Mental health of informal caregivers during the COVID-19 pandemic: a Swiss cohort study

DOI: https://doi.org/https://doi.org/10.57187/s.3884

Introduction

The COVID-19 pandemic and its associated public health measures disrupted health and care systems [1], impacting clinically vulnerable people and their informal caregivers [2–6]. Informal caregivers (hereafter used interchangeably with caregivers) are family or friends who provide non-professional care. They represent a sizeable part of the general population (5% to 44% of adults across different European countries) [7–11] and are integral to health and care systems [12, 13]. It is well known from pre-pandemic data that the caregiving burden is associated with poorer mental health outcomes [14, 15]. The pandemic unsettled nearly every aspect of informal caregivers’ lives and caregiving routines with new challenges such as lockdown, fear of transmitting the virus and restricted access to human and material resources that assist with caregiving. Moreover, caregivers may have taken additional professional adjustments and preventive measures, such as limiting social contacts to avoid transmitting the virus, leading to potential financial consequences, social isolation and a negative impact on their well-being and mental health [5, 6, 16, 17]. The pandemic may have also pushed previously non-caregivers to become new caregivers for their relatives or friends who could no longer assume some of the tasks they used to handle due to restrictions and vulnerability factors. All these factors may have exacerbated the impact of providing care on caregivers’ mental health.

During the first few months of the pandemic, informal caregivers reported poorer mental and physical health and an overall lower quality of life than non-caregivers [4, 18–24]. A few studies have examined caregivers’ mental and physical health levels compared to pre-pandemic levels. Some highlighted an increase in stress, anxiety, depression, and caregiving burden during the early phases of the pandemic, while others suggested comparable or better caregiver mental health [25, 26]. Caregiving conditions and caregivers’ health could widely vary depending on local policies and public health measures.

In Switzerland, caregivers’ mental health during the pandemic remains underexplored. Therefore, the purposes of this study were (a) to determine the prevalence of mental distress among caregivers and non-caregivers, (b) to describe the perceived evolution of the caregiving roles and burden during the COVID-19 pandemic and (c) to identify protective and risk factors for mental distress in caregivers in the context of the COVID-19 pandemic.

Material and methods

Study design, setting and sample

Data were drawn from the Specchio-COVID19 cohort study, initiated in December 2020 to follow adults (≥18 years old) who participated in successive SARS-CoV-2 serosurveys between April 2020 and June 2021 [27–31]. Serosurvey participants were randomly selected from the Bus Santé population-based study, from Geneva registries provided by the Swiss Federal Office of Statistics or the Cantonal Office for Population and Migration, and from a convenience sample of essential workers (i.e. those employed in roles considered critical for delivering vital services such as healthcare, transportation, food production and social work, among others) living or working in Geneva [27]. After a serology, they were invited to join the cohort. Participants’ sociodemographic, health and lifestyle characteristics were assessed at inclusion in the cohort, and thematic and follow-up health questionnaires were offered regularly through an online digital platform (www.specchio-hub.ch). All participants in the Specchio-COVID19 study provided informed and written consent upon study enrolment.

This study used data from an inclusion questionnaire (completed between December 2020 and June 2021) and four additional questionnaires administered between June and July 2021. The first focused on general and mental health and included the 12-item General Health Questionnaire (GHQ-12). The second centred on well-being and mental health, including measures of stress, depression, and social support; its completion was optional for inclusion in this study. The third included a question assessing caregiver status. Finally, the fourth was exclusively sent to caregivers and explored their caregiving responsibilities and the characteristics of their care recipients. The latest included variables were selected as candidate risk and protective factors for mental distress in caregivers based on existing research and practical considerations from experts in the field. The variables collected in each questionnaire are detailed in table S1 in the appendix.

Participants in the Specchio-COVID19 study were eligible for this analysis if they had completed (a) a questionnaire about general and mental health and (b) a follow-up questionnaire with a question assessing caregiver status (figure 1).

Figure 1Flowchart.

