Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jun 12.
Published in final edited form as: J Pers Assess. 2020 Jan 9;103(2):278–288. doi: 10.1080/00223891.2019.1705843

Constructing a Performance Measure of Future Time Orientation

Mathew J Biondolillo 1, Leonard H Epstein 1
PMCID: PMC9188834  NIHMSID: NIHMS1650169  PMID: 31917605

Abstract

Three studies present the development of the Scrambled Sentences Task for Future Time Orientation (SST-FTO), a performance measure of future time orientation. In Study 1, undergraduate research assistants rated a pool of 30 experimental items as delineating between future and present time orientations demonstrating the content validity of SST-FTO items. Study 2 established the convergent validity of the SST-FTO administered online showing performance related to a self-report measure of time orientation and a performance measure of delay discounting but not to a measure of temporal focus. Study 3 further established the validity of a shortened SST-FTO administered online following an episodic future thinking intervention known to affect delay discounting. The intervention influenced delay discounting but not SST-FTO performance. SST-FTO measures correlated with pre-intervention self-reported future orientation and predicted delay discounting even after accounting for intervention effects and self-reported future orientation. Internal consistency of the measure was demonstrated in all three studies through item-total correlations and Cronbach’s alphas. Results suggested the SST-FTO is a robust performance measure of future time orientation, predictive of decision-making on performance measures of delay discounting.

Keywords: time orientation, future, delay discounting, measure, task

Constructing an Implicit Measure of Future Orientation

On a daily basis, people make innumerable decisions that can have lasting effects on health and well-being. Should you have a donut or oatmeal? Should you go to the gym or go home and relax? Should you get to bed or stay up and watch the end of an exciting game? For some, the taste of the donut, the comfort of the living room, and the excitement of a walk-off homerun are much more alluring than lowering cholesterol, improving fitness, and being more alert in the morning. There is considerable interest in individual differences predictive of decision-making when choosing between immediate and delayed alternatives such as these. This paper focuses on one such individual difference, future time orientation (FTO), and presents the development of a performance measures of FTO predictive of decision-making.

Time orientation can be conceptualized as the degree to which one attends to, is motivated by, and engages in action towards the past, present, or future (Crockett, Weinman, Hankins, & Marteau, 2009; Shipp, Edwards, & Lambert, 2009) and is a facet of time perspective, the overarching views one holds about the past, present, and future (Zimbardo & Boyd, 1999; Zimbardo, Keough, & Boyd, 1997). FTO denotes a predominant focus on the future and encompasses motivational factors such as the value of goals one hopes to attain and failures one hopes to avoid, cognitive factors related to one’s ability to envision an extended future, and expectancies regarding goal attainment (Gjesme, 1983; Trommsdorff, 1986). It is shaped by social, environmental, and developmental factors (Gjesme, 1983; Trommsdorff, 1983, 1986) and is a relatively stable and trait-like quality by adulthood (Crockett et al., 2009; Zimbardo & Boyd, 1999). FTO is often juxtaposed with present time orientation (PTO), the predisposition for present-oriented action (Zimbardo et al., 1997). Whereas a present-oriented person would more likely choose the donut, the lounge chair, and watching extra innings, a future-oriented person would more likely choose the oatmeal, the gym, and a full night of sleep – choices with greater long-term instrumental value.

FTO is closely related to other constructs that consider foresight important in decision-making. These include effortful control (Posner & Rothbart, 2000), which relates to the inhibition of a dominant response for a non-dominant response, delay of gratification (Mischel, Shoda, & Rodriguez, 1989), which relates to the postponement of one reward for the sake of a later reward, and conscientiousness (Costa, McCrae, & Dye, 1991), a trait marked by a tendency to follow social norms and to persist in goal pursuit; however, these constructs are theoretically distinct. Effortful control and delay of gratification imply the use of self-regulatory mechanisms to make decisions for future benefit, whereas FTO denotes the degree of default future-oriented decision-making. For example, those with a greater FTO may not need to engage in as much effort control and would be more likely to delay gratification when faced with a choice between an immediate versus a delayed reward as their dominant response would be for a delayed reward. Furthermore, although a conscientious person is likely to be more future-oriented and to keep long-term plans in mind, conscientiousness encompasses attributes beyond FTO that may also lead to healthy decisions, such as orderliness and responsibility (Bogg & Roberts, 2013).

FTO may be more closely aligned with delay discounting (DD), which pertains to the degree to which one devalues future outcomes as the delay to achieve those outcomes increases (Bickel & Marsch, 2001). A wealth of literature has shown that a greater FTO is related to healthy behaviors such as less smoking, drinking, drug use, risky sexual behavior, delinquency, and gambling, a better diet, and greater exercise (Crockett et al., 2009; Daugherty & Brase, 2010; Teuscher & Mitchell, 2011). These behaviors are also related to lower DD (Story, Vlaev, Seymour, Darzi, & Dolan, 2014). Research shows that those with a greater FTO are less likely to discount the future and more likely to make decisions with longer-term health benefits (Daugherty & Brase, 2010), and age differences in DD may be mediated by FTO (Steinberg et al., 2009). Although more highly predictive of health behavior than Big Five personality traits, DD and FTO are not redundant as each are incrementally predictive of health behaviors (Daugherty & Brase, 2010). Whereas DD denotes the weighing of specific, mutually exclusive reward alternatives at near and distal points in the future, FTO describes a more general tendency to think about the future, devoid of juxtaposed present and future reward valuations. Due to the clinical relevance of these two characteristics, interventions seeking to improve decision-making and motivate behavior change ought to consider both DD and FTO (Teuscher & Mitchell, 2011). Whereas interventions can modify DD (for a review see Rung & Madden, 2018), manipulations of FTO have been unsuccessful (Castella, Minguell, Muro, Sotoca, & Estaun, 2018; Hall & Fong, 2003), but it remains to be seen if effective DD interventions also influence FTO.

