Engagement in Adulthood: Perceptions and Participation in Daily Activities

Abstract

The present research explores how older adults experience daily activities through an application of the Day Reconstruction Method (Kahneman, Kreuger, Schakade, Schwartz, & Stone, 2004). Over the course of the day, individuals (N = 192, M = 72 years) spent an average of 14.50 hours engaged in a variety of activities. Individual differences in activity patterns could be partly explained by age and educational attainment. The oldest individuals (81-92 years) perceived lower levels of competence when engaging in daily activities. Regardless of age, however, individuals with greater educational attainment allocated more time and felt more intellectually challenged in their daily experiences.

There is substantial inter-individual variability in patterns of activity over the lifespan, with some individuals focusing their efforts on a narrow range of activities and others engaging in a wide range of activity domains (Agahi, Ahacic, & Parker, 2006; Kelly, 1993). In choosing whether or not to participate in certain activities, consideration is given to the level of interest, ability, and enjoyment associated with specific leisure pursuits (Kelly, 1993, 1996,). Individual characteristics such as age, education, and social and emotional goals may also influence the type of activity in which an individual participates (Kelly, 1996; Nilsson, Lofgren, Fisher, & Bernspang, 2006; Verbrugge, Gruber-Baldini, & Fozard, 1996). Therefore, the present investigation considers how individual characteristics influence perceptions and participation in daily experiences.

Research examining activity patterns generally suggest that there is much lifespan continuity in patterns of engagement; however, there are also patterns of change (Agahi et al., 2006; Iso-Ahola, Jackson, & Dunn, 1994; Kelly, 1996; Strain, Grabusic, Searle, & Dunn, 2002). Older adults report spending fewer hours participating in clubs and organizations, using a computer, supervising activities of others, socializing with friends, teaching or attending classes, writing, and engaging in musical or other artistic activities and spend more hours watching television, reading newspapers or magazines, and participating in various hobbies (Iso-Ahola et al., 1994; Paillard-Borg, Wang, Winblad, & Fratiglioni, 2009; Salthouse, Berish, & Miles, 2002; Strain et al., 2002; Verbrugge et al., 1996). As many older adults continue to pursue an engaged lifestyle, it may be that individuals modify activities in a manner that allows for continued participation (Baltes, 1997). It is also possible that adults become more selective in activities as cognitive and physical resources decline, thus conserving energy for continued participation in activities essential for daily living (Baltes & Baltes, 1990). Consistent with this view are findings suggesting that participation in more essential activities (i.e., domestic pursuits, self-maintenance) continues with increasing age, however, older adults have significantly lower levels of intentions to engage in optional activities in the future (Rousseau, Pushkar, & Reis, 2005).

With increased age, there is also a shift in goals, motivations, and priorities. Particularly, the regulation of emotion becomes increasingly salient over the life course, while the goal of receiving novel information becomes less important (Carstensen, 1995). This shift may partly explain why older people seem to be less drawn to novelty (e.g., Agahi et al., 2006; Iso-Ahola et al., 1994), yet have an increased preference for activities that engender pleasure and hold the most importance in their lives (e.g., Nilsson et al., 2006; Rousseau et al., 2005). Therefore, goals and motivations may influence participation in activities, so as to maximize the enjoyment and allocation of resources to more meaningful or pleasurable activities.

As engagement in leisure pursuits is highly goal relevant, activities may be chosen because they produce a desired (or minimize an undesired) affective state (Goodwin, Intrieri, & Papini, 2005). Unfortunately, relatively few studies have examined the affective component of involvement in specific activities. In one such study, Lawton (1994) found that positive affect and mastery were associated with greater participation in senior centers, clubs, movies/concerts, gardening, hobbies, eating out, and volunteer work. It has also been suggested that older adults, particularly the less educated, are reluctant to engage in activities, such as art, music, and writing, partly due to feelings of incompetence (Atchley, 2000). Together, these findings suggest that individuals who view themselves as more capable and consider an activity as more enjoyable are also more likely to select and maintain participation in a variety of social and intellectual activities (Rousseau et al., 2005). Therefore, if an individual does not expect success in an activity, as a result, less participation may occur (Bandura, 1982). Although competence may affect initial selection of activities, it is also possible that the amount of success achieved through participation may affect self-perceptions of competence, either facilitating or hindering subsequent performance (Lachman, 2006).

