# Burnout in the general population: Role of anxiety, depression and traumatic events

Lucia Romo, Clément Duret, Laurent Cruchet, Stéphanie Nann, Samantha

Tessier, Oulmann Zerhouni

► To cite this version:

Lucia Romo, Clément Duret, Laurent Cruchet, Stéphanie Nann, Samantha Tessier, et al.. Burnout in the general population: Role of anxiety, depression and traumatic events. Journal of Affective Disorders Reports, 2025, 21, pp.100941. 10.1016/j.jadr.2025.100941. hal-05355492

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Research Paper

# Burnout in the general population: Role of anxiety, depression and traumatic events

<figure><img src="image_3.png" /></figure>

Lucia Romo<sup>a,b,c,*</sup> <sup>DD</sup>, Clément Duret<sup>b,D</sup>, Laurent Cruchet<sup>b,d D</sup>, Stéphanie Nann<sup>a,b D</sup>, Samantha Tessier<sup>e,D</sup>, Oulmann Zerhouni<sup>a,f D</sup>

## ARTICLE INFO

### Keywords:

Burnout

PTSD

Anxiety

Depression

Trauma

Public health

General population

## ABSTRACT

**Objective:** This study aims to examine the predictors of work exhaustion in the general population, with a particular focus on the roles of burnout, anxiety, depression, and trauma-related symptoms.

**Methods:** A cross-sectional survey was conducted among a sample from the French general population. The survey included measures of burnout using the Copenhagen Burnout Inventory (CBI), anxiety (GAD-7), depression (PHQ-9), and trauma-related symptoms (International Trauma Questionnaire [ITQ]). Correlation and Regression analyses were performed to identify significant predictors of work exhaustion.

**Results:** The analysis revealed that personal burnout (CBI) were significant positive predictors of work exhaustion. Older individuals and men reported higher levels of work exhaustion. However, anxiety, depression, and trauma-related symptoms did not emerge as significant predictors.

**Conclusion:** The findings underscore the critical role of specific dimensions of burnout, particularly personal burnout, in predicting work exhaustion. These results suggest that targeted interventions addressing these aspects of burnout may be crucial in reducing work-related stress and improving employee well-being. The study also highlights the need for further research on the indirect effects of trauma on work exhaustion in the general population.

## 1. Burnout in non-healthcare settings

While burnout was traditionally associated with healthcare providers and educators, emerging research indicates that this syndrome affects individuals across various professions and even those not engaged in formal employment. As evidenced in studies such as those conducted by Aronsson et al. (2017), factors including elevated job demands, diminished autonomy, and inadequate compensation are strongly associated with burnout across a range of professional contexts. Furthermore, the occurrence of burnout in the general population has also been associated with a multitude of social and psychological factors. Vňuková et al. (2023) observed an increasing recognition of burnout syndrome, with a particular prevalence among women, who exhibited

heightened perceived threat related to burnout in comparison to men. This growing awareness highlights the significance of mental health in mitigating burnout severity, as public consciousness can facilitate more effective preventive strategies. Similarly, in a study involving police officers, Violanti et al. (2018) identified overcommitment and effort-reward imbalance as key predictors of burnout, further underscoring the role of workplace dynamics in this syndrome's development. The more expansive conceptualization of burnout's influence underscores its significance extending beyond occupational contexts. This calls for a thorough examination of the factors contributing to and resulting from burnout across a diverse demographic spectrum.

<footnote><sup>a</sup> University Paris Nanterre UR 4430, Departement of Psychology, 200 av de la république, 92001 Nanterre Cedex, France</footnote>

<footnote><sup>b</sup> Hôpital Universitaire Raymond-Poincaré, Service de Pathologies Professionnelles (AP-HP), 92380 Garches, France</footnote>

<footnote><sup>c</sup> Inserm CESP 1018 UPS, 114, rue Edouard-Vaillant 94 805 Villejuif Cedex, France</footnote>

<footnote><sup>d</sup> GHU Paris Psychiatrie et Neurosciences, Clinique des Maladies Mentales et de l'Encéphale (CMME), 75014 Paris, France</footnote>

<footnote><sup>e</sup> Centre pénitentiaire des Hauts-de-Seine, 133 avenue de la Commune de Paris, BP 1414, 92014 Nanterre Cedex, France</footnote>

<footnote><sup>f</sup> Université de Rouen Normandie, CRFDP, 1 rue Thomas Becket, 76821 Mont-Saint-Aignan Cedex, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: lromodes@parisnanterre.fr (L. Romo), clement.duret@aphp.fr (C. Duret), laurent.cruchet@gmail.com (L. Cruchet), stephanienann@gmail.com (S. Nann), samanthatessier.st@gmail.com (S. Tessier), zerhounioulmann@gmail.com (O. Zerhouni).</footnote>
## 2. The role of trauma and psychopathological vulnerabilities

Traumatic experiences and pre-existing psychopathological conditions, such as anxiety and depression, have been identified as critical factors influencing the onset and progression of burnout. Firefighters showed a strong association between burnout and job demands and effort-reward imbalances, which in turn increased the risk of post-traumatic stress disorder (PTSD, Kim et al. (2019). However, while trauma was directly linked to burnout, its association with PTSD was less pronounced, suggesting that burnout might act as a mediator in the relationship between trauma and other psychological outcomes.

Furthermore, individuals experiencing a work-life imbalance, which often coexists with traumatic stress, exhibited significant cognitive impairments, including difficulties with attention, memory, and executive functioning (Al-Adawi et al., 2022). These cognitive deficits, coupled with emotional exhaustion, contribute to the overall burden of burnout, which represents a critical area of concern for public health interventions.

## 3. Burnout in specific populations

The general population, particularly those outside traditional employment sectors, has been underrepresented in burnout research. Nevertheless, studies in specific populations provide valuable insights into the broader applicability of burnout concepts. For instance, Jones-Bitton et al. (2019) conducted a study among farmers, revealing that a significant proportion exhibited burnout symptoms comparable to or exceeding those in more studied occupational groups. Among students, particularly first-year university students, emotional exhaustion is a prevalent issue. Aguayo et al. (2019) found that younger students reported higher levels of emotional exhaustion compared to their older peers, indicating that the transition to higher education might be a critical period for the development of burnout.

Caregivers, another group frequently affected by burnout, often face cultural and contextual challenges that exacerbate their stress levels. Rote et al. (2019) emphasizes the need to consider cultural factors when assessing burnout in caregivers, as these elements can significantly influence the perception and expression of burnout symptoms.

## 4. The French context: a gap in research

In France, research on burnout within the general population remains limited. The existing studies often focus on specific professional groups, with little attention given to the broader public. This gap in the literature presents a significant challenge for understanding the full scope of burnout and its impact on public health in France. Moreover, the lack of comprehensive data hinders the development of targeted interventions that could address the unique needs of the French population.

## 5. Objective and hypothesis

This study aims to explore the relationships between burnout, PTSD, C-PTSD and other psychological factors such as depression and anxiety in the general population of France. We aim to examine the distinctions between simple and complex PTSD and their respective contributions to burnout. Additionally, the study will investigate the role of depression and anxiety as potential mediators in the relationship between trauma and burnout.

