The relationship between burden and well-being among caregivers of Italian people diagnosed with severe neuromotor and cognitive disorders

Research in Developmental Disabilities 39 (2015) 43–54

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Research in Developmental Disabilities

Review article

The relationship between burden and well-being among caregivers of Italian people diagnosed with severe neuromotor and cognitive disorders Andrea Fianco a,*, Raffaela D.G. Sartori a,1, Luca Negri a,1, Saverio Lorini b,2, Giovanni Valle b,2, Antonella Delle Fave a,1 a b

Department of Pathophysiology and Transplantation, University of Milano, Via F. Sforza, 35, 20146 Milano, Italy IRCCS Fondazione Don Carlo Gnocchi, Centro IRCSS ‘‘S. Maria Nascente’’, Via A. Capecelatro, 66, 20148 Milano, Italy

A R T I C L E I N F O

A B S T R A C T

Article history: Received 16 September 2014 Received in revised form 22 December 2014 Accepted 19 January 2015 Available online 6 February 2015

In studies on caregiving, high levels of perceived burden are commonly considered as synonymous with poor well-being. This study aimed at better disentangling the relationship between burden and well-being dimensions through their joint investigation. To this purpose, perceived well-being and social resources were evaluated among caregivers reporting different levels of burden. Participants were 91 caregivers (mean age = 50.4; SD = 9.6), parents of people diagnosed with severe neuromotor and cognitive disorders. Participants completed a semi-structured interview and a set of scaled questionnaires: Caregiver Burden Inventory (CBI), Satisfaction with Life Scale, Positive and Negative Affect Schedule, Depression Anxiety Stress Scale, Eudaimonic and Hedonic Happiness Investigation, Resilience Scale for Adults, and Multidimensional Scale of Perceived Social Support. Participants were divided into two groups according to their perceived burden level, assessed through CBI. In both groups, the subjective components of burden accounted for the major fraction of the total burden level. Participants perceiving high burden reported higher levels of depression related emotions, lower life satisfaction and lower resilience than participants perceiving low burden. No group difference emerged in perceived meaningfulness and social support. A regression analysis showed that the best predictor of perceived burden was life satisfaction, followed to a lesser extent by resilience, while depression related emotions did not provide significant contribution. Findings suggest that the joint assessment of burden and well-being dimensions, that are co-existing in caregivers’ experience, allow for the identification of personal and relational resources that can be usefully included in interventions addressed to caregivers. ß 2015 Elsevier Ltd. All rights reserved.

Keywords: Caregivers Disability Burden Well-being Resources Satisfaction Resilience

* Corresponding author. Tel.: +39 02 5031 9703; fax: +39 02 5031 9705. E-mail addresses: andrea.fi[email protected] (A. Fianco), [email protected] (Raffaela D.G. Sartori), [email protected] (L. Negri), [email protected] (G. Valle), [email protected] (A.D. Fave). 1 Tel.: +39 02 5031 9703; fax: +39 02 5031 9705. 2 Tel.: +39 02 02 403081; fax: +39 02 40092297. http://dx.doi.org/10.1016/j.ridd.2015.01.006 0891-4222/ß 2015 Elsevier Ltd. All rights reserved.

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Contents 1.

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4. 5. 6.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Psychological and social stressors in caregiving . 1.1. Psychological and social resources in caregiving 1.2. Aims and hypotheses . . . . . . . . . . . . . . . . . . . . . . 1.3. Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Research instruments. . . . . . . . . . . . . . . . . . . . . . 2.2. Data organization and analysis . . . . . . . . . . . . . . 2.3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Caregiver burden . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Well-being and perceived social support . . . . . . 3.3. Psychosocial predictors of burden . . . . . . . . . . . . 3.4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction People diagnosed with severe neuromotor and cognitive disorders experience substantial limitations in autonomy and restriction of daily activities, thus requiring continuous assistance. Across countries and disease typologies, the vast majority of caregivers (86%) are represented by family members, also defined as ‘‘informal caregivers’’ (National Alliance for Caregiving, 2009) since most often they do not have professional competences and skills in assistance procedures. Family caregivers are prominently women (85%), who fulfill their caring role from 7 to 11 h a day on average, up to 10–15 h when clinical conditions worsen (Neugaard, Andresen, McKune, & Jamoom, 2008). Medical technology advancements and prolonged life expectancy contributed to a substantial increase in the number of long-term caregivers worldwide. In Italy, there are 2,600,000 people with disabilities, supported by 100,000 to 200,000 family caregivers (Istituto Nazionale di Statistica, Istat, 2009). 1.1. Psychological and social stressors in caregiving Informal caregivers have to cope with physical, psychological and social stressors that negatively affect their health conditions and quality of life. A variety of studies showed that, compared with the general population, caregivers report more physical and psychological symptoms, use medications and healthcare services more frequently (Schulz and Martire, 2004), suffer from depression, exhibit maladaptive coping strategies (Molyneux, McCarthy, McEniff, Cryan, & Conroy, 2008) and develop burnout symptoms (Neugaard et al., 2008). The primary stressors experienced by informal caregivers are related to both disease severity and the amount of time devoted to assistance. In particular, variability in care-recipients’ symptoms, behaviors, and disease progression negatively affect the level and quality of assistance, by increasing caregivers’ feelings of guilt and powerlessness (Trail, Nelson, & Van, 2003). The quality of family relationships, as well as contextual variables such as policies, social support and cultural views of disease and disability can contribute to mitigate or aggravate the impact of these primary stressors (Carretero, Garces, Rodenas, & Sanjose, 2009; Lin et al., 2009). The increased risk of burnout identified among informal caregivers is closely related to their perceived level of burden, defined as a multidimensional response to negative appraisals and perceived stress (Neugaard et al., 2008). In the last 30 years researchers have paid special attention to the investigation and assessment of burden. The Burden Interview (Zarit, Reever, & Bach-Peterson, 1980) was specifically designed to assess the distress experienced by caregivers of elderly relatives. The Caregiver Burden Measure (Montgomery, Gonyea, & Hooyman, 1985; Montgomery, Kwak, Kosloski, & O’Connell Valuch, 2011) provides information on caregivers’ perceived privacy, personal freedom, worry, recreational activities, relationships with other family members, hopelessness and anxiety. The Caregiving Burden Scale (Gerritsen & van der Ende, 1994) was built to evaluate the quality of the relationship between caregiver and care-recipient, and its impact on perceived burden. The Modified Caregiver Strain Index (Robinson, 1983; Thornton & Travis, 2003) measures caregivers’ physical involvement in caring and time devoted to other family members. The Caregiver Burden Inventory (CBI, Novak & Guest, 1989) provides information on both the Objective Burden (OB) – the everyday time and commitment caregivers devote to caring activities – and the Subjective Burden (SB) – perceived lack of opportunities in daily life, fatigue, physical problems, socialization and participation issues, and the emotions experienced toward the care-recipient (Caserta, Lund, & Scott, 1996).

