Time Perspective in Hereditary Cancer: Psychometric Properties of a Short Form of the Zimbardo Time Perspective Inventory in a Community and Clinical Sample

Abstract

Aims: We aimed to assess the psychometric properties of a 25-item short form of the Zimbardo Time Perspective Inventory in a community sample (N = 276) and in individuals with a strong family history of cancer, considering genetic testing for cancer risk (N = 338). Results: In the community sample, individuals with high past-negative or present-fatalistic scores had higher levels of distress, as measured by depression, anxiety, and aggression. Similarly, in the patient sample, past-negative time perspective was positively correlated with distress, uncertainty, and postdecision regret when making a decision about genetic testing. Past-negative-oriented individuals were also more likely to be undecided about, or against, genetic testing. Hedonism was associated with being less likely to read the educational materials they received at their clinic, and fatalism was associated with having lower knowledge levels about genetic testing. Conclusions: The assessment of time perspective in individuals at increased risk of cancer can provide valuable clinical insights. However, further investigation of the psychometric properties of the short form of this scale is warranted, as it did not meet the currently accepted criteria for psychometric validation studies.

Introduction

Time perspective is the process whereby personal and social experiences are assigned to temporal categories (or time frames) that help give meaning to those experiences (Zimbardo and Boyd, 1999). Time perspectives are used to form expectations and goals and can influence people's decisions and actions. The Zimbardo Time Perspective Inventory (ZTPI) is a 56-item self-report measure of individuals' time perspectives (Zimbardo and Boyd, 1999). Since its development, the ZTPI and its predecessor, the Stanford Time Perspective Inventory, have been used in various research settings, including studies that investigated the relationships between time perspective and self-efficacy (Zimbardo and Boyd, 1999), resilience (Chubick et al., 1999; Covas, 2000), gambling (Hodgins and Engel, 2002; Wassarman, 2002), sleep problems (Vranesh et al., 1999), suicidal ideation (Laghi et al., 2009), and academic achievement (Mello and Worrell, 2006). The ZTPI has been used less frequently in health-related fields such as in individuals with a strong family history of cancer. In clinical areas such as familial cancer, the concept of time perspective may provide some interesting insights into the issues and concerns of individuals concurrently considering their family history of cancer, and their current symptoms and experiences, as well as having to make decisions about managing their future risk of developing cancer.

The ZTPI provides a score on five factors: past-negative, past-positive, present-hedonistic, present-fatalistic, and future. Past-oriented individuals are focused on family, tradition, and history (Boniwell and Zimbardo, 2003). High scores on the past-negative scale generally reflect individuals who experience pain and regret when thinking of the past. In contrast, a high score on the past-positive scale reflects a warm, sentimental view of the past. In terms of the two present-time perspectives, a high score on the present-hedonistic scale represents a risk-taking attitude toward life, whereas a high score on the present-fatalistic scale reflects feelings of hopelessness and a lack of autonomy, or control, over life. The future scale represents general future orientation. High scores on this scale are associated with strong goals and a willingness to sacrifice immediate pleasures to receive larger rewards later (Zimbardo and Boyd, 1999). Researchers have hypothesized that individuals who are able to balance their past experiences, present desires, and the possible future consequences are best placed to make a good decision in response to situational demands (Boniwell and Zimbardo, 2003). Therefore, an ideal mental framework would obtain a balanced score on each of the five factors of the ZTPI, rather than having a particularly high score on one dimension (Boniwell and Zimbardo, 2003).

With respect to decision making about health-related issues, previous studies have investigated the relationship between time perspective and health behavior and shown that high scores on both the present-fatalistic and present-hedonistic scales are associated with risky driving (Zimbardo et al., 1997), having more frequent sexual encounters, exhibiting risky sexual behaviors (Rothspan and Read, 1996; Hamilton et al., 2003), and using drugs and alcohol (Keough et al., 1999; Wills et al., 2001). The present-hedonistic scale appears to be the best predictor of risky health behaviors independent of the other time perspectives. Henson and colleagues (2006), for example, found that hedonism correlates positively with alcohol and drug use and increased number of sexual partners. Although fatalism was not strongly predictive of health behavior, it was related to reduced use of seat belts, smoking, and riskier sexual behavior in men (Henson et al., 2006).

Future-oriented individuals, on the other hand, appear more likely to engage in protective health behavior. For example, future time perspective has been shown to be related to increased exercise, condom use, and oral contraceptive use in females (Henson et al., 2006). Moreover, future perspective scores have been shown to be negatively correlated with drug and alcohol use (Apostolidis et al., 2006b; Henson et al., 2006) and smoking (Henson et al., 2006; Adams and Nettle, 2009), suggesting that the scale can predict both healthy and risky health behaviors.

The ZTPI has previously been reported to have acceptable internal consistency (with Cronbach's alpha coefficients for each scale ranging from 0.74 to 0.82) and test-retest reliability (with scores ranging from 0.70 through 0.80 across a 4-week test-retest period), as well as acceptable levels of convergent, divergent, and predictive validity (Zimbardo and Boyd, 1999). The original exploratory factor analysis for this scale reported that the five ZTPI factors explained 36% of the total variance of the scale, the χ²/degrees of freedom ratio was reported as 2.30, and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy of 0.83 (Zimbardo and Boyd, 1999). Although the psychometric properties of the 56-item version of this scale have now been established, in some clinical settings the patients may be faced with several lengthy questionnaires while also coping with potentially reduced levels of concentration and energy caused by their condition or treatment. It is possible that completing all 56 items of the ZTPI may pose an unnecessary burden on patients and research participants if a shorter form of the inventory could be used without negatively affecting its psychometric properties. Thus, this study aimed to assess the psychometric properties of a shorter, 25-item version of the ZTPI first in an Australian community sample (study 1) and then in a sample of individuals with a strong family history of cancer, considering genetic testing for cancer risk (study 2).

