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Low quality of life and psychological wellbeing contrast with moderate perceived burden in carers of people with severe multiple sclerosis

Journal of the Neurological Sciences, Volume 366, July 2016, Pages 139 - 145

Abstract

Background

Few studies have investigated wellbeing and burden in carers of people with severe multiple sclerosis (PwSMS).

Objectives

To assess the impact of providing care to PwSMS, and explore variables associated with perceived carer burden.

Methods

Cross-sectional assessment of health-related quality of life (HRQOL), mood symptoms (Hospital Anxiety and Depression Scale, HADS), and perceived carer burden (22-item Zarit Burden Interview, ZBI) in 78 PwSMS carers. Multivariate linear regression explored carer and PwSMS factors associated with ZBI score.

Results

Carers (61% women, mean age 60.2 years, 53% spouse/partner) had significantly lower HRQOL (all SF-36 scales) than the norm, especially for Role Limitation Emotional/Physical, and Emotional Wellbeing. Sixty-eight percent had pathologic (≥ 8) Anxiety, and 44% had pathologic Depression scores on HADS. Nonetheless, perceived carer burden was only moderate (mean ZBI score 35.6, SD 14.3). High carer anxiety (p < 0.0001), low household income (p = 0.009), and living with the PwSMS (p = 0.02) were independent predictors of perceived burden.

Conclusions

Caring for PwSMS has a detrimental effect on HRQOL and psychological wellbeing. High carer anxiety, low economic status, and living in predict higher burden. It is crucial to recognize PwSMS carers as full partners in the provision of care, and to respond to their own needs.

Highlights

  • Caring for people with severe MS has a detrimental effect on quality of life.
  • Nonetheless, perceived carer burden was only moderate.
  • High carer anxiety, low economic status, and living in predict higher burden.
  • It is crucial to recognize carers as full partners in the provision of care.

Keywords: Primary progressive multiple sclerosis, Secondary progressive multiple sclerosis, Caregivers, Illness burden, Quality of life, Outcome measure, Palliative care.

1. Introduction

Around 15% of people with multiple sclerosis (MS) have a progressive course from the outset (primary progressive MS), and a further 65% develop progressive disease after a variable period with relapsing-remitting course (secondary progressive MS) [1]. For those with primarily or secondarily progressive MS, treatment options to delay or prevent further clinical worsening are limited [2] and life expectancy is reduced by about a decade [3]. Post-marketing studies on disease-modifying MS treatments suggest that they may prolong survival [4]. Thus, people with MS can live for many years in a highly dependent condition.

A systematic literature review on 2097 carers of people with MS at all disease stages [5] revealed a huge impact on several aspects of carer life. More recent studies found reduced carer mental health, physical health, and health-related quality of life (HRQOL) [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], and [16].

We found only two studies that focused on carers of persons with severe MS (PwSMS), both of which used a qualitative approach. Golla et al. recently assessed the unmet needs of 12 carers of PwSMS in Cologne, Germany [17]. They found that carers and PwSMS formed a tight dyad, such that carers tended to group the unmet needs of the PwSMS with their own and rarely focused on their own wishes and restrictions. Similarly, a qualitative Italian study [18] uncovered emotional ‘contagion’ between PwSMS and their carers: the latter felt themselves to be the exclusive interpreters and providers of their loved ones' needs, and reported a profound sense of isolation and fear for the future.

In developing best practices to improve outcomes for people with chronic and progressive neurological diseases, it is important to gain insight into levels of burden, psychological distress, and HRQOL in carers [19]. In the present study, we assessed the consequences of providing care to PwSMS, and explored factors associated with perceived carer burden. The study was a secondary (cross-sectional) analysis of baseline data of the ongoing PeNSAMI trial [20], conducted on Italian PwSMS and their carers. Carer outcome measures were the 22-item Zarit Burden Interview (ZBI) [21] and [22], the Short Form-36 (SF-36) [23], and the Hospital Anxiety and Depression Scale (HADS) [24].

