use of leisure time will help mitigate against burnout.

Methods

This study was conducted at a large tertiary hospital in Singapore, whose bed numbers make up a significant proportion of the total acute hospital beds in the public healthcare sector. In addition to patient care, the hospital also provides specialist and postgraduate training to AHPs, doctors and nurses. It has a staff strength numbering in the thousands, with a wide array of allied health specialities represented.

All healthcare workers from the hospital with corporate email access were invited to participate in our survey, conducted from 13 September 2022 to 12 March 2023. Our study questionnaire was hosted on a secure, online platform, Form SG (GovTech, Singapore) and distributed to all staff via email. The survey was written in English to avoid any literacy issues. Staff who lacked corporate email access were excluded from the study. Participants were informed that data collected would be fully anonymised. Participation in our survey was carried out on a voluntary basis. No financial incentives or compensation were provided to participants.

The present study is part of a larger study of burnout among HCWs in our hospital. Of the total number of HCWs who responded, we identified those working as AHPs e.g. social workers, physiotherapists, occupational therapists, speech therapists, and pharmacists for further analysis.

Survey instruments

The following survey instruments were utilized.

Oldenburg burnout inventory (OLBI)

OLBI is a 16-item validated burnout assessment tool encompassing 2 dimensions: Exhaustion and Disengagement.¹⁴ Each dimension consists of 8 items rated on a 4-point Likert scale, with a higher number of points indicating higher burnout response. Mean and standard deviation (SD) were calculated for each domain and compared across baseline participant characteristics. The sum of Exhaustion and Disengagement scores provided the total burnout score. Although the Maslach Burnout Inventory (MBI) is widely regarded as the standard in quantifying burnout,¹⁵ we used the OLBI instead because, in addition to measuring the affective component, OLBI also accounted for the physical and cognitive components of burnout. A previous study in Singapore also utilized the OLBI, and we felt that using the same inventory would be more conducive for data comparison in the local setting.

Patient health questionnaire-4 (PHQ-4)

PHQ-4 is a four-item survey whose responses are selected on a 4-point Likert-type scale.¹⁶ It measures the core symptoms of depression and anxiety. Summation of the scores of each of the 4 items provide the total score. Scores are categorized as normal (0–2), mild (3–5), moderate (6–8), and severe (9–12). Total score ≥3 for the first 2 questions indicates more of an anxiety presentation. Total score ≥3 for the remaining 2 questions proposes more of a depressive picture.

Brief perceived social support questionnaire (Fragebogen zur Sozialen Unterstützung Kurzform mit sechs Items: F-SozU K-6)

F-SozU K-6 is a valid, reliable, and economical instrument used to survey perceived social support outside of the workplace.¹⁷ Responses are rated on a 5-point scale ranging from 1 (not true at all) to 5 (very true), where higher scores indicate higher levels of support.

Demand-control-support questionnaire (DCSQ-17)

DCSQ-17 is a 17-item battery of questions quantifying employees’ perception of the demands, control/decision latitude, and social support inherent in their jobs.¹⁸ The demand subscale is made up of 5 items rated on a 4-point Likert scale. Items quantitatively evaluate psychological pressure such as the time, effort, and speed required to achieve a task. The control or decision latitude subscale consists of 6 items, evaluating cognitive abilities in the execution of occupation-related tasks and the degree of autonomy the staff has in deciding how to execute such tasks. The work- related social support subscale looks at access to available work-related social support and comprises 6 items rated on a 4-point Likert scale.

Leisure time satisfaction scale (LTS)

LTS is a scale to measure satisfaction with one’s leisure activities and comprises 6 items, with Likert-type response options from 0 (not at all) to 2 (a lot).¹⁹ The LTS shows excellent psychometric properties, including internal consistency, a single factor structure, and convergent validity.

Ethics approval

Ethics approval for the study was obtained from a centralised Institutional Review Board. Exemption of participant consent was granted, in view of the study being categorised as “Anonymous, Educational Tests, Surveys, Interviews or Observation.” (reference number 2002/2004).