Study 1

Materials and methods

The short form of the ZTPI was created by extracting the 25 items with the highest factor loadings in the original inventory, such that each factor was represented by five items (see Table 1 for a list of retained items). The inventory developers kindly provided the factor loading information from data collected using 606 Stanford University students during the original validation study (Zimbardo and Boyd, 1999). As Levy (1967) has noted, however, the creation of a short form of a scale in this manner may lead to the selection of a more homogeneous group of items than in the original scale.

Table 1.

Factor Structure of the Zimbardo Time Perspective Inventory Short-Form

		Factor ^a
Item no.	Actual item	1	2	3	4	5
Past-negative
1	I often think of what I should have done differently in my life.	0.581	0.102	—	—	—
		0.573	—	—	—	−0.134
9	Painful past experiences keep being replayed in my mind.	0.812	—	—	—	—
		0.738	—	—	—	—
15	It's hard for me to forget unpleasant images of my youth.	0.737	—		—
		0.501	—	−0.202	−0.199	0.133
22	I think about the bad things that have happened to me in the past.	0.841	—	—	—	—
		0.677	—	—	−0.104	—
25	I think about the good things that I have missed out on in my life.	0.543	—	—	—	—
		0.611	—	—	—	—
Past-positive
2	It gives me pleasure to think about my past.	−0.325	—	—	0.690	—
		−0.163	—	0.121	0.731	—
5	On balance, there is much more good to recall than bad in my past.	−0.468	0.152	0.111	0.404	0.154
		−0.304	—	0.131	0.466	0.204
8	I enjoy stories about how things used to be in the “good old times.”	—	—		0.444	—
		0.129	—	−0.232	0.479	—
10	Happy memories of good times spring readily to mind.	−0.221	—	—	0.584	0.158
		−0.189	—	—	0.552	—
13	I get nostalgic about my childhood.	0.155	—	—	0.512	—
		0.162	—	—	0.343	—
Present-hedonistic
3	I do things impulsively.	0.108	0.460	—	0.120	−0.243
		—	0.555	—	—	—
11	I make decisions on the spur of the moment.	—	0.477	—	0.149	−0.255
		—	0.538	—	—	−0.174
12	It is important to put excitement in my life.	—	0.543	—	0.227	—
		—	0.574	—	0.113	—
14	Taking risks keeps my life from becoming boring.	—	0.778	—	0.224	—
		—	0.779	—	—	0.153
20	I take risks to put excitement in my life.	—	0.839	—	−0.180	—
		—	0.709	—	—	—
Future
4	When I want to achieve something, I set goals and consider specific means for reaching those goals.	—	0.115	0.119	—	0.603
		—	0.148	0.107	0.103	0.608
6	Meeting tomorrow's deadline and doing other necessary work comes before tonight's play.	—	−0.104	—	—	0.597
		—	—	—	—	0.452
19	I complete projects on time by making steady progress.	—	—	—	—	0.639
		—	—	—	0.102	0.593
21	I am able to resist temptations when I know that there is work to be done.	−0.176	—	—	—	0.584
		—	—	—	—	0.392
23	I keep working at difficult uninteresting work if it will help me get ahead.	0.234	—	—	—	0.435
		0.219	—	—	—	0.290
Present-fatalistic
7	Since whatever will be, will be, it doesn't really matter what I do.	—	—	−0.637	0.102	−0.137
		—	—	−0.489	0.154	—
16	You can't really plan for the future because things change so much.	—	0.156	−0.477	—	−0.128
		—	0.111	−0.425	—	—
17	My life path is controlled by forces I cannot influence.	—	—	−0.695	—	—
		—	—	−0.753	—	—
18	It doesn't make sense to worry about the future, since there is nothing that I can do about it anyway.	—	−0.101	−0.717	—	—
		−0.187	—	−0.818	—	—
24	Often luck pays off better than hard work.	0.186	0.174	−0.228	—	−0.183
		0.282	0.135	−0.141	0.221	—

Community sample loadings are given in top line, followed by the patient sample loadings below. Factor pattern matrix: loadings on factors <0.1 were suppressed and therefore not presented in the table.

Participants received an invitation to complete an online survey using an e-mail snowballing technique. The e-mail invitation included a description of the study and the URL link to the survey. A monthly $50 gift voucher draw was offered as an incentive to participate. Participants provided their e-mail addresses in the survey, and these were stored on a secure server, separate from their questionnaire responses. Fourteen days after completion of the first survey, an automated e-mail was sent to remind participants to complete the second survey. A 14-day retest interval was selected because it was long enough for participants to forget the details of the questionnaire, yet short enough to reduce the likelihood of bias introduced by significant life events in the interval between questionnaires.

All participants met the following eligibility criteria: (i) were able to give informed consent, (ii) were able to read English proficiently, and (iii) were aged 18 years or older. The human research ethics committee of Macquarie University approved the study and both studies were carried out in accordance with universal ethical principles (Emanuel et al., 2000).

Questionnaire 1 included the following items:

(1) Demographic characteristics: Data on age, educational level, previous medical or health training, marital status, and having had a previous diagnosis of cancer were collected.

