Migraine and work – beyond absenteeism: Migraine severity and occupational burnout

Abstract

Background

Migraine, a condition affecting 12% of the population, is a prevalent cause of disability, significantly impacts individuals during their most productive working years. Several studies have established that a migraine patient's job performance is often limited by absenteeism and presenteeism. The present study aimed to investigate the impact of migraines on occupational burnout, which affects up to 40% of workers.

Methods

A subset of participants from the Negev Migraine Cohort, including both migraine patients and non-migraine controls, were asked to complete the study questionnaire. The main exposures of interest were migraine diagnosis and severity. The primary outcome was occupational burnout. Migraine severity and associated disability were evaluated using the Migraine Disability Assessment (MIDAS) score, psychiatric comorbidities using the Depression, Anxiety and Stress Scale – 21 Items (DASS-21) scale and occupational burnout using the Maslach Burnout Inventory (MBI-GS version) scale. Statistical analyses included multivariable quantile regression models to identify associations and adjust for potential confounders.

Results

In total, 675 migraine patients and 232 non-migraine participants participated in the study. Migraine patients exhibited higher rates of depression (mean DASS-21: 0.864 vs. 0.664, standardized mean difference (SMD) = 0.262), tended to work longer hours (median weekly hours: 40.0 vs. 36.0, SMD = 0.148) and expressed a preference for remote work (20.3% vs. 10.3%, SMD = 0.097). Migraine patients reported significantly higher levels of occupational burnout (mean burnout score: 3.46 vs. 2.82, SMD = 0.469). Controlling for depression, anxiety and stress, migraine diagnosis (25th percentile estimate = 0.67, p = 0.002, 75th percentile estimate = 0.92, p = 0.032) and migraine severity (estimates: 2.2–5.3, p < 0.001 for all) were associated with higher levels of occupational burnout.

Conclusions

Migraine diagnosis and severity is associated with an occupational burnout, after controlling for various psychological and work-related factors. The findings underscore the need for workplace adjustments to support migraine patients’ participation in the work market.

Graphical abstract

This is a visual representation of the abstract.

Keywords

absenteeism commuting time gender differences migraine severity occupational burnout presenteeism remote work work productivity

Introduction

Migraine is a prevalent cause for disability, affecting millions worldwide, with a prevalence of 12% in the general population (1). Because its prevalence peaks in the most productive age groups (25–55 years), it is a significant contributor to migraine-related disability, and to the indirect cost of this disorder (2). Between 35 and 40% of migraine patients reported that, in the last 3 months, they were unemployed (3).

Several studies have addressed the impact of migraine on work productivity using self-reported absenteeism (full days in which a worker does not attend work) and presenteeism (days worked with reduced productivity). Migraine is estimated to cause 16% of US workforce presenteeism, with the migraine-related productivity loss in terms of absenteeism and presenteeism estimated at 2300 USD per year per employee with migraine (4,5).

The concept of occupational burnout was adopted by the World Helath Organization in its 11th Revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon (6). It is defined as a syndrome resulting from chronic workplace stress that has not been successfully managed and characterized by feelings of energy depletion or exhaustion; increased mental distance from one's job, or feelings of negativism or cynicism related to one's job; and reduced professional efficacy (7,8).

Migraine was found to be associated with burnout among nurses and medical residents (9,10). However, these studies often do not clarify whether the observed associations are primarily a result of psychiatric comorbidities, such as depression and anxiety, or the severity of the migraine itself. Most existing research focuses on specific populations (e.g. healthcare workers) and there is a lack of comprehensive studies that consider a broader range of occupational settings and control for potential confounders such as psychiatric comorbidities (11 –14).

Moreover, migraine may impact various aspects of patients’ work life that have not been vigorously studied. Specifically, migraine attacks can compel choosing workplaces in proximity to their residence place (15). Additionally, the struggle to work amidst an ongoing migraine attack can lead to exhaustion and a gradual decline in work involvement overtime (16). The present study aimed to investigate these aspects of migraine-related work impairment.

In this cohort study, we hypothesized that migraine diagnosis and higher migraine severity are associated with increased occupational burnout, controlling for other health characteristics. In the secondary analysis, we aimed to evaluate the relationships between migraine diagnosis, different measures of migraine severity, psychiatric comorbidities and occupational burnout.

