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Aging & Mental Health Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/camh20
Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study a
b
a
a
a
Nathalie Bailly , Kamel Gana , Catherine Hervé , Michèle Joulain & Daniel Alaphilippe a
Department of Psychology, University François Rabelais, Tours, France
b
Department of Psychology, University of Bordeaux, Bordeaux, France Published online: 31 Jan 2014.
To cite this article: Nathalie Bailly, Kamel Gana, Catherine Hervé, Michèle Joulain & Daniel Alaphilippe (2014) Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study, Aging & Mental Health, 18:5, 662-670, DOI: 10.1080/13607863.2013.875121 To link to this article: http://dx.doi.org/10.1080/13607863.2013.875121
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Aging & Mental Health, 2014 Vol. 18, No. 5, 662–670, http://dx.doi.org/10.1080/13607863.2013.875121
Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study Nathalie Baillya*, Kamel Ganab, Catherine Hervea, Michele Joulaina and Daniel Alaphilippea a
Department of Psychology, University Fran¸c ois Rabelais, Tours, France; bDepartment of Psychology, University of Bordeaux, Bordeaux, France
Downloaded by [Queensland University of Technology] at 07:03 31 October 2014
(Received 19 April 2013; accepted 31 July 2013) Objective: The aim of the present study was to investigate the relationship between flexible goal adjustment and life satisfaction (as an enduring component of subjective well-being) using six-year longitudinal data from a sample of older adults. Methods: The study included 704 participants aged 63–97 years assessed four times over a six-year period. Simultaneous and lagged models were specified and estimated using structural equation modeling. Results: Both simultaneous and lagged coefficients indicated that a high score on flexible goal adjustment significantly predicted subsequent levels of life satisfaction. Conclusion: In line with successful aging theory, our findings support the view that the ability to adjust personal goals flexibly is a central resource when unattainable goals are encountered and it contributes to well-being in old age. Keywords: aging; flexible goal adjustment; life satisfaction; longitudinal study
Introduction Adaptation is an important concept that is of particular interest to many researchers in the field of gerontology. Indeed, growing old entails the risks of having to cope with uncontrollable and irreversible losses (bereavement, death of close friends, role losses, etc.) as well as decline in mental and physical functions (Baltes & Lindenberger, 1997; Hay & Diehl, 2010; Herve, Alaphilippe, Bailly, & Joulain, 2010; Hunt, Wisocki, & Yanko, 2003; Li, Lindenberger, Freund, & Baltes, 2001; Wolff, Starfield, & Anderson, 2002). However, despite these challenges, the majority of older adults maintain a positive view of self and life (Diener, Suh, Lucas, & Smith, 1999; Mroczek & Kolarz, 1998). Within this framework, theories of ‘successful aging’ emphasize the importance of maintaining a sense of control over personal development (Baltes & Baltes, 1993; Heckhausen & Dweck, 1998; Rowe & Kahn, 1997). Becoming old has been described as a life task in which individuals have to adjust their goals and aspirations to age-related constraints and restrictions in order to maintain personal continuity (Austin & Vancouver, 1996; Carver & Scheier, 2001; Emmons, 1986). The importance of goal adjustment has been developed in the dual process model of Brandtst€adter and Renner (1990), Brandtst€adter and Rothermund (1994), and Brandtst€adter and Rothermund (2002). They believe that two independent coping modes play an important role in the relationships between functional declines and losses and psychological well-being: the assimilative mode and the accommodative mode. Assimilative tenacity refers to an individual’s tendency to tenaciously pursue goals even in the face of obstacles. In the accommodative mode,
*Corresponding author. Email: [email protected] Ó 2014 Taylor & Francis
goals and ambitions are adjusted to situational constraints. Accommodative flexibility describes a tendency to positively re-interpret initially adverse situations and to relinquish blocked goal perspectives easily. While assimilative activities attempt to ‘solve’ a problem, accommodative processes tend to ‘dissolve’ problems through a readjustment in the individual’s system of preferences. It is important to note that the accommodative mode should not be confused with depression or resignation towards one’s aging. While both assimilative and accommodative modes contribute to successful aging (Brandtst€adter, Wentura, & Rothermund, 1999; Heyl, Wahl, & Mollenkopf, 2007), with age, when goal pursuit exceeds resources, switching from assimilative to accommodative modes helps to regain an overall sense of efficacy: there is a life course gradient to accommodative coping. With age, empirical studies indicate that the accommodative flexibility mode tends to increase and the assimilative tenacity mode tends to decrease (Brandtst€adter & Greve, 1994; Heyl et al., 2007; Niessen, Heinrichs, & Dorr, 2009). Shifts in goals contribute to maintaining a positive balance of gains and losses in later life (Brandtst€adter, 2009; Brandtst€adter & Renner, 1990; Brandtst€adter & Rothermund, 2002). Thus, to age well would imply that people remain flexible in their daily lives so as to adapt to the different challenges linked to advancing age (Piazza, Charles, & Almeida, 2007). The importance of goal adjustment is substantiated by a broad array of findings from questionnaire studies and experiments, as well as from interviews with elderly people. A body of work shows that goal adjustment predicts high levels of well-being in general (Wrosch & Miller,
