Journal of Happiness Studies

, Volume 14, Issue 1, pp 169–184

Comparing Three Methods to Measure a Balanced Time Perspective: The Relationship Between a Balanced Time Perspective and Subjective Well-Being

Authors

  • Jia Wei Zhang
    • Department of PsychologySan Francisco State University
    • Department of PsychologyUniversity of California
    • Department of PsychologySan Francisco State University
  • Maciej Stolarski
    • Faculty of PsychologyUniversity of Warsaw
Research Paper

DOI: 10.1007/s10902-012-9322-x

Cite this article as:
Zhang, J.W., Howell, R.T. & Stolarski, M. J Happiness Stud (2013) 14: 169. doi:10.1007/s10902-012-9322-x

Abstract

The goals of this study were to determine the relations between having a balanced time perspective (BTP) with various measures of subjective well-being (SWB) and to test how various operationalizations of a BTP might impact the relation between having a BTP and SWB. We operationalized a balanced time perspective using: (a) Drake et al.’s Time Soc 17(1):47–61, (2008) cut-off-point method, (b) Boniwell et al.’s J Posit Psychol 5(1):24–40, (2010) suggestion of using a hierarchical cluster analysis, and (c) a deviation from a balanced time perspective (DBTP; Stolarski et al. Time Soc, 2011). The results demonstrated that having a BTP is related to increased satisfaction with life, happiness, positive affect, psychological need satisfaction, self-determination, vitality, and gratitude as well as decreased negative affect. Also, the DBTP was the best predictor of SWB. We discuss why individuals with a BTP are likely to be happier in life.

Keywords

Time perspectivesWell-beingSubjective timeHappinessBalanced time perspective

1 Introduction

The study of subjective well-being (SWB) is rapidly growing as we learn more about the predictors and benefits of happiness (see Lyubomirsky et al. 2005 for a review). Recently, Durayappah (2010) proposed a temporal model of SWB (i.e., the 3P model of SWB). Durayappah’s 3P model of SWB includes the fundamental elements of time—the past, present, and future—because the evaluation of SWB “considers not only current proceedings, but also the moments that have occurred, as well as those yet to be” (p. 5) and, thus, time perspectives should influence global evaluations of SWB. Also, other researchers have proposed that a balanced time perspective (BTP) leads to increased SWB (Boniwell et al. 2010; Drake et al. 2008; Stolarski et al. 2011). Unfortunately, Boniwell et al. Drake et al. and Stolarski et al. each operationalized a BTP differently. Thus, it remains an open question as to which operationalization of a BTP best predicts increased SWB. For these reasons, the goal of this study was to compare these three operationalizations and examine the relations between a BTP and SWB across these methods.

2 The Cultural Invariance and Explanatory Validity of the ZTPI

One’s time perspective is defined by Boyd and Zimbardo as the “often nonconscious subjective manner in which each of us relates to time and the process whereby the continual flow of personal and social experiences is assigned to, parceled into, temporal categories or time frames” (Boyd and Zimbardo, 2005, p. 1271). When such time frames become habitual, they represent a dispositional style and predict life choices. Based on a series of exploratory studies (see Gonzalez and Zimbardo 1985; Zimbardo and Boyd, 1999; Zimbardo and Gonzalez 1984), Zimbardo and Boyd (1999) argued that there are five time perspectives that are important in predicting attitudes, feelings, and behaviors: past positive (having a sentimentally good view of past events), past negative (remembering the past as distressful), present hedonistic (enjoying immediate pleasures), present fatalistic (believing that there is little relation between the present and future), and future (striving for long-term goals). Additionally, recent studies have demonstrated that this five factor structure is consistent across culture. For example, the five factor structure was replicated in Brazil (Milfont et al. 2008), France (Apostolidis and Fieulaine 2004), Spain (Diaz-Moralez 2006) and Greece (Anagnostopoulos and Griva 2011). These five time perspectives are measured with Zimbardo and Boyd’s (1999) 56–item Zimbardo Time Perspective Inventory (ZTPI). Since its development, many studies have used the ZTPI as their measure of time perspectives.

During the development and validation of the ZTPI, Zimbardo and Boyd (1999) demonstrated that all five time perspectives predicted psychosocial outcomes. For example, they demonstrated that having a past negative time perspective predicted unsatisfactory interpersonal relationships, whereas having a past positive time perspective is associated with involvement with friends and family. Since that seminal article, other studies have reported numerous significant relations between the ZTPI and various behavioral as well as psychological outcomes (see Boniwell and Zimbardo, 2004, for a review). For example, the ZTPI predicts specific risky behaviors (e.g., smoking, drinking, and drug use; Keough et al. 1999), risky driving behaviors (Zimbardo et al. 1997), water conservation and pro-environmental behaviors (Corral-Verdugo et al. 2006), having large support groups and companionship from friends and significant others (Holman and Zimbardo 2009), and experimental participation compliance rates (Harber et al. 2003). Recently, researchers have examined the relationship between ZTPI and SWB. Below, we review this literature.