Early educational experiences or other social learning opportunities may provide the knowledge, skills, and competencies necessary for participation in a certain activity, thereby establishing lifelong patterns of engagement. Research indicates that older adults with higher levels of educational attainment tend to be more active and engage in a wider variety of activities (Hultsch, Hammer, & Small, 1993; Paillard-Borg et al., 2009; Strain et al., 2002), including those that are cognitively demanding (Wilson et al., 1999). For instance, Aartsen and colleagues (2002) found that experiential (e.g., visiting a cultural institution) and developmental activities (e.g., attending an educational course) were more prevalent among highly educated individuals. Conversely, research has also found that television viewing is more prevalent among individuals with lower educational attainment (Wilson, Bennett, Gilley, Beckett, Barnes, & Evans, 2000). Moreover, educational differences have been observed for the type of television program selected. For example, the favorite television category among less educated individuals was soap operas, whereas highly educated individuals selected the news, nature shows, mysteries, or comedies as their favorite category (Fogel & Carlson, 2006). Although highly educated individuals may be more likely to select and perform activities that are typically thought of as intellectually challenging, it is possible that educational experiences provide the skills and competencies to modify any activity so as to create complexity in otherwise simple environments.

From the preceding discussion it becomes evident that individual differences in chronological age, motivational goals, perceived ability, and educational experiences may affect the subjective interpretation and evaluation of activities, as well as the extent and nature of participation. Unfortunately, prior studies have mostly focused on behavioral participation or time allocation to specific activities, neglecting the importance of the subjective perception of daily experiences as a predictor of engagement in adulthood. Although findings from such studies have tremendously increased our knowledge of activity patterns, research involving more comprehensive approaches may help increase the quality and completeness of previous reports.

The present study explores daily experiences through an application of the Day Reconstruction Method (DRM; Kahneman et al., 2004), which has heretofore not previously been used to understand age differences in activity. The DRM builds on the strengths of diary approaches (Juster & Stafford, 1985; Robinson & Godbey, 1997) and experience sampling techniques (Stone, Shiffman, & DeVries, 1999). As a methodological tool, the DRM offers many key benefits, such as the joint assessment of the perceptions and performance of activities, information about the duration and frequency of each experience, lower respondent burden, and high flexibility in adapting the content of the instrument to the needs of the specific study. Studies have indicated a close correspondence between the DRM and established results from experience sampling (Kahneman et al., 2004).

Method

Participants

Community-dwelling adults at least 60 years of age were recruited for the current study through posted advertisements in a community newspaper and flyers displayed in various locations around the community (e.g., medical clinics, recreation centers, and local shops). Additionally, recruitment letters were mailed to eligible participants in an existing laboratory data pool.

Participants were screened for eligibility through a telephone interview and an assessment of independent Activities of Daily Living (ADL; Lawton & Brody, 1969). To be eligible for participation, individuals had to (a) be able to perform basic daily tasks with no assistance (indicated by an ADL score of 16), (b) not reside in residential retirement communities, as these individuals may have different opportunities for engagement, (c) be retired or only work part-time, so that they would be able to record activities for a non-working day, (d) be free of conditions that would impair reading or writing (e.g., severe arthritis in hands, macular degeneration), and (e) not have been diagnosed with Alzheimer’s disease or other debilitating dementias (self-reported) that would limit the ability to recall experiences of the previous day.

On the basis of selection criteria in the present study, one interested individual was excluded from participation because she required a great deal of assistance with tasks of daily functioning. Additionally, two interested older adults residing in residential senior housing communities were excluded from participation.

The final sample consisted of 192 participants. Individuals ranged in age from 60 to 92 years (M = 71.8 years; SD = 7.2; median = 71.0 years) and had an average of 16 years of formal education (e.g., equivalent of a bachelor’s degree). The majority of participants were retired¹ (86.5%), female (65.1%), Caucasian (99.0%), and were very satisfied or satisfied with their health (77.6%).

