- Email: [email protected]
Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis
Journal Pre-proof Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis
Renzo Bianchi PII:
S0022-3999(19)31239-5
DOI:
https://doi.org/10.1016/j.jpsychores.2020.109954
Reference:
PSR 109954
To appear in:
Journal of Psychosomatic Research
Received date:
29 December 2019
Revised date:
23 January 2020
Accepted date:
3 February 2020
Please cite this article as: R. Bianchi, Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis, Journal of Psychosomatic Research(2019), https://doi.org/10.1016/ j.jpsychores.2020.109954
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© 2019 Published by Elsevier.
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis
Renzo Bianchi, Ph.D. [email protected]
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Institute of Work and Organizational Psychology, University of Neuchâtel, Neuchâtel, NE, Switzerland
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Corresponding author: Renzo Bianchi, Institute of Work and Organizational Psychology, University of Neuchâtel, Émile-Argand 11, 2000 Neuchâtel, NE, Switzerland. Tel: +41 32
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718 1390; fax: +41 32 718 1391. Email: [email protected]
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Conflicts of interest
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None declared.
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Sources of funding
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None declared.
Acknowledgements
The author thanks Noémie Pasquier for her help with data collection.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Abstract Objective. To date, the issue of burnout-depression overlap remains contentious. In this study, we examined whether burnout symptoms form a syndrome that is distinct from depression. Methods. The study involved 332 employed individuals (65% female; mean age: 34). Burnout symptoms were assessed with the Shirom-Melamed Burnout Measure (SMBM). The SMBM operationalizes burnout based on three interconnected components, namely,
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physical fatigue, cognitive weariness, and emotional exhaustion. Depressive symptoms were
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assessed with the PHQ-9, a scale that covers the main manifestations of major depression.
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Confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) bifactor analysis were conducted. Results. On average, the factors underlying burnout’s
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components correlated more strongly with the Depressive Symptom factor than with each
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other. Remarkably, such results were obtained even when fatigue-related items were excluded from the depression scale. Second-order CFA revealed that the factors underlying burnout’s
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components and the Depressive Symptom factor were reflective of the same higher-order
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factor. ESEM bifactor analysis indicated that the general factor accounted for about 2/3 of the
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common variance extracted. Conclusion. Consistent with a growing corpus of research, this study suggests that the burnout-depression distinction is untenable. Because the burnoutdepression distinction tends to convey the idea that burnout is not as serious a problem as depression, many people struggling with depression might underestimate the gravity of their condition and not seek help when self-identifying as “burned out.” Maintaining a line of demarcation between burnout and depression may thus be problematic from both a scientific and a health standpoint. Keywords: bifactor analysis; burnout; confirmatory factor analysis; fatigue; occupational health.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis 1. Introduction Burnout has been regarded as a syndrome in which the individual is left exhausted and demotivated by a long-term confrontation with insurmountable job stress [1,2]. Although burnout has elicited growing interest among occupational health specialists over the last
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decades, the nature of the syndrome and (discriminant) validity of the construct remain strongly debated [3,4]. To date, there is no established diagnosis for burnout and burnout is
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not nosologically recognized by either the American Psychiatric Association or the World
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Health Organization [5,6]. A major object of controversy in burnout research concerns the
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extent to which burnout refers to anything other than a depressive condition [3,4]. Depression is primarily characterized by anhedonia and dysphoric mood, with fatigue
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and loss of energy constituting common presenting complaints in affected patients [5]. At an
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etiological level, depressive symptoms have been identified as basic responses to unresolvable
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stress in human beings (and mammals in general) and are considered basic signals of a discrepancy between positive, rewarding experiences on the one hand, and negative, punitive experiences on the other hand [7-9]. While depression is nosologically characterized and diagnosable [5], it is best viewed as a dimensional variable [10]. Depressive symptoms thus vary in intensity, frequency, and pervasiveness along a continuum, with depressive disorders representing only a portion of that continuum―its high end [3,11]. Theoretically speaking, because (a) depressive symptoms constitute basic responses to unresolvable stress (either job-related or not) and (b) burnout is supposed to result from insurmountable job stress, the reason for expecting burnout to fall outside, rather than inside, the spectrum of depression is unclear [3]. On a related note, when burnout and depression are
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION both approached dimensionally, the continua of the two entities mirror one another (Figure 1), rendering the burnout-depression distinction―including the distinction between full-blown burnout and clinical depression―difficult to articulate [3,11,12]. It is worth underlining that the job-related character of burnout has often been regarded as a key distinctive feature of the phenomenon [2,4]. However, because burnout could be both job-related and depressive in nature, the discriminant value of the “job-relatedness” argument is open to question [3,13]. Depressive symptoms can emerge and develop in the work context―in response to
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occupational stressors―before potentially impregnating larger areas of an individual’s life
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[12].
Substantiating the abovementioned concerns, the burnout-depression distinction has
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been increasingly called into question on empirical grounds [3]. Burnout has been found to
processing
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overlap with depression in terms of: (a) primary symptoms and causes [13-15]; (b) cognitive of emotional information
(e.g.,
biased
memorizing in favor of negative
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information, negative interpretation of ambiguous information) [16-19]; (c) dispositional
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correlates and risk factors (e.g., neuroticism, history of anxiety and depressive disorders) [20-
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22]; and (d) prescribed treatments (e.g., antidepressant medication) [23-25]. A recent metaanalytic study, however, concluded that while burnout and depression were substantially associated with one another, the size of the association remained compatible with the view that the two constructs are distinct [26]. In addition, it has been argued that the presence of fatigue-related items in both burnout and depression scales may have “inflated” the burnoutdepression association [4,26]. Although the validity of this argument is not beyond question [27], the extent to which the strength of the burnout-depression association can be imputed to content overlap at the level of fatigue-related items requires further clarification [14]. Overall, more research has been called for before definite conclusions can be envisaged regarding the distinctiveness of burnout vis-à-vis depression [4]. 4
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION In the present study, the issue of burnout-depression overlap was addressed through an examination of the unity of burnout as a syndrome. By definition, a syndrome refers to a combination of co-occurring symptoms characterizing a given entity [5, 28]. On this basis, it was reasoned that, if burnout constitutes a syndrome that is distinct from depression, then burnout symptoms should combine with each other rather than with depressive symptoms. That burnout’s components be more strongly linked to each other than to any aspect of depression has been considered crucial to establishing the discriminant validity of the burnout
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construct [29]. Despite its importance, this aspect of burnout’s distinctiveness has received insufficient attention thus far. The earlier mentioned meta-analysis, for instance, did not
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compare the correlations between burnout and depression to the correlations among burnout’s
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components [26]. Clarifying whether burnout is well characterized when separated from
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depression is key to our ability to assess, prevent, and treat burnout effectively.