More precisely, we predict that the Copenhagen Burnout Inventory (CBI) will demonstrate strong correlations with subjective perceptions of burnout within the general French population. Secondary hypotheses include the expectation that personal burnout, as measured by the CBI, will significantly predict work exhaustion. Furthermore, it is postulated that elevated levels of depression, as evaluated by the Patient Health Questionnaire (PHQ-9), and anxiety, as assessed by the Generalized

Anxiety Disorder Scale (GAD-7), will be linked to heightened burnout across all assessed dimensions, including personal burnout, work-related burnout, and client-related burnout. Conversely, it is anticipated that resilience, as measured by the Brief Resilience Scale (BRS), will be inversely related to burnout. Individuals exhibiting higher resilience are expected to report lower levels of burnout.

## 6. Methods

### 6.1. Participants

This study was designed as an observational online survey to comprehensively assess burnout and related mental health dimensions among participants. It was conducted between May and June 2022, and the participants were residents of mainland France. The participants completed a 15-minute voluntary online survey on the Qualtrics platform, which anonymizes responses. Consent from all participants was obtained before they participated in the study. A total of 634 participants completed the questionnaire, 53 % of whom were men ($M_{Age} = 39.7$; $SD_{Age} = 11.24$, see Table 1). Participants were residents of mainland France, aged 18–60 years, recruited through online advertisements on social media platforms (e.g., Facebook, LinkedIn) and professional networks. Advertisements briefly described the purpose of the study, its duration (≈15 min), its voluntary nature, and the right to withdraw. Interested individuals accessed an electronic informed consent form that detailed the study objectives, procedures, assurances of confidentiality, and the ability to withdraw at any time without penalty. We excluded all respondents with at least one missing item on our questionnaires, resulting in a final sample of $N = 634$.

### 6.2. Material

#### 6.2.1. *Copenhagen burnout inventory (CBI, $\alpha = 0.93$)*

Developed by the Danish Institute for Workplace Health, the CBI assesses burnout not only in work settings but also across multiple contexts. This comprehensive approach makes the CBI particularly suitable for a wider range of occupations. The CBI consists of three scales: (i) Personal Burnout, which measures general feelings of exhaustion and fatigue, ($\alpha = 0.86$) (ii) Job Burnout, which focuses on exhaustion directly related to work ($\alpha = 0.81$), and (iii) Client-Related Burnout, which assesses burnout feelings related to interactions with clients or patients. A higher score indicates higher burnout (Kristensen et al., 2005).

#### 6.2.2. *Generalized anxiety disorder scale (GAD-7)*

The Generalized Anxiety Disorder Scale (GAD-7) is a self-report questionnaire designed to assess the severity of generalized anxiety disorder (GAD). The GAD-7 is a widely utilized self-report questionnaire that has been specifically designed to facilitate the screening and measurement of the severity of GAD. The GAD-7 was developed by Spitzer et al. (2006) and consists of seven items that assess the frequency of anxiety symptoms over the past two weeks. These include feelings of nervousness, an inability to stop worrying, and difficulty relaxing. Each item is rated on a four-point Likert scale, with responses ranging from "0" (indicating "Not at all") to "3" (indicating "Nearly every day"). The total score ranges from 0 to 21, with higher scores indicating greater anxiety severity. Scores of 5, 10, and 15 are typically used as cut-off points for mild, moderate, and severe anxiety, respectively. The GAD-7 has demonstrated good reliability and validity in various populations and is widely used in both clinical and research settings (Micoulaud-Franchi et al., 2016).

#### 6.2.3. *Patient health questionnaire-9 (PHQ-9)*

The Patient Health Questionnaire-9 (PHQ-9) is a self-report measure designed to assess the severity of depressive symptoms in accordance with the diagnostic criteria for major depressive disorder outlined in the
<table><caption>**Table 1**

Descriptive statistics.</caption><thead><tr><th></th><th>Sex</th><th>N</th><th>Missing</th><th>Mean</th><th>Median</th><th>SD</th></tr></thead><tbody><tr><td rowspan="2">ITQ_Re-experiencing</td><td>Women</td><td>296</td><td>15</td><td>2.8716</td><td>3.0000</td><td>2.1871</td></tr><tr><td>Men</td><td>338</td><td>10</td><td>2.9793</td><td>3.0000</td><td>2.1075</td></tr><tr><td rowspan="2">ITQ_Avoidance</td><td>Women</td><td>296</td><td>15</td><td>3.1149</td><td>3.0000</td><td>2.3085</td></tr><tr><td>Men</td><td>338</td><td>10</td><td>3.1864</td><td>3.0000</td><td>2.0909</td></tr><tr><td rowspan="2">ITQ_Threat</td><td>Women</td><td>296</td><td>15</td><td>3.1858</td><td>3.0000</td><td>2.3002</td></tr><tr><td>Men</td><td>338</td><td>10</td><td>3.3550</td><td>3.0000</td><td>2.2310</td></tr><tr><td rowspan="2">ITQ Post-Traumatic Stress Disorder</td><td>Women</td><td>296</td><td>15</td><td>9.1723</td><td>9.0000</td><td>5.9955</td></tr><tr><td>Men</td><td>338</td><td>10</td><td>9.5207</td><td>10.0000</td><td>5.7686</td></tr><tr><td rowspan="2">ITQ_Affective Dysregulation</td><td>Women</td><td>294</td><td>17</td><td>3.4932</td><td>3.5000</td><td>1.8908</td></tr><tr><td>Men</td><td>336</td><td>12</td><td>3.4375</td><td>3.0000</td><td>1.8742</td></tr><tr><td rowspan="2">ITQ_Negative Self-Concept</td><td>Women</td><td>294</td><td>17</td><td>3.2687</td><td>3.0000</td><td>2.6007</td></tr><tr><td>Men</td><td>336</td><td>12</td><td>2.9048</td><td>3.0000</td><td>2.4659</td></tr><tr><td rowspan="2">ITQ_Disturbance in Relationships</td><td>Women</td><td>294</td><td>17</td><td>3.5544</td><td>4.0000</td><td>2.4416</td></tr><tr><td>Men</td><td>336</td><td>12</td><td>3.4077</td><td>3.5000</td><td>2.3570</td></tr><tr><td rowspan="2">ITQ_Complex PTSD</td><td>Women</td><td>294</td><td>17</td><td>10.3163</td><td>10.0000</td><td>5.8810</td></tr><tr><td>Men</td><td>336</td><td>12</td><td>9.7500</td><td>10.0000</td><td>5.8133</td></tr><tr><td rowspan="2">ITQ_AvoidanceThreat</td><td>Women</td><td>296</td><td>15</td><td>3.1503</td><td>3.0000</td><td>2.1102</td></tr><tr><td>Men</td><td>338</td><td>10</td><td>3.2707</td><td>3.5000</td><td>1.9933</td></tr><tr><td rowspan="2">GAD-7</td><td>Women</td><td>304</td><td>7</td><td>10.1809</td><td>10.0000</td><td>5.3242</td></tr><tr><td>Men</td><td>344</td><td>4</td><td>9.5291</td><td>9.0000</td><td>5.3386</td></tr><tr><td rowspan="2">PHQ-9</td><td>Women</td><td>304</td><td>7</td><td>11.5132</td><td>11.0000</td><td>6.0760</td></tr><tr><td>Men</td><td>343</td><td>5</td><td>10.8017</td><td>10</td><td>6.2969</td></tr><tr><td rowspan="2">Brief Resilience Scale</td><td>Women</td><td>293</td><td>18</td><td>17.2935</td><td>18</td><td>3.8136</td></tr><tr><td>Men</td><td>336</td><td>12</td><td>18.5238</td><td>18.0000</td><td>3.5718</td></tr><tr><td rowspan="2">CBI_Personal burnout</td><td>Women</td><td>308</td><td>3</td><td>15.5909</td><td>16.0000</td><td>3.7139</td></tr><tr><td>Men</td><td>347</td><td>1</td><td>14.0432</td><td>14</td><td>4.2147</td></tr><tr><td rowspan="2">CBI_Work-related burnout</td><td>Women</td><td>308</td><td>3</td><td>16.8344</td><td>17.0000</td><td>5.0627</td></tr><tr><td>Men</td><td>347</td><td>1</td><td>15.7406</td><td>16</td><td>5.5236</td></tr><tr><td rowspan="2">CBI ann-related burnout</td><td>Women</td><td>308</td><td>3</td><td>12.9058</td><td>13.0000</td><td>5.5716</td></tr><tr><td>Men</td><td>347</td><td>1</td><td>13.0605</td><td>13</td><td>5.6039</td></tr></tbody></table>

Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; Kroenke et al., 2001). The PHQ-9 is comprised of nine items, each corresponding to one of the nine diagnostic criteria for depression, including anhedonia, depressed mood, sleep disturbances, fatigue, and suicidal ideation. The respondents indicate the frequency with which they have been bothered by each symptom over the past two weeks on a 4-point Likert scale, with scores ranging from 0 ("Not at all") to 3 ("Nearly every day"). The total score ranges from 0 to 27, with higher scores indicating more severe depressive symptoms. Cut-off scores of 5, 10, 15, and 20 represent thresholds for mild, moderate, moderately severe, and severe depression, respectively. The PHQ-9 is known for its high internal consistency, sensitivity, and specificity, making it a reliable tool for both clinical assessment and research (Carballeira et al., 2007).

### 6.2.4. International trauma questionnaire (ITQ)

The International Trauma Questionnaire (ITQ) is a self-report measure designed to assess post-traumatic stress disorder (PTSD) and complex PTSD (CPTSD) in accordance with the criteria set forth in the International Classification of Diseases, 11th edition (ICD-11). The instrument comprises a number of subscales. The Re-experiencing (RE) subscale assesses the presence and frequency of intrusive memories and flashbacks. The Avoidance (AV) subscale evaluates the extent to which trauma-related thoughts and reminders are avoided. The Threat (TH) subscale captures the degree to which the subject perceives a persistent sense of threat. Furthermore, the ITQ assesses affective dysregulation (AD), encompassing emotional lability, negative self-concept (NSC), which pertains to profound feelings of self-worthlessness, and disturbance in relationships (DR), which gauges challenges in maintaining close interpersonal bonds. Furthermore, the ITQ comprises a composite PTSD subscale and a broader Complex PTSD (CPTSD) subscale, which incorporates symptoms of PTSD along with emotional dysregulation, negative self-concept, and relational disturbances. Each item is rated on a Likert scale, with higher scores indicating greater symptom severity, thereby enabling a comprehensive assessment of the impact of trauma on psychological functioning. The questionnaire includes 18 items that

evaluate symptoms like intrusion, avoidance, emotional dysregulation, and negative self-concept. The ITQ is scored on a Likert scale from 0 ("not at all") to 4 ("extremely"), with higher scores indicating more severe PTSD symptoms (Cloitre et al., 2018).

### 6.2.5. Brief resilience scale (BRS)

The BRS (Smith et al., 2008) assesses an individual's ability to recover from stress. It consists of 6 items, each rated on a 5-point Likert scale from 1 ("Strongly disagree") to 5 ("Strongly agree"). In this study, the BRS had a Cronbach's alpha of 0.60, indicating moderate reliability.

### 6.2.6. Work exhaustion

Participants were asked to rate their work exhaustion on a scale ranging from "never" to "always" on a 1 to 10 Likert scale. This evaluation served as a filter question, by selecting participants who reported an experienced work exhaustion higher than 6 on a 1–10 rating scale. Correlation between our single item and the full emotional exhaustion subscale of the Copenhagen Burnout Inventory was high ($r = 0.82, p < .001$), confirming convergent validity. However, 33 % of the variance remains unshared - consistent with the single item's focus on "today's" work exhaustion rather than "typical" feelings over weeks.<fnref n="1" />

## 7. Procedure

The survey was completed online via the Qualtrics platform, which ensured the anonymity of responses. The survey was designed to be completed in approximately 15 min. Prior to commencing the burnout