Day Reconstruction Method

The Day Reconstruction Method (DRM; Kahneman et al., 2004) was administered as a structured, self-administered questionnaire to assess how people spend their time and experience the various activities of their lives. The first section asked participants to construct a short diary of the previous day to support accurate retrieval on a subsequent response form. This diary did not have to be returned for analysis, thus allowing for the use idiosyncratic notes and details they would rather not share. The second section consisted of structured questions about their daily activities (see Appendix for sample questions). Individuals were asked to parse their day in a series of discrete episodes without receiving instructions on how fine-grained these blocks of time should be (e.g., every 15 minutes vs. 2 hour segments), therefore, the total number of episodes varied for each individual. For each episode, individuals were presented with a checklist of 22 predetermined activities and asked to record any activity in which they were engaged within the specified time frame, as well as an opportunity to report other activities not included on the list. The majority of activities were taken from the existing DRM measure, however, modifications were made to capture activities of interest and increase the appropriateness of the measure for use with older adults. For instance, the activity of “taking care of my children” was replaced with “taking care of children.” Additionally, seven activities were included to reflect activities commonly reported among older adults: writing letters or e-mail, volunteering, clubs/organizations, reading, playing games, hobbies, and self-care (e.g., personal hygiene).

Participants were then asked to rate each episode on twenty-one experiential descriptors on a scale from 0 (not at all) to 6 (very much). Twelve descriptors (i.e., impatient for it to end, competent, happy, hassled, warm, angry, depressed, worried, enjoying myself, frustrated, criticized, tired) were taken from the existing DRM measure. Nine additional descriptors (i.e., intellectually challenged, put forth effort, made a contribution, in control, felt like time flew by, bored, attention was focused, rewarding experience, did it automatically) were included as they reflected domains of particular interest and relevance to the current study. The last section of the DRM collected additional descriptive information (e.g., typicality of the reported day, satisfaction with health).

For analyses, behavioral participation in activities was defined in three ways: total duration of time spent in activities (in hours), total number of activities, and number of unique (diverse) activities. Additionally, data were collapsed across selected descriptors within each episode to obtain mean ratings for positive affect (i.e., happy, warm/friendly, enjoying myself, rewarding experience; α = .91), negative affect (i.e., hassled/pushed around, depressed/blue, impatient for it to end, bored, frustrated/annoyed, angry/hostile, worried/anxious, criticized/put down; α = .89), effortful allocation (i.e., attention was focused, put forth effort; α = .80), and competence (i.e., competent/capable, in control; α = .87). Intellectual challenge was considered separately. For each experiential dimension, ratings were averaged across episodes to provide a mean experience rating over the course of the day.²

Procedures

Data were collected as part of a larger investigation of engagement-cognition relations in adulthood (Parisi, 2007). Participants were mailed the DRM and instructed to complete the assessment at home and return the packet to the laboratory. To better characterize activities that were performed on a typical weekday, data collection was restricted to activities that were completed on a Monday (21.9%), Tuesday (24.0%), Wednesday (22.4%), Thursday (16.7%), or Friday (11.5%) (value in parentheses represents the percentage of individuals who responded for that day of the week). Because individuals were asked to provide information for a single day of activities, an item was included that asked how typical the reported day was compared to past weeks. The majority of participants (69.3%) reported that the reported day was typical for them. Other participants reported that the day was much worse (2.1%), somewhat worse (10.4%), somewhat better (12.5%), and much better (5.2%) than past weeks. Although two participants recalled activities completed on a Sunday (1.0%) they reported that it was a typical day and, therefore, were not removed from analysis.

Results and Discussion

Patterns of Engagement

The first goal was to describe the daily activities of older adults in terms of episodes, activity, and subjective experience (Table 1). On average, participants reported a total of 12.96 (SD = 3.91; range 5 to 24) episodes, with each episode lasting approximately 1.24 hours (SD = 0.48). In addition, individuals spent an average of 14.50 hours (SD = 1.90; range 7.50 to 18.75 hours) in 22.24 activities (SD = 8.25; range 5 to 56) over the course of one day. Averaged across episodes, daily experiences were associated with higher levels of positive affect (M = 3.84; SD = 1.19) than negative affect (M = 0.65; SD = 1.00), t(190) = 30.04, p < .001. Furthermore, individuals typically associated their daily activities with low levels of intellectual challenge (M = 1.77; SD = 1.19) and moderate levels of effortful allocation (M = 3.56; SD = 1.16) and competence (M = 3.98; SD = 1.38).

Table 1.

