Weekend Experiences and Subjective Well-being of Retired Older Adults Jinmoo Heo, PhD; Junhyoung Kim, PhD; Byung-Gook Kim, PhD; Seongmoo Heo, MA Objectives: To examine how involvement in activities is related to subjective wellbeing (SWB) among older adults in particular during weekends. To explore the situational and behavioral factors such as day of week, type of activities, and social context and their impact on subjective well being of older adults. Methods: The experience sampling method (ESM) was used with retired older adults. Results: Participants reported lower levels of SWB on the weekend. They experienced high-
R
ecent demographic changes worldwide have resulted in an increased proportion of older adults. Changes in life expectancy have led to an increase in the amount of time that older adults spend as retirees. Consequently, promoting the subjective well-being (SWB) of older adults has been of interest to researchers. Previous studies have reported factors that relate to the SWB of older adults, such as activity type1,2 social context3,4 and time use.5 Research has shown that involvement in leisure has an impact on the perceived health of older adults. In their study of older adults with arthritis, Payne, Mowen, and Montoro-Rodriguez6 proposed that individuals who pursued a combination of physical, sedentary, and cognitive leisure activities reported a better health perception. Sener, Terzioglu, and Karabulut7 also stressed the importance of active leisure involvement for the positive mental health of older adults. Pursuing an active lifestyle seems to be important to older adults because they are likely to maintain mental alertness, hold positive attitudes toward life, and avoid stress.8 Empirical research has suggested that social in-
Jinmoo Heo, Assistant Professor, Department of Recreation, Park and Tourism Sciences, Texas A&M University, College Station, TX. Junhyoung Kim, Assistant Professor, Department of Recreation, Parks, and Leisure Services, Central Michigan University, Mt. Pleasant, MI. Byung-Gook Kim, Assistant Professor, Department of Hotel and Tourism, Daegu University, Gyeongbuk, South Korea. Seongmoo Heo, doctoral Candidate, Department of Industrial Economics, Graduate School of Chinese Academy of Social Sciences, Beijing, China. Correspondence Mr Heo; [email protected]
598
er levels of SWB when they were engaged in active leisure on the weekend. Social contexts were significant predictors of older adults’ SWB on the weekend. Conclusion: These findings extend the body of knowledge that involvement in active leisure and socializing with friends improve SWB of older adults Key words: subjective well-being, older adults, leisure, social context, retirement Am J Health Behav. 2014;38(4):598-604 DOI: http://dx.doi.org/10.5993/AJHB.38.4.13
teractions are linked to the SWB of older adults. Maintaining informal (ie, family, friends, neighbors) and formal (ie, religious groups, volunteering) interactions is likely to provide social support and, often, contribute to the well-being of older adults.9 According to Krause,10 older adults who maintain good relationships with close companions or friends are likely to experience a higher level of well-being. Payne et al6 also reported that social contact with friends was positively related to the mental health of older adults. These findings infer that whereas spouses, children, and siblings are perceived as the most common sources of social support,11 friends also may be important to older adults’ SWB. To date, time use studies have enhanced the understanding of older adults’ lifestyles. Engaging in housework (meal preparation, repairs, household shopping, laundry), paid work, active leisure (eg, volunteering, religion and education, attending cultural and entertainment events, sport and fitness), passive leisure (eg, watching television, listening to music, relaxing), and personal activities (eg, sleeping, eating, bathing) would typify older adults’ daily lives.12 Another time use study reported that passive leisure activities occupy a significant portion of older adults’ daily lives.13 Therefore, it appears that engagement in passive leisure activities is likely to increase among older adults. On the other hand, a few studies have reported the impact of days of the week in older adults’ lifestyles. According to Tudor-Locke, Jones and Myers,14 older adults’ physical activity levels tend to be higher on weekdays than on the weekends. Tinsley, Tinsley and Croskeys15 investigated park