<footnote n="1">¹ We note that single-item measures of fatigue or exhaustion have been widely used and psychometrically evaluated in occupational health research. For example, Wanous et al. (1997) showed that a single exhaustion item achieved test-retest reliability $r = .85$ and correlated $r = .75-.80$ with multi-item scales of emotional exhaustion. Dolbier et al. (2005) also found strong criterion validity of single-item exhaustion ratings against physiological markers (salivary cortisol).</footnote>
<table><caption>**Table 2**
Pearson's r, raw p-value, and the Benjamini-Hochberg FDR-adjusted q-value.</caption><thead><tr><th></th><th>WE</th><th>Age</th><th>ITQ_RE</th><th>ITQ_AV</th><th>ITQ_TH</th><th>ITQ_PTSD</th><th>ITQ_AD</th><th>ITQ_NSC</th><th>ITQ_DR</th><th>ITQ_CPTSD</th><th>GAD-7</th><th>PHQ-9</th><th>CBI_Pers</th><th>CBI_Work</th><th>CBI ann</th><th>BRS</th></tr></thead><tbody><tr><td>Work Exhaustion</td><td>—</td><td>0.149<br/>(<0.001,<br/>&lt;0.001)</td><td>0.154<br/>(<0.001,<br/>&lt;0.001)</td><td>0.182<br/>(<0.001,<br/>&lt;0.001)</td><td>0.216<br/>(<0.001,<br/>&lt;0.001)</td><td>0.207<br/>(<0.001,<br/>&lt;0.001)</td><td>0.151<br/>(<0.001,<br/>&lt;0.001)</td><td>0.141<br/>(<0.001,<br/>&lt;0.001)</td><td>0.180<br/>(<0.001,<br/>&lt;0.001)</td><td>0.183<br/>(<0.001,<br/>&lt;0.001)</td><td>0.292<br/>(<0.001,<br/>&lt;0.001)</td><td>0.251<br/>(<0.001,<br/>&lt;0.001)</td><td>0.401<br/>(<0.001,<br/>&lt;0.001)</td><td>0.402<br/>(<0.001,<br/>&lt;0.001)</td><td>0.290<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.146<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>Age</td><td>0.149<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.172<br/>(<0.001,<br/>&lt;0.001)</td><td>0.202<br/>(<0.001,<br/>&lt;0.001)</td><td>0.194<br/>(<0.001,<br/>&lt;0.001)</td><td>0.213<br/>(<0.001,<br/>&lt;0.001)</td><td>0.119<br/>(0.003,<br/>0.003)</td><td>0.011<br/>(0.792,<br/>0.792)</td><td>0.061<br/>(0.131,<br/>0.132)</td><td>0.068<br/>(0.092,<br/>0.094)</td><td>0.147<br/>(<0.001,<br/>&lt;0.001)</td><td>0.174<br/>(<0.001,<br/>&lt;0.001)</td><td>0.146<br/>(<0.001,<br/>&lt;0.001)</td><td>0.112<br/>(0.005,<br/>0.005)</td><td>0.128<br/>(0.001,<br/>0.001)</td><td>0.149<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_RE</td><td>0.154<br/>(<0.001,<br/>&lt;0.001)</td><td>0.172<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.697<br/>(<0.001,<br/>&lt;0.001)</td><td>0.677<br/>(<0.001,<br/>&lt;0.001)</td><td>0.886<br/>(<0.001,<br/>&lt;0.001)</td><td>0.471<br/>(<0.001,<br/>&lt;0.001)</td><td>0.481<br/>(<0.001,<br/>&lt;0.001)</td><td>0.495<br/>(<0.001,<br/>&lt;0.001)</td><td>0.563<br/>(<0.001,<br/>&lt;0.001)</td><td>0.518<br/>(<0.001,<br/>&lt;0.001)</td><td>0.546<br/>(<0.001,<br/>&lt;0.001)</td><td>0.409<br/>(<0.001,<br/>&lt;0.001)</td><td>0.403<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.229<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_AV</td><td>0.182<br/>(<0.001,<br/>&lt;0.001)</td><td>0.202<br/>(<0.001,<br/>&lt;0.001)</td><td>0.697<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.689<br/>(<0.001,<br/>&lt;0.001)</td><td>0.893<br/>(<0.001,<br/>&lt;0.001)</td><td>0.533<br/>(<0.001,<br/>&lt;0.001)</td><td>0.500<br/>(<0.001,<br/>&lt;0.001)</td><td>0.557<br/>(<0.001,<br/>&lt;0.001)</td><td>0.616<br/>(<0.001,<br/>&lt;0.001)</td><td>0.517<br/>(<0.001,<br/>&lt;0.001)</td><td>0.578<br/>(<0.001,<br/>&lt;0.001)</td><td>0.424<br/>(<0.001,<br/>&lt;0.001)</td><td>0.448<br/>(<0.001,<br/>&lt;0.001)</td><td>0.402<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_TH</td><td>0.216<br/>(<0.001,<br/>&lt;0.001)</td><td>0.194<br/>(<0.001,<br/>&lt;0.001)</td><td>0.677<br/>(<0.001,<br/>&lt;0.001)</td><td>0.689<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.890<br/>(<0.001,<br/>&lt;0.001)</td><td>0.527<br/>(<0.001,<br/>&lt;0.001)</td><td>0.534<br/>(<0.001,<br/>&lt;0.001)</td><td>0.571<br/>(<0.001,<br/>&lt;0.001)</td><td>0.635<br/>(<0.001,<br/>&lt;0.001)</td><td>0.577<br/>(<0.001,<br/>&lt;0.001)</td><td>0.596<br/>(<0.001,<br/>&lt;0.001)</td><td>0.458<br/>(<0.001,<br/>&lt;0.001)</td><td>0.466<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.227<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_PTSD</td><td>0.207<br/>(<0.001,<br/>&lt;0.001)</td><td>0.213<br/>(<0.001,<br/>&lt;0.001)</td><td>0.886<br/>(<0.001,<br/>&lt;0.001)</td><td>0.893<br/>(<0.001,<br/>&lt;0.001)</td><td>0.890<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.574<br/>(<0.001,<br/>&lt;0.001)</td><td>0.568<br/>(<0.001,<br/>&lt;0.001)</td><td>0.608<br/>(<0.001,<br/>&lt;0.001)</td><td>0.680<br/>(<0.001,<br/>&lt;0.001)</td><td>0.604<br/>(<0.001,<br/>&lt;0.001)</td><td>0.645<br/>(<0.001,<br/>&lt;0.001)</td><td>0.484<br/>(<0.001,<br/>&lt;0.001)</td><td>0.494<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.262<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_AD</td><td>0.151<br/>(<0.001,<br/>&lt;0.001)</td><td>0.119<br/>(0.003,<br/>0.003)</td><td>0.471<br/>(<0.001,<br/>&lt;0.001)</td><td>0.533<br/>(<0.001,<br/>&lt;0.001)</td><td>0.527<br/>(<0.001,<br/>&lt;0.001)</td><td>0.574<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.538<br/>(<0.001,<br/>&lt;0.001)</td><td>0.602<br/>(<0.001,<br/>&lt;0.001)</td><td>0.801<br/>(<0.001,<br/>&lt;0.001)</td><td>0.529<br/>(<0.001,<br/>&lt;0.001)</td><td>0.583<br/>(<0.001,<br/>&lt;0.001)</td><td>0.450<br/>(<0.001,<br/>&lt;0.001)</td><td>0.484<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.227<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_NSC</td><td>0.141<br/>(<0.001,<br/>&lt;0.001)</td><td>0.011<br/>(0.792,<br/>0.792)</td><td>0.481<br/>(<0.001,<br/>&lt;0.001)</td><td>0.500<br/>(<0.001,<br/>&lt;0.001)</td><td>0.534<br/>(<0.001,<br/>&lt;0.001)</td><td>0.568<br/>(<0.001,<br/>&lt;0.001)</td><td>0.538<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.654<br/>(<0.001,<br/>&lt;0.001)</td><td>0.874<br/>(<0.001,<br/>&lt;0.001)</td><td>0.604<br/>(<0.001,<br/>&lt;0.001)</td><td>0.673<br/>(<0.001,<br/>&lt;0.001)</td><td>0.492<br/>(<0.001,<br/>&lt;0.001)</td><td>0.494<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.387<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_DR</td><td>0.180<br/>(<0.001,<br/>&lt;0.001)</td><td>0.061<br/>(0.131,<br/>0.132)</td><td>0.495<br/>(<0.001,<br/>&lt;0.001)</td><td>0.557<br/>(<0.001,<br/>&lt;0.001)</td><td>0.571<br/>(<0.001,<br/>&lt;0.001)</td><td>0.608<br/>(<0.001,<br/>&lt;0.001)</td><td>0.602<br/>(<0.001,<br/>&lt;0.001)</td><td>0.654<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.887<br/>(<0.001,<br/>&lt;0.001)</td><td>0.552<br/>(<0.001,<br/>&lt;0.001)</td><td>0.644<br/>(<0.001,<br/>&lt;0.001)</td><td>0.467<br/>(<0.001,<br/>&lt;0.001)</td><td>0.509<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.285<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>ITQ_CPTSD</td><td>0.183<br/>(<0.001,<br/>&lt;0.001)</td><td>0.068<br/>(0.092,<br/>0.094)</td><td>0.563<br/>(<0.001,<br/>&lt;0.001)</td><td>0.616<br/>(<0.001,<br/>&lt;0.001)</td><td>0.635<br/>(<0.001,<br/>&lt;0.001)</td><td>0.680<br/>(<0.001,<br/>&lt;0.001)</td><td>0.801<br/>(<0.001,<br/>&lt;0.001)</td><td>0.874<br/>(<0.001,<br/>&lt;0.001)</td><td>0.887<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.658<br/>(<0.001,<br/>&lt;0.001)</td><td>0.743<br/>(<0.001,<br/>&lt;0.001)</td><td>0.549<br/>(<0.001,<br/>&lt;0.001)</td><td>0.578<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.357<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>GAD-7</td><td>0.292<br/>(<0.001,<br/>&lt;0.001)</td><td>0.147<br/>(<0.001,<br/>&lt;0.001)</td><td>0.518<br/>(<0.001,<br/>&lt;0.001)</td><td>0.517<br/>(<0.001,<br/>&lt;0.001)</td><td>0.577<br/>(<0.001,<br/>&lt;0.001)</td><td>0.604<br/>(<0.001,<br/>&lt;0.001)</td><td>0.529<br/>(<0.001,<br/>&lt;0.001)</td><td>0.604<br/>(<0.001,<br/>&lt;0.001)</td><td>0.552<br/>(<0.001,<br/>&lt;0.001)</td><td>0.658<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.796<br/>(<0.001,<br/>&lt;0.001)</td><td>0.684<br/>(<0.001,<br/>&lt;0.001)</td><td>0.694<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.387<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>PHQ-9</td><td>0.251<br/>(<0.001,<br/>&lt;0.001)</td><td>0.174<br/>(<0.001,<br/>&lt;0.001)</td><td>0.546<br/>(<0.001,<br/>&lt;0.001)</td><td>0.578<br/>(<0.001,<br/>&lt;0.001)</td><td>0.596<br/>(<0.001,<br/>&lt;0.001)</td><td>0.645<br/>(<0.001,<br/>&lt;0.001)</td><td>0.583<br/>(<0.001,<br/>&lt;0.001)</td><td>0.673<br/>(<0.001,<br/>&lt;0.001)</td><td>0.644<br/>(<0.001,<br/>&lt;0.001)</td><td>0.743<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.796<br/>(<0.001,<br/>&lt;0.001)</td><td>0.646<br/>(<0.001,<br/>&lt;0.001)</td><td>0.662<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.350<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>CBI_Pers</td><td>0.401<br/>(<0.001,<br/>&lt;0.001)</td><td>0.146<br/>(<0.001,<br/>&lt;0.001)</td><td>0.409<br/>(<0.001,<br/>&lt;0.001)</td><td>0.424<br/>(<0.001,<br/>&lt;0.001)</td><td>0.458<br/>(<0.001,<br/>&lt;0.001)</td><td>0.484<br/>(<0.001,<br/>&lt;0.001)</td><td>0.450<br/>(<0.001,<br/>&lt;0.001)</td><td>0.492<br/>(<0.001,<br/>&lt;0.001)</td><td>0.467<br/>(<0.001,<br/>&lt;0.001)</td><td>0.549<br/>(<0.001,<br/>&lt;0.001)</td><td>0.684<br/>(<0.001,<br/>&lt;0.001)</td><td>0.646<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.804<br/>(<0.001,<br/>&lt;0.001)</td><td>0.538<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.319<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>CBI_Work</td><td>0.402<br/>(<0.001,<br/>&lt;0.001)</td><td>0.112<br/>(0.005,<br/>0.005)</td><td>0.403<br/>(<0.001,<br/>&lt;0.001)</td><td>0.448<br/>(<0.001,<br/>&lt;0.001)</td><td>0.466<br/>(<0.001,<br/>&lt;0.001)</td><td>0.494<br/>(<0.001,<br/>&lt;0.001)</td><td>0.484<br/>(<0.001,<br/>&lt;0.001)</td><td>0.494<br/>(<0.001,<br/>&lt;0.001)</td><td>0.509<br/>(<0.001,<br/>&lt;0.001)</td><td>0.578<br/>(<0.001,<br/>&lt;0.001)</td><td>0.695<br/>(<0.001,<br/>&lt;0.001)</td><td>0.662<br/>(<0.001,<br/>&lt;0.001)</td><td>0.804<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.654<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.335<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>CBI ann</td><td>0.290<br/>(<0.001,<br/>&lt;0.001)</td><td>0.128<br/>(0.001,<br/>0.001)</td><td>0.379<br/>(<0.001,<br/>&lt;0.001)</td><td>0.402<br/>(<0.001,<br/>&lt;0.001)</td><td>0.446<br/>(<0.001,<br/>&lt;0.001)</td><td>0.460<br/>(<0.001,<br/>&lt;0.001)</td><td>0.389<br/>(<0.001,<br/>&lt;0.001)</td><td>0.340<br/>(<0.001,<br/>&lt;0.001)</td><td>0.432<br/>(<0.001,<br/>&lt;0.001)</td><td>0.450<br/>(<0.001,<br/>&lt;0.001)</td><td>0.541<br/>(<0.001,<br/>&lt;0.001)</td><td>0.510<br/>(<0.001,<br/>&lt;0.001)</td><td>0.538<br/>(<0.001,<br/>&lt;0.001)</td><td>—</td><td>0.654<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.239<br/>(<0.001,<br/>&lt;0.001)</td></tr><tr><td>BRS</td><td>-0.146<br/>(<0.001,<br/>&lt;0.001)</td><td>0.149<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.229<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.244<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.227<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.262<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.227<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.387<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.285<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.357<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.387<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.357<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.350<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.319<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.335<br/>(<0.001,<br/>&lt;0.001)</td><td>-0.239<br/>(<0.001,<br/>&lt;0.001)</td></tr></tbody></table>