Downloaded by [Queensland University of Technology] at 07:03 31 October 2014
Aging & Mental Health 2009) and in the face of age-related developmental losses (Brandtst€adter & Renner, 1990; Brandtst€adter & Rothermund, 2002), because it aims to eliminate such discrepancies by adjusting personal goals and preferences rather than by changing the actual situation. More precisely, flexible goal adjustment (FGA) correlates positively with life satisfaction (LS), optimism, sense of control, and low depression in old age (Bailly, Herve, Joulain, & Alaphilippe, 2012a; Boerner, 2004; Brandtst€adter & Renner, 1990; Heyl et al., 2007; Mueller & Kim, 2004; Trepanier, Lapierre, Baillargeon, & Bouffard, 2001). In addition, disposition to the accommodative mode has been found to mitigate the effects of age on depression (Bailly, Joulain, Herve, & Alaphilippe, 2012b; Rothermund & Brandtst€adter, 2003). Such effects have also been demonstrated in relation to bodily handicaps, impaired health, loss of sensory functions, and chronic pain (Boerner, 2004; Heyl et al., 2007; Seltzer, Greenberg, Floyd, & Hong, 2004). Noticeably, the scale of assimilative persistence does not show such buffering effects, although – in terms of bivariate correlations – it is also positively linked to well-being in all age groups. Furthermore, flexible individuals are more likely to interpret their biographical past in self-enhancing ways and to find more positive meaning in losses and set back (Brandtst€adter, Rothermund, Kranz, & K€ uhn, 2010; Brandtst€adter, Wentura, & Greve, 1993; Brandtst€adter et al., 1999; Schmitz, Saile, & Nilges, 1996). Qualitative studies among elderly participants have revealed significant links between the relative frequency of accommodative statements and subjective life quality (Brandtst€adter, Rothermund, & Schmitz, 1997). Participants who expressed accommodative tendencies were more satisfied with their current situation and with their aging, and reported a more positive attitude towards the course of their life in general. In hindsight, they experienced more continuity and found more meaning in their life. In addition, the content analysis of accommodative participants conveys an impression of calm and even perhaps wisdom. At the same time, within the framework of a goal management program Trepanier et al. (2001) focused on how people between 50 and 75 years old pursued personal projects and adapted to retirement. They showed that (1) retirees used flexibility more than tenacity to cope with hurdles met when pursuing personal projects in retirement and (2) the most flexible people reported higher levels of LS and self-esteem and lower levels of depression. On the other hand, tenacity was not found to be significantly linked to LS or depression. Thus, flexibility seems to be a powerful predictor of various subjective well-being (SWB) indicators and helps serious problems to be avoided when goals are unattainable. It enables people to adjust their aspirations, to undertake new projects to replace those which have become impossible to realize (Brandtst€adter & Rothermund, 1994, 2002; Heckhausen, 1997; Rothermundt & Brandtst€adter, 2003; Trepanier et al., 2001). While FGA seems to be an important determinant of aging people’s positive psychological functioning, few studies have investigated the beneficial effects of flexibility over the long term. Yet, identifying predictors of wellbeing could help to identify at-risk individuals early on
663
and provide information to help develop interventions to promote adjustment. The few longitudinal studies conducted on this subject have shown that flexibility is a good short-term and long-term predictor of well-being. In the Wisconsin longitudinal study, Kubicek, Korunda, Raymo, and Hoonnaker (2011) investigated the determinants of well-being in a cohort of retirees with a mean age of 65. Flexibility was found amongst the predictive variables considered. These results indicate that FGA significantly explained the mental health (well-being and depression) of the retirees 11 years later. Their flexibility evaluated in 1993 was positively correlated with wellbeing (r ¼ .35) and negatively correlated with depression (r ¼ .26) evaluated in 2004. Another longitudinal study conducted by Kelly, Wood, and Mansell (2013) investigating a large cohort of people initially aged 55–56 years indicated that highly flexible individuals experienced