Heo et al usage by older adults and found that ethnic group differences existed. Caucasian respondents reported higher levels of use on weekdays, whereas use among other ethnic groups was higher on the weekends. Understanding how retired individuals structure their time use patterns is important because it affects their health and quality of life. Compared with younger individuals, adults who have retired appear to allocate more time to engaging in leisure activities and doing house-related work.16 It seems that older adults may utilize their free time effectively and various factors influence their participation in leisure activities. Der Ananian and Janke17 elaborated on several determinants that influence time use patterns in older adults, including age, mental health, sex, education level, income level, race, ethnicity, marital status, and life events. Leisure studies have provided evidence that older adults’ participation in leisure activities leads to improving mental health and quality of life.18-20 For example, using a qualitative approach with 28 community dwelling older adults, Stathi, Fox, and Mckenna8 conducted a qualitative study to explore the value of leisure on psychological well-being. They found that as a result of participating in leisure activities, older adults increased their levels of happiness and enjoyment. They suggested that participation in leisure activities makes a contribution to quality of life. In a study of online communities for older adults, Nimrod21 found that the main function of these communities is to provide enjoyable interactions, resources for leisure activities, and practice information (eg, recreation, shopping and travel). In this study, active engagement in leisure activities through online communities was considered to be a coping strategy for older adults that contributed to psychological well-being and quality of life. Nimrod suggested that online communities, as an expression of leisure involvement, were used as an avenue for coping with stress and improving a sense of happiness among older adults, which resulted in positive mental health. Taken together, the results of these studies can be used to infer that older adults’ engagements in certain type of activities as well as the existence of enriching social relationships may contribute to their SWB. Furthermore, whereas the literature has provided insights into older adults’ time use, few studies have investigated the behavior of older adults on the weekend. Abundant research exists on the weekday time use of the general population, but investigations into weekend time use are rare.22 Based on the proposition that some contextual factors are conducive to SWB, this study explores the role of activity types and social contexts on the SWB of older adults on the weekend. METHOD Participants The study sample was composed of 12 older adults (6 males and 6 females). All were married
Am J Health Behav.™ 2014;38(4):598-604
and Caucasian, and retired with a mean age of 71. With respect to educational attainment, 6 of the participants indicated that they had completed high school, whereas the other 6 participants had baccalaureate or advanced degrees. Using a convenience sampling technique, the participants were recruited from a local aging agency in a Midwestern US city. They were offered payments ($20 USD each) to participate in the study. All of the participants were physically healthy and independent. They were affiliated with one or more of the agency’s activity programs, including art and humanity classes (eg, painting, quilting, knitting, choral group, crafts) and health and fitness classes (eg, yoga, self-defense, dance, exercise to music, cardiovascular exercise, Tai chi). Procedures The data were collected using the experience sampling method (ESM), which is a random time sampling self-assessment technique that allows for a contextual analysis of behavior.23 ESM is known as an effective tool by which to assess average moods or the dynamics of mood and emotion.24 ESM studies provide considerably larger amount of information on participants’ daily experiences. In the present study, each participant generated an average of 40 valid ESM reports. ESM samples tend to be purposive and are not usually designed to be nationally representative samples. Studies with as few as 8 participants can produce enough reliable data for statistical analysis.25,26 Participants in the present study wore pre-programmed wristwatches set to beep randomly 7 times a day between 9 a.m. and 9 p.m. for 7 consecutive days. We assured the participants that they would receive signals at random times, with the restriction that 2 signals would not beep closer than 30 minutes apart, but not further apart than 2 hours. This sampling frequency was created to provide 49 ESM reports per participant over the one-week period and generated a total of 588 ESM responses (49 x 12 respondents = 588). After eliminating the incomplete responses, 489 ESFs were used in the analysis (83.1% response rate). The participants also carried an Experience Sampling Form (ESF), which is a self-report questionnaire designed to capture the participants’ experiences. The ESF contained questions about activities, companions, locations, content of thoughts, and various subjective states. The ESF was supplemented by questionnaires, which included demographic questions, completed by the participants at the end of the 7-day timeframe. When signaled by the wristwatches, the participants completed a series of questions in various formats (ie, openended questions, Likert-type statements, semantic differential items) on the ESF. Instrumentation Subjective well-being. Eight 7-point bipolar semantic differential items assessed subjective