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*********************************************
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PLEASE INSERT FIGURE 1 ABOUT HERE
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********************************************* 2. Methods
2.1. Study sample and recruitment procedure Participants were recruited in Switzerland in June and July 2016 through contacts with Swiss organizations in both the public and the private sector as well as through advertisements in social media. Our participation request contained a brief description of the study (e.g., general topic, targeted population, expected duration) and a weblink allowing individuals to complete the study. The organizations were free to forward our request to their employees or to ignore it. The only eligibility criterion for participating in the study was to be currently employed. Employed individuals were thus invited to participate whether experiencing job stress or not. 5
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Participation was voluntary. Confidentiality was guaranteed to each respondent. Individual consent was requested. The study was conducted in accordance with the ethical standards of the institutional review board of the University of MASKED FOR REVIEW. 2.2. Measures of interest Burnout symptoms were assessed with the Shirom-Melamed Burnout Measure (SMBM) [1,2]. The SMBM is an explicitly work-contextualized questionnaire. The SMBM divides
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burnout into three components, namely, physical fatigue (six items; e.g., “I feel physically
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drained”; Cronbach’s α = 0.90), cognitive weariness (five items; e.g., “I feel I am not focused
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in my thinking”; Cronbach’s α = 0.90), and emotional exhaustion (three items; e.g., “I feel I
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am not capable of investing emotionally in coworkers and recipients”; Cronbach’s α = 0.81). It is noteworthy that the physical fatigue subscale of the SMBM refers to a general kind of ill-
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being at work (e.g., “I feel fed up”; “I feel burned out”) as much as it refers to actual physical
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fatigue. The cognitive weariness subscale of the SMBM homogeneously gauges cognitive
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impairment (e.g., attentional problems, difficulties in reasoning). The emotional exhaustion subscale of the SMBM deals with burnout symptoms at an interpersonal level. Participants
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were asked to indicate how they felt over the previous two weeks. They responded using a 4point rating scale, from 0 for not at all to 3 for nearly every day. The SMBM is a measure of reference in burnout research [1,2]. Scores on the SMBM correlate almost perfectly (disattenuated correlations around .90) with scores on the core dimension of the Maslach Burnout Inventory (MBI)-General Survey, another popular measure of burnout [1,29]. By contrast with the MBI, however, the SMBM is in the public domain and reflects a theorydriven approach to burnout [1]. Depressive symptoms were assessed with the PHQ-9 [30], a scale that covers the main manifestations of major depression as referenced in the latest edition of the Diagnostic and Statistical Manual of Mental Disorders [5]. The PHQ-9 thus allows for the assessment of 6
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION anhedonia, depressed mood, sleep disturbance, fatigue/loss of energy, appetite alteration, guilt/worthlessness, concentration impairment, psychomotor malfunction, and thoughts of self-harm. In addition, the PHQ-9 enables the investigator to establish a provisional diagnosis of major depression based on a dedicated algorithm [30]. The response frame used with the PHQ-9 was identical to the response frame used with the SMBM. Cronbach’s α for the PHQ9 was 0.83.
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2.3. Data analyses Data were analyzed principally within a factor analytic framework, using Mplus 8 [31]. The
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items were treated as ordinal. The weighted least squares—mean and variance adjusted—
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(WLSMV) method was employed. Goodness of fit was assessed based on five complementary indices: The Root Mean Square Error of Approximation (RMSEA), the Comparative Fit
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Index (CFI), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual
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(SRMR), and the Weighted Root Mean Square Residual (WRMR).
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First, a four-factor confirmatory factor analysis (CFA) was conducted. Latent Physical
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Fatigue, Cognitive Weariness, and Emotional Exhaustion factors were created based on the items belonging to the original subscales of the SMBM and a latent Depressive Symptom factor was created based on the items belonging to the PHQ-9. The aim of this CFA was to examine the correlations among the latent factors attached to the measures of burnout and depression. A second-order model was then tested, in which the latent Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors were defined as firstorder factors. The goal was to examine whether the latent factors attached to the measures of burnout and depression could be considered reflective of the same overarching factor.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Third, an exploratory structural equation modeling (ESEM) bifactor analysis with partially specified target rotation (PSTR) was conducted [32]. The logic of PSTR is highly similar to that of CFA. However, by contrast with CFA, in which loadings are forced to equal zero, PSTR extracts factors and then attempts to match the target as well as possible. In the specification employed, all items were allowed to load on the general factor and each item was allowed to load on a bifactor that was specific to the scale or subscale to which the item belonged. For instance, a PHQ-9 item would load on the general factor as well as on a PHQ-9
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bifactor. Because four (sub)scales were submitted to examination (the PHQ-9 and the three SMBM subscales), four bifactors were considered in addition to the general factor. The mean
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item loading on the general factor as well as the explained common variance (ECV) and
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omega hierarchical (omegaH) indices were computed. ECV is an index of the proportion of
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the common variance extracted that is explained by the general factor [33,34]. OmegaH is an index of total score reliability [34]. The state of the art suggests that “when omegaH is high (>
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.80), total scores can be considered essentially unidimensional, in the sense that the vast
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majority of reliable variance is attributable to a single common source” [33].
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In view of the claim, made by some investigators [4,26], that the burnout-depression association may be driven by content overlap at the level of fatigue-related items, the CFAs were re-run with three fatigue-related items deliberately excluded from the PHQ-9 (items 3 [sleep disturbance], 4 [fatigue/loss of energy], and 7 [concentration impairment]). Such a procedure allowed for a more “conservative” approach to the burnout-depression association. 3. Results A total of 332 participants, employed in various occupational domains (e.g., human resources, education, healthcare), were enrolled in the present study (65% female; mean age: 34). Participants’ mean length of employment in their current occupation was 7 years. Descriptive statistics pertaining to the PHQ-9 and SMBM items (e.g., range, skewness, kurtosis) are 8
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION available in Supplementary Material 1. About 9% of the participants (n = 31) met the criteria for a provisional diagnosis of major depression in the study sample. The first CFA, in which the nine items of the PHQ-9 were allowed to load on a Depressive Symptom factor, the six items of the SMBM’s physical fatigue subscale were allowed to load on a Physical Fatigue factor, the five items of the SMBM’s cognitive weariness subscale were allowed to load on a Cognitive Weariness factor, and the three items
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of the SMBM’s emotional exhaustion subscale were allowed to load on an Emotional
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Exhaustion factor showed an acceptable fit: RMSEA = 0.073 (90% confidence interval [CI]:
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0.066-0.079); CFI = 0.959; TLI = 0.954; SRMR = 0.074. The four factors strongly correlated with each other (from 0.59 to 0.89; see Table 1). The three latent burnout factors correlated
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less strongly with each other―0.63 on average―than with the Depressive Symptom
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factor―0.76 on average.