3 Balanced Time Perspective and SWB

The relationships between the five time perspectives and SWB tend to be consistent and robust. For example, those with a past positive time perspective report higher levels of self-esteem and happiness (Zimbardo and Boyd, 1999) as well as increased life satisfaction, mindfulness, positive affect, and decreased negative affect—whereas those with a past negative or present fatalistic time orientation are less satisfied with their lives, mindful, happy, and experience less positive affect and more negative affect (Boniwell et al. 2010; Drake et al. 2008). More recently, Zhang and Howell (2011) found that time perspectives accounted for an additional 13.7% of the variance in life satisfaction beyond personality traits. The pattern of the correlations between the five time perspectives and SWB support the proposition that a BTP (i.e., low scores on the past negative and present fatalistic as well as moderate to high scores on the past positive, present hedonistic, and future time perspectives, see Zimbardo and Boyd 2008) is a key to the good life (see Zimbardo 2002).

Is a BTP strongly related to increased subjective well-being? The benefits of a BTP have been posited by previous research (see Boniwell and Zimbardo 2003; Boniwell and Zimbardo 2004; Zimbardo and Boyd 1999). However, only recently have scholars empirically tested the relationship between a BTP and SWB (see Drake et al. 2008 and Boniwell et al. 2010). First, Drake et al. (2008) calculated a BTP by categorizing the five time perspectives into low (below the 33rd percentile) and moderate or high (above the 33rd percentile). They found that those with a BTP were significantly happier and more mindful than those without a BTP. Second, Boniwell et al. (2010)—who criticized this cut-off-approach and suggested using a person-oriented operationalization of a BTP—grouped participants into BTP categories by using hierarchical cluster analysis. Though they operationalized a BTP differently, they also showed that those in the BTP cluster scored higher on psychological adjustment than those in the non-BTP clusters.

However, neither of these methods are optimal operationalizations of a BTP. First, both of these methods categorized people into groups. This technique resulted in a small number of people being categorized as having a BTP (i.e. Drake et al. reported that only 7% of people met their BTP criteria; Boniwell et al. reported that only between 10 and 23% met their BTP criteria). Moreover, the two methods are sample-dependent. That is, the cluster or cut-off approach may categorize individuals has having a “balanced” time perspective whose time perspective profile is different from how Zimbardo (2002) originally defined a BTP. A recent study developed a new measure of a BTP to address this concern (Stolarski et al. (2011)). The authors developed the deviation from a balanced time perspective (DBTP) method to score each person’s time perspective profile—in this case on how “non-balanced” each person is (see the Method section for the complete equation). Thus, the DBTP coefficient is a measure of fit between the individual’s time perspective profile and the optimal time perspective profile as stated by Zimbardo and Boyd (2008). Stolarski et al. argued that the DBTP reflects the nature of time perspective balance more accurately because a DBTP value close to zero indicates an almost perfectly balanced time perspective (the theoretical ideal), whereas a large positive value indicates a person’s time perspective is out of balance (and, is expected to be, maladaptive).

4 The Current Study

Recently, a pair of studies demonstrated there is a positive correlation between having a BTP and subjective well-being (Drake et al. 2008; Boniwell et al. 2010). However, Stolarski et al. (2011) expressed concerns with these two operationalizations and developed the DBTP approach to be a more accurate scoring method of a BTP. The aims of this study, then, are: (a) to examine the relation between having a BTP with various measures of SWB and (b) to determine the best operationalization of a BTP [the cut-off-method (Drake et al. 2008), using a hierarchical cluster analysis (Boniwell et al. 2010), or the DBTP (Stolarski et al. 2011)] by examining the unique predictive validity explained in SWB by each BTP method.

5 Method

5.1 Participants

In total, we recruited four samples (N = 1,739) to test the relations between the five time perspectives (and the three operationalizations of a BTP) and various SWB constructs. First, to examine the relations between the five time perspectives and four SWB constructs (i.e., life satisfaction, happiness, positive and negative affect) we recruited two samples from San Francisco State University (SFSU). The first sample consisted of 562 participants (68.1% females; mean age = 25.69, SD = 9.63) and the second consisted of 200 participants (73% females; mean age = 23.39, SD = 7.79). Next, we recruited a third sample to examine the five time perspectives with numerous SWB constructs (i.e., the original four constructs as well as psychological need satisfaction, self-determination, vitality, and gratitude). The third sample consisted of 496 participants (67.3% females; mean age = 24.84, SD = 9.80) recruited from SFSU and various social networking sites (e.g., Facebook, Craigslist). Finally, to replicate our findings with a relatively older and more geographically diverse sample, a fourth sample consisting of 481 participants (69.2% females; mean age = 32.99, SD = 12.39) was recruited from Amazon’s Mechanical Turk (see Buhrmester et al. 2011 for a review of the diversity and generalizability of Mturk samples).