DOI:
http://dx.doi.org/10.5993/AJHB.38.4.13
599
Weekend Experiences and Subjective Well-being of Retired Older Adults
Table 1 Mean Scores and Mann-Whitney U-tests for Day of Week on SWB (Positive Affect and Arousal) Weekdays
Weekend
Mann-Whitney U
Mean Rank
Sum of Ranks
M
SD
Positive affect
249.39
82297.50
234.29
37018.50
24457.50
Arousal
258.02
85403.00
217.73
34402.00
21841.00*
* Denotes significance at the .01 level
well-being. As in past research conducted by Larson, Mannell and Zuzanek,27 the first 4 items (ie, happy-sad, cheerful-irritable, friendly-angry, sociable-lonely) measured positive affect, whereas the next 4 items (ie, active-passive, alert-drowsy, energetic-tired, excited-bored) were used to assess mental and physical arousal. The scores of each item ranged from one to 7, and higher values on these items correspond to the positive state. For example, with the happy-sad item, a score of one represented feeling sad, and a score of 7 indicated feeling happy at the moment that the participants received the signals. Composite scores for positive affect and arousal were used based on the sum of each item. Larson et al27 reported acceptable internal consistencies of those items, and the Cronbach’s alpha for positive affect and arousal in the present study were .864 and .825 respectively. Day of the week. Based on the participants’ response time, the day of the week variable was created. Estimates for weekdays were reports from Monday at 9 a.m. to Friday at 5 p.m. All other times were considered to be the weekend in the analysis. Activity types. As in Victorino and Gauthier’s12 study, activities listed in the ESFs were grouped into 4 categories: personal activities, housework, active leisure and passive leisure. Personal activities consisted of self-care activities, such as sleeping, washing, health-related self-care, grooming, dressing, and toileting. Housework activities included cooking, lawn care, pet care, repairing clothing, home maintenance, and vehicle repair. The active leisure category captured playing games/sports, exercising, knitting, and creating art. Examples of passive leisure activities were watching TV, relaxing, playing card games, using the computer, and listening to music. Social context. Social context was identified using one question – “Whom were you with?” The responses were segmented into the following categories: alone-with others, with family-other occasions, and with friends-other occasions. Data Analysis The data analysis was performed using the Statistical Package for the Social Sciences (SPSS) program 20.0. Descriptive analysis was calculated to identify the characteristics of the sample. The
600
Mann-Whitney U test and multivariate analysis of variance (MANOVA) were employed to examine the differences of measurement groups. RESULTS To determine whether the day of the week was related to significantly different SWB scores, the Mann-Whitney U-test was employed to identify differences between the weekdays and weekends with a small sample size. The mean values for positive affect and arousal were above the midrange point (ie, 16), which suggested that the participants reported being relatively happy, cheerful, friendly, sociable, active, alert, energetic, and excited during the study period. The mean rank, sum of ranks, and Mann-Whitney U-test results are shown in Table 1. Data in Table 1 demonstrate the mean difference of the positive affect and arousal between the weekdays and weekend. The mean level of the positive affect between the weekdays and weekend were not statistically significant. However, significantly different means were observed between the weekdays and weekends for arousal. The level of arousal was higher during the weekdays than on the weekend. Because the present research was designed specifically to examine factors conducive to SWB on the weekend, further analyses reported the positive affect and arousal scores captured on the weekend. A one-way MANOVA with 4 activity types (ie, personal activity, housework, active leisure, passive leisure) as the between-factor variable and SWB (ie, positive affect, arousal) as the dependent variable were employed to determine the differences in SWB based on activity types (Table 2). The MANOVA results revealed significant differences among the activity types on the dependent variables, with the Wilks lambda multivariate test being significant and partial eta squared indicating a medium effect [Wilks’l = .80, F(2, 153) = 6.01, p < .01, multivariate η2 = .106]. An analysis of variance (ANOVA) was conducted on each dependent variable as a follow-up test to the MANOVA. The activity type differences were significant for the positive affects [F(2, 153) = 7.57, p < .01, partial η2 = .129] and arousal [F(2, 153) = 6.39, p < .01, partial η2 = .111]. Examination of the Tukey’s post hoc tests for the 2 dependent
Heo et al
Table 2 Descriptive Statistics on SWB (Positive Affect and Arousal) and Multivariate Analysis of Variance (MANOVA) Results Weekend Positive Affect Activity Types
