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Correspondence: Address correspondence to Christina Bode, University of Twente, Department of Psychology and Communication of Health and Risk, P.O. Box 217, 7500 AE Enschede, The Netherlands. E-mail: c.bode{at}utwente.nl
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Abstract |
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Key Words: Proactive coping • Future self-regulation • Successful aging • Intervention • RCT design • Middle and late adulthood
Despite these findings, there are few educational programs with proven effectiveness that stimulate investment in the future in the third and fourth age. Future investment is approached as behavior that not only focuses on the present life situation but also on the future. Future investment describes behavior that tries to reach positive outcomes and avoid pitfalls. Implemented educational programs for older adults concentrate on specific types of problems that already exist, such as reducing loneliness (Stevens, Martina, & Westerhof, 2006) or depression (Cuijpers, 1998), or coping with a chronic condition (Lorig et al., 1999). These programs operate in a reactive perspective, because they intend to minimize experienced (age-related) losses. In order to stress the potentials of the second half of life, the shift to proactive coping appears useful and the development of related educational programs promising.
We conceptualize proactive coping as the promotion of desired future outcomes and the prevention of undesired changes (Bode, De Ridder, & Bensing, 2006). In this perspective, the participant defines the meaning of desired and undesired changes. The combination of preventing (threatening) losses and striving for improvement can provide a useful framework for promoting successful aging through a deceleration of the unfavorable proportion of losses and gains in later phases of the life span (Baltes, 1997). It is our contention that proactive coping can promote successful aging by stimulating people to invest in their future, focusing on personal growth and the optimization of life in middle and late adulthood.
Until now, proactive coping has been studied as risk management (i.e., preventing losses; Aspinwall & Taylor, 1997) or as goal management (i.e., striving for life improvement; Greenglass, 2003; Schwarzer & Knoll, 2003). In our view, it is the combination of risk management and goal management that makes proactive coping a particularly promising concept with regard to aging. It recognizes possible losses in the process of aging but it simultaneously emphasizes positive development in late life by improving self-regulating capacities. On the basis of this assumption, we developed a brief educational intervention using a group format. The program, titled "In Anticipation of the Golden Years," trains people aged 50 to 75 years in proactive coping competencies and supports them in developing more future-oriented behavior.
In contrast to studies that use proactive coping as a stable disposition (Seibert, Crant, & Kraimer, 1999) or as a mediator construct (Greenglass, 2003), we follow the process model of proactive coping as a set of skills as conceptualized by Aspinwall and Taylor (1997). These authors highlight the potential value of conceptualizing coping as a set of competencies and not just as relatively stable behavioral preferences. Training competencies should be a promising way to improve proactive coping. The process model describes five interrelated tasks of proactive self-regulation: resource accumulation, attention recognition, initial appraisal, preliminary coping, and the use of feedback. The program follows this process model; at the sessions, each topic has been translated into group tasks and individual trajectories, which are as follows: (a) importance of prevention and preparation, (b) identifying and coping with early warning signals, (c) positive future goals and adequate strategies, and (d) use of feedback (see Bode et al., 2006). Our approach differs from existing educational interventions for older adults that are either reactive in their approaches or focus on specific types of problems that the individuals may already experience (Bode et al., 2006; Steverink, Lindenberg, & Slaets, 2005). From an intervention perspective, the proactive and future-oriented approach in combination with self-management techniques is the specific contribution of this new program.
In this article, we address two main issues: whether the program was effective, and whether there are differential program effects with regard to psychological and demographical characteristics of participants and intervention-related characteristics. The criterion for program effectiveness is improvement in proactive coping competencies. We expect these competencies to improve in the experimental group and remain stable at the follow-up measurement, and we expect to observe no changes in the control group.