Statistical analysis

Analyses were conducted using Stata version 17.0 (Stata Corp. 2021), and statistical significance was set as 2-sided 5% (p < 0.05). The internal and reliability consistency of the scales used were assessed via Cronbach Alphas and Confirmatory Factor Analysis (CFA), respectively. Descriptive statistics for normally distributed numerical variables were presented as mean (SD or standard deviation) and as median (range) for non-normally distributed numerical variables, and n (%) for categorical variables. Burnout was the primary categorical outcome. Logistic regression was used to determine the occurrence of burnout across all the factors, both for the univariate and multivariate analyses. Odds ratios and their respective 95% confidence intervals were reported.

Table 1 shows good reliability (Cronbach alpha of >0.7) and good internal consistency (comparative fit index of >0.9) except for the psychological demand and decision latitude subscales of the DCSQ-17. The OLBI also showed some suboptimal internal consistency.

Table 1.

Cronbach alphas & CFA goodness of fits.

Scale	Cronbach alphas (>0.7)	CFACFI (>0.9)
Burnout total	0.886	0.858
Leisure time	0.887	0.946
Perceived social support	0.903	0.950
PHQ total	0.886	0.978
Demand control support total
Psychological demand	0.578	0.778
Decision latitude	0.737	0.807
Social support	0.901	0.954

Results

136 AHP staff responded to the survey. Table 2 lists the demographic characteristics of the sample. Nearly 70% of the respondents were female, with about 65% under the age of 39 years. About 46% had worked less than 10 years in this hospital, 18% had lived in this country for less than 15 years, with about 10% having no immediate family living here. The single and the married personnel were of roughly equal proportions (49.3% vs. 47.8%).

Table 2.

Characteristics of the sample.

Variable	Allied health (n = 136)
Gender
Female	95 (69.9)
Male	37 (27.2)
Others	4 (2.9)
Working years
≤10 years	62 (45.6)
>10 years	74 (54.4)
Age (years)
20–29	35 (25.7)
30–39	53 (39.0)
40–49	26 (19.1)
50–59	13 (9.6)
60 and above	9 (6.6)
Immediate family in Singapore
No	14 (10.3)
Yes	122 (89.7)
Living in Singapore
≤15 years	24 (17.6)
>15 years	112 (82.4)
Marital status
Single	67 (49.3)
Married	65 (47.8)
Others	4 (2.9)
Burnout
Total	45.35 ± 7.57 27–60
Disengagement	22.14 ± 4.32 12–32
Exhaustion	23.21 ± 3.76 13–31
Disengagement ≥21.0	84 (61.8)
Exhaustion ≥22.5	79 (58.1)
Burnout yes (disengagement ≥21.0 and exhaustion ≥22.5)	70 (51.5)
PHQ
Normal	36 (26.5)
Mild	53 (39.0)
Moderate	28 (20.6)
Severe	19 (14.0)
Leisure time	4.57 ± 2.95 0–12
Perceived social support	28.43 ± 7.28 8–42
Demand control support
Psychological demand	15.29 ± 2.40 9–20
Decision latitude	14.49 ± 3.64 6–21
Social support	16.06 ± 3.93 7–24

Values are n (%), otherwise mean ± sd, range.

Table 3 displays the results of our study. Over half (51.5%) of AHPs met the criteria for burnout when taking into account the sum total of cut off scores of disengagement (≥21.0) and exhaustion (≥22.5). Those with higher psychological distress (as reflected by elevated PHQ-4 scores averaging moderate distress) had higher odds of experiencing burnout (p = 0.002).

Table 3.

Burnout multivariate predictors.