the greatest decreases in symptoms of depression, hostility, and physical ill-health 10 years later. Other studies have also shown the role of flexibility in quality of life of people who have been hospitalized. In a sample of 64 people aged 18 years and over with major limp amputation, Coffey, Gallagher, Desmond, and Ryall (2013) examined the predictive role of FGA on their quality of life. Measures were taken three times: admission to rehabilitation, six weeks post discharge, and six months post discharge. Results indicated that having strong disposition towards goal adjustment at T1 predicted lower disability and higher environmental quality of life at T3 (Coffey et al., 2013). Finally, in a longitudinal study of stroke patients, Darlington et al. (2009) observed that prior flexibility significantly predicted quality of life 9–12 months later. According to empirical and practical work, we can assume that flexibility in goal adjustment is an important resource for aging people and that flexibility plays a central role in well-being. However, the long-term consequences of flexibility need to be verified. Thus, based on a six-year longitudinal study, we aimed to investigate further the relationships between LS as a component of wellbeing (Diener, Kesebir, & Lucas, 2008) and FGA in old age. We tested two hypothetical models: the first in which FGA would impact on well-being within a single period (simultaneous model) and the second in which prior goal adjustment would predict well-being at latter time points (lagged structural models).
Methods Participants and procedure This research used data from an ongoing longitudinal study on ‘adjustment to retirement’ initiated in 2001 by a team of researchers at the University of Tours, and which follows a non-institutionalized elderly cohort of residents from France (recruited through an advertisement in a specialized journal). The survey was mailed and participants returned the completed questionnaire in a prepaid envelop. Anonymity was ensured by attributing an identification number to each participant. Data collection was performed every two years. On the first assessment in
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2001, the sample of this cohort comprised 906 participants with a mean age of 72.5 years (SD ¼ 5.89, range ¼ 62–95). 1 The data used in this article were collected at four time points2. LS and FGA data were available in 2003 (T1) for 704 participants (56.8% married or had a partner; 57.7% female; mean age ¼ 74.35), in 2005 (T2) for 571 participants (55.8% married or had a partner; 57.7% female, mean age ¼ 76.11), in 2007 (T3) for 530 participants (53.7% married or had a partner; 58.9% female, mean age ¼ 78.37) and in 2009 (T4) for 415 participants (51% married or had a partner; 60% female, mean age ¼ 79.32) (Table 1). The sample (in 2003) included a large proportion of graduates: 39.21% of the participants have attended university and only 0.5% had no educational qualifications. Concerning health evaluation, we used a single-item self-rating of overall health, which asked participants to respond to a question regarding their perceived general health: ‘In general, would you say your health is very poor, poor, fair, good, very good?’ (Benyamini, Idler, Leventhal, & Leventhal, 2000). The answers to this item ranged from 1 (very good) to 5 (very poor). The means of the study variables are presented in Table 1. All the participants lived in their own homes. Refusal, low cognitive performance and death are the common reasons for attrition in prospective studies of older people. However, to investigate the potential impact of attrition, differences in variables used in this study were tested between participants who completed the Time 1 measures and participants who dropped out of the study before Time 4. Participants who dropped out were older (p < .001) and less educated (p ¼ .019) than the others. Concerning FGA and LS, there were no differences in the attrition population. Measures LS was measured using the Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) which consists of five items rated on a 7-point Likert scale ranging from 1 (Strongly disagree) to 7 (Strongly agree). A higher score is indicative of a high level of LS. In the present sample, Cronbach alphas of the LS were .87 at T2, .89 at T3, .86 at T4, and .85 at T5. FGA was assessed using a French version of Brandtst€adter and Renner’s (1990) FGA scale (Bailly et al., 2012a). FGA contains 10 items. Items are rated on a