Episodes, Activity, and Experiential Ratings

	Overall
	M	SD
Episodes
Total number of episodes reported	12.96	3.91
Average length of episode (hours)	1.24	0.48
Average activities reported per episode	1.77	0.61
Activity
Total duration of time in activities (hours)	14.50	1.90
Total number of activities	22.24	8.25
Number of unique activities	10.86	2.56
Affect
Intellectual challenge	1.77	1.19
Positive affect	3.84	1.19
Negative affect	0.65	1.00
Effortful allocation	3.56	1.16
Competence	3.98	1.38

Relationships were found among the ratings for experiential descriptors such that individuals who felt more intellectually challenged reported higher levels of positive affect (r = .32), put forth more effort (r = .44), and felt more competent (r = .29) (ps < .05). Similarly, competence was strongly associated with both positive ratings (r = .74) and effortful allocation (r = .75) (ps < .01). In other words, individuals who feel competent in daily activities tend to enjoy them more, as well as put forth more effort during participation. Ratings of intellectual challenge significantly differed from both effortful allocation, t(185) = 19.31, and competence ratings, t(185) = 19.38 (ps < .001), suggesting that an individual’s perceived levels of competence (e.g., skill and ability) and effort outweighs their level of perceived challenge in daily experiences (see Voelkl & Ellis, 1998).

To capture a more detailed portrait of individuals’ experiences over the course of the day, Table 2 shows the mean ratings on experiential descriptors for particular activities (center columns), as well as the proportion of respondents who reported that they participated in at least one instance of the activity throughout the day (far right column). Overall, the most frequently reported activities were essential daily activities (e.g., eating, self-care, preparing food), watching television, reading, and socializing, while the least frequently reported were intimate relations and taking care of children. Participants perceived games, clubs/organizations, and computer/internet to be the most intellectually challenging, however, the majority of activities did not elicit high levels of intellectual simulation. Individuals allocated the most effort (i.e., attention was focused, put forth effort) when volunteering, taking care of children, and exercising; whereas, the lowest amounts of effort were allocated to basic daily functioning (eating, napping, self-care) and watching television. Additionally, individuals reported moderate to high levels of positive affect and competence for the majority of activities indicated, suggesting that individuals may select activities that are enjoyable and match their skills, knowledge, and level of ability.

Table 2.

Mean Experiential Ratings for Activities for Full Sample

	Mean Experiential Rating
Activities	Intellectual challenge	Positive	Effort	Competent	Proportion of sample reporting
Eating	1.35	4.01	2.14	3.85	0.98
Watching TV	1.79	3.68	2.98	3.40	0.87
Reading	2.32	3.90	3.47	3.78	0.80
Self-care	0.79	3.30	3.04	3.91	0.79
Preparing food	1.16	3.83	3.33	4.05	0.72
Socializing	2.07	4.66	3.80	3.84	0.72
Housework	1.06	3.36	3.51	4.06	0.56
Talking on phone	1.78	4.15	3.71	3.88	0.51
Nap/resting	0.91	3.38	1.88	2.94	0.49
Computer/internet	3.11	3.82	4.25	4.12	0.48
Shopping	1.12	3.82	3.68	4.18	0.47
Commuting	1.02	3.66	3.52	4.14	0.46
Exercising	1.07	4.24	4.74	4.36	0.39
Writing/e-mail	2.62	3.84	4.09	4.30	0.35
Working	2.45	3.81	4.44	4.49	0.35
Games	3.83	4.17	4.23	4.18	0.34
Praying/mediating	1.83	4.26	3.77	3.97	0.21
Hobbies	2.74	4.57	4.32	4.30	0.18
Volunteering	1.90	4.52	4.54	4.44	0.16
Clubs/organizations	3.73	4.65	4.43	4.59	0.11
Gardening	1.00	3.99	3.94	4.30	0.11
Intimate relations	0.67	5.00	3.42	3.00	0.03
Taking care of children	2.70	4.99	4.55	4.50	0.03

Note. Positive affect is the average of happy, warm/friendly, enjoying myself, and rewarding experience; effortful allocation is the average of attention was focused and put forth effort; and competence is the average of competent/capable and in control. Affective ratings were based on a 7-point scale (0 = not at all; 6 = very much).

Does Engagement Vary With Age or Education?