5.2 Measures

All participants completed the Zimbardo Time Perspective Inventory (ZTPI) as well as various SWB measures. Specifically, participants in samples 1 and 2 completed the satisfaction with life scale, subjective happiness scale, and positive and negative affect schedule. Participants from sample 3 completed, in addition to the original four measures of SWB, measures of psychological need satisfaction, self-determination, vitality, and gratitude to assess eudaimonic well-being. Finally, the older and more diverse participants in sample 4 completed the satisfaction with life scale. Tables 1 and 2 reported the means, standard deviations, reliability coefficients, and inter-correlations for all variables administered in each sample.
Table 1

Means, standard deviations, alphas, and inter-correlations of time perspective and well-being indicators from Sample 1 and Sample 2

 

M

SD

α

PP

PN

PH

PF

F

SWLS

SHS

PA

NA

Sample 1 (n = 562)

 PP

3.50

0.56

0.71

        

 PN

3.05

0.71

0.83

−0.27***

       

 PH

3.36

0.52

0.80

0.20***

0.19***

      

 PF

2.50

0.62

0.76

−0.11**

0.49***

0.32***

     

 F

3.52

0.52

0.76

0.13**

−0.04

−0.16***

−0.29***

    

 SWLS

4.67

1.28

0.87

0.36***

−0.42***

0.15***

−0.21***

0.13**

   

 SHS

4.91

1.22

0.85

0.40***

−0.44***

0.23***

−0.23***

0.12**

0.65***

  

 PA

2.64

0.95

0.88

0.19***

−0.11*

0.14**

−0.09*

0.21***

0.21***

0.32***

 

 NA

1.60

0.69

0.89

−0.18***

0.38***

0.02

0.30***

−0.15***

−0.30***

−0.29***

−0.13**

Sample 2 (n = 200)

 PP

3.53

0.69

0.79

        

 PN

3.09

0.71

0.84

−0.19**

       

 PH

3.38

0.57

0.84

0.26***

0.13

      

 PF

2.56

0.64

0.76

−0.01

0.45***

0.34***

     

 F

3.43

0.50

0.71

0.28***

0.08

−0.07

−0.29***

    

 SWLS

4.46

1.43

0.89

0.52***

−0.51***

0.16*

−0.17*

0.19**

   

 SHS

4.84

1.34

0.88

0.52***

−0.46***

0.22**

−0.24**

0.21**

0.72***

  

 PA

3.38

0.73

0.88

0.30***

−0.21**

0.27***

−0.05

0.27***

0.60***

0.58***

 

 NA

2.21

0.78

0.89

−0.15*

0.56***

0.09

0.36***

−0.06

−0.45***

−0.45***

−0.14*

PP past positive, PN past negative, PH present hedonism, PF present fatalism, and F future. SHS subjective happiness. SWLS satisfaction with life. PA positive affect and NA negative affect. Psych needs is psychological needs and is the average of autonomy, competence and relatedness. SDS is self-determination scale

* p < 0.05; ** p < 0.01; *** p < 0.001

Table 2

Means, standard deviations, alphas, and inter-correlations of time perspectives and well-being indicators from Sample 3 and Sample 4

 

M

SD

α

PP

PN

PH

PF

F

SWLS

SHS

PA

NA

Psych needs

SDS

Vitality

Gratitude

Sample 3 (n = 493)

 PP

3.49

0.65

0.78

            

 PN

3.09

0.75

0.83

−.28***

           

 PH

3.39

0.53

0.81

.24***

0.22***

          

 PF

2.49

0.64

0.76

.02

0.35***

0.32***

         

 F

3.50

0.55

0.79

.07

−0.01

−0.23***

−0.28***

        

 SWLS

4.56

1.40

0.90

.42***

−0.49***

0.10*

−0.16***

0.13**

       

 SHS

4.89

1.27

0.87

.43***

−0.46***

0.19***

−0.18***

0.10*

0.60***

      

 PA

3.47

0.73

0.87

.30***

−0.24***

0.26***

−0.19***

0.24***

0.41***

0.56***

     

 NA

2.05

0.75

0.86

−.30***

0.48***

−0.01

0.31***

−0.12*

−0.41***

−0.49***

−0.21***

    

 Psych needs

5.02

0.83

0.83

.34***

−0.48***

0.13**

−0.34***

0.15**

0.51***

0.57***

0.54***

−0.53***

   

 SDS

3.71

0.73

0.84

.32***

−0.44***

0.08

−0.28***

0.07

0.43***

0.41***

0.30***

−0.49***

0.64***

  

