Abstract
Background
With increasing longevity, more caregiving responsibilities fall on fewer family members, potentially impacting their well-being. This study investigates the health status, well-being, and elements of burden among informal caregivers of community-dwelling older adults receiving home care nursing in Iceland, including how burden may be related to well-being, gendered differences, and the complex nature of caregiving.
Methods
A cross-sectional survey was conducted in four municipalities. Informal caregivers completed a self-report questionnaire on their caring situation, health, and well-being. Correlation and regression analyses examined relationships between caregiver characteristics, burden, and well-being.
Results
A total of 483 informal caregivers participated, with an average age of 61 years (SD = 12, range: 25–95), 165 men (34.2%) and 318 women (65.8%). The average age of care recipients was 84 years (SD = 7, range: 66–100). Women reported higher levels of stress (80.4% vs. 73% of men) and scored higher on both the Multifaceted Strain Scale (7.43 vs. 4.95, scale 0–19) and the Role Overload Scale (1.00 vs. 0.64, scale 0–4). Score on the Caregiver Well-Being Index had positive correlations with the Multifaceted Strain Scale (ρ = 0.57, p < 0.001) and caregiver decreased social participation (ρ = 0.44, p < 0.001). Regression results showed that a lesser feeling of having a good life (β = 0.22, p < 0.001), the caregiver’s self-perception of burden (β = 0.20, p < 0.05) and score on the Multifaceted Strain Scale (β = 0.08, p < 0.001) significantly predicted caregiver well-being, with the full model explaining 41% of the variance in caregiver well-being.
Conclusions
Caregiver burden is a multidimensional construct with significant implications for caregiver well-being. Key predictors of reduced well-being include self-perceived burden, multifaceted strain, and a diminished sense of life satisfaction. Gender differences were notable, with women reporting higher levels of strain and role overload. These findings underscore the need for comprehensive and gender-sensitive support strategies. Addressing social, financial, physical, and psychological challenges may help improve caregiver well-being and, in turn, the quality of care delivered to older adults.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-025-06320-x.
Keywords: Informal caregiving, Informal caregiver, Caregiver well-being, Caregiver burden, Elements of burden, Gender differences
Background
An ageing global population leaves social and healthcare systems worldwide with challenges. By 2050, approximately one in five people will be age 60 years or older [1]. Declining birth rates and increased longevity lead to more responsibility for fewer descendants and relatives. This shift has various consequences, some detrimental to caregivers’ health and well-being, like poor sleep quality and less self-care [2]. This growing concern raises questions regarding caregiver well-being and potential support measures.
In recent years, in policy and practice, a growing trend is ageing in place. It combines the desires of ageing individuals and governmental efforts to delay and/or prevent institutionalisation, making public services as accessible as possible, while also emphasising cost-effectiveness. A side effect of this policy reform has been increased expectations towards the older persons’ next of kin regarding informal care. The prioritization of health and social services of those with higher care demands increases the responsibility placed on informal caregivers, no matter if they feel up for the task or not [3].
The estimated numbers of informal caregivers, depending on the definition used, range from 14.4% [4] to 25% [5] of the adult population in Europe and 23.4% in Canada [6]. Global estimations are not readily available [7]. A clear definition of what exactly constitutes caregiving is lacking, leading to differences in measurements and estimates [3, 8]. Informal caregiving has been described as „the act of providing unpaid assistance and support to family members or acquaintances who have physical, psychological, or developmental needs” (p.401) [9]. The concept was created to provide a clear contrast to formal care, with formal carers being those whose paid labour is to provide care [10].
Taking on the role of an informal caregiver can be both a rewarding and demanding task. Despite the growing number of individuals providing informal care, it is still undervalued, and informal caregivers are often overlooked as a group until a crisis occurs [11]. They are rarely recognized as an at-risk population despite emerging evidence suggesting otherwise [12]. Moreover, there is a growing body of research highlighting the significant impact of informal caregiving on both the caregiver and the person being cared for [13, 14]. It is therefore crucial to understand how the act of caregiving can be made easier for everyone involved.
Among the challenges reported by caregivers are financial difficulties [15, 16], sleep disturbances [17, 18] and reduction in overall health and well-being, both physical [19] and mental [20]. Caregivers report less social participation [21] and increased symptoms of depression [22]. Emerging evidence suggests an association between higher levels of loneliness and providing informal care [23]. Some caregivers might feel overwhelmed by caregiving demands and lack of resources to the point of being unable to continue caregiving [24]. Research has shown a higher level of compassion fatigue among adult children and spouse/partner caregivers than formal caregivers, indicating that caregiving is more challenging for the informal caregiver [25].
Reported caregiver burden and caregiver stress are present in most of the relevant literature. It is recognised as multifaceted and presents itself in various ways [26]. Influencing factors are still being identified, those that mediate or accelerate the experienced burden. Caregivers in similar situations experience different levels of burden. Positive outcomes, such as feelings of fulfilment or personal growth, also vary depending on individual circumstances [27]. This suggests that caregiving burden and capacity are not solely shaped by external factors such as the type of dependency of the person receiving care, but also by the caregiver’s own traits, health, and resilience.