Arousal
M
SD
M
SD
Personal activity
19.94
5.21
17.96
5.73
Housework
19.74
3.94
20.48
3.16
Active leisure
23.87
3.28
21.74
3.89
Passive leisure
19.89
3.59
18.09
4.02
19.23
4.70
Total
20.66
4.44
Df
2/153
2/153
F
7.57*
6.39*
ηp2
.129
.111
* Denotes significance at the
R
ecent demographic changes worldwide have resulted in an increased proportion of older adults. Changes in life expectancy have led to an increase in the amount of time that older adults spend as retirees. Consequently, promoting the subjective well-being (SWB) of older adults has been of interest to researchers. Previous studies have reported factors that relate to the SWB of older adults, such as activity type1,2 social context3,4 and time use.5 Research has shown that involvement in leisure has an impact on the perceived health of older adults. In their study of older adults with arthritis, Payne, Mowen, and Montoro-Rodriguez6 proposed that individuals who pursued a combination of physical, sedentary, and cognitive leisure activities reported a better health perception. Sener, Terzioglu, and Karabulut7 also stressed the importance of active leisure involvement for the positive mental health of older adults. Pursuing an active lifestyle seems to be important to older adults because they are likely to maintain mental alertness, hold positive attitudes toward life, and avoid stress.8 Empirical research has suggested that social in-
Jinmoo Heo, Assistant Professor, Department of Recreation, Park and Tourism Sciences, Texas A&M University, College Station, TX. Junhyoung Kim, Assistant Professor, Department of Recreation, Parks, and Leisure Services, Central Michigan University, Mt. Pleasant, MI. Byung-Gook Kim, Assistant Professor, Department of Hotel and Tourism, Daegu University, Gyeongbuk, South Korea. Seongmoo Heo, doctoral Candidate, Department of Industrial Economics, Graduate School of Chinese Academy of Social Sciences, Beijing, China. Correspondence Mr Heo; [email protected]
598
er levels of SWB when they were engaged in active leisure on the weekend. Social contexts were significant predictors of older adults’ SWB on the weekend. Conclusion: These findings extend the body of knowledge that involvement in active leisure and socializing with friends improve SWB of older adults Key words: subjective well-being, older adults, leisure, social context, retirement Am J Health Behav. 2014;38(4):598-604 DOI: http://dx.doi.org/10.5993/AJHB.38.4.13
teractions are linked to the SWB of older adults. Maintaining informal (ie, family, friends, neighbors) and formal (ie, religious groups, volunteering) interactions is likely to provide social support and, often, contribute to the well-being of older adults.9 According to Krause,10 older adults who maintain good relationships with close companions or friends are likely to experience a higher level of well-being. Payne et al6 also reported that social contact with friends was positively related to the mental health of older adults. These findings infer that whereas spouses, children, and siblings are perceived as the most common sources of social support,11 friends also may be important to older adults’ SWB. To date, time use studies have enhanced the understanding of older adults’ lifestyles. Engaging in housework (meal preparation, repairs, household shopping, laundry), paid work, active leisure (eg, volunteering, religion and education, attending cultural and entertainment events, sport and fitness), passive leisure (eg, watching television, listening to music, relaxing), and personal activities (eg, sleeping, eating, bathing) would typify older adults’ daily lives.12 Another time use study reported that passive leisure activities occupy a significant portion of older adults’ daily lives.13 Therefore, it appears that engagement in passive leisure activities is likely to increase among older adults. On the other hand, a few studies have reported the impact of days of the week in older adults’ lifestyles. According to Tudor-Locke, Jones and Myers,14 older adults’ physical activity levels tend to be higher on weekdays than on the weekends. Tinsley, Tinsley and Croskeys15 investigated park
Heo et al usage by older adults and found that ethnic group differences existed. Caucasian respondents reported higher levels of use on weekdays, whereas use among other ethnic groups was higher on the weekends. Understanding how retired individuals structure their time use patterns is important because it affects their health and quality of life. Compared with younger individuals, adults who have retired appear to allocate more time to engaging in leisure activities and doing house-related work.16 It seems that older adults may utilize their free time effectively and various factors influence their participation in leisure activities. Der Ananian and Janke17 elaborated on several determinants that influence time use patterns in older adults, including age, mental health, sex, education level, income level, race, ethnicity, marital status, and life events. Leisure studies