One issue limiting our understanding of the relation between FTO and DD is that DD measurement is largely based on performance measures asking individuals to make hypothetical decisions (Epstein et al., 2003; Sze, Stein, Bickel, Paluch, & Epstein, 2017), whereas FTO measurement is largely reliant on self-report (Shipp et al., 2009; Strathman, Gleicher, Boninger, & Edwards, 1994; Zimbardo & Boyd, 1999). Self-report measures are prone to social desirability bias (Nederhof, 1985; Paulhus & John, 1998), therefore it is suggested that performance measures, which can implicitly assess personality and minimize social desirability, may be more valid in assessing individual differences (Robinson & Neighbors, 2006). The present research first describes the development of the Scrambled Sentence Task for Future Time Orientation (SST-FTO), an implicit, performance measure of FTO, then examines its stability following an episodic future thinking (EFT) intervention known to influence DD.

Three studies examined the characteristics of this newly constructed measure. Study 1 sought to select the most content-valid items for the SST-FTO from an item pool, which was further refined in two follow-up studies. Study 2 assessed the internal consistency of the measure as well as its convergent validity and divergent validity with self-report measures of FTO and a performance measure of DD. Finally, Study 3 further refined the measure and assessed its responsiveness to an intervention shown to influence DD.

Development of the SST-FTO

The SST-FTO is an adaptation of a task developed to measure depressive thinking (Wenzlaff, 1993; Wenzlaff & Bates, 1998) that has been previously adapted to measure big picture appraisal (BPA; Haner & Rude, 2015) and future time perspective (Demeyer & De Raedt, 2014). These two concepts relate to one’s ability to see time over an extended period into the future but do not tap into one’s preference for attending to and making decisions for the future versus the present, which is the intent of the SST-FTO. The task involves showing participants a series of six words displayed in a scrambled order. The participant is asked to select five of the six words in any order to compose a grammatically correct statement (not a question). The implicit nature of the task is that each stimulus contains two target words whose selection changes the meaning of the sentence. An example stimulus from the SST for depressive symptomology is “looks the future bright very dismal”, which can be unscrambled into “the future looks very bright” or “the future looks very dismal”, the latter indicating depressive symptomology (Wenzlaff & Bates, 1998). To mask the intent of the measure and reduce socially desirable responding, participants are given a time limit and are thus pressured to unscramble the sentences quickly. Control sentences that are unrelated to the experimental measure are also included among experimental items. In addition, a cognitive load (CL) condition is often employed where participants are asked to memorize and retain a six-digit number during the task. Scores are computed as a proportion of the responses of a particular quality (i.e. depressive sentences/depressive + non-depressive sentences). These tasks have proven reliable and valid in paper-and-pencil and computer administration where stimuli are presented one-at-a-time (Haner & Rude, 2015; Viviani, Dommes, Bosch, Stingl, & Beschoner, 2017).

In the present study, we employed a computer administration under a CL condition. A large pool of sentences that could be unscrambled in a present or future-oriented manner was constructed by the first author and colleagues. These items were examined in an initial pilot test (not presented in this paper), revised, and 30 items were selected for additional testing.

Study 1

Method

The intent of Study 1 was to establish the content validity of items in the initial pool of stimuli and identify those that significantly distinguished between FTO and PTO.

Participants.

Participants were 27 undergraduate research assistants at a large public university in New York State. Participants were recruited anonymously.

Procedure.

A survey administered on Survey Monkey contained all 30 items, each presented once in its present-oriented format and again in its future-oriented format (see Table 1). The order of item presentation was random, but future and present versions of the same item were not allowed to appear on the same page of the survey (10 sentences per page). Participants were asked to read and rate each sentence according to the degree to which it expressed FTO on a 5-point Likert scale (1 = Very Little; 5 = Very Much). FTO was first described as:

“…individuals' focus on and consideration of the future when thinking and when making decisions. This means that an individual has a clear vision for the future, plans to achieve future goals, and will make decisions for future benefits even when faced with immediately satisfying alternatives. An individual showing a future time orientation might put their immediate desires aside, resist tempting impulses, and instead take actions that get them closer to a future goal. This could include showing self-control in avoiding pleasurable activities today if they might have negative consequences in the future. Alternatively, it could involve showing discipline and perseverance to realize an important goal instead of pursuing satisfying diversions. In contrast, someone displaying a present time orientation might abandon plans and long-term goals in order to pursue immediately rewarding experiences even if they jeopardize their long-term goals.”

Data analytic plan.

Scale reliability was examined by computing the intra-class correlation (ICC) for ratings on all items. Paired-samples t-tests examined differences in ratings of present and future-oriented solutions of items for content validity. Items whose solutions were not rated significantly differently or that failed to differentiate between present and future orientation (as indicated by ratings on opposite sides of the scale midpoint) were dropped from the scale, and an additional ICC was computed on the remaining items. Cronbach’s alphas were then computed separately for future and present-oriented solutions of remaining items.

Results and Discussion

Twenty-one participants rated all items, and the ICC for item ratings was r = .81 indicating good inter-rater reliability. All items’ past and future solutions were rated significantly differently in the expected direction with the exception of item 25 (Table 1). Four other items had solutions rated on the same side of the scale mid-point (items 10, 21, 24, and 28). These five items were removed from further testing. The ICC for all remaining items was r = .71. Cronbach’s alpha for the 25 future-oriented solutions was α = .86, and for the present-oriented solutions, α = .85. These 25 items were further examined in Study 2.

Study 2

Method

Study 2 tested the convergent validity of the SST-FTO and the reliability of the task administered online via Inquisit (Software, 2015) in a large sample of participants recruited through Amazon Mechanical Turk (AMT). AMT is a web service frequently used in the social sciences to connect researchers to human research participants and produces quality data (Buhrmester, Kwang, & Gosling, 2011), which may be widely generalizable in the US population (Burnham, Le, & Piedmont, 2018). We chose to administer the SST-FTO under CL as is commonly done in order to minimize socially desirable responding (Rude, Wenzlaff, Gibbs, Vane, & Whitney, 2002). We sought to examine the correspondence between SST-FTO performance and self-reported time orientation measured with the Consideration of Future Consequences Scale (CFCS; Strathman et al., 1994) and the Temporal Focus Scale (TFS; Shipp et al., 2009), as well as with performance measures of working memory (WM) and DD. We were also interested in whether differences in response latencies for future or present-oriented items would also relate to the above measures; however, no significant correlations were noted so we have omitted further discussion of response latencies.