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1.2. Psychological and social resources in caregiving While a large amount of studies suggest that moderate to severe disabilities in care-recipients are related to high caregiver burden (Molyneux et al., 2008; Sussman & Regehr, 2009), some studies detected weak or no association between care-recipients’ functioning and caregivers’ burden levels (Campbell et al., 2008). Moreover, recent advancements in wellbeing research highlighted the pivotal role of individual and contextual resources in promoting personal growth and social inclusion of both care-recipients and caregivers (Bauer, Koepke, Sterzinger, & Spiessl, 2012; Cummins, 2005; Lin et al., 2009). Based on these findings, the Adult Carers Quality of Life Questionnaire (AC-QoL; Joseph, Becker, Elwick, & Silburn, 2012) was recently developed to quantify not only the negative dimensions of caregiving, but also the positive ones such as environmental mastery, personal growth, sense of value, satisfaction, and social support. Within a biopsychosocial approach to healthcare (Engel, 1977), the need for considering positive aspects and resources available in sub-optimal health conditions guided the development of the International Classification of Functioning, Disability and Health (ICF, WHO, 2001). ICF is based on three major assumptions: (1) human functioning is a complex system in which biological, psychological and social dimensions dynamically interact; (2) functioning and disability result from the interaction between individual health conditions and personal and environmental factors – facilitators or barriers – which may hinder or promote participation and social inclusion; (3) the evaluation of health conditions should not only aim at identifying impairments, deficits or social restrictions, but also positive dimensions such as individuals’ residual abilities, psychological assets and potentials, as well as social resources. From this perspective, both environmental and personal features can mediate the impact of disease on individuals’ quality of life (Dixon, Johnston, Rowley, & Pollard, 2008; Seekins, Traci, Cummings, Oreskovich, & Reveslot, 2008). As specifically concerns caregivers, psychosocial resources can counterbalance the negative outcomes of the burden perceived in daily caring activities. Studies on social resources highlighted that family cohesion, social support, education, community networks, economic affordance and job opportunities remarkably affect the quality of life and social inclusion of people with disabilities and their caregivers (Albrecht & Goldsmith, 2003; Bodde & Seo, 2009; Motl, McAuley, Snook, & Gliottoni, 2009). At the personal level, studies showed the mediating role of coping style (Bauer et al., 2012), internal locus of control (Lloyd & Hastings, 2009), and psychological acceptance (MacDonald, Hastings, & Fitzsimons, 2010). Moreover, in the last two decades increasing attention was paid to the identification and assessment of perceived wellbeing indicators. Within this domain, a line of research was centered on the construct of subjective well-being (SWB), that comprises a cognitive component (satisfaction with life) and an affective one (predominance of positive emotions on negative feelings in daily life; Diener, 2000). Other researchers focused instead on the so-called eudaimonic dimensions of well-being, that include self-determination, personal growth, goal setting and pursuit, and meaning-making (Delle Fave, Brdar, Freire, Vella-Brodrick, & Wissing, 2011; Huta & Waterman, 2013; Ryan & Deci, 2001; Ryff & Singer, 2008). Studies highlighted that well-adjusted caregivers report high positive and low negative affect (Robertson, Zarit, Duncan, Rovine, & Femia, 2007; Song et al., 2014). As concerns meaning in life, assessed as sense of coherence (SOC; Antonovsky, 1987), findings showed that high levels of caring stress were associated with poor health, low SOC, and higher risk of burnout (Ekwall, Sivberg, & Hallberg, 2007; Oelofsen & Richardson, 2006). Both social and psychological resources contribute to promoting resilience (Heiman, 2002; Masten & Reed, 2002; Rutter, 2012; Zauszniewski, Bekhet, & Suresky 2009), a complex construct comprising the individual, family and social factors that allow individuals to face life adversities turning them into opportunities for constructive growth. A variety of risk and protective factors can facilitate or hinder the resilience process. In particular, balanced and constructive family relationships play an important role in supporting the informal caregiver’s adaptive management of care-recipient disability (Rolland & Walsh, 2006). These findings suggest that perceived burden may not represent the only criterion to evaluate informal caregivers’ quality of life. Attention should be also devoted to personal, family and social resources that can contribute to caregivers’ well-being and psychosocial adjustment. 1.3. Aims and hypotheses The present study was aimed at investigating the association between perceived levels of burden and well-being indicators among informal caregivers, parents of people diagnosed with severe neuromotor and cognitive disorders. We were also interested in investigating whether and to which extent well-being indicators and depression related emotions predicted subjective burden (SB) and objective burden (OB). Considering the lack of empirical studies addressing this issue, we hypothesized that: - (H1) Perceived SB would account for a higher proportion of the global burden score compared with OB among both caregivers perceiving high burden and caregivers perceiving low burden. Thus we tested the null hypothesis of detecting no difference in SB and OB proportions between caregivers perceiving different levels of total burden. - (H2) High perceived burden would be associated with lower levels of subjective and eudaimonic well-being and social support, while low burden would be associated with higher subjective and eudaimonic well-being and social support. Thus we tested the null hypothesis of detecting no differences between caregivers with high or low burden in levels of subjective and eudaimonic well-being and social support.