Notes: r = Pearson's coefficient. Raw p-values and FDR-adjusted q-values are shown as (p, q). All entries with raw p<.001 remain highly significant after correction, with q < 0.001. Cells show r (p, q). All p<.001 entries have q < 0.001; the six non-<0.001 p-values and their corresponding q-values are given explicitly.
<table><caption>**Table 3**
Regression analysis.</caption><thead><tr><th rowspan="2">Effect</th><th rowspan="2">Estimate</th><th rowspan="2">SE</th><th colspan="2">95 % Confidence Intervals</th><th rowspan="2">β</th><th rowspan="2">df</th><th rowspan="2">t</th><th rowspan="2">p</th></tr><tr><th>Lower</th><th>Upper</th></tr></thead><tbody><tr><td>(Intercept)</td><td>7.4638</td><td>0.0555</td><td>7.3548</td><td>7.5728</td><td>-0.0056</td><td>604</td><td>134.4762</td><td>&lt;0.001</td></tr><tr><td>PHQ-9</td><td>-0.0172</td><td>0.0179</td><td>-0.0524</td><td>0.0180</td><td>-0.0670</td><td>604</td><td>-0.9575</td><td>0.339</td></tr><tr><td>GAD-7</td><td>-0.0017</td><td>0.0195</td><td>-0.0400</td><td>0.0365</td><td>-0.0058</td><td>604</td><td>-0.0891</td><td>0.929</td></tr><tr><td>ITQ-Re-experiencing</td><td>-0.0442</td><td>0.0643</td><td>-0.1705</td><td>0.0821</td><td>-0.0597</td><td>604</td><td>-0.6871</td><td>0.492</td></tr><tr><td>ITQ_Avoidance</td><td>-0.0376</td><td>0.0643</td><td>-0.1638</td><td>0.0886</td><td>-0.0522</td><td>604</td><td>-0.5850</td><td>0.559</td></tr><tr><td>ITQ Post-Traumatic Stress Disorder</td><td>0.0426</td><td>0.0397</td><td>-0.0353</td><td>0.1205</td><td>0.1586</td><td>604</td><td>1.0734</td><td>0.284</td></tr><tr><td>ITQ Negative Self-Concept</td><td>-0.0260</td><td>0.0557</td><td>-0.1355</td><td>0.0834</td><td>-0.0420</td><td>604</td><td>-0.4672</td><td>0.640</td></tr><tr><td>ITQ Disturbance in Relationships</td><td>0.0499</td><td>0.0602</td><td>-0.0685</td><td>0.1682</td><td>0.0758</td><td>604</td><td>0.8275</td><td>0.408</td></tr><tr><td>ITQ Complex PTSD</td><td>-0.0463</td><td>0.0410</td><td>-0.1269</td><td>0.0343</td><td>-0.1720</td><td>604</td><td>-1.1284</td><td>0.260</td></tr><tr><td>CBI Personal burnout</td><td>0.0963</td><td>0.0249</td><td>0.0474</td><td>0.1453</td><td>0.2468</td><td>604</td><td>3.8627</td><td>&lt;0.001</td></tr><tr><td>CBI Work-related burnout</td><td>0.0527</td><td>0.0211</td><td>0.0112</td><td>0.0942</td><td>0.1786</td><td>604</td><td>2.4967</td><td>0.013</td></tr><tr><td>CBI Client-related burnout</td><td>0.0001</td><td>0.0139</td><td>-0.0272</td><td>0.0274</td><td>0.0003</td><td>604</td><td>0.0067</td><td>0.995</td></tr><tr><td>Brief Resilience Scale</td><td>-0.0026</td><td>0.0174</td><td>-0.0367</td><td>0.0315</td><td>-0.0061</td><td>604</td><td>-0.1482</td><td>0.882</td></tr><tr><td>Men - Women</td><td>0.2621</td><td>0.1199</td><td>0.0267</td><td>0.4976</td><td>0.1663</td><td>604</td><td>2.1863</td><td>0.029</td></tr><tr><td>Age</td><td>0.0148</td><td>0.0051</td><td>0.0047</td><td>0.0249</td><td>0.1051</td><td>604</td><td>2.8908</td><td>0.004</td></tr></tbody></table>