We hypothesized that SST-FTO scores would correlate positively with CFCS scores and TFS-future subscale scores, and negatively with TFS-current subscale scores and log transformed k-values (log k) calculated from the DD task. Lower log k values denote lower DD.

Participants.

Adults (N = 276, 56% female) were recruited from AMT to complete a decision-making study. Most participants identified as White (76%) or Black/African American (14%) and non-Hispanic (87%). Another 4% of participants identified as Asian, 4% as Other or mixed race, and 1% identified as American Indian/Alaskan Native or Native Hawaiian/Other Pacific Islander. Participants’ average age was M = 36.17 years (SD = 11.11 years).

Procedure.

Prior to administration of the task, the 25 sentences from Study 1 were rearranged into a random order as determined by random number generator (see Appendix B), and to ensure equivalence of stimuli, matched pairs t-tests examined target word length and placement in sentences, and a Wilcoxon signed-rank test examined frequency of target word use according to ranking in The Corpus of Contemporary American English (Davies, 2008-). No differences were noted in length, t(24) = −.34, p = .74, d = .07, placement, t(24) = −.89, p = .38, d = .18, or frequency of target words, z = −1.76, p = .08, r = .25. Participants read a study description on AMT and followed a link to the survey hosted on Qualtrics. Screening questions screened out participants under 18 years old, those with a history of ADHD, depression, anxiety, or PTSD, those who admitted illicit substance use (besides marijuana), and any who admitted drinking greater than 21 drinks per week as these conditions may affect attention to tasks and/or prospection (Bickel & Marsch, 2001; Gamble, Moreau, Tippett, & Addis, 2019; Griffiths et al., 2012; Hallford, Austin, Takano, & Raes, 2018; Kleim, Graham, Fihosy, Stott, & Ehlers, 2014). Eligible participants were directed to a consent form and asked to give electronic consent. After consenting, participants completed a demographics questionnaire, the CFCS, and the TFS in that order. They then completed a digit-span WM test administered on Qualtrics. Next participants were directed via hyperlink to the SST-FTO hosted on Inquisit. After completing the SST, participants were given a code to enter into Qualtrics to continue to the DD task, after which they were thanked and debriefed. Responses were individually screened to ensure that each response was from a unique MTurk worker ID and IP address. Participants attempting to re-enter and complete the survey following any prior attempt (screen fail or completed survey) were excluded. Participants were compensated $2.00 for successfully completing the study while meeting attention checks. An additional $1.00 could be earned for constructing at least 60% grammatically correct sentences (45 total), and $0.50 could be earned for successfully recalling each of two six-digit numbers given for the CL procedure ($1.00 for recalling both).

Measures.

Demographics.

Demographic information was collected by survey-based questionnaire (e.g., sex, age, race/ethnicity, family income, employment status, social status, education).

Scrambled sentences task for future time orientation.

A version of the SST (Wenzlaff & Bates, 1998) was modeled after computerized versions of the task used in past research (Haner & Rude, 2015; Sanchez, Everaert, De Putter, Mueller, & Koster, 2015; Viviani et al., 2017). Participants were shown a series of six-word scrambled sentences, each displayed for 10 s with a 1000 ms fixation cross displayed between trials. Stimuli appearance was identical to that in Sanchez et al. (2015). Participants were asked to click on five of the six words in a sequence creating a syntactically and grammatically correct sentence that was not a question. Upon clicking a word, a number indicating the word’s order in the participant’s sentence appeared above the word (a ‘1’ appeared above the first word clicked, a ‘2’ above the second, etc.). Sentences assembled in a different order from that tested in Study 1 were scored as correct so long as they were syntactically acceptable. There were also 20 neutral control sentences to obscure the intent of the measure. An example control sentences was, “to books read magazines I prefer”. During the task, a maximum of two consecutive sentences of the same type (experimental or control) could be shown. Participants completed two blocks of either 12 or 13 trials, each trial lasting until the participant had chosen five words or until the 10 s period had expired. Sentence order was randomly decided for each participant. Before each block, participants were shown a six-digit, randomly generated number that they were asked to remember and report at the end of the block. Prior to testing, participants completed five control practice trials under CL. The proportion of future-to-total correctly assembled experimental sentences was used as measures of their FTO, with higher proportions indicating greater FTO.

Working memory.

A computerized adaptation of the Visual Digit Span-Backwards task (Woods et al., 2011) was administered to participants to assess visuospatial WM. The task presented participants with a sequence of digits (from 1 to 9) displayed for 1 s each and asked that they recall the reverse order of their presentation. The task started at a two-digit sequence and increased to a ceiling of eight digits. Participants were given two attempts to complete a two-digit practice trial, and were then shown two trials at each sequence length, 14 trials in total. WM span was calculated as the longest sequence the participant completed correctly.

Time orientation.

Two measures were used to measure self-reported time orientation. The CFCS (Strathman et al., 1994) was used to assess the extent to which individuals consider future outcomes of their behavior and are influenced by the imagined consequences. Participants indicated the degree to which 12 statements were characteristic of themselves on a 5-point Likert scale (1 = extremely uncharacteristic; 5 = extremely characteristic). An example item states, “I consider how things might be in the future, and try to influence those things with my day-to-day behavior.” After transforming reverse-scored items, the scale is summed. Higher scores represent a greater future orientation. In the present study, Cronbach’s alpha for the 12-item scale was α = .86. In addition, the TFS (Shipp et al., 2009) was used to measures the degree to which participants focus on the past, current/present, or future. On a 7-point Likert scale (1 = never; 3 = sometimes; 5 = frequently; 7 = constantly), participants indicated how frequently they think about the time frame indicated by items. Four items composed past, current, and future subscales. Example items include, “I replay memories of the past in my mind” (past), “My mind is on the here and now” (current), and “I think about times to come” (future). Cronbach’s alphas for the past, current, and future subscales were α = .89, α = .82, and α = .91 respectively.

Delay discounting.

The 5-trail adjusting delay task (Koffarnus & Bickel, 2014) measured a respondent’s preference for delayed versus immediate rewards. The task asks that participants choose whether they would like to receive one sum of money ($100) in three weeks or half of that amount now. Choosing the delayed reward increased the delay to receive it on the next trial, and choosing the immediate reward decreased the delay. Following five trials, a curve is fit to the data that indicates their degree of DD, and a parameter estimating the shape of the curve (k) is calculated. Steeper curves with higher k values represent a preference for smaller immediate rewards over greater delayed rewards. Since k is non-normally distributed, the more normally distributed logarithmically transformed log k was used in this study as a measure of DD.

