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Abstract

Background

Migraine, a neurovascular disorder that affects quality of life, with peak prevalence during individuals’ most productive working years. Work–family conflict (WFC), a well-documented source of stress, occurs when work and family responsibilities interfere with each other. While migraine has been associated with occupational impairment, its association with WFC remains underexplored. The present study examines the association between migraine diagnosis, severity and WFC, stratified by gender.

Methods

This study analyzed data from the SMILE cohort, a subset of the Negev Migraine Cohort. Participants with and without migraine were recruited and completed a structured questionnaire assessing WFC. The main exposures were migraine diagnosis and severity, measured using the Migraine Disability Assessment (MIDAS) score. The primary outcome was WFC. Covariates included sociodemographic characteristics, employment factors, and psychological distress (Depression, Anxiety and Stress Scale – 21 Items (DASS-21)). Statistical analyses involved multivariable gamma generalized linear mode regression models and quantile regression to examine associations, adjust for potential confounders and effect modification by gender.

Results

In total, 675 migraine patients and 232 non-migraine participants were included in the study; 80.6% of migraine patients were female. Severe disability (MIDAS score ≥21) was reported by 65.0% of migraine patients, with employment rates of 89.2% for females and 93.1% for males. Migraine patients worked longer hours per week (median 40.0 vs. 36.0 hours for females, and 48.0 vs. 42.0 hours for males), and were more likely to work over 42 hours per week (18.2% vs. 7.0% for females and 32.8% vs. 8.7% for males, standardized mean difference = 0.487). Migraine diagnosis was associated with higher Work To Family and Family To Work strain-based conflict scores among males (β = 0.43, 95% confidence interval = 0.06–0.78, p = 0.03 and β = 0.35, 95% 95% confidence interval = 0.03–0.66, p = 0.04, respectively); however, no statistically significant associations were observed among female. Higher migraine severity (MIDAS) was correlated with greater WFC, with the effect more pronounced at higher levels of migraine disability and more strongly associated with men (p < 0.01 for all).

Conclusions

Migraine is associated with higher WFC, especially in strain-based domains, with a stronger effect in men. Greater migraine severity further amplifies this conflict. These findings emphasize the need for workplace and clinical strategies to support migraine patients in managing work–life balance.

Graphical abstract

This is a visual representation of the abstract.

Keywords

absenteeism gender differences migraine severity work–family conflict presenteeism strain-based work–-family conflict

Introduction

Migraine is a neurovascular disorder characterized by recurrent episodes of severe headaches, often accompanied by other neurological symptoms. Millions of people worldwide experience these episodes, which can vary in severity and frequency, with a higher prevalence among women.¹ The occurrence of migraine peaks between the ages of 25 and 55 years, which are typically the most productive years in a person's career and often coincide with family-building and child-rearing.^2–4

Work and family roles represent two of the most important roles of adult life. Work–family conflict (WFC) is the most studied perspective on how work and family interact.⁵ WFC refers to a form of interpersonal conflict in which demands across work and family roles are mutually incompatible in some respect.^6,7 WFC is one of the crucial issues that affect people's well-being, especially their stress levels.^8,9

Migraine significantly affects patients’ quality of life, often limiting their ability to participate in daily activities.¹⁰ The extent of this impact is related to migraine severity. In the workplace, migraine leads to both absenteeism (taking sick days) and presenteeism (being at work with reduced productivity).^11,12 Higher migraine severity is also associated with occupational burnout and a tendency to avoid longer commutes.^13–15 Unsurprisingly, migraine also affects family life.¹⁶

In this cohort study, we hypothesized that migraine diagnosis and higher migraine severity are associated with increased WFC in a bidirectional way: work interferes with family (WIF) and family interferes with work (FIW), controlling for other health characteristics.

Methods

Study setting

This study is an observational evaluation of WFC in a cohort of 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 (CHS), 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.