It has been established that providing informal care to a loved one can significantly impact the caregiver in various ways. The term “caregiver burden” broadly describes the negative effects that informal caregiving can have on the caregiver. While different definitions exist, this paper examines caregiver burden using variables informed by the conceptual model created by Liu, Heffernan, and Tan [28]. The model, based on an extensive concept analysis, encompasses three main aspects of caregiver burden: (1) Antecedents, what comes before, (2) Attributes, what happens during, and (3) Consequences, what happens after; each consisting of three sub-elements. Each element results from a thorough analysis of existing literature on caregiver burden. The model builds on theoretical developments by Pearlin et al. on stress theory [29], the stress process model in relation to caregiving [30] and conceptualization by Bastawrous [31]. To firmly root our analysis within the current discussion surrounding informal caregivers, the conceptual model developed by Liu, Heffernan, and Tan [28] was used to identify variables representing elements of caregiver burden.
Fig. 1.
Conceptual model of caregiver burden.
Source: [28] Liu Z, Heffernan C, Tan J: Caregiver burden: A concept analysis. International Journal of Nursing Sciences 2020, 7(4):438–445. Licensed under CC BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/.
Numerous instruments, tools, and measurements exist to identify informal caregivers’ strengths, struggles, and support needs [32, 33]. The empirical data presented in this paper were gathered with a new self-report instrument for informal caregivers, the interRAI-SCaN. This research is the first of its kind on the Icelandic caregiver population. Research has been done on who provides informal care in Iceland and what it entails [34, 35], but not on the informal caregiver’s well-being, feelings, and needs.
For almost three decades, research has consistently shown that the majority of informal caregivers are women. They tend to dedicate more time to caregiving, provide care for longer periods, and are more likely to deliver intimate care [36, 37]. Societal gender norms and cultural values make it difficult for women to set boundaries in relation to their caregiver role, and as a result, leave them more vulnerable to the negative effects of caregiving [38]. This has also been observed in Iceland [37]. Given the growing reliance on informal caregivers, it is important to study further not only the gendered dynamics but also how these caregivers, regardless of gender, are coping with the demands and challenges of their roles.
The aim of this study is to investigate the health status, well-being, gender differences, and elements of burden among informal caregivers of community-dwelling older adults receiving home care nursing. In that effort, the following research questions are asked: What are the health status and overall well-being of informal caregivers of community-dwelling older adults receiving home care nursing services in Iceland, and how do these outcomes differ by gender? To what extent do informal caregivers in this population experience indicators of caregiver burden? What factors are associated with the presence and severity of caregiver burden among these informal caregivers?
Methods
Design and setting
This study had a cross-sectional design and was conducted in four municipalities in the capital area of Iceland. Iceland’s healthcare system is a state-centred, publicly funded model with universal coverage [39]. The study involves informal caregivers of older adults receiving home care nursing in the service area.
Sampling and participants
The study participants were informal caregivers identified by users of home care nursing services. This study employed a total population approach, including all individuals who were eligible and caregivers of older adults receiving services during the recruitment period. Care recipients aged 65 years and older were asked to name their caregivers, identifying one primary caregiver who provides the most assistance and, if applicable, a secondary caregiver who offers additional assistance in a lesser capacity.
Home care nursing staff contacted the identified informal caregivers by phone to introduce the study. Those who agreed to participate were sent a text message containing a link to the survey, hosted on a secure online platform.
Data collection procedures
The period of data collection took place from September 2022 to December 2023. The inclusion criteria were that the participant spoke Icelandic and was over the age of 18. Participants were excluded if they didn’t speak Icelandic or had themselves moved into long-term care at the time they were contacted. Each participant could only respond as the primary caregiver of one care recipient.
A total of 691 caregivers were contacted with an invitation to participate. 483 (70%, n = 691) participants signed in to the online platform, and of these, 338 (70%, n = 483) completed the questionnaire fully, either online or with assistance. Those who did not feel equipped to fill out the questionnaire online could either answer via telephone or in person. Of the 338 that were complete, 239 (70.7%, n = 338) were completed online while 99 (29.3%, n = 338) were completed with assistance. Thereof 13 (13.1%, n = 99) participants requested to answer the questionnaire in person, and 86 (86.9%, n = 99) via telephone. In-person assessments were responded to in the participants’ homes. One member of the research team was responsible for all participant support, a trained social worker, to maximise data consistency. All answers were recorded as the participant stated them, as the instrument is self-report only, and no clinical assessment is involved. See Supplemental Table S1 for the full participant flowchart. This study was approved by the Icelandic Ethical Review Committee (No: VSN-21-170) and the Scientific Committee of the Health Care Centre of the Capital Area (14.01.22).
Measures and scales
The instrument used in this study, the interRAI Self-Reported Carer Needs (SCaN) Assessment, was developed for use with informal caregivers to grasp the caregiver’s point of view [40]. The instrument was translated from English to Icelandic by five members of the research team with various professional backgrounds. Back-translation was performed by specialists at The Icelandic Health Science Institute and approved by the authors of the instrument, interRAI.
Demographic information collected included caregivers’ age and gender, care recipients’ age and gender, civil status, living arrangement, relationship to caregiver, length of caregiving, and caregiver status as primary or secondary caregiver.
The Caregiver Well-Being Index is a screener developed from items in the interRAI-SCaN instrument. It measures levels of well-being among informal caregivers on a scale of 1 to 4. The scale has been tested and validated and shown to effectively identify caregivers who may benefit from additional support in their caregiving roles. A higher score indicates a decrease in well-being and a higher risk of adverse outcomes [41]. In the present study, the Caregiver Well-Being Index demonstrated good internal consistency, with a Cronbach’s alpha (α = 0.88) and McDonald’s omega (ω = 0.88).