Variable	BurnoutExhaustion ≥22.5 & disengagement ≥21.0		Multivariate (with scales total)		Multivariate (with sub domains)
Variable	No66 (48.5%)	Yes70 (51.5%)	OR (95% CI)	p value	OR (95% CI)	p value
Gender
Male	19 (51.4%)	18 (48.6%)	1.0	—	1.0	—
Female	47 (49.5%)	48 (50.5%)	0.9 (0.2–4.1)	0.897	0.9 (0.2–4.1)	0.903
Others	0 (0.0%)	4 (100%)	NA	NA	NA	NA
Working duration, years
≤10 years	23 (37.1%)	39 (62.9%)	0.4 (0.1–2.4)	0.342	0.4 (0.1–2.4)	0.341
>10 years	43 (58.1%)	31 (41.9%)	1.0	—	1.0	—
Age, years
20–29	10 (28.6%)	25 (71.4%)	47.9 (2.5–928.2)	0.011	47.9 (2.5–928.2)	0.010
30–39	24 (45.3%)	29 (54.7%)	6.1 (0.7–51.8)	0.098	6.1 (0.7–51.7)	0.099
40–49	15 (57.7%)	11 (42.3%)	2.8 (0.3–23.3)	0.331	2.8 (0.3–23.4)	0.335
50–59	9 (69.2%)	4 (30.8%)	1.0	—	1.0	—
60 and above	8 (88.9%)	1 (11.1%)	1.0	—	1.0	—
Immediate family in Singapore
No	7 (50.0%)	7 (50.0%)	1.0	—	1.0	—
Yes	59 (48.4%)	63 (51.6%)	2.5 (0.2–39.3)	0.505	2.6 (0.2–40.2)	0.503
Living in Singapore, years
≤15 years	10 (41.7%)	14 (58.3%)	7.3 (1.2–45.7)	0.034	7.4 (1.1–47.2)	0.035
>15 years	56 (50.0%)	56 (50.0%)	1.0	—	1.0	—
Marital status
Single	28 (41.8%)	39 (58.2%)	0.7 (0.2–3.1)	0.664	0.7 (0.2–3.1)	0.672
Married	34 (52.3%)	31 (47.7%)	1.0	—	1.0	—
Others	4 (100.0%)	0 (0.0%)	1.0	—	1.0	—
PHQ
Total Mean (sd)	2.94 (2.4)	6.46 (3.2)	1.5 (1.2–1.9)	0.002
Depression Mean (sd)	1.24 (1.2)	2.96 (1.7)			1.5 (0.9–2.5)	0.152
Anxiety Mean (sd)	1.70 (1.4)	3.50 (1.7)			1.5 (0.9–2.5)	0.085
Leisure time Mean (sd)	5.97 (2.5)	3.26 (2.7)	0.9 (0.7–1.1)	0.266	0.9 (0.7–1.1)	0.268
Perceived social support Mean (sd)	30.80 (6.4)	26.20 (7.4)	1.03 (0.9–1.1)	0.532	1.03 (0.9–1.1)	0.531
Demand control support
Psychological demand Mean (sd)	14.50 (2.2)	16.04 (2.3)	1.01 (0.8–1.3)	0.929	1.01 (0.8–1.1)	0.933
Decision latitude Mean (sd)	15.70 (3.1)	13.34 (3.8)	0.9 (0.8–1.1)	0.352	0.9 (0.8–1.1)	0.351
Social support Mean (sd)	18.42 (3.0)	13.83 (3.4)	0.6 (0.5–0.8)	<0.001	0.6 (0.5–0.8)	<0.001

NA—not available due to zero counts.

Bold values indicate the P<0.05.

Multivariate analyses revealed that those aged between 20 and 29 years had higher odds of experienced burnout (p < 0.05). Living in Singapore for a duration of 15 years and under was significantly associated with burnout (p < 0.05).

There was no significant association between burnout scores and gender, marital status, number of years worked, or whether immediate family were living in this country (p > 0.05).

Similarly, there was no significant association between burnout scores and perceived social support and satisfaction with leisure time (p > 0.05). By contrast, those who had less social support at work scores were found to have higher odds of experiencing burnout (p < 0.001).

Discussion

Our findings that younger age was a significant predictor for burnout is not an isolated one. Several studies have shown that burnout scores were highest in HCWs below age 30.^20,21 It is possible that older staff could have suffered burnout and resigned from our hospital, thus excluding themselves from our study. Yet there were others who found that older workers showed less propensity for burnout, with the postulation that work experience could be a protective factor. Surveys of Australian psychologists and Polish physiotherapists have found that more years of working experience resulted in less burnout.^22,23 Similarly, a study of American social workers observed that older social workers tended to experience less burnout.²⁴

Historic data puts forward that females had higher incidences of burnout, and this might be potentially due to the differing social roles of men and women.^25,26 Traditionally, women face dual pressures of work and family compared to males, predisposing them to more burnout. However, such data could potentially be skewed since study respondents were mostly female. But in another study where 61% of the HCWs were male, more females still reported being burnt out compared to males.²⁷ Our data suggested that gender was not significantly associated with burnout, even with female respondents making up the bulk of the respondents. In our results, the prevalence of burnout was roughly 50% of the respondents, regardless of gender.