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- (H3) Subjective and eudaimonic well-being dimensions as well as depression indicators would be better predictors of SB than of OB. Thus we tested the null hypothesis of detecting no relationship of the well-being and depression indicators with SB and OB. 2. Method 2.1. Procedure Participants were recruited at IRCCS Fondazione Don Carlo Gnocchi, an institution supporting people diagnosed with disabling diseases and their families through a variety of healthcare and psychosocial services, including medical rehabilitation, occupational therapy, formal education programs, vocational trainings, and interventions based on assistive technologies. After approval by the local Ethical Committee, informal caregivers were contacted through a letter describing the main aims of the project. They could express willingness to participate in the study by informing a reference person at the Foundation. One member of the university research team was in charge of the data collection. During the first meeting with the researcher, participants filled out an informed consent form, and were involved in a semi-structured interview, investigating the personal, family and social challenges and resources perceived in their role as caregivers. At the end of the interview, participants were provided with a set of questionnaires investigating perceived burden and psychological and social indicators of well-being and depression. They were invited to fill out the questionnaires within two weeks, and to return them to the researcher during a debriefing session, in which they had the opportunity to express personal comments and evaluations. Participants’ anonymity was guaranteed in all research phases. 2.2. Research instruments The semi-structured interview (Delle Fave, Fianco, & Sartori, 2015) was designed taking as a reference point the ICF model and the construct of family resilience. It comprised open-ended questions investigating the daily barriers and facilitators perceived by caregivers at the personal, family and social levels. To the purpose of the present study, only the answers to the following question will be taken into account: ‘‘What are, in your opinion, the most important personal skills needed to cope with this situation?’’ In addition, participants filled out the following scales: - Caregiver Burden Inventory (CBI, Novak & Guest, 1989; Italian version (Marvardi et al., 2005). CBI consists of 24 items on 0–4 Likert-type scales; items are grouped into five factors measuring different components of burden such as time dependence, developmental burden, physical burden, social burden and emotional burden. - Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985; Italian version Goldwurm, Baruffi, & Colombo, 2004) assessing the cognitive component of subjective well-being through 5 items on 7 point scales; - Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988; Italian version Terraciano, McCrae, & Costa, 2003), evaluating the frequency of 10 positive and 10 negative emotions in daily life through 20 items on 5 point scales; - Depression Anxiety Stress Scale–depression subscale (DASS; Lovibond & Lovibond, 1995; Italian version Conti, 1999) evaluating the negative emotional states related to depression through 7 items on 0–3 point scales; - Eudaimonic and Hedonic Happiness Investigation (EHHI; Delle Fave, Brdar, Freire, Vella-Brodrick, & Wissing, 2011), assessing through 1–7 point scales the level of happiness and meaningfulness perceived in life in general and 10 different domains: work, family, standard of living, relationships, health, personal growth, leisure, spirituality/religion, community, and society; - Resilience Scale for Adults (RSA; Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003, Italian version Peveri, 2010), which investigates the positive adaptation to stress conditions through 33 items on 1–5 Likert-type scales organized in 6 subscales: Family Cohesion and Support (CF), Social Resources (RS), Self-efficacy and Self-esteem (PS), Future Plan (PF), Social Competences (CS) and Social Support (SS). The total score is obtained by summing the item values of each factor: a score between 33 and 77 indicates a high level of resilience, a score between 78 and 121 a moderate level and a score above 122 a low level of resilience; - Multidimensional Scale of Perceived Social Support (MSPSS; Zimet, Dahlem, Zimet, & Farley, 1988; Italian version Prezza & Principato, 2002), investigating perceived social support by family, friends and significant others through 12 items on 1–6 scales. 2.3. Data organization and analysis Before data analysis, participants were divided into two groups according to their high or moderate/low levels of perceived burden. In order to verify whether the proportion of OB and SB within the total burden score differed according to perceived burden levels (H1), mean and median values of overall CB and its five components (one for OB and four for SB) were first calculated in the two groups of participants. Values were compared between groups through Wilcoxon–Mann–Whitney test. The OB/total CB ratio and the SB/total CB ratio were then calculated for each participants, and mean group ratios were compared between groups.