Methods

Study population and study design

Setup

This study comprises an observational evaluation of occupational burnout among migraine patients in the southern district of Israel, the Negev region. Overall, 8.2% of the Israeli population lives in this region; 75% are Jewish and 25% are Bedouin. Clalit Health Services, the largest Israeli health maintenance organization (HMO), is also the largest healthcare provider in the Negev region, covering approximately 67% of its 730,000 residents, with primary clinics available in every city, town or settlement. The structure of the healthcare system in Israel is based on a universal coverage system providing primary care through four HMOs. The National Health Insurance Law mandates that all citizens residing in Israel join one of four official non-profit HMOs that are prohibited by law from denying membership.

The Negev Migraine Cohort

In a previous population-based, retrospective, observational cohort study, adult (≥18 years) patients with migraine were identified from the Clalit Health Services database in southern Israel. Diagnoses were based on physician-assigned ICD-9 codes for migraine and/or claims for triptans, between 2000 and 2018. Although used off-label for cluster headache treatment (16), triptans are migraine-specific (17) and are only approved in Israel for the acute treatment of migraine. A 1:2 matched control group was identified as well by gender, age and primary clinic (patients are assigned to clinics based on place of residency associated with socioeconomic status). The methodology, as well as the characteristics of the patients, are detailed in a previous study (18).

Identification of migraine-related impact themes

During 2021, we employed random sampling methods to recruit adult (≥18 years) migraine and non-migraine participants from the Negev Migraine Cohort. Patients were contacted by phone by study personnel and asked to participate in a series of semi-structured focus groups, both in-person and virtual, conducted under the supervision of the principal investigator (GI). Participants were asked how migraine affects their lives, as well as how would their life be different if they did not suffer from migraine. The study questionnaires were then developed based on the themes suggested by the participants, focusing on evaluating the association between migraine diagnosis, severity and occupational burnout.

Overall, 1475 adult migraine patients were contacted to recruit 675 (46%) migraine patients and 515 adult non-migraine participants to recruit 232 (45%) non-migraine participants, as planned. Recruited participants (migraine and non-migraine) received links to the study questionnaire by an external online surveys company, blinded to the migraine status of the participants. The survey company was also responsible for monitoring responses and sending reminders to participants. The study population's flow is shown in Figure 1.

Figure 1.

Flowchart of participant selection from Clalit insured patients aged ≥18 within the southern district, showing the matching process and subsequent filtering to final migraine and non-migraine cohorts.

Data collection

The study questionnaire included both specific items and previously used and validated questionnaires, which specifically addressed themes referred to in the focus groups. The study questionnaire also included a question regarding migraine status to confirm the study group of each participant. None of the participants reported a diagnosis that contradicted the physician-assigned diagnosis. The following segments were included in the questionnaire:

Demographic data and Self-Rated Health – this form gathered information about the participant's age, sex, ethnicity, marital status, socioeconomic status, smoking, physical activity and comorbid conditions.

The Depression, Anxiety and Stress Scale – 21 Items (DASS-21) – a set of three self-report scales designed to measure the emotional states of depression, anxiety, and stress. Each of the three DASS-21 scales contains seven items, divided into subscales with similar content. The DASS-21 has been validated in multiple studies, with Cronbach's alpha ranging from 0.77 to 0.91 (19).

Migraine Patient-Reported Outcome Measures (PROMs): The Migraine Disability Assessment (MIDAS) – a tool to assess the impact of migraine on a patient daily activity. The questionnaire captures information on disability in terms of missed days of paid work (or school), household work (chores) and non-work time (family, social and leisure activities). The score ranges from 0 to 450, with higher scores indicating more severe disability. The MIDAS has been validated in multiple studies, with Cronbach's alpha ranging from 0.79 to 0.89 (20,).

Employment status – this form gathered information about the participant's employment status, working hours, workplace commuting time, desire to work from home and tenure at the workplace.

Maslach Burnout Inventory (MBI-GS version) (21) – a psychological assessment instrument self-report tool designed to assess the degree of occupational burnout. The questionnaire consists of 16 items divided into three dimensions exhaustion, cynicism, and professional integrity. Responses are given on a scale of 1 to 7, with a high score indicating high burnout. In a study by Kellerman (22), the tool had a general reliability of alpha = 0.87, whereas the exhaustion dimension had a reliability of 0.89, cynicism was 0.69 and professional integrity was 0.72.