The Multifaceted Strain Scale was created by the authors of this study and is based on the conceptual model of caregiver burden [28]. According to the model, multifaceted strain is one of the attributes of caregiver burden. The scale measures the cumulative disruption across multiple aspects of daily life experienced by the caregiver. It includes eight variables: sleep difficulties, pain frequency, pain intensity, unstable health, questioning one’s ability to provide care, having no time for oneself, feeling exhausted, and self-rated health, all of which were used to represent various dimensions of caregiver strain (see Supplemental Table S2). The total score ranges from 0 to 19, with higher scores indicating greater strain. The included items reflect physical, emotional, and personal-life aspects of caregiver burden. The Multifaceted Strain Scale is a newly constructed measure; formal validation studies are pending. However, the items were theory-driven, based on a published conceptual model, and the scale showed good internal consistency as indicated by Cronbach’s alpha (α = 0.82) and McDonald’s omega (ω = 0.85) in the present sample.
The Role Overload Scale measures caregivers’ difficulties managing four areas of their lives: work, family, education, and finances, alongside their caregiving role. Each area is scored as 0 (no difficulty) or 1 (difficulty), and the total score ranges from 0 to 4, with higher scores indicating greater role overload [42]. In the present study, the Role Overload Scale exhibited lower internal consistency than other scales, with a Cronbach’s alpha (α = 0.61) and McDonald’s omega (ω = 0.64). The scale has previously been used and psychometrically evaluated among informal caregivers [42]. Role overload refers to the stress and burden that caregivers experience when balancing multiple responsibilities. Unlike the Multifaceted Strain Scale, which captures subjective and health-related aspects of burden, the Role Overload Scale focuses on external role conflict and competing responsibilities.
Statistical analysis
Data were presented as the mean and standard deviation for continuous variables, while frequency and percentage were used for categorical variables. T-test and Chi-square test were used to compare the basic features and health status among male and female informal caregivers. To assess scale reliability, inter-item consistency coefficients were calculated using Cronbach’s alpha (α) and McDonald’s omega (ω).
Correlations between key variables were assessed using Spearman’s rank correlation. Hierarchical multiple linear regression analysis was conducted to investigate the relationship between various predictor variables and the Caregiver Well-Being Index. In this study, the Caregiver Well-Being Index is the outcome variable. Predictor variables were chosen based on the conceptual model of caregiver burden [28]. Each variable employed from the SCaN instrument corresponds to an element in the caregiver burden model. For example, decreased quality of life, categorized under Consequences in the conceptual model, is represented by the question: ‘On the whole, my life is good’, measured on a five-point scale.
We employed four regression models to assess the predictive capacity of different variables on the Caregiver Well-Being Index score. Model 1 focused on background factors (caregiver age, care recipient age, female caregiver, female care recipient, married caregiver, spouse as caregiver, child or child-in-law as caregiver, shared home with care recipient, primary caregiver), model 2 examined antecedents (financial difficulties, multiple responsibility, decreased social participation), model 3 investigated attributes (self-perception of stress, multifaceted strain scale, over time), and model 4 addressed consequences (decreased care provision, on the whole my life is good, health deterioration). F-statistics and adjusted R-squared values were calculated to evaluate the model fit, indicating the proportion of variance in the Caregiver Well-Being Index score explained by the predictor variables. Durbin-Watson was utilised to assess the independence of residuals, ensuring that the regression analysis assumptions were met. Multicollinearity was assessed using Variance Inflation Factor (VIF) and tolerance values. The significance level was set at p < 0.05. Missing values were handled using listwise deletion. Only participants with complete data on the outcome variable (Caregiver Well-Being Index) were included in the regression analyses.
Results
Descriptive characteristics
Caregiver’s mean age was 61 years old for men (n = 165) and 60 years old for women (n = 318), with ages ranging from 25 years old in both groups, up to 93 years old for men and 95 years old for women. Care recipients’ mean age was 84 for men and women, ranging from 66 to 100 years old in both groups. More men (66.7%) were appointed as primary caregivers by the care recipient compared to women (57.5%). The chi-square test (χ² = 9.924, p = 0.002) shows a statistically significant difference in the distribution of male and female caregivers based on the gender of the care recipient. 73.3% of male caregivers care for female recipients, compared to 58.8% of female caregivers who care for female recipients. This shows that a higher proportion of men in the sample care for women. Examination of the standardised residuals shows that the only statistically significant cell in that analysis is men caring for men (25.1%, Standardised residuals: -2), with the total value being lower than expected.
Whether the caregiver shares a home with the care recipient also shows a statistically significant difference between genders (χ² = 5.393, p = 0.020). However, the standardised residuals for each cell are below the 1.96 significance threshold, and the Cramer’s V value is 0.112, indicating a very weak association (see Table 1).
Table 1.
