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Informal Caregiving and Subjective Well-Being: Evidence of a Population-Based Longitudinal Study of Older Adults in Germany
JAMDA xxx (2015) 1e6
JAMDA journal homepage: www.jamda.com
Original Study
Informal Caregiving and Subjective Well-Being: Evidence of a Population-Based Longitudinal Study of Older Adults in Germany André Hajek PhD *, Hans-Helmut König MD, MPH, Prof Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
a b s t r a c t Keywords: Informal caregiving subjective well-being mental health positive and negative affect life satisfaction health-related quality of life
Objectives: The aim of this study was to examine whether informal caregiving affects subjective wellbeing (SWB) of the caregivers in the long run. Methods: The German Ageing Survey (DEAS) is a nationwide, representative longitudinal study of community-dwelling individuals living in Germany aged 40 and older. The surveys in 2002, 2008, and 2011 were used (11,264 observations). Several components of SWB were used, covering functional and mental health, and affective (positive affect and negative affect) as well as cognitive well-being. Although functional health was quantified by the subscale “physical functioning” of the 36-Item Short Form Health Survey (SF-36), mental health was assessed by using the Center for Epidemiologic Studies Depression Scale (CES-D). Life satisfaction (cognitive well-being) was quantified by using the Satisfaction with Life Scale (SWLS) and positive and negative affect (affective well-being) was assessed using the Positive and Negative Affect Schedule (PANAS). Results: Longitudinal regressions revealed that informal care affected (1) mental health in the total sample and in both sexes as well as (2) cognitive well-being in women. The effect of informal care on mental health was significantly moderated by self-efficacy in the total sample. Conclusion: Our findings emphasize the role of informal caregiving for mental health and cognitive wellbeing (women). Moreover, our findings highlight the role of self-efficacy in the relation between informal care and mental health. Thus, to prevent declines in mental health due to informal care, it might be a fruitful approach to strengthen self-efficacy. Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Subjective well-being (SWB) refers to the question of how people think and feel about their lives.1 It is a very broad concept with 2 core components: affective well-being (AWB) and cognitive well-being (CWB).2 Although AWB refers to the experience of positive affects (PA), such as enthusiasm and the absence of negative affects (NA), including sadness or anxiety, CWB refers to the cognitive evaluation of life as a whole.3 AWB and CWB are distinct constructs. They, for example, differ in their stability over time,4 and in their association with other variables.5 Furthermore, related concepts in medical research exist, concentrating on health-related quality of life (HRQoL), including the core components functional and mental health status.6,7 HRQoL is an important health outcome indicator and is the main concern of health care professionals.6,7
The authors declare no conflicts of interest. * Address correspondence to André Hajek, PhD, Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Martinistr 52, 20246 Hamburg, Germany. E-mail address: [email protected] (A. Hajek). http://dx.doi.org/10.1016/j.jamda.2015.10.015 1525-8610/Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Cross-sectionally, informal caregiving is one of the major predictors of HRQoL.8e10 Furthermore, informal caregiving is known to be associated with other adverse outcomes (eg, it restricts time to spend with friends, to fulfill family obligations, or to pursue other leisure activities).11 Informal caregiving is also associated with distress12 and burnout symptoms,13 which have serious consequences for productivity.14 Furthermore, changes in caregivers’ SWB can have numerous negative consequences for care-recipients such as abusive behavior.15 Nevertheless, generally, individuals in need of care prefer to live at home as long as possible to maintain familiar environment or to keep their social ties. Given these preferences, it is expected that the need for informal care will increase markedly in the next decades due to demographic ageing, highlighting the importance of informal care. To understand caregiving distress more deeply, the stress and coping model (adapted to caregiving) has widely been used as theoretical model.16,17 According to this model, informal caregivers differ in SWB even though they face similar situations. This can be explained by the fact that informal caregivers differ by numerous variables.
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Although the role of social support and coping strategies has been studied extensively within the framework of the stress and coping model,18 the effect of self-efficacy on SWB over time is almost unclear. Self-efficacy can be defined as “the conviction that one can successfully execute the behavior required to produce the outcomes.”19 Most of the studies examining the relation between self-efficacy and SWB were cross-sectional.20e22 Only 2 longitudinal studies exist investigating the effect of self-efficacy on physical and mental health in a longitudinal approach.23,24 Both of them found significant effects of self-efficacy, however, without explicitly focusing on the potential role as a moderator. To our knowledge, no longitudinal study has investigated the effect of informal care on SWB in the aforementioned broad sense, namely, covering AWB and CWB as well as HRQoL and how this relationship may be moderated by self-efficacy among older adults in the long run thus far. It addresses the issue of whether the numerous measures of SWB are differentially affected by informal caregiving and selfefficacy. Therefore, we aimed at investigating (1) whether informal care affects SWB in the long run and (2) whether this effect is moderated by self-efficacy in a longitudinal approach, drawing on a representative sample of individuals aged 40 and older. Consequently, informal caregivers at risk for decline in SWB can be identified. Additionally, insights into the causality can be derived. This knowledge is crucial to create interventional strategies.
Methods Sample Data were drawn from the second, third, and fourth waves from the public release of the German Ageing Survey (DEAS), provided by the Research Data Centre of the German Centre of Gerontology (DZA). This is a population-based, representative survey of the communitydwelling population aged 40 and older in Germany. A national probability sampling was used. Individuals were interviewed at home by trained staff using a standardized questionnaire. Because a measure of depression was included from the second wave onward, we restricted our analysis for reasons of consistency to the waves 2 to 4. A total of 5194 individuals participated in the second wave, 8200 individuals participated in the third wave, and 4855 individuals participated in the fourth wave. Differences in sample sizes between waves were mainly due to the collection of new samples (except for 2011, which is a “pure” panel survey). More details regarding the sampling frame and the sample composition were provided elsewhere.25 We solely included respondents with within-variation in fixed effect (FE) regressions.
Subjective Well-Being Functional health was quantified by the subscale “physical functioning” of the 36-Item Short Form Health Survey (SF-3626), ranging from 0 (worst score) to 100 (best score), and mental health was assessed by the Center for Epidemiologic Studies Depression Scale (CES-D27), which consists of 15 items, resulting in a sum score (0e45, with high values indicating worse ratings of mental health). Life satisfaction (CWB) was measured by the Satisfaction with Life Scale (SWLS28) with 5 items on a 5-point rating scale, ranging from 1 to 5 (high values indicate high CWB). Moreover, PA and NA were assessed using the Positive and Negative Affect Schedule (PANAS29), each quantified with 10 items on 5-point rating scales that ranged from 1 (very slightly or not at all) to 5 (extremely). High values indicate high PA or NA.