Measures

Caregiving status was the main exposure of this study. Individuals who answered affirmatively to the question “Since the start of the pandemic, have you regularly helped (in a non-professional role) a person close to you (dependent, elderly, ill or disabled person) with the tasks of daily living (for example, washing or shopping, meals, housework)?” in June 2021 were categorised as informal caregivers.

The primary outcome was mental distress, measured by the 12-item General Health Questionnaire. This internationally validated scale comprises 12 mental health questions (e.g. concentration, sleep loss, stress, confidence), including six positively and six negatively worded questions. Each item is scored on a four-point Likert system ranging from zero to three points. Its maximum total score is 36 points, with a higher score indicating greater distress. Mental distress was defined as a score of ≥12 points [32, 33].

Additional mental health measures included well-being as measured by the WHO-5 Well-being Index (WHO-5), loneliness as measured by the UCLA Loneliness Scale (UCLA-3), and perceived stress as measured by the 10-item Perceived Stress Scale (PSS-10), with the definitions provided in appendix table S1.

The covariates included caregivers’ demographics (e.g. age, sex, birth country, and education) and pre-existing mental and physical health, assessed at inclusion in the cohort. A previous SARS-CoV-2 infection was defined as either (a) a positive serological, antigenic or polymerase chain reaction (PCR) test self-reported at inclusion or in a follow-up questionnaire, (b) a positive serology indicating natural infection (presence of anti-nucleocapsid antibodies) or (c) a positive PCR test according to a database established by regional public health authorities before 1 June 2021 [34].

Potential risk and protective factors for distress among caregivers were assessed at inclusion in the cohort (e.g. demographics), in a questionnaire about well-being and mental health (e.g. social support) and in an optional questionnaire about caregiving responsibilities and care recipient’s characteristics. They are defined in table S1 in the appendix and can be summarised as follows: (a) factors related to the caregiver (e.g. age, sex, and pre-existing conditions), (b) factors related to caregiving (e.g. frequency, distance from caregiver to care recipient, type of care, such as help with activities of daily living, and age of the care recipient) and (c) factors related to the COVID-19 pandemic (e.g. increase in caregiving burden and availability of healthcare professionals). If a caregiver cared for more than one individual, the participant was asked to answer a set of questions on caregiving specific to each person (e.g. care recipient’s age, reason for care, relationship, distance, and frequency and type of care). For care recipient-related variables, the data was derived from the first reported care recipient unless otherwise specified.

Statistical analyses

Baseline sociodemographic and mental health characteristics were compared between caregivers and non-caregivers and between caregivers with and without mental distress. Risk and protective factors for mental distress in caregivers were also assessed. All descriptive analyses included absolute numbers with relative percentages for categorical variables and means and standard deviations or medians with interquartile ranges for continuous variables. Hypotheses were tested using the chi-squared tests, Welch’s two-sample t-test or the Wilcoxon-Mann-Whitney test, as appropriate. The significance level was set at p<0.05.

The prevalence of distress was adjusted for confounders and compared among caregivers and non-caregivers. Based on existing literature, potential confounders of the association between caregiver status and mental distress were identified using a directed acyclic graph: sex, age and country of birth (figure S1 in the appendix). The adjusted prevalence of distress was calculated using average adjusted predictions. First, a linear regression model was fitted, including caregiver status as the primary predictor and confounders as covariates, including age, sex and birth country. Then, predictions were made for each individual in the dataset using their observed values for all covariates and averaged within caregiver and non-caregiver groups. This approach estimates the expected prevalence of distress, adjusted for the distribution of other confounders in the study population. A sensitivity analysis was conducted on a subsample of participants exclusively drawn from random samples of the general population (i.e. excluding essential workers).

The risk and protective factors for mental distress in caregivers were assessed using unadjusted and adjusted logistic regressions. The adjustment set included sex, age, education, social support, pre-existing mental condition and pre-existing physical condition. The results are reported as odds ratios (ORs) with 95% confidence intervals (CIs). Sensitivity analyses were conducted to test the robustness of the observed associations. First, the same models were run in a subsample of the caregivers from the general population (i.e. excluding essential workers). Then, when a caregiver reported caring for multiple care recipients, the data relative to the first care recipient was replaced with the data for the second care recipient. This approach allowed for an examination of whether the results were influenced by the characteristics of the care recipient in cases where a caregiver cared for multiple care recipients.