have provided evidence that older adults’ participation in leisure activities leads to improving mental health and quality of life.18-20 For example, using a qualitative approach with 28 community dwelling older adults, Stathi, Fox, and Mckenna8 conducted a qualitative study to explore the value of leisure on psychological well-being. They found that as a result of participating in leisure activities, older adults increased their levels of happiness and enjoyment. They suggested that participation in leisure activities makes a contribution to quality of life. In a study of online communities for older adults, Nimrod21 found that the main function of these communities is to provide enjoyable interactions, resources for leisure activities, and practice information (eg, recreation, shopping and travel). In this study, active engagement in leisure activities through online communities was considered to be a coping strategy for older adults that contributed to psychological well-being and quality of life. Nimrod suggested that online communities, as an expression of leisure involvement, were used as an avenue for coping with stress and improving a sense of happiness among older adults, which resulted in positive mental health. Taken together, the results of these studies can be used to infer that older adults’ engagements in certain type of activities as well as the existence of enriching social relationships may contribute to their SWB. Furthermore, whereas the literature has provided insights into older adults’ time use, few studies have investigated the behavior of older adults on the weekend. Abundant research exists on the weekday time use of the general population, but investigations into weekend time use are rare.22 Based on the proposition that some contextual factors are conducive to SWB, this study explores the role of activity types and social contexts on the SWB of older adults on the weekend. METHOD Participants The study sample was composed of 12 older adults (6 males and 6 females). All were married
Am J Health Behav.™ 2014;38(4):598-604
and Caucasian, and retired with a mean age of 71. With respect to educational attainment, 6 of the participants indicated that they had completed high school, whereas the other 6 participants had baccalaureate or advanced degrees. Using a convenience sampling technique, the participants were recruited from a local aging agency in a Midwestern US city. They were offered payments ($20 USD each) to participate in the study. All of the participants were physically healthy and independent. They were affiliated with one or more of the agency’s activity programs, including art and humanity classes (eg, painting, quilting, knitting, choral group, crafts) and health and fitness classes (eg, yoga, self-defense, dance, exercise to music, cardiovascular exercise, Tai chi). Procedures The data were collected using the experience sampling method (ESM), which is a random time sampling self-assessment technique that allows for a contextual analysis of behavior.23 ESM is known as an effective tool by which to assess average moods or the dynamics of mood and emotion.24 ESM studies provide considerably larger amount of information on participants’ daily experiences. In the present study, each participant generated an average of 40 valid ESM reports. ESM samples tend to be purposive and are not usually designed to be nationally representative samples. Studies with as few as 8 participants can produce enough reliable data for statistical analysis.25,26 Participants in the present study wore pre-programmed wristwatches set to beep randomly 7 times a day between 9 a.m. and 9 p.m. for 7 consecutive days. We assured the participants that they would receive signals at random times, with the restriction that 2 signals would not beep closer than 30 minutes apart, but not further apart than 2 hours. This sampling frequency was created to provide 49 ESM reports per participant over the one-week period and generated a total of 588 ESM responses (49 x 12 respondents = 588). After eliminating the incomplete responses, 489 ESFs were used in the analysis (83.1% response rate). The participants also carried an Experience Sampling Form (ESF), which is a self-report questionnaire designed to capture the participants’ experiences. The ESF contained questions about activities, companions, locations, content of thoughts, and various subjective states. The ESF was supplemented by questionnaires, which included demographic questions, completed by the participants at the end of the 7-day timeframe. When signaled by the wristwatches, the participants completed a series of questions in various formats (ie, openended questions, Likert-type statements, semantic differential items) on the ESF. Instrumentation Subjective well-being. Eight 7-point bipolar semantic differential items assessed subjective
DOI:
http://dx.doi.org/10.5993/AJHB.38.4.13
599
Weekend Experiences and Subjective Well-being of Retired Older Adults
Table 1 Mean Scores and Mann-Whitney U-tests for Day of Week on SWB (Positive Affect and Arousal) Weekdays