Independent Variables Individuals were asked if they provide informal care by using the question “Are there people you look after or care for regularly due to their poor state of health, either on a private or volunteer basis?” (no; yes). Self-efficacy was quantified by using the HOPE scale with 8 items,30 ranging from 1 to 4 (high values indicate high self-efficacy). Examples for items of the 4-point HOPE scale are “I can think of many ways to get the things in life that are most important to me”; “There are lots of ways around any problem”; “I meet the goals that I set for myself”; or “I’ve been pretty successful in life” (ranging from 1 ¼ strongly agree to 4 ¼ strongly disagree). Furthermore, we analyzed other time-dependent regressors that were assumed to be relevant for SWB, such as sociodemographic factors,31 social network, and morbidity.32 Age and monthly household net income in Euro (logarithmized) was taken into account. Additionally, the number of important people in regular contact (ranging from 0 to 9) was taken into account. Moreover, morbidity (total number of physical diseases, eg, cardiovascular diseases, diabetes, cancer, respiratory diseases, eye diseases, hearing problems) was used. These conditions were informed by the Charlson Comorbidity Index.33 Additionally, dummy coded variables for region, employment status (Ref.: working; retired; other: not employed), and family status (Ref.: married, living together with spouse; married, living separated from spouse; divorced; widowed; never married) (not shown in regression analysis for the sake of space, but available on request) were added as control variables. For descriptive purposes, the time-constant independent variables sex and education (International Standard Classification of Education [ISCED]34 with 3 categories: low [ISCED 0e2], medium [ISCED 3e4], and high [ISCED 5e6]) were reported at baseline. It is worth mentioning that these variables cannot be included in FE regressions because only time-dependent variables can be included in these regressions, which is described in more detail in the statistical analyses. In sensitivity analysis, informal caregiving was replaced by selfreported average time per week for help/assistance (logarithmized). Statistical Analyses The effect of time-dependent independent variables on SWB was estimated using panel regression techniques enabling us to control for time-invariant unobserved heterogeneity such as optimism or genetic predisposition. This is important in SWB research as, in most cases, unobserved factors are correlated with independent variables in a systematic manner.35 In this case, random effect regression techniques are inconsistent and, hence, FE regressions are the preferred method because they produce consistent estimates (under the assumption of strict exogeneity).36 It is worth noting that FE regressions solely use within-variations over time. Therefore, the FE estimator is also called “within-estimator.” Taking into account heteroscedasticity and serial correlation of the error terms, SEs were computed that cluster errors at the individual level.37 Results Descriptive Analysis At baseline (wave 2), most were male (51.5%) and had a medium education (52.5%) according to ISCED categories. In Table 1, we reported descriptive statistics of time-dependent variables in individuals who reported SWB outcomes in at least 2 waves. At wave 2, mean age was 59.1 years (10.4 years), ranging from 40 to 83 years. Most were married, living together with spouse (78.0%), and still working (44.7%). The monthly household net income was V2987.9
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Table 1 Descriptive Statistics for Time-Dependent Variables Over Time (Waves 2e4) Wave 2, n ¼ 1646 Age, mean (SD) Marital status, n (%) Married, living together with spouse Married, living separated from spouse Divorced Widowed Single Employment status, n (%) Working Retired Other: not employed Monthly household net income in Euro,* mean (SD) No. of important people in regular contact,y mean (SD) Self-efficacy (HOPE Scale),z mean (SD) Morbidity (total no. of physical diseases),x mean (SD) Informal care, n (%) Providing informal care Not providing informal care Functional health (subscale “Physical Functioning” of the SF-36),k mean (SD) Mental health (CES-D),{ mean (SD) CWB (SWLS),** mean (SD) NA,yy mean (SD) PA,zz mean (SD)
59.1 (10.4) 1283 25 134 134 69 736 669 241 2987.9 5.2 3.1 2.2
(78.0) (1.6) (8.1) (8.1) (4.2) (44.7) (40.6) (14.7) (1875.3) (2.5) (0.4) (1.7)
222 (13.5) 1416 (86.5) 88.5 (17.0) 7.1 3.9 2.0 3.5
(5.9) (0.7) (0.5) (0.5)
Wave 3, n ¼ 3044 63.1 (11.1) 2249 40 254 345 158 1082 1599 365 2587.8 4.7 3.0 2.4
(73.8) (1.3) (8.4) (11.3) (5.2) (35.5) (52.5) (12.0) (2447.6) (2.8) (0.4) (1.8)
435 (14.8) 2512 (85.2) 84.9 (19.8) 6.5 3.8 2.1 3.5
(5.4) (0.7) (0.5) (0.5)
Wave 4, n ¼ 3023 65.5 (10.7) 2227 34 249 355 155 958 1752 309 2714.5 5.0 3.0 2.6
(73.7) (1.1) (8.3) (11.8) (5.1) (31.7) (58.0) (10.3) (1715.0) (2.7) (0.4) (1.9)
428 (14.7) 2481 (85.3) 82.7 (21.3) 7.0 3.8 2.1 3.5
(5.8) (0.7) (0.5) (0.5)
Missing values for metric variables (if occurred): *A total of 435 missing values in the second wave, 445 missing values in the third wave, and 261 missing values in the fourth wave. y Seventeen missing values in the second wave, 1 missing value in the third wave. z Forty-one missing values in the second wave, 90 missing values in the third wave, and 100 missing values in the fourth wave. x Forty-three missing values in the second wave, 128 missing values in the third wave, and 144 missing values in the fourth wave. k Seventeen missing values in the second wave, 3 missing values in the third wave, and 13 missing values in the fourth wave. { Ninety-one missing values in the second wave, 89 missing values in the third wave, and 65 missing values in the fourth wave. **Forty-two missing values in the second wave, 90 missing values in the third wave, and 104 missing values in the fourth wave. yy Forty-three missing values in the second wave, 91 missing values in the third wave, and 102 missing values in the fourth wave. zz Forty-three missing values in the second wave, 91 missing values in the third wave, and 102 missing values in the fourth wave.
( V1,875.3). The mean number of important people in regular contact was 5.2 (2.5), and the mean number of physical diseases was 2.2 (1.7). The mean self-efficacy (HOPE scale) was 3.1 (0.4). Most did not provide informal care (86.5%). As for our SWB measures, mean CWB (SWLS) was 3.9 (0.7), mean NA (PANAS) was 2.0 (0.5), mean PA (PANAS) was 3.5 (0.5), mean functional health (Subscale “Physical Functioning” of the SF-36) was 88.5 (17.0) and mean mental health (CES-D) was 7.1 (5.9). After 9 years (wave 4), the proportion of employed individuals decreased to 31.7%. Other variables remained nearly constant. Regression Analysis FE regressions revealed that informal care affected (1) mental health in the total sample (b ¼ 1.0) and in both sexes (men: b ¼ 1.3; women: b ¼ 0.9) and (2) CWB in women (b ¼ 0.1) (Table 2). However, informal care did not affect NA, PA, and functional health in the total sample and in both sexes. The effect of informal care on mental health was moderated by self-efficacy in the total sample (Table 3). FE regressions showed that age (except for PA), morbidity, and self-efficacy affected each dependent variable in total sample and in both sexes. Sensitivity Analysis We checked the robustness (in terms of significance) of our variables of interest by comparing the main model (Table 2) with alternate models (results of model specifications are not shown, but are available on request from the authors). In sensitivity analysis, informal caregiving was replaced by average time per week for help/assistance (logarithmized). Although the effect of caregiving time on CWB also vanished in women, the other findings remained the same in terms of