Data analytic plan.

SST-FTO responses were screened to ensure an adequate number of items were completed for analyses and to test for outliers in response times (z ± 3 SD). After excluding 32 participants for completing fewer than 25% of experimental items correctly, responses were coded as 1 = future-oriented, 0 = incorrect, or −1 = present-oriented and the internal consistency of responses was examined in the remaining sample (N = 243). Power analysis indicated this sample size allowed 99% power to detect a correlation of r = .32 between CFCS and DD, an effect observed in prior research (Basile & Toplak, 2015). Cronbach’s alpha was examined for all items, and any whose exclusion would increase scale reliability were eliminated from further analyses (four in total) and proportions of future, incorrect, and present solutions were examined for each item. SST-FTO scores were then calculated from remaining items. Independent samples t-tests and one-way ANOVAs for categorical variables and bivariate correlations for continuous variables examined associations between participant characteristics and SST-FTO responses. Bivariate correlations examined associations of CFCS, TFS, and DD with SST-FTO scores. Finally, separate linear regressions examined moderation of CFCS and TFS scores’ associations with SST-FTO scores by age and WM.

Results and Discussion

Participants successfully completed an average of M = 17.87 (SD = 3.98) of the 25 experimental items. Reliability of responses to experimental SST-FTO items was assessed by performing a Cronbach’s alpha for all items and examining item-total correlations (Table 1). Analyses indicated that excluding the four items with the lowest item-total correlations improved internal consistency. We re-ran item-total correlations, computed a Cronbach’s alpha on remaining responses, and examined response frequencies to each item in the remaining 21 items. Item-total correlations ranged from r = .14 to r = .46 with a mean of r = .29 representing good internal consistency (Clark & Watson, 1995), and all remaining items allowed for variability in orientation of responses (Table 1). Cronbach’s alpha on the 21-item scale was r = .74 and the mean number of correct, scoreable responses on the remaining 21 experimental items was M = 15.41 (SD = 3.43).

In examining SST-FTO responses, no differences or associations were noted on the basis of participant characteristics, including with age or WM (Table 2 for correlations). A small-to-medium-sized correlation between SST-FTO and CFCS scores was found, but no correlations were noted with TFS-subscales suggesting SST-FTO performance was moderately reflective of explicit time orientation, but not reflective of the future or present focus individually. In terms of DD, CFCS scores significantly predicted log k, and SST-FTO scores trended towards significance in predicting log k. Moderation analyses examining if age or WM moderated the relation of CFCS and DD scores with SST-FTO scores found no interactions.

Study 2 provided preliminary evidence that the SST-FTO functioned as a performance measure of FTO. Correlations between SST-FTO scores and explicit time orientation as measured by the CFCS were similar to those observed by Haner and Rude (2015) between the SST-BPA and putative correlates, but were not so high to suggest complete collinearity. Of note is that SST-FTO scores were not associated with TFS scores, suggesting that the TFS isn’t able to measure the relative valuation of the future versus the present, which was intended to be captured by the SST-FTO and is captured in the CFCS and DD task. In addition, the correlation between SST-FTO scores and DD, though not significant at the p = .05 level, was in the expected direction. Associations between the SST-FTO and both the CFCS and DD were not moderated by WM or participant age, suggesting they were not a result of differences in these participant characteristics. In Study 3, we examined if performance on the SST-FTO was responsive to an episodic future thinking (EFT) intervention known to affect DD (Peters & Buchel, 2010).

Study 3

Method

Study 3 tested the 21-item SST-FTO administered online in another sample of AMT participants. The main purpose of Study 3 was to examine the responsiveness of SST-FTO scores to an effective DD intervention. In addition, we sought to re-examine convergent validity of SST-FTO performance and internal consistency of the measure following the manipulation. Again, we administered the SST-FTO under CL. Correlations of SST-FTO scores with CFCS scores, WM, age, and a performance measure of DD were examined, and group differences in SST-FTO scores and DD were examined following an EFT intervention.

We hypothesized SST-FTO scores would be positively correlated with CFCS scores and negatively correlated with DD scores. As TFS scores were uncorrelated with SST-FTO scores in Study 2, we re-examined this correlation in Study 3. Finally, we predicted the experimental group would have lower DD and a greater FTO than the control group.

Participants.

Adults (N = 230, 51% female) between 18 and 64 years old (M = 37.34 years, SD = 10.70 years) were recruited from AMT to complete a decision-making study. Most participants were White (74%) or Black/African American (10%) and non-Hispanic (90%). Another 9% of participants were Asian, 2% American Indian/Alaskan Native, 4% Mixed-race, and less than 1% Native Hawaiian/Pacific Islander or Other.

Procedure.

Similar to Study 2, participants read a study description on AMT and followed a link to the survey hosted on Qualtrics where they first answered screening questions. Exclusionary criteria were the same as in Study 2. Procedures were similar to Study 2 except that that before completing the SST-FTO, participants were randomized to either a group that did an EFT procedure or one that did an episodic recent thinking (ERT) control procedure. The EFT procedure was similar to that used in prior DD research (Daniel, Stanton, & Epstein, 2013; Sze et al., 2017), and asked participants to vividly imagine and describe future positive events that could happen at five different points in the future (a week, a month, six months, a year, and five years). The ERT procedure involved the description of vivid recent past events (one to five days ago). All events were first described in a one-sentence “tag”, rated along several characteristics, and were further elaborated. Next, participants were directed via hyperlink to the SST on Inquisit (2015). After completing the SST, participants were given a code to enter in Qualtrics to continue to the DD task. The DD task presented participants with their event tags from the EFT/ERT procedure and asked them to imagine their events while making hypothetical choices between receiving smaller sums of money now, or larger sums of money at time periods matched to those used to cue EFT events. After the DD task, participants were thanked and debriefed. Responses were screened for unique MTurk worker IDs and IP addresses as in Study 2. Participants were compensated $4.00 for successfully completing the study while meeting attention checks. An additional $1.00 could be earned for constructing at least 60% grammatically correct sentences (41 total), and $0.50 could be earned for successfully recalling each of two six-digit numbers given for the CL procedure ($1.00 for recalling both).