Characteristics of informal caregivers and care recipients (N = 483 (in some cases, total available observations for a given variable are < 483 due to missing values))
| Variable | Men n (%) (n = 165) | Women n (%) (n = 318) | Total n (%)(n = 483) | Statistics | Sig | |
|---|---|---|---|---|---|---|
| Caregiver age | χ² 6.027 | NS | ||||
| 49 or less | 28 (17.0) | 55 (17.3) | 83 (17.2) | |||
| 50–64 | 73 (44.2) | 146 (45.9) | 219 (45.3) | |||
| 65–74 | 34 (20.6) | 83 (26.1) | 117 (24.2) | |||
| 75+ | 30 (18.2) | 34 (10.7) | 64 (13.3) | |||
| Mean age (SD) | 61 (13) | 60 (12) | 61 (12.3) | f 1.919 | NS | 0.167 |
| Care recipient age | χ² 2.858 | NS | 0.240 | |||
| 65–74 | 28 (16.0) | 33 (10.7) | 61 (12.6) | |||
| 75–84 | 58 (33.1) | 111 (36.0) | 169 (35.0) | |||
| 85+ | 89 (50.9) | 164 (53.2) | 253 (52.4) | |||
| Mean age (SD) | 84 (7.3) | 84 (7.5) | 84 (7.4) | f 0.027 | NS | 0.870 |
| Care recipient gender | χ² 9.924 | S | 0.002 | |||
| Male CR | 44 (25.1) | 131 (41.2) | 175 (36.2) | |||
| Female CR | 121 (73.3) | 187 (58.8) | 308 (63.8) | |||
| Caregiver civil status | χ² 2.219 | NS | 0.136 | |||
| Married / partner | 120 (85.7) | 233 (79.8) | 353 (81.7) | |||
| Single | 20 (14.3) | 59 (20.2) | 79 (18.3) | |||
| CG to CR relationship | χ² 5.113 | NS | 0.078 | |||
| Spouse | 31 (22.6) | 41 (14.0) | 72 (16.8) | |||
| Child or child-in-law | 99 (72.3) | 231 (79.1) | 330 (76.9) | |||
| Other | 7 (5.1) | 20 (6.8) | 27 (6.3) | |||
| Shared home | χ² 5.393 | S | 0.020 | |||
| CG shares a home with CR | 36 (26.5) | 49 (16.8) | 85 (19.9) | |||
| CG resides elsewhere | 100 (73.5) | 242 (83.2) | 342 (80.1) | |||
| Caregiver role | χ² 3.786 | NS | 0.052 | |||
| Primary caregiver | 110 (66.7) | 183 (57.5) | 293 (60.7) | |||
| Secondary caregiver | 55 (33.3) | 135 (42.5) | 190 (39.3) |
CG caregiver, CR care recipient, f F-statistic from ANOVA testing group mean differences, χ² Chi-squared statistic testing associations between categorical variables, SD standard deviation
Bivariate analyses
Multiple responsibility conflict was more prevalent among women (39.9%) than men (26.1%, χ² = 6.284, p = 0.012). Self-perception of caregiving as a source of stress was higher among women (χ² = 10.100, p < 0.001), with 50.0% of women reporting stress compared to 31.8% of men. A majority of caregivers (63.5%) feel stressed but do not intend to reduce the care they provide, and 84.4% consider their lives to be good always or most of the time. 57.2% rate their health as good or excellent (see Table 2).
Table 2.
Experiences and health of informal caregivers (N = 483 (in some cases, total available observations for a given variable are < 483 due to missing values))
| Variable | Men (n = 165) | Women (n = 318) | Total (n = 483) | Statistics | Sig | |
|---|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | ||||
| Caregiver financial difficulties | χ² 0.369 | NS | 0.543 | |||
| Yes | 10 (9.0) | 17 (7.1) | 27 (7.7) | |||
| No | 101 (91.0) | 221 (92.9) | 322 (92.3) | |||
| Caregiver multiple responsibility conflict | χ² 6.284 | S | 0.012 | |||
| No | 82 (73.9) | 143 (60.1) | 225 (64.5) | |||
| Yes | 29 (26.1) | 95 (39.9) | 124 (35.5) | |||
| Caregiver social participation | χ² 4.710 | NS | 0.095 | |||
| No change in participation | 66 (47.5) | 112 (39.6) | 178 (42.2) | |||
| Less, no distress | 48 (34.5) | 94 (33.2) | 142 (33.6) | |||
| Less, distress | 25 (18.0) | 77 (27.2) | 102 (24.2) | |||
| Caregiver self-perception of stress | χ² 10.100 | S | < 0.001 | |||
| No | 75 (68.2) | 119 (50.0) | 194 (55.7) | |||
| Yes | 35 (31.8) | 119 (50.0) | 154 (44.3) | |||
| Years spent caregiving by the caregiver | χ² 0.643 | NS | 0.423 | |||
| Less than 5 | 73 (54.5) | 170 (58.6) | 243 (57.3) | |||
| 5 or more | 61 (45.5) | 120 (41.4) | 181 (42.7) | |||
| Caregiver level of stress | χ² 5.354 | NS | 0.148 | |||
| Not stressed | 30 (27.0) | 47 (19.6) | 77 (21.9) | |||
| Stressed, but I will not change the care I provide | 71 (64.0) | 152 (63.3) | 223 (63.5) | |||
| Stressed, and I need to reduce the care I provide | 9 (8.1) | 36 (15.0) | 45 (12.8) | |||
| Stressed to the point of crisis, will stop caring | 1 (0.9) | 5 (2.1) | 6 (1.7) | |||
| On the whole, my life is good | χ² 7.048 | NS | 0.133 | |||
| Always | 56 (50.9) | 91 (38.2) | 147 (42.2) | |||
| Most of the time | 38 (34.5) | 109 (45.8) | 147 (42.2) | |||
| Sometimes | 11 (10.0) | 22 (9.2) | 33 (9.5) | |||
| Rarely | 5 (4.5) | 12 (5.0) | 17 (4.9) | |||
| Never | 0 (0.0) | 4 (1.7) | 4 (1.1) | |||
| Health deterioration (0–17) | f 0.623 | NS | 0.280 | |||
| Mean (SD) | 2.3 (2.3) | 2.6 (2.3) | 2.5 (2.2) | |||
| Caregiver self-rated health | χ² 7.721 | NS | 0.052 | |||
| Excellent | 9 (8.1) | 16 (6.6) | 25 (7.1) | |||
| Good | 66 (59.5) | 111 (45.9) | 177 (50.1) | |||
| Fair | 30 (27.0) | 88 (36.4) | 118 (33.4) | |||
| Poor | 6 (5.4) | 27 (11.2) | 33 (9.3) |
f F-statistic from ANOVA testing group mean differences, χ² Chi-squared statistic testing associations between categorical variables, SD standard deviation
Scale reliability
Women had a higher average score on the Multifaceted Strain Scale (M = 7.43, SD = 5.05) compared to men (M = 4.95, SD = 4.19; f = 7.48, p = 0.007). In addition, there was a significant difference between the group mean scores on the Caregiver Well-Being Index (f = 8,157, p < 0.005). Among women, the mean score was 1.65 (SD = 0.95) and 1.39 (SD = 0.83) among men on a scale of 1–4, a higher score indicating a decrease in well-being (see Table 3). Comparison of scales by gender was also conducted, including only cases used in the regression analysis, with little to no difference in the results (see Supplemental Table S3).