significance. Thus, caregiving time affected mental health in the total sample and in both sexes, showing that the effect of informal caregiving was insensitive to the measure used. Discussion Main Findings Longitudinal regressions showed that informal care affected (1) mental health in the total sample and in both sexes and (2) CWB in women. The effect of informal care on mental health was moderated by self-efficacy in the total sample. Furthermore, longitudinal regressions revealed that age (except for PA), morbidity, and self-efficacy affected each dependent variable in total sample and in both sexes. Previous Research The association between informal caregiving and SWB is crosssectionally well established. As yet, however, longitudinal studies investigating the effect of informal caregiving on SWB are rare.38,39 For example, Smith et al39 found that increases in caregiving stressors were related to increased caregiver depression, derived from a sample of 310 informal caregivers of elderly care-recipients at baseline (and 213 individuals 1 year later). Even in another study,38 solely informal caregivers were included (130 dementia caregivers at baseline, with 3 assessments at baseline, 3 months later and 1 year later). Thus, our findings extend previous short-term longitudinal findings that mostly focus on individuals providing informal care already at baseline. Consequently, our findings indicate that the occurrence of informal caregiving considerably reduced mental health in the long term, underlining the urgent need for interventions to prevent mental
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Table 2 Longitudinal Predictors of SWB: Results of FE Regressions (Waves 2e4) Variables
CWB
CWB, Men
Age Morbidity Monthly household net income in Euro (log) No. of important people in regular contact Self-efficacy Informal caregiving (Ref.: no) Constant Observations No. of individuals R2
0.0104* (0.00224) 0.0115* (0.00302) 0.00933y (0.00333) 0.00838* (0.00191) 0.00652z (0.00255) 0.0102* (0.00290) 0.00148 (0.00175) 0.0350* (0.00695) 0.0348* (0.00894) 0.0348y (0.0107) 0.0746* (0.00606) 0.0711* (0.00803) 0.0795* (0.00925) 0.0220* (0.00550) 0.106* (0.0303) 0.0958z (0.0399) 0.104z (0.0458) 0.0175 (0.0261) 0.0223 (0.0364) 0.0102 (0.0378) 0.0201 (0.0242)
0.00201 (0.00291) 0.000860 (0.00371)
0.728* (0.0326) 0.0388 (0.0244) 0.181 (0.567) 11263 7922 0.209
0.750* (0.0442) 0.00235 (0.0369) 0.0196 (0.606) 5880 4108 0.236
CWB, Women
NA
0.00272 (0.00460)
0.710* (0.0479) 0.0690z (0.0325) 0.504 (0.412) 5377 3811 0.192
NA, Men
NA, Women
PA
0.00492x (0.00262)
0.00475 (0.00351)
0.00536 (0.00394) 0.00655y (0.00237)
0.317* (0.0278) 0.000811 (0.0197)
0.305* (0.0384) 0.0348 (0.0280)
0.334* (0.0409) 0.0243 (0.0274)
2.871* (0.303) 11264 7922 0.121
3.178* (0.367) 5883 4111 0.124
3.654* (0.414) 5375 3808 0.126
0.490* (0.0262) 0.000800 (0.0187) 1.141* (0.318) 11262 7920 0.165
Beta-coefficients were reported; cluster-robust SEs in parentheses. Regressions are also controlled for family status, employment status, and region. Observations with missing values were dropped (list-wise deletion). * P < .001; yP < .01; zP < .05; xP < .10.
illnesses. On the positive side, it should be noted that informal caregiving did not affect most of the other outcome measures (except for CWB in women). This might be explained by the fact that informal caregiving is also associated with positive effects such as receiving gratitude from the care-recipients, higher self-esteem, meaning in one’s life or personal growth,17 and these positive effects may especially influence the CWB as well as AWB. In sum, these aforementioned effects might compensate for the adverse effects of informal caregiving. Most of the previous studies analyzing the relation between selfefficacy and SWB were based on cross-sectional data. Because, as already stated earlier, it is mandatory to control for unobserved heterogeneity in SWB research,35 longitudinal studies are needed to receive unbiased estimates. Nevertheless, cross-sectional studies clearly confirmed that self-efficacy is associated with SWB40,41 and might moderate the relation between stressors and mental health.22,24 By using a linear mixed model, Romero-Moreno et al.38 found that caregivers’ self-efficacy significantly predicted decreases in depression over time. Our findings also provide empirical evidence for the stress and coping model for caregiving because self-efficacy significantly affected SWB longitudinally. Yet, the interaction between self-efficacy and informal care on mental health have not been examined in a longitudinal approach. In this regard, our findings extend previous knowledge and highlight the importance of selfefficacy in the relation between informal caregiving and mental health. Drawing on the stress and coping model,42 this moderating effect may be explained by the role of self-efficacy in controlling upsetting thoughts (eg, controlling thoughts about negative aspects of informal care) and managing behavioral problems referring to the
ability to respond to disruptive behavior in daily life care (eg, respond to rapid mood swings of the care-recipient).24 Moreover, we would like to emphasize that our findings concerning these longitudinal predictors correspond to previous longitudinal studies.43,44
Strengths and Limitations To our knowledge, this is the first longitudinal study investigating the moderating effect of self-efficacy in the relation between informal caregiving and SWB in older adults in Germany. Additionally, SWB was quantified with validated instruments (eg, CES-D) in a variety of ways (covering functional and mental health, AWB as well as CWB), examining whether the numerous measures of SWB were affected differentially in the long run (2002 to 2011). Moreover, by exploiting longitudinal data, the effect of changes in the independent variables on SWB can be assessed. Additionally, timeinvariant unobserved heterogeneity can be taken into account by using FE regressions. Another point that should be highlighted is that a representative sample of community-dwelling individuals aged 40 and older living in Germany was used. Nevertheless, we cannot rule out that our FE estimates are biased due to reverse causality (eg, AWB affects self-efficacy). Moreover, time spans between our waves were rather long. Thus, short-term changes may be covered for reasons of adaptation processes.45 Furthermore, another limitation is that our estimates might be slightly biased downward due to endogenous selection bias in the German Ageing Survey.46 Moreover, other predictors (eg, satisfaction with leisure time47 or the need for care48) might play a role in the relation between
Table 3 Longitudinal Predictors of Mental Health (With Interaction-Term: Self-Efficacy Informal Caregiving): Results of FE Regressions (Waves 2e4) Variables
Mental Health
Mental Health, Men
Mental Health, Women
Age Morbidity Monthly household net income in Euro (log) Number of important people in regular contact Self-efficacy Informal caregiving (Ref.: no) Self-efficacy Informal caregiving Constant Observations No. of Individuals R2
0.0843* 0.364* 0.266 0.0521 1.713* 5.693z 1.500z 20.59* 11048 7786 0.0386
0.0723z 0.353* 0.328 0.00669 2.130* 4.150 0.917 20.03* 5763 4034 0.0501
0.102z 0.378* 0.198 0.105x 1.296y 6.983z 1.978x 27.26* 5279 3749 0.0410
(0.0243) (0.0734) (0.325) (0.0331) (0.324) (2.395) (0.756) (5.017)
(0.0295) (0.0997) (0.420) (0.0405) (0.467) (2.849) (0.890) (4.851)
(0.0396) (0.110) (0.492) (0.0542) (0.446) (3.463) (1.101) (4.804)
Beta-coefficients were reported; cluster-robust SEs in parentheses. Regressions are also controlled for family status, employment status, and region. Observations with missing values were dropped (list-wise deletion). *P < .001; yP < .01; zP < .05; xP < .10.