5-point Likert scale, ranging from 1 (Strongly disagree) to 5 (Strongly agree). High scores on the FGA scale indicate high accommodative flexibility. In the present sample, Cronbach alphas of the FGA were .70 at T2, .68 at T3, .74 at T4, and .74 at T5. Covariates. Sex, marital status (married or living with a partner), education level, and age measured at baseline were introduced as covariates. Participants’ educational attainment was measured with their responses to an item asking them to select the highest level of education they had reached (ranging from ‘Basic schooling’ (1) to University degree (6)). Statistical analyses Structural equation modeling (SEM) with latent variables was employed to investigate the relationships between FGA and LS. We followed the two-stage modeling procedure recommended by Anderson and Gerbing (1988) consisting in establishing the validity of the measurement model before evaluating the structural model. In the first step, we tested the measurement model that defines the relationships between all observed and unobserved study variables. A correlated eight-factor model (M1) and a correlated eight-factor model in which factor loadings of each indicator were constrained to be equal across time (M2) were constructed. Time invariance in factor loadings was required to ensure that the latent variable (LS and FGA) was the same at each time point. Having established measurement models and based on the theoretical framework, the impact of FGA on LS3 was tested. At each time point, the latent variable representing life satisfaction (LS1, LS2, LS3, LS4) and flexible goal adjustment (FLEX1, FLEX2, FLEX3, FLEX4) was specified with indicators. In line with correlational studies which have shown an effect of flexibility on well-being, a simultaneous model where FGA predicts LS within single periods was tested first. In detail, two simultaneous structural equation models were tested as follows: an M3 model where FGA predicts LS within single periods and an M4 model with invariant factor and structural paths. The simultaneous components are presented in Figure 1. Second, to test the long-term effects of flexibility on LS, we tested a lagged structural model where FGA predicts LS at later time points. Two lagged structural models were tested: the M3a model where FGA predicts LS at later time points, and the M4a model with invariant factor
Table 1. Means and (standard deviations) of the study variables. Measures Age Sex (%women) Married or living with a partner (%) Health status LS FGA
Wave 1 (2003) (n ¼ 704)
Wave 2 (2005) (n ¼ 571)
Wave 3 (2007) (n ¼ 530)
Wave 4 (2009) (n ¼ 415)
74.35 (5.71) [63–97] 57.7% 56.8% 2.60 (1.45) 25.49 (5.59) 37.7 (5.02)
76.11 (5.69) [66–101] 57.7% 55.8% 2.23 (1.48) 23.85 (8.83) 37.7 (4.75)
78.37 (5.16) [68–99] 58.9% 53.7% 2.43(1.48) 26 (5.46) 37.5 (4.95)
79.32 (4.99) [70–101] 60% 51% 2.52 (1.69) 25.92 (5.37) 36.70 (4.23)
Note. For self-rated health, a higher score is indicative of poor perceived general health – LS: life satisfaction; FGA: flexible goal adjustment.
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Aging & Mental Health
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Figure 1. Simultaneous effect model of flexibility on life satisfaction. The standardized coefficients displayed were obtained from the Model 4 estimation. LS ¼ life satisfaction; P1–P3 ¼ LS parcels. FLEX ¼ flexibility; P10 –P30 ¼ flexibility parcels. D ¼ disturbance. For clarity, error covariances are not depicted in the diagram. All the factor loadings are significant at p < .001. p< .001.
loadings and structural paths. For the simultaneous and lagged model, we controlled for the effects of age at baseline, sex, and level of education, these variables were included in the models as covariates. The lagged components are presented in Figure 2. The items were also randomly aggregated into three parcels, which were used as indicators of latent variables in the models. Item parceling has the least risk of introducing bias when the construct is measured by congeneric
indicators (Bandalos, 2002; McDonald, 1999). Furthermore, item parcels produce more reliable latent variables than individual items (for item aggregation, see Bagozzi & Edwards, 1998; Coffman & MacCallum, 2005; Little, Cunningham, Shahar, & Widaman, 2002; Nasser-Abu Alhija & Wisenbakern, 2006). Thus, we used a random procedure to create item parcels. The five indicators used to measure the underlying latent construct of LS were parceled into three parcels of items (P1: items 2, 4; P2: items
Figure 2. Lagged structural model of flexibility on life satisfaction. The standardized coefficients displayed were obtained from the Model 4a estimation. LS ¼ life satisfaction; P1–P3 ¼ LS parcels. FLEX ¼ flexibility; P10 –P30 ¼ flexibility parcels. D ¼ disturbance. For clarity, error covariances are not depicted in the diagram. All the factor loadings are significant at p < .001. p< .001.
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Table 2. Goodness-of-fit summary for the models tested in this study.
Measurement models M1 with free factor loadings M2 stability model Simultaneous effects M3: FGA LS M4 : M3 with invariant constraints Lagged effects M3a: FGA LS M4a : M3a with invariant constraints
x2
df
p
TLI
CFI
RMSEA
90% CI of RMSEA
580.89 605.72
320 332
Aging & Mental Health Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/camh20
Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study a
b
a
a
a
Nathalie Bailly , Kamel Gana , Catherine Hervé , Michèle Joulain & Daniel Alaphilippe a
Department of Psychology, University François Rabelais, Tours, France
b
Department of Psychology, University of Bordeaux, Bordeaux, France Published online: 31 Jan 2014.