In addition to the effectiveness of the program, we also investigated the possible positive and negative side effects of participation. With regard to positive side effects, we assumed that, as participants underwent various learning processes, worked through the tasks in the proactive coping model, and experienced behavioral confirmation, their general self-efficacy beliefs (Bandura, 1977) would improve. With regard to negative side effects, the program stimulates older adults to think about the future and their future behaviors by working with anticipated regret (Abraham & Sheeran, 2004). This technique is used in order to stimulate issues high on personal motivation, but it poses the danger of creating threats concerning the future. We assume, however, that a positive reformulation of threats will prevent an increase in worrying and negative mood.
The second research question concerns differential effectiveness of the program, because these results can inform us about the most promising groups for inclusion in subsequent replications of the program. We examined three clusters of possible predictors for the intervention's success: participants' psychological characteristics, demographical characteristics, and intervention-specific attributes. In the first cluster, we examined proactive orientation, preferences in the consideration of future consequences, and subjective well-being. We expected these psychological characteristics to be associated with improvement in proactive competencies, because they outline resources for future-oriented self-regulation. The tendency to worry, however, is expected to compromise the acquisition of proactive skills because people with high levels of worrying might have less emotional and attentional resources to invest in future self-regulation.
Demographic characteristics of participants formed the second predictive cluster. Studies by Ouwehand (2005) suggest that people with more resources should find it easier to acquire proactive competencies than those with fewer resources. Higher levels of education, good health status, and the absence of physical limitations reflect a higher level of resources. We also explored age, gender, marital status, and current occupational situation as predictor variables, because they represent status on central domains of life that might facilitate or hinder the acquisition of competencies.
The final cluster of predictors consists of intervention-specific variables that might influence the effectiveness of the program by facilitating the development of relevant competencies. These include the older adults' participation rate, the perceived importance of their individual goals, their success in formulating the goal in concrete and achievable terms, and finally whether they achieved their goal.
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Program Description
The program consisted of four 2-hour sessions with 8 to 10 participants. Trainers with professional backgrounds as nurses, occupational therapists, and psychologists used a standard protocol (Bode & de Ridder, 2004); we selected them on the basis of their age (50+) and experience with teaching. They were intensively trained for 20 hours on an individual basis.
In the first session, trainers helped participants to identify the advantages of preparing oneself for the future. In the homework assignment, participants were asked to write down signals warning them that things in their life were going in the wrong direction. The assignment required them to anticipate topics about which they would have regrets in 5 years if they did not work on them now (Abraham & Sheeran, 2004).
In the second session, trainers discussed with participants the recognition and handling of early warning signals in the process of aging, and they helped them to identify proactive ways of coping with warning signals. Furthermore, participants selected one personal future goal from the homework on anticipated regret. Participants worked on this goal during the following 2 weeks (the individual trajectory).
In the third meeting, trainers helped participants specify strategies to reach their personal goal by the use of the technique of mental simulation. According to Taylor, Pham, Rivkin, and Armor (1998), mental simulation involving the initiation and maintenance of problem-solving activities produces progress in achieving those goals. In our program, the technique of mental simulation served as a means of virtually practicing skills that facilitate proactive activities. Using a structured protocol induced by the trainer, the participants imagined two alternative ways for attaining the desired state. After the mental simulation, everyone decided which action he or she would try out in reality to achieve the personal goal.
In the last session, participants evaluated the attempts to reach the individual goal. In addition, the trainers discussed the productive use of feedback, because of the importance this feedback has in the process model of proactive coping. Participants examined the increase in knowledge about their own potential, the supportive or hindering function of their environment, and the attainability of their goals and plans. The program ended with a general evaluation.
The attendance rate was very good: 62 (73%) of participants attended all four meetings, 20 (24%) participated three times, and only 2 individuals missed two sessions.
