Assessing validity and reliability of Copenhagen burnout tool and DASS-21 amongst faculty members

Abstract

BACKGROUND:

Various tools had been used to measure the level of burnout, anxiety, and depression. The Copenhagen Burnout Inventory assesses personal, work or job, and patient related burnout, whereas DASS21 assesses stress, anxiety, and depression.

OBJECTIVES:

This study aimed to evaluate the validity, reliability of Copenhagen burnout tool and DASS-21 amongst the faculty members employed in Pakistan.

METHODS:

This cross-sectional research incorporated 384 medical, dental, and nursing faculty working full time at university. Data for research was collected from January to May 2023. Copenhagen and DASS21 survey were the survey tools used to identify the level of burnout and stress. Reliability of both tools was assessed using Cronbach alpha. Confirmatory factor analysis was performed to detect factorial structure of both tools. Pearson correlation was conducted to detect association between various domains. Multiple logistic regression was computed to detect relationship between the domains.

RESULTS:

From a total of 384 participants, there were 118 (30.7%) males, 266 (69.3%) females. There were 169 (44%) medical, 140 (36.5%) dental, and 75 (19.5%) nursing faculty. Reliability analysis revealed satisfactory results for both tools. Confirmatory factor analysis demonstrated a four-model fit for the CBI, whilst a three-factor model was observed for DASS21. Personal burnout demonstrated positive and significant correlation with work related burnout, and stress, while it showed significant but negative correlation with depression.

CONCLUSION:

Female faculty displaced higher academic burnout as compared to men. A statistically significant correlation between burnout, anxiety, and depression. Both tools displayed high reliability and validity for the current sample.

Keywords

Anxiety burnout depression stress Pakistan

1. Introduction

Freudenberger used the term “burnout” for the first time in 1974 [1]. According to Peterson et al., this condition occurs due to continuous work stress and excessive energy, effort, and resource consumption, which over time produces a shift in psychological state. It is an extended emotional reaction after persistent psychologically stressful events at work [2]. Emotional weariness, depersonalization, and reducing personal effectiveness were characteristic features of burnout which Maslach outlined [3]. Professionals who experience this psychological reaction to stress report feeling less competent and successful; it is especially common among those having close human contact [4]. Since work-related burnout has been associated with unfavorable physiological and psychological issues including exhaustion, despair, and anxiety [5]. It has a negative impact on the performance of faculty which reduces their level of job satisfaction, decreases the level of engagement at work, increases their intention to resign, and lowers their quality of life [6].

Stress at work could lead to work-related burnout in an individual, at any level of employment, and in any occupation. Stress has become increasingly prevalent among university staff members worldwide [7]. High levels of anxiety and depression as well as low job satisfaction have been linked to work-related expectations, and negative coping strategies among staff members [8]. A study discovered that over five years, academicians, and non-academicians both reported significant rises in stress levels, with academicians reporting higher levels than non-academicians do. Gillespie et al. observed several variables related to workplace culture. These include inadequate resources and funding, excessive workloads, subpar management techniques, job insecurity, and inadequate compensation and recognition [9].

A number of tools, including the Copenhagen Burnout Inventory (CBI), Psychologist Burnout Inventory (PBI), the Pines’ Burnout measure (BM), the Maslach Burnout Inventory (MBI), and the Oldenburg Burnout Inventory (OLBI) have been designed to quantify burnout in epidemiological studies [10]. The most widely used instrument to gauge burnout to date is MBI [11]. However, the MBI’s items, dimensionality, and structure drew criticism. Researchers from low- and middle-income nations cannot access or afford the MBI because it is licensed and requires an application fee. Moreover, according to Kristensen et al. Copenhagen Burnout Inventory is a novel method for measuring burnout [12]. With acceptable validity and reliability, this tool allows the assessment of burnout in three subdimensions: client-related burnout (CB), work-related burnout (WB), and personal burnout (PB) [6]. Numerous research has confirmed the rate of burnout using CBI among health care workers and it has been translated into various languages [13, 14].