 Vitality

4.62

1.23

0.90

.40***

−0.37***

0.31***

−0.22***

0.11*

0.56***

0.69***

0.63***

−0.41***

0.62***

0.43***

 

 Gratitude

5.72

0.98

0.82

.42***

−0.36***

0.19***

−0.27***

0.19***

0.45***

0.52***

0.35***

−0.41***

0.59***

0.40***

0.51***

Sample (n = 481)

 PP

3.54

0.65

0.75

            

 PN

3.08

0.79

0.84

−.38***

           

 PH

3.18

0.53

0.82

.07

0.17***

          

 PF

2.41

0.62

0.77

−.11*

0.43***

0.27***

         

 F

3.61

0.49

0.79

.23***

−0.20***

−0.25***

−0.42***

        

 SWLS

4.57

1.48

0.89

.39***

−0.59***

0.09

−0.39***

0.28***

       

PP past positive, PN past negative, PH present hedonism, PF present fatalism, and F Future. SHS subjective happiness. SWLS satisfaction with life. PA positive affect and NA negative affect. Psych needs is psychological needs and is the average of autonomy, competence and relatedness. SDS is self-determination scale

* p < 0.05; ** p < 0.01; *** p < 0.001

† indicates the intra correlation between the same correlation, which is always 1

5.3 Measuring Time Perspectives

5.3.1 Zimbardo Time Perspective Inventory

We measured time perspectives using the ZTPI developed by Zimbardo and Boyd (1999). The ZTPI is a 56-item questionnaire and each time perspective is assessed using a 5-point scale (1 = very untrue of me, 5 = very true of me). Nine items measure the past positive perspective (“On balance, there is much more good to recall than bad in my past”). Ten items measure the past negative perspective (“I often think of what I should have done differently in my life”). Fifteen items measure the present hedonistic perspective (“I believe that getting together with one’s friend to party is one of life’s important pleasures”). Nine items measure the present fatalistic perspective (“Fate determines much in my life”). Thirteen items measure the future perspective (“I believe a person’s day should be planned ahead each morning”).

5.4 Measuring SWB

In addition to completing the ZTPI, to measure subjective well-being, participants (based on the goals of the sample—see the above Measures section) completed: (a) The Satisfaction With Life Scale (SWLS; Diener et al. 1985); (b) The Subjective Happiness Scale (SHS; Lyubomirsky and Lepper 1999); (c) The Positive and Negative Affect Schedule (PANAS; Watson et al. 1988); (d) The Basic Need Satisfaction in Life Scale (Gagne 2003), which is a questionnaire that measures the psychological needs (i.e., autonomy, competence, and relatedness) necessary for optimal well-being; (e) a measure of self-determination (SDS; Sheldon et al. 1996); (f) the Subjective Vitality Scale (Ryan and Frederick, 1997) to measure perceptions of having energy and feeling alive; and (g) the 6-item Gratitude questionnaire (McCullough et al. 2002) to measure participant’s disposition to feel gratitude. Because life satisfaction and affect assess the cognitive and emotional aspect of well-being, respectively, we followed the recommendation of Diener and Lucas (1999) and the procedures of Sheldon and Elliot (1999) and created a composite score of SWB—specifically, we computed the average of life satisfaction and affect balance (i.e., positive affect minus negative affect). Also, we created a psychological need satisfaction composite score by computing the average of autonomy, competence, and relatedness.

5.5 Three Operationalizations of a BTP

We operationalized a balanced time perspective in three different ways. First, we employed the cut-off-point method used by Drake et al. (2008) which categorizes each time perspective as low (below the 33rd percentile), moderate (between the 33rd and 66th percentile), or high (above the 66th percentile). Using this method, a balanced time perspective is defined by (a) low scores on past negative and present fatalistic and (b) moderate to high scores on past positive, present hedonism, and future. The Drake et al. cut-off method resulted in 26, 8, 27, and 33 participants (in samples 1–4, respectively; see Table 3) being categorized as having a BTP. Second, we followed the hierarchical cluster analysis method used by Boniwell et al. (2010) to group individuals into clusters based on their five time perspectives (i.e., we used Ward’s method and the Squared Euclidean metric to determine group membership; see Boniwell et al. for a detailed explanation of the cluster analysis procedure). Though we examined the time perspective profiles for each group when using a 2-group, 3-group, 4-group, and 5-group cluster method across four samples, none of the clusters within these groupings demonstrated the typical profile expected for individuals with a BTP. Specifically, the groups that most closely meet Zimbardo and Boyd’s (2008) BTP criteria were either too low on the present hedonism or future time perspectives. Thus, we selected the 2-cluster results because they best resembled the characterization of a BTP across all four samples (See Table 3 for the pattern of means). Finally, we used the deviation from a balanced time perspective (DBTP) method to determine how ill-balanced each person is in their time perspectives (Stolarski et al. 2011).
Table 3