To cite this article: Nathalie Bailly, Kamel Gana, Catherine Hervé, Michèle Joulain & Daniel Alaphilippe (2014) Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study, Aging & Mental Health, 18:5, 662-670, DOI: 10.1080/13607863.2013.875121 To link to this article: http://dx.doi.org/10.1080/13607863.2013.875121
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Aging & Mental Health, 2014 Vol. 18, No. 5, 662–670, http://dx.doi.org/10.1080/13607863.2013.875121
Does flexible goal adjustment predict life satisfaction in older adults? A six-year longitudinal study Nathalie Baillya*, Kamel Ganab, Catherine Hervea, Michele Joulaina and Daniel Alaphilippea a
Department of Psychology, University Fran¸c ois Rabelais, Tours, France; bDepartment of Psychology, University of Bordeaux, Bordeaux, France
Downloaded by [Queensland University of Technology] at 07:03 31 October 2014
(Received 19 April 2013; accepted 31 July 2013) Objective: The aim of the present study was to investigate the relationship between flexible goal adjustment and life satisfaction (as an enduring component of subjective well-being) using six-year longitudinal data from a sample of older adults. Methods: The study included 704 participants aged 63–97 years assessed four times over a six-year period. Simultaneous and lagged models were specified and estimated using structural equation modeling. Results: Both simultaneous and lagged coefficients indicated that a high score on flexible goal adjustment significantly predicted subsequent levels of life satisfaction. Conclusion: In line with successful aging theory, our findings support the view that the ability to adjust personal goals flexibly is a central resource when unattainable goals are encountered and it contributes to well-being in old age. Keywords: aging; flexible goal adjustment; life satisfaction; longitudinal study
Introduction Adaptation is an important concept that is of particular interest to many researchers in the field of gerontology. Indeed, growing old entails the risks of having to cope with uncontrollable and irreversible losses (bereavement, death of close friends, role losses, etc.) as well as decline in mental and physical functions (Baltes & Lindenberger, 1997; Hay & Diehl, 2010; Herve, Alaphilippe, Bailly, & Joulain, 2010; Hunt, Wisocki, & Yanko, 2003; Li, Lindenberger, Freund, & Baltes, 2001; Wolff, Starfield, & Anderson, 2002). However, despite these challenges, the majority of older adults maintain a positive view of self and life (Diener, Suh, Lucas, & Smith, 1999; Mroczek & Kolarz, 1998). Within this framework, theories of ‘successful aging’ emphasize the importance of maintaining a sense of control over personal development (Baltes & Baltes, 1993; Heckhausen & Dweck, 1998; Rowe & Kahn, 1997). Becoming old has been described as a life task in which individuals have to adjust their goals and aspirations to age-related constraints and restrictions in order to maintain personal continuity (Austin & Vancouver, 1996; Carver & Scheier, 2001; Emmons, 1986). The importance of goal adjustment has been developed in the dual process model of Brandtst€adter and Renner (1990), Brandtst€adter and Rothermund (1994), and Brandtst€adter and Rothermund (2002). They believe that two independent coping modes play an important role in the relationships between functional declines and losses and psychological well-being: the assimilative mode and the accommodative mode. Assimilative tenacity refers to an individual’s tendency to tenaciously pursue goals even in the face of obstacles. In the accommodative mode,
*Corresponding author. Email: [email protected] Ó 2014 Taylor & Francis
goals and ambitions are adjusted to situational constraints. Accommodative flexibility describes a tendency to positively re-interpret initially adverse situations and to relinquish blocked goal perspectives easily. While assimilative activities attempt to ‘solve’ a problem, accommodative processes tend to ‘dissolve’ problems through a readjustment in the individual’s system of preferences. It is important to note that the accommodative mode should not be confused with depression or resignation towards one’s aging. While both assimilative and accommodative modes contribute to successful aging (Brandtst€adter, Wentura, & Rothermund, 1999; Heyl, Wahl, & Mollenkopf, 2007), with age, when goal pursuit exceeds resources, switching from assimilative to accommodative modes helps to regain an overall sense of efficacy: there is a life course gradient to accommodative coping. With age, empirical studies indicate that the accommodative flexibility mode tends to increase and the assimilative tenacity mode tends to decrease (Brandtst€adter & Greve, 1994; Heyl et al., 2007; Niessen, Heinrichs, & Dorr, 2009). Shifts in goals contribute to maintaining a positive balance of gains and losses in later life (Brandtst€adter, 2009; Brandtst€adter & Renner, 1990; Brandtst€adter & Rothermund, 2002). Thus, to age well would imply that people remain flexible in their daily lives so as to adapt to the different challenges linked to advancing age (Piazza, Charles, & Almeida, 2007). The importance of goal adjustment is substantiated by a broad array of findings from questionnaire studies and experiments, as well as from interviews with elderly people. A body of work shows that goal adjustment predicts high levels of well-being in general (Wrosch & Miller,