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*********************************************
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PLEASE INSERT TABLE 1 ABOUT HERE
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********************************************* The second-order model involving the Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors as first-order factors fit the data satisfactorily: RMSEA = 0.072 (90% CI: 0.065-0.079); CFI = 0.960; TLI = 0.955; SRMR = 0.075. All first-order factors loaded substantially on the higher-order factor―from 0.66 for the Emotional Exhaustion factor to 0.98 for the Depressive Symptom factor (0.84 on average; Figure 2). ********************************************* PLEASE INSERT FIGURE 2 ABOUT HERE
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION ********************************************* The bifactor model (Table 2) showed an excellent fit: RMSEA = 0.036 (90% CI: 0.025-0.047); CFI = 0.993; TLI = 0.988; WRMR = 0.460. All PHQ-9 and SMBM items loaded substantially on the general factor―from 0.50 to 0.87 (M = 0.67). OmegaH was .86. The items of the PHQ-9 and physical fatigue and cognitive weariness subscales of the SMBM loaded on average more strongly on the general factor than on their respective bifactors; this
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was not true for the items of the SMBM’s emotional exhaustion subscale. The ECV index
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showed that the general factor accounted for well over half the common variance extracted
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(66%). When excluding the items of the emotional exhaustion subscale of the SMBM, the
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ECV index reached 0.70.
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********************************************* PLEASE INSERT TABLE 2 ABOUT HERE
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*********************************************
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The additional CFA, which only differed from the first CFA by the exclusion of three
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fatigue-related items from the PHQ-9 (items 3, 4, and 7), showed a good fit: RMSEA = 0.060 (90% CI: 0.051-0.068); CFI = 0.977; TLI = 0.973; SRMR = 0.061. Again, the four factors strongly correlated with each other (from 0.56 to 0.77; see Table 1). Despite the removal of three fatigue-related items from the PHQ-9, the three burnout factors still correlated more strongly with the Depressive Symptom factor―0.70 on average―than with each other―0.63 on average. The second-order model involving the Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors as first-order factors fit the data well: RMSEA = 0.058 (90% CI: 0.050-0.067); CFI = 0.978; TLI = 0.974; SRMR = 0.062. All first-
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION order factors loaded substantially on the higher-order factor―from 0.69 for the Emotional Exhaustion factor to 0.90 for the Depressive Symptom factor (0.82 on average; Figure 3). ********************************************* PLEASE INSERT FIGURE 3 ABOUT HERE *********************************************
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In ancillary analyses, we compared burnout scores in participants who met the criteria
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for a provisional diagnosis of major depression and participants who did not meet such
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criteria. Welch’s analysis of variance revealed that depressed participants had higher burnout scores (M = 1.42, SD = 0.68) than non-depressed ones (M = 0.54, SD = 0.46), p < 0.001. The
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effect size was large, d = 1.52.
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4. Discussion
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This study does not support the view that burnout symptoms form a unified, non-depressive
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syndrome. First, contrary to what would be expected if burnout indeed constituted a distinct syndrome [3,28,29], the mean correlation among the burnout factors did not exceed the mean
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correlation of the burnout factors with the Depressive Symptom factor. Remarkably, such results were obtained even when fatigue-related items were excluded from the depression scale under scrutiny, suggesting that the overlap of burnout with depression is much more profound than assumed by some investigators [4,26]. Second, the burnout factors and the Depressive Symptom factor were found to reflect the same higher-order factor. Third, ESEM bifactor analysis showed that all burnout and depression items loaded substantially on the general factor, which accounted for about 2/3 of the common variance extracted. In keeping with our factor analytic findings, participants who met the criteria for a provisional diagnosis of major depression exhibited much higher levels of burnout symptoms than participants who did not meet such criteria. Overall, these results suggest that the symptoms assessed by 11
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION burnout and depression scales can be viewed as the constituents of a single syndrome, consistent with the mounting evidence that burnout problematically overlaps with depression [3,14,35]. It is of note that this study’s findings apparently contrast with the findings of factor analytic studies conducted in the mid-1990s and early 2000s [36,37]. However, important shortcomings were identified in the studies in question [14], including model misspecification
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and problematic item exclusion [37], or the assessment of burnout and depressive symptoms
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within highly different time windows [36,37]. Furthermore, these studies were conducted in
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an era when fitting ordinal structural equation models was challenging [14,35].
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Interestingly, the overlap of burnout with depression was discernible in the initial descriptions of the burnout syndrome. Freudenberger, who introduced the burnout construct in
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psychology, already indicated that the burned-out professional “looks, acts and seems
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depressed” [38]. In addition to exhaustion, this author enumerated depressive symptoms such
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as sadness, crying spells, resignation, discouragement, hopelessness, irritability, frustration, and changes in sleep and weight as components of burnout [38,39]. A burnout scale published
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by Freudenberger and Richelson included items such as “Are you often invaded by a sadness you can’t explain?” or “Is joy elusive?” [40]. Such items are strongly evocative of depressed mood and anhedonia―the two main characteristics of depressive conditions [3,5]. Similar items are commonly employed in depression scales [30,41]. Other items found in Freudenberger and Richelson’s scale [40], such as “Are you seeing close friends and family members less frequently?” or “Do you have very little to say to people?”, refer to social withdrawal, a well-known aspect of depression [42]. From an etiological standpoint, Freudenberger and Richelson considered burnout to result from an investment (cost) that was devoid of the expected return on investment (benefit), that is to say, from the experience of a loss [40]. The etiology of depression has been described along the same lines [7,8,43]. Loss of 12
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION gratification is reportedly the most frequent complaint among depressed patients [42]. A close examination of how the burnout construct emerged in the research literature may help us understand why burnout was approached as a new phenomenon despite the striking similarity between the characteristics ascribed to burnout and the long-identified characteristics of depression. The present study has several strengths, such as the use of advanced statistical
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analyses or the control for content overlap at the level of fatigue-related items. However, the
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study also has limitations. First, the recruited sample was a convenience sample, the
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representativeness of which (e.g., in terms of sex or age) cannot be clearly established. This being mentioned, it should be underlined that the implementation of methods promoting
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sample representativeness such as random sampling is problematic when the populations of
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interest cannot be accurately circumscribed or exhaustively contacted, which was the case in this study. Second, only one measure of burnout, the SMBM, and one measure of depression,
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the PHQ-9, were employed. Although these two scales are measures of reference in burnout
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would have been a plus.