2. Methods

2.1. Ethical approval

The study was approved by the Ethics Committees of the C. Besta Neurological Institute and Foundation, Milan; the S. Lucia Foundation, Rome; and the University Hospital of Catania. The trial is registered with Controlled Clinical Trials (trial registration number ISRCTN73082124).

2.2. Design and participants

The ongoing PeNSAMI trial to determine the effectiveness of a home-based palliative approach for PwSMS and their carers has been described in detail elsewhere [20]. The present cross-sectional study is a secondary analysis of selected baseline (pre-randomization) data. The carer was a family member, relative, friend, next of kin or key decision maker, as designated by the (cognitively competent) MS patient. Paid carers were included, provided they were the patient's next of kin or a key decision maker. Carers of PwSMS with severe cognitive compromise were designated by the patient's referring physician. Informed written consent was obtained from all patients and carers during pre-study evaluation.

2.3. Outcome measures

Three questionnaires (cited in order of administration) were completed by carers: HADS [24], SF-36 [23], and ZBI [21] and [22]. Carers of PwSMS with severe cognitive compromise also completed carer versions of the Core-Palliative care Outcome Scale (Core-POS) [25] and [26] and Palliative Care Outcome Scale-Symptoms-MS (POS-S-MS) [27].

HADS consists of 14 multiple choice (0–3 Likert scale) items probing symptoms of anxiety (7 items) and depression (7 items). HADS Anxiety and Depression scores range from 0 (no symptoms) to 21 (most severe symptoms) [24].

SF-36 is a widely-used self-reported generic measure of HRQOL consisting of 36 items in eight domains (Physical Functioning, Social Functioning, Role Limitation Physical, Role Limitation Emotional, Pain, Vitality, Mental Health, and General Health) grouped into two composite scales (Physical Health Composite, PHC and Mental Health Composite, MHC) [23].

ZBI is the most widely-used instrument for measuring carer subjective burden [22], [28], and [29]. It contains 22 questions each with five possible Likert-like responses, ranging from 0 “never” to 4, “nearly always”. Total score ranges from 0 to 88, a higher score indicating greater perceived carer burden.

We used the existing Italian versions of HADS [30], SF-36 [31], ZBI [21], and Core-POS; we translated the POS-S-MS into Italian (forward and backward translation procedures) from the original English version [32]. Household income was obtained from the Italian Revenue Agency - Tax Register Information System.

2.4. Statistical analyses

Continuous data were summarised by means and standard deviations, or medians and ranges or interquartile ranges (IQRs), as appropriate. Categorical data were summarised by frequencies. The normality of the distribution of variables was tested using the Shapiro–Wilk W test. Differences across centers were tested by Kruskal–Wallis or ANOVA for continuous variables, and chi-square test for nominal and ordinal variables. Internal consistency was assessed by Cronbach's alpha, with values above 0.70 considered to indicate good internal consistency [33]. We calculated the percentages of subjects with minimum and maximum scores: values > 20% indicated a floor or ceiling effect. Item-total correlations in the 0.30–0.70 range were considered adequate [33]. SF-36 scale scores for carers were compared with Italian norms (n = 2031 adults) [31] using two-sample with unequal variances t-tests.

We used linear regression modeling to investigate variables associated with ZBI score (dependent variable). The following independent variables were investigated: carer variables – gender, age, education, living with the PwSMS, HADS Anxiety and Depression scores, SF-36 PHC and MHC scores; PwSMS variables – gender, age, education, age at MS diagnosis, course, presence of severe cognitive compromise, Expanded Disability Status Scale (EDSS) score [34], Functional Independence Measure (FIM) score [35], Core-POS score, POS-S-MS score, number of relatives living with him/her, and household income.

For HADS Depression, the cutoff was the pathologic score (≥ 8); for the other independent continuous variables with non-normal distribution (EDSS, FIM, POS-S-MS, carer age, PwSMS age, age at MS diagnosis, number of relatives living with the PwSMS, and household income) the cutoff was the median. Independent variables significant in the univariate analyses were included in a multivariate model using a stepwise approach. The normality of residuals was checked using kernel density, standardized-normal, and quintile-normal plots; heteroskedasticity was assessed with the Breusch-Pagan test; multicollinearity was assessed by the variance inflation factor (acceptable values < 10). All statistical tests were two-tailed; differences were considered significant at an alpha level of < 0.05. Data were analyzed using Stata release 12 (Stata Corp LP, College Station, TX, USA).