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In order to verify (H2), well-being and perceived social support were evaluated in each group through qualitative and quantitative instruments, and the findings were then compared between groups. The answers to the open-ended question were coded by two independent raters using a coding system based on the ICF perspective (Delle Fave, Fianco, & Sartori, 2015) and grouped into two broad categories: (1) psychological resources (related to the psychological constructs of coping, resilience, hardiness, self-efficacy and emotions); (2) relational resources (referring to educational and assistance role, social participation and money availability). Meetings involving a third rater were organized whenever doubts emerged. The percentage of participants who provided at least one answer in each category was computed for each group, and Fisher’s Exact Test was run on these percentages to check for group differences. The preliminary organization of quantitative data differed according to each scale’s structure. Global scores were calculated for each participant for SWLS and DASS by averaging single item values. For PANAS, item values were separately averaged for positive affect and negative affect subscales; Hedonic Balance was then calculated by subtracting the negative affect from the positive affect score (Schimmack, 2007). As concerns RSA, the six factor scores (CF, RS, PS, PF, CS, SS) and the total score were obtained for each participants by summing related item values. MSPSS items were also summed to provide a total score and three sub-scores referring to ‘‘Significant Others’’, ‘‘Family’’ and ‘‘Friends’’. No transformation was required for the EHHI ratings of meaningfulness and happiness. Participants’ and group mean and median values were subsequently calculated for the above described scales and subscales, and compared between groups through Wilcoxon–Mann–Whitney test. Finally, in order to investigate whether and to which extent well-being and depression indicators predicted burden levels (H3), a multivariate linear regression analysis was performed with OB and SB as criterion variables, and SWLS, RSA and DASS scores as predictors. Due to the limited sample size, only three variables were selected as predictors, on the basis of their relevance in the well-being literature: life satisfaction to represent subjective well-being, resilience total score as indicator of eudaimonic well-being, and depression related emotions as indicator of depression. Using the same set of independent variables, two separate hierarchical multiple regression analyses were subsequently performed for each criterion variable as follow-up tests. As a final step, a multivariate test was further employed to check for differences in the effect of each predictor on dependent variables. 3. Results 3.1. Participants Participants were 70 women and 21 men, aged 36–82 (M = 50.4, SD = 9.6), parents of persons diagnosed with cognitive and neuromotor disorders attending a daycare center in northern Italy. Almost half of the participants (47.3%) had a high school diploma, 31.9% had completed elementary or secondary school, and 20.9% had a university degree. Workers (prominently office employees) accounted for 42.9% of the sample, while 57.1% of the participants received a retirement pension or carer allowance. The majority (70%) was married or cohabiting, while 30% were widowed or divorced. Care-recipients were 54 females and 37 males aged 5–53 (M = 19, SD = 11.2). Diagnoses primarily consisted in neurological diseases affecting motor functions (50.5%), prominently spastic tetraplegia (35%) and cerebral palsy (9.9%). Genetic disorders followed, including malformations and chromosomal abnormalities (16.5%) and Down syndrome (6.6%). Specific developmental disorders of motor function accounted for 12.1% of the diagnoses, autism for 6.6% and other mental and behavioral disorders for 7.7%. Most caregivers (74.7%) had received the diagnosis at child’s birth, 13.2% within child’s first year of life, and 12.1% within child’s age of 5–6. As a preliminary step, participants’ risk for burnout was evaluated through the Caregiver Burden Inventory (CBI, Novak & Guest, 1989) in its Italian version (Marvardi et al., 2005). This instrument was selected among the various questionnaires designed to this purpose because it provides information on all the major bio-psychosocial, components of perceived burden, at the physical, emotional/psychological and social levels. CBI consists of 24 items on 0–4 Likert-type scales; overall burden is calculated as a cumulative score ranging from 0 to 96. Total scores between 0 and 24 indicate low risk of burnout, scores between 25 and 36 moderate risk, and scores above 36 high risk (Novak & Guest, 1989). Items are grouped into five factors measuring different components of burden. The first factor refers to OB (items 1–5) and the other four refer to SB dimensions (items 6–24). In particular, items 1–5 measure ‘‘time dependence’’, the daily time caregivers devote to caring activities; items 6–10 measure the ‘‘developmental burden’’ associated to the restriction of opportunities in daily life; items 11–14 measure ‘‘physical burden’’, in terms of energy investment, fatigue perception and physical health problems. The ‘‘social burden’’ (items 15–19) includes perceived social inclusion and participation. Finally, items 20–24 measure the ‘‘emotional burden’’ associated with assistance to the care-recipient. Since the study was aimed at investigating informal caregivers’ psychosocial resources in relation to perceived burden, participants were divided into two groups according to their level of burden. Group 1 (G1) included participants with a CBI score above 36 and Group 2 (G2) caregivers with a CBI score between 0 and 35. G1 included 36 women and 4 men aged 36–73 (M = 49.8, SD = 8.13), parents of people aged 5–48 (M = 17.3, SD = 9.78). Around half of the participants in this group (55%) received a retirement pension or carer allowance, while the remaining 45% worked. As for education level, 55% of the participants had a high school degree, 25% had an elementary or middle school degree diploma, and 20% a university degree.