Comparing group means and cluster means for BTP and non-BTP groups

Cut-off approach

 

Non-BTP

BTP

  

Sample 1 (n = 562)

(n = 536)

(n = 26)

t (560)

Cohen’s d

Past positive

3.47

4.05

8.60***

1.28

Past negative

3.09

2.11

12.95***

1.81

Present hedonistic

3.34

3.57

2.24*

0.48

Present fatalistic

2.53

1.65

13.26***

1.84

Future

3.49

3.89

3.83***

0.87

Sample 2 (n = 200)

(n = 192)

(n = 8)

t (198)

Cohen’s d

Past positive

3.49

4.30

3.36**

1.35

Past negative

3.12

2.08

4.24***

1.89

Present hedonistic

3.37

3.54

0.82

0.36

Present fatalistic

2.59

1.59

6.51***

1.92

Future

3.41

3.84

2.34*

1.02

Sample 3 (n = 493)

(n = 466)

(n = 27)

t (491)

Cohen’s d

Past positive

3.46

3.88

5.35**

0.78

Past negative

3.12

2.32

12.76***

1.43

Present hedonistic

3.38

3.46

1.57

0.19

Present fatalistic

2.52

1.81

11.49***

1.45

Future

3.48

3.84

5.89***

0.82

Sample 4 (n = 481)

(n = 448)

(n = 33)

t (479)

Cohen’s d

Past positive

3.52

3.99

4.29***

0.87

Past negative

3.14

2.15

7.26***

1.65

Present hedonistic

3.16

3.43

2.91**

0.63

Present fatalistic

2.44

1.81

5.82***

1.35

Future

3.59

3.92

3.85***

0.78

Hierarchical cluster approach

 

Non-BTP

BTP

  

Sample 1 (n = 562)

(n = 281)

(n = 281)

t (560) =

Cohen’s d

Past positive

3.29

3.71

9.84***

0.82

Past negative

3.54

2.54

23.64***

2.02

Present hedonistic

3.45

3.25

4.60***

0.39

Present fatalistic

2.86

2.13

17.29***

1.47

Future

3.39

3.63

5.49***

0.47

Sample 2 (n = 200)

(n = 103)

(n = 97)

t (198) =

Cohen’s d

Past positive

3.32

3.73

4.43***

0.62

Past negative

3.55

2.58

13.25***

1.88

Present hedonistic

3.45

3.30

1.87

0.26

Present fatalistic

2.90

2.18

9.72***

1.39

Past positive

3.32

3.73

4.43***

0.62

Sample 3 (n = 493)

(n = 262)

(n = 231)

t (491) =

Cohen’s d

Past positive

3.28

3.71

7.76***

0.71

Past negative

3.58

2.51

22.84***

2.07

Present hedonistic

3.49

3.26

4.82***

0.44

Present fatalistic

2.79

2.13

13.24***

1.21

Future

3.38

3.64

5.36***

0.49

Sample 4 (n = 481)

(n = 210)

(n = 271)

t (479) =

Cohen’s d

Past positive

3.21

3.78

10.54***

0.97

Past negative

3.75

2.54

25.74***

2.37

Present hedonistic

3.31

3.07

5.16***

0.46

Present fatalistic

2.80

2.09

15.16***

1.38

Future

3.43

3.75

7.45***

0.69

Cut-off is the approach used by Drake et al. (2008). HCA is the Hierachical Cluster Analysis used by Boniwell et al. (2010)

* p < 0.05; ** p < 0.01; *** p < 0.001

$$ DBTP = \sqrt {(oPN - ePN)^{2} + (oPP - ePP)^{2} + (oPF - ePF)^{2} + (oPH - ePH)^{2} + (oF - eF)^{2} } $$

Stolarski and colleagues argued that the DBTP assumes there is not a threshold for better BTP; instead, the DBTP proposes there is a point on each time perspective at which an individual experiences optimal well-being. Also, when an individual score equally above or below this point, the DBTP is scored the same. That is, what is important in scoring the DBTP is the distance each person is from each optimal value. They defined the optimal value on each time perspective as a score of 4.60 on past positive, 1.95 on past negative, 3.90 on present hedonism, 1.50 on present fatalism, and 4.00 on the future time perspective. Thus, the concern that only a small number of people can meet or exceed the optimal threshold on all five time perspectives—which is a weakness of using the cut-off-point method suggested by Drake et al. (2008)—is not realized when employing the DBTP because, instead of categorizing individuals, each person receives a score for their distance from the optimal time perspective profile.