3. Results

Between January and November 2015, 78 PwSMS-carer dyads received the baseline visit. Table 1 shows information on carers and the PwSMS. Mean carer age was 60.2 years (range 23–84); most (62%) were women. Fifty-three percent were spouses of the PwSMS, 15% parents, 10% sons/daughters, and 17% other relatives; 3 (4%) were paid carers. The latter were immigrant women (two from Romania and one from El Salvador) in Italy from 7, 10 and 12 years; two cared for the PwSMS for 2 years, one for 6 years; two were 31 and one 56 years old; two had secondary education and one college education.

Table 1

General and clinical characteristics of the 78 carer-PwSMS dyads.

 

Characteristic Carers PwSMS
No (%)
Women 48 (62) 43 (55)
Age (years)a 60.2, 61.0 (23–84) 59.2; 58.3 (41–80)
Education: No education completed 0 1 (1)
 Primary (5–8 years) 27 (34) 30 (38)
 Secondary (12–13 years) 32 (41) 31 (40)
 College/university (14 + years) 19 (25) 16 (21)
Occupation: Employed 35 (44) 4 (5)
 Retired (age) 25 (32) 10 (13)
 Housewife 14 (18) 0
 Unemployed 2 (3) 1 (1)
 Student 2 (3) 0
 Retired (disability) 0 63 (81)
Age at MS diagnosis (years)a 37.0; 35.5 (16–66)
EDSS scorea 8.49; 8.5 (8.0–9.5)
Severe cognitive compromise 15 (19)
Paid caregiver available 24 hb 18 (23)
2014 Household income (€)a and c 39,078; 32,159 (5862–154,732)
Relation to PwSMS: Spouse/partner 41 (53)
 Parent 12 (15)
 Other relative 13 (17)
 Son/daughter 8 (10)
 Paid caregiver 3 (4)
 Friend 1 (1)
Living with the PwSMS 69 (88)
No of relatives living with the PwSMS 1.5; 1 (0–6)

a Mean; median (range).

b Including three who formed part of dyad.

c For two PwSMS, 2013 household income was available.

EDSS: Expanded Disability Status Scale; PwSMS: person with severe multiple sclerosis.

PwSMS (55% women; mean age 59.2 years, range 41–80) were diagnosed at a mean age of 37 years (range 16–66); median EDSS score was 8.5 (IQR 8.0–9.0); median FIM score was 48 (IQR 40–60; Shapiro–Wilk W test, p = 0.02); 19% had severe cognitive compromise. Median household income in 2014 was € 32,159 (IQR 17.883–51,495), with positively skewed distribution (p < 0.0001).

All eight SF-36 scale scores were lower (p < 0.001) than the Italian norm [31], the most important differences being for Role Limitation Emotional – mean score 48.9 (95% confidence interval, CI 39.8–58.0) vs. 76.2 (95% CI 65.7–67.5) for the Italian norm; and Role Limitation Physical – mean score 51.6 (95% CI 42.6–60.6) vs. 84.5 (95% CI 83.5–85.5) for the Italian norm (Fig. 1).

Fig. 1

Fig. 1

Mean SF-36 scale scores of the 78 carers of PwSMS (black columns) in comparison to the Italian normative population (n = 2031; grey columns) [31]. All differences (two-sample t-test with unequal variances) are significant (p < 0.001). Replies are missing for Vitality (n = 4), General Health and Mental Health (n = 3), Social Functioning (n = 2), and Role Limitation Emotional (n = 1).

 

Because of missing items, the two SF-36 composite scores (PHC and MHC) were only available for 71 carers. Mean PHC was 43.8 (95% CI 41.2–46.4); mean MHC was 40.1 (95% CI 37.8–42.5).