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G2 comprised 34 women and 17 men aged 34–82 (M = 50.9, SD = 10.63). Their children were aged 4–63 (M = 20.2, SD = 12.10). Among them, 58.8% had a retirement pension or carer allowance, while 41.2% worked. The most frequent education level was high school degree (41.2% of the participants), followed by elementary or secondary school diploma (37.3%), and university degree (21.6%). Comparisons through Fisher’s Exact Test (for categorical data) and t-test (for age) did not highlight significant group differences as concerns caregivers’ age and occupational status, as well as level of education. Only gender differed (p < .05), with a lower number of men included in G1. 3.2. Caregiver burden Mean scores were calculated for the total burden and for the five subscales, and then compared between the two groups of caregivers. Total burden scored 49.6 (SD = 10.9) in G1 and 25.7 (SD = 8.43) in G2. Time dependence (corresponding to objective burden) accounted for the highest fraction of the overall score in both groups (M = 18, SD = 2.11 and M = 13.3, SD = 5.33 respectively). The four subjective burden components followed, with the same rank order in G1 and G2: developmental (M = 11.3, SD = 4.69 and M = 4.2, SD = 2.92), physical (M = 11, SD = 3.95 and M = 4.2, SD = 2.81), social (M = 6.1, SD = 3.96 and M = 2.6, SD = 2.02) and emotional burden (M = 3.5, SD = 3.75 and M = 1.4, SD = 1.78). The total burden and all subscale scores were significantly higher among caregivers at risk of burnout (G1): Time dependence (Z = 5.33 p < .001), developmental (Z = 6.56 p < .001), physical (Z = 6.92 p < .001), social (Z = 4.51 p < .001), emotional burden (Z = 3.51 p < .001) and total burden (Z = 7.94 p < .001). In order to evaluate the proportion of the subjective burden component within the total burden score between groups, the developmental, physical, social and emotional burden scores were first summed for each participant. The OB/total score ratio and the SB/total score ratio were calculated and compared between groups (Table 1). Significant differences emerged (Z = 4.6, p < .001): G1 caregivers reported higher SB than G2 caregivers, while OB was significantly higher among G2 (Z = 4.6, p < .001). 3.3. Well-being and perceived social support Qualitative findings. Table 2 summarizes the percentage of answers in the categories referring to the personal skills required to cope with caregiving, as well as the percentage of participants providing at least one answer in these categories. Hardiness ranked first among G1 participants, followed by problem-focused coping, patience and educational role. Among G2 caregivers, adaptive coping strategies were the most frequent answer category, followed by patience, hardiness and educational role. In order to compare the frequency of each answer category between groups, the number of participants who provided at least one answer in each category was computed. Fisher’s Exact Test highlighted one significant group difference for hardiness, predominantly reported by G1 caregivers (p < .05). Quantitative findings. Table 3 reports the mean and median values of the total score of satisfaction with life, hedonic balance, and depression related emotions in the two groups of caregivers. Significant differences emerged for all three dimensions (Z = 4.5, p < .001, Z = 3.13, p < .01 and Z = 2.38, p < .05 respectively). Participants in G1 reported lower levels of life satisfaction and hedonic balance, as well as higher levels of depression related emotions than participants in G2. Table 4 illustrates the levels of happiness and meaningfulness reported by the two groups in association with ten life domains and life in general. Significant differences were again detected. G1 participants reported lower levels of happiness in family (Z = 2.29, p < .05), health (Z = 2.86, p < .01), community (Z = 2.52, p < .05), society (Z = 2.6, p < .01) and life as a whole (Z = 2.63, p < .01). As for meaningfulness, instead, no significant group difference emerged. The mean and median values of the components of resilience and perceived social support are reported in Table 5. Participants in G1 reported moderate levels of both the total resilience score, and all its components, while G2 participants reported high resilience levels, overall and across subscales. Social support scores were globally high in both groups. Few significant differences were detected. G1 participants reported lower values of total resilience (Z = 2.05, p < .05) and of the subscale ‘‘planning for the future’’ (Z = 4.39, p < .001). As for perceived social support, no group differences emerged in the total score, but family showed significantly lower values among G1 participants (Z = 2.21 p < .05).