Downloaded by [Queensland University of Technology] at 07:03 31 October 2014
Aging & Mental Health 2009) and in the face of age-related developmental losses (Brandtst€adter & Renner, 1990; Brandtst€adter & Rothermund, 2002), because it aims to eliminate such discrepancies by adjusting personal goals and preferences rather than by changing the actual situation. More precisely, flexible goal adjustment (FGA) correlates positively with life satisfaction (LS), optimism, sense of control, and low depression in old age (Bailly, Herve, Joulain, & Alaphilippe, 2012a; Boerner, 2004; Brandtst€adter & Renner, 1990; Heyl et al., 2007; Mueller & Kim, 2004; Trepanier, Lapierre, Baillargeon, & Bouffard, 2001). In addition, disposition to the accommodative mode has been found to mitigate the effects of age on depression (Bailly, Joulain, Herve, & Alaphilippe, 2012b; Rothermund & Brandtst€adter, 2003). Such effects have also been demonstrated in relation to bodily handicaps, impaired health, loss of sensory functions, and chronic pain (Boerner, 2004; Heyl et al., 2007; Seltzer, Greenberg, Floyd, & Hong, 2004). Noticeably, the scale of assimilative persistence does not show such buffering effects, although – in terms of bivariate correlations – it is also positively linked to well-being in all age groups. Furthermore, flexible individuals are more likely to interpret their biographical past in self-enhancing ways and to find more positive meaning in losses and set back (Brandtst€adter, Rothermund, Kranz, & K€ uhn, 2010; Brandtst€adter, Wentura, & Greve, 1993; Brandtst€adter et al., 1999; Schmitz, Saile, & Nilges, 1996). Qualitative studies among elderly participants have revealed significant links between the relative frequency of accommodative statements and subjective life quality (Brandtst€adter, Rothermund, & Schmitz, 1997). Participants who expressed accommodative tendencies were more satisfied with their current situation and with their aging, and reported a more positive attitude towards the course of their life in general. In hindsight, they experienced more continuity and found more meaning in their life. In addition, the content analysis of accommodative participants conveys an impression of calm and even perhaps wisdom. At the same time, within the framework of a goal management program Trepanier et al. (2001) focused on how people between 50 and 75 years old pursued personal projects and adapted to retirement. They showed that (1) retirees used flexibility more than tenacity to cope with hurdles met when pursuing personal projects in retirement and (2) the most flexible people reported higher levels of LS and self-esteem and lower levels of depression. On the other hand, tenacity was not found to be significantly linked to LS or depression. Thus, flexibility seems to be a powerful predictor of various subjective well-being (SWB) indicators and helps serious problems to be avoided when goals are unattainable. It enables people to adjust their aspirations, to undertake new projects to replace those which have become impossible to realize (Brandtst€adter & Rothermund, 1994, 2002; Heckhausen, 1997; Rothermundt & Brandtst€adter, 2003; Trepanier et al., 2001). While FGA seems to be an important determinant of aging people’s positive psychological functioning, few studies have investigated the beneficial effects of flexibility over the long term. Yet, identifying predictors of wellbeing could help to identify at-risk individuals early on
663
and provide information to help develop interventions to promote adjustment. The few longitudinal studies conducted on this subject have shown that flexibility is a good short-term and long-term predictor of well-being. In the Wisconsin longitudinal study, Kubicek, Korunda, Raymo, and Hoonnaker (2011) investigated the determinants of well-being in a cohort of retirees with a mean age of 65. Flexibility was found amongst the predictive variables considered. These results indicate that FGA significantly explained the mental health (well-being and depression) of the retirees 11 years later. Their flexibility evaluated in 1993 was positively correlated with wellbeing (r ¼ .35) and negatively correlated with depression (r ¼ .26) evaluated in 2004. Another longitudinal study conducted by Kelly, Wood, and Mansell (2013) investigating a large cohort of people initially aged 55–56 years indicated that