Median HADS Anxiety score was 10.0 (IQR 5.0–11.0); median HADS Depression score was 7.0 (IQR 4.0–9.0). A non-normal distribution was found for HADS Depression score (p = 0.005). Fifty-three (68%) carers had pathologic scores (≥ 8) for HADS Anxiety, 34 (44%) for Depression, and 32 (41%) for both. A pathologic HADS Anxiety score was associated with lower SF-36 MHC (mean 36.0 vs. 50.0; p < 0.0001), lower PHC (mean 41.3 vs. 49.8; p = 0.002), and with higher ZBI score (mean 40.7 vs. 25.2; p < 0.0001). A pathologic HADS Depression score was associated with lower SF-36 MHC (mean 35.0 vs. 44.3; p = 0.0001), lower PHC (mean 40.8 vs. 46.2; p = 0.04), and higher ZBI (mean 41.9 vs. 30.8; p = 0.001).

Most PwSMS outcome measures (EDSS, FIM, Core-POS, POS-S-MS) were not associated with carer HRQOL or HADS scores, the single exception was Core-POS score, which was significantly higher (worse) in carers with pathologic HADS Anxiety (mean Core-POS 14.0 vs. 8.7; p = 0.001), and Depression score (mean Core-POS 14.5 vs. 10.6; p = 0.01).

3.2. Perceived carer burden and its determinants

Summary ZBI (and HADS and SF-36) statistics are shown in Table 2.

Table 2

Summary statistics of scale scores for the 78 carers of PwSMS. Zarit Burden Interview (ZBI) was available for 76 carers.

 

Measure No (%) subj. with missing items Mean (SD); median (range) Shapiro–Wilk
W test - p value
No (%) subj. scoring min/max Cronbach's alpha No (%) items out of rangea
ZBI 2 (2.5%) 35.6 (14.3); 34.5 (8–72) 0.46 0/0 0.89 3 (14%)/0
SF-36 PHC 7 (10%) 43.8 (11.1); 44.5 (18.1–64.1) 0.09 0/0
 SF-36 MHC 7 (10%) 40.1 (10.1); 40.1 (17.4–62.3) 0.76 0/0
HADS Anxiety 0 8.8 (4.2); 10 (0–18) 0.20 1 (1%)/0 0.79 1 (14%)/0
 HADS Depression 0 7.1 (4.4); 7 (0 − 21) 0.004 3 (4%)/1 (1%) 0.82 0/1 (14%)

a Item–total correlation range, 0.30–0.70.

HADS: Hospital Anxiety and Depression Scale; PHC: Physical Health Composite; MHC: Mental Health Composite; SF-36: Short Form 36.

Overall, carers scored 35.6 points (of a possible 88) on ZBI, indicating moderate burden. Total ZBI score correlated moderately and negatively with both SF-36 composite scores, and moderately and positively with HADS Anxiety and Depression scores (Table 3).

Table 3

Correlation matrix (Spearman's rho) of carer inventories.

 

SF-36 PHC SF-36 MHC HADS Anxiety HADS Depression ZBI
SF-36 PHC 0.30
p = 0.01
− 0.41
p = 0.0004
− 0.39
p = 0.0006
− 0.40
p = 0.0006
SF-36 MHC − 0.65
p < 0.001
− 0.57
p < 0.001
− 0.53
p < 0.001
HADS Anxiety 0.59
p < 0.001
0.55
p < 0.001
HADS Depression 0.47
p < 0.001

HADS: Hospital Anxiety and Depression Scale; PHC: Physical Health Composite; MHC: Mental Health Composite; SF-36: Short Form 36; ZBI: Zarit Burden Inventory.

Fig. 2 shows responses to each ZBI item. Highest median [IQR] scores were for item 8 (‘Do you feel your relative is dependent upon you?’; 4.0 [3.0–4.0]); item 7 (‘Are you afraid what the future holds for your relative?’; 3.0 [2.0–4.0]); and item 14 (‘Do you feel that your relative seems to expect you to take care of him/her, as if you were the only one he/she could depend on?’; 3.0 [2.0–4.0]). Lowest scores were for item 4 (‘Do you feel embarrassed over your relative's behavior?’; 0.0 [0.0–1.0]); item 6 (‘Do you feel that your relative currently affects your relationship with other family members or friends in a negative way?’; 0.0 [0.0–2.0]); and item 13 (‘Do you feel uncomfortable about having friends over, because of your relative?’; 0.0 [0.0–0.5]).