(2) ZTPI short-form (25 items) (Table 1): The ZTPI asks respondents to indicate how characteristic a statement is of them on a five-point Likert scale. Response options range from “very uncharacteristic” to “very characteristic.”

(3) Depression Anxiety and Stress Scale (DASS) (21 items): The DASS measures current symptoms of depression, anxiety, and stress and has well-documented psychometric properties (Lovibond and Lovibond, 1995). Respondents complete a four-point severity/frequency scale, with response options ranging from “did not apply to me at all” to “applied to me very much.”

(4) Aggression Questionnaire (29 items): This measures four subtypes of aggression (physical aggression, verbal aggression, anger, and hostility) (Buss and Perry, 1992). The questionnaire asks respondents to rate each item on a scale of 1 = “extremely uncharacteristic of me” to 5 = “extremely characteristic of me.”

(5) Minnesota Multiphasic Personality Inventory (MMPI)-based Sensation Seeking Scale (18 items): This scale is based on the widely known Zuckerman Sensation Seeking Scale (Zuckerman, 1979). It has similar psychometric properties to the Zuckerman scale and asks respondents to state whether each item is “true” or “false” when describing themselves. Items marked as “true” are summed to give the sensation seeking score (Viken et al., 2005).

Questionnaire 2 included the following items:

(1) ZTPI short-form (25 items).

(2) Consideration of future consequences scale (12 items): This scale assesses the extent to which individuals consider distant versus immediate consequences of their behavior (Petrocelli, 2003). Participants respond to each item using a five-point scale ranging from “extremely uncharacteristic” to “extremely characteristic.”

(3) Self-esteem scale (10 items): The Rosenberg Self-Esteem Scale assesses individuals' perceived self-esteem by asking respondents if they agree or disagree with a list of statement about themselves (Rosenberg, 1965). Response options range from “strongly disagree” to “strongly agree.”

(4) Preference for consistency scale (PFC-B) (9 items): The brief form of this scale assesses individuals' preferences for stability and predictability. It asks participants to respond on a nine-point scale ranging from 1 = “strongly disagree” to 9 = “strongly agree.”

Data analysis

Data were analyzed using SPSS (SPSS Inc., 2005) and AMOS (Amos Development Corporation, 2003). The factor structure of the ZTPI was examined with confirmatory factor analysis (CFA) using maximum likelihood estimation procedures and oblique rotation. CFA is a structural equation modeling technique used to determine the goodness of fit between a hypothesized model and the sample data. CFA was selected because it facilitates the identification and measurement of the relationship between latent variables and allows for greater analysis of the causal effects between the identified latent variables (Kline, 1998). Exploratory factor analyses were also conducted, and the results are presented in Tables 1 and 2 Table 3 reports the χ²/degrees of freedom ratio for each study; however, as relying solely on this ratio is not recommended (Wheaton, 1987), the following additional goodness-of-fit indices were used to assess the degree of fit between the model and the sample: the Root Mean Square Error of Approximation (RMSEA), the Comparative Fit Index (CFI), and the Tucker Lewis Index (TLI). Convergent validity was established by examining the correlations between the ZTPI scales and other measures of similar constructs. Discriminant validity was investigated by confirming nonsignificant correlations between the ZTPI scales and measures that are not theoretically related to the scale in question.

Table 2.

Factor Correlation Matrix

Factor	1	2	3	4	5
1	1.000	0.72	−0.279	−0.092	−0.096
	1.000	0.118	−0.331	−0.084	0.020
2	0.072	1.000	−0.102	0.149	−0.326
	0.118	1.000	−0.221	0.152	0.221
3	−0.279	−0.102	1.000	0.074	0.282
	−0.331	−0.221	1.000	−0.103	0.064
4	−0.092	0.149	0.074	1.000	−0.054
	−0.84	0.152	−0.103	1.000	0.122
5	−0.096	−0.326	0.282	−0.054	1.000
	0.020	−0.085	0.064	0.122	1.000

Community sample loadings are given in top line, followed by the patient sample loadings below.

Table 3.

Confirmatory Factor Analysis Goodness-of-Fit Indices for Studies 1 and 2

	Study 1: Community sample	Study 2: Patient sample	Combined results of both studies
No. of complete datasets	276	331	597
χ² (DF)	572.7 (264)	589.9 (264)	871.9 (264)
Ratio: χ²/DF	2.2	2.27	3.3
RMSEA	0.065	0.062	0.062
	(90% CI: 0.058-0.073)	(90% CI: 0.055-0.069)	(90% CI: 0.052-0.068)
CFI	0.857	0.831	0.848
TLI	0.837	0.808	0.827

Model allowed covariance between items 3 (“I do things impulsively”) and 11 (“I make decisions on the spur of the moment”).

DF, degrees of freedom; RMSEA, Root Mean Square Error of Approximation; CFI, Comparative Fit Index; TLI, Tucker Lewis Index; CI, confidence interval.

Results

Characteristics of the sample

A total of 276 respondents (89 men and 187 women) completed questionnaire 1, and 253 (91.7%) of them completed both questionnaires. Table 4 outlines their demographic characteristics. There were no significant demographic or medical differences between respondents who completed both questionnaires, compared with those who completed only the first questionnaire. The mean age of the respondents was 35.4 years (standard deviation = 12.2). Women tended to score higher than men on the future scale, although this was not statistically significant (t = −1.95; p = 0.053). Educational level was significantly related to future scores, with participants with university qualifications having the highest future scores [F(4272) = 2.78; p = 0.027]. Age was significantly positively correlated with future score (r = 0.21; p < 0.001) and negatively correlated with past-positive (r = −0.15; p = 0.014), past-negative (r = −0.20; p = 0.001), present-hedonistic (r = −0.26; p < 0.000), and present-fatalistic scores (r = −0.143; p = 0.017). There was a significant difference in present-hedonistic and future scores by marital status, such that individuals who were “divorced” or “never married” had the highest present-hedonistic scores and individuals who were “married” had the highest future scores [F(6269) = 2.67; p = 0.016; F(6269) = 2.81; p = 0.011, respectively]. There were no significant differences between individuals with a previous diagnosis of cancer and those unaffected by cancer on any of the ZTPI short-form scales.