Note. This table displays the parameter estimates (coefficients) from a linear regression analysis assessing the predictors of work exhaustion. The table includes the unstandardized coefficients (Estimate), standard errors (SE), 95 % confidence intervals (Lower and Upper), standardized coefficients (β), degrees of freedom (df), t-values (t), and significance levels (p). The predictors include PHQ-9 for depression, GAD-7 for anxiety, CBI subscales for burnout and demographic factors (sex, age). The standardized coefficients (β) are presented for each predictor within the model.

and mental health assessments, participants were required to provide informed consent and furnish the researchers with information pertaining to their demographic characteristics. To mitigate the potential impact of order effects, the presentation of the questionnaires was randomized for each participant. Following the completion of the survey, participants were provided with a debriefing session, during which the objectives of the study was outlined and resources on mental well-being and strategies to manage burnout were made available. Throughout the study, confidentiality was maintained, and all data were stored securely in compliance with the Ethics Committee of the University of Paris Nanterre and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards

### 7.1. Statistical analysis

Correlation analyses will be conducted to examine the relationships between the CBI, and participants' perceptions of burnout and the mental health variables (PHQ-9, GAD-7, BRS) will be examined to explore the expected relationships between burnout, depression, anxiety, and resilience.

Multiple regression analyses will be employed to identify significant predictors of work exhaustion as the dependent variable. Predictors will include the dimensions of the CBI, PHQ-9 scores, GAD-7 scores, BRS scores, and demographic variables (age and sex). The regression models will test the primary and secondary hypotheses by determining whether personal burnout (CBI) is a significant predictors of work exhaustion, while controlling for other factors. Bivariate Pearson correlations between all continuous variables were calculated and adjusted for multiple comparisons using the Benjamini-Hochberg FDR procedure ($q < 0.05$). Regression analyses then tested the unique contribution of each predictor; given the single-model framework, no further correction was applied to regression coefficients.

Hierarchical multiple regressions were also used to examine the incremental contribution of demographic variables, personal resources and psychopathology, burnout dimensions, and trauma symptoms in predicting work exhaustion (N = 627). All predictors were mean-centered, and collinearity diagnostics confirmed acceptable variance inflation factors (VIFs = 1.07–4.11).