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PA, Men
PA, Women
Functional Health
Functional Health, Men
Functional Health, Women
Mental Health
Mental Health, Men
Mental Health, Women
0.00148 (0.00238) 0.0178z (0.00714) 0.000887 (0.0353)
0.00478x (0.00257) 0.0250y (0.00845) 0.0415 (0.0339)
0.601* (0.0650) 1.329* (0.204) 0.718 (1.031)
0.611* (0.0905) 1.655* (0.293) 0.853 (1.132)
0.566* (0.0934) 0.971* (0.277) 2.071 (1.742)
0.0832* (0.0243) 0.363* (0.0736) 0.274 (0.323)
0.0719z (0.0295) 0.354* (0.1000) 0.336 (0.419)
0.0996z (0.0396) 0.375* (0.110) 0.198 (0.490)
0.00652z (0.00315)
0.00616x (0.00365)
0.126 (0.0856)
0.112 (0.114)
0.128 (0.126)
0.0520 (0.0331)
0.00737 (0.0404)
0.104x (0.0544)
0.482* (0.0370) 0.00985 (0.0242)
3.624* (0.798) 0.0839 (0.778)
3.824* (1.116) 0.523 (1.158)
3.503y (1.129) 0.404 (1.044)
1.902* (0.328) 1.043* (0.264)
2.218* (0.461) 1.279* (0.376)
103.2* (10.38) 11257 7909 0.0765
107.0* (11.51) 5884 4107 0.111
103.4* (14.72) 5367 3799 0.0557
19.89* (3.641) 11048 7786 0.0367
26.24* (4.493) 5763 4034 0.0494
0.502* (0.0376) 0.00314 (0.0295) 2.226* (0.383) 5881 4109 0.181
1.345* (0.378) 5375 3808 0.159
informal caregiving and SWB. However, due to reasons of data availability, these variables were not included in regression analysis. Conclusions Our findings contribute to the scarce longitudinal evidence regarding the long-term impact of informal care on SWB, covering numerous aspects of subjective well-being (CWB, AWB, as well as functional and mental health), providing support to the stress and coping model for caregiving. Moreover, our findings emphasize the importance of informal caregiving for mental health and CWB (women). Particularly, the former relation can hardly be overemphasized, in terms of both significance and magnitude. Furthermore, given that individuals in need of care prefer to live at home as long as possible, it is most likely that the need for informal care will increase markedly in the next decades due to demographic aging. Therefore, interventions to prevent mental illnesses in informal caregivers are urgently needed. Practitioners as well as policymakers should be aware of these upcoming challenges in the next decades. Respite care (provision of short-term accommodation, typically on a daily or weekly basis) might be helpful to relieve the stress of being a caregiver.49 Moreover, more health promotion interventions might be useful to encourage informal caregivers to use counseling services.50 In turn, these services might have positive effects on their health. Furthermore, the role of self-efficacy in the relation between informal care and mental health can be highlighted. In sum, selfefficacy might be a relevant tool to identify informal caregivers at risk for mental health problems. Additionally, to prevent declines in mental health due to informal care, it might be a fruitful approach to strengthen self-efficacy.51,52 For example, home visits by occupational therapists providing physical, educational, and social environmental modifications53e55 might help to enhance self-efficacy. Furthermore, strengthening coping skills might be important for stressful situations in daily caregiving,56,57 and financial support may help to alleviate the monetary stress of informal caregiving. References 1. Diener E. Subjective well-being. Psychol Bull 1984;95:542e575. 2. Busseri MA, Sadava SW. A review of the tripartite structure of subjective wellbeing: Implications for conceptualization, operationalization, analysis, and synthesis. Pers Soc Psychol Rev 2011;15:290e314. 3. Luhmann M, Hofmann W, Eid M, Lucas RE. Subjective well-being and adaptation to life events: A meta-analysis. J Pers Soc Psychol 2012;102:592e615. 4. Eid M, Diener E. Global judgments of subjective well-being: Situational variability and long-term stability. Soc Ind Res 2004;65:245e277.
1.606* (0.463) 0.894z (0.366) 28.19* (4.790) 5279 3749 0.0374
5. Kahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. Proc Natl Acad Sci U S A 2010;107:16489e16493. 6. Tian-hui C, Lu L. A systematic review: How to choose appropriate healthrelated quality of life (HRQOL) measures in routine general practice? J Zhejiang Univ Sci B 2005;6:936e940. 7. Wilson IB, Cleary PD. Linking clinical variables with health-related quality of life: A conceptual model of patient outcomes. JAMA 1995;273: 59e65. 8. Bleijlevens MH, Stolt M, Stephan A, et al. Changes in caregiver burden and health-related quality of life of informal caregivers of older people with Dementia: Evidence from the European RightTimePlaceCare prospective cohort study. J Adv Nurs 2015;71:1378e1391. 9. Brodaty H, Donkin M. Family caregivers of people with dementia. Dialogues Clin Neurosci 2009;11:217. 10. Markowitz JS, Gutterman EM, Sadik K, Papadopoulos G. Health-related quality of life for caregivers of patients with Alzheimer disease. Alzheimer Dis Assoc Disord 2003;17:209e214. 11. Gilleard C, Gilleard E, Gledhill K, Whittick J. Caring for the elderly mentally infirm at home: A survey of the supporters. J Epidemiol Community Health 1984;38:319e325. 12. Schulz R, O’Brien AT, Bookwala J, Fleissner K. Psychiatric and physical morbidity effects of dementia caregiving: Prevalence, correlates, and causes. Gerontologist 1995;35:771e791. 13. Neugaard B, Andresen E, McKune SL, Jamoom EW. Health-related quality of life in a national sample of caregivers: Findings from the behavioral risk factor surveillance system. J Happiness Stud 2008;9:559e575. 14. Maslach C, Schaufeli WB, Leiter MP. Job burnout. Annu Rev Psychol 2001;52: 397e422. 15. Cooper C, Selwood A, Blanchard M, et al. The determinants of family carers’ abusive behaviour to people with dementia: Results of the CARD study. J Affect Disord 2010;121:136e142. 16. Folkman S. Stress, Appraisal, and Coping. New York, NY: Springer Publishing Company LLC; 1984. 17. Haley WE. Family caregivers of elderly patients with cancer: Understanding and minimizing the burden of care. J Support Oncol 2003;1:25e29. 18. Gottlieb BH, Rooney J. Coping effectiveness: Determinants and relevance to the mental health and affect of family caregivers of persons with dementia. Aging Ment Health 2004;8:364e373. 19. Bandura A. Self-efficacy: Toward a unifying theory of behavioral change. Psychol Rev 1977;84:191. 20. Cheng S-T, Lam LCW, Kwok T, et al. Self-efficacy is associated with less burden and more gains from behavioral problems of Alzheimer’s disease in Hong Kong Chinese caregivers. Gerontologist 2013;53:71e80. 21. Nogales-González C, Romero-Moreno R, Losada A, et al. Moderating effect of self-efficacy on the relation between behavior problems in persons with dementia and the distress they cause in caregivers. Aging Ment Health 2015;19: 1022e1030. 22. Rabinowitz YG, Mausbach BT, Gallagher-Thompson D. Self-efficacy as a moderator of the relationship between care recipient memory and behavioral problems and caregiver depression in female dementia caregivers. Alzheimer Dis Assoc Disord 2009;23:389e394. 23. George NR, Steffen A. Physical and mental health correlates of self-efficacy in dementia family caregivers. J Women Aging 2014;26:319e331. 24. Romero-Moreno R, Losada A, Mausbach B, et al. Analysis of the moderating effect of self-efficacy domains in different points of the dementia caregiving process. Aging Ment Health 2011;15:221e231. 25. Engstler H, Motel-Klingebiel A. Datengrundlagen und Methoden des deutschen Alterssurveys (DEAS). In: Motel-Klingebiel A, Wurm S, Tesch-Römer C, editors.