Table 4.

Demographic Characteristics of Participants in Studies 1 (Community Sample) and 2 (Patient Sample)

	Study 1	Study 2
	N = 276	N = 338
	n (%)	n (%)
Gender
Male	89 (32.2)	42 (12.4)
Female	187 (67.8)	296 (87.6)
Age
Mean (SD)	35.4 (12.2)	49.4 (12.9)
Range	18-68	18-86
Education level
High school only	41 (14.9)	111 (33.0)
Certificate/diploma	43 (15.6)	105 (31.2)
Undergraduate degree	107 (38.8)	61 (18.1)
Postgraduate degree	85 (30.8)	60 (17.8)
Medical/health training?
No	190 (68.8)	260 (76.9)
Yes	86 (31.2)	78 (23.1)
Marital status
Never married	114 (41.3)	40 (11.9)
Married/de facto	140 (50.7)	244 (72.6)
Widowed	2 (0.7)	10 (3.0)
Separated/divorced	20 (7.2)	40 (11.9)
Strong family history of cancer
Breast/ovarian	7 (2.5)	235 (69.5)
HNPCC^a	1 (0.4)	103 (30.5)
Disease status
Personal cancer diagnosis	14 (5.1)	200 (59.2)
Unaffected by cancer	262 (94.9)	138 (40.8)

HNPCC refers to hereditary nonpolyposis colorectal cancer, the most commonly reported hereditary colorectal cancer syndrome, which is otherwise known as Lynch syndrome.

SD, standard deviation.

ZTPI dimensionality and intercorrelations between scales

The CFA procedure showed that the basic five-factor structure of the model and the χ²/degrees of freedom ratio were in line with previously reported data (Zimbardo and Boyd, 1999; Apostolidis and Fieulaine, 2004). However, the model failed to reach the currently accepted criteria for good fit in covariance structure analyses. For example, Hu and Bentler (1999) recommended a cutoff value of >0.95 for the TLI and CFI indices and <0.06 for the RMSEA index. Table 3 presents the results for the CFA of a model in which the errors of items 3 (“I do things impulsively”) and 11 (“I make decisions on the spur of the moment”) were allowed to covary, which seemed a reasonable relaxation, as they appear to be extremely similar items. As can be seen, the RMSEA index was close to the value recommended by Hu and Bentler (1999) but, at 0.84 and 0.86, the TLI and CFI were far below the recommended value of 0.95.

Further investigation of the data revealed no range restrictions but showed that overall, inter-item correlations were quite low (absolute values ranged from 0.001 to 0.722, with a median of 0.12), which may have contributed to the less than satisfactory CFA results. It is worth noting that the Kaiser-Meyer-Olkin measure of sampling adequacy was 0.76, in the “middling” range (Kaiser, 1974), and that the first five unrotated factors in a principal components analysis accounted for 54% of the variance of the variables. Removing the worst performing items and changing the factor structure to include six factors (with items 3 and 11 forming their own latent factor: “impulsivity”) did not significantly improve the results.

Table 5 shows Cronbach's alpha and item total correlation coefficients. Internal consistency coefficients were acceptable for the five scales of the ZTPI short-form for the community sample, although the alpha coefficient for the past-positive scale was marginal at 0.69. These figures are consistent with those reported elsewhere (Zimbardo and Boyd, 1999; Apostolidis et al., 2006a). Each scale was found to be relatively homogeneous, with satisfactory correlations between each item and total scores. Test-retest reliability of subjects' responses was calculated by correlating the score on administration of the ZTPI short-form in questionnaire 1 with scores obtained when the scale was readministered after 14 days. Pearson and intraclass correlation coefficients and difference scores were calculated to explore the extent of agreement of scores from one occasion to another and showed that the ZTPI short-form has acceptable test-retest reliability (Table 6).

Table 5.

Item Total Correlation Coefficients and Cronbach's Alpha Coefficients for Each Zimbardo Time Perspective Inventory Scale for Studies 1 (Community Sample) and 2 (Patient Sample)

		Study 1	Study 2
Past-negative scale	Scale total Cronbach's α	0.83	0.76
Item total correlation coefficients	Item 1	0.53	0.43
	Item 9	0.71	0.62
	Item 15	0.68	0.47
	Item 22	0.74	0.64
	Item 25	0.51	0.49
Present-hedonistic scale	Scale total Cronbach's α	0.79	0.77
Item total correlation coefficients	Item 3	0.57	0.54
	Item 11	0.59	0.54
	Item 12	0.45	0.43
	Item 14	0.56	0.60
	Item 20	0.65	0.57
Future scale	Scale total Cronbach's α	0.72	0.59
Item total correlation coefficients	Item 4	0.48	0.42
	Item 6	0.54	0.36
	Item 19	0.55	0.44
	Item 21	0.49	0.30
	Item 23	0.36	0.23
Past-positive scale	Scale total Cronbach's α	0.69	0.62
Item total correlation coefficients	Item 2	0.63	0.57
	Item 5	0.42	0.38
	Item 8	0.33	0.30
	Item 10	0.52	0.43
	Item 13	0.34	0.25
Present-fatalistic scale	Scale total Cronbach's α	0.71	0.69
Item total correlation coefficients	Item 7	0.55	0.42
	Item 16	0.49	0.38
	Item 17	0.52	0.64
	Item 18	0.48	0.53
	Item 24	0.33	0.25

Table 6.