As activity patterns may vary as a function of personal characteristics or experiences, responses were separately examined for age and educational attainment.³

Patterns of Engagement as a Function of Age

To characterize the frequency of engaging in various activities, as well as how the perceived experiences of participation changes with age, activity patterns were examined within four age cohorts (60-66, 67-73, 74-80, 81-92 years). One-way analysis of variance (ANOVA) on each variable revealed that there was no significant differences between age groups for the total number of episodes, F(3, 191) = 0.43; total duration of time spent in activities, F(3, 191) = 1.21; the total number of activities, F(3, 191) = 0.20; or the number of unique activities reported, F(3, 191) = 1.43 (ps > .05).

Likewise, a comparison of the four age cohorts revealed no significant differences among age groups for the perceived level of intellectual challenge, F(3, 185) = 0.13; positive affect, F(3, 190) = 2.07; negative affect, F(3, 190) = 2.05; or effortful allocation, F(3, 189) = 1.91 (ps > .05). In other words, adults were similar in how they evaluated the inherent enjoyment and effort associated with activities. An interesting exception was that the oldest adults (81-92 years) perceived lower levels of competence when compared with their younger counterparts (60-66 years) [F(3, 189) = 3.12, p < .05; M_{60-66 years} = 4.26, M_{81-92 years} = 3.37].

In terms of specific activities, older adults did report reduced participation in commuting, χ²(3) = 9.28, p < .05; exercise, χ²(3) = 7.91, p < .05; and working, χ²(3) = 7.30, p < .10. Interestingly, when compared with the youngest group (60-66 years), the oldest adults (81-92 years) also reported lower levels of positive affect for these activities: commuting, F(3, 83) = 3.23; working, F(3, 63) = 2.78; and exercising, F(3, 70) = 3.12 (ps < .05).

Although declines in cognitive and physical ability may limit participation in late life, the oldest adults reported participating in activities to the same extent as the young-old adults. As individuals age, however, they may become increasingly aware of these declines, which may partially account for lowered levels of perceived competence when performing daily activities. In turn, older adults may allocate less effort as a means to help sustain participation in activities.

Patterns of Engagement as a Function of Educational Attainment

Other individual difference factors, such as education, may account for some of the variability in engagement patterns in adulthood. Univariate analyses revealed that individuals (n = 87) with less than the equivalent of a bachelors degree (less than 16 years), differed from those with higher levels of educational attainment (16 or more years; n = 105) in terms of the number of episodes reported (M _{low educ} = 12.09, M _{high educ} = 13.68), t(190) = 2.85; and in the total duration of time spent in activities (M _{low educ} = 14.03, M _{high educ} = 14.88), t(189) = 3.16. With respect to affective ratings, there was a significant difference in terms of intellectual challenge, (M _{low educ} = 1.43, M _{high educ} = 2.04), t(189) = 3.55, with individuals with a lower level of educational attainment perceiving less intellectual challenge resulting from their daily activities. Individuals differing in level of education did not differ in ratings of perceived positive affect, t(189) = 0.89; effortful allocation, t(189) = 1.40; or competence, t(189) = 0.06, over the course of the day.

Individuals with more years of formal education reported greater participation in writing/e-mail (χ²(1) = 3.10, p < .10), which may be related to their more frequent computer use (χ²(1) = 7.03, p < .01). Additionally, participation in exercise (χ²(1) = 13.93, p < .01), games (χ²(1) = 7.39, p < .01), and working (χ²(1) = 3.10, p < .10) was more prevalent among the highly educated, whereas television watching was slightly reduced (χ²(1) = 3.48, p < .10) for this group. Furthermore, individuals with a higher level of educational attainment also perceived greater levels of intellectual challenge when engaged in socializing (M _{low educ} = 1.76, M _{high educ} = 2.35), t(135) = 1.99; writing/e-mail (M _{low educ} = 1.97, M _{high educ} = 2.99), t(66) = 2.24; computer/internet (M _{low educ} = 2.65, M _{high educ} = 3.37), t(91) = 1.99; working (M _{low educ} = 1.62, M _{high educ} = 2.93), t(63) = 2.70; reading (M _{low educ} = 1.93, M _{high educ} = 2.62), t(152) = 2.39; watching television (M _{low educ} = 1.33, M _{high educ} = 2.23), t(162) = 3.57; and playing games (M _{low educ} = 2.97, M _{high educ} = 4.23), t(64) = 2.77.