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A. Hajek, H.-H. König / JAMDA xxx (2015) 1e6 Altern im Wandel. Befunde des Deutschen Alterssurveys (DEAS). Stuttgart: Verlag W. Kohlhammer; 2010. p. 34e60. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Med Care 1992;30:473e483. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population. Appl Psychol Meas 1977;1:385e401. Pavot W, Diener E. Review of the satisfaction with life scale. Psychol Assess 1993;5:164. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: The PANAS scales. J Pers Soc Psychol 1988;54: 1063. Snyder CR, Harris C, Anderson JR, et al. The will and the ways: Development and validation of an individual-differences measure of hope. J Pers Soc Psychol 1991;60:570. König H-H, Bernert S, Angermeyer MC, et al. Comparison of population health status in six European countries: Results of a representative survey using the EQ-5D questionnaire. Med Care 2009;47:255e261. Chiu HC, Chen CM, Huang CJ, Mau LW. Depressive symptoms, chronic medical conditions and functional status: A comparison of urban and rural elders in Taiwan. Int J Geriatr Psychiatry 2005;20:635e644. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol 1994;47:1245e1251. United Nations Educational, Scientific, and Cultural Organization. International Standard Classification of Education. Paris, France: ISCED; 1997. Re-edition ed2006. Ferrer-i-Carbonell A, Frijters P. How important is methodology for the estimates of the determinants of happiness? Econ J 2004;114:641e659. Cameron AC, Trivedi PK. Microeconometrics: Methods and applications. New York: Cambridge University Press; 2005. Stock JH, Watson MW. Heteroskedasticity: Robust standard errors for fixed effects panel data regression. Econometrica 2008;76:155e174. Romero-Moreno R, Márquez-González M, Mausbach BT, Losada A. Variables modulating depression in dementia caregivers: A longitudinal study. Int Psychogeriatr 2012;24:1316e1324. Smith GR, Williamson GM, Miller LS, Schulz R. Depression and quality of informal care: A longitudinal investigation of caregiving stressors. Psychol Aging 2011;26:584. Márquez-González M, Losada A, López J, Peñacoba C. Reliability and validity of the Spanish version of the revised scale for caregiving self-efficacy. Clin Gerontol 2009;32:347e357. Steffen AM, McKibbin C, Zeiss AM, et al. The revised scale for caregiving selfefficacy reliability and validity studies. J Gerontol B Psychol Sci Soc Sci 2002; 57:P74eP86.
42. Chun M, Knight B, Youn G. Differences in stress and coping models of emotional distress among Korean, Korean-American and White-American caregivers. Aging Ment Health 2007;11:20e29. 43. Eisele M, Kaduszkiewicz H, König H, et al. Determinants of health-related quality of life in older primary care patients: Results of the longitudinal observational AgeCoDe study. Br J Gen Pract 2015;65:e716ee723. 44. Zhang JX, Walker JD, Wodchis WP, et al. Measuring health status and decline in at-risk seniors residing in the community using the Health Utilities Index Mark 2. Qual Life Res 2006;15:1415e1426. 45. Clark AE, Georgellis Y. Back to baseline in Britain: Adaptation in the British household panel survey. Economica 2013;80:496e512. 46. Schiel S, Dickmann C, Aust F. Methodenbericht Deutscher Alterssurvey (DEAS): 4. Befragungswelle. Panelbefragung; 2011. 47. Moore RC, Harmell AL, Chattillion E, et al. Bonn PEAR model and sleep outcomes in dementia caregivers: Influence of activity restriction and pleasant events on sleep disturbances. Int Psychogeriatr 2011;23: 1462e1469. 48. Amirkhanyan AA, Wolf DA. Parent care and the stress process: Findings from panel data. J Gerontol B Psychol Sci Soc Sci 2006;61:S248eS255. 49. Zarit SH, Gaugler JE, Jarrott SE. Useful services for families: Research findings and directions. Int J Geriatr Psychiatry 1999;14:165e178. 50. Hankey GJ. Informal care giving for disabled stroke survivors: Training the care giver benefits the patient, the care giver, and the community. BMJ 2004;328: 1085. 51. Kuhn D, Fulton BR. Efficacy of an educational program for relatives of persons in the early stages of Alzheimer’s disease. J Gerontol Soc Work 2004;42: 109e130. 52. Sörensen S, Pinquart M, Duberstein P. How effective are interventions with caregivers? An updated meta-analysis. Gerontologist 2002;42:356e372. 53. Corcoran MA, Gitlin LN. Dementia management: An occupational therapy home-based intervention for caregivers. Am J Occup Ther 1992;46: 801e808. 54. Gitlin LN, Corcoran M, Winter L, et al. A randomized, controlled trial of a home environmental intervention effect on efficacy and upset in caregivers and on daily function of persons with dementia. Gerontologist 2001;41:4e14. 55. Gitlin LN, Corcoran M, Winter L, et al. Predicting participation and adherence to a home environmental intervention among family caregivers of persons with dementia. Family Relations 1999;48:363e372. 56. Saad K, Hartman J, Ballard C, et al. Coping by the carers of dementia sufferers. Age Ageing 1995;24:495e498. 57. Schulz R, Hebert RS, Dew MA, et al. Patient suffering and caregiver compassion: New opportunities for research, practice, and policy. Gerontologist 2007;47: 4e13.
JAMDA journal homepage: www.jamda.com
Original Study
Informal Caregiving and Subjective Well-Being: Evidence of a Population-Based Longitudinal Study of Older Adults in Germany André Hajek PhD *, Hans-Helmut König MD, MPH, Prof Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
a b s t r a c t Keywords: Informal caregiving subjective well-being mental health positive and negative affect life satisfaction health-related quality of life
Objectives: The aim of this study was to examine whether informal caregiving affects subjective wellbeing (SWB) of the caregivers in the long run. Methods: The German Ageing Survey (DEAS) is a nationwide, representative longitudinal study of community-dwelling individuals living in Germany aged 40 and older. The surveys in 2002, 2008, and 2011 were used (11,264 observations). Several components of SWB were used, covering functional and mental health, and affective (positive affect and negative affect) as well as cognitive well-being. Although functional health was quantified by the subscale “physical functioning” of the 36-Item Short Form Health Survey (SF-36), mental health was assessed by using the Center for Epidemiologic Studies Depression Scale (CES-D). Life satisfaction (cognitive well-being) was quantified by using the Satisfaction with Life Scale (SWLS) and positive and negative affect (affective well-being) was assessed using the Positive and Negative Affect Schedule (PANAS). Results: Longitudinal regressions revealed that informal care affected (1) mental health in the total sample and in both sexes as well as (2) cognitive well-being in women. The effect of informal care on mental health was significantly moderated by self-efficacy in the total sample. Conclusion: Our findings emphasize the role of informal caregiving for mental health and cognitive wellbeing (women). Moreover, our findings highlight the role of self-efficacy in the relation between informal care and mental health. Thus, to prevent declines in mental health due to informal care, it might be a fruitful approach to strengthen self-efficacy. Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Subjective well-being (SWB) refers to the question of how people think and feel about their lives.1 It is a very broad concept with 2 core components: affective well-being (AWB) and cognitive well-being (CWB).2 Although AWB refers to the experience of positive affects (PA), such as enthusiasm and the absence of negative affects (NA), including sadness or anxiety, CWB refers to the cognitive evaluation of life as a whole.3 AWB and CWB are distinct constructs. They, for example, differ in their stability over time,4 and in their association with other variables.5 Furthermore, related concepts in medical research exist, concentrating on health-related quality of life (HRQoL), including the core components functional and mental health status.6,7 HRQoL is an important health outcome indicator and is the main concern of health care professionals.6,7
The authors declare no conflicts of interest. * Address correspondence to André Hajek, PhD, Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Martinistr 52, 20246 Hamburg, Germany. E-mail address: [email protected] (A. Hajek). http://dx.doi.org/10.1016/j.jamda.2015.10.015 1525-8610/Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Cross-sectionally, informal caregiving is one of the major predictors of HRQoL.8e10 Furthermore, informal caregiving is known to be associated with other adverse outcomes (eg, it restricts time to spend with friends, to fulfill family obligations, or to pursue other leisure activities).11 Informal caregiving is also associated with distress12 and burnout symptoms,13 which have serious consequences for productivity.14 Furthermore, changes in caregivers’ SWB can have numerous negative consequences for care-recipients such as abusive behavior.15 Nevertheless, generally, individuals in need of care prefer to live at home as long as possible to maintain familiar environment or to keep their social ties. Given these preferences, it is expected that the need for informal care will increase markedly in the next decades due to demographic ageing, highlighting the importance of informal care. To understand caregiving distress more deeply, the stress and coping model (adapted to caregiving) has widely been used as theoretical model.16,17 According to this model, informal caregivers differ in SWB even though they face similar situations. This can be explained by the fact that informal caregivers differ by numerous variables.