According to a recent scoping review, teachers’ rates of moderate-to-severe burnout ranged from 25 to 74%, while the rate of chronic stress ranged from 8.3 to 87% [15]. Numerous factors, including work-related factors which comprises years of teaching experience, class size, job satisfaction, and subject taught, as well as sociodemographic characteristics such as age, marital status, and genders, are said to have an impact on teachers’ stress and burnout [16]. A study executed at a Turkish institute involving 250 academicians demonstrated that 49.2% of them experienced anxiety [17]. Another research conducted on academic and non-academic staff in Malaysia showed that the incidence of stress was 5%, anxiety was 22.8%, while depression was 10.9% [18].

Previously various studies had been conducted in Pakistan, had assessed the stress levels within the health care professionals using MBI and DASS 21 scale [19, 20], some had only preferred to use DASS-21 scale for their analysis [21, 22]. Whereas, one study had used CBI and DASS21 scale, however this investigation did not evaluate the psychometric properties and the reliability of the CBI and DASS scale [23]. A study by Muzafar et al., had evaluated the anxiety levels within the medical students using CBI and observed overall reliability to be 0.87, which was considered to be satisfactory [24]. Moreover, mostly studies in Pakistan had evaluated the anxiety and stress levels within doctors, nurses, medical practioners and medical students. None of the prior studies had evaluated the psychometric properties within the medical, dental and nursing teaching faculty using CBI and DASS-21 scale. Hence, the current study aimed to evaluate the validity, reliability of Copenhagen burnout tool and DASS-21 amongst the faculty members in Karachi, Pakistan.

2. Materials and methods

2.1. Study type & sampling technique

This cross-sectional study was conducted amongst 384 faculty members, which included 169 medical, 140 dental, and 75 nursing faculty working at university from January to May 2023. Online questionnaires were formulated and were distributed to the faculty members through WhatsApp and emails. It required 15–17 minutes to fill in the survey forms. The participants were selected using the convenience sampling technique. Institutional ethical approval was obtained, which was according to declaration of Helsinki.

2.2. Inclusion and exclusion criteria

The inclusion criteria comprised for faculty members working full time, giving consent to participate in research, and providing complete information. Whilst the exclusion criteria included faculty members not providing complete information and unwilling to participate in research.

2.3. Research tools

2.3.1. Copenhagen burnout inventory (CBI)

Copenhagen Burnout Inventory (CBI) comprised of 19 questions, comprised of three domains, which included personal burnout, work-related and client related burnout [12]. The initial part of the questionnaire included demographic details of the participants, comprised of age, gender, field of work, years of experience, and sector of work. Personal burnout related questions included feeling tired, physically, or emotionally exhausted, feeling worn out, can’t take any more, and feeling unwell. Work related burnout included feeling emotionally exhausted and frustrated, tired at end of day, finding working hours tiring, while client related workout comprised of being tired, frustrated to work with clients, drains energy.

2.3.2. Depression, anxiety and stress scale (DASS-21)

DASS-21 helped compute the state of depression, anxiety, and stress among individuals [7]. Each of the three subdivisions comprised of seven questions. It consisted of three domains, which included stress, anxiety, and depression. Some of the questions included difficulty to work, getting agitated, nothing to look forward to, feels like about to panic, not worthy as a person, not enthusiastic about anything. The subscales include seven items using a scale of zero (did not apply to me at all) to three (applied most of the time). For each subscale, a total score was computed by using the sum of the 7 questions.

2.4. Reliability of tools

Reliability of CBI and DASS-21 was measured using the Cronbach’s alpha. The reliability of CBI was found to be 0.873 whilst for DASS-21 it was 0.855. Reliability for all subdivisions of both study tools had also been measured and displayed in Table 1.

Table 1.
Demographic details of the study participants.