Fig. 2

Fig. 2

Percentage distribution of responses to the 22 Zarit Burden Interview items. Figs. at top of each column are item median value.

 

Variables associated with total ZBI score in the regression analyses are shown in Table 4. Higher carer HADS Anxiety and Depression score, and living with the PwSMS, were associated with greater carer burden. Higher SF-36 PHC and MHC were associated with lower burden. Of PwSMS characteristics, age > 35 years at MS diagnosis and higher (worse) Core-POS score were associated with greater carer burden, while female gender, EDSS > 8.5, and household income > € 32,000 were associated with lower burden. All variables significantly associated with ZBI in the univariate analyses were considered for the multivariate model. For carer inventory scores which measured similar constructs and correlated significantly with each other (specifically HADS Anxiety, and SF-36 MHC; Table 3) only one inventory was included in the multivariate model. The multivariate model (Table 4) included four carer variables, five PwSMS variables, and study center. Of these, higher carer HADS Anxiety (β 1.84, 95% CI 1.01–2.67; p < 0.0001), lower household income (β − 8.55, 95% CI − 14.92 – -2.18; p = 0.009), and carer and PwSMS living together (β 10.47, 95% CI 1.85–19.99; p = 0.02) were independent predictors of greater carer burden. The total adjusted variance explained by the model (adjusted R2) was 0.50. All checks for the normality of residuals were satisfactory, except for the quintile-normal plots (tails deviate slightly from normal distribution; Supplementary File).

Table 4

Characteristics associated with Zarit Burden Interview score in linear regression analyses. Statistically significant values are reported in bold.

 

Characteristic Univariate Multivariate
β coefficient (95% CI) P value β coefficient (95% CI) P value
Carers
 Age > 60 years 0.60 (− 5.99–7.20) 0.85
 Female sex 3.84 (− 2.89–10.58) 0.26
 College/university education − 2.58 (− 10.17–5.02) 0.50
 HADS Anxiety score 1.92 (1.24–2.59) < 0.001 1.84 (1.01–2.67) < 0.0001
 HADS Depression score ≥ 8.0 11.12 (4.98–17.26) 0.001 3.10 (− 3.27–9.47) 0.33
 SF-36 PHC score − 0.50 (− 0.81–− 0.20) 0.002 0.13 (− 0.18–0.44) 0.41
 SF-36 MHC score − 0.81 (− 1.11–− 0.52) < 0.001
 Living with the PwSMS 11.76 (1.90–21.62) 0.02 10.47 (1.85–19.99) 0.02
Persons with severe MS
 Age > 58 years 6.06 (− 0.39–12.51) 0.06
 Female sex − 6.86 (− 13.30–− 0.42) 0.04 − 4.85 (− 10.86–1.16) 0.11
 College/university education − 4.26 (− 12.49–3.97) 0.31
 Age at MS diagnosis > 35 years 9.97 (3.79–16.15) 0.002 4.98 (− 0.53–10.50) 0.08
 Secondary progressive MS − 2.08 (− 9.56–5.40) 0.58
 Severe cognitive compromise − 0.36 (− 8.64–7.93) 0.93
 EDSS > 8.5 − 10.23 (− 17.47–− 2.99) 0.006 − 4.85 (− 11.52–1.82) 0.15
 FIM total score > 48 1.02 (− 5.59–7.64) 0.76
 Core-POS score 0.48 (0.02–0.93) 0.04 − 0.13 (− 0.57–0.31) 0.40
 POS-S-MS score > 22.5 0.15 (0.25–0.54) 0.46
 Living with ≥ 2 relatives 1.31 (− 2.39–5.03) 0.48
 Household income > € 32,000 − 6.79 (− 13.20–− 0.37) 0.04 − 8.55 (− 14.92–− 2.18) 0.009
 Centre (Milan, reference): Rome 0.42 (− 7.25–8.09) 0.80
 Catania − 3.00 (− 10.10–4.08) 0.40

Adjusted R2 = 0.50; Breusch-Pagan test for heteroskedasticity, chi2 = 2.83, p = 0.09; variance inflation factor test for multicollinearity range: 1.2–1.9.