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Although the role of social support and coping strategies has been studied extensively within the framework of the stress and coping model,18 the effect of self-efficacy on SWB over time is almost unclear. Self-efficacy can be defined as “the conviction that one can successfully execute the behavior required to produce the outcomes.”19 Most of the studies examining the relation between self-efficacy and SWB were cross-sectional.20e22 Only 2 longitudinal studies exist investigating the effect of self-efficacy on physical and mental health in a longitudinal approach.23,24 Both of them found significant effects of self-efficacy, however, without explicitly focusing on the potential role as a moderator. To our knowledge, no longitudinal study has investigated the effect of informal care on SWB in the aforementioned broad sense, namely, covering AWB and CWB as well as HRQoL and how this relationship may be moderated by self-efficacy among older adults in the long run thus far. It addresses the issue of whether the numerous measures of SWB are differentially affected by informal caregiving and selfefficacy. Therefore, we aimed at investigating (1) whether informal care affects SWB in the long run and (2) whether this effect is moderated by self-efficacy in a longitudinal approach, drawing on a representative sample of individuals aged 40 and older. Consequently, informal caregivers at risk for decline in SWB can be identified. Additionally, insights into the causality can be derived. This knowledge is crucial to create interventional strategies.
Methods Sample Data were drawn from the second, third, and fourth waves from the public release of the German Ageing Survey (DEAS), provided by the Research Data Centre of the German Centre of Gerontology (DZA). This is a population-based, representative survey of the communitydwelling population aged 40 and older in Germany. A national probability sampling was used. Individuals were interviewed at home by trained staff using a standardized questionnaire. Because a measure of depression was included from the second wave onward, we restricted our analysis for reasons of consistency to the waves 2 to 4. A total of 5194 individuals participated in the second wave, 8200 individuals participated in the third wave, and 4855 individuals participated in the fourth wave. Differences in sample sizes between waves were mainly due to the collection of new samples (except for 2011, which is a “pure” panel survey). More details regarding the sampling frame and the sample composition were provided elsewhere.25 We solely included respondents with within-variation in fixed effect (FE) regressions.
Subjective Well-Being Functional health was quantified by the subscale “physical functioning” of the 36-Item Short Form Health Survey (SF-3626), ranging from 0 (worst score) to 100 (best score), and mental health was assessed by the Center for Epidemiologic Studies Depression Scale (CES-D27), which consists of 15 items, resulting in a sum score (0e45, with high values indicating worse ratings of mental health). Life satisfaction (CWB) was measured by the Satisfaction with Life Scale (SWLS28) with 5 items on a 5-point rating scale, ranging from 1 to 5 (high values indicate high CWB). Moreover, PA and NA were assessed using the Positive and Negative Affect Schedule (PANAS29), each quantified with 10 items on 5-point rating scales that ranged from 1 (very slightly or not at all) to 5 (extremely). High values indicate high PA or NA.
Independent Variables Individuals were asked if they provide informal care by using the question “Are there people you look after or care for regularly due to their poor state of health, either on a private or volunteer basis?” (no; yes). Self-efficacy was quantified by using the HOPE scale with 8 items,30 ranging from 1 to 4 (high values indicate high self-efficacy). Examples for items of the 4-point HOPE scale are “I can think of many ways to get the things in life that are most important to me”; “There are lots of ways around any problem”; “I meet the goals that I set for myself”; or “I’ve been pretty successful in life” (ranging from 1 ¼ strongly agree to 4 ¼ strongly disagree). Furthermore, we analyzed other time-dependent regressors that were assumed to be relevant for SWB, such as sociodemographic factors,31 social network, and morbidity.32 Age and monthly household net income in Euro (logarithmized) was taken into account. Additionally, the number of important people in regular contact (ranging from 0 to 9) was taken into account. Moreover, morbidity (total number of physical diseases, eg, cardiovascular diseases, diabetes, cancer, respiratory diseases, eye diseases, hearing problems) was used. These conditions were informed by the Charlson Comorbidity Index.33 Additionally, dummy coded variables for region, employment status (Ref.: working; retired; other: not employed), and family status (Ref.: married, living together with spouse; married, living separated from spouse; divorced; widowed; never married) (not shown in regression analysis for the sake of space, but available on request) were added as control variables. For descriptive purposes, the time-constant independent variables sex and education (International Standard Classification of Education [ISCED]34 with 3 categories: low [ISCED 0e2], medium [ISCED 3e4], and high [ISCED 5e6]) were reported at baseline. It is worth mentioning that these variables cannot be included in FE regressions because only time-dependent variables can be included in these regressions, which is described in more detail in the statistical analyses. In sensitivity analysis, informal caregiving was replaced by selfreported average time per week for help/assistance (logarithmized). Statistical Analyses The effect of time-dependent independent variables on SWB was estimated using panel regression techniques enabling us to control for time-invariant unobserved heterogeneity such as optimism or genetic predisposition. This is important in SWB research as, in most cases, unobserved factors are correlated with independent variables in a systematic manner.35 In this case, random effect regression techniques are inconsistent and, hence, FE regressions are the preferred method because they produce consistent estimates (under the assumption of strict exogeneity).36 It is worth noting that FE regressions solely use within-variations over time. Therefore, the FE estimator is also called “within-estimator.” Taking into account heteroscedasticity and serial correlation of the error terms, SEs were computed that cluster errors at the individual level.37 Results Descriptive Analysis At baseline (wave 2), most were male (51.5%) and had a medium education (52.5%) according to ISCED categories. In Table 1, we reported descriptive statistics of time-dependent variables in individuals who reported SWB outcomes in at least 2 waves. At wave 2, mean age was 59.1 years (10.4 years), ranging from 40 to 83 years. Most were married, living together with spouse (78.0%), and still working (44.7%). The monthly household net income was V2987.9
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Table 1 Descriptive Statistics for Time-Dependent Variables Over Time (Waves 2e4) Wave 2, n ¼ 1646 Age, mean (SD) Marital status, n (%) Married, living together with spouse Married, living separated from spouse Divorced Widowed Single Employment status, n (%) Working Retired Other: not employed Monthly household net income in Euro,* mean (SD) No. of important people in regular contact,y mean (SD) Self-efficacy (HOPE Scale),z mean (SD) Morbidity (total no. of physical diseases),x mean (SD) Informal care, n (%) Providing informal care Not providing informal care Functional health (subscale “Physical Functioning” of the SF-36),k mean (SD) Mental health (CES-D),{ mean (SD) CWB (SWLS),** mean (SD) NA,yy mean (SD) PA,zz mean (SD)
59.1 (10.4) 1283 25 134 134 69 736 669 241 2987.9 5.2 3.1 2.2
(78.0) (1.6) (8.1) (8.1) (4.2) (44.7) (40.6) (14.7) (1875.3) (2.5) (0.4) (1.7)
222 (13.5) 1416 (86.5) 88.5 (17.0) 7.1 3.9 2.0 3.5
(5.9) (0.7) (0.5) (0.5)
Wave 3, n ¼ 3044 63.1 (11.1) 2249 40 254 345 158 1082 1599 365 2587.8 4.7 3.0 2.4
(73.8) (1.3) (8.4) (11.3) (5.2) (35.5) (52.5) (12.0) (2447.6) (2.8) (0.4) (1.8)
435 (14.8) 2512 (85.2) 84.9 (19.8) 6.5 3.8 2.1 3.5
(5.4) (0.7) (0.5) (0.5)
Wave 4, n ¼ 3023 65.5 (10.7) 2227 34 249 355 155 958 1752 309 2714.5 5.0 3.0 2.6
(73.7) (1.1) (8.3) (11.8) (5.1) (31.7) (58.0) (10.3) (1715.0) (2.7) (0.4) (1.9)
428 (14.7) 2481 (85.3) 82.7 (21.3) 7.0 3.8 2.1 3.5
(5.8) (0.7) (0.5) (0.5)
Missing values for metric variables (if occurred): *A total of 435 missing values in the second wave, 445 missing values in the third wave, and 261 missing values in the fourth wave. y Seventeen missing values in the second wave, 1 missing value in the third wave. z Forty-one missing values in the second wave, 90 missing values in the third wave, and 100 missing values in the fourth wave. x Forty-three missing values in the second wave, 128 missing values in the third wave, and 144 missing values in the fourth wave. k Seventeen missing values in the second wave, 3 missing values in the third wave, and 13 missing values in the fourth wave. { Ninety-one missing values in the second wave, 89 missing values in the third wave, and 65 missing values in the fourth wave. **Forty-two missing values in the second wave, 90 missing values in the third wave, and 104 missing values in the fourth wave. yy Forty-three missing values in the second wave, 91 missing values in the third wave, and 102 missing values in the fourth wave. zz Forty-three missing values in the second wave, 91 missing values in the third wave, and 102 missing values in the fourth wave.