Table 1 Mean and mean ratio of SB and OB in the two groups. Caregivers with CBI > 36 (G1, N = 40) Mean (SD) Subjective burden (SB) Objective burden (OB)

31.4 (10.9) 18 (2.1)

Caregivers with CBI < 36 (G2, N = 51) Mean ratioa (SD) ***

0.62 (0.07) 0.38***(0.07)

Note: N = number of participants. a Mean of the ratio between subjective or objective burden score and total burden score. *** P < .001.

Mean (SD)

Mean ratio1 (SD)

12.4 (5.8) 13.3 (5.3)

0.49 (0.19) 0.51 (0.19)

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Table 2 Personal resources reported by the two groups of caregivers: percentage distribution of answers and participants. Caregivers with CBI < 36 (G2, N = 51) Answer % (participants %)

Caregivers with CBI > 36 (G1, N = 40) Answer % (participants %)

Resources

Psychological Hardiness Coping Patience Resilience Health Optimism Emotions Hope Sense of coherence Spirituality

24.7 18.3 12.9 10.7 4.3 3.2 1.1 – 1.1 1.1

(47.5) (30) (25) (20) (10) (7.5) (2.5)

Relational Educational role Assistance role Participation Money None No. of answers

11.8 4.3 3.2 1.1 2.2 93

(25) (7.5) (5) (2.5) (5)

15.2 24.1 21.4 8.9 2.7 1.8 3.6 1.8 – 0.9

(2.5) (2.5)

(21.6) (37.2) (41.2) (15.7) (5.9) (3.9) (7.8) (3.9) (2)

11.6 (23.5) – 6.2 (11.8) 1.8 (3.9) – 112

Note: N = number of participants.

Table 3 Means and median scores of life satisfaction, hedonic balance and depression related emotions in the two groups. Caregivers with CBI > 36 (G1, N = 40)

SWLS Hedonic balance DASS

Caregivers with CBI < 36 (G2, N = 51)

Mean (SD)

Median

Mean (SD)

Median

3.1 (1.37) 6.7 (9.78) 6.9 (4.54)

2.7 6.5 6

4.5 (1.34) 13.9 (9.46) 4.6 (3.38)

4.6 13 4

Note: N = number of participants.

Table 4 Mean and median values of happiness and meaningfulness reported by the two groups across life domains.

Work Family Standard of living Social relations Health Personal growth Free time Spirituality Community Society General

Caregivers CBI > 36 (G1, N = 40) Happiness

Caregivers CBI < 36 (G2, N = 51) Happiness

Caregivers CBI > 36 (G1, N = 40) Meaningfulness

Caregivers CBI < 36 (G2, N = 51) Meaningfulness

Mean (SD-Median)

Mean (SD-Median)

Mean (SD-Median)

Mean (SD-Median)

4.1 5.2 4.4 4.7 4.5 4.9 3.1 3.9 3.7 3.1 4.2

4.6 (1.33–5) 5.8 (1.33–6) 4.8 (1.38–5) 5.1 (1.11–5) 5.4 (1.34–6) 5.3 (1.31–6) 3.9 (1.52–4) 4.1 (1.94–4) 4.7 (1.38–5) 4 (1.4–4) 5.1(1.41–5)

5.6 6.6 5.4 5.7 6.6 5.8 5.1 4.2 4.7 4.7 6.2

5.6 6.5 5.1 5.6 6.5 5.9 4.8 4.8 4.8 4.4 6.1

(1.51–5) (1.41–5) (1.44–4) (1.63–5) (1.55–5) (1.55–5) (1.94–2) (2.2–4) (1.65–4) (1.78–3) (1.63–4)

(1.41–6) (0.72–7) (1.26–6) (1.36–6) (0.87–7) (1.55–6.5) (1.71–5) (2.25–4.5) (1.96–5) (2–5) (0.97–6)

(1.54–6) (1.32–7) (1.31–5) (1.22–6) (1.26–7) (1.22–6) (1.49–5) (1.81–5) (1.52–5) (1.79–4) (1.22–6)

Note: N = number of participants.

3.4. Psychosocial predictors of burden As a preliminary step, data were checked for any violation of multivariate regression assumptions. No univariate outliers were found; however, SB showed a moderate positive skewness and OB a slight positive one. Both variables were transformed accordingly. The Q-Q plot of ordered d2 against quantiles of x2 indicated no violation of multivariate normality; Mardia’s skewness and kurtosis test almost confirmed this result (pS = .03; pK = ns). The D–D plot of Mahalanobis distance of residuals and predicted values showed no violation of dispersion homogeneity; this conclusion was further supported by univariate studentized plots. No multivariate outliers were found through inspection of Q–Q plot of robust Mahalanobis distances against the corresponding quantiles. Similarly, no influential observations were detected employing Hat Matix

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Table 5 Mean and median values of resilience and social support components in the two groups. Caregivers with CBI > 36 (G1, N = 40)

Caregivers with CBI < 36 (G2, N = 51)

Mean (SD)

Median

Mean (SD)

Median

Resilience components Family cohesion (CF) Social resources (RS) Self-efficacy and self-esteem (PS) Future plan (PF) Social Competences (CS) Social support (SS) Total resilience