Missing data ranged from 0 to 20% per variable. Multiple imputation by chained equations (MICE) with predictive mean matching was used to treat missing data in all models [35].

All analyses were conducted using R (v.4.1.2; R Foundation for Statistical Computing, Vienna, Austria) with packages including dplyr (v.1.1.4), tidyverse (v.2.0), gtsummary (v.1.7.2), marginaleffects (v.0.17), mice (v.3.16), ggplot2 (v.3.4.4), and likert (v.1.3.5). The code is available at: https://gist.github.com/cedricfollonier/052233eb0bb4c8025f400c8fc1289a3e.

Patient and public involvement

Participants were not involved in setting the research questions or outcome measures or designing the study. However, they showed overwhelming support for the study through continuing attendance for follow-up.

Results

Demographic characteristics, physical health and mental health of caregivers and non-caregivers

Among the Specchio-COVID19 participants eligible for this study, 1086 (20%) declared being caregivers (figure 1). Table 1 presents the characteristics of caregivers and non-caregivers. Overall, their mean age was 51 years, 56% were female, and 52% had completed tertiary education. Caregivers were more often female (60% vs 55%, p = 0.002), born in Switzerland (70% vs 59%, p <0.001), and had lower household income (p = 0.002) than non-caregivers.

The overall observed prevalence of mental distress (GHQ-12 score ≥12 points) was 38% (95% CI: 36–39%) as of June 2021. Caregivers were more frequently affected than non-caregivers (41% vs 37%, p = 0.009), even after adjusting for age, sex and country of birth (41% vs 36%, p = 0.004). In both groups, the most frequently reported items of the GHQ-12 were feeling under stress and losing sleep (figures S2 and S3). In addition, caregivers reported slightly poorer well-being (64 vs 68 points, p = 0.048) and higher levels of perceived stress (23 vs 22 points, p <0.001). There was no significant difference in the prevalence of loneliness (13% vs 13%, p = 0.905). The unadjusted and adjusted prevalence of distress remained similar and significantly more frequent among caregivers in a sensitivity analysis conducted on a subsample representative of the general population (appendix table S2).

Caregiving responsibilities and evolution during the pandemic

The characteristics of the responding and non-responding caregivers are detailed in table S3 in the appendix: respondents were older (54 vs 50 years, p <0.001) and more often female (64% vs 58%, p = 0.040).

Among caregivers, 7% of the care recipients were spouses or partners, and 64% were first-degree relatives (table 2). Most caregivers cared for a single person (66%, figure S4 in the appendix). When caregivers cared for more than one person, the characteristics of the first and second care recipients they reported are shown in table S4 in the appendix. Care recipients often lived separately from their caregivers but within a 10 km distance. Ageing (78%) was the predominant reason for caregiving, with 63% of care recipients aged 80 years old or above (appendix figure S5). Help with instrumental activities of daily living (96%) and social support (66%) were frequent. Most caregivers (78%) received additional support from another informal (e.g. another caregiver or a volunteer) or formal (e.g. a home care nurse) source (appendix figure S6).

The pandemic appears to have influenced informal caregiving, with 40% of caregivers experiencing decreased healthcare availability, 61% expressing concerns about being unable to help their care recipient in case of COVID-19 or quarantine, and 24% feeling more isolated in their role since the pandemic onset. Among professionally active caregivers, 13% had to make occupational adaptations to accommodate their caregiving responsibilities, including taking paid leave (38%), work schedule flexibility (31%), reduction in working hours (23%) or resignation (6%) (appendix figure S7). In addition, 47% of caregivers experienced an increase in caregiving burden since the pandemic onset, primarily driven by increased care recipient needs (67%), willingness to limit contacts with the care recipient (61%), and reduced availability of other sources of formal support (34%) (appendix figure S8).