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and depression research, the inclusion of additional measures of burnout and depression
Consistent with a growing body of research [3,13,14,35], this study suggests that urging practitioners and researchers to draw a demarcation line between burnout and depression is unwise. Disquietingly, a “separatist” approach to burnout and depression may be detrimental to worker health protection. Indeed, reducing burnout to feelings of exhaustion and demotivation when the syndrome appears to entail all “classical” symptoms of depression is likely to result in misguided assessment, prevention, and treatment strategies. Because the burnout-depression distinction tends to convey the idea that burnout is not as serious a problem as depression, many people struggling with depression might underestimate the gravity of their condition and not seek help when self-identifying as “burned out.” 13
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Conflicts of interest
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None.
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Freudenberger HJ. The staff burn-out syndrome in alternative institutions. Psychotherapy: Theory Res Practice 1975;12:73-82. http://dx.doi.org/10.1037/h0086411
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University of Pennsylvania Press, 2009.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Table 1. Correlations among the latent Depressive Symptom factor and the latent factors linked to burnout’s components (N = 332). Depressive
Physical Fatigue
Cognitive
Emotional
Symptom factor
factor
Weariness factor
Exhaustion factor
―
0.77
0.77
0.56
0.89
―
0.70
0.62
0.81
0.70
―
0.57
0.59
0.62
0.57
―
Depressive Symptom factor Physical
Fatigue
factor Cognitive Weariness factor Emotional
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Exhaustion factor
Notes. Entries above the diagonal concern the confirmatory factor analysis from which fatigue-related items 3, 4, and 7 were excluded from the PHQ-9; entries below the diagonal concern the confirmatory factor analysis in
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which all the items of the PHQ-9 were included.
Table 2. Summary of the exploratory structural equation bifactor analysis with partially specified target rotation (N = 332). General factor Scale
Subscale
PHQ-9
―
Bifactors
Item
Distress
PHQ-9
PF
1 2
0.58 0.69
0.35 0.60
0.17 0.16
0.05 -0.16
3 4
0.61 0.84
0.04 -0.12
0.00 0.17
-0.20 -0.09
21
CW
EE
Communality
I-ECV
S-ECV
ECV
0.07 -0.15
0.52 0.84
0.66 0.57
0.73
0.66
-0.02 -0.07
0.41 0.78
0.90 0.91
CW
0.68
0.03
-0.08
-0.08
0.07
0.47
0.97
6 7 8 9 1
0.62 0.66 0.63 0.55 0.73
0.45 -0.10 0.27 0.68 -0.14
-0.07 -0.25 -0.07 -0.18 0.32
0.02 0.26 0.15 0.02 -0.05
-0.05 0.01 0.00 0.06 -0.02
0.59 0.58 0.52 0.81 0.67
0.64 0.75 0.76 0.37 0.80
2 3 4 5 6
0.65 0.82 0.55 0.81 0.87
0.04 -0.01 0.15 -0.07 -0.05
0.32 0.38 0.53 0.43 0.42
-0.08 -0.04 0.24 0.04 0.05
0.09 -0.08 0.19 -0.08 -0.01
0.55 0.82 0.74 0.84 0.93
0.77 0.82 0.40 0.78 0.81
1 2 3 4 5
0.65 0.65 0.74 0.71 0.72
-0.10 -0.03 0.16 0.11 -0.01
-0.04 0.13 0.01 0.01 0.06
0.59 0.57 0.47 0.53 0.57
0.02 -0.02 -0.06 0.00 0.04
0.76 0.73 0.82 0.81 0.84
0.55 0.57 0.67 0.61 0.61
1 0.58 0.03 -0.04 0.07 0.50 0.61 2 0.54 -0.04 0.06 -0.06 0.73 0.82 3 0.50 -0.01 0.06 -0.07 0.80 0.89 Notes. SMBM: Shirom-Melamed Burnout Measure; PF: physical fatigue; CW: cognitive weariness; EE: emotional common variance; I-ECV: item-level ECV; S-ECV: (sub)scale-level ECV.
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PF
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SMBM
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0.73
0.60
0.56 0.40 0.36 0.28 exhaustion; ECV: explained
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Figure 1. Schematic representation of the theoretically expected overlap of burnout with depression. Unresolvable stress constitutes the common etiological denominator of the burnout and depression processes. The burnout process overlaps with the depression process, rendering a between-process distinction foundationless. The clinical stage of the depression process, at which a depressive disorder can potentially be diagnosed (categorial approach), is an integral part of the continuum of depression (dimensional approach); it corresponds to the high end of the depression continuum. It is noteworthy that the clinical stage of burnout has not been characterized in either a clear or a consensual manner to date. Burnout has remained nosologically and diagnostically undefined―notably because of its similarities with depression, an entity that has been nosologically and diagnostically defined long before the emergence of the burnout construct. Importantly, the conception of burnout and depression illustrated here reconciles dimensional and categorical approaches to (psycho)pathology; such a conception allows us to overcome the classic, yet problematic, opposition between dimensions and categories.
23
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Figure 2. Graphical summary of the second-order factor analysis that included the full version of the PHQ-9 (N = 332). “ds”: Depressive Symptom factor; “pf”: Physical Fatigue factor; “cw”: Cognitive Weariness factor; “ee”: Emotional Exhaustion factor; “dep”: Depression factor.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION
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Figure 3. Graphical summary of the second-order factor analysis in which three fatiguerelated items were deliberately excluded from the PHQ-9 (N = 332). “ds”: Depressive Symptom factor; “pf”: Physical Fatigue factor; “cw”: Cognitive Weariness factor; “ee”: Emotional Exhaustion factor; “dep”: Depression factor.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Highlights • Burnout dimensions correlate more strongly with depression than with each other. • Burnout and depression (sub)scales are reflective of a common overarching factor. • Bifactor analysis indicates that burnout overlaps with depression.