15.5 13.2 16.5 15.5 13.2 9.2 83.6

15 12.5 17 16 13 9 84

14.4 11.2 15.5 12.2 12.3 9.2 77.1

(3) (3.83) (2.6) (3.32) (3.9) (2.56) (14.45)

14 10 15 12 12 9 76

Social support components Family Friends Significant others Total perceived support

20 (6.64) 18.4 (8.11) 23.8 (5.91) 58.8 (20.09)

21 20 23 61.5

23.2 (4.38) 20 (5.23) 23.1 (4.1) 63.3 (17.37)

24 21 24 68

(2.8) (5.09) (2.78) (2.95) (4.81) (2.84) (14.9)

Note: N = number of participants. Table 6 Correlations among variables included in the multivariate regression. N = 91 (1) (2) (3) (4) (5)

Subjective burden (SB) Objective burden (OB) RSA SWLS DASS

(1)

(2)

(3)

(4)

(5)

– .41** .35** .56** .31*

– .07 .19 .04

– .31* .51**

– .32*

–

Note: N = number of participants; SWLS = satisfaction With Life Scale; RSA = Resilience Scale for Adults; DASS = Depression Anxiety Stress Scale. * p < .01 ** p < .001.

Approach, Cook’s distance, Welsch–Kuh type statistic and Covariance Ratio (Hossain & Naik, 1989). Table 6 displays the correlations between the variables used in multivariate regression. It is worth mentioning again that in the resilience scale lower scores indicate high levels of resilience. Although DASS and RSA were moderately correlated, values of VIF indexes ranged from 1.16 to 1.4 indicating a very low level of multicollinearity. Adopting Wilks’ criterion, the overall multivariate regression model was significant L = .61; F(6, 170) = 8.05; p < .001. Only satisfaction with life L = .76; F(2, 85) = 13.41; p < .001 and Resilience L = .92; F(2, 85) = 3.8; p < .026 significantly contributed to the model; no significant effect was found for depression related emotions L = .99; F(2, 85) = 0.25; p = ns. Table 7 displays results of the follow-up univariate hierarchical regression analyses performed on each dependent variable separately. Since satisfaction with life showed the highest contribution to the multivariate model, it was entered in step 1; for the same reason, resilience and depression related emotions followed in steps 2 and 3 respectively. OB’s model did not result in any significant F or DR2 value. Looking at the SB’s output, the first step model was statistically significant F(1, 88) = 40.16; p < .001 explaining 31% of variance. The introduction of resilience produced both a significant R2 change, accounting for an additional 4% of variance, and a significant overall value F(2, 87) = 23.01; p < .001. Even in an overall Table 7 Regression analysis for SB and OB using satisfaction with life, resilience and depression related emotions as predictors. N = 91

Subjective burden (SB)

Variable

B

Step 1 SWLS Step 2 SWLS RSA Step 3 SWLS RSA DASS

SE B

Objective burden (OB) R2

B

.31 .52**

.08

.56

.46** .02*

.08 .01

.50 .19

.45** .02 .02

.09 .01 .03

.49 .16 .07

.35

.35

DR2

B

SE B

R2

B

**

DR2

.04 .11

.06

.19

.14* .01

.06 .01

.24 .15

.13* .01 .01

.07 .01 .03

.23 .18 .05

.04*

.00

.06

.02

.06

.00

Note: N = number of participants; SWLS = Satisfaction With Life Scale; RSA = Resilience Scale for Adults; DASS = Depression Anxiety Stress Scale. * p < .05. ** p < .001.