Mean Scores, Ranges, Standard Deviations, Intercorrelations, and Test-Retest Statistics

Measure	Mean (range)	SD	PN	PH	F	PP	Test-retest reliability ^a
Study 1 (community sample) (N = 275)
PN	2.60 (1.0-4.8)	0.85	—	—	—	—	0.81 (0.89)
PH	3.06 (1.2-5.0)	0.76	0.07	—	—	—	0.74 (0.92)
F	3.47 (1.2-5.0)	0.72	−0.15^b	−0.37^c	—	—	0.83 (0.90)
PP	3.53 (1.4-5.0)	0.64	−0.37^c	0.10	−0.05	—	0.81 (0.89)
PF	2.27 (1.0-4.0)	0.63	0.34^c	0.27^c	−0.33^c	−0.10	0.77 (0.87)
Study 2 (patient sample) (N = 338)
PN	2.48 (1.0-4.6)	0.82	—	—	—	—	—
PH	2.99 (1.0-5.0)	0.76	0.13^b	—	—	—	—
F	3.48 (1.4-5.0)	0.62	0.02	−0.05	—	—	—
PP	3.61 (1.8-5.0)	0.61	−0.18^c	0.09^b	0.14^b	—	—
PF	2.59 (1.0-4.6)	0.74	0.31^c	0.26^c	−0.04	0.13^b	—

p-Values were <0.001 for all scales; Pearson correlation coefficient (intraclass correlation coefficient) is reported.

p < 0.05.

p < 0.01.

PN, past-negative; PH, present-hedonistic; F, future; PP, past-positive; PF, present-fatalistic.

Table 6 presents the descriptive statistics and intercorrelations for each ZTPI scale. Several scales correlate strongly, as has been reported previously (Zimbardo and Boyd, 1999; Apostolidis et al., 2006a).

Psychological outcome variables

Because of the skewed distribution of scores on several variables (particularly the DASS scores, which were negatively skewed, and the self-esteem score, which was positively skewed), nonparametric (Spearman's rho) correlations were calculated between ZTPI scores and the other measures, as shown in Table 7. As expected, past-negative scores were positively correlated with depression, anxiety, and aggression. Present-hedonistic scores were positively correlated with sensation seeking. Future scores were positively correlated with consideration of future consequences and preference for consistency. Past-positive scores were positively correlated with self-esteem. Finally, present-fatalistic scores were positively correlated with depression, anxiety, and aggression.

Table 7.

Spearman's Rho Correlations Between the Zimbardo Time Perspective Inventory Short-Form and Other Measures

	Past-negative	Present-hedonistic	Future	Past-positive	Present-fatalistic
Study 1
DASS: Depression	0.48^a	−0.13^b	−0.23^a	−0.21^a	0.34^a
DASS: Anxiety	0.29^a	0.03	−0.15^b	−0.10	0.27^a
DASS: Stress	0.45^a	0.07	−0.04	−0.19^a	0.16^a
Aggression	0.42^a	0.27^a	−0.16^a	−0.12	0.29^a
Sensation seeking	0.02	0.50^a	−0.25^a	0.16^a	0.14^b
Consideration of future consequences	−0.10	−0.24^a	0.50^a	0.05	−0.44^a
Self-esteem	−0.54^a	−0.05	0.15^a	0.33^a	−0.40^a
Preference for consistency	0.07	−0.22^a	0.26^a	0.03	−0.09
Study 2
Read the materials	0.03	−0.14^a	0.06	0.04	0.03
HADS: Depression	0.35^a	−0.08	0.02	−0.17^a	0.13^b
HADS: Anxiety	0.44^a	−0.06	0.05	−0.18^a	0.04
IES: Avoidance	0.28^a	0.03	0.09	−0.07	0.10
IES: Intrusion	0.32^a	0.03	0.10	−0.06	0.10
DCS: Decisional conflict	0.25^a	−0.05	−0.08	−0.11^b	0.15^a
Knowledge about testing	−0.05	−0.05	0.02	−0.01	−0.23^a
Regret	0.15^a	−0.09	0.00	−0.13^b	−0.01

Significant at p < 0.01.

Significant at p < 0.05.

DASS, Depression Anxiety and Stress Scale; HADS, Hospital Anxiety and Depression Scale; IES, Impact of Event Scale; DCS, Decisional Conflict Scale.

Discussion

Our findings suggest that the assessment of time perspective may be a useful strategy to predict psychological distress in Australian adults. However, given the poor CFA results in this sample it is difficult to make conclusive statements about the validity of each of the scales in the short form of the ZTPI used in this study. Our findings suggest that individuals who score highly on the past-negative and present-fatalistic scales may be more likely to report higher levels of depression, anxiety, and aggression. Given the cross-sectional nature of the correlations presented in this study, these findings may represent a true relationship between past-negativity and psychological distress, or may also reflect a common personality trait underlying both measures, that is, negative affectivity. Indeed, previous studies have demonstrated a strong relationship between negative affectivity and both depression and past-negative time perspective (Keough et al., 1999; Boniwell and Zimbardo, 2003). Future studies further teasing out these issues are required before conclusive statements can be made regarding the relationship between past-negative time perspective and psychological distress.