Study design

This retrospective population-based cohort study is a part of the SMILE project (Southern Israel Migraine Impact on Life Experiences). In brief, the SMILE cohort was recruited from the Negev Migraine Cohort (NMC), a previous population-based, retrospective, observational cohort of adult (≥18 years) patients with migraine identified from the CHS database in southern Israel identified by physician-assigned International Classification of Diseases, 9th Revision (ICD-9) codes for migraine and/or claims for triptans, between 2000 and 2018. 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 patient characteristics, are described in detail elsewhere.¹⁷

In 2021, we employed random sampling methods to recruit adult (≥18 years) migraine and non-migraine participants from the NMC to participate in a series of semi-structured focus groups, both in-person and virtual. Participants were asked how migraine affects their lives and how their lives would be different if they did not suffer from migraine. Study questionnaires were developed based on themes suggested by the participants, focusing on evaluating the association between migraine diagnosis, severity and WFC.

For the recruitment of the SMILE cohort, 1475 migraine patients and 515 control participants (from the NMC) were contacted, to recruit 675 (46%) migraine patients and 232 (45%) non-migraine participants. Recruited participants (migraine and non-migraine) received links to the study questionnaire from an external online survey company, blinded to their migraine status. Participants were excluded if they completed the questionnaire partially (i.e. missing key exposure or outcome items) or provided illogical responses. The study's general design and recruitment process were previously reported.¹⁸

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 (SHR) – 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) – This is 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

The Migraine Disability Assessment (MIDAS) – This is a tool to assess the impact of migraine on a patient's 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 gathers self-reported information about the participant's employment status, working hours, workplace commuting time, tenure at the workplace, preference for remote work and self-reported efficiency when working from home. The latter two items are assessed using a 1–5 Likert scale.

Work–Family Conflict (WFC) – The WFC tool, developed by Carlson et al.,²¹ assesses the extent of WFC through a multidimensional approach that examines how individuals balance family life with work responsibilities. This validated measure includes 12 statements rated on a five-point Likert scale, where higher scores indicate greater levels of conflict. The WFC captures two primary dimensions of WFC: Work to Family (WIF) (examining how work responsibilities impact family life) and Family to Work (FIW) (examining how family obligations interfere with work tasks). Each of these dimensions is further subdivided into time-based conflict, which reflects how time demands in one role limit engagement in the other, and strain-based conflict, which evaluates the emotional toll on family life, particularly related to feelings of exhaustion or mental fatigue. The original WFC measure demonstrated Cronbach's alpha values ranging from 0.70 to 0.88 for its subscales.

Although the study employed well-validated instruments, including the WFC scale and the MIDAS questionnaire, we did not conduct an independent validation of these tools within our specific study population.

Statistical analysis

The primary outcome of this study was WFC. The main exposures of interest were migraine diagnosis and migraine severity, measured using the MIDAS score. The sample size, 675 migraine patients and 232 non-migraine participants, was determined to ensure sufficient power to detect a minimal effect size of 5% in WFC score scales, 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.¹⁶

To describe demographic, SHR, migraine-related characteristics and patient-reported outcome measures (PROMs), we first computed the mean ± SD for normally distributed quantitative variables, medians and interquartile ranges for non-normally distributed quantitative variables and percentages for categorical variables. We also compared the employment characteristics between the migraine vs. non-migraine groups stratified by gender. 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 WFC query metrics, we initially performed univariate analyses using a Spearman's rank-order non-parametric correlation test in the entire cohort and by gender stratification. However, the primary analyses employed multivariable Gamma Generalized Linear Mode (GLM) regression. The primary outcomes were WIF and FIW (strain-based) score scales and the main exposure of interest was migraine diagnosis. 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 WFC is depicted in Figure 1. 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 1.

Directed acyclic graphs of the assumptions on associations between variables.

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, measured by the MIDAS score, and WFC, we fitted quantile regression models at five different quantiles (τ = 0.1, 0.25, 0.5, 0.75 and 0.9) adjusted for various covariates. The resulting regressions lines for each quantile were plotted to visualize these associations. We also conducted a subgroup analysis by gender to examine the effect variability of migraine diagnosis and severity on WFC between males and females. Estimates and 95% confidence intervals (CIs) are shown along with p-values for all the models.