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• The burnout-depression distinction appears to be untenable.
26
Renzo Bianchi PII:
S0022-3999(19)31239-5
DOI:
https://doi.org/10.1016/j.jpsychores.2020.109954
Reference:
PSR 109954
To appear in:
Journal of Psychosomatic Research
Received date:
29 December 2019
Revised date:
23 January 2020
Accepted date:
3 February 2020
Please cite this article as: R. Bianchi, Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis, Journal of Psychosomatic Research(2019), https://doi.org/10.1016/ j.jpsychores.2020.109954
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 Published by Elsevier.
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis
Renzo Bianchi, Ph.D. [email protected]
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Institute of Work and Organizational Psychology, University of Neuchâtel, Neuchâtel, NE, Switzerland
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Corresponding author: Renzo Bianchi, Institute of Work and Organizational Psychology, University of Neuchâtel, Émile-Argand 11, 2000 Neuchâtel, NE, Switzerland. Tel: +41 32
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718 1390; fax: +41 32 718 1391. Email: [email protected]
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Conflicts of interest
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None declared.
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Sources of funding
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None declared.
Acknowledgements
The author thanks Noémie Pasquier for her help with data collection.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Abstract Objective. To date, the issue of burnout-depression overlap remains contentious. In this study, we examined whether burnout symptoms form a syndrome that is distinct from depression. Methods. The study involved 332 employed individuals (65% female; mean age: 34). Burnout symptoms were assessed with the Shirom-Melamed Burnout Measure (SMBM). The SMBM operationalizes burnout based on three interconnected components, namely,
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physical fatigue, cognitive weariness, and emotional exhaustion. Depressive symptoms were
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assessed with the PHQ-9, a scale that covers the main manifestations of major depression.
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Confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) bifactor analysis were conducted. Results. On average, the factors underlying burnout’s
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components correlated more strongly with the Depressive Symptom factor than with each
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other. Remarkably, such results were obtained even when fatigue-related items were excluded from the depression scale. Second-order CFA revealed that the factors underlying burnout’s
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components and the Depressive Symptom factor were reflective of the same higher-order
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factor. ESEM bifactor analysis indicated that the general factor accounted for about 2/3 of the
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common variance extracted. Conclusion. Consistent with a growing corpus of research, this study suggests that the burnout-depression distinction is untenable. Because the burnoutdepression distinction tends to convey the idea that burnout is not as serious a problem as depression, many people struggling with depression might underestimate the gravity of their condition and not seek help when self-identifying as “burned out.” Maintaining a line of demarcation between burnout and depression may thus be problematic from both a scientific and a health standpoint. Keywords: bifactor analysis; burnout; confirmatory factor analysis; fatigue; occupational health.
2
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis 1. Introduction Burnout has been regarded as a syndrome in which the individual is left exhausted and demotivated by a long-term confrontation with insurmountable job stress [1,2]. Although burnout has elicited growing interest among occupational health specialists over the last
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decades, the nature of the syndrome and (discriminant) validity of the construct remain strongly debated [3,4]. To date, there is no established diagnosis for burnout and burnout is
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not nosologically recognized by either the American Psychiatric Association or the World
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Health Organization [5,6]. A major object of controversy in burnout research concerns the
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extent to which burnout refers to anything other than a depressive condition [3,4]. Depression is primarily characterized by anhedonia and dysphoric mood, with fatigue
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and loss of energy constituting common presenting complaints in affected patients [5]. At an
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etiological level, depressive symptoms have been identified as basic responses to unresolvable
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stress in human beings (and mammals in general) and are considered basic signals of a discrepancy between positive, rewarding experiences on the one hand, and negative, punitive experiences on the other hand [7-9]. While depression is nosologically characterized and diagnosable [5], it is best viewed as a dimensional variable [10]. Depressive symptoms thus vary in intensity, frequency, and pervasiveness along a continuum, with depressive disorders representing only a portion of that continuum―its high end [3,11]. Theoretically speaking, because (a) depressive symptoms constitute basic responses to unresolvable stress (either job-related or not) and (b) burnout is supposed to result from insurmountable job stress, the reason for expecting burnout to fall outside, rather than inside, the spectrum of depression is unclear [3]. On a related note, when burnout and depression are
3
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION both approached dimensionally, the continua of the two entities mirror one another (Figure 1), rendering the burnout-depression distinction―including the distinction between full-blown burnout and clinical depression―difficult to articulate [3,11,12]. It is worth underlining that the job-related character of burnout has often been regarded as a key distinctive feature of the phenomenon [2,4]. However, because burnout could be both job-related and depressive in nature, the discriminant value of the “job-relatedness” argument is open to question [3,13]. Depressive symptoms can emerge and develop in the work context―in response to
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occupational stressors―before potentially impregnating larger areas of an individual’s life
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[12].
Substantiating the abovementioned concerns, the burnout-depression distinction has
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been increasingly called into question on empirical grounds [3]. Burnout has been found to
processing
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overlap with depression in terms of: (a) primary symptoms and causes [13-15]; (b) cognitive of emotional information
(e.g.,
biased
memorizing in favor of negative
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information, negative interpretation of ambiguous information) [16-19]; (c) dispositional
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correlates and risk factors (e.g., neuroticism, history of anxiety and depressive disorders) [20-
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22]; and (d) prescribed treatments (e.g., antidepressant medication) [23-25]. A recent metaanalytic study, however, concluded that while burnout and depression were substantially associated with one another, the size of the association remained compatible with the view that the two constructs are distinct [26]. In addition, it has been argued that the presence of fatigue-related items in both burnout and depression scales may have “inflated” the burnoutdepression association [4,26]. Although the validity of this argument is not beyond question [27], the extent to which the strength of the burnout-depression association can be imputed to content overlap at the level of fatigue-related items requires further clarification [14]. Overall, more research has been called for before definite conclusions can be envisaged regarding the distinctiveness of burnout vis-à-vis depression [4]. 4
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION In the present study, the issue of burnout-depression overlap was addressed through an examination of the unity of burnout as a syndrome. By definition, a syndrome refers to a combination of co-occurring symptoms characterizing a given entity [5, 28]. On this basis, it was reasoned that, if burnout constitutes a syndrome that is distinct from depression, then burnout symptoms should combine with each other rather than with depressive symptoms. That burnout’s components be more strongly linked to each other than to any aspect of depression has been considered crucial to establishing the discriminant validity of the burnout
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construct [29]. Despite its importance, this aspect of burnout’s distinctiveness has received insufficient attention thus far. The earlier mentioned meta-analysis, for instance, did not
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compare the correlations between burnout and depression to the correlations among burnout’s
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components [26]. Clarifying whether burnout is well characterized when separated from
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depression is key to our ability to assess, prevent, and treat burnout effectively.