( V1,875.3). The mean number of important people in regular contact was 5.2 (2.5), and the mean number of physical diseases was 2.2 (1.7). The mean self-efficacy (HOPE scale) was 3.1 (0.4). Most did not provide informal care (86.5%). As for our SWB measures, mean CWB (SWLS) was 3.9 (0.7), mean NA (PANAS) was 2.0 (0.5), mean PA (PANAS) was 3.5 (0.5), mean functional health (Subscale “Physical Functioning” of the SF-36) was 88.5 (17.0) and mean mental health (CES-D) was 7.1 (5.9). After 9 years (wave 4), the proportion of employed individuals decreased to 31.7%. Other variables remained nearly constant. Regression Analysis FE regressions revealed that informal care affected (1) mental health in the total sample (b ¼ 1.0) and in both sexes (men: b ¼ 1.3; women: b ¼ 0.9) and (2) CWB in women (b ¼ 0.1) (Table 2). However, informal care did not affect NA, PA, and functional health in the total sample and in both sexes. The effect of informal care on mental health was moderated by self-efficacy in the total sample (Table 3). FE regressions showed that age (except for PA), morbidity, and self-efficacy affected each dependent variable in total sample and in both sexes. Sensitivity Analysis We checked the robustness (in terms of significance) of our variables of interest by comparing the main model (Table 2) with alternate models (results of model specifications are not shown, but are available on request from the authors). In sensitivity analysis, informal caregiving was replaced by average time per week for help/assistance (logarithmized). Although the effect of caregiving time on CWB also vanished in women, the other findings remained the same in terms of
significance. Thus, caregiving time affected mental health in the total sample and in both sexes, showing that the effect of informal caregiving was insensitive to the measure used. Discussion Main Findings Longitudinal regressions showed that informal care affected (1) mental health in the total sample and in both sexes and (2) CWB in women. The effect of informal care on mental health was moderated by self-efficacy in the total sample. Furthermore, longitudinal regressions revealed that age (except for PA), morbidity, and self-efficacy affected each dependent variable in total sample and in both sexes. Previous Research The association between informal caregiving and SWB is crosssectionally well established. As yet, however, longitudinal studies investigating the effect of informal caregiving on SWB are rare.38,39 For example, Smith et al39 found that increases in caregiving stressors were related to increased caregiver depression, derived from a sample of 310 informal caregivers of elderly care-recipients at baseline (and 213 individuals 1 year later). Even in another study,38 solely informal caregivers were included (130 dementia caregivers at baseline, with 3 assessments at baseline, 3 months later and 1 year later). Thus, our findings extend previous short-term longitudinal findings that mostly focus on individuals providing informal care already at baseline. Consequently, our findings indicate that the occurrence of informal caregiving considerably reduced mental health in the long term, underlining the urgent need for interventions to prevent mental
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Table 2 Longitudinal Predictors of SWB: Results of FE Regressions (Waves 2e4) Variables
CWB
CWB, Men
Age Morbidity Monthly household net income in Euro (log) No. of important people in regular contact Self-efficacy Informal caregiving (Ref.: no) Constant Observations No. of individuals R2
0.0104* (0.00224) 0.0115* (0.00302) 0.00933y (0.00333) 0.00838* (0.00191) 0.00652z (0.00255) 0.0102* (0.00290) 0.00148 (0.00175) 0.0350* (0.00695) 0.0348* (0.00894) 0.0348y (0.0107) 0.0746* (0.00606) 0.0711* (0.00803) 0.0795* (0.00925) 0.0220* (0.00550) 0.106* (0.0303) 0.0958z (0.0399) 0.104z (0.0458) 0.0175 (0.0261) 0.0223 (0.0364) 0.0102 (0.0378) 0.0201 (0.0242)
0.00201 (0.00291) 0.000860 (0.00371)
0.728* (0.0326) 0.0388 (0.0244) 0.181 (0.567) 11263 7922 0.209
0.750* (0.0442) 0.00235 (0.0369) 0.0196 (0.606) 5880 4108 0.236
CWB, Women
NA
0.00272 (0.00460)
0.710* (0.0479) 0.0690z (0.0325) 0.504 (0.412) 5377 3811 0.192
NA, Men
NA, Women
PA
0.00492x (0.00262)
0.00475 (0.00351)
0.00536 (0.00394) 0.00655y (0.00237)
0.317* (0.0278) 0.000811 (0.0197)
0.305* (0.0384) 0.0348 (0.0280)
0.334* (0.0409) 0.0243 (0.0274)
2.871* (0.303) 11264 7922 0.121
3.178* (0.367) 5883 4111 0.124
3.654* (0.414) 5375 3808 0.126
0.490* (0.0262) 0.000800 (0.0187) 1.141* (0.318) 11262 7920 0.165
Beta-coefficients were reported; cluster-robust SEs in parentheses. Regressions are also controlled for family status, employment status, and region. Observations with missing values were dropped (list-wise deletion). * P < .001; yP < .01; zP < .05; xP < .10.