Table 3.
Comparison of scales by gender (N = 483 (in some cases, total available observations for a given variable are < 483 due to missing values))
| Variable | Men (n = 165) | Women (n = 318) | Total (n = 483) | Statistics | Sig | |
|---|---|---|---|---|---|---|
| n (%) | n (%) | n (%) | ||||
| Caregiver Well-Being Index (1–4) | χ² 11.330 | S | 0.010 | |||
| Excellent well-being | 87 (78.4) | 146 (60.6) | 233 (66.2) | |||
| Good well-being | 11 (9.9) | 53 (22.0) | 64 (18.2) | |||
| Fair well-being | 7 (6.3) | 23 (9.5) | 30 (8.5) | |||
| Poor well-being | 6 (5.4) | 19 (7.9) | 25 (7.1) | |||
| Mean | 1.39 | 1.65 | 1.57 | f 8.157 | S | 0.013 |
| SD | 0.833 | 0.947 | 0.92 | |||
| Multifaceted strain scale (0–19) | f 7.477 | S | 0.001 | |||
| Mean | 4.95 | 7.43 | 6.67 | |||
| SD | 4.19 | 5.05 | 4.92 | |||
| Role overload scale (0–4) | f 0.811 | S | 0.002 | |||
| Mean | 0.64 | 1.00 | 0.89 | |||
| SD | 0.95 | 1.08 | 1.05 |
f F-statistic from ANOVA testing group mean differences, χ² Chi-squared statistic testing associations between categorical variables
Inter-item consistency was calculated for the three scales used in the study, measured using Cronbach’s alpha (α) and McDonald’s omega (ω) [43]. The Caregiver Well-Being Index demonstrates high reliability with both α and ω values of 0.88. The Multifaceted Strain Scale also shows good reliability, with an alpha of 0.82 and an omega of 0.85. In contrast, the Role Overload Scale exhibits lower reliability, with an alpha of 0.61 and an omega of 0.64. These values indicate the internal consistency of the scales, with higher values suggesting better reliability.
Correlational findings
There was a positive correlation between the caregiver well-being score and the score on the Role Overload Scale (ρ = 0.30, p < 0.001), suggesting decreased well-being with increased stress and burden, measured by the Role Overload Scale. The Caregiver Well-Being Index score also positively correlated with scores on the Multifaceted Strain Scale (ρ = 0.57, p < 0.001), indicating that worse caregiver well-being goes hand in hand with increased caregiver strain. The caregiver well-being score is positively correlated with decreased social participation (ρ = 0.44, p < 0.001) and self-perceived burden (ρ = 0.39, p < 0.001), suggesting that less social involvement and the caregiver’s self-perception of more burden are associated with diminished caregiver well-being. The caregiver well-being score exhibited a positive correlation with reported financial difficulties (ρ = 0.29, p < 0.001), indicating that financial difficulties are adversely associated with caregiver well-being.
When analysing the correlation between the Role Overload Scale and other key variables, the highest significant positive was with caregiver self-perceived burden (ρ = 0.45, p < 0.001). Caregivers’ age on the other hand had the highest significant negative correlation with the Role Overload Scale (ρ = -0.36, p < 0.001), suggesting an association between increased age and decreased caregiver stress and burden. There was a significant negative association between being a spousal caregiver and scores on the Role Overload Scale (ρ = -0.21, p < 0.001); in contrast, a significant positive correlation was found between being a child, or a child-in-law, of the care recipient and a higher score on the Role Overload Scale (ρ = 0.23, p < 0.001). Other significant positive correlations with scores on the Role Overload Scale include reported multiple responsibility conflict (ρ = 0.36, p < 0.001) and scores on the Multifaceted Strain Scale (ρ = 0.30, p < 0.001). Correlations with scores on the Multifaceted Strain Scale showed a significant association between decreased social participation (ρ = 0.51, p < 0.001), the presence of self-perceived burden (ρ = 0.44, p < 0.001), and reported financial difficulties (ρ = 0.32, p < 0.001) (see Supplemental Table S4). Significant correlations are presented in Fig. 2.