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********************************************* 2. Methods
2.1. Study sample and recruitment procedure Participants were recruited in Switzerland in June and July 2016 through contacts with Swiss organizations in both the public and the private sector as well as through advertisements in social media. Our participation request contained a brief description of the study (e.g., general topic, targeted population, expected duration) and a weblink allowing individuals to complete the study. The organizations were free to forward our request to their employees or to ignore it. The only eligibility criterion for participating in the study was to be currently employed. Employed individuals were thus invited to participate whether experiencing job stress or not. 5
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Participation was voluntary. Confidentiality was guaranteed to each respondent. Individual consent was requested. The study was conducted in accordance with the ethical standards of the institutional review board of the University of MASKED FOR REVIEW. 2.2. Measures of interest Burnout symptoms were assessed with the Shirom-Melamed Burnout Measure (SMBM) [1,2]. The SMBM is an explicitly work-contextualized questionnaire. The SMBM divides
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burnout into three components, namely, physical fatigue (six items; e.g., “I feel physically
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drained”; Cronbach’s α = 0.90), cognitive weariness (five items; e.g., “I feel I am not focused
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in my thinking”; Cronbach’s α = 0.90), and emotional exhaustion (three items; e.g., “I feel I
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am not capable of investing emotionally in coworkers and recipients”; Cronbach’s α = 0.81). It is noteworthy that the physical fatigue subscale of the SMBM refers to a general kind of ill-
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being at work (e.g., “I feel fed up”; “I feel burned out”) as much as it refers to actual physical
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fatigue. The cognitive weariness subscale of the SMBM homogeneously gauges cognitive
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impairment (e.g., attentional problems, difficulties in reasoning). The emotional exhaustion subscale of the SMBM deals with burnout symptoms at an interpersonal level. Participants
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were asked to indicate how they felt over the previous two weeks. They responded using a 4point rating scale, from 0 for not at all to 3 for nearly every day. The SMBM is a measure of reference in burnout research [1,2]. Scores on the SMBM correlate almost perfectly (disattenuated correlations around .90) with scores on the core dimension of the Maslach Burnout Inventory (MBI)-General Survey, another popular measure of burnout [1,29]. By contrast with the MBI, however, the SMBM is in the public domain and reflects a theorydriven approach to burnout [1]. Depressive symptoms were assessed with the PHQ-9 [30], a scale that covers the main manifestations of major depression as referenced in the latest edition of the Diagnostic and Statistical Manual of Mental Disorders [5]. The PHQ-9 thus allows for the assessment of 6
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION anhedonia, depressed mood, sleep disturbance, fatigue/loss of energy, appetite alteration, guilt/worthlessness, concentration impairment, psychomotor malfunction, and thoughts of self-harm. In addition, the PHQ-9 enables the investigator to establish a provisional diagnosis of major depression based on a dedicated algorithm [30]. The response frame used with the PHQ-9 was identical to the response frame used with the SMBM. Cronbach’s α for the PHQ9 was 0.83.
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2.3. Data analyses Data were analyzed principally within a factor analytic framework, using Mplus 8 [31]. The
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items were treated as ordinal. The weighted least squares—mean and variance adjusted—
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(WLSMV) method was employed. Goodness of fit was assessed based on five complementary indices: The Root Mean Square Error of Approximation (RMSEA), the Comparative Fit
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Index (CFI), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual
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(SRMR), and the Weighted Root Mean Square Residual (WRMR).
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First, a four-factor confirmatory factor analysis (CFA) was conducted. Latent Physical
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Fatigue, Cognitive Weariness, and Emotional Exhaustion factors were created based on the items belonging to the original subscales of the SMBM and a latent Depressive Symptom factor was created based on the items belonging to the PHQ-9. The aim of this CFA was to examine the correlations among the latent factors attached to the measures of burnout and depression. A second-order model was then tested, in which the latent Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors were defined as firstorder factors. The goal was to examine whether the latent factors attached to the measures of burnout and depression could be considered reflective of the same overarching factor.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Third, an exploratory structural equation modeling (ESEM) bifactor analysis with partially specified target rotation (PSTR) was conducted [32]. The logic of PSTR is highly similar to that of CFA. However, by contrast with CFA, in which loadings are forced to equal zero, PSTR extracts factors and then attempts to match the target as well as possible. In the specification employed, all items were allowed to load on the general factor and each item was allowed to load on a bifactor that was specific to the scale or subscale to which the item belonged. For instance, a PHQ-9 item would load on the general factor as well as on a PHQ-9
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bifactor. Because four (sub)scales were submitted to examination (the PHQ-9 and the three SMBM subscales), four bifactors were considered in addition to the general factor. The mean
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item loading on the general factor as well as the explained common variance (ECV) and
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omega hierarchical (omegaH) indices were computed. ECV is an index of the proportion of
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the common variance extracted that is explained by the general factor [33,34]. OmegaH is an index of total score reliability [34]. The state of the art suggests that “when omegaH is high (>
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.80), total scores can be considered essentially unidimensional, in the sense that the vast
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majority of reliable variance is attributable to a single common source” [33].
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In view of the claim, made by some investigators [4,26], that the burnout-depression association may be driven by content overlap at the level of fatigue-related items, the CFAs were re-run with three fatigue-related items deliberately excluded from the PHQ-9 (items 3 [sleep disturbance], 4 [fatigue/loss of energy], and 7 [concentration impairment]). Such a procedure allowed for a more “conservative” approach to the burnout-depression association. 3. Results A total of 332 participants, employed in various occupational domains (e.g., human resources, education, healthcare), were enrolled in the present study (65% female; mean age: 34). Participants’ mean length of employment in their current occupation was 7 years. Descriptive statistics pertaining to the PHQ-9 and SMBM items (e.g., range, skewness, kurtosis) are 8
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION available in Supplementary Material 1. About 9% of the participants (n = 31) met the criteria for a provisional diagnosis of major depression in the study sample. The first CFA, in which the nine items of the PHQ-9 were allowed to load on a Depressive Symptom factor, the six items of the SMBM’s physical fatigue subscale were allowed to load on a Physical Fatigue factor, the five items of the SMBM’s cognitive weariness subscale were allowed to load on a Cognitive Weariness factor, and the three items
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of the SMBM’s emotional exhaustion subscale were allowed to load on an Emotional
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Exhaustion factor showed an acceptable fit: RMSEA = 0.073 (90% confidence interval [CI]:
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0.066-0.079); CFI = 0.959; TLI = 0.954; SRMR = 0.074. The four factors strongly correlated with each other (from 0.59 to 0.89; see Table 1). The three latent burnout factors correlated
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less strongly with each other―0.63 on average―than with the Depressive Symptom
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factor―0.76 on average.