Statistical analysis

The primary outcome of this study was occupational burnout. The main exposures of interest were migraine diagnosis and migraine severity, as measured using the MIDAS score. We hypothesized that migraine diagnosis and higher migraine severity would be associated with higher levels of occupational burnout. The sample size, comprising 675 migraine patients and 232 non-migraine participants, was determined to ensure sufficient power to detect a minimal effect size of 3% in occupational burnout, with 80% statistical power and a significance level of 0.05. These target numbers were determined based on the assumptions extracted from the previous studies (8,9).

For descriptive statistics, we used the mean ± SD for normally distributed quantitative variables, medians and ranges for non-normally distributed quantitative variables, and percentages for qualitative variables. For univariate analyses, we used appropriate statistical tests. A chi-squared test was used for categorical variables, with Fisher's exact test when needed. Continuous variables were compared using t-tests for normally distributed variables and a Mann–Whitney U-test for non-normally distributed variables.

To identify factors associated with occupational burnout, we initially performed univariate analyses using Spearman's rank-order non-parametric correlation test in the entire cohort and subgroups of migraine and non-migraine participants. However, the primary analyses employed multivariable quantile regression for multiple quantiles (τ = 0.25, 0.5 and 0.75). The primary outcome was occupational burnout, and the main exposure of interest was migraine diagnosis. This approach allowed us to examine how the effect of migraine on burnout varied across different points of the burnout distribution. These models were adjusted to selected covariates based on the results of the univariable analysis, as well as on clinical or epidemiological significance using a directed acyclic graph (DAG) to represent associations between variables. The DAG connecting migraine exposure (diagnosis and severity) with occupational burnout is depicted in Figure 2. In the DAG, arrows between variables indicate an association and unconnected variables have no direct association. All statistical analyses were performed considering the DAG framework and including chosen covariates to minimize the bias of the estimands of migraine exposure on study outcomes.

Figure 2.

Demographics variables: age, ethnicity, gender, educational status and socioeconomic status. Work-related variables: commuting time and working Hours. Psychiatric comorbidities: depression, anxiety and stress.

Estimates and 95% confidence intervals (CIs) are shown along with p-values for all the models.

Controls were matched to migraine patients based on age (±1 year), sex and primary clinic in the initial retrospective cohort. We aimed to recruit matched controls to complete the questionnaires, but exact matching was not always achieved. Consequently, if a standardized mean difference (SMD) above 0.1 was observed, the multivariable models were adjusted to account for these differences, ensuring valid comparisons.

To assess the association between migraine severity, as measured by the MIDAS score, and occupational burnout, we fitted quantile regression models at five different quantiles adjusted for various covariates. The resulting regressions lines for each quantile were plotted to visualize these relationships.

Finally, we conducted a subgroup analysis by gender to examine the effect of migraine severity on occupational burnout, and to compare the results between males and females.

For all analyses, p < 0.05 (two-sided) was considered statistically significant. Statistical analyses were performed using the RStudio, version 1.4.2.2 (RStudio: Integrated Development for R. RStudio Inc., Boston, MA, US). The study was approved by the Soroka Medical Center Institutional Review Board.

Results

In total, 675 participants with migraine and 232 without migraine (≥18 years) were included in the analysis. Table 1 presents the demographic and self-reported health characteristics. Most of the population was female (80.6% of the migraine group and 80.2% non-migraine participants). Migraine patients were younger (median age of 43.0 years vs. 49.0 years; SMD = 0.591 years), had a higher number of children (SMD = 0.302) and were less educated (completed education beyond the high school level, such as university, or other advanced degrees) (SMD = 0.372). There was no significant difference in self-rated health, smoking status or presence of comorbid cardiovascular diseases including heart disease, hypertension or diabetes.

Table 1.

Demographic and self rated health characteristics.