Measures.

Only measures unique to Study 3 are outlined below.

Delay discounting.

Participants were asked to make hypothetical choices between a fixed reward available after a time delay and an immediate reward whose magnitude incrementally ascended or descended depending upon participant choices (Sze et al., 2017). The delayed (fixed) amount was always $100 and the immediate reward started at $50 and adjusted from 0.1 to 100% of the delayed reward. An initial choice for the smaller reward resulted in a downwards adjustment in its value on the next trial, and an initial choice of a larger reward resulted in an upwards adjustment in the value of the smaller reward. Six trials were presented at each of five delays (1 week, 1 month, 6 months, 1 year, and 5 years) until rewards reached an indifference point (IP), representing the immediate reward amount of equal value to the fixed, delayed reward. For example, an IP of $75 at the 1 year delay means receiving $75 now (a decay in value of $25) has the same value as receiving $100 in a year. During the task, EFT participants were shown their tags for each delay, whereas ERT participants were shown past event tags corresponding to the relative distance of the future delay from the present (for example, the event from 1 day ago was shown for 1 week delay, the event from 2 days ago was shown for 1 month delay, etc.). Participants were first shown the delay coming up and were then asked to read their event description corresponding to that delay (each displayed for 10 s). Tags were then presented at the top of the screen and participants were cued to think about their events while making decisions. Delay order was randomized such that they did not systematically increase or decrease. DD was again assessed by log k values.

Episodic cue ratings.

Participants rated how important, enjoyable, exciting, and vivid each event was, and how much they could think about details (fluency) of each event described in the EFT/ERT task on 5-point Likert scales (1 = “Not at all”; 5 = Very much”).

Data analytic plan.

EFT/ERT responses were screened to ensure sufficient effort and attention. Seventeen participants were excluded for failure to follow EFT/ERT instructions. SST-FTO responses were coded and screened as in Study 2, resulting in the exclusion of nine participants, one of which was for response times on SST items of z > 3 SD. An additional participant was excluded for having taken the survey twice. Internal consistency of responses was again examined as in Study 2. Bivariate correlations for continuous variables and independent samples t-tests or one-way ANOVAs for categorical variables examined relations between SST-FTO scores and participant characteristics.

DD data were screened for nonsystematic discounting using the criteria outlined by Johnson and Bickel (2008). Data were nonsystematic if a participant’s IP at a delay was greater than the prior delay by at least $20 (20% of the maximum reward). This could occur at each delay starting with delay 2. In addition, if the IP at the longest delay was not less than that of the first delay by at least $10 (10% of the maximum reward), it was also considered nonsystematic. We allowed for no more than two violations of these criteria, resulting in one further exclusion. Analyses are presented in the remaining sample of N = 203. Power analysis indicated this sample size exceeded the N = 64 needed to detect an effect of EFT on DD at an effect size of d = 0.72, as observed in prior research (Daniel, Sawyer, Dong, Bickel, & Epstein, 2016).

As a manipulation check, one-sample t-tests within each group examined if the vividness and enjoyment of EFT/ERT events were above the scale mid-point and an independent-samples t-test examined differences in DD. Next, independent samples t-tests for continuous variables and Chi-square tests for categorical variables screened for group differences in participant characteristics and EFT/ERT event ratings. Variables with significant differences were used as covariates in analyses of DD and SST-FTO scores. Independent samples t-tests examined group differences in SST-FTO scores. Bivariate correlations examined associations of CFCS, TFS, WM, age, and DD with SST-FTO scores, and one-way ANCOVAs examined if SST-FTO scores, the intervention, interactions between SST-FTO scores and the intervention, and covariates predicted DD. As TFS scores were found not to correlate with SST-FTO scores, we are not discussing those with results of Study 3.

Results and Discussion

Participants successfully completed an average of M = 29.80 (SD = 5.97) of the 41 total items, and M = 15.59 (SD = 3.09) of the 21 experimental items. Analyses indicated that excluding the five items with the lowest item-total correlations improved internal consistency. The remaining 16 items were found to have acceptable item-total correlations ranging from r = .23 to r = .47, with a mean item-total correlation of r = .35, suggesting good internal consistency (Clark & Watson, 1995) and remaining items allowed for variability in response orientation (Table 1). Cronbach’s alpha on the 16-item scale was r = .75, and the mean number of correct responses on the remaining 16 items was M = 12.00 (SD = 2.41), Thus, the SST-FTO demonstrated good reliability even after the manipulation.

In terms of the association between participant characteristics and SST-FTO scores, none were noted including with age or WM (Table 2). In examining effects of the manipulation, we found that events generated were significantly higher than the neutral midpoint of the scale for both enjoyment and vividness in both groups (ps < .001; Table 3 for group means). We also examined if the intervention successfully affected DD and noted significantly lower discounting in the EFT group, t(201) = 3.44, p < .01; d = .48. Thus the intervention successfully triggered positive and vivid events and manipulated DD.

Group differences in background variables were then examined, and no differences were noted (Table 3). We also examined differences in the ratings of EFT and ERT events and found that EFT events were rated higher in enjoyment, importance, excitement, rehearsal, and vividness than ERT events (Table 3). We then examined intervention effects in SST-FTO scores and groups did not differ, t(201) = .54, p = .59; d = .08. Contrary to predictions, the effect of the manipulation was not seen in SST-FTO performance.

Next, we examined correlations of SST-FTO scores, CFCS scores, and DD (Table 2). SST-FTO scores showed a medium-sized correlation with explicit time orientation measured by the CFCS. As for associations with DD, CFCS scores were not predictive of log k, whereas SST-FTO scores were.