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********************************************* The second-order model involving the Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors as first-order factors fit the data satisfactorily: RMSEA = 0.072 (90% CI: 0.065-0.079); CFI = 0.960; TLI = 0.955; SRMR = 0.075. All first-order factors loaded substantially on the higher-order factor―from 0.66 for the Emotional Exhaustion factor to 0.98 for the Depressive Symptom factor (0.84 on average; Figure 2). ********************************************* PLEASE INSERT FIGURE 2 ABOUT HERE
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION ********************************************* The bifactor model (Table 2) showed an excellent fit: RMSEA = 0.036 (90% CI: 0.025-0.047); CFI = 0.993; TLI = 0.988; WRMR = 0.460. All PHQ-9 and SMBM items loaded substantially on the general factor―from 0.50 to 0.87 (M = 0.67). OmegaH was .86. The items of the PHQ-9 and physical fatigue and cognitive weariness subscales of the SMBM loaded on average more strongly on the general factor than on their respective bifactors; this
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was not true for the items of the SMBM’s emotional exhaustion subscale. The ECV index
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showed that the general factor accounted for well over half the common variance extracted
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(66%). When excluding the items of the emotional exhaustion subscale of the SMBM, the
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ECV index reached 0.70.
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********************************************* PLEASE INSERT TABLE 2 ABOUT HERE
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The additional CFA, which only differed from the first CFA by the exclusion of three
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fatigue-related items from the PHQ-9 (items 3, 4, and 7), showed a good fit: RMSEA = 0.060 (90% CI: 0.051-0.068); CFI = 0.977; TLI = 0.973; SRMR = 0.061. Again, the four factors strongly correlated with each other (from 0.56 to 0.77; see Table 1). Despite the removal of three fatigue-related items from the PHQ-9, the three burnout factors still correlated more strongly with the Depressive Symptom factor―0.70 on average―than with each other―0.63 on average. The second-order model involving the Physical Fatigue, Cognitive Weariness, Emotional Exhaustion, and Depressive Symptom factors as first-order factors fit the data well: RMSEA = 0.058 (90% CI: 0.050-0.067); CFI = 0.978; TLI = 0.974; SRMR = 0.062. All first-
10
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION order factors loaded substantially on the higher-order factor―from 0.69 for the Emotional Exhaustion factor to 0.90 for the Depressive Symptom factor (0.82 on average; Figure 3). ********************************************* PLEASE INSERT FIGURE 3 ABOUT HERE *********************************************
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In ancillary analyses, we compared burnout scores in participants who met the criteria
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for a provisional diagnosis of major depression and participants who did not meet such
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criteria. Welch’s analysis of variance revealed that depressed participants had higher burnout scores (M = 1.42, SD = 0.68) than non-depressed ones (M = 0.54, SD = 0.46), p < 0.001. The
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effect size was large, d = 1.52.
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4. Discussion
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This study does not support the view that burnout symptoms form a unified, non-depressive
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syndrome. First, contrary to what would be expected if burnout indeed constituted a distinct syndrome [3,28,29], the mean correlation among the burnout factors did not exceed the mean
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correlation of the burnout factors with the Depressive Symptom factor. Remarkably, such results were obtained even when fatigue-related items were excluded from the depression scale under scrutiny, suggesting that the overlap of burnout with depression is much more profound than assumed by some investigators [4,26]. Second, the burnout factors and the Depressive Symptom factor were found to reflect the same higher-order factor. Third, ESEM bifactor analysis showed that all burnout and depression items loaded substantially on the general factor, which accounted for about 2/3 of the common variance extracted. In keeping with our factor analytic findings, participants who met the criteria for a provisional diagnosis of major depression exhibited much higher levels of burnout symptoms than participants who did not meet such criteria. Overall, these results suggest that the symptoms assessed by 11
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION burnout and depression scales can be viewed as the constituents of a single syndrome, consistent with the mounting evidence that burnout problematically overlaps with depression [3,14,35]. It is of note that this study’s findings apparently contrast with the findings of factor analytic studies conducted in the mid-1990s and early 2000s [36,37]. However, important shortcomings were identified in the studies in question [14], including model misspecification
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and problematic item exclusion [37], or the assessment of burnout and depressive symptoms
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within highly different time windows [36,37]. Furthermore, these studies were conducted in
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an era when fitting ordinal structural equation models was challenging [14,35].
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Interestingly, the overlap of burnout with depression was discernible in the initial descriptions of the burnout syndrome. Freudenberger, who introduced the burnout construct in
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psychology, already indicated that the burned-out professional “looks, acts and seems
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depressed” [38]. In addition to exhaustion, this author enumerated depressive symptoms such
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as sadness, crying spells, resignation, discouragement, hopelessness, irritability, frustration, and changes in sleep and weight as components of burnout [38,39]. A burnout scale published
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by Freudenberger and Richelson included items such as “Are you often invaded by a sadness you can’t explain?” or “Is joy elusive?” [40]. Such items are strongly evocative of depressed mood and anhedonia―the two main characteristics of depressive conditions [3,5]. Similar items are commonly employed in depression scales [30,41]. Other items found in Freudenberger and Richelson’s scale [40], such as “Are you seeing close friends and family members less frequently?” or “Do you have very little to say to people?”, refer to social withdrawal, a well-known aspect of depression [42]. From an etiological standpoint, Freudenberger and Richelson considered burnout to result from an investment (cost) that was devoid of the expected return on investment (benefit), that is to say, from the experience of a loss [40]. The etiology of depression has been described along the same lines [7,8,43]. Loss of 12
Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION gratification is reportedly the most frequent complaint among depressed patients [42]. A close examination of how the burnout construct emerged in the research literature may help us understand why burnout was approached as a new phenomenon despite the striking similarity between the characteristics ascribed to burnout and the long-identified characteristics of depression. The present study has several strengths, such as the use of advanced statistical
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analyses or the control for content overlap at the level of fatigue-related items. However, the
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study also has limitations. First, the recruited sample was a convenience sample, the
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representativeness of which (e.g., in terms of sex or age) cannot be clearly established. This being mentioned, it should be underlined that the implementation of methods promoting
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sample representativeness such as random sampling is problematic when the populations of
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interest cannot be accurately circumscribed or exhaustively contacted, which was the case in this study. Second, only one measure of burnout, the SMBM, and one measure of depression,
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the PHQ-9, were employed. Although these two scales are measures of reference in burnout
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would have been a plus.