Weekend
Mann-Whitney U
Mean Rank
Sum of Ranks
M
SD
Positive affect
249.39
82297.50
234.29
37018.50
24457.50
Arousal
258.02
85403.00
217.73
34402.00
21841.00*
* Denotes significance at the .01 level
well-being. As in past research conducted by Larson, Mannell and Zuzanek,27 the first 4 items (ie, happy-sad, cheerful-irritable, friendly-angry, sociable-lonely) measured positive affect, whereas the next 4 items (ie, active-passive, alert-drowsy, energetic-tired, excited-bored) were used to assess mental and physical arousal. The scores of each item ranged from one to 7, and higher values on these items correspond to the positive state. For example, with the happy-sad item, a score of one represented feeling sad, and a score of 7 indicated feeling happy at the moment that the participants received the signals. Composite scores for positive affect and arousal were used based on the sum of each item. Larson et al27 reported acceptable internal consistencies of those items, and the Cronbach’s alpha for positive affect and arousal in the present study were .864 and .825 respectively. Day of the week. Based on the participants’ response time, the day of the week variable was created. Estimates for weekdays were reports from Monday at 9 a.m. to Friday at 5 p.m. All other times were considered to be the weekend in the analysis. Activity types. As in Victorino and Gauthier’s12 study, activities listed in the ESFs were grouped into 4 categories: personal activities, housework, active leisure and passive leisure. Personal activities consisted of self-care activities, such as sleeping, washing, health-related self-care, grooming, dressing, and toileting. Housework activities included cooking, lawn care, pet care, repairing clothing, home maintenance, and vehicle repair. The active leisure category captured playing games/sports, exercising, knitting, and creating art. Examples of passive leisure activities were watching TV, relaxing, playing card games, using the computer, and listening to music. Social context. Social context was identified using one question – “Whom were you with?” The responses were segmented into the following categories: alone-with others, with family-other occasions, and with friends-other occasions. Data Analysis The data analysis was performed using the Statistical Package for the Social Sciences (SPSS) program 20.0. Descriptive analysis was calculated to identify the characteristics of the sample. The
600
Mann-Whitney U test and multivariate analysis of variance (MANOVA) were employed to examine the differences of measurement groups. RESULTS To determine whether the day of the week was related to significantly different SWB scores, the Mann-Whitney U-test was employed to identify differences between the weekdays and weekends with a small sample size. The mean values for positive affect and arousal were above the midrange point (ie, 16), which suggested that the participants reported being relatively happy, cheerful, friendly, sociable, active, alert, energetic, and excited during the study period. The mean rank, sum of ranks, and Mann-Whitney U-test results are shown in Table 1. Data in Table 1 demonstrate the mean difference of the positive affect and arousal between the weekdays and weekend. The mean level of the positive affect between the weekdays and weekend were not statistically significant. However, significantly different means were observed between the weekdays and weekends for arousal. The level of arousal was higher during the weekdays than on the weekend. Because the present research was designed specifically to examine factors conducive to SWB on the weekend, further analyses reported the positive affect and arousal scores captured on the weekend. A one-way MANOVA with 4 activity types (ie, personal activity, housework, active leisure, passive leisure) as the between-factor variable and SWB (ie, positive affect, arousal) as the dependent variable were employed to determine the differences in SWB based on activity types (Table 2). The MANOVA results revealed significant differences among the activity types on the dependent variables, with the Wilks lambda multivariate test being significant and partial eta squared indicating a medium effect [Wilks’l = .80, F(2, 153) = 6.01, p < .01, multivariate η2 = .106]. An analysis of variance (ANOVA) was conducted on each dependent variable as a follow-up test to the MANOVA. The activity type differences were significant for the positive affects [F(2, 153) = 7.57, p < .01, partial η2 = .129] and arousal [F(2, 153) = 6.39, p < .01, partial η2 = .111]. Examination of the Tukey’s post hoc tests for the 2 dependent
Heo et al
Table 2 Descriptive Statistics on SWB (Positive Affect and Arousal) and Multivariate Analysis of Variance (MANOVA) Results Weekend Positive Affect Activity Types
Arousal
M
SD
M
SD
Personal activity
19.94
5.21
17.96
5.73
Housework
19.74
3.94
20.48
3.16
Active leisure
23.87
3.28
21.74
3.89
Passive leisure
19.89
3.59
18.09
4.02
19.23
4.70
Total
20.66
4.44
Df
2/153
2/153
F
7.57*
6.39*
ηp2
.129
.111
* Denotes significance at the