Education may, therefore, build the skills and competencies to pursue more intellectual activities, so that more highly educated individuals (regardless of age) may be more likely to seek out opportunities for intellectual challenge or to create environments that are perceived as more cognitively demanding. Moreover, individuals differing in educational experiences may modify activities, such as by selecting reading materials (e.g., novel vs. magazine) or television programs (e.g., news vs. soap opera), to maintain a level of intellectual challenge that meets their skills and ability.

Conclusion

Dispelling the myth that aging is characterized by the lack of ability or interest in active engagement, older adults in the present study continue to engage in a wide variety of activities, including watching television, reading, socializing, shopping, and several other home and community engagements. When compared to the youngest adults (60-66 years), however, the oldest adults (81-92 years) did report reduced participation for commuting, exercising, and working. These findings are consistent with other studies suggesting that older people continue to be involved in numerous activities, although the nature of the activities may change over time (e.g., Horgas, Wilms, & Baltes, 1998; Paillard-Borg et al., 2009; Palmore, 1968; Strain et al., 2002; Verbrugge et al., 1996). For instance, Iso-Ahola and colleagues (1994) found that individuals tend to reduce participation in exercise and outdoor activities, but increase participation in hobbies (volunteer work, gardening, handicrafts) and home-based activities over the lifespan. Other lines of inquiry have suggested that activities in later adulthood may be more closely related to factors such as health and personality than age itself (Lefrancois, Leclerc, & Poulin, 1998; Mannell, 1999). Therefore, chronological age may not fully explain activity patterns in adulthood (Strain et al., 2002).

Moreover, most studies have examined only behavioral participation in activities without considering how the experience is perceived. Our findings suggest that although adults at different ages were similar in their extent of participation, the oldest adults (81-92 years) perceived lower levels of competence when compared with their younger counterparts (60-66 years). These feelings of reduced competence among older adults, whether reflective of actual ability or not, may affect enjoyment and the self-regulation of effortful allocation towards participation. Further, when specific activities were examined, the oldest adults reported less participation in commuting, exercising, and working. These activities were also associated with lower levels of positive affect among this age group. Therefore, older adults may choose to participate in activities that are enjoyable in order to produce or maintain a desired affective state (e.g., Nilsson et al., 2006; Rousseau et al., 2005).

Regardless of age, however, educational attainment impacted the extent and perception of activity. Assuming that early educational experiences may develop the necessary skills and competencies to pursue cognitive challenges in adulthood, it is hardly surprising that individuals with higher levels of educational attainment allocated more time and put forth more effort when engaging in intellectually complex activities. Furthermore, enhanced feelings of competence (by possessing the necessary skills and competencies) may foster success and intrinsic enjoyment with effortful problem solving tasks, thus increasing the likelihood that an individual will continue to engage in intellectually challenging activities.

As individuals greatly differ in how they approach and experience daily activities, these findings illustrate the limited information available when activity is viewed solely in terms of the frequency of engagement. Unfortunately, very few methods are available for collecting the relevant data. The application of experience sampling (ESM; Csikszentmihalyi & Larson, 1987) is often considered the gold standard in providing rich descriptions about daily experiences in individuals’ lives. This method, however, is expensive, places a high burden on the respondents, and requires a high level of compliance. As such, experience sampling may not be the most feasible method for large-scale data collection. Other diary studies have additionally explored the allocation of time to different activities; however, the DRM extends this approach by capturing the momentary affective experience that individuals derive from daily activities.

In practice, an appreciation of how individuals allocate their time and resources can potentially be useful when designing intervention strategies and activity programs for older adults. For instance, our findings suggest that individuals associate their daily experiences with low levels of intellectual stimulation. Assuming that participation in cognitively complex endeavors may enhance cognitive potential (“use it or lose it”) (e.g., Schaie, 2005; Schooler & Mulatu, 2001), we should consider how to best design and present opportunities for intellectual stimulation. However, when activities become increasingly more difficult, older adults may perceive these experiences as negative. Consequently, individuals may feel less competent and be less motivated to allocate effort and attentional resources towards participation in cognitively demanding activities (Newson & Kemps, 2006). Therefore, achieving a better understanding of how daily experiences are perceived (i.e., effortful, challenging, or enjoyable) can ultimately be useful in matching programs with individual preferences and abilities so as to maximize the benefits of such programs.