6 Results

6.1 Correlations Between Time Perspectives and SWB

Consistent with past research, time perspectives are correlated with various SWB constructs (see Tables 1, 2). Across all four samples, we found that those with a past positive, present hedonistic, and future time perspective reported the highest levels of subjective well-being. On the other hand, those with a past negative and present fatalistic time perspective reported the lowest levels of subjective well-being.

6.2 Is having a BTP Predictive of Increased SWB?

Regardless of how a BTP is operationalized, a BTP is characterized by having low scores on the past negative and present fatalism time perspectives while having moderate to high scores on the past positive, present hedonism, and future time perspectives. First, we found that participants categorized as having a BTP using Drake et al.’s method met the above criteria (see Table 3). However, the cluster analysis method (as suggested by Boniwell et al. 2010) only partially met the expected BTP profile (again see Table 3). For example, compared to participants with a non-balanced time perspective, participants categorized as having a BTP scored significantly lower on present hedonism in samples 1, 3 and 4. To examine these previous two operational definitions of a BTP with the DBTP method, we compared the average DBTP scores across the BTP group membership assignments from the Drake et al. and Boniwell et al. methods. Because the DBTP value represents how far an individual’s five time perspectives scores deviate from the five optimal scores (as defined by a BTP), we expect those categorized has having a BTP (by both the Drake et al. and Boniwell et al. methods) would have smaller deviations from the optimal BTP profile (as predicted by Zimbardo and Boyd, 2008). As expected, compared to those categorized as not having a BTP, individuals categorized as having a BTP had smaller deviations from the optimal BTP profile across all four samples.

Next, because individuals are categorized into groups by the Drake et al. and Boniwell et al. methods, we used the more conservative Spearman’s rho correlation coefficient to assess the strength of the relationship between a having a BTP and SWB for all three BTP operationalizations (again, the DBTP score indicates how far an individual is from an optimal BTP—thus, higher scores on the DBTP indicate a less optimal time perspective profile). As demonstrated in Table 4, having a BTP was positively correlated with life-satisfaction, subjective happiness, positive affect (except in Sample 1 and 2 when using the cut-off-approach), and negatively correlated with negative affect (except in Sample 2 when using the cut-off-approach). All these trends were mirrored by the strong negative relations between DBTP and life satisfaction, happiness, positive affect as well as the strong positive relation between DBTP and negative affect. Further, having a BTP was associated with increased psychological need satisfaction, self-determination, vitality, and gratitude (see Table 4 sample 3) while increased DBTP predicted decreased psychological need satisfaction, self-determination, vitality, and gratitude. Importantly, the correlations in Table 4 remained the same when we controlled for gender or age.
Table 4

External Correlations between the three BTP approaches and well-being indicators

 

SWLS

SHS

PA

NA

SWB

    

Sample 1 (n = 562)

 Cut-off

0.17***a

0.21***a

0.05a

−0.10**a

0.18***a

 HCA

0.37***b

0.40***b

0.14**a,b

−0.37***bc

0.44***b

 DBTP

−0.49***c

−0.53***c

−0.21***c

0.41***c

−0.55***c

Sample 2 (n = 200)

 Cut-off

0.19**a

0.16*a

0.01a

−0.13a

0.17*a

 HCA

0.38***b

0.39***b

0.17*a,b

−0.42***b,c

0.45***b

 DBTP

−0.63***c

−0.64***c

−0.35***c

0.47***c

−0.64***c

 

SWLS

SHS

PA

NA

SWB

Psychological needs

Self-determination

Vitality

Gratitude

Sample 3 (n = 493)

 Cut-off

0.14**a

0.16**a

0.10*a

−0.15***a

0.18***a

0.23***a

0.18***a

0.14**a

0.16**a

 HCA

0.41***b

0.39***b

0.27***b

−0.46***bc

0.53***b

0.45***b

0.41***b,c,†

0.37***b

0.38***b

 DBTP

−0.52***c

−0.54***c

−0.39***c

0.48***c

−0.64***c

−0.54***c

−0.48***c

−0.51***c

−0.51***c

Sample 4 (n = 481)

 Cut-off

0.28***a

 HCA

0.52***b

 DBTP

−0.63***c

Correlations with different subscripts are significantly different but correlations with the same subscripts are not significantly different. Cut-off is the approach used by Drake et al. (2008). HCA is the Hierachical Cluster Analysis used by Boniwell et al. (2010). DBTP is deviation from balanced time perspective used by Stolarski et al. (2011). SHS subjective happiness, SWLS satisfaction with life, PA positive affect and NA negative affect. Psychological needs is the average of autonomy, competence and relatedness. SWB subjective well-being is the sum of life satisfaction, positive affect subtract from negative affect. The relations between the DBTP and SWB measures will be in the opposite direction when compared to the cut-off point method and the cluster analysis as the other two methods determined the groups who have a BTP while the DBTP scores individuals on how far they are from an optimal BTP—thus, higher scores on the DBTP indicate a less optimal time perspective. The results were similar whether we controlled for gender and age or not. Therefore, we reported the zero-order correlation here. ‘‘–’’ indicates that data were not available.