Variable n %

Gender Male 118 30.73

Female 266 69.27

Age 26–30 146 38.02

35–40 56 14.58

41–45 182 47.40

Domain Dental 140 36.46

Medical 169 44.01

Nursing 75 19.53

Level of Education Bachelors 169 41.67

Doctoral 19 4.95

Master 205 53.39

Work experience Less than 5 years 138 35.94

5–10 years 107 27.86

11–20 years 139 36.20

Marital status Married 271 70.57

Single 113 29.43

Type of Job Government 191 49.74

Private 193 50.26

Variable		n	%
Gender	Male	118	30.73
	Female	266	69.27
Age	26–30	146	38.02
	35–40	56	14.58
	41–45	182	47.40
Domain	Dental	140	36.46
	Medical	169	44.01
	Nursing	75	19.53
Level of Education	Bachelors	169	41.67
	Doctoral	19	4.95
	Master	205	53.39
Work experience	Less than 5 years	138	35.94
	5–10 years	107	27.86
	11–20 years	139	36.20
Marital status	Married	271	70.57
	Single	113	29.43
Type of Job	Government	191	49.74
	Private	193	50.26

2.5. Sample size calculation

The sample size for the current investigation was computed using Openepi software. At confidence interval of 95%, with 5% margin of error, the required sample size for the study was calculated to be 384 participants.

2.6. Statistical analysis

Data was analyzed using SPSS version 26. Reliability of the study tools was evaluated using Cronbach alpha. Descriptive statistics comprised of mean and standard deviation. Construct validity was evaluated using the exploratory factor analysis. Factor analysis also revealed Eigen values for each variable. Pearson correlation determined the level of correlation between the domains of Copenhagen and DASS21. Multiple logistic regression was also computed which demonstrated relationship between the subdivisions of both tools.

3. Results

Table 1 showed that the study sample comprised of 384 participants, which comprised of 118 (30.7%) males, 266 (69.3%) females. Regarding the age of participants, there were 146 (38%) within the age range of 26–30 years, 56 (14.6%) from 35–40 years, and 182 (47.4%) fro, 41–45 years of age. There were 169 (44%) medical, 140 (36.5%) dental, and 75 (19.5%) nursing faculty. There were 205 (53.4%) faculty with master’s education, 160 (41.7%) Bachelors and 19 (4.9%) Doctorate. The faculty having 11–20 years’ experience were 139(36.2%), 107 (27.9%) faculty had 5–10 years of experience, 138 (35.9%) had less than 5 years of experience. (Table 1)

Table 2 determined the reliability of the Copenhagen scale using Cronbach alpha, which was found to be 0.873 whilst for DASS-21 it was 0.855. Reliability for the subdivisions of Copenhagen and DASS 21 was also analyzed. (Table 2)

Table 2.
Reliability analysis of domains of Copenhagen and DASS 21 scales.

Variable Cronbach’s alpha

Domains Copenhagen Scale 0.873

Personal burnout 0.866

Work burnout 0.855

Client related burnout 0.898

Domains DASS 21 0.855

Anxiety 0.885

Depression 0.826

Stress 0.854

	Variable	Cronbach’s alpha
Domains	Copenhagen Scale	0.873
	Personal burnout	0.866
	Work burnout	0.855
	Client related burnout	0.898
Domains	DASS 21	0.855
	Anxiety	0.885
	Depression	0.826
	Stress	0.854

Table 3 demonstrates the factor analysis, which had been conducted for both Copenhagen burnout scales. Four Eigen values greater than 1 have been identified. The factor loading has been identified for all the questions asked by the faculty using this tool. (Table 3)

Table 3.

Factor analysis of Copenhagen scale.