Participants
In Figure 1 the flow of participants through each stage of the study is described. Before baseline measurement, we allocated a total of 178 individuals to the experimental or control group by way of consecutive admission. Between randomization and baseline measurement, 20 participants dropped out. The primary reasons given were that they felt too young and did not want to participate in research after all. During the study, the experimental group was reduced from 84 at T0 to 71 at T2, mainly because of health- and work-related reasons. The control group began with 74 persons; at T2, 60 participants returned the third questionnaire. The main reason for dropout was refusal to continue research participation. Our analyses of participants who dropped out revealed that dropout was independent of assignment to experimental or control group, 
2(158,1) = 0.33; p =.56, and individuals who dropped out did not differ on demographic characteristics from those who returned all three questionnaires [gender, 2(158,1) = 0.25, p =.616; marital status, 2(155,4) = 4.29, p =.37; employment status, 2(156,2) = 0.16, p =.92; age, F(158,1) = 0.45, p =.50; subjective health, F(155,1) = 1.85, p =.18], except for their educational status. Participants with 10 to 13 years of education dropped out more often than people with 14 or more years of education [2(156,3) = 8.5, p =.04].
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= 0.77), such as "When I set important goals for myself, I rarely achieve them," with response categories ranging from 1 (I never do so) to 6 (I do so very often). We recoded this scale with higher values meaning higher self-efficacy.
In order to measure participants' tendency to worry, we administered the Penn State Worry Questionnaire (Molina & Borkovec, 1994), for which there was high reliability (Cronbach's = 0.94). The 16 items (e.g., "I am always worrying about something," with a 5-point format, from not at all typical to very typical) assess a clinically significant tendency to worry without regard to specific topics, and high values mean a high tendency to worry.
To measure negative mood, we used the Tension subscale of the Profile of Mood States (Wald & Mellenbergh, 1990). Participants assessed how they felt over the past few days, using a list of six adjectives. Responses categories ranged from 1 (not at all) to 5 (very much; Cronbach's = 0.88).
Predictor Variables for Differential Effects
We measured proactive coping orientation by using the Preventive Coping subscale from the Proactive Coping Inventory (Greenglass, 2003). This subscale (Cronbach's = 0.84) deals with the anticipation of potential stressors and the initiation of preparation before these stressors fully develop. The original scale contains 10 items; we omitted the single item on developing job skills, as we deemed this question to be irrelevant for the participants. Sample items are "I think ahead to avoid dangerous situations" and "I plan for future eventualities," and answer categories ranged from 1 (I never do so) to 6 (I do so very often).
The Consideration of Future Consequences Scale (Strathman, Gleicher, Boninger, & Edwards, 1994) measures the extent to which people consider distant versus immediate consequences of potential behaviors. It includes 12 items, such as "I only act to satisfy immediate concerns, figuring the future will take care of itself" and the answer categories range from 1 (extremely characteristic) to 5 (extremely uncharacteristic). High values reflect the tendency of a person to consider future consequences (Cronbach's a = 0.80).
To measure subjective well-being, we used the short version of the Subjective Well-Being Scale for the Elderly (van Linschoten, Gerritsen, & Romijn, 1993). The eight items cover subjective well-being with regard to health, social contacts, self-esteem, positive affects, and negative affects; response categories range from 1 to 3 (Cronbach's = 0.81). We recoded this scale so that high values represent high levels of subjective well-being.
We collected all measures at T0, T1, and T2. In addition, at T0, participants answered questions about their age, gender, marital status, current employment situation, and highest educational status. Furthermore, participants evaluated their health status on a 5-point scale (very good to very bad), to give an appraisal of their physical limitations (not at all limited to very limited), and to evaluate their fitness (fit, rather fit, or not fit). At T1, participants in the experimental group reported how many sessions they attended and how important their personal goals were (not important, more or less important, or important). They reported whether they were able to formulate their personal goals in concrete (yes or no) and achievable (yes or no) terms, and whether they finally achieved their goals (yes–more or less–no).
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Results |
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In order to examine differential effectiveness, we further analyzed the intervention effects in the experimental group. We examined the predictive value of three variable groups: psychological and demographic characteristics at baseline, and program specific characteristics at T1.