Core-POS: Core-Palliative care Outcome Scale; EDSS: Expanded Disability Status Scale; FIM: Functional Independence Scale; HADS: Hospital Anxiety and Depression Scale; MHC: Mental Health Composite; PHC: Physical Health Composite; POS-S-MS: Palliative care Outcome Scale-Symptoms-MS; PwSMS: Person with severe multiple sclerosis; ZBI: Zarit Burden Interview.

We performed a regression model (sensitivity analysis) excluding the three dyads in which the carer was paid. This model included presence of full-time paid carer (not part of dyad; Table 1) as an additional independent variable. The results were closely similar to those of the main model: specifically, carer HADS Anxiety (β 1.98, 95% CI 1.11–2.84; p < 0.0001), lower household income (β − 8.84, 95% CI − 15.31–− 2.38; p = 0.008), and carer and PwSMS living together (β 11.97, 95% CI 3.14–20.80; p = 0.009) still had independent effects on perceived carer burden (Supplementary Table 1).

4. Discussion

Carers play fundamental roles in providing long-term support to PwSMS, preventing patient institutionalization [5], [9], [12], and [36]. Our study has shown that this role has a strong negative impact on carer HRQOL. In fact all SF-36 dimensions were significantly worse than the Italian norms, and the differences were particularly large for Role Limitation Physical, Role Limitation Emotional, and Emotional Wellbeing (Fig. 1). Reduced HRQOL in carers of people with MS was reported in a systematic review of studies performed between 1990 and 2002 [5] and also in more recent studies [7], [8], [10], [11], [14], [16], and [37].

We also found that mood symptoms were common in carers, 41% of whom had pathologic scores on both the Anxiety and Depression scales of HADS. A postal survey of 142 carers (mean age 53 years, 50% women, 65% partners) of people with MS (21% with patient-determined EDSS > 6.5) [14] found significantly lower vitality and psychological wellbeing (as assessed by SF-36 and the Chicago Multiscale Depression Inventory) than in age- gender- and area of residence-matched contemporaneous controls. Reduced carer vitality and wellbeing were found unrelated to MS-associated physical impairment, but were associated with patient mood symptoms. A population-based study of 278 Spanish carers of people with MS (58% relapsing-remitting; EDSS range 0–9.0) [11] also found that carer HRQOL was strikingly reduced.

In contrast to the marked impact on HRQOL and psychological wellbeing, we found that perceived carer burden was moderate overall. The three other publications on carers of people with MS using the 22-item ZBI found rather less perceived burden but also investigated carers of patients across the disability spectrum: the Spanish study had a mean ZBI of 22.0 (range 0–72) [11]; a clinic-based study on 99 French carers had a mean ZBI of 27.3 (range 0–80; MS patients with EDSS 1.0–9.5) [37]; and a large online survey (1333 MS care partners from the North American Research Committee on MS) found a mean ZBI of 24.6 (standard deviation 15.1) [15].

It is noteworthy that in our carer population, uneasiness and embarrassment due to the charge's behavior (items 4, 6 and 13) were rarely a problem, while perceived heavy caring responsibilities (items 8 and 14) and being afraid of the future (item 7) were common. Similar ZBI responses were found in carers of patients with acquired brain injury [38]. These findings suggest that some ZBI items − a scale originally developed for carers of people with dementia – are less pertinent to carers of people with MS. Other explanations for the overall moderate burden could be carer difficulty in recognizing their own needs and tending to confuse them with those of their loved ones [17] and [18] and a sense of fulfillment due to the carer role [39].