Variables	1	2	3	4
How often do you feel tired?	–0.008	0.337	0.108	–0.263
How often are you physically exhausted?	–0.044	0.759	0.341	–0.204
How often are you emotionally exhausted?	0.135	0.546	0.188	–0.198
How often do you think: I can’t take it anymore	–0.127	0.351	0.401	–0.26
How often do you feel worn out?	–0.145	0.589	0.542	–0.03
How often do you feel weak and susceptible to illness?	–0.139	0.868	0.237	–0.105
Is your work emotionally exhausting	–0.566	0.405	–0.305	0.336
Do you feel burnt out because of your work?	–0.267	0.306	0.477	0.532
Does your work frustrate you?	–0.628	0.427	0.13	0.163
Do you feel worn out at the end of the working day?	–0.229	0.09	0.509	0.057
Are you exhausted in the morning at the thought of another day at work?	0.538	0.45	0.245	–0.072
Do you feel that every working hour is tiring for you?	0.544	0.08	0.28	–0.259
Do you feel that every working hour is tiring for you?	0.117	0.497	0.588	0.253
Do you have enough energy for family and friends during leisure time?	0.255	–0.143	–0.454	0.018
Do you find it hard to work with patients?	–0.051	0.524	–0.235	0.527
Do you find it frustrating to work with patients?	0.139	0.174	–0.407	0.645
Does it drain your energy to work with patients	0.166	0.475	–0.365	0.459
Do you feel that you give more than you get back when you work with patients?	0.075	0.77	–0.125	–0.184
Are you tired of working with patients?	0.094	0.642	–0.277	0.366
Do you wonder how long will be able to continue working with patients?	–0.063	0.155	–0.625	0.337

Extraction Method: Principal component analysis, Rotation Method, Varimax.

Table 4 exhibits the factor analysis, using DASS-21. Three Eigen values greater than 1 had been assessed, using the factor loading had been identified for all the questions using this tool. (Table 4)

Table 4.

Factor analysis of DASS21 scale.

Variables	1	2	3
I found it hard to wind down	0.175	0.453	–0.111
I was aware of dryness of my mouth	0.323	0.24	–0.488
I couldn’t seem to experience any positive feeling at all	0.624	0.257	–0.306
I experienced breathing difficulty	0.417	0.427	–0.257
I found it difficult to work up the initiative to do things	0.744	–0.362	–0.119
I tended to over–react to situations	0.264	0.11	–0.181
I experienced trembling (e.g. in the hands)	0.22	–0.409	0.28
I felt that I was using a lot of nervous energy	0.077	–0.525	0.472
I was worried about situations in which I might panic and make a fool of myself	0.426	–0.095	0.203
I felt that I had nothing to look forward to	0.721	–0.016	0.326
I found myself getting agitated	0.567	0.014	0.125
I found it difficult to relax	0.465	–0.535	0.458
I felt downhearted and blue	0.764	–0.306	0.083
I was intolerant of anything that kept me from getting on with what I was doing	0.594	–0.092	0.478
I felt I was close to panic	0.814	0.028	0.082
I was unable to become enthusiastic about anything	0.607	0.114	–0.234
I felt I wasn’t worth much as a person	0.765	0.089	–0.137
I felt that I was rather touchy	0.174	0.27	0.526
I was aware of the action of my heart in the absence of physical exertion	0.828	–0.034	0.041
I felt scared without any good reason	0.33	0.553	–0.176
I felt that life was meaningless	0.309	0.65	–0.075

Extraction Method: Principal component analysis, Rotation Method, Varimax

Table 5 demonstrated correlation between DASS and Copenhagen scale. Personal burnout demonstrated positive and significant correlation with work related burnout, and stress, while it had significant but negative correlation with depression. Work related burnout also had positive and significant correlation with client related burnout and stress. Client related burnout exhibited positive but significant association with anxiety and stress, while it had negative correlation with depression. Anxiety was also positively correlated with depression and stress. Lastly, depression was also positively linked to stress. (Table 5)

Table 5.

Correlation between domains of Copenhagen and DASS21.

	Personal	Work	Client	Anxiety	Depression	Stress
Personal burnout	1	.587^**	0.042	–0.001	–.130*	.195^**
Work burnout	.587^**	1	.130*	–0.092	0.069	.168^**
Client related	0.042	.130^*	1	.320^**	–.189^**	.383^**
Anxiety	–0.001	–0.092	.320^**	1	.187^**	.626^**
Depression	–.130^*	0.069	–.189^**	.187^**	1	.467^**
Stress	.195^**	.168^**	.383^**	.626^**	.467^**	1

^**Correlation is significant at the 0.01 level (2–tailed). ^*Correlation is significant at the 0.05 level (2–tailed).