Demographic	Migraine(n = 675)	Non-migraine(n = 232)	SMD
Gender: female, n (%)	544 (80.6%)	186 (80.2%)	0.011
Age, median [Q1, Q3]	43.0 [34.0, 54.0]	49.0 [39.0, 66.0]	0.591
Marital status, n (%)
Married	405 (60.0%)	146 (62.9%)	0.189
Number of children, mean (SD)	2.87 (1.34)	3.31 (1.57)	0.302
Education level, n (%)
Post-secondary education	243 (36.0%)	103 (44.4%)	0.372
Self-Rated Health Status, mean (SD) (1–10, with 1 being poor and 10 being excellent)	7.48 (2.05)	7.85 (1.81)	0.190
Comorbid cardiovascular diseases, n (%)	71 (10.5%)	28 (12.1%)	0.050
Smoking, n (%)	173 (25.6%)	42 (18.1%)	0.180

Abbreviation: SMD = standardized mean difference.

Table 2 presents the migraine-related characteristics. The median age of onset of symptoms was 20.0 years (interquartile range (IQR) = 15.0–27.0 years). The median age of diagnosis was 24.0 years (IQR = 18.0–30.0 years). Some 39% of the migraine-suffering participants were using migraine preventive therapy. The median MIDAS score was 30.0 (IQR = 15.0–64.0), with the majority (65.0%) of participants reporting severe disability. The median monthly migraine-related medical leave days was 2.0 days (IQR = 0.0–3.0 days) and the median number of days with reduced productivity at work due to migraine was 3.0 days (IQR = 1.0–5.0 days). All these patient-reported outcome measures, including headache days and intensity, absenteeism and presenteeism, were significantly higher for migraine patients compared to non-migraine participants (p < 0.001 for all). Migraine patients were also more likely than non-migraine participants to be depressed (SMD = 0.262), or under stress (SMD = 0.348), but there was no significant difference in anxiety status.

Table 2.

Migraine-related characteristics and patient-reported outcome measures (PROMs).

Characteristics	Migraine(n = 675)	Non-migraine(n = 232)	SMD
Onset age, median [Q1, Q3]	20.0 [15.0, 27.0]	NA	NA
Diagnosis age, median [Q1, Q3]	24.0 [18.0, 30.0]	NA	NA
Treated by migraine preventive drugs, n (%)	263 (39.0%)	NA	NA
MIDAS score, median [Q1, Q3]	30.0 [15.0, 64.0]	NA	NA
Headache days in last three months (MIDAS A),
median [Q1, Q3]	10.0 [5.0, 20.0]	1.00 [0, 6.0]	0.698
Headache intensity (1–10) (MIDAS B), median [Q1, Q3]	8.00 [7.0, 9.0]	4.00 [1.0, 7.0]	1.495
MIDAS score groups, n (%)
Little or no disability (0–5)	77 (11.4%)	NA	NA
Mild disability (6–10)	40 (6.0%)	NA	NA
Moderate disability (11–20)	119 (17.6%)	NA	NA
Severe disability (21+)	439 (65.0%)	NA	NA
Absenteeism days per month, median [Q1, Q3]	2.0 [0, 3.0]	0 [0, 1.0]	0.347
Presenteeism days per month, median [Q1, Q3]	3.0 [1.0, 5.0]	0 [0, 1.0]	0.626
DASS-21
Depression Symptoms Scale (0–3), mean (SD)	0.864 (0.811)	0.664 (0.712)	0.262
Anxiety Symptoms Scale (0–3), mean (SD)	0.776 (0.776)	0.693 (0.772)	0.107
Stress Symptoms Scale (0–3), mean (SD)	1.23 (0.876)	0.931 (0.819)	0.348

Abbreviations: DASS-21 = Depression, Anxiety and Stress Scale – 21 Items; NA = not available; MIDAS = Migraine Disability Assessment; SMD = standardized mean difference.

Table 3 presents employment and burnout characteristics. The employment rate was similar among migraine patients (89.9%) and non-migraine participants (90.9%) (SMD = 0.139%). Employed migraine patients worked more weekly hours (40.0 hours, IQR = 21.0–45.0 hours) compared to employed non-migraine participants (36.0 hours, IQR = 27.0–42.0 hours, SMD = 0.148 hours). Commuting time was similar among employed migraine patients (15.0 minutes, IQR = 10.0–30.0 minutes) and employed non-migraine participants (SMD = 0.112 minutes). migraine participants reported higher self-efficiency when working from home compared to non-migraine participants (5.0, IQR = 3.0–7.0 vs. 4.0 IQR = 1.0–5.0, SMD = 0.556). Burnout MBI-GS score was higher for employed migraine patients than employed non-migraine participants (3.46 vs. 2.82; SMD = 0.468). This difference was also reflected in higher mean scores for exhaustion, cynicism and professional efficacy (p < 0.05 for all).