Fig. 2.
Heatmap of significant correlations between the caregiver well-being index and related factors
Multivariate models
The regression analysis examined the impact of various predictors on the Caregiver Well-Being Index Score across four models. A higher score on the caregiver well-being index indicates a decrease in well-being. Model 1 included only background factors, while Models 2 through 4 sequentially added antecedents, attributes, and consequences.
Model 1 accounted for background factors, explaining 7% of the variance (F = 4.00, p < 0.001). Significant predictors included caregiver (CG) age (β = -0.02, p < 0.01), care recipient (CR) age, (β = 0.02, p < 0.05), female CG (β = 0.27, p < 0.01), and married CG (β = -0.36, p < 0.01).
Model 2 added antecedents, increasing the explained variance to 24% (F = 8.57, p < 0.001). Financial difficulties (β = 0.83, p < 0.001) and decreased social participation (β = 0.51, p < 0.001) were significant predictors, in addition to the previously significant background factors.
Model 3 incorporated attributes, raising the explained variance to 37% (F = 14.47, p < 0.001). Significant predictors included self-perception (β = 0.29, p < 0.01) and the Multifaceted Strain Scale (β = 0.08, p < 0.001), alongside caregiver age (β = -0.01, p < 0.05), care recipient age (β = 0.02, p < 0.05), and financial difficulties (β = 0.36, p < 0.05).
Model 4 integrated consequences, which explained 41% of the variance (F = 14.11, p < 0.001). Significant predictors in the final model were care recipient age (β = 0.02, p < 0.01), decreased care provision (β = 0.15, p < 0.05), a lesser feeling of having a good life (QOL) (β = 0.22, p < 0.001), health deterioration (β = -0.05, p < 0.05), self-perception of stress (β = 0.20, p < 0.05), and the score on the Multifaceted Strain Scale (β = 0.08, p < 0.001).
Across models, caregiver and care recipient age remained consistently associated with well-being, while other factors emerged as significant as models became more comprehensive. Entering the background factors, antecedents, attributes, and consequences all significantly enhanced the model’s predictability, indicating that the source of caregiver well-being is multidimensional. The Durbin-Watson statistics across all models were within the acceptable range (1.60–1.85), indicating no serious autocorrelation issues. All but two predictors were within acceptable collinearity limits (Variance Inflation Factor [VIF] < 5; Tolerance > 0.2). Spouse as caregiver (VIF = 10.1) and shared home (VIF = 6.5) showed elevated values but were retained due to theoretical relevance (see Table 4).
Table 4.
Regression model for the effects of predictors on caregiver well-being (N = 347 (listwise deletion was applied))
| Model 1 | Model 2 | Model 3 | Model 4 | |
|---|---|---|---|---|
| Background factors | β | β | β | β |
| CG age | -0.02** | -0.02* | -0.01* | -0.01* |
| CR age | 0.02* | 0.02* | 0.02* | 0.02** |
| Female CG | 0.27** | 0.25* | 0.00 | -0.03 |
| Female CR | -0.03 | -0.08 | -0.08 | -0.06 |
| Married CG | -0.36** | -0.21 | -0.17 | -0.14 |
| Spouse as CG | 0.15 | 0.20 | 0.32 | 0.36 |
| Child/in-law as CG | -0.29 | -0.34 | -0.24 | -0.22 |
| Shared home | 0.45 | 0.18 | -0.11 | -0.17 |
| Primary caregiver | 0.03 | 0.05 | 0.07 | 0.08 |
| Antecedents | ||||
| Financial difficulties | 0.83*** | 0.36* | 0.25 | |
| Multiple responsibility | 0.02 | -0.14 | -0.10 | |
| Decreased social participation | 0.51*** | 0.13 | 0.06 | |
| Attributes | ||||
| Self-perception of stress | 0.29** | 0.20* | ||
| Multifaceted strain scale | 0.08*** | 0.08*** | ||
| Over time | 0.04 | 0.02 | ||
| Consequences | ||||
| Decreased care provision | 0.15* | |||
| On the whole, my life is good | 0.22*** | |||
| Health deterioration | -0.05* | |||
| Model statistics | ||||
| F-statistic | 4.00 | 8.57 | 14.47 | 14.11 |
| df | 9 | 12 | 15 | 18 |
| p | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
| R Square adj. | 0.07 | 0.24 | 0.37 | 0.41 |
| Durbin-Watson | 1.60 | 1.83 | 1.85 | 1.81 |
CG caregiver, CR care recipient, F F-statistic testing model significance, df degrees of freedom, p P-value for F, R² adj. adjusted R-squared, Durbin-Watson test for residual autocorrelation; β standardized regression coefficient. *** p < 0.001 ** p < 0.01 *p < 0.05
Discussion
The findings of this study show how various elements of caregiver burden may be related to well-being among informal caregivers of home-dwelling older adults receiving home-care nursing. They suggest that challenges are rarely limited to one area of caregiving. Difficulties in one aspect of the caregiving role can lead to challenges in other areas or appear simultaneously. The results indicate that caregiver burden and well-being are complex and multidimensional, with the caregiver’s self-perception of stress being an important predictor of well-being.