Table 6 showed multiple linear regression analysis conducted amongst the various domains of Copenhagen and DASS21. Standardized as well as the non-standardized regression coefficients (β), along with 95% of the confidence interval and associated p-values demonstrating the level of significance for each of the variables had been analyzed. Domains from Copenhagen scale which comprised of personal, work and client related had been taken as dependent variable, while anxiety, stress, and depressions were counted as independent variables. Association of personal burnout with anxiety revealed B = –8.13, 95% CI = –11.957 to –4.303, β= –0.258, p < 0.001; with depression B = –7.69, 95% CI = –10.28 to –5.101, β= –0.318, p < 0.001; between stress and personal burnout, it was seen that B = 13.597, 95% CI = 9.962 to –17.232, β=0.505, p < 0.001. Relationship between work related burnout and anxiety was characterized by B = –9.231, 95% CI = –12.671 to –5.791, β= –0.334, p < 0.001; with stress it was B = 9.549, 95% CI = 6.282 to 12.816, β=0.405, p < 0.001. Whereas between client related burnout and depression it was seen that B = –13.281, 95% CI = –16.003 to –10.559, β= –0.464, p < 0.001; association between client related burnout and stress was noted to be B = 18.11, 95% CI = 14.29 to 21.93, β=0.568, p < 0.001. (Table 6)

Table 6.

Multiple linear regression for the domains for CBI and DASS.

		Unstandardized		Standardized	t	p	95% Confidence
		Coefficients		Coefficients			Interval
		B	Std. Error	Beta			Lower Bound	Upper Bound
Personal	Anxiety	–8.13	1.946	–0.258	–4.177	<0.001^**	–11.957	–4.303
Burnout	Depression	–7.69	1.317	–0.318	–5.839	<0.001^**	–10.28	–5.101
	Stress	13.597	1.849	0.505	7.355	<0.001^**	9.962	17.232
Work	Anxiety	–9.231	1.749	–0.334	–5.277	<0.001^**	–12.671	–5.791
Burnout	Stress	9.549	1.662	0.405	5.747	<0.001^**	6.282	12.816
Client	Depression	–13.281	1.384	–0.464	–9.595	<0.001^**	–16.003	–10.559
Burnout	Stress	18.11	1.943	0.568	9.321	<0.001^**	14.29	21.93

a. Dependent Variable: Personal, work and client related burnout.

4. Discussion

According to study by Tran et al., it was identified that chronic stress is a leading factor responsible for causing burnout, which could be due to mental and physical exhaustion [6]. Findings from the current investigation showed that about 54% of the faculty suffered from anxiety, 44% from depression while nearly 60% were stressed. A survey conducted on university faculty revealed that 69% of the faculty had displayed signs of stress, while 55% of faculty members had seriously contemplated retiring at an early age [25]. Supporting faculty members suffering from work-related stress is essential as employment-related stress usually corresponds to higher chances of cardiovascular disease (CVD) and psychological disorders [26]. Moreover, females had higher burnout as compared to men. Findings from a prior study showed that female instructors showed lower levels of depersonalization but more emotional weariness and work-related stress (particularly emotional demands and work– family conflict) than did male educators. Regarding gender disparities in the workplace, there could be a variety of causes. First, when it comes to coping mechanisms, males engage in more physical activities than females. Second, females exhibit higher levels of attachment with their jobs, which could be responsible for higher stress, and burnout [27]. Stress can also be driven by more responsibilities at home for the family.