Risk and protective factors for distress in caregivers

Risk and protective factors for distress in caregivers are presented in tables 2, 3 and 4. Among caregiver-related factors, older caregivers had a lower likelihood of expressing mental distress, while those with limited social support presented a higher likelihood (table 2).

Among caregiving- and care recipient-related factors, caregivers caring for an individual with a mental condition and those living more than 10 km away from the care recipient had about 20% increased odds of suffering from mental distress. The caregiver and care-recipient’s degree of relationship, duration of care relationship, frequency of care, and older age of the care recipient (≥80 years old) were not significantly associated with mental distress, but the confidence intervals were large (table 3).

Among COVID-19 pandemic-related factors, caregivers feeling more isolated in their caregiving role since the pandemic onset, those worrying about the inability to carry the care responsibility due to COVID-19 or quarantine, and those experiencing decreased availability of healthcare workers had significantly higher odds of experiencing mental distress (table 4).

Sensitivity analyses showed similar results in direction and magnitude (tables S5 and S6 in the appendix), suggesting that these results may apply to the general population and are robust regardless of whether the caregiver cared for one or more persons.

Discussion

This study highlights higher mental distress in caregivers compared to non-caregivers 16 months after the onset of the COVID-19 pandemic. Caregivers reported perceiving significant changes in their caregiving responsibilities since the onset of the pandemic, including reduced healthcare access, increased concerns, feelings of isolation, occupational adjustments to meet their caregiving duties, and a greater caregiving burden. Low social support, caring for an individual with a mental condition, living far from the care recipient, feeling more isolated in one’s caregiver role and worrying about the inability to care in case of COVID-19 or quarantine were risk factors for mental distress in caregivers.

The proportion of caregivers varies significantly across countries and its definition tends to be polymorphous. The proportion of caregivers in our sample was 20%, aligning with previous findings in Europe, where between 5% and 44% of the population provide informal care [7–11]. Nonetheless, the open nature of the question used to identify caregivers leaves room for personal interpretation, reflecting each respondent’s own interpretation of their caregiver status. Therefore, it may have favoured the selection of those more deeply engaged in caregiving tasks, such as assistance with bathing or meal preparation, potentially underrepresenting those whose caregiving roles were purely administrative or social.

Both before and during the pandemic, the literature tends to describe poorer mental health in caregivers than in non-caregivers across multiple outcomes such as anxiety, depression, mental distress and suicidal ideation [4, 15, 18–25, 36–39]. These results are nuanced and could be explained by regional, caregiver subgroups (e.g. caregivers of a child with autism or adults with dementia) and measurement variations. In addition, findings in the context of the pandemic emerge from data collected at the beginning and/or at the height of the pandemic, and it remains unknown whether this effect will last over time. In this study, caregivers experienced more instances of mental distress and stress and a slightly lower level of well-being than non-caregivers. This result supports pre-pandemic research showing that caring for someone, while rewarding, can be stressful and burdensome, leading to adverse physical and mental effects, such as increased stress, depression, emotional and cognitive impairments, and decreased subjective well-being [14, 15, 40]. This burden arises from the demanding nature of caregiving responsibilities, which can limit the time caregivers have available to attend to their own health needs and directly affect physical health [41].

Among caregivers, several factors may contribute to depression, stress, and low subjective well-being. Caregiver-related factors such as sex, education or socioeconomic status were not significantly associated with mental distress in this study. This finding is contradictory to previous studies, which showed that females experience more negative impacts of caregiving on their mental health [42, 43]. There were no associations but wide confidence intervals for factors such as the degree of relationship, duration of the care relationship and frequency of care, which had been previously linked with poorer mental health among caregivers [15, 42, 43]. Other factors, including the caregiver’s responsibility for a care recipient with a mental condition and living at a distance, both adding stress and demands, were identified. These results partly support previous studies, which highlighted that mental health was negatively impacted by the presence of cognitive-behavioural disorders in care recipients [15, 42, 43]. Finally, limited social support was shown to be associated with poorer mental health among caregivers, as previously suggested [44].