The results show that a big portion of the sample considers themselves in relatively good health and the caregiving situation manageable, with 21.9% reporting not being stressed by caregiving and 63.5% reporting being stressed but not about to change the care they provide. 84.4% say that on the whole, their life is good, and only 9.3% report their self-rated health as poor. These findings align with a recent Swedish study that reported that a majority of people providing informal care (57.9%) did not describe it as burdensome, while 8.3% said that their self-rated health was quite bad or bad [44]. Another Swedish study presented findings on different caregiver profiles, highlighting that caregivers are not a homogeneous group and arguing for a broad spectrum of support measures [45]. These findings underscore the importance of identifying those who do not manage their caregiving situation well and ensuring targeted support for those caregivers.
Results revealed numerous differences between male and female caregivers in Iceland. Women had higher levels of stress and higher scores on the Multifaceted Strain Scale, and on the Role Overload Scale compared to their male counterparts, aligning with previous research that highlights gender differences in caregiving roles [35, 38]. This difference should be considered as it could impact the caregiver’s health and caregiving abilities [46]. These findings align with suggestions for interventions and support systems in wider caregiving contexts, acknowledging the unique challenges men and women face in caregiving roles. Interestingly, while prior studies found financial strain to be a serious issue among informal caregivers [13], it seems to be minimal in this study, with only 7.7% of participants reporting financial difficulties. One study reported that 80% of caregivers of chronically ill older adults in Thailand experienced financial strain [47]. Another study showed the prevalence of high financial hardship was 52% among informal caregivers in USA [48]. The discrepancy in financial difficulties might be due to differences in the health care systems, social welfare systems, and financial compensation available across countries. Iceland’s universal public health insurance provides extensive coverage of services [49] and the pension system is run on mandatory occupational pension funds, making it sustainable and available to all [50]. Both of these factors likely contribute to the low frequency of financial strain.
Results indicated that scores on the Multifaceted Strain Scale, decreased social participation, self-perceived stress, the Role Overload Scale, and financial difficulties were strongly associated with the Caregiver Well-Being Index scores. Higher scores on these variables correlated with poorer well-being outcomes, indicating that as these challenges increase, the well-being of caregivers deteriorates. These results highlight the value of considering all aspects of the caregiving role and harmonise with previous suggestions by Sigurðardóttir and Ernsth Bravell [51] that offering services early on might make caregivers feel more capable in their role. In a study conducted by Conway [52] caregivers reported feeling unprepared and ill-equipped for their caregiving role while still seeing it as their duty, emphasizing the importance of appropriate support measures.
Caregiver self-perceived burden and caregiver age are strongly associated with the Role Overload Scale, with older caregivers showing lower scores. The findings suggest that interventions aimed at reducing perceived burden and addressing the needs of younger caregivers, with multiple responsibilities, may be beneficial in lightening the stress and burden represented by the Role Overload Scale. The decreasing score with increasing age observed in this study may be linked to a reduction in responsibilities as caregivers age, or adaptation to the role, as noted in previous studies [53, 54]. A recent longitudinal study conversely suggests that adjustment to the caregiver role varies and is not attainable in some cases [55]. The concept of adaptation to the caregiver role over time, therefore, warrants further research in and of itself. This interpretation aligns with elements of the stress process model [30], which emphasizes how primary stressors, secondary strains, and coping resources interact to shape caregiver outcomes. Within this framework, adaptation and resilience are not viewed as fixed traits but as dynamic processes that unfold over time in response to ongoing stressors.
Findings revealed the Multifaceted Strain Scale had a significant association with decreased social participation, suggesting that caregivers experiencing higher levels of strain may withdraw from social participation, or vice versa. Social participation is a key component of well-being in older age, as outlined by the WHO [56]. Furthermore, research indicates that social participation is positively associated with carers’ mental health and subjective well-being [57]. The results of this study suggest that carers who experience caregiver strain are the same caregivers who cannot keep up with former levels of social participation. That is in line with previous studies where caregivers have admitted they would want to spend more time on physical activities, hobbies, and their social lives than they can while in their caregiving role [21]. This is why it is important to make respite and in-home services for the care recipient more accessible.
The Multifaceted Strain Scale also had a significant association with self-perceived burden, highlighting that caregivers’ self-perception of their burden is a critical factor influencing various aspects of the caregiving experience, including caregiver strain. Caregivers who are able to describe their own qualities or strengths reported less burden in a study by Rattray et al. [58] indicating that positive self-perception can be a source of empowerment and resilience for the caregiver. The caregiver’s experienced burden has been shown to be moderated by the caregiver’s mental health, relationship quality, and social support in a study done by Tough, Brinkhof, and Fekete [59]. Helping caregivers focus on the positive aspects of caregiving has been identified as a key coping mechanism for caregivers [11]. Therefore, it is valuable to highlight the caregiver’s strengths and build on them to reduce the burden and enhance well-being. Building on the caregiver’s strength also aligns with our results that most of the caregivers want to continue as carers despite feeling stressed.
Using the caregiver burden conceptual framework by Liu, Heffernan, and Tan [28] different aspects of caregiver burden were applied to better understand what impacts caregiver well-being by running correlations and regression models. Caregiver and care recipient age consistently predicted scores on the Caregiver Well-Being Index across all models. Specifically, older caregivers reported higher levels of well-being, while increasing the care recipient’s age was associated with a decline in the caregiver’s well-being. These findings align with previous research indicating that care recipient age-related physical and cognitive limitations can exacerbate caregiver burden [60].