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significant model F(3, 86) = 15.41; p < .001, the addition of depression related emotions in step 3 did not contribute in predicting SB level, further confirming multivariate results. The best fitting model for predicting caregiver’s SB was thus reached in step 2 as a linear combination of life satisfaction and resilience levels, with the former variable showing a higher b value than the latter. High values of satisfaction predicted low levels of SB while low levels of resilience indicated high perceived SB. A multivariate test further confirmed that the parameters for SB and OB differed both for satisfaction with life L = .86; F(1, 86) = 14.1; p < .001 and resilience L = .92; F(1, 86) = 7.41; p = .008; no differences were instead detected for depression related emotions L = .99; F(1, 86) = 0.13; p = ns. 4. Discussion The purpose of this study was to investigate the relationship between informal caregivers’ perceived burden and wellbeing and depression dimensions. To our knowledge, this is the first study jointly assessing perceived burden and well-being components, further including the comparison of these dimensions between caregivers differing in burden levels. As concerns participants’ demographic features, the substantial gender imbalance is consistent with the international literature, highlighting the predominant involvement of women in caring activities, in particular those involving complex levels of assistance (Neugaard et al., 2008). As for the study aims, three major hypotheses were formulated. The first one concerned the predominance of subjective burden within the total burden, at any level of perceived total burden. The hypothesis was confirmed among caregivers with high levels of total burden, classified as being at risk for burnout. On the opposite, among caregivers with low levels of overall burden subjective and objective burden accounted for similar proportions of the total score. These findings suggest that the perception of subjective burden is a crucial dimension to be considered in interventions addressed to prevent burnout among informal caregivers, and in particular parents of people with severe medical diagnoses. Mere reduction of the time devoted to assistance (corresponding to objective burden) could be not sufficient to promote well-being. We then hypothesized that high levels of burden would be associated with lower psychological and social resources, assessed through qualitative and quantitative measures of well-being, resilience, and perceived social support. The qualitative investigation of personal skills and resources highlighted the prominent relevance attributed to hardiness by caregivers with high levels of burden. Hardiness (Kobasa, Maddi, & Kahn, 1982) includes abilities such as courage, perseverance and commitment toward goal pursuit, and the tendency to approach problems as opportunities for growth, thus contributing to well-being promotion (Ben-Zur, Duvdevany, & Lury, 2005; Clark, 2002). Caregivers with lower levels of burden instead emphasized problem-focused coping and patience as their prominent resources. No specific references could be found on patience in the psychological literature, while few studies investigated caregivers’ psychological acceptance (Lloyd & Hastings, 2008; MacDonald et al., 2010). Although the two constructs share some conceptual components, patience – a virtue widely discussed in philosophical and religious treatises across cultures – has not been thoroughly investigated in psychology, thus deserving further studies. Consistent with previous findings (Delle Fave, Brdar, Wissing, & Vella-Brodrick, 2013; Lin, Chen, & Li, 2012), relational competences emerged as relevant resources especially with regard to the educational role of these caregivers, that represents an important component of their responsibility as parents of the care-recipients. We then analyzed group differences in depression-related emotions and well-being indicators. Caregivers at risk for burnout reported significantly higher levels of depressive emotions, as well as lower levels of life satisfaction, hedonic balance, family social support and happiness in general and with health, family, community and society. On the other hand, no group differences were detected in the levels of meaningfulness across life domains, and in perceived social support in general, related to significant others and friends. As for resilience, significant group differences were detected for the future planning dimension and for the total resilience score. Nevertheless, caregivers at risk for burnout reported moderate rather than low levels of resilience. In line with other studies (Delle Fave et al., 2015; Friborg, Barlaug, Martinussen, Rosenvinge, & Hjemdal, 2005), these findings suggest that, despite high burden levels and emotional distress, caregivers in this group were able to redefine and reorganize their own life through resource development, meaning making, and strengthening of relational ties. Finally, a multiple linear regression was run to evaluate whether life satisfaction, resilience and depression related emotions could predict caregivers’ burden level. Findings showed that high values of life satisfaction predicted significantly lower levels of objective and subjective burden, resilience contribution was limited, while depression related emotions were not a significant predictor of burden. These findings suggest that caregivers who are more satisfied have a lower probability to perceive high burden and to be thus exposed to burnout risk. These results were in line with studies conducted with caregivers of people with different diseases (Bassi et al., 2014; Brouwer, Exel, Berg, Bos, & Koopmanschap, 2008; Cohen, Colantonio, & Vernich, 2002; Pickett, Altmaier, & Paulsen, 2007). Moreover, the recent mental health continuum model (Keyes, 2007) provided empirical support to the WHO’s definition of health as presence of well-being, showing that wellbeing and ill-being dimensions belong to two different and relatively independent continua, rather than being opposite poles of the same continuum. Overall, these studies concur to suggest that the presence of psychological resources such as life satisfaction and resilience can be considered as a protective factor per se, and it should not be equated to the absence of negative symptoms. Well-being promotion based on the assessment of positive indicators should be more systematically pursued in intervention programs addressed to caregivers (Peer & Hillman, 2014; Resch, Benz, & Elliott, 2012). Since findings suggest that high burden is not synonymous with low well-being, in line with the dual continua model it can be assumed that burden and

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depressive emotions are not situated at the opposite pole of satisfaction, happiness and resilience along a single ill-being/ well-being continuum. They rather represent independent measures of functioning. For this reason, intervention programs addressed to caregivers should integrate the investigation of burden with the detection of psychosocial resources (Joseph, Becker, Elwick, & Silburn, 2012). From the ICF perspective, designing interventions focused on the implementation of contextual facilitators, such as subjective and eudaimonic well-being components at the personal level, and social support and resilience at the relational level, could contribute to caregivers’ optimal functioning besides and beyond interventions focused on burden reduction. 5. Limitations All the caregivers in this study were end users of the rehabilitation services provided by IRCCS Fondazione Don Carlo Gnocchi, an institution representing a positive model of integrated care. Therefore, results cannot be generalized, and further investigation is required, involving users of different typologies of health and social services. Moreover, the study design was cross-sectional, thus not allowing for any causality assumption. The joint longitudinal evaluation of burden and well-being indicators could allow for the investigation of perceived burden from a dynamic perspective, taking into account changes in caregivers’ life related to individual and environmental characteristics. 6. Conclusion Although informal caregivers cope with many difficulties in daily life, personal, family and social resources substantially contribute to enhance their quality of life. In line with the bio-psychosocial perspective endorsed by ICF, this study highlighted the importance to evaluate both ill- and well-being dimensions through a systemic approach, considering both psychological and environmental components. 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