Present-hedonistic scores were positively correlated with sensation seeking, and both types of present-oriented individuals tended to be less educated, younger, and divorced or never married. Future scores were positively correlated with consideration of future consequences and preference for consistency, and congruent with previous research, high scores on the future scale were associated with having post-school educational qualifications, being older, and being married (Zimbardo et al., 1997). Past-positive scores were positively correlated with self-esteem. Having had a previous diagnosis of cancer did not appear to affect individuals' time perspective. Reliability analyses showed evidence of satisfactory test-retest reliability and internal consistency across the five scales of the ZTPI short-form; however, significant concerns remain about the factor structure of the scale in this population.

Study 2

To broaden the findings in study 1, we investigated the usefulness of the ZTPI short-form in 338 individuals with a strong family history of breast/ovarian cancer or hereditary nonpolyposis colorectal cancer. To our knowledge, the ZTPI has not been used in this group of individuals for whom decision-making about health behavior is of critical importance. In many countries, individuals with a strong family history of cancer are able to have a genetic test to determine whether or not they are at increased risk of developing cancer. Those identified as being at high risk are able to reduce their chance of developing cancer through the increased use of screening and preventative measures (Scheuer et al., 2002; Wise and Mutch, 2005).

Hypotheses

We hypothesized the following points:

(1) Individuals with high past-negative scores would feel threatened by their family history of cancer and therefore would experience greater emotional distress and uncertainty while considering genetic testing, plus increased postdecision regret.

(2) Individuals with high present-hedonistic and present-fatalistic scores would be less inclined to consider their future health and therefore less likely to read information regarding their family history of cancer.

(3) Individuals with high future scores would be most interested in genetic testing, given these individuals' focus on their future world.

Materials and methods

Participants in this study were recruited as part of a larger study evaluating decision aids for individuals considering genetic testing for cancer risk. A detailed description of the recruitment procedures can be found in the article by Wakefield et al. (2007b). Briefly, participants were recruited to the study at the end of their first genetic counselling consultation at one of six familial cancer clinics in Australia and were given their first study questionnaire. It was not possible to readminister the ZTPI short-form at 14 days after receipt of the first questionnaire; therefore, test-retest reliability was not assessed in this sample. Six months postconsultation, a second questionnaire was mailed to participants.

Participants met the following eligibility criteria: (i) able to give informed consent, (ii) able to read English proficiently, (iii) aged 18 years or older, and (iv) eligible for genetic testing for cancer risk (Australian Cancer Network, 1999; National Breast Cancer Centre, 2000).

Questionnaire 1 included the following items:

(1) ZTPI short-form (25 items): As described in study 1.

(2) Demographic characteristics: As described in study 1.

(3) Having read the information provided: Participants were asked to rate how thoroughly they read the information materials they received at the familial cancer clinic consultation (five response options included “from cover to cover,” “very thoroughly,” “briefly,” “just the relevant parts for me,” and “not at all”).

(4) Decisional conflict: The Decisional Conflict Scale was used to assess uncertainty about choosing among alternatives and feeling uninformed, unclear about personal values, and unsupported in decision making (O'Connor et al., 1998). The scale has satisfactory reliability and validity (O'Connor, 1995).

(5) Knowledge of genetic testing: Eight true-false items assessed knowledge about the genetic testing process and the benefits, risks, and limitations of genetic testing. All items had been previously pilot tested (Wakefield et al., 2007b).

(6) Impact of Event Scale: The 15-item Impact of Event Scale was used to measure the frequency and severity of intrusive and avoidant thoughts about being at risk of developing cancer (Horowitz et al., 1979). The scale has good internal consistency and test-retest reliability in women at increased risk of hereditary breast cancer (Thewes et al., 2001).

(7) Hospital Anxiety and Depression Scale: This 14-item scale requires respondents to choose between four responses that most closely describe how they have been feeling in the past week (Zigmond and Snaith, 1983). The scale has two dimensions: anxiety and depression. It has high internal consistency and good reliability in cancer patients (Ibbotson et al., 1994; Hall et al., 1999; Johnston et al., 2000).

(8) Decision about genetic testing: Participants were asked about their current decision about genetic testing, with the following response options: “undecided,” “having the genetic test,” and “not having the test.”

The second questionnaire included the following items:

(1) Decision about genetic testing: Participants were asked about their final decision about genetic testing, with the following response options: “undecided,” “had the genetic test,” and “did not have the test.”

(2) Decision Regret Scale: This 5-item scale assesses the level of healthcare decision regret and has been shown to have good internal consistency and validity (Brehaut et al., 2003).

Data analysis

Data were analyzed as described in study 1.

Results

Characteristics of the sample

A total of 338 respondents completed questionnaire 1, and 310 (91.7%) of them completed the second questionnaire after 6 months. There were no significant demographic or medical differences between respondents who completed both questionnaires, compared with those who completed only one questionnaire. A total of 266 (78.7%) participants completed the regret scale, as 44 participants were yet to make a decision about genetic testing and so could not answer the regret scale questions. The mean age of the respondents was 49.4 years (standard deviation = 12.9). Table 4 outlines their demographic characteristics. Approximately 60% of the sample had a previous personal diagnosis of cancer, and the remaining 40% had a strong family history of the disease. No significant gender differences on the ZTPI short-form scales were found. Educational level was significantly related to the present-fatalistic scale, with individuals with no postschool qualifications having the highest present-fatalistic scores [F(4324) = 7.76; p < 0.001]. Age was significantly positively correlated with future score (r = 0.12; p = 0.024) and negatively correlated with present-hedonistic score (r = −0.20; p < 0.001). There were no significant differences in ZTPI short-form scores according to marital status. Whether or not the participant had a previous diagnosis of cancer did not impact on ZTPI scores.