Financial difficulties were a significant predictor in Model 2, suggesting that economic strain is a critical antecedent influencing caregiver well-being. This fits the conceptual framework that suggests economic challenges increase caregiver burden [28], potentially due to the additional financial costs associated with caregiving. Or, as suggested by other studies, the reduced ability to participate in the labour market [16]. It was still a significant predictor in Model 3, but not in Model 4, suggesting that as other factors of caregiver burden are considered, financial strain plays a smaller role in overall well-being, at least in this sample.
Self-perception and scores on the Multifaceted Strain Scale (measured in Model 3 and Model 4) were significantly associated with caregiver well-being. Caregivers with negative self-perceptions and higher levels of strain reported poorer well-being. This aligns with previous literature emphasising the need for psychosocial interventions to help caregivers manage strain [61]. The results of this study strengthen the argument for interventions aimed at addressing self-perception and strain to improve caregiver well-being.
Consequences like decreased care provision by the caregiver and a lesser feeling of having a good life were also significant in the final model (Model 4), revealing how caregiving responsibilities can impact caregivers’ ability to provide adequate care and their life satisfaction. This aligns with prior studies linking caregiver burden to lower quality of life and well-being [42, 44]. The continued significance of new factors added to the model underscores how complex the concept of caregiver burden truly is and the need to holistically assess every caregiver’s unique situation.
By examining how various elements of caregiver burden impact caregiver well-being, the results of this study can inform interventions that can improve caregiver well-being and address issues related to caregiver burden. Understanding these relationships is crucial for developing targeted programs and policies to decrease caregiver burden and increase the well-being of caregivers, ultimately benefiting the individuals they care for as well. Although interventions aimed at informal caregivers are of high relevance, it is important to note that adequate and well-functioning old age care, such as home help or home nursing aimed at the recipient of care, is also of importance for the informal caregivers.
Based on the identified associations between elements of caregiver burden and caregiver well-being, the findings could inform the development of screening tools to identify caregivers at risk of experiencing caregiver burden. Early interventions could include counselling, support groups, educational resources, or respite care, aimed at preventing the escalation of experienced burden and sustaining caregiving capacity.
Strengths, limitations, and future research
A strength of this study is that it provides important information on an understudied vulnerable population in Iceland, namely, informal caregivers. The study contributes valuable local data and allows for comparison with international findings. While it’s possible that individuals experiencing the most severe burden may not have felt equipped to participate, the diversity of the sample across different age groups, genders, and caregiving roles still offers insight into the informal caregiver population in Iceland.
As 30% of participants who signed into the online platform did not complete the questionnaire, there is a risk of nonresponse bias. This may particularly limit the representation of caregivers who are less willing or able to engage in conventional research formats, potentially resulting in an underestimation of the burden or unmet needs in this subgroup. Findings may be generalisable to similar community care contexts, though limited by regional characteristics and non-response.
Some participants may have found the questionnaire more technically challenging than anticipated, which might contribute to the lower completion rate. The instrument is, however, still under development and will be optimised through continuing research. Another limitation is that the study was cross-sectional; thus, the cause-and-effect relationships were not established, and it was impossible to explore caregiver well-being trajectories over time.
Future research should include longitudinal studies on caregiver well-being and the caregiving trajectory. The effectiveness of tailored support interventions, such as respite care, caregiver support groups, and disease-specific education, should be researched. Effort should be put into innovative ways to enhance caregiver well-being and prevent or reduce caregiver burden, starting with input from caregivers themselves and the use of participatory research methods.
Conclusion
Findings suggest that the health and well-being of informal caregivers of community-dwelling older adults receiving home care nursing services in Iceland are associated with several factors. An emerging one is the caregiver’s self-perception of burden. Healthcare and social professionals should recognise the potential implications of informal caregiving and proactively address caregivers’ needs before the accumulation of issues leads to poor well-being. Complex challenges require multilayered approaches; thus, caregiver well-being should be evaluated and monitored to offer suitable services at every caregiving stage in diverse forms. It is not a ‘one-size-fits-all’ matter.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors would like to thank Hrafnhildur Eymundsdóttir and Eva Kristjánsdóttir for their contribution. This work is published in respectful memory of Professor Emeritus Þorsteinn Vilhjálmsson.
Abbreviations
- CG
Caregiver
- CR
Care recipient
- SCaN
the interRAI Self-Reported Carer Needs (SCaN) Assessment
Author contributions
Designed and conceptualised the study: KB, IH, SHS, TA. Secured funding: KB. Conducted analyses: KO, SSS. Drafted the manuscript: SSS. Managed the work and assisted in drafting: IH, and SHS. Interpreted results and revised the manuscript: KB, IH, SHS, MJ, KO, TA. All authors approved the final manuscript.
Funding
The St. Joseph’s Hospital Foundation funded this study through a research grant from the Research Centre for Gerontology at the National University Hospital of Iceland and the University of Iceland (RHLÖ). Open access funding was provided by the Science and Welfare: The Sigrún and Þorsteinn Fund. The interpretation and conclusions contained herein do not represent those of the funding agencies.
Data availability
The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Directorate of Health, Reykjavík, Iceland.
Declarations
Ethics approval and consent to participate
Ethics approval was obtained from the Icelandic Ethical Review Committee (No: VSN-21-170) and the Scientific Committee of the Health Care Centre of the Capital Area (14.01.22). Informed consent was secured electronically from all participants via the online platform used.
Consent for publication
Not applicable.
Clinical trial number
not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at the Directorate of Health, Reykjavík, Iceland.