Table 5 shows the hierarchical regression analyses for the psychological characteristics. All dependent variables were best predicted by their pretest value. In addition, participants with lower levels of well-being at T0 had a better chance of increasing their feedback skills at T1. The realistic goal setting competency at T2 could be predicted by high levels of proactive orientation and low levels in considering the future consequences of one's own behavior. The increase in the future appraisal competency at follow-up could be predicted by high levels of proactive orientation.
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The final regression analyses examined whether intervention-specific variables predicted the outcome measures at T1 and T2 (Table 6). For two of the four proactive competencies, intervention-specific characteristics had a significant predictive value in addition to the pretest value of the relevant variable (Table 6). Participants who succeeded in formulating the personal goal in concrete terms reported a significant increase in the following competencies: realistic goal setting, future appraisal, and use of resources. There was no additional value of intervention-specific characteristics in predicting the follow-up measurement.
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Discussion |
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In the final analyses, we investigated differential effects in the experimental group. We expected three clusters of variables to contribute to the prediction of intervention effects. Demographic characteristics had no predictive value. This result is surprising, because we expected that people with more resources would be able to invest more in proactive coping. It might reflect the easy accessibility of the program and shows that all participating age groups can profit from the intervention. Psychological characteristics predicted one post-test and several follow-up effects on proactive competencies. We expected the result that proactive orientation facilitated improvement of proactive competencies, because it should lessen participants' doubts about developing proactive competencies. The effect with regard to the consideration of future consequences variable was unexpected; higher levels at baseline predicted lower improvement of the realistic goal setting competency at follow-up. It could be that people who scored higher on this scale were overly optimistic about their proactive competencies before the program. Confrontation during the program could cause people to scale back their self-evaluation to realistic proportions, leading them to report lower levels of competencies after the program. An examination with then-test methodology would clarify this postulated response shift (Schwartz, Sprangers, Carey, & Reed, 2004).
Regarding intervention-specific characteristics, we found that only the concrete formulation of the individual goal facilitated improvement of proactive competencies. The concrete formulation of goals seems to be the necessary starting point for improving goal-setting skills such as finding solutions, maintaining goal attendance, and finding alternatives if one solution does not work. The concrete formulation also might serve as anchor point for the appraisal of future changes. In sum, the analyses of differential effectiveness give relatively few hints for offering the program to specific groups. In our view, these findings support the strategy to work with heterogeneous groups and to make the program easily accessible.
Finally, some methodological considerations should be mentioned. This study employed a prospective randomized control trial design, and we had acceptable dropout rates. These characteristics, together with the use of highly reliable instruments, suggest that the results of this investigation are valid.
A point for improvement in future studies is that not all outcome variables should be based on self-report because the effects of social desirability cannot be ruled out. Observational data might offer an alternative solution because they involve observable behavior, and thus applied competencies. However, observation has other inaccuracy problems and involves considerably more time and effort. Another option might be a reality test of proactive competencies, for example, by asking participants to give advice to someone else preparing for aging, bearing the proactive coping principles in mind. A similar thinking-aloud method was developed for investigating wisdom (Baltes & Staudinger, 2000).
In this study, we presented effects on the outcome measures that focus on improvement of competencies. We believe that, in the long run, an increase in proactive coping competencies will support successful aging. Therefore, we plan additional research on outcomes that will concentrate on long-term improvements in the personal experience of aging as well as subjective and psychological well-being.
To conclude, in the present study we found that an educational program based on proactive coping theory improved proactive competencies. Three months after the intervention was finished, we found that these results remained stable. As a result of these particularly positive effects and the lack of negative side effects, the "In Anticipation of the Golden Years" program has been integrated in the regular program of the participating health service institutes, and we are now planning a national implementation of the program.
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1 Department of Health Psychology, Utrecht University, The Netherlands.
2 Department of Psychology and Communication of Health and Risk, University of Twente, Enschede, The Netherlands.
Decision Editor: Linda S. Noelker, PhD
Received for publication November 7, 2005. Accepted for publication September 19, 2006.
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