* p < 0.05; ** p < 0.01; *** p < 0.001

Guided by the major aim of this study, we further compared the strength of relationships between having a BTP and SWB across the three methods (see Meng et al. 1992, for a review of comparing correlated correlation coefficients). We found the strength of the correlation between having a BTP with life satisfaction, happiness, positive affect, psychological need satisfaction, vitality, and gratitude to be the strongest when operationalized as the DBTP (see Table 4). However, the correlation between a BTP with negative affect and self-determination was not significantly different when operationalized using the Boniwell et al. method or as a DBTP. Overall, however, the results suggest that the DBTP was the strongest correlate with SWB.

6.3 The Unique Variance in SWB Explained by Each BTP Operationalizations

Finally, we tested the unique variance in SWB explained by each BTP operationalization (see Table 5). As expected, the DBTP operationalization was the strongest predictor of SWB in every regression model when compared to the cut-off and the cluster analysis operationalizations. Further, the cut-off approach was not a significant predictor of SWB in any model, while the cluster method approach was only a significant predictor of positive affect (in Samples 1, 2, and 3), negative affect (in Sample 3), and self-determination (in Sample 3). In short, the regression models further supported the fact that the DBTP is a stronger predictor of SWB than the other two methods.
Table 5

Multiple regressions between the three BTP approaches and well-being indicators

 

SWLS

SHS

PA

NA

SWB

    

β

β

β

β

β

β

β

β

β

Sample 1 (n = 562)

 Cut-off

−0.02

0.02

−0.04

0.05

−0.03

 HCA

0.05

0.06

−0.02

−0.16**

0.08

 DBTP

−0.46***

−0.48***

−0.23***

0.31***

−0.52***

Sample 2 (n = 200)

 Cut-off

0.05

0.08

0.10

0.04

−0.09

 HCA

0.07

0.08

0.11*

−0.19*

−0.01

 DBTP

−0.69***

−0.73***

−0.48***

0.36***

−0.69***

 

SWLS

SHS

PA

NA

SWB

PN

SD

Vitality

Gratitude

Sample 3 (n = 493)

 Cut-Off

0.07

−0.06

−0.06

0.04

−0.07

0.02

-0.01

−0.06

−0.04

 HCA

0.09

0.04

0.02

−24***

0.12*

0.17**

0.16**

0.04

0.05

 DBTP

−0.48***

−0.54***

−0.40***

0.33***

−0.55***

−0.42***

−0.37***

−0.51***

−0.49***

Sample 4 (n = 481)

 Cut-off

−0.01

 HCA

0.08

 DBTP

−0.60***

Because of space limitation, we only showed standardized betas from the multiple regressions. There was no multicollinearity issues found. All tolerance and VIF levels met those suggested by Cohen et al. (tolerance value is > 0.10 or VIF is < 10; 2003). Cut-Off is the approach used by Drake et al. (2008). HCA is the Hierarchical Cluster Analysis used by Boniwell et al. (2010). DBTP is deviation from balanced time perspective used by Stolarski et al. (2011). SHS subjective happiness, SWLS satisfaction with life, PA positive affect and NA negative affect, PN psychological needs, SD self-determination. Psychological Needs is the average of autonomy, competence and relatedness. SWB Subjective well-being and is the sum of life satisfaction, positive affect subtract from negative affect

p < 0.05; ** p < 0.01; *** p < 0.001

7 Discussion

Overall, we demonstrated that: (1) time perspectives are strongly correlated with various SWB constructs (replicating Boniwell et al. 2010, Drake et al. 2008, and Zhang and Howell, 2011) and (2) having a BTP is related to increased satisfaction with life, happiness, and positive affect as well as decreased negative affect (replicating Drake et al. 2008 and Boniwell et al. 2010). Mirroring these results, we showed that as an individual’s time perspective profile deviates from the optimal BTP profile (as measured by the DBTP) they experience less satisfaction with life, happiness, and positive affect as well as more negative affect. Further, we extend past work by showing that having a BTP is associated with increased psychological need satisfaction, self-determination, vitality, and gratitude whereas increased deviation from the optimal BTP profile predicts decreased eudaimonic well-being. Most importantly, the DBTP was typically the strongest predictor of SWB and explained more unique variance in SWB when compared to the Boniwell et al. (2010), Drake et al. (2008) methods.