We then examined intervention effects on DD. First, we entered SST-FTO scores as a covariate in an ANCOVA predicting log k from condition, and each predictor independently predicted log k (for condition, F(1, 200) = 12.66, p < .001, η2p = .06; for SST-FTO, F(1, 200) = 5.39, p = .021, η2p = .03). Thus SST-FTO scores predictive a significant amount of variance in DD that was unaccounted for by the intervention. We next ran an ANCOVA predicting log k from condition with CFCS scores as a covariate to see if explicit time orientation added predictive power similar to SST-FTO scores, however, there was no effect of CFCS scores on log k, F(1, 200) = 2.26, p = .14, η2p = .01). We also added both CFCS and SST-FTO scores as covariates in the ANCOVA predicting log k from condition. CFCS scores failed to predict log k, F(1, 199) = 0.70, p = .41, η2p < .01, whereas SST-FTO scores predicted a greater, marginally significant amount of variance in log k, F(1, 199) = 3.79, p = .053, η2p = .02. In the face of the intervention, SST-FTO scores predicted a greater amount of variance in DD unaccounted for by explicit time orientation. Finally, in an ANCOVA predicting log k from condition and SST-FTO scores, we added the interaction term representing the condition-by-SST-FTO interaction as a covariate, and this effect was not significant, F(1, 199) = 0.001, p = .97, η2p < .001. Thus, the SST-FTO-DD relation was unaffected by the manipulation.

To ensure apparent SST-FTO effects were not due differences in event ratings, participant ratings of EFT/ERT events were added as additional covariates in the above ANCOVA. As prior EFT studies have found a high degree of covariance among event ratings and have combined them into a single rating (Daniel et al., 2016), we first computed a Cronbach’s alpha for the five ratings of event characteristics. Cronbach’s alpha was α = .89 suggesting the five ratings could be combined into a single measure of event quality. We summed the average ratings for enjoyability, importance, excitement, fluency, and vividness into a single score and added this measure as a covariate in the ANCOVA predicting log k scores from condition and SST-FTO scores. Again, SST-FTO scores predicted DD, F(1, 199) = 5.34, p = .022, η2p = .03.

As a final check of measure reliability, we re-examined Study 2 data using only the 16 items identified in Study 3. The pattern and significance of Study 2 results were unchanged.

General Discussion

The results of the three studies reported here provide preliminary support for the reliability and validity of the SST-FTO as an implicit measure of FTO. FTO denotes a predominant focus on the future, and research suggests it is a relatively stable individual difference, predictive of a number of health-related outcomes (Crockett et al., 2009; Zimbardo & Boyd, 1999). To date, FTO measurement has largely relied on self-report. A performance-based measure of FTO could be a useful tool to aid efforts to predict future-oriented behavior. The present research suggests the SST-FTO is such a measure.

Study 1 sought to establish the content validity of SST-FTO items by asking undergraduate research assistants to rate the degree to which alternative sentence solutions reflected the authors’ definition of FTO. The content validity of the 30-item pool was demonstrated by the high rate of agreement among respondents given only a brief description of FTO. Five of the 25 items were not retained due to the alternative solutions not being rated significantly differently or not being on opposite sides of the scale median, indicating they may not appropriately distinguish future from present orientation. A computerized administration of the 25 remaining items was further refined in Studies 2 and 3.

Study 2 examined the measure’s internal consistency and convergent validity in a sample recruited from AMT. Four items demonstrated low internal consistency and were removed. Scores from remaining items correlated in expected ways with CFCS and DD. A greater proportion of future-oriented responses related to a greater FTO and lower DD, supporting the convergent validity of the SST-FTO.

Study 3 examined the responsiveness of the measure to an EFT intervention known to influence DD as well as its internal consistency and convergent validity following the manipulation. The manipulation effectively influenced DD, but did not influence SST-FTO responses. This suggests FTO may be trait-like by adulthood (Crockett et al., 2009). Still, SST-FTO scores predicted DD in bivariate correlations and when accounting for intervention effects. Those who created a greater proportion of future-oriented sentences demonstrated lower DD. Associations between SST-FTO scores and DD were also stronger than those between CFCS scores and DD following the intervention, and SST-FTO effects were not accounted for by differences in EFT/ERT event ratings. Thus the SST-FTO provides a measure of FTO whose association with DD is not redundant with effects of an EFT intervention or self-reported FTO.

Despite these results, limitations must be acknowledged. First, item-total correlations of a few items were lower in Study 3 than 2. As discussed previously, Study 3 involved a manipulation prior to SST-FTO administration, which may have affected some responses more than others. As the 16-item solution demonstrated good internal consistency even following the manipulation, and Study 2 results were unchanged when using the 16 items from Study 3, we recommend future research measuring FTO use the 16-item measure.

Second, associations of the SST-FTO with the TFS were absent in both studies. Although we had expected correlations with the TFS, upon closer inspection of the TFS it is reasonable to expect none. TFS subscales do not represent the relative degree of future and past-oriented thinking, which is captured by the CFCS, DD, and by the SST-FTO. Thus, the lack of association supports the discriminant validity of the SST-FTO. Additional studies to establish discriminant validity may endeavor to investigate the measure’s association with scales of similar constructs such as the Zimbardo Time Perspective Inventory (Zimbardo & Boyd, 1999).

Third, we only administered the SST-FTO under CL in an online format, which we feel was necessary to mask the intent of the measure and reduce bias in sample selected from AMT. Prior SST studies have administered the task without the CL procedure and in paper-and-pencil format (Demeyer & De Raedt, 2014; Haner & Rude, 2015). As paper and computerized assessment of the SST has been found to behave similarly with and without the CL procedure (Haner & Rude, 2015), we do not feel these issues are particularly problematic. In clinical samples with diminished WM or with individuals less-skilled with computers it would be beneficial to know if a paper-and-pencil administration or administration without the CL procedure would behave similarly as in the present research, and future studies should investigate these alternative means of task administration.

Finally, some have argued that the presentation of EFT event cues during DD tasks may bias DD assessment due to a demand effect (Rung & Madden, 2018). We tried to limit demand with the ERT control that also resulted in positive, vivid events. We also controlled for group differences in event characteristics and did not note a DD effect related to participant-rated event quality, so we feel demand characteristics are not the cause of observed EFT effects on DD.