More years of living in Singapore was associated with lower odds of burnout. This could potentially be due to a higher likelihood of workers having more time and opportunities to integrate into local society and their respective professions with increased years of residing locally. Interestingly, our data showed that social support outside of the workplace did not seem to impact burnout significantly. This goes against the expectation that reduced social support leads to increased burnout, as one would assume that frequent interactions with family and friends should reduce burnout risks. This is despite previous research offering that social isolation and the removal of the supportive effects of family and friends could lead to more burnout.²⁸

Also, having more leisure satisfaction did not have a significant association with burnout rates, unlike some reports which suggested those who engaged in non-work activities, such as physical exercise had less occurrences of burnout.²⁹ Instead, our findings indicate that workplace support rather than external support made a greater impact over whether one ultimately suffered from burnout. This was supported by a nursing study whereby support in the workplace from supervisors and coworkers was found to play a fundamental role in preventing burnout.³⁰ Local factors could also help to explain our findings. International surveys and analyses highlight the disproportionate impact of working life on the average Singaporean. A study in 2022 ranked Singapore as the 4th most overworked city out of 100 cities analyzed.³¹ Another study ranked Singapore 10th out of 63 economies in 2021 for average working hours per year, where a higher rank equates longer working hours.³² Given the workplace’s outsized role locally, it is not surprising that workplace support seems to possess greater significance in moderating burnout over non-workplace support.

Perhaps our observations could also be influenced by our AHPs’ ability to utilize various support networks in the workplace. It was reported that workplace interventions that emphasize self-care, worker empowerment and access to mental health services had been found to decrease levels of psychological stress, anxiety and burnout in healthcare workers.³³ A workplace environment with such professional support had been shown to protect against both burnout, depression and anxiety.⁸

Our results suggested that those who had higher total PHQ scores had higher odds of experienced burnout, although it is not certain whether the depressive and anxiety symptoms contributing to higher PHQ scoring arose from being burnt out or stemmed from a pre-existing depressive or anxiety disorder. Studies have shown that HCWs who reported moderate to severe levels of burnout were almost 4 times more likely to have a history of depression.⁶ As such, it might be useful to pre-screen employees for a history of mood and anxiety disorders in order to identify those who might become vulnerable to relapse during times of stress and who might then require additional psychiatric or psychological support during such periods. However conducting such pre-screenings for all prospective and current employees may not always be feasible given logistical and resource constraints. Obtaining disclosure of personal health information would also have to be on a purely voluntary basis and there might be concerns of unwanted focus or discrimination against those with mental health struggles.

Limitations

There are certain limitations to our findings. The data obtained is from a cross-sectional survey, which leaves us unable to rule out reverse causality since temporal precedence cannot be established. Using longitudinal studies reduces recency bias but also face their own difficulties, such as respondents dropping out of the study over time, resulting in missing data. By software design, all our survey questions had to be answered before the questionnaire could be submitted. As such, we did not have to deal with the prospect of missing data.

Suboptimal reliability and internal consistency were evident in the subscales of the DCSQ, and to a lesser extent in the OLBI, and thus the results may be interpreted with a degree of caution. However, the subscales were retained as we felt content validity was still high, and the subscales were relevant to measure the psychological and cognitive aspects of work tasks contributing to burnout. The OLBI was retained as it provided useful measurement of the physical and cognitive components of burnout and has the potential for data comparison with other local studies.

Our study numbers were comparatively small compared to the total AHP strength in the hospital. 7.1% of AHPs at our tertiary institution took part in our survey (136 respondents from a population of 1903 total AHPs). Thus, views shared might not be a complete representation of the AHP population, and our study will suffer from some sampling bias. Our focus on AHPs was made post-hoc from a larger study across all HCWs in our hospital. This may introduce some secondary analysis bias. Overall, the generalization of this study to the wider AHP population is limited.