7.1 The Importance of Measuring a Balanced Time Perspective

A reliance on a single time perspective limits one’s ability to meet the situational demands of life and will, most likely, bias how we think, see, and behave (Boniwell and Zimbardo 2004). Not surprisingly, a BTP was proposed by Zimbardo and Boyd (1999) as the most “psychologically and physically healthy for individuals” (p. 1285). Also, the study of an individual’s time perspective profile is crucial to the understanding their SWB (Durayappah 2010). The reasons for these predictions is that individuals with a BTP can reconcile life experiences between temporal states better (Bohart 1993) and can make choices that will maximize their well-being in a given situation. That is, a BTP sustains and amplifies SWB because it enables people to meet the demands of life (e.g., knowing when to enjoy life and when to be goal directed).

However, to accurately test this premise requires a precise measurement of a BTP. Although the cut-off-approach and cluster analysis method are both valid operationalizations of a BTP, as well as positively associated with SWB, these methods have drawbacks. For example, the cut-off-approach (Drake et al. 2008) predicts very few individuals to possess a BTP—this is likely due to the rather strict criteria to be classified as having a BTP. Also, the cluster analysis method does not allow for explicit cross-sample comparisons because it cannot reproduce similar cluster structures in different samples (Boniwell et al. 2010). Therefore, the categorization of people into BTP groups appears rather unconvincing and maybe misleading. It is argued by Stolarski et al. (2011) that a more realistic operationalizations of a BTP is to score individuals for how much they deviate from a BTP. Our results support the DBTP as the best method to operationalize a BTP because the DBTP demonstrates the strongest correlations with SWB. Thus, until a more precise measurement is available, the DBTP is the most accurate measure of BTP.

7.2 Can these Results Clarify Previous Non-Convergent Findings?

It is reasonable to expect non-convergent findings in previous research. For example, Drake et al. (2008) found that present hedonism was negatively correlated with subjective happiness whereas Boniwell et al. (study 2; 2010) and Zhang and Howell (2011) reported a positive correlation between present hedonism and happiness. Further, the current study repeatedly finds a positive correlation between present hedonism and SWB—specifically, we demonstrated that present hedonism is consistently correlated with increased happiness and positive affect (and tended to be correlated with increased life satisfaction as well). Interestingly, the participants in the Drake et al. (2008) study were given a 14-day period to complete the questionnaire whereas data from previous studies (Boniwell et al. 2010; Zhang and Howell 2011) and the current study were collected at one time point. Though we do not suspect this methodological difference to account for the non-convergent finding, it is possible that the differences in methodology may have caused the discrepancy. Therefore, we encourage future research to examine the relation between present hedonism and various SWB constructs by using systematically comparable methods and samples in the same studies.

7.3 Study Strengths and Limitations

If a BTP is an important ingredient to a meaningful life, then we should expect that a BTP predicts different facets SWB. For this reason, we used the measurements of SWB that are consistent with their respective temporal categories argued by the 3P model of SWB (Durayappah 2010). Indeed, the use of both hedonic (i.e., SWLS, SHS) and eudaimonic (i.e., psychological need satisfaction, vitality, and self-determination) well-being supports the conclusion that a BTP may be a major component of human flourishing. We suggest, however, that other measurements which capture various facets of SWB (e.g., see Diener et al. 2010) should be used to further test BTP-SWB link. Also, future research should continue to provide critical assessments of the ZTPI—with a particular focus on how changes in the measurement of time perspectives may impact the measurement of a BTP. Further, we replicated previous studies (Boniwell et al. 2010; Drake et al. 2008; Zhang and Howell 2011) by demonstrating the strong relation between the past positive and past negative time perspectives with SWB. However, what is not clear is whether the distant past or the recent past is what is strongly influencing SWB. We expect that recent life events (as opposed to distant life events) strongly influence the evaluation of subjective well-being (Lucas et al. 2004; Lucas 2005; Suh et al. 1996). One limitation is the use of a convenience sampling strategy in the first three samples. Future research should extend the findings from Sample 4 by recruiting a stratified sample (e.g., stratified on age, gender, and SES). Lastly, the optimal scores used to calculate a DBTP was based on the recommendation from Zimbardo and Boyd (2008). Whether these are true optimal scores should be explicitly tested. Thus, future research is encouraged to “conduct additional exploratory case studies with the aim of developing a working, rather than hypothetical profile of individuals with an optimal or balanced TP” (Boniwell and Zimbardo 2004; p. 174).

8 Conclusion

Are people with a BTP happier than people with a maladaptive time perspective profile? The examination of time perspectives and SWB contributes to our understanding of the fundamental elements of happiness. This study corroborates past research by demonstrating that there is a strong positive relation between a BTP and SWB (also see, Boniwell et al. 2010; Drake et al. 2008). Thus, the study of subjective time demonstrates that happiness is associated with the relative importance and emotional valence people assign to their past, present, and future.

Copyright information

© Springer Science+Business Media B.V. 2012