For all analyses, p < 0.05 (two-sided) was considered statistically significant. All analyses were performed using R, version 4.4.1 (R Foundation for Statistical Computing, Vienna, Austria) in the RStudio 2024.04.2 environment (Posit PBC, Boston, MA, USA). The study was approved by the Soroka Medical Center Institutional Review Board, reference number 0284-19.

Results

The study included 907 participants, comprising 675 migraine patients and 232 non-migraine controls. Table 1 shows that the migraine group was younger (median age 43.0 vs. 49.0 years, SMD = 0.591) and had a lower proportion of post-secondary education (36.0% vs. 44.4%, SMD = 0.372) compared to the non-migraine group. Gender, marital status and self-reported health status were similar between groups.

Table 1.

Demographic, migraine-related characteristics and patient-reported outcome measures (PROMs).

	Migraine			Non-migraine	SMD
	Female sex (N = 544)	Male sex (N = 131)	Total cohort (N = 675)	Total cohort (N = 232)	SMD
	Demographic characteristics
Gender, female (%)	544 (100.0%)	0 (0.0%)	544 (80.6%)	186 (80.2%)	0.011
Age (years), median [Q1, Q3]	43.0 [33.0, 55.0]	43.0 [35.0, 51.0]	43.0 [34.0, 54.0]	49.0 [39.0, 66.0]	0.591
Marital status, married (%)	312 (57.4%)	93 (71.0%	405 (60.0%)	146 (62.9%)	0.189
Number of children, mean (SD)	2.81 (1.38)	3.09 (1.12)	2.87 (1.34)	3.31 (1.57)	0.302
Education level, post-secondary education (%)	203 (37.3%)	40 (30.5%)	243 (36.0%)	103 (44.4%)	0.372
Self-rated health status (scale range: 1–10, with 1 being poor and 10 being excellent), mean (SD)	7.52 (2.02)	7.31 (1.85)	7.48 (2.05)	7.85 (1.81)	0.190
	Migraine-related characteristics
Onset age (years), median [Q1, Q3]	19.0 [15.0, 27.0]	20.0 [16.0, 29.0]	20.0 [15.0, 27.0]
Diagnosis age (years), median [Q1, Q3]	24.0 [18.0, 30.0]	24.0 [18.5, 30.0]	24.0 [18.0, 30.0]
Treated by migraine preventive drugs %	215 (39.5%)	48 (36.7%)	263 (39.0%)
MIDAS score, median [Q1, Q3]	30.0 [15.0, 64.0]	26.0 [11.0, 56.0]	30.0 [15.0, 64.0]
MIDAS score groups
Little or no disability (0–5)	55 (10.1%)	22 (16.8%)	77 (11.4%)
Mild disability (6–10)	31 (5.7%)	9 (6.9%)	40 (6.0%)
Moderate disability (11–20)	94 (17.3%)	25 (19.1%)	119 (17.6%)
Severe disability (21+)	364 (66.9%)	75 (57.2%)	439 (65.0%)
Mean triptan pills per month, mean (SD)	3.7 (2.9)	2.6 (2.4)	3.4 (2.1)
1–4	387 (71.1%)	101 (77.1%)	488 (72.3%)
5–9	97 (17.8%)	19 (14.5%)	116 (17.2%)
10+	60 (11.0%)	11 (8.4%)	71 (10.5%)

MIDAS = Migraine Disability Assessment; SMD = standardized mean difference; Q1 = first quartile; Q3 = third quartile.

The migraine phenotype of the SMILE cohort was characterized by a median age of migraine onset of 19.0 years for females and 20.0 years for males, with a diagnosis age of 24 years for both genders. The median number of headache days over the past three months was 10 (interquartile range = 5–20) and the median reported headache intensity was 8.0 on a 1–10 scale (MIDAS B). Based on the MIDAS questionnaire, 65.0% of patients were classified as having severe migraine-related disability (MIDAS ≥ 21). Regarding acute medication use, 72.3% of migraine participants reported using one to four triptan pills per month, 17.2% used five to nine pills (suggesting the potential need for prophylaxis) and 10.5% used ≥10 pills, indicative of possible medication overuse headache. Additionally, 39% of participants were actively treated with migraine preventive therapy at the time of data collection.