ZTPI dimensionality and intercorrelations between scales

As in study 1, the basic five-factor structure of the model and the χ²/degrees of freedom ratio were in line with previously reported data, but the model failed to reach the strict criteria of CFA. Again, further data analysis did not reveal any clear problems with the dataset (inter-item correlations ranged from 0.00 to 0.69, with a median of 0.09; KMO = 0.77; and the first five components accounted for 53.4% of the variance). Columns 3 and 4 of Table 3 present the relevant CFA data for the patient sample and also the data from both studies combined.

Table 5 shows Cronbach's alpha and item total correlation coefficients. Internal consistency coefficients for the five scales of the ZTPI short-form were not as strong as those reported for study 1, with the alpha coefficients for the future, past-positive, and present-fatalistic scales being marginal. Each scale was found to be relatively homogeneous with satisfactory correlations between item and total scores. Three items had an item total correlation coefficient of less than 0.30 (items 23, 13, and 24). We inspected all correlations, scatter plots, and distributions for these items and found that there were no noticeable statistical problems with these items. Potentially, these items may have less relevance in the context of hereditary cancer, especially item 24 (“Often luck pays off better than hard work”); individuals with a family history of cancer are likely to have a different perspective on the relationship between luck and hard work in the face of a potential genetic fault running in their family. Table 6 presents the descriptives and intercorrelations for each ZTPI scale, and as in study 1, several scales correlate strongly.

Psychological outcome variables

As predicted in hypothesis 1, past-negative scores were positively correlated with anxiety, depression, intrusion, avoidance, decisional conflict, and regret (Table 7). In partial support of hypothesis 2, hedonism was negatively correlated with how thoroughly the participant read the materials they received at their clinic. Contrary to hypothesis 2, present-fatalistic scores were not related to how thoroughly participants read their information materials, although participants with high present-fatalistic scores had lower genetic testing knowledge scores, higher levels of depression, and decisional conflict. Contrary to hypothesis 3, future scores were not significantly correlated with any of the measures assessed in this study. Interestingly, past-positive scores appeared related to more positive psychological outcomes, with significant negative correlations between scores on this scale and anxiety, depression, decisional conflict, and regret.

Decision about genetic testing

ZTPI scale scores were transformed into dichotomous variables for the purposes of this analysis (by dividing each scale at the median to determine those categorized as “high” or “low” for each ZTPI scale). Overall, over 90% of the sample reported that they had decided to undergo genetic testing and this remained stable over time. There was a significant difference in genetic testing uptake according to past-negative score. Immediately after their consultation, individuals with high past-negative scores were significantly more likely to be undecided about testing (10.4%) or to have decided against testing (4.3%), compared with those with low past-negative scores (5.4% undecided and 0.0% against testing) [χ²(3327) = 9.61; p = 0.010]. This difference was not significant at 6 months after the consultation, although it remained in the same direction [7.1% undecided and 6.1% against testing in high past-negative group, compared with 6.2% undecided and 0.9% against testing in low past-negative group; χ²(3327) = 4.63; p = 0.099]. There were no significant differences in genetic testing uptake according to scores on the remaining four scales.

Discussion

Taking into consideration the poor CFA results for this study, the findings of study 2 suggest that familial cancer clinic patients who have high past-negative scores on the ZTPI short-form may be at increased risk of emotional distress when considering genetic testing for cancer risk. As hypothesized, scores on the past-negative scale were significantly correlated with depression, anxiety, avoidance, intrusion, decisional conflict, and regret, suggesting that patients who score highly on the past-negative scale may require additional emotional support during genetic counseling. As discussed in study 1, however, these results may reflect a common underlying dimension of individual negative affectivity and these relationships need to be further investigated before conclusive statements can be made regarding the support needs of this population. As well, past-negative-oriented participants were more likely to report being undecided about, or against, genetic testing immediately after their consultation with the familial cancer clinic. Possibly, past-negative-oriented individuals feel more threatened by their family history of cancer, making them less inclined to engage in the genetic testing process, which necessarily requires an in-depth analysis of their own and their family's past cancer experiences. Further, one of the primary values of genetic testing is to determine an individual's risk of developing cancer and therefore assist them to make plans regarding managing that risk. Individuals with a past-negative orientation may be less interested in planning future healthcare strategies and thus see less value in the genetic testing process. Further studies investigating the possible usefulness of the past-negative scale as a predictor of emotional distress in medical situations would be worthwhile, particularly in the genetics setting where patients' family histories are critical to their decision-making processes.

Complementing the past-negative findings, past-positive-oriented individuals were less likely to report high levels of depression, anxiety, decisional conflict, and regret, suggesting that the way individuals interpret their past has a significant impact on their emotional well-being during genetic counseling for cancer risk. High scorers on the present-hedonistic scale were less likely to read the information materials they received at the clinic, and high scorers on the present-fatalistic scale had lower knowledge scores, suggesting that individuals with a present orientation may be less inclined to read and comprehend the information materials they receive from their clinicians. Henson et al. (2006) suggest that present-oriented individuals may require more behavior-based, rather than education-based, interventions to encourage them to adopt protective health behaviors. Our findings provide some support for this suggestion. Future research investigating the possibility of tailoring interventions according to individuals' time perspective, and their effect on protective health behaviors such as adherence to screening recommendations and interest in prophylactic surgery, in this population is warranted.