As regards factors influencing carer burden in the regression analysis (Table 4), we found no effect for carer gender. By contrast, Buchanan et al. [12] found that men carers had greater odds of reporting higher burden than women carers (ad hoc interview); while Knight et al. [40] found that wife carers experienced a higher overall burden husband carers (telephone interview). Like us, Riviera-Navarro et al. found no association between 22-item ZBI score and gender [11].

We found that no PwSMS characteristic was associated with perceived carer burden in the multivariate model, possibly because our patient population was uniformly and severely disabled (EDSS ≥ 8.0). However, separate regression modeling of the 63 dyads (80% of cohort) whose PwSMS completed the HADS (no severe cognitive compromise) revealed that PwSMS HADS Anxiety was independently associated with higher perceived burden (β 1.13, 95% CI 0.10–2.16; p = 0.03; data not shown).

We found that carer anxiety was the most important variable associated with perceived burden, which persisted after controlling for PwSMS variables (age at MS diagnosis, gender, EDSS and Core-POS score).

Household income was the next most important variable. Financial strain was a risk factor for carer distress (adjusted odds ratio 1.68, 95% CI 1.60–1.76; P < 0.0001) in a large Canadian survey on carers of people with neurological conditions, including MS [16]. Aronson et al. [36] also found an association between carer HRQOL and family income in 345 carers of people with MS (postal survey in Ontario, Canada) [36]. MS partner burden has been associated with caregiving hours and reduced ability to remain in paid employment [41].

Finally, living with the PwSMS was also associated with higher caregiver burden, probably because living together implies more intimate physical and emotional involvement in the multiple aspects of PwSMS daily living [42].

Study limitations are that population size was relatively small and longitudinal information was not available in our (cross-sectional) snapshot of community-based MS carers recruited to a clinical trial. Furthermore we did not investigate length of time in carer role, carer morbidities, or social support, which could plausibly have influenced perceived burden. Nonetheless, to our knowledge no other multicenter study has investigated wellbeing and burden in carers of PwSMS. Importantly, presence of a paid carer as part of the dyad (n = 3) had no influence on factors contributing to carer burden, as shown by our sensitivity analysis.

To conclude, we have found that carers of PwSMS have significantly reduced HRQOL and psychological wellbeing. Perceived burden was moderate overall – consisting mainly of concerns about caring responsibilities, and worry about the future – but high carer anxiety, low economic status, and living with the PwSMS predict higher perceived carer burden. Most informal carers wish to continue caring for their loved ones into the future [17] and [18], so that they can live in their home and community [5], [9], and [12]. To achieve this, integration of health and social care services is vital. It is also important to recognize the role of the carer as full partner in the provision of care, and to respond to carer own needs.

The following are the supplementary data related to this article.

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Supplementary File

Graphs used to check for normality in the residuals.

 

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Supplementary Table 1

Characteristics associated with Zarit Burden Interview score in multivariate linear regression analysis. The three paid caregivers have been excluded from this analysis.

 

Conflicts of interest

PC has been a board member of Biogen, and received travel grants from Sanofi, Biogen, and Merk Serono. AL has been a Bayer, Biogen, Merck Serono and Genzyme advisory board member. She received travel grants and honoraria from Bayer, Biogen, Merck Serono, Novartis, Sanofi and Teva and her Institution received research grants from Bayer, Biogen, Merck Serono, Novartis, Sanofi and Teva. MGG has received research funding from Merck Serono and consulting and speaking fees from Biogen. FP has received speaking honoraria from Bayer, Biogen, Merck Serono, Novartis, and Sanofi. He has been a Bayer, Biogen, Merck Serono, and Novartis advisory board member. AS has been a board member of Biogen and Novartis, and has received speaker honoraria from Excemed, Genzyme, and Merck Serono. All other authors declare that they have no competing interests.

Funding

This work was supported by the Fondazione Italiana Sclerosi Multipla [grant number 2014/S/1]. The funding source had no role in study design, data collection, data analysis, data interpretation, report writing, or decision to submit the article for publication.

Acknowledgements

The authors thank Don Ward for help with the English.