Table 2 presents employment characteristics, showing that employment rates were high across all groups, although the direction of difference varied by gender: among females, non-migraine participants had a slightly higher employment rate (91.9% vs. 89.2%, SMD = 0.139), whereas, among males, migraine participants had a higher employment rate (93.1% vs. 87.0%, SMD = 0.139). However, migraine patients reported higher weekly work hours (median 40.0 vs. 36.0 hours for females and 48.0 vs. 42.0 hours for males, SMD = 0.148) and a greater percentage of the males working more than 42 hours per week (18.2% vs. 7.0% for females, and 32.8% vs. 8.7% for males, SMD = 0.487). Migraine patients also rated their work-from-home efficiency higher (median 5.50 vs. 4.00 for females and 5.0 vs. 1.0 for males, SMD = 0.556). These ratings were collected using an employment status self-questionnaire developed for the present study. The questionnaire also assessed self-reported preference for remote work and current work-from-home status. Migraine patients also exhibited higher levels of depression, anxiety and stress compared to the non-migraine group. The full distribution of psychological distress measures has been previously reported.¹⁸

Table 2.

Employment characteristics.

	Migraine(N = 675)		Non-migraine(N = 232)		SMD
	Female sex (N = 544)	Male sex (N = 131)	Female sex (N = 186)	Male sex (N = 46)	SMD
Currently working (%)	485 (89.2%)	122 (93.1%)	171 (91.9%)	40 (87.0%)	0.139
Weekly work hours, median [Q1, Q3]	40.0 [21.0, 45.0]	48.0 [40.0, 55.5]	36.0 [27.0, 42.0]	42.0 [36.0, 50.0]	0.148
> 42 weekly work hours (%)	99 (18.2%)	43 (32.8%)	13 (7.0%)	4 (8.7%)	0.487
Currently work from home (%)	49 (9.0%)	14 (10.7%)	18 (9.7%)	6 (13.0%)	0.125
Self-reported preference for remote work (scale range: 1–7), median [Q1, Q3]	4.00 [1.00, 6.0]	3.00 [1.0, 6.0]	4.00 [1.00, 6.0]	3.00 [1.0, 5.0]	0.097
Self-reported efficiency in work from home (scale range: 1–7), median [Q1, Q3]	5.50 [3.0, 7.0]	5.00 [1.75, 7.0]	4.00 [2.0, 5.0]	1.00 [1.0, 3.0]	0.556

SMD = standardized mean difference; Q1 = first quartile; Q3 = third quartile.

Figure 2 shows WFC metrics, comparing migraine and non-migraine groups by gender. Migraine patients reported higher scores across most conflict dimensions. For males, the migraine group had higher WIF strain-based scores (median 3.33 vs. 2.67, SMD = 0.225) and FIW strain-based scores (median 2.33 vs. 2.00, SMD = 0.111) than the non-migraine group. In females, migraine patients also scored higher on WIF strain-based (median 3.0 vs. 2.67, SMD = 0.225). The supplementary material (Table S1) shows other factors associated with WFC, with significant correlations observed for age, educational status, depression, anxiety and stress (all p < 0.01).

Figure 2.

Work–family conflict query metrics. SMD = standardized mean difference.

Table 3 presents results from the multivariable gamma GLM regression models, assessing the association between migraine diagnosis and WFC. For WIF strain-based conflict, migraine diagnosis was associated with a higher conflict score among males (β = 0.43, 95% CI = 0.06–0.78, p = 0.03), but not among females. Similarly, for FIW strain-based conflict, migraine diagnosis was significantly associated with higher conflict in males (β = 0.35, 95% CI = 0.03–0.66, p = 0.04).

Table 3.

Multivariable analysis – migraine diagnosis association with work family conflict, gamma GLM regression models.

Model outcome	Gender	Estimate of migraine diagnosis effect on outcome	95% CI	p-value
Work to Family (strain-based) (1–5 score scale)	All cohort	0.29	–0.05, 0.52	0.09
	Female	0.18	–0.04, 0.40	0.12
	Male	0.43	0.06, 0.78	0.03
Family to Work (strain-based) (1–5 score scale)	All cohort	0.26	–0.09, 0.50	0.14
	Female	0.14	–0.13, 0.39	0.27
	Male	0.35	0.03, 0.66	0.04

Multivariable gamma GLM regression model result. The primary outcomes of this models were Work to Family /Family to work strain-based scores (1–5 score scale), based on a five-point Likert scale from the Work–Family conflict questionnaire, where higher scores indicate greater strain-related conflict.