## 8. Results

### 8.1. Correlation analysis

Pearson product-moment correlations between all study variables are presented in Table 2 (pairwise Ns = 622–653). To control for false discovery rate across the 120 tests, p-values were adjusted using the Benjamini-Hochberg procedure; both raw p-values and FDR-adjusted q-values are reported. Work exhaustion was positively correlated with CBI personal burnout, r(653) = 0.401, $p < .001$, $q < 0.001$, and CBI work-related burnout, r(653) = 0.402, $p < .001$, $q < 0.001$, and showed moderate associations with depressive symptoms, PHQ-9, r(645) = 0.251, $p < .001$, $q < 0.001$, and anxiety symptoms, GAD-7, r(646) = 0.292, $p < .001$, $q < 0.001$. Work exhaustion also correlated significantly, albeit weaker, with all ITQ subscales, $rs = 0.154–0.216$, $ps < 0.001$, $qs < 0.001$, and negatively with resilience, r(627) = -0.146, $p < .001$, $q < 0.001$. Age showed a small positive correlation with work exhaustion, r(653) = 0.149, $p < .001$, $q < 0.001$. For age and trauma, only the correlation between age and the ITQ Affective Dysregulation subscale survived correction, r(622) = 0.119, $p = .003$, $q = 0.003$; age was not associated with the ITQ Negative Self-Concept, r(622) = 0.011, $p = .792$, $q = 0.792$, the ITQ Disturbance in Relationships, r(622) = 0.061, $p = .131$, $q = 0.132$, or the ITQ CPTSD Total, r(622) = 0.068, $p = .092$, $q = 0.094$. All other correlations that were significant at the unadjusted level ($p < .001$) remained significant after FDR correction ($q < 0.001$). We found that work exhaustion was significantly and positively correlated with age (r(653) = 0.15, $p < .001$). The CBI subscales, including Personal Burnout, Work-related Burnout, and Client-related Burnout, all exhibited a statistically significant positive correlation with work exhaustion. The strongest correlation was observed with the CBI Work-related Burnout subscale (r(653) = 0.40, $p < .001$), followed closely by the CBI Personal Burnout subscale (r(653) = 0.40, $p < .001$) and the CBI Client-related Burnout subscale (r(653) = 0.29, $p < .001$). Additionally, mental health variables demonstrated significant correlations with burnout measures. The Generalized Anxiety Disorder Scale (GAD-7) and the Patient Health Questionnaire (PHQ-9) was significantly correlated with work exhaustion, with r(646) = 0.29, $p < .001$ and r(645) = 0.25, $p < .001$, respectively. Additionally, the GAD-7 and PHQ-9 scores showed a significant positive correlation with CBI Work-related Burnout ($r = 0.72, p < .001$; $r = 0.66, p < .001$). Notably, the Brief Resilience Scale (BRS) demonstrated a negative correlation with work exhaustion (r(627) = -0.15, $p < .001$) and all dimensions of burnout as measured by the CBI. We found significant correlations between work
exhaustion and several subscales of the International Trauma Questionnaire (ITQ). A small positive correlation was found between work exhaustion and both the ITQ Re-experiencing ($r = 0.1538, p < .001$) and Avoidance ($r = 0.1815, p < .001$) subscales. The correlation with the ITQ Threat subscale was slightly stronger ($r = 0.2162, p < .001$), indicating an association between work exhaustion and feeling threatened. Moderate correlations were observed between work exhaustion and PTSD symptoms ($r = 0.2072, p < .001$) and complex PTSD ($r = 0.1830, p < .001$), suggesting that work exhaustion is associated with higher levels of trauma-related symptoms. Although these correlations are moderate, they highlight the relationship between occupational stress and trauma (see Table 2).

## 8.2. Multiple regression analyses

The CBI Personal Burnout subscale was also found to be a significant positive predictor of work exhaustion, $F(1, 604) = 14.92, p < .001, η^2p = 0.024$, indicating that higher personal burnout was associated with increased work exhaustion. Similarly, the CBI Work-related Burnout subscale showed a positive association with work exhaustion, $F(1, 604) = 6.23, p = .013, η^2p = 0.010$.

Sex and age were also significant predictors of work exhaustion. Specifically, sex showed a significant effect, $F(1, 604) = 4.78, p = .029, η^2p = 0.008$, with men reporting higher work exhaustion than women. Age was also positively associated with work exhaustion, $F(1, 604) = 8.36, p = .004, η^2p = 0.014$, indicating that older individuals reported higher levels of work exhaustion. Other predictors, including PHQ-9, GAD-7, and the remaining ITQ subscales, did not significantly contribute to the prediction of work exhaustion in this model, suggesting that these variables were less relevant in explaining variations in work exhaustion.

Parameter estimates further clarified the contributions of each predictor. CBI Personal Burnout and Work-related Burnout both had a significant positive estimate ($β = 0.247, p < .001$ and $β = 0.179, p = .013$, respectively), reinforcing their significant impact on work exhaustion. Sex and age were significant with estimates of $β = 0.166, p = .029$ and $β = 0.105, p = .004$, respectively, indicating that being male and older age were associated with higher work exhaustion (see Table 3).

For hierarchical regressions, in Step 1, age and gender accounted for a significant but small amount of variance in work exhaustion, $R = 0.147, R^2 = 0.022, F(2, 624) = 6.93, p = .001$. After adding the Brief Resilience Scale, PHQ-9, and GAD-7 in Step 2, there was a significant increase in explained variance, $ΔR^2 = 0.093, FΔ(3, 621) = 21.79, p < .001$. The overall model was also significant, $R = 0.339, R^2 = 0.115, F(5, 621) = 16.12, p < .001$. In Step 3, the inclusion of the three CBI burnout subscales (personal, work-related, client-related) produced another significant increment, $ΔR^2 = 0.101, FΔ(3, 618) = 26.66, p < .001$, with the model reaching $R = 0.465, R^2 = 0.216, F(8, 618) = 21.32, p < .001$. Finally, adding the aggregated ITQ score in Step 4 did not significantly improve the prediction of work exhaustion, $ΔR^2 = 0.001, FΔ(1, 617) = 0.75, p = .388$; the full model remained significant, $R = 0.466, R^2 = 0.217, F(9, 617) = 19.03, p < .001$.

We examined variance inflation factors (VIFs) and tolerances for all predictors in our multiple regression. Most variables had acceptable collinearity ($VIF < 5$), but the five ITQ subscales had VIFs ranging from 6.12 to 18.81, indicating redundancy among trauma-related constructs. To address this, we computed a single ITQ total score (sum of all subscales), which yielded a VIF of 3.52 and a tolerance of 0.28-well within acceptable limits. We then re-ran the regression, substituting the ITQ total for the individual subscales. Replacing the ITQ subscales with an ITQ-total score ($N = 622$) yielded $R^2 = 0.2452, F(12, 609) = 16.48, p < .001$. As before, only emotional exhaustion, depersonalization, personal and work burnout, age, and gender significantly predicted work exhaustion; ITQ total score remained nonsignificant ($β = -0.047, p = .415$). These results confirm that our conclusions are robust to how

trauma symptoms are represented and are not an artifact of multicollinearity. Both approaches yielded essentially identical patterns: ITQ (subscales or total) remained nonsignificant, and the same predictors (personal and work burnout, age, gender) emerged as significant.

## 9. Discussion

The objective of this study was to identify predictors of work exhaustion in a general population sample, with a particular focus on the role of various psychological and demographic factors. A regression model was employed to examine the contribution of depression (PHQ-9), anxiety (GAD-7), Copenhagen Burnout Inventory (CBI), and trauma-related symptoms (assessed by the International Trauma Questionnaire [ITQ]) to work exhaustion. The findings indicated that certain dimensions of burnout and demographic factors were notable predictors of work exhaustion, whereas other psychological variables, such as depression, anxiety, and select trauma-related subscales, did not significantly contribute to the model.

The CBI Personal Burnout and CBI Work-related Burnout subscales were significant predictors, thereby underscoring the impact of both personal and work-specific burnout on overall work exhaustion. These findings align with prior research that underscores the significance of burnout in elucidating work exhaustion and its deleterious impact on employee well-being and job performance (Schaufeli et al., 2009).