The reliability analysis for the Copenhagen burnout scale was determined to be 0.873, which was considered satisfactory, likewise the reliability for DASS21 was also satisfactory (0.855). Reliability with respect to domains for Copenhagen also demonstrated good reliability and was found to be 0.866 in personal burnout, in work related burnout it was 0.855, and in client related burnout it was 0.898. Our findings are comparatively like a Vietnamese study, where reliability for PB was 0.91, which was higher than our study; in work related it was 0.87 which was nearly identical to our findings; whilst for client related, they observed 0.88, which was also showed comparable findings [28]. Whereas reliability for DASS 21 domains showed that reliability for anxiety was 0.885, while 0.826 and 0.854 was observed for depression and stress. Similar findings have been reported by a previously conducted study, where nearly the same reliability was observed for each domain [29]. Hence this identifies reliability and validity regarding the use of this scale in our sample participants.

Various studies had analyzed psychometric properties of these study tools using exploratory factor analysis. A Serbian version of the CBI was used by Todorovic et al. to test the instrument’s reliability in assessing burnout among Serbian medical students. After applying EFA to the CBI, the study verified that presence of three factors and showed a strong degree of association [30]. Another study carried out on Portuguese doctors; authors observed three factors model to be a suitable fit. The average variance extraction results indicated that all three factors had strong discriminant validity, except the component related to work and personal burnout. This may imply an association between some work-related and personal factors that contributes to burnout. [31]. Likewise, an Italian study had also observed three factors to be a suitable fit in their analysis [32]. In the current study, in contrast with earlier mentioned studies four factor models were identified to be most suitable. Mahmood et al., also observed four factors to be good fit for their model, however authors had subdivided work-related domain into two divisions [33]. Moreover, in our study, most of the faculty reported higher work-related burnout such as being tired at the end of the day. This could be because faculty must deal with students and constant teaching load in addition to the administrative workload tends to affect the mental health of the faculty members teaching in various disciplines.

Three-factor solutions, along with two-factor solutions have been identified by previous studies examining the DASS-21 factor structure. Nevertheless, to obtain excellent fit estimates, each of these models underwent some adjustments [34]. A study by Daza et al., observed two factor models, authors in their research had placed stress and anxiety items together to formulate a single factor which was termed as anxiety-stress factor, which improved their model [35]. Investigations which had observed three factor model also made changes in their models for instance using cross loadings to achieve best fit for their study [36]. Likewise in our study three factor model was observed to be a great fit in our study. Comparable to our findings, a three-factor model was described by a study conducted in the USA. This study identified three factor models to be ideal fit in their study [34].

Correlation between the subdivisions of Copenhagen burnout and DASS21 scale revealed statistically significant association. Personal and client related workload showed significant correlation with stress and depression. Work related burnout showed association with stress only. A study conducted on nine state universities in India reported a positive correlation between burnout and work-related stress on the faculty members [37]. Another Iranian study performed on health care workers showed that, 54% of participants had at least one mental illness. Stress, anxiety, and depression rates were 40.3%, 42.9%, and 42.6%, respectively. Overall, the analysis showed that participants experienced greater rates of stress, anxiety, and depression as compared to other nations [38]. Regardless of the form of stress participants faced at work, those who had access to work assistance showed lower rates of depression. This demonstrates the fact that positive encouragement and support from managers and peers may help reduce depressive and hopeless feelings [39]. Another study was conducted on nurses which aimed to identify their stress level and its association with their job performance. This study demonstrated that only 10% of nurses had taken leave from work, and lower stress levels were identified. Hence, the study concluded that higher professional support should be encouraged for the workers along with introduction of various educational programs, coping strategies, and interventions to promote social and emotional support, which could have a greater impact on lowering the number of absenteeism and enhances the staff/faculty performance. One other element that could be utilized to lower absenteeism from work is financial incentives [40].