This study is not without its limitations. As the present study relied on retrospective self-reports, it is possible that the data may be incomplete, inaccurate, or distorted (Salthouse et al., 2002). However, as activities were written down chronologically shortly after they are actually undertaken, the tendency to under- or over-report certain activities may be diminished (Juster & Stafford, 1991). Another problem associated with retrospective accounts is that individuals of higher cognitive ability may be better able to reconstruct their day. Therefore, it is possible that participants of lower ability forgot what they were doing or how they felt about the activity.

Furthermore, measures of engagement were defined on the responses to a single one-day report and, therefore, may not accurately reflect habitual patterns of engagement. A longer data collection period would have more accurately characterized an individual’s lifestyle, thus increasing the reliability and validity of the reports. This may be especially true for activities that are highly irregular and unlikely to be captured by a single day diary (Juster & Stafford, 1991). Data of this nature would also allow for the examination of changes in the extent of participation or perceived experience of activity over time, especially when individuals are confronted with inevitable age-related changes in physical and cognitive ability.

Lastly, adults in the present sample were healthy, highly educated, and particularly successful in maintaining high levels of engagement; thus, limiting the generalizability of our findings. Similarly, other lifestyle factors that have been implicated as conditions for successful aging (e.g., nutrition, health, environmental conditions) may have also been more consistent within this sample. This study should be replicated in larger, more diverse cohorts (e.g., in terms of race/ethnicity, socio-economic status, education, and geographic location (rural vs. urban)) to determine the robustness and potential applicability of the present findings.

Clearly, further research that contextualizes activity and encompasses the complexity with which daily activities are experienced is warranted. This preliminary study has the potential to open many avenues of research that rely on the measurement of activities and motivational basis for understanding patterns of engagement in adulthood. As activities vastly differ in terms of meaningfulness among individuals, it may not only be the extent of participation but also the way in which these activities are approached and experienced that is key to aging successfully.

APPENDIX. Sample Questions from Structured Response Form

This is episode number _____, which began at _______ and ended at _______.

What were you doing? (please check all that apply)

__ commuting	__ working
__ shopping	__ preparing food
__ doing housework	__ taking care of children
__ eating	__ praying/worshipping/meditating
__ socializing	__ hobby (specify: ____________)
__ nap/resting	__ computer/internet
__ writing letters/e-mail	__ on the phone
__ volunteering	__ exercising
__ clubs/organizations	__ self-care (i.e., hygiene, taking meds)
__ intimate relations
__ reading (what were you reading?: ___________________)
__ watching TV (what were you watching?: __________________)
__ games (i.e., cards, puzzles) (specify game: _________________)
__ other (specify activity: ____________________________)

How did you feel during this episode?

Not at all						Very much
Impatient for it to end............................ 0	1	2	3	4	5	6
Happy ................................................... 0	1	2	3	4	5	6
Frustrated/annoyed................................ 0	1	2	3	4	5	6
Depressed/blue...................................... 0	1	2	3	4	5	6
Competent/capable................................ 0	1	2	3	4	5	6
Hassled/pushed around.......................... 0	1	2	3	4	5	6
Warm/friendly....................................... 0	1	2	3	4	5	6
Angry/hostile ........................................ 0	1	2	3	4	5	6
Worried/anxious.................................... 0	1	2	3	4	5	6
Enjoying myself .................................... 0	1	2	3	4	5	6
Criticized/put down............................... 0	1	2	3	4	5	6
Tired ..................................................... 0	1	2	3	4	5	6
Intellectually challenged........................ 0	1	2	3	4	5	6
Put forth effort ...................................... 0	1	2	3	4	5	6
Made a contribution .............................. 0	1	2	3	4	5	6
In control .............................................. 0	1	2	3	4	5	6
Felt like time flew by ............................ 0	1	2	3	4	5	6
Bored.................................................... 0	1	2	3	4	5	6
Attention was focused ........................... 0	1	2	3	4	5	6
Rewarding experience ........................... 0	1	2	3	4	5	6
Did it automatically............................... 0	1	2	3	4	5	6