Table 3.

Employment and burnout characteristics.

Characteristics		Migraine(n = 675)	Non- migraine(n = 232)	SMD
Currently working, n (%)		607 (89.9%)	211 (90.9%)	0.139
Male		122 (93.1%)	40 (87.0%)	0.067
Female		485 (89.2%)	171 (91.9%)	0.162
Years of experience in current workplace Mean (SD)		10.0 (8.97)	13.8 (11.7)	0.190
Median [Q1, Q3]		6.0 [2.0, 14.0]	7.0 [2.0, 16.0]
Weekly work hours, mean (SD)		35.1 (16.9)	32.7 (15.3)	0.148
Median [Q1, Q3]		40.0 [21.0, 45.0]	36.0 [27.0, 42.0]
Commuting time to workplace (minutes) Mean (SD)		29.6 (38.1)	25.7 (21.4)	0.112
Median [Q1, Q3]		15.0 [10.0, 30.0]	15.0 [10.0, 30.0]
MIDAS score groups	Little or no disability (0–5)	20.0 [10.0, 30.0]	19.0 [15.0, 40.0]
	Mild disability (6–10)	20.0 [10.0, 28.0]	11.0 [8.0, 30.0]
	Moderate disability (11–20)	15.0 [10.0, 40.0]	18.0 [10.0, 30.0]
	Severe disability (21+)	15.0 [10.0, 30.0]	22.0 [10.0, 35.0]
Desire to work from home (1–7), mean (SD)		3.78 (2.33)	3.56 (2.31)	0.097
Median [Q1, Q3]		4.00 [1.0, 6.0]	4.00 [1.0, 5.0]
High preference for remote work (5–7) (%)		137 (20.3%)	24 (10.3%)
Self-reported efficiency in work from Home (1–7), mean (SD)		4.69 (2.30)	3.47 (2.10)	0.556
Median [Q1, Q3]		5.00 [3.0, 7.0]	4.00 [1.0, 5.0]
COVID-19 related unpaid leave, n (%)		78 (11.6%)	18 (7.8%)	0.052
Male		10 (7.6%)	4 (8.7%)	0.223
Female		68 (12.5%)	14 (7.5%)	0.038
Burnout
Total score (1–7), mean (SD)		3.46 (1.43)	2.82 (1.29)	0.469
Median [Q1, Q3]		3.0 [2.0, 5.0]	2.0 [1.0, 3.0]
Exhaustion (1–7), mean (SD)		3.72 (1.51)	3.01 (1.48)	0.480
Median [Q1, Q3]		4.0 [2.0, 5.0]	3.0 [1.0, 4.0]
Cynicism (1–7), mean (SD)		3.73 (1.79)	2.90 (1.65)	0.483
Median [Q1, Q3]		3.0 [2.0, 5.0]	2.0 [1.0, 4.0]
Professional efficacy (1–7), mean (SD)		3.13 (1.47)	2.54 (1.17)	0.446
Median [Q1, Q3]		3.0 [2.0, 4.0]	2.0 [1.0, 3.0]

Abbreviations: MIDAS = Migraine Disability Assessment; SMD = standardized mean difference.

To evaluate the associations between migraine status and severity, and occupational burnout, we first performed correlation analyses (see supplemental material, Table 1). The results indicated that depression, anxiety and stress were significantly associated with burnout for all participants (Spearman's rho = 0.699, 0.607 and 0.701, p < 0.001). Higher age was significantly associated with a lower MBI-GS score (Spearman's rho = −0.290, p < 0.001). Weekly work hours were found to be significantly associated with burnout for all participants (Spearman's rho = 0.260, p = 0.049). Higher education was also associated with the development of burnout (Spearman's rho = 0.490, p = 0.041). Commuting time, gender, ethnicity, children number and marital status were not found to be significantly associated with burnout.

Table 4 presents the results of the multivariable quantile regression models examining the association between migraine diagnosis and burnout at different quantiles of the burnout distribution. At the 25th percentile (τ = 0.25), migraine diagnosis was significantly associated with a 0.67 unit increase in burnout (p = 0.002). At the median (τ = 0.5), the association was not statistically significant, however for the 75th percentile (τ = 0.75), migraine diagnosis was significantly associated with a 0.92 unit increase in burnout (p = 0.032).