Despite these limitations, the SST-FTO consistently correlated with the CFCS and DD, and not with participant characteristics. Furthermore, SST-FTO scores predicted variance in DD unaccounted for by the effects of an intervention that affected DD and was more strongly predictive of DD following the intervention than other trait measures. Thus, the SST-FTO captures aspects of FTO not otherwise measured via self-report. Its correspondence with DD, a construct shown to predict future-oriented health behaviors, suggests the SST-FTO may have utility in the prediction of health outcomes and decision-making; however, additional testing is needed in clinical populations to support these applications. Nevertheless, at a time when instant gratification is a thumb press away at all times, the addition of an implicit, performance measure of FTO may be a useful tool for those seeking to better predict who will endure the bitterness of patience to reap its sweet rewards.

Acknowledgments

This research was supported in part by grant R01 HD080292 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. All data, analytic methods, and study materials are available by contacting the first author. This research was not preregistered with or without an analysis plan in an independent, institutional registry.

Appendix

Appendix A

Table 1.

Summary of Content Ratings, Item-total Correlations, and Solution Distributions

Item Present
Target		 Future
Target		 Content rating
of solutions		 Item-total correlations Distribution of
Future/Present Solutions
(%)
Present Future Study 2 Study 3 Study 2 Study 3
1 I usually _ others' feedback ignore consider −1.22 1.00 0.37 0.44 63/24 58/28
2 I'm _ for what's happening unprepared prepared −0.83 0.74 0.19 0.24 61/26 61/27
3 My problems demand _ action swift careful −0.04 1.09 0.14a 33/27
4 Sacrificing for tomorrow is _ pointless practical −1.57 1.00 0.29 0.46 32/14 30/10
5 I _ consider long–term consequences rarely frequently −1.48 1.65 0.39 0.37 49/39 43/42
6 I do things _ thinking before after −0.78 1.22 0.15 0.18b 41/22 53/19
7 My decisions are made _ quickly deliberately −0.91 1.09 0.29 0.23 56/31 57/33
8 I act _ much thought without after −1.30 1.13 0.29 0.23 26/37 37/36
9 I _ plan before acting rarely frequently −1.48 1.65 0.26 0.28 44/31 45/33
*10 My actions will influence _ today tomorrow 0.60 1.48
11 I usually take _ action quick careful −0.26 1.30 0.16 0.09b 40/28 38/19
12 I usually _ thinking ahead dislike enjoy −1.30 1.30 0.33 0.39 60/25 58/27
13 I chose the _ path easy challenging −0.70 0.61 0.28 0.30 33/40 33/39
14 I will make sacrifices _ later now −0.65 0.96 0.33 0.35 42/17 48/18
15 My success usually requires _ urgency patience −0.48 1.43 0.08a 50/5
16 I make–up my mind _ quickly carefully −0.87 1.52 0.28 0.20b 42/39 49/34
17 My behavior is usually _ impulsive sensible −1.48 0.70 0.32 0.46 62/26 57/32
18 Having patience is a(an) _ hindrance asset −1.65 1.74 0.19 0.30 38/2 35/6
19 I _ take time deciding rarely frequently −1.26 1.35 0.20 0.36 65/24 58/30
20 I've _ time making plans wasted saved −0.78 1.17 0.46 0.29 36/45 37/47
*21 I want things done _ fast well 0.04 1.35
22 It's _ to resist temptation difficult easy −1.00 0.61 0.13a 35/42
23 I mostly consider _ outcomes immediate future −0.39 1.39 0.23 0.16b 49/14 45/19
*24 I should _ get working eventually immediately 0.13 0.61
*25 I'm concerned about _ week this next 0.30 0.35
26 Many people _ planning ahead dislike prefer −0.74 1.26 −0.01a 37/18
27 My best days are _ here ahead −0.52 1.39 0.25 0.11b 68/15 70/15
*28 I rarely _ my plans follow change −1.32 −0.23
29 I _ see things through rarely usually −1.43 1.22 0.47 0.45 39/39 36/45
30 Challenging tasks get me _ frustrated motivated −0.50 0.91 0.31 0.39 35/26 34/24
Open in a new tab

Notes. In column 1, items are presented in their originally intended unscrambled format. The underscore denotes the intended location of either the present or future target word (columns 2 and 3). Content ratings are presented centered on 0 and can range from −2 to +2. Higher scores represent greater future orientation. The distribution of future-to-present solutions in Studies 2 and 3 are presented in columns 8 and 9 as a percentage of all responses rated as future and present-oriented. Subtracting both percentages from 100% will give you the percentage of responses deemed incorrect.

*

Items that were excluded from the measure for Studies 2 and 3 based upon ratings in Study 2.

a

Items that were eliminated from analyses in Study 2 based upon low item-total correlations.

b

Items that were eliminated from analyses in Study 3 based upon low item-total correlations

Table 2.

Bivariate Correlations of SST-FTO scores and related measures in Studies 2 and 3

Study 2
1 2 3 4 5 6
1. Age
2. WM .15+
3. CFCS −.03 .00
4. TFS-Current .10 .19** −.20**
5. TFS-Future −.05 .06 .22** .04
6. DD −.13+ −.15* −.20** .06 .00
7. SST-FTO −.02 .02 .26** −.07 .05 −.13+
Study 3
1 2 3 4 5 6
1. Age
2. WM −.04
3. CFCS .09 .02
4. TFS-Current .07 .04 −.17*
5. TFS-Future −.06 .08 .45** .07
6. DD −.09 .02 −.08 .09 .08
7. SST-FTO .03 .06 .31** −.04 .03 −.15*
Open in a new tab

Notes. WM = working memory. CFCS = Considerations of Future Consequences scale. TFS-Current = Temporal Focus Scale current subscale. TFS-Future = Temporal Focus Scale future subscale. DD = Delay Discounting. SST-FTO = Scrambled Sentence Task for Future Time Orientation.

+

p < .10.

*

p < .05.

**

p < .01.

***

p < .001.

Table 3.

Study 3 Group Means and Standard Deviations on Background Characteristics, SST-FTO, and DD Measures.