The COVID-19 pandemic is thought to have exacerbated the regular emotional, physical and financial strains associated with caregiving [45] and introduced a distinct set of challenges for caregivers. Accordingly, in this study, approximately 40% of caregivers experienced a decrease in the availability of healthcare professionals who might have had difficulty maintaining routine health services due to the surge of patients with COVID-19 and restrictive public health measures. Consequently, caregivers had to assume additional responsibilities, including tasks typically performed by professional caregivers, and experienced increased workload, task complexity, and time commitment dedicated to caregiving, with potential financial implications. Given this context, nearly half of the caregivers reported that the burden of care had increased since the onset of the pandemic, primarily due to increased care recipient needs, limited contact with other individuals involved in caregiving and reduced availability of formal support systems. This finding is consistent with a trend reported throughout Europe [38, 46]. Over half of the caregivers reported concerns about being unable to help their care recipient due to COVID-19 or quarantine, and about a quarter felt more isolated in their role; they were more likely to suffer from mental distress, as previously identified [47]. Ultimately, the association between decreasing healthcare professional availability, not receiving any external support during the pandemic, and increased mental distress underscores the importance of formal and informal support networks in the context of caregiving. These networks are essential in preserving caregiver’s well-being and enhancing their capacity for providing optimal care to their recipients.

This study screened mental distress using the GHQ-12, scored with the Likert method (0–1–2–3), considering a threshold of 12 points. This scoring method is more reliable for screening depressive disorders than the binary method, where responses are scored as 0–0–1–1 [48], but results in a higher prevalence of mental distress (38% vs 20% using the binary method) by including individuals with milder symptoms of distress. Nonetheless, the high prevalence of mental distress underscores the difficult times encountered during the study period due to the disruptions caused by the health crisis.

Implications for public health policies and research

This study identified modifiable risk factors for distress in caregivers during a pandemic. In the event of a future pandemic or any events leading to disruption in healthcare systems, measures should be implemented to ensure that caregivers receive appropriate social support, including from formal and informal support networks. We also highlighted a need for rapidly implementable solutions when regular caregivers temporarily cannot provide care due to unforeseen personal or societal circumstances, including developing contingency plans, such as identifying backup caregivers, arranging temporary home nursing care or utilising temporary placement facilities. These measures would benefit both caregivers, who have particular needs, and their care recipients through continuity of care.

Mental health improved in the general population after the early stages of the pandemic [49]. However, the trajectory of caregiver mental health during the subsequent stages of the pandemic remains unknown, making it challenging to discern whether the impact of the pandemic is transient or long-lasting in this population. Longitudinal investigations are warranted to follow the evolution of informal caregivers’ well-being and mental health and provide insights into the possible lasting consequences of this global health crisis.

Strengths and limitations

This study had several strengths, including comprehensive data regarding sociodemographic status, mental health and caregiving responsibilities during the pandemic, derived from a cohort primarily composed of individuals randomly selected from the general population. While previous studies have mainly focused on specific populations of caregivers and care recipients, often suffering from severe conditions such as autism or dementia, this study included a wide range of caregivers and care recipients and thus might be more representative of real-life caregiving. Indeed, this approach allows the identification of shared characteristics and challenges they might face collectively.

Several limitations should be acknowledged. Including both a population-based sample and a sample of essential workers may have limited the representativeness of our findings. However, the results were similar when the analysis was restricted to participants from the population-based sample. Self-selection bias may have occurred at different levels: older, better-educated, and more health-conscious people are more likely to enrol in research studies and maintain participation over time, as commonly observed in cohort studies [50]. Caregivers may have been both more and less likely to answer the caregiving questionnaire, depending on their willingness to share their experiences and their exhaustion level. Unfortunately, the absence of pre-pandemic data prevented a direct comparison of mental health status and caregiving responsibilities change. Mental distress was measured when public health measures were progressively being eased in Switzerland, and its prevalence may have been lower than during the height of the pandemic but higher than in the post-pandemic period. Finally, caregiving responsibilities are influenced by societal, political, health and care settings, and these results should be generalised cautiously.