Table 4.

Multivariable analysis: Migraine diagnosis association with MBI-GS burnout score, quantile regression models.

Characteristics	Quantile (tau)	Estimate of migraine effect on burnout	95% CI	p-value
Migraine diagnosis	0.25	0.67	0.24, 1.1	0.002
	0.5	0.50	−0.10, 1.1	0.11
	0.75	0.92	0.08, 1.7	0.032

Multivariable quantile regression model result. The primary outcome of this model was occupational burnout. The main exposure of interest was migraine diagnosis. The adjustment includes age, gender, ethnicity, education, depression, anxiety, stress, commuting time, and weekly work hours

Quantile (tau): represents different points in the distribution of burnout scores.

Estimate: the estimated effect of migraine diagnosis on burnout scores.

The estimated effect at the 25th quantile (tau = 0.25) indicates that, for individuals in the lower burnout range, having a migraine diagnosis is associated with an increase of 0.67 points on the burnout scale compared to non-migraine individuals, after adjusting for other factors.

Abbreviation: CI = confidence interval.

Figure 3 depicts the association between occupational burnout and migraine severity, controlling for demographic factors (gender, age, educational status and ethnicity) and psychological factors (depression, anxiety and stress), as well as weekly work hours and commuting time. After adjusting, the quantile regression analysis results indicate that higher MIDAS scores (estimates: 2.2–5.3, p < 0.001 for all) are associated with higher burnout scores across all quantiles. The effect of the MIDAS score on burnout appears to be consistent across different levels of burnout severity.

Figure 3.

The graphs presented show the association between migraine severity (measured by MIDAS score) and burnout across different quantiles for the overall cohort, males, and females. The quantile regression examines how migraine severity associates various points in the distribution of burnout. Each quantile (line) represents a separate model, showing where the burnout level is for each MIDAS score value. The adjustment includes age, gender, ethnicity, education, depression, anxiety, stress, commuting time, and weekly work hours. Abbreviations: MIDAS = Migraine Disability Assessment.

To address potential concerns regarding the use of the MIDAS score as a measure of migraine severity and its association with occupational burnout, we conducted a sensitivity analysis examining the association between migraine severity, measured by average pain intensity, and occupational burnout. The analysis revealed that higher median headache intensity is associated with higher burnout scores (estimates: 1.5 for the entire cohort (95% CI = 0.72–2.3), 2.5 for the male subgroup (95% CI = 0.86–4.2) and 1.2 for the female subgroup (95% CI = 0.28–2.1) (p < 0.001 for all) across the entire cohort.

Migraine patient-reported outcome measures stratified by gender are provided in the supplementary material (Table 2). Among 544 female and 131 male migraine patients, the median diagnosis age was 24.0 years (IQR = 18.0–30.0 years) for both females and males (SMD = 0.023 years). Some 39.5% percentage of females and 36.7% of males were treated with preventive drugs (SMD = 0.058). The mean MIDAS score was higher for females (54.8 ± 68.8) compared to males (45.3 ± 60.9), but this difference was not statistically significant (SMD = 0.146). The mean number of headache days in the last three months was similar between females and males, as was the mean headache intensity.

As shown in the supplemental material (Table 2), men experience higher levels of MBI-GS than women for all burnout scores. Males had a significantly higher median total burnout score of 4.0 (IQR = 3.0–5.0) compared to females, who had a median score of 3.0 (IQR = 2.0–4.0, SMD = 0.486). In terms of cynicism, males reported a higher median score of 4.0 (IQR = 3.0–6.0) compared to a female median score of 3.0 (IQR = 2.0–4.0, SMD = 0.401).

The gender analysis demonstrates the association between migraine severity, as measured by the MIDAS score on burnout, stratified by gender. For the male subgroup, as illustrated in Figure 3, there was a notable increase in burnout scores at the 10th percentile with increasing MIDAS scores, suggesting that males with lower initial burnout scores experience a significant increase from migraine severity. Conversely, the 75th percentile shows a smaller increase. In the female subgroup, the association between MIDAS scores and burnout is positive across most quantiles. However, at the 10th percentile, the burnout scores show minimal increase with higher MIDAS scores.