The main exposure of interest was migraine diagnosis. The adjustment includes age, gender, ethnicity, education, marital status, children number, depression, anxiety, stress and weekly work hours.

CI = confidence interval; Estimate = The estimated effect of migraine diagnosis on work family conflict scores; GLM = generalized linear model.

The supplementary material (Table S2) highlights the associations between migraine severity (measured by MIDAS scores) and WFC metrics, stratified by gender. For males, higher MIDAS scores were associated with WIF strain-based conflict (Spearman's rho = 0.39, p = 0.01). Additionally, FIW strain-based conflict showed correlations with MIDAS scores in both males (Spearman's rho = 0.42, p < 0.01) and females (Spearman's rho = 0.18, p = 0.01).

Figure 3 illustrates the association between migraine-related disability (measured by MIDAS scores) and WFC dimensions (strain-based) across different quantiles, stratified by gender. The quantile regression models show that higher MIDAS scores are consistently associated with increased WIF and FIW strain-based conflict across all quantiles for both males and females. Notably, the magnitude of WFC rises more steeply at higher quantiles of MIDAS scores, indicating that individuals with greater migraine disability experience more pronounced strain. Additionally, males exhibit a slightly steeper increase in conflict with rising MIDAS scores compared to females, suggesting a stronger association between migraine severity and WFC among male participants.

Figure 3.

(A) Multivariable analysis – Migraine Associated Disability (MIDAS score), associated with Family to Work (strain-based), quantile regression models for multiple quantiles by gender. (B) Multivariable analysis – Migraine Associated Disability (MIDAS score), associated with Work to Family (strain-based), quantile regression models for multiple quantiles by gender.

Discussion

The present study aimed to examine the association between migraine and WFC considering both the directionality and dimensions of WFC. Our findings indicate that migraine is associated with increased WFC, particularly in the strain-based subdomains, and that this association is more pronounced in men. Furthermore, migraine severity appears to exacerbate WFC, particularly among male participants. These results contribute to the growing body of literature on the impact of chronic health conditions on work–family balance and have significant implications for both workplace policies and clinical management.

Individuals with migraine reported higher levels of both WIF conflict and FIW conflict compared to non-migraine participants. The strongest associations were observed in the strain-based dimensions of WFC, suggesting that individuals with migraine experience emotional and cognitive strain that interferes with their ability to effectively manage work and family responsibilities. This finding aligns with previous studies highlighting the disabling impact of migraine on productivity, absenteeism and overall work performance.^10,16 The association between chronic health conditions and WFC has been underexplored in the literature, with only one prior study specifically addressing migraine.¹⁶ Our study extends these findings by differentiating between WIF and FIW and incorporating a multidimensional perspective on WFC.

A key finding of the present study is the differential impact of migraine on WFC by gender. Men with migraine exhibited a stronger association with WFC than women, particularly in the strain subdomain. These findings challenge traditional assumptions that women experience greater WFC as a result of societal expectations of caregiving roles.^22–24 While prior meta-analytic research suggests that gender differences in overall WFC are small,²⁵ our study indicates that men with migraine may experience unique challenges related to role expectations. The gender role strain theory²⁶ suggests that men who experience chronic illness may struggle with perceived inadequacies in fulfilling their traditional provider roles.²⁷ This could explain the heightened WFC observed in men with migraine because work-related strain may amplify their feelings of conflict between professional and personal responsibilities.

Our study further demonstrates that migraine severity significantly influences WFC. Higher MIDAS were associated with increased WFC, with a particularly pronounced effect in men. The quantile regression models indicate that, as migraine severity increases, the impact on WFC becomes more pronounced across all quantiles, but the strongest effects are observed at the upper end of the WFC distribution. Given that migraine is associated with cognitive disturbances, fatigue, and emotional dysregulation,^28,29 it is plausible that individuals with severe migraine are particularly vulnerable to experiencing heightened strain in managing both work and family roles.