Using a multivariate linear model to examine the relationship between the domains of CBI and DASS21, we found significant correlation between personal burnout and stress, anxiety, and depression. Most of the faculty demonstrated personal burnout which was significantly linked with stress and anxiety. Similarly various previously conducted studies had revealed significantly greater burnout scores, notably for depersonalization, emotional tiredness, and intellectual burnout [41, 42]. Work-related burnout has been linked with stress and anxiety, which could be attributed to certain personal and professional elements. For instance, young educators are more likely to be excited regarding their employment, while experienced faculty members could get bored and grow more exhausted over the period of time. One study found that teachers with the low (0–5) years of experience had the lowest prevalence of burnout, which is consistent with this theory [43]. Teachers may experience a transition from work-related stress to depressive symptoms, and a poor work environment has also been linked to increased anxiety and depression symptoms. With more work to do and longer work hours, teachers will inevitably face more demand for their services, which will raise stress levels and eventually cause anxiety and depression [44].

4.1. Limitations

The current study had few limitations. Study participants may have varying understandings and could have reported their responses based on their psychological states as of the self-reported approach had been used. Secondly convenience sampling technique was used to collect data, for the faculty teaching at a single institute in Pakistan, hence findings cannot be generalized. Thirdly, faculty members from certain domains were involved in the current analysis from a university, hence these findings could not be generalized.

4.2. Recommendations

Burnout is a complex reaction to pressures at work. Healthcare professionals overlook their own physical, mental, social, and emotional well-being due to a sense of duty to the community. Effective methods to reduce burnout involve scheduling work more effectively, encouraging self-management, teaching physical, mental, and emotional self-care, and implementing stress reduction mindfulness activities. Other successful approaches include organizing one-to-one support meetings, offering counsel, and provide support groups [45].

5. Conclusion

It can be concluded that female faculty members displaced higher academic burnout as compared to men. More than half of the study participants suffered from stress, anxiety, depression, and had work related burnout. A statistically significant correlation between burnout, anxiety, and depression. Both tools displayed high reliability and validity for the current sample. A four-factor model was identified as ideal fit using CBI, while three-factor model was suitable in case of DASS21.

Footnotes

Acknowledgments

We are grateful to the faculty members for helping with the process of data collection.

Ethical considerations

Ethical approval was obtained from institutional ethical review committee of Women Medical and Dental College (81/2023) before this study was initiated.

Informed consent

All participants gave consent before they filled the forms. All the information obtained was kept anonymous.

Conflict of interest

The authors have no conflicts of interest.

Funding

None.

Author contributions

Xiaomeng Sun: Critically reviewed the Manuscript, data analysis.

Beenish Fatima Alam: Manuscript writing, study design, and interpretation.

Muhammad Aamir Ghafoor Chaudhary: writing manuscript, data interpretation and analysis.

Summara khan: Data collection, designed data analysis, methodology.

Amna Khan: Data collection, applying for ethical approval.

Hassan Jan: data collection, interpretation of results.

Talib Hussain: applying institutional review, applying statistical analysis.

Shahid Khan: critically reviewed manuscript, supervised the study.

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Assessing validity and reliability of Copenhagen burnout tool and DASS-21 amongst faculty members

Abstract

BACKGROUND:

OBJECTIVES:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1. Study type & sampling technique

2.2. Inclusion and exclusion criteria

2.3. Research tools

2.3.1. Copenhagen burnout inventory (CBI)

2.3.2. Depression, anxiety and stress scale (DASS-21)

2.4. Reliability of tools

2.6. Statistical analysis

3. Results

Table 2. Reliability analysis of domains of Copenhagen and DASS 21 scales. Variable Cronbach’s alpha Domains Copenhagen Scale 0.873 Personal burnout 0.866 Work burnout 0.855 Client related burnout 0.898 Domains DASS 21 0.855 Anxiety 0.885 Depression 0.826 Stress 0.854

4.1. Limitations

4.2. Recommendations

5. Conclusion

Footnotes

Acknowledgments

Ethical considerations

Informed consent

Conflict of interest

Funding

Author contributions

References

Table 2.
Reliability analysis of domains of Copenhagen and DASS 21 scales.

Variable Cronbach’s alpha

Domains Copenhagen Scale 0.873

Personal burnout 0.866

Work burnout 0.855

Client related burnout 0.898

Domains DASS 21 0.855

Anxiety 0.885

Depression 0.826

Stress 0.854