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and depression research, the inclusion of additional measures of burnout and depression
Consistent with a growing body of research [3,13,14,35], this study suggests that urging practitioners and researchers to draw a demarcation line between burnout and depression is unwise. Disquietingly, a “separatist” approach to burnout and depression may be detrimental to worker health protection. Indeed, reducing burnout to feelings of exhaustion and demotivation when the syndrome appears to entail all “classical” symptoms of depression is likely to result in misguided assessment, prevention, and treatment strategies. Because the burnout-depression distinction tends to convey the idea that burnout is not as serious a problem as depression, many people struggling with depression might underestimate the gravity of their condition and not seek help when self-identifying as “burned out.” 13
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Conflicts of interest
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None.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Table 1. Correlations among the latent Depressive Symptom factor and the latent factors linked to burnout’s components (N = 332). Depressive
Physical Fatigue
Cognitive
Emotional
Symptom factor
factor
Weariness factor
Exhaustion factor
―
0.77
0.77
0.56
0.89
―
0.70
0.62
0.81
0.70
―
0.57
0.59
0.62
0.57
―
Depressive Symptom factor Physical
Fatigue
factor Cognitive Weariness factor Emotional
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Exhaustion factor
Notes. Entries above the diagonal concern the confirmatory factor analysis from which fatigue-related items 3, 4, and 7 were excluded from the PHQ-9; entries below the diagonal concern the confirmatory factor analysis in
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which all the items of the PHQ-9 were included.
Table 2. Summary of the exploratory structural equation bifactor analysis with partially specified target rotation (N = 332). General factor Scale
Subscale
PHQ-9
―
Bifactors
Item
Distress
PHQ-9
PF
1 2
0.58 0.69
0.35 0.60
0.17 0.16
0.05 -0.16
3 4
0.61 0.84
0.04 -0.12
0.00 0.17
-0.20 -0.09
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CW
EE
Communality
I-ECV
S-ECV
ECV
0.07 -0.15
0.52 0.84
0.66 0.57
0.73
0.66
-0.02 -0.07
0.41 0.78
0.90 0.91
CW
0.68
0.03
-0.08
-0.08
0.07
0.47
0.97
6 7 8 9 1
0.62 0.66 0.63 0.55 0.73
0.45 -0.10 0.27 0.68 -0.14
-0.07 -0.25 -0.07 -0.18 0.32
0.02 0.26 0.15 0.02 -0.05
-0.05 0.01 0.00 0.06 -0.02
0.59 0.58 0.52 0.81 0.67
0.64 0.75 0.76 0.37 0.80
2 3 4 5 6
0.65 0.82 0.55 0.81 0.87
0.04 -0.01 0.15 -0.07 -0.05
0.32 0.38 0.53 0.43 0.42
-0.08 -0.04 0.24 0.04 0.05
0.09 -0.08 0.19 -0.08 -0.01
0.55 0.82 0.74 0.84 0.93
0.77 0.82 0.40 0.78 0.81
1 2 3 4 5
0.65 0.65 0.74 0.71 0.72
-0.10 -0.03 0.16 0.11 -0.01
-0.04 0.13 0.01 0.01 0.06
0.59 0.57 0.47 0.53 0.57
0.02 -0.02 -0.06 0.00 0.04
0.76 0.73 0.82 0.81 0.84
0.55 0.57 0.67 0.61 0.61
1 0.58 0.03 -0.04 0.07 0.50 0.61 2 0.54 -0.04 0.06 -0.06 0.73 0.82 3 0.50 -0.01 0.06 -0.07 0.80 0.89 Notes. SMBM: Shirom-Melamed Burnout Measure; PF: physical fatigue; CW: cognitive weariness; EE: emotional common variance; I-ECV: item-level ECV; S-ECV: (sub)scale-level ECV.
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SMBM
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0.73
0.60
0.56 0.40 0.36 0.28 exhaustion; ECV: explained
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Figure 1. Schematic representation of the theoretically expected overlap of burnout with depression. Unresolvable stress constitutes the common etiological denominator of the burnout and depression processes. The burnout process overlaps with the depression process, rendering a between-process distinction foundationless. The clinical stage of the depression process, at which a depressive disorder can potentially be diagnosed (categorial approach), is an integral part of the continuum of depression (dimensional approach); it corresponds to the high end of the depression continuum. It is noteworthy that the clinical stage of burnout has not been characterized in either a clear or a consensual manner to date. Burnout has remained nosologically and diagnostically undefined―notably because of its similarities with depression, an entity that has been nosologically and diagnostically defined long before the emergence of the burnout construct. Importantly, the conception of burnout and depression illustrated here reconciles dimensional and categorical approaches to (psycho)pathology; such a conception allows us to overcome the classic, yet problematic, opposition between dimensions and categories.
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Figure 2. Graphical summary of the second-order factor analysis that included the full version of the PHQ-9 (N = 332). “ds”: Depressive Symptom factor; “pf”: Physical Fatigue factor; “cw”: Cognitive Weariness factor; “ee”: Emotional Exhaustion factor; “dep”: Depression factor.
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Figure 3. Graphical summary of the second-order factor analysis in which three fatiguerelated items were deliberately excluded from the PHQ-9 (N = 332). “ds”: Depressive Symptom factor; “pf”: Physical Fatigue factor; “cw”: Cognitive Weariness factor; “ee”: Emotional Exhaustion factor; “dep”: Depression factor.
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Journal Pre-proof RUNNING HEAD: BURNOUT-DEPRESSION DISTINCTION Highlights • Burnout dimensions correlate more strongly with depression than with each other. • Burnout and depression (sub)scales are reflective of a common overarching factor. • Bifactor analysis indicates that burnout overlaps with depression.
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• The burnout-depression distinction appears to be untenable.
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