highly flexible individuals experienced the greatest decreases in symptoms of depression, hostility, and physical ill-health 10 years later. Other studies have also shown the role of flexibility in quality of life of people who have been hospitalized. In a sample of 64 people aged 18 years and over with major limp amputation, Coffey, Gallagher, Desmond, and Ryall (2013) examined the predictive role of FGA on their quality of life. Measures were taken three times: admission to rehabilitation, six weeks post discharge, and six months post discharge. Results indicated that having strong disposition towards goal adjustment at T1 predicted lower disability and higher environmental quality of life at T3 (Coffey et al., 2013). Finally, in a longitudinal study of stroke patients, Darlington et al. (2009) observed that prior flexibility significantly predicted quality of life 9–12 months later. According to empirical and practical work, we can assume that flexibility in goal adjustment is an important resource for aging people and that flexibility plays a central role in well-being. However, the long-term consequences of flexibility need to be verified. Thus, based on a six-year longitudinal study, we aimed to investigate further the relationships between LS as a component of wellbeing (Diener, Kesebir, & Lucas, 2008) and FGA in old age. We tested two hypothetical models: the first in which FGA would impact on well-being within a single period (simultaneous model) and the second in which prior goal adjustment would predict well-being at latter time points (lagged structural models).
Methods Participants and procedure This research used data from an ongoing longitudinal study on ‘adjustment to retirement’ initiated in 2001 by a team of researchers at the University of Tours, and which follows a non-institutionalized elderly cohort of residents from France (recruited through an advertisement in a specialized journal). The survey was mailed and participants returned the completed questionnaire in a prepaid envelop. Anonymity was ensured by attributing an identification number to each participant. Data collection was performed every two years. On the first assessment in
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2001, the sample of this cohort comprised 906 participants with a mean age of 72.5 years (SD ¼ 5.89, range ¼ 62–95). 1 The data used in this article were collected at four time points2. LS and FGA data were available in 2003 (T1) for 704 participants (56.8% married or had a partner; 57.7% female; mean age ¼ 74.35), in 2005 (T2) for 571 participants (55.8% married or had a partner; 57.7% female, mean age ¼ 76.11), in 2007 (T3) for 530 participants (53.7% married or had a partner; 58.9% female, mean age ¼ 78.37) and in 2009 (T4) for 415 participants (51% married or had a partner; 60% female, mean age ¼ 79.32) (Table 1). The sample (in 2003) included a large proportion of graduates: 39.21% of the participants have attended university and only 0.5% had no educational qualifications. Concerning health evaluation, we used a single-item self-rating of overall health, which asked participants to respond to a question regarding their perceived general health: ‘In general, would you say your health is very poor, poor, fair, good, very good?’ (Benyamini, Idler, Leventhal, & Leventhal, 2000). The answers to this item ranged from 1 (very good) to 5 (very poor). The means of the study variables are presented in Table 1. All the participants lived in their own homes. Refusal, low cognitive performance and death are the common reasons for attrition in prospective studies of older people. However, to investigate the potential impact of attrition, differences in variables used in this study were tested between participants who completed the Time 1 measures and participants who dropped out of the study before Time 4. Participants who dropped out were older (p < .001) and less educated (p ¼ .019) than the others. Concerning FGA and LS, there were no differences in the attrition population. Measures LS was measured using the Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) which consists of five items rated on a 7-point Likert scale ranging from 1 (Strongly disagree) to 7 (Strongly agree). A higher score is indicative of a high level of LS. In the present sample, Cronbach alphas of the LS were .87 at T2, .89 at T3, .86 at T4, and .85 at T5. FGA was assessed using a French version of Brandtst€adter and Renner’s (1990) FGA scale (Bailly et al., 2012a). FGA contains 10 items. Items are rated on a