illnesses. On the positive side, it should be noted that informal caregiving did not affect most of the other outcome measures (except for CWB in women). This might be explained by the fact that informal caregiving is also associated with positive effects such as receiving gratitude from the care-recipients, higher self-esteem, meaning in one’s life or personal growth,17 and these positive effects may especially influence the CWB as well as AWB. In sum, these aforementioned effects might compensate for the adverse effects of informal caregiving. Most of the previous studies analyzing the relation between selfefficacy and SWB were based on cross-sectional data. Because, as already stated earlier, it is mandatory to control for unobserved heterogeneity in SWB research,35 longitudinal studies are needed to receive unbiased estimates. Nevertheless, cross-sectional studies clearly confirmed that self-efficacy is associated with SWB40,41 and might moderate the relation between stressors and mental health.22,24 By using a linear mixed model, Romero-Moreno et al.38 found that caregivers’ self-efficacy significantly predicted decreases in depression over time. Our findings also provide empirical evidence for the stress and coping model for caregiving because self-efficacy significantly affected SWB longitudinally. Yet, the interaction between self-efficacy and informal care on mental health have not been examined in a longitudinal approach. In this regard, our findings extend previous knowledge and highlight the importance of selfefficacy in the relation between informal caregiving and mental health. Drawing on the stress and coping model,42 this moderating effect may be explained by the role of self-efficacy in controlling upsetting thoughts (eg, controlling thoughts about negative aspects of informal care) and managing behavioral problems referring to the
ability to respond to disruptive behavior in daily life care (eg, respond to rapid mood swings of the care-recipient).24 Moreover, we would like to emphasize that our findings concerning these longitudinal predictors correspond to previous longitudinal studies.43,44
Strengths and Limitations To our knowledge, this is the first longitudinal study investigating the moderating effect of self-efficacy in the relation between informal caregiving and SWB in older adults in Germany. Additionally, SWB was quantified with validated instruments (eg, CES-D) in a variety of ways (covering functional and mental health, AWB as well as CWB), examining whether the numerous measures of SWB were affected differentially in the long run (2002 to 2011). Moreover, by exploiting longitudinal data, the effect of changes in the independent variables on SWB can be assessed. Additionally, timeinvariant unobserved heterogeneity can be taken into account by using FE regressions. Another point that should be highlighted is that a representative sample of community-dwelling individuals aged 40 and older living in Germany was used. Nevertheless, we cannot rule out that our FE estimates are biased due to reverse causality (eg, AWB affects self-efficacy). Moreover, time spans between our waves were rather long. Thus, short-term changes may be covered for reasons of adaptation processes.45 Furthermore, another limitation is that our estimates might be slightly biased downward due to endogenous selection bias in the German Ageing Survey.46 Moreover, other predictors (eg, satisfaction with leisure time47 or the need for care48) might play a role in the relation between
Table 3 Longitudinal Predictors of Mental Health (With Interaction-Term: Self-Efficacy Informal Caregiving): Results of FE Regressions (Waves 2e4) Variables
Mental Health
Mental Health, Men
Mental Health, Women
Age Morbidity Monthly household net income in Euro (log) Number of important people in regular contact Self-efficacy Informal caregiving (Ref.: no) Self-efficacy Informal caregiving Constant Observations No. of Individuals R2
0.0843* 0.364* 0.266 0.0521 1.713* 5.693z 1.500z 20.59* 11048 7786 0.0386
0.0723z 0.353* 0.328 0.00669 2.130* 4.150 0.917 20.03* 5763 4034 0.0501
0.102z 0.378* 0.198 0.105x 1.296y 6.983z 1.978x 27.26* 5279 3749 0.0410
(0.0243) (0.0734) (0.325) (0.0331) (0.324) (2.395) (0.756) (5.017)
(0.0295) (0.0997) (0.420) (0.0405) (0.467) (2.849) (0.890) (4.851)
(0.0396) (0.110) (0.492) (0.0542) (0.446) (3.463) (1.101) (4.804)
Beta-coefficients were reported; cluster-robust SEs in parentheses. Regressions are also controlled for family status, employment status, and region. Observations with missing values were dropped (list-wise deletion). *P < .001; yP < .01; zP < .05; xP < .10.
A. Hajek, H.-H. König / JAMDA xxx (2015) 1e6
5
PA, Men
PA, Women
Functional Health
Functional Health, Men
Functional Health, Women
Mental Health
Mental Health, Men
Mental Health, Women
0.00148 (0.00238) 0.0178z (0.00714) 0.000887 (0.0353)
0.00478x (0.00257) 0.0250y (0.00845) 0.0415 (0.0339)
0.601* (0.0650) 1.329* (0.204) 0.718 (1.031)
0.611* (0.0905) 1.655* (0.293) 0.853 (1.132)
0.566* (0.0934) 0.971* (0.277) 2.071 (1.742)
0.0832* (0.0243) 0.363* (0.0736) 0.274 (0.323)
0.0719z (0.0295) 0.354* (0.1000) 0.336 (0.419)
0.0996z (0.0396) 0.375* (0.110) 0.198 (0.490)
0.00652z (0.00315)
0.00616x (0.00365)
0.126 (0.0856)
0.112 (0.114)
0.128 (0.126)
0.0520 (0.0331)
0.00737 (0.0404)
0.104x (0.0544)
0.482* (0.0370) 0.00985 (0.0242)
3.624* (0.798) 0.0839 (0.778)
3.824* (1.116) 0.523 (1.158)
3.503y (1.129) 0.404 (1.044)
1.902* (0.328) 1.043* (0.264)
2.218* (0.461) 1.279* (0.376)
103.2* (10.38) 11257 7909 0.0765
107.0* (11.51) 5884 4107 0.111
103.4* (14.72) 5367 3799 0.0557
19.89* (3.641) 11048 7786 0.0367
26.24* (4.493) 5763 4034 0.0494
0.502* (0.0376) 0.00314 (0.0295) 2.226* (0.383) 5881 4109 0.181
1.345* (0.378) 5375 3808 0.159
informal caregiving and SWB. However, due to reasons of data availability, these variables were not included in regression analysis. Conclusions Our findings contribute to the scarce longitudinal evidence regarding the long-term impact of informal care on SWB, covering numerous aspects of subjective well-being (CWB, AWB, as well as functional and mental health), providing support to the stress and coping model for caregiving. Moreover, our findings emphasize the importance of informal caregiving for mental health and CWB (women). Particularly, the former relation can hardly be overemphasized, in terms of both significance and magnitude. Furthermore, given that individuals in need of care prefer to live at home as long as possible, it is most likely that the need for informal care will increase markedly in the next decades due to demographic aging. Therefore, interventions to prevent mental illnesses in informal caregivers are urgently needed. Practitioners as well as policymakers should be aware of these upcoming challenges in the next decades. Respite care (provision of short-term accommodation, typically on a daily or weekly basis) might be helpful to relieve the stress of being a caregiver.49 Moreover, more health promotion interventions might be useful to encourage informal caregivers to use counseling services.50 In turn, these services might have positive effects on their health. Furthermore, the role of self-efficacy in the relation between informal care and mental health can be highlighted. In sum, selfefficacy might be a relevant tool to identify informal caregivers at risk for mental health problems. Additionally, to prevent declines in mental health due to informal care, it might be a fruitful approach to strengthen self-efficacy.51,52 For example, home visits by occupational therapists providing physical, educational, and social environmental modifications53e55 might help to enhance self-efficacy. Furthermore, strengthening coping skills might be important for stressful situations in daily caregiving,56,57 and financial support may help to alleviate the monetary stress of informal caregiving. References 1. Diener E. Subjective well-being. Psychol Bull 1984;95:542e575. 2. Busseri MA, Sadava SW. A review of the tripartite structure of subjective wellbeing: Implications for conceptualization, operationalization, analysis, and synthesis. Pers Soc Psychol Rev 2011;15:290e314. 3. Luhmann M, Hofmann W, Eid M, Lucas RE. Subjective well-being and adaptation to life events: A meta-analysis. J Pers Soc Psychol 2012;102:592e615. 4. Eid M, Diener E. Global judgments of subjective well-being: Situational variability and long-term stability. Soc Ind Res 2004;65:245e277.
1.606* (0.463) 0.894z (0.366) 28.19* (4.790) 5279 3749 0.0374
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