Discussion

The present study aimed to evaluate self-reported work-related parameters (i.e. weekly working hours, commuting time, absenteeism, presenteeism and occupational burnout) among migraine patients and non-migraine participants, as well as to assess their associations with migraine severity (i.e. monthly migraine days, and MIDAS).

The most notable finding in our study was the association between occupational burnout and migraine. Migraine patients were found to have higher burnout than non-patients, and migraine severity was independently associated with burnout even when controlling for well-known mental comorbidities of migraine, such as depression anxiety and stress. However, even after controlling the psychological comorbidities, migraine severity remained an independent predictor of occupational burnout.

A possible explanation for this association is migraine-related cognitive disturbances. Such disturbances can be disabling and cause avoidance (referred to by some as “cogniphobia”) from a mental effort even interictally (23). Cognitive deficits before, during or after migraine attacks may increase the cognitive overload of migraine patients and promote burnout (24 –26). However, it is important to consider that burnout itself may adversely affect cognitive function, indicating a potential association between these two conditions. Although the present study did not evaluate cognitive deficits, they may partially explain the association between burnout and migraine. Future research should incorporate direct assessments of cognitive function to clarify the role that cognitive impairment plays in the relationship between migraine and occupational burnout.

The findings of the present study are in line with previous research that has identified a higher risk of burnout among individuals with chronic illnesses, particularly those that cause pain and disability (12). Migraine, as a chronic neurological disorder, is a significant source of pain and can greatly impact an individual's ability to carry out daily activities. In addition to physical symptoms, individuals with migraine often experience high levels of stress, anxiety and depression, which can contribute to burnout in the workplace. Work-related emotional symptoms (especially stress) have previously been associated with migraine and migraine severity (27).

The association between migraine and occupational burnout has also been studied before (28). González-Quintanilla et al. (23) used the Maslach Burnout Inventory to study 94 migraine patients with associations found between different sub-scales of burnout and migraine severity. Our study, however, utilized quantile regression to examine the impact of migraine severity across different points in the burnout distribution, includes gender-specific patterns and adjusts for multiple confounders, offering a comprehensive understanding of how migraine affect various aspects of occupational burnout. The results suggest that the impact of migraine diagnosis on burnout varies across the distribution of burnout, with stronger effects observed at the lower and upper ends of the distribution. This variation may be a result of differences in coping mechanisms, baseline burnout levels, variability in symptom severity, work environment demands and psychological resilience among participants at different points in the burnout distribution.

Notably, although meta-analyses on gender and burnout often report no gender differences or higher burnout in women (29 –31), our study found that men with migraine experience higher levels of occupational burnout across all levels of migraine severity. This may be explained by gender role theory (32), where the clash between the breadwinner role and their medical condition makes men particularly vulnerable to high levels of burnout. In healthy participants, this dynamic is less pronounced because of the absence of a chronic, debilitating condition such as migraine, allowing for better role balance and resilience.

Given that migraine affects more than 10% of the workforce, increased burnout among migraine patients may have significant impacts on individuals and economies. Considering new opportunities in migraine care, this impact could at least be partially mediated. Modern work models, such as working from home or hybrid work models, may allow migraine patients higher, more productive ways to participate in the work market. Thus, interventional studies are needed to explore the efficacy of migraine therapies and new work models on workers and economies.

Stigma, especially internalized stigma, may significantly contribute to occupational burnout in participants with migraine. This stigma often stems from societal attitudes and workplace interactions, leading to feelings of shame, anxiety and guilt. Internalized stigma can intensify emotional stress and discourage individuals from seeking support, thereby increasing their risk of burnout (5). Additionally, the pressure to work through symptoms to avoid being perceived negatively can exacerbate presenteeism, further contributing to burnout.

In our study cohort, half of the participants with migraine reported migraine-related absenteeism of at least one day per month and 25% missing at least two days per month. Migraine patients also reported an average of 4.5 days of migraine-related reduced productivity/month and 25% of them reported five of such days per month or more. Previous studies have reported lower rates of migraine-related productivity loss. A narrative review published in 2019 calculated that patients lost on average 4.4 workdays per year and worked with reduced productivity for a further 11.4 days per year. (33) The findings in our cohort are approximately four- to five-times higher. This discrepancy could be a result of our study population having a higher baseline severity of migraine, as indicated by higher MIDAS scores, leading to more frequent and severe migraine attacks and consequently greater absenteeism and presenteeism.