In contrast, the regression analysis indicated that the ITQ subscales, which assess a range of trauma-related symptoms, were not significant predictors of work exhaustion. This finding was somewhat unexpected, given the established links between trauma, PTSD, and burnout in occupational settings (Brower, 2021; Blevins et al., 2015). The only trauma-related predictor that approached significance was the ITQ Post-Traumatic Stress Disorder (PTSD) subscale, indicating that while trauma may contribute to work exhaustion, its effects may be more complex or influenced by other factors not included in this study. Prior research has underscored the contribution of trauma to burnout, particularly in high-stress domains such as healthcare and emergency services (Beck et al., 2015; Sinclair and McFadden, 2017). However, the absence of notable findings in the present study may indicate that trauma's influence on work exhaustion is less direct in the general population, or that other moderating factors, like social support or individual resilience, play a pivotal role in mitigating these effects.

Furthermore, the analysis revealed that both sex and age were significant predictors of work exhaustion. The results indicated that male respondents exhibited higher levels of work exhaustion than their female counterparts. Additionally, older age was associated with increased work exhaustion. These findings are surprisingly at odds with previous literature suggesting that women are generally considered to be at higher risk for experiencing burnout and work-related stress than men, although in this study the higher proportion of men (53%) seeking help may reflect a bias in help-seeking behavior rather than actual risk. This may be due to differences in job expectations, coping strategies, and career stages (Ahola et al., 2014; Purvanova and Muros, 2010). The observation that older individuals experience increased levels of work exhaustion may reflect the increased levels of responsibility that often come with age, rather than issues related to declining physical health or diminished abilities. (Schaufeli and Enzmann, 1998). These results suggest that personal and work-related burnout are important predictors of work exhaustion in our sample of French workers; however, without data on specific occupations or industries, these conclusions must be considered preliminary and may not generalize to all job types.

### 9.1. Implications for burnout management

Emotional exhaustion seems to plays an important role in predicting work exhaustion. This shows that we need to do more to help people with this aspect of burnout. Organizations should focus on reducing emotional demands and enhancing emotional resilience among
employees. This could include stress management workshops, access to mental health resources, and a supportive work environment (Leiter and Maslach, 2014). Emotional exhaustion is strongly linked to work exhaustion. Addressing this aspect of burnout will have the biggest impact on improving employee well-being and reducing overall work-related stress.

The non-significant role of trauma-related symptoms in predicting work exhaustion in this study gives rise to questions concerning the interaction between trauma and work-related stress. It is possible that the effects of trauma on work exhaustion are indirect, influenced by factors such as social support, job control, or individual resilience. Future research should explore these potential mediating factors and consider using longitudinal designs to better capture the dynamic nature of trauma and its impact on work exhaustion over time (Bonanno et al., 2011). Additionally, it may be beneficial to examine specific occupational groups or settings where trauma is more common to better understand its impact on burnout and work exhaustion.

We also found that different groups have different needs. Interventions should be tailored to address these needs. Older workers may need support to cope with the specific demands of their work, such as the emotional strain and workload in the care sector, or the increased responsibilities and workload in large corporations. Similarly, interventions that address the different experiences of men and women in the workforce could help reduce burnout and promote well-being. Research has shown that men and women may experience burnout differently, with women often reporting higher levels of emotional exhaustion (Purvanova and Muros, 2010).

## 9.2. Limitations

This study provides valuable insights into predictors of work exhaustion, but has some limitations. First, the study design does not allow us to draw causal conclusions. The results show a link between the factors, but we don't know if one causes the other. Longitudinal studies are needed to explore how these factors interact and to identify potential causes (Taris and Kompier, 2003).

Second, the self-report measures could be biased. People might have underreported or overreported their levels of work exhaustion, burnout, or trauma-related symptoms because of social desirability or recall biases. Future research could benefit from incorporating objective measures to complement self-report data.

Another limitation is the multicollinearity among the predictors, particularly the ITQ subscales. Despite the use of the Lasso regression approach to address issues of multicollinearity, some predictors were still aliased or removed from the model due to high correlations. This indicates that the ITQ subscales may have similar measurement properties with regard to trauma-related constructs, which makes it difficult to identify their specific contributions to work exhaustion (Dormann et al., 2013). It would be beneficial for future studies to consider the use of alternative statistical techniques, such as factor analysis, in order to better differentiate the distinct dimensions of trauma and their effects on work-related outcomes. Morover, all outcomes were assessed using validated self-report questionnaires, which, while reliable, are inherently subject to participants' current mood, recall, and social desirability biases. Future studies would benefit from supplementing self-report measures with more objective indices of exhaustion and stress (e.g., physiological markers such as salivary cortisol or heart rate variability, passive digital work activity logs, or performance-based cognitive tasks) to triangulate findings and reduce common method variance. Although our single-item measure for Work Exhaustion has established face and criterion validity, its discriminant validity relative to multidimensional burnout requires further investigation. Future research should include both multi-item work fatigue scales (e.g., Shirom-Melamed Work Fatigue Inventory) and objective indicators (e.g., heart rate variability) to confirm that the constructs are separable.

In addition, the generalizability of the findings may be limited by the

specific characteristics of the sample. The study was conducted in a general population sample in France, and the findings may not be fully applicable to other cultural contexts or professional groups (Schaufeli, 2017). Replication of the study in different settings and with different populations would help to establish the robustness of the findings and explore potential cultural or contextual differences in predictors of work exhaustion (Maslach and Leiter, 2016). Because participants were recruited through convenience sampling via online advertisements rather than probability-based methods, our sample may not perfectly reflect the French workforce. Future studies should replicate these findings in nationally representative or stratified panels to increase generalizability.

Finally, the study did not control for other potential confounding variables, such as job type, organizational culture, or socioeconomic status, that may influence work exhaustion. Future research should aim to include a broader range of contextual factors to provide a more comprehensive understanding of the determinants of work exhaustion (Bakker and Demerouti, 2007).

## 10. Conclusion

The findings show that personal burnout is an important factor contributing to work-related stress. The study raises questions about how trauma affects work exhaustion and the need for more research.

These findings have a significant impact. They show that we need to have different ways of helping people with burnout. We also need to think about different groups of people. As organizations deal with employee well-being and productivity, it is essential to develop strategies that promote resilience, reduce burnout, and enhance work satisfaction. Work exhaustion is not just about individuals and to tackle it, we need to support people and create healthy workplaces: given that they are replicated, these results help us do that by providing insights for more informed and impactful interventions.

### Data availability

The data that support the findings can be requested from the Authors

### Funding statement

This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.

### Ethics approval statement

All procedures involving human participants performed in this study were in accordance with the Ethics Committee of the University of Paris Nanterre and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Patient consent statement: Informed consent was obtained from all participants included in the study.

### Permission to reproduce material from other sources

Non applicable.

### CRediT authorship contribution statement

**Lucia Romo:** Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Conceptualization.
**Clément Duret:** Writing – original draft, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Conceptualization.
**Laurent Cruchet:** Writing – original draft, Validation, Project administration, Methodology, Data curation.
**Stéphanie Nann:** Writing – original draft, Methodology, Investigation, Data curation.
**Samantha Tessier:** Writing – original draft,
Investigation, Formal analysis. **Oulmann Zerhouni:** Writing – original draft, Formal analysis, Conceptualization.

Declaration of competing interest

All authors declare that they have no conflict of interest.

Acknowledgements

The authors would like to thank Chloé Touzé for her contribution to data gathering.

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