5-point Likert scale, ranging from 1 (Strongly disagree) to 5 (Strongly agree). High scores on the FGA scale indicate high accommodative flexibility. In the present sample, Cronbach alphas of the FGA were .70 at T2, .68 at T3, .74 at T4, and .74 at T5. Covariates. Sex, marital status (married or living with a partner), education level, and age measured at baseline were introduced as covariates. Participants’ educational attainment was measured with their responses to an item asking them to select the highest level of education they had reached (ranging from ‘Basic schooling’ (1) to University degree (6)). Statistical analyses Structural equation modeling (SEM) with latent variables was employed to investigate the relationships between FGA and LS. We followed the two-stage modeling procedure recommended by Anderson and Gerbing (1988) consisting in establishing the validity of the measurement model before evaluating the structural model. In the first step, we tested the measurement model that defines the relationships between all observed and unobserved study variables. A correlated eight-factor model (M1) and a correlated eight-factor model in which factor loadings of each indicator were constrained to be equal across time (M2) were constructed. Time invariance in factor loadings was required to ensure that the latent variable (LS and FGA) was the same at each time point. Having established measurement models and based on the theoretical framework, the impact of FGA on LS3 was tested. At each time point, the latent variable representing life satisfaction (LS1, LS2, LS3, LS4) and flexible goal adjustment (FLEX1, FLEX2, FLEX3, FLEX4) was specified with indicators. In line with correlational studies which have shown an effect of flexibility on well-being, a simultaneous model where FGA predicts LS within single periods was tested first. In detail, two simultaneous structural equation models were tested as follows: an M3 model where FGA predicts LS within single periods and an M4 model with invariant factor and structural paths. The simultaneous components are presented in Figure 1. Second, to test the long-term effects of flexibility on LS, we tested a lagged structural model where FGA predicts LS at later time points. Two lagged structural models were tested: the M3a model where FGA predicts LS at later time points, and the M4a model with invariant factor
Table 1. Means and (standard deviations) of the study variables. Measures Age Sex (%women) Married or living with a partner (%) Health status LS FGA
Wave 1 (2003) (n ¼ 704)
Wave 2 (2005) (n ¼ 571)
Wave 3 (2007) (n ¼ 530)
Wave 4 (2009) (n ¼ 415)
74.35 (5.71) [63–97] 57.7% 56.8% 2.60 (1.45) 25.49 (5.59) 37.7 (5.02)
76.11 (5.69) [66–101] 57.7% 55.8% 2.23 (1.48) 23.85 (8.83) 37.7 (4.75)
78.37 (5.16) [68–99] 58.9% 53.7% 2.43(1.48) 26 (5.46) 37.5 (4.95)
79.32 (4.99) [70–101] 60% 51% 2.52 (1.69) 25.92 (5.37) 36.70 (4.23)
Note. For self-rated health, a higher score is indicative of poor perceived general health – LS: life satisfaction; FGA: flexible goal adjustment.
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Figure 1. Simultaneous effect model of flexibility on life satisfaction. The standardized coefficients displayed were obtained from the Model 4 estimation. LS ¼ life satisfaction; P1–P3 ¼ LS parcels. FLEX ¼ flexibility; P10 –P30 ¼ flexibility parcels. D ¼ disturbance. For clarity, error covariances are not depicted in the diagram. All the factor loadings are significant at p < .001. p< .001.
loadings and structural paths. For the simultaneous and lagged model, we controlled for the effects of age at baseline, sex, and level of education, these variables were included in the models as covariates. The lagged components are presented in Figure 2. The items were also randomly aggregated into three parcels, which were used as indicators of latent variables in the models. Item parceling has the least risk of introducing bias when the construct is measured by congeneric
indicators (Bandalos, 2002; McDonald, 1999). Furthermore, item parcels produce more reliable latent variables than individual items (for item aggregation, see Bagozzi & Edwards, 1998; Coffman & MacCallum, 2005; Little, Cunningham, Shahar, & Widaman, 2002; Nasser-Abu Alhija & Wisenbakern, 2006). Thus, we used a random procedure to create item parcels. The five indicators used to measure the underlying latent construct of LS were parceled into three parcels of items (P1: items 2, 4; P2: items
Figure 2. Lagged structural model of flexibility on life satisfaction. The standardized coefficients displayed were obtained from the Model 4a estimation. LS ¼ life satisfaction; P1–P3 ¼ LS parcels. FLEX ¼ flexibility; P10 –P30 ¼ flexibility parcels. D ¼ disturbance. For clarity, error covariances are not depicted in the diagram. All the factor loadings are significant at p < .001. p< .001.
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Table 2. Goodness-of-fit summary for the models tested in this study.
Measurement models M1 with free factor loadings M2 stability model Simultaneous effects M3: FGA LS M4 : M3 with invariant constraints Lagged effects M3a: FGA LS M4a : M3a with invariant constraints
x2
df
p
TLI
CFI
RMSEA
90% CI of RMSEA
580.89 605.72
320 332