Commuting time was negatively associated with migraine severity (not reaching statistical significance), suggesting that participants with more severe migraine tend to avoid longer daily travels to work protecting themselves from worsening symptoms, which can lead to occupational burnout. Commuting to work can be a challenge for individuals with migraine (34), with 50% of patients experiencing motion sickness (35), which may even trigger or exacerbate migraine attacks (36). Longer commuting time are associated with shorter sleep, which is a possible exacerbating factor for migraine patients. This associations of commuting time, migraine and occupational burnout, not previously reported, may limit migraine patients’ employment opportunities and income potential.

Working from home as an alternative to traditional work models was popularized during the COVID-19 pandemic. The participants of the study were asked to rank their preference to work from home. This preference was found to be associated with migraine severity, possibly as a result of the higher burnout and the desire to avoid longer commuting time among high-severity migraine patients. The study also found that participants with migraine tend to work more hours, which may be explained by compensatory behavior because of presenteeism. When productivity is reduced during migraine episodes, these participants might extend their work hours to make up for lost efficiency. This behavior could reflect a need to meet job demands despite the challenges posed by their condition.

The present study is the first to evaluate occupational burnout in a community sample of migraine patients and has several limitations. The response rate of both migraine and non-migraine participants was 45% and the participating cohort is composed of patients with relatively severe migraine (more than 50% of them with moderate to severe disability, 39% treated by preventive therapy), which may limit the generalizability of the results. However, the study evaluated the association of work-related factors with migraine severity, as well as a dichotomous comparison between migraine patients and non-migraine participants, allowing us to gain insights into less explored aspects of migraine in the workplace. Moreover, the lack of available data on job type prevented us from matching or conducting secondary analyses based on this variable, which may influence the association between migraine and occupational burnout. We have not adjudicated the migraine diagnosis by a certified neurologist. Thus, the migraine diagnosis misclassification bias could potentially affect the study results by assigning migraine status to subjects with other types of headaches. Yet such a bias would be a bias toward zero hypothesis.

In conclusion, the present study provides evidence that participants with migraine are at higher risk of burnout in the workplace, particularly when their symptoms are more severe. Interventions aimed at reducing burnout among participants with migraine should take into account factors such as work hours and commuting time, as well as the impact of psychological factors such as stress, anxiety and depression. By addressing these factors, employers may be able to create a more supportive work environment for individuals with migraine, which could ultimately lead to improved work outcomes and better quality of life.

Clinical implications

Migraine diagnosis and severity is associated with an occupational burnout, after controlling for various psychological and work-related factors.

Men with migraine report elevated levels of burnout, in contrast to conventional gender expectations.

The findings underscore the need for workplace adjustments to support migraine patients’ participation in the work market.

Supplemental Material

sj-docx-1-cep-10.1177_03331024241289930 - Supplemental material for Migraine and work – beyond absenteeism: Migraine severity and occupational burnout – A cohort study

Supplemental material, sj-docx-1-cep-10.1177_03331024241289930 for Migraine and work – beyond absenteeism: Migraine severity and occupational burnout – A cohort study by Ido Peles, Shaked Sharvit, Yair Zlotnik, Michal Gordon, Victor Novack, Ronit Waismel-Manor and Gal Ifergane in Cephalalgia

Footnotes

Acknowledgments

The study investigators received funding from Teva to conduct the study. Teva had no input on study design, execution, data collection, analysis, interpretation of results and preparation of the manuscript.

Author contributions

IP was responsible for data analysis and manuscript preparation. SS was responsible for focus group interviews, development of study questionnaires and participated in the study conceptualization. YZ participated in study design and manuscript writing. MG was responsible for data analysis. VN was responsible for design and data analysis. RWM was responsible for manuscript writing and theoretical aspects. GI was responsible for ideation and conceptualization, study design, data analysis and manuscript preparation.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declaration of conflicting interests

Gal Ifergane received consulting fees and honorariums from Teva, Novartis, Eli Lilli, Pfizer, and Abbvie. The remaining authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical approval

The study was approved by the Soroka Medical Center Helsinky committee.

Funding

The study was funded by Teva Pharmaceutical Industries,

ORCID iD

Ido Peles

Supplemental material

Supplemental material for this article is available online.

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