Appendix A. PeNSAMI project investigators

Steering Committee: R Amadeo, A Giordano, M Ponzio, MG Grasso, A Lugaresi, F Patti, G Martino, L Palmisano, S Veronese, P Zaratin, MA Battaglia, A Solari.

Data Management and Analysis Committe: A Giordano, D Radice (statistician): Division of Epidemiology and Biostatistics, European Institute of Oncology, Milan; M Ponzio (statistician), G Ferrari, A Solari.

Independent Data and Safety Monitoring Committee: DJ Oliver: Wisdom Hospice, University of Kent, Rochester, Kent, UK; E Pucci: Neurology Unit, Ospedale Provinciale di Macerata, Macerata; L Tesio: Department of Biomedical Sciences for Health, University of Milan, Milan.; The Istituto Auxologico Italiano, IRCCS, Milan.

Qualitative Analysis Panel: E Bianchi, E Pietrolongo, A Solari, A Giordano, I Rossi, S Cilia, M Giuntoli, C Borreani.

Literature Review Panel: MG Grasso, L Palmisano, A Fittipaldo, A Giordano.

Intervention Panel: C Cugno, R Causarano, P Morino: ‘Ex Convento delle Oblate’ Hospice, Local Health Unit of Florence, Florence, S Veronese.

Centers and Investigators: AISM Liguria Region Rehabilitation Service, Genoa: ML Lopes de Carvalho, M Giuntoli, R Motta, MA Battaglia; Antea Charitable Association, Rome: G Casale, MC Stefanelli; FARO Charitable Foundation, Turin: S Veronese, C Cugno; Foundation IRCCS Istituto Nazionale per la Cura dei Tumori, Milan: C Borreani, E Bianchi; Foundation IRCCS Neurological Institute C Besta, Milan: A Solari, P Confalonieri, AM Giovannetti, V Torri Clerici, E Rossetti, A Totis, A Campanella, A Giordano, F Martini, A Fittipaldo, G Ferrari, R Mantegazza; IRCCS S Lucia Foundation, Rome: MG Grasso, I Rossi, E Troisi, A Pompa, L Tucci, F Ippoliti, G Morone, A Fusco; Istituto Superiore di Sanità, Rome: L Palmisano; Associazione Italiana Sclerosi Multipla (AISM), Genoa: R Amadeo, G Martino; Fondazione Italiana Sclerosi Multipla (FISM), Genoa: P Zaratin, M Ponzio, MA Battaglia; Niguarda Ca′ Granda Hospital, Milan: R Causarano, D Da Col, B Lissoni; G d'Annunzio University, Chieti-Pescara, Chieti: A Lugaresi, E Pietrolongo, M Onofrj; University Hospital Policlinico Vittorio Emanuele, Catania: F Patti, S Cilia, C Leone, V Cascio, V Cimino, G Occhipinti, A Pappalardo, C Cavallaro, F Zagari.

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Footnotes

a Unit of Neuroepidemiology, Foundation IRCCS Neurological Institute C. Besta, via Celoria 11, 20133 Milan, Italy

b MS Centre, Neurology Clinic, University Hospital Policlinico Vittorio Emanuele, via S. Sofia, 78, 95123 Catania, Italy

c Scientific Direction, Foundation IRCCS Neurological Institute C. Besta, via Celoria 11, 20133 Milan, Italy

d Multiple Sclerosis Unit, IRCCS S. Lucia Foundation, Via Ardeatina 306, 00142 Rome, Italy

e Department of Therapeutic Research and Medicine Evaluation, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy

f Unit of Neuroimmunology, and Neuromuscular Diseases, Foundation IRCCS Neurological Institute C. Besta, via Celoria 11, 20133 Milan, Italy

g Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, Via dei Vestini 31, 66013 Chieti, Italy

h Department of Research, Fondazione Italiana Sclerosi Multipla (FISM), Via Operai 40, 16149 Genoa, Italy

i FARO Charitable Foundation, Via Oddino Morgari 12, 10125 Turin, Italy

Corresponding author.

1 Members listed at end of paper.


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