In contrast with our third hypothesis, future time perspective did not predict individuals' interest in genetic testing. This intriguing finding may have been due to a ceiling effect, with high levels of interest in genetic testing for the large majority of participants in the study, or may also reflect a lack of validity of this scale in this particular population. Indeed, the items used for the future scale appear more focused on shorter term, work-related concerns such as “meeting tomorrow's deadlines” and “completing projects on time,” rather than much longer term and complex health-related issues such as making decisions about cancer-related screening and prevention.

Despite the positive results described above, we raise significant concerns about the psychometric properties of this short form of the ZTPI, particularly its factor structure. It was beyond the scope of the present study to conduct a comparison of this form with the performance of the traditional longer form of the ZTPI in an Australian community sample and in patients with a strong family history of cancer. However, it is likely that such a comparison would have indicated the reasons for the suboptimal psychometric properties of the ZTPI short-form in this study. For example, it is possible that too few items were retained per scale, or that the items chosen were not the ideal items to fully represent each scale in question. As such, without further investigation, the original 56-item ZTPI remains the most valid and reliable means of assessing individual time perspective to date.

The discrepant findings between the two studies also warrant further discussion. Although, in general, many of the results held true across both samples for studies 1 and 2, some intercorrelations were different between the two groups. For example, the future scale was significantly negatively correlated with depression and anxiety in the community sample (study 1), but these correlations were not reflected in individuals with a strong family history of cancer (study 2). Similarly, scores on the past-positive scale were significantly negatively correlated with anxiety in study 2 participants, whereas no such relationship existed between these variables in study 1 participants. It is not possible to make conclusive statements regarding the cause of these nonconvergent findings; however, they may reflect the fact that the two samples represent diverse populations. It is possible that different populations have different “profile patterns” in terms of time perspective. It is also possible that time perspective is situationally determined and that these differences were caused by the different current experiences of the two samples. Further research in this area would be interesting.

Finally, the participants in both studies tended to have higher education levels than the general population, with 85.1% of study 1 participants and 77.0% of study 2 participants having a postschool qualification, compared with 51.5% of the general population (Australian Bureau of Statistics, 2006). For study 1, this is not surprising, given the study was advertised through a university Web site. Indeed, it is likely that individuals who volunteer to participate in Web-based research are demographically different from those found in random samples of the population, and this issue would have been exacerbated by advertising the study through a university. Future research using Web-based surveys would benefit from the use of a randomly sampled, nationally representative, Web-enabled panel of participants to ensure that the participating samples were more representative of the population as a whole. For study 2, it has been previously reported that patients attending familial cancer clinics tend to be more educated than the general population; however, this gap appears to be narrowing (Cull et al., 1999; Wakefield et al., 2007a). An educated group such as this may be more future oriented and less present oriented than the general population.

Implications

This study showed that individuals in the general community with a past-negative or present-fatalistic orientation may be more emotionally distressed than individuals oriented toward other time perspectives. In the familial cancer clinic setting, the study showed that patients with a past-negative time perspective were also more likely to be distressed, feel uncertain about genetic testing, and experience postdecision regret at 6 months after genetic counseling. Past-negative-oriented individuals were also more likely to be undecided about, or against, genetic testing. Hedonism was associated with being less likely to read the educational materials they received at their familial cancer clinic, and fatalism was associated with having lower knowledge levels about genetic testing. Taken together, these findings suggest that assessment of patients' time perspectives may be a useful means of identifying those who might benefit from additional support during genetic counseling for cancer risk. Until more psychometric evaluation is conducted on the short form of the ZTPI presented in this study, the original 56-item ZTPI is likely to be the most valid and reliable means of assessing individual time perspective.

Footnotes

Acknowledgments

The authors thank all the men and women who completed the questionnaires for this study. They also thank their consumer representative, Sandra Tanner. The study was funded by a project grant from The Cancer Council of New South Wales (Project Grant 300441). Claire Wakefield is supported by an Australian Postgraduate Award. Bettina Meiser is supported by a Career Development Award from the National Health and Medical Research Council of Australia (ID 350989). The authors also thank the members of the Australian GENetic testing Decision Aid (AGenDA) Collaborative Group, which comprises clinicians who recruited patients for this study and other researchers who contributed their expertise to other aspects of the project. The members of the AGenDA Collaborative Group are listed in alphabetical order of group or institution: Centre for Genetics Education, Sydney (K. Barlow-Stewart); Familial Cancer Service, Westmead Hospital, Sydney (G. Fenton, A. Goodwin, J. Kirk, P. Zodgekar); Hereditary Cancer Clinic, Prince of Wales Hospital, Sydney (L. Andrews, J. Koehler, A. Overkov, N. Kasparian, M. Peate, J. Tyler, K. Tucker, B. Warner); Hunter Genetics, Newcastle (T. Dudding, M. Gleeson, C. Groombridge, S. O'Donnell, A. Spigelman); Macquarie University (C. McMahon); Peter McCallum Cancer Institute, Melbourne (L. Hossack, M. Kentwell, M. Young); Royal Melbourne Hospital, Melbourne (C. Aragona, R. D'Souza, C. Gaff, L. Hodgkin); St Vincent's Hospital, Sydney (R. Ward, R. Williams); University of Sydney (P. Butow, E. Lobb).

Disclosure Statement

The authors have no conflicts of interest to declare.

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