This study was confined to those with a corporate email account. Temporary staff might not have corporate email accounts and therefore this demographic may not have been adequately captured in our survey. Such temporary staff tend to be younger and have less working experience, and their exclusion may have potentially led to some underreporting of burnout in those who have spent shorter time in the workforce. However, temporary staff tend to be assigned less intensive and extensive job scopes and workloads compared to permanent staff. This theoretically reduces the potential stress and burnout they might face, which can offset underreporting of burnout.

There might also be some potential underreporting of burnout since those already struggling with time constraints and work pressures could be less willing to take the time to participate in the survey. However, their missed participation can be mitigated by those who were already grappling with burnout and were compelled to share their experiences when given a platform to do so.

Our study assumes AHPs to be one universal homogenous profession, but in reality, there is a myriad of AHP specializations with different job scopes. This study does not delve into how burnout and its predictors might differ across various allied health specialties e.g. Occupational Therapists (OTs), Pharmacists and Respiratory Therapists. For instance, OTs working in chronic care (e.g., rehabilitation, psychiatric institutions) had significantly higher levels of emotional exhaustion than community care and in hospital settings, and significantly higher depersonalization than community care OTs.²⁷ Respiratory Therapists might be at higher risk for burnout as their work tended to encompass critically ill patients in the Intensive Care or High Dependency Units, compared to Pharmacists who were comparatively deskbound. Thus, we acknowledge that without further subgroup analyses of a heterogenous AHP population, the relevance of our findings to each AHP subspeciality may be limited.

We did not ask for the exact professions of the subjects to reduce the number of identifying questions to keep responses as candid as possible. We tried to prune the number of survey questions to keep the length of the questionnaire shorter, as a longer response time might have discouraged participation. Incentives could have been given as compensation, but we omitted this to avoid introducing bias into the study.

Strengths

To the best of our knowledge, this study is one of the relatively few Singaporean studies to examine elements associated with burnout in the post-pandemic era, let alone in the AHP population. Our study provides deeper insight into the role of social determinants of burnout such as perceived social support and satisfaction with leisure time available, and the local availability of family, marital support and time spent in this locale. It also offers a comparison of whether workplace or domestic support is more protective against burnout.

Aggregating AHPs together as a group has a few advantages. It gives the authors the ability to aggregate a larger sample size and allows us to find out what are the common burnout predictors that transcend individual professions. Such a holistic view can reveal sector-wide trends, facilitating the formulation of broadly applicable interventions e.g. resilience training, mental health screenings or peer support programs that can benefit multiple AHP profession simultaneously. This also avoids the repetitive and prolonged process of reinventing solutions for each AHP subgroup.

Our study was performed during and after the gradual standing down from a pandemic posture. This provides a baseline for which subsequent studies on AHP stress and burnout can be measured against.

Conclusion

We have highlighted factors associated with burnout in a cohort of AHPs, with a perceived lack of workplace support a significant factor which needs to be addressed. There is also a potential need to implement individual and organizational interventions that target those at greatest risk for burnout, in particular younger AHPs, foreign staff and those exhibiting symptoms of anxiety and depression. The aim would be to improve mental health literacy i.e. teaching the staff to recognise these symptoms as well as signs of stress or burnout, and to encourage early help seeking from staff counselling, psychological and psychiatric services available in our hospital. Early detection of psychological problems and intervention will hopefully lead to reversal of the effects of stress and the restoration of healthy life of these individuals. Given the detrimental effects that burnout could have on patient care, it is essential to regularly monitor the level of psychological distress and burnout in our AHPs. Future research should focus on evaluating the effectiveness of work place interventions and to regularly monitor the mental health of our AHPs. Our work can also be used as a baseline to further delve into different AHP specialities and elucidate what predictors of burnout are unique to each of them.

Footnotes

ORCID iD

Gerard Michael Heng Yi Tong

Ethical considerations

Ethics approval for the study was sought from the SingHealth Centralised Institutional Review Board, which granted exemption of participant consent, in view of the study being categorised as “Anonymous, Educational Tests, Surveys, Interviews or Observation.” (reference number 2002/2004).

Author contributions

All authors listed above:

1. Have made substantial contributions to the design of this study, and acquisition and analysis of data used in this work.

2. Were involved in drafting the paper and revising it.

3. Have given their approval for this submission to be published and agreed to be accountable for the accuracy and integrity of this work.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data used to support the findings of this study are included within the article.*

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