Conclusion

Sixteen months after the onset of the COVID-19 pandemic, most caregivers reported an increase in their caregiving burden. Compared to non-caregivers, they faced additional mental health challenges, which could be attributed to increased caregiving responsibilities and reduced support. Public health policies should ensure caregivers receive additional support and resources, such as social support, and continuity of care from formal caregivers, and include rapidly implementable solutions to maintain caregiving continuity, especially during pandemics.

Data availability

Data will be shared upon reasonable request.

Acknowledgments

The authors are indebted to the participants of the Specchio-COVID19 cohort for their commitment and cooperation. This study would not have been possible without the instrumental and passionate contribution of the staff in the Unit of Population Epidemiology, Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland; the professionalism of our partners Médecine & Hygiène and dotBase; and all our colleagues not included in the Specchio-COVID19 study group. We particularly thank the Specchio-COVID19 operational team, who dedicatedly responded to participants’ queries. We also thank the Corona Immunitas digital follow-up group for their help in developing the caregiver questionnaire.

Specchio-COVID19 study group: Isabelle Arm-Vernez, Andrew S. Azman, Delphine Bachmann, Antoine Bal, Jean-François Balavoine, Rémy P. Barbe, Hélène Baysson, Julie Berthelot, Aminata Rosalie Bouhet, Gaëlle Bryand-Rumley, François Chappuis, Prune Collombet, Sophie Coudurier-Boeuf, Delphine S. Courvoisier, Carlos de Mestral, Paola D’ippolito, Richard Dubos, Roxane Dumont, Nacira El Merjani, Antoine Flahault, Natalie Francioli, Clément Graindorge, Idris Guessous, Séverine Harnal, Samia Hurst, Laurent Kaiser, Gabriel Kathari, Omar Kherad, Julien Lamour, Pierre Lescuyer, Arnaud G. L’Huillier, Andrea Jutta Loizeau, Elsa Lorthe, Chantal Martinez, Shannon Mechoullam, Ludovic Metral-Boffod, Mayssam Nehme, Natacha Noël, Francesco Pennacchio, Didier Pittet, Klara M. Posfay-Barbe, Géraldine Poulain, Caroline Pugin, Nick Pullen, Viviane Richard, Déborah Rochat, Khadija Samir, Hugo Santa Ramirez, Etienne Satin, Philippe Schaller, Stephanie Schrempft, Claire Semaani, Silvia Stringhini, Stéphanie Testini, Anshu Uppal, Déborah Urrutia-Rivas, Charlotte Verolet, Pauline Vetter, Jennifer Villers, Guillemette Violot, Nicolas Vuilleumier, Ania Wisniak, Sabine Yerly, and María-Eugenia Zaballa.

Author contributions: CF was involved in conceptualisation, formal analysis, methodology and writing the original draft; NP was involved in conceptualisation, data curation, formal analysis, methodology, supervision, and writing, reviewing and editing the manuscript; HB was involved in investigation, project administration, conceptualisation, and writing, reviewing and editing the manuscript; MEZ was involved in conceptualisation, project administration, and reviewing and editing the manuscript; FP was involved in software implementation, data curation and reviewing and editing the manuscript; SS was involved in investigation and reviewing and editing the manuscript; SL was involved in conceptualisation, investigation, and reviewing and editing the manuscript; MN was involved in reviewing and editing the manuscript; IG was involved in conceptualisation, funding acquisition, project administration, and reviewing and editing the manuscript; SS was involved in conceptualisation, investigation, funding acquisition, project administration, and reviewing and editing the manuscript; EL was involved in conceptualisation, methodology, supervision, writing, and reviewing and editing the manuscript.

Declaration of Generative AI and AI-assisted technologies in the writing process: During the preparation of this work, the authors used AI-assisted technologies to improve readability and language. After using these tools, the authors reviewed and edited the content as needed and take full responsibility for the manuscript’s content.

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Appendix

The appendix is available in the pdf version of the article at https://doi.org/10.57187/s.3884.