The observed associations between migraine and WFC have significant clinical and occupational implications. Employers and policymakers should consider workplace interventions that mitigate migraine's impact on employees’ work–life balance.³⁰ Flexible work arrangements, hybrid work models and mental health support programs could help alleviate WFC among migraine patients, potentially improving job satisfaction and health outcomes. It is reasonable to hypothesize that accurate migraine diagnosis, optimal migraine management, and accessibility to advanced migraine-specific therapies can possibly ameliorate WFC and allow better quality of life and work productivity. This potential effect warrants further investigation.

The present study has several strengths, including its use of a large, well-characterized cohort and its comprehensive approach to analyzing WFC using multiple dimensions. The inclusion of gender-stratified analyses provides novel insights into the differential effects of migraine on WFC. However, certain limitations must be acknowledged. The study relies on self-reported data, which may introduce recall bias. Additionally, 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 and 39% treated by preventive therapy). On the other hand, the cohort predominantly represents individuals with low-frequency episodic migraine, as indicated by a median of 10 headache days over the past three months. As such, the findings may not be fully generalizable. 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 WFC. Future longitudinal studies are needed to examine the directionality of the association between migraine and WFC, as well as potential mediating and moderating factors such as job type and coping strategies.

In conclusion, the present study highlights a significant association between migraine and WFC, particularly in the strain-based domains. The findings underscore the importance of considering gender differences, with men experiencing a stronger association between migraine and WFC. Moreover, migraine severity exacerbates WFC, further complicating the ability to balance professional and family responsibilities. Addressing WFC in clinical and workplace settings and optimal migraine care should be considered complementary steps in improving the quality of life for individuals with migraine and enhancing productivity and well-being in the workforce. Public health relevance

Migraine is associated with increased work–family conflict, particularly in strain-based domains, which may contribute to occupational stress and reduced well-being.

The impact of migraine on work–life balance is more pronounced in men, highlighting the need for gender-specific workplace interventions.

Greater migraine severity is associated with higher levels of work–family conflict, suggesting that effective migraine management may help mitigate work–life disruptions.

Employers and policymakers should consider flexible work arrangements and mental health support to accommodate employees with migraine.

Addressing work–family conflict in migraine patients could improve productivity, reduce absenteeism and enhance overall quality of life.

Supplemental Material

sj-docx-1-cep-10.1177_03331024251352533 - Supplemental material for Invisible burdens: Gender-specific associations between migraine and work–family conflict

Supplemental material, sj-docx-1-cep-10.1177_03331024251352533 for Invisible burdens: Gender-specific associations between migraine and work–family conflict by Ido Peles, Shaked Sharvit, Yana Mechnik Steen, Michal Gordon, Victor Novack, Ronit Waismel-Manor and Gal Ifergane in Cephalalgia

Supplemental Material

sj-docx-2-cep-10.1177_03331024251352533 - Supplemental material for Invisible burdens: Gender-specific associations between migraine and work–family conflict

Supplemental material, sj-docx-2-cep-10.1177_03331024251352533 for Invisible burdens: Gender-specific associations between migraine and work–family conflict by Ido Peles, Shaked Sharvit, Yana Mechnik Steen, Michal Gordon, Victor Novack, Ronit Waismel-Manor and Gal Ifergane in Cephalalgia

Footnotes

Acknowledgements

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

ORCID iD

Ido Peles

Ethical statement

The study was approved by the Soroka Medical Center Helsinky committee, reference number 0284-19.

Author contributions

Ido Peles: Data analysis and manuscript preparation. Shaked Sharvit: focus group interviews, development of study questionnaires, participated in study conceptualization. Yana Mechnik Steen: Participated in study design and manuscript writing. Michal Gordon: Data analysis. Victor Novack: Design and data analysis. Ronit Waismel Manor: Manuscript writing, theoretical aspects. Gal Ifergane: Ideation and conceptualization, study design, data analysis, manuscript preparation.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by Pharmaceutical Industries.

Declaration of conflicting interests

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

Data availability statement

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

Supplemental material

Supplemental material for this article is available online

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