EFT
 ERT
Measure M SD M SD
Age (in years) 38.01 10.86 37.16 10.73
Income ($ in thousands) 61.63 39.25 58.95 32.95
WM 7.36 1.04 7.37 1.04
CFCS 42.62 8.60 44.12 8.67
Enjoyment** 4.66 0.40 4.48 0.53
Excitement*** 4.55 0.47 3.98 0.68
Importance** 4.31 0.64 3.97 0.73
Fluency* 4.59 0.43 4.42 0.66
Vividness** 4.62 0.44 4.40 0.69
Event Ratings Composite*** 22.72 1.95 21.25 2.76
SST-FTO 0.57 0.24 0.59 0.26
log k** −6.78 2.17 −5.81 1.88
Open in a new tab

Notes. EFT = Episodic Future Thinking group. ERT = Episodic Recent Thinking group. WM = Working Memory. CFCS = Considerations of Future Consequences scale. SST-FTO = Scrambled Sentence Task for Future Time Orientation.

*

p < .05.

**

p < .01.

***

p < .001

Appendix B

SST-FTO Experimental Stimuli in Studies 2 and 3

  1. CONSIDER USUALLY FEEDBACK I IGNORE OTHERS*

  2. UNPREPARED HAPPENING FOR I'M WHAT'S PREPARED*

  3. ACTION CAREFUL MY SWIFT PROBLEMS DEMAND

  4. TOMORROW POINTLESS PRACTICAL SACRIFICING IS FOR*

  5. I RARELY LONG-TERM FREQUENTLY CONSEQUENCES CONSIDER*

  6. I THINGS AFTER DO THINKING BEFORE

  7. DECISIONS QUICKLY MY ARE DELIBERATELY MADE*

  8. MUCH THOUGHT WITHOUT I AFTER ACT*

  9. BEFORE FREQUENTLY I RARELY ACTING PLAN*

  10. CAREFUL I TAKE USUALLY ACTION QUICK

  11. I AHEAD THINKING DISLIKE USUALLY ENJOY*

  12. EASY THE I PATH CHOSE CHALLENGING*

  13. I SACRIFICES NOW LATER MAKE WILL*

  14. REQUIRES PATIENCE URGENCY USUALLY MY SUCCESS

  15. MIND QUICKLY MAKE-UP I CAREFULLY MY

  16. SENSIBLE IMPULSIVE IS BEHAVIOR MY USUALLY*

  17. IS HAVING PATIENCE HINDRANCE A(AN) ASSET*

  18. TAKE FREQUENTLY I RARELY TIME DECIDING*

  19. TIME SAVED MAKING PLANS I'VE WASTED*

  20. IT'S TEMPTATION RESIST TO DIFFICULT EASY

  21. MOSTLY IMMEDIATE I FUTURE CONSIDER OUTCOMES

  22. DISLIKE MANY PLANNING PEOPLE AHEAD PREFER

  23. ARE BEST AHEAD DAYS HERE MY

  24. I RARELY THINGS SEE USUALLY THROUGH*

  25. GET FRUSTRATED ME MOTIVATED CHALLENGING TASK*

* Denotes item retained in 16-item measure in Study 3.

References

  1. Basile AG, & Toplak ME (2015). Four converging measures of temporal discounting and their relationships with intelligence, executive functions, thinking dispositions, and behavioral outcomes. Front Psychol, 6, 728. doi: 10.3389/fpsyg.2015.00728 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bickel WK, & Marsch LA (2001). Toward a behavioral economic understanding of drug dependence: delay discounting processes. Addiction, 96(1), 73–86. doi: 10.1080/09652140020016978 [DOI] [PubMed] [Google Scholar]
  3. Bogg T, & Roberts BW (2013). The case for conscientiousness: evidence and implications for a personality trait marker of health and longevity. Ann Behav Med, 45(3), 278–288. doi: 10.1007/s12160-012-9454-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Buhrmester M, Kwang T, & Gosling SD (2011). Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data? Perspect Psychol Sci, 6(1), 3–5. doi: 10.1177/1745691610393980 [DOI] [PubMed] [Google Scholar]
  5. Burnham MJ, Le YK, & Piedmont RL (2018). Who is Mturk? Personal characteristics and sample consistency of these online workers. Mental Health, Religion & Culture, 1–11. doi: 10.1080/13674676.2018.1486394 [DOI] [Google Scholar]
  6. Castella J, Minguell G, Muro A, Sotoca C, & Estaun S (2018). Intervention based on Temporal Orientation to reduce alcohol consumption and enhance risk perception in adolescence. Quadernos De Psicologia, 20(1), 53–63. doi: 10.5565/rev/qpsicologia.1417 [DOI] [Google Scholar]
  7. Clark LA, & Watson D (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7(3), 309–319. doi:Doi 10.1037/1040-3590.7.3.309 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Costa PT, McCrae RR, & Dye DA (1991). Facet Scales for Agreeableness and Conscientiousness: A Revision of the NEO Personality Inventory. Personality and Individual Differences, 12(9), 887–898. doi: 10.1016/0191-8869(91)90177-d [DOI] [Google Scholar]
  9. Crockett RA, Weinman J, Hankins M, & Marteau T (2009). Time orientation and health-related behaviour: measurement in general population samples. Psychol Health, 24(3), 333–350. doi: 10.1080/08870440701813030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Daniel TO, Sawyer A, Dong Y, Bickel WK, & Epstein LH (2016). Remembering Versus Imagining: When Does Episodic Retrospection and Episodic Prospection Aid Decision Making? Journal of Applied Research in Memory and Cognition, 5(3), 352–358. doi: 10.1016/j.jarmac.2016.06.005 [DOI] [Google Scholar]
  11. Daniel TO, Stanton CM, & Epstein LH (2013). The future is now: reducing impulsivity and energy intake using episodic future thinking. Psychol Sci, 24(11), 2339–2342. doi: 10.1177/0956797613488780 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Daugherty JR, & Brase GL (2010). Taking time to be healthy: Predicting health behaviors with delay discounting and time perspective. Personality and Individual Differences, 48(2), 202–207. doi: 10.1016/j.paid.2009.10.007 [DOI] [Google Scholar]
  13. Davies M (2008-). The Corpus of Contemporary American English (COCA): 560 million words, 1990-present. https://corpus.byu.edu/coca/ [Google Scholar]
  14. Demeyer I, & De Raedt R (2014). The Effect of Future Time Perspective Manipulation on Affect and Attentional Bias. Cognitive Therapy and Research, 38(3), 302–312. doi: 10.1007/s10608-013-9584-6 [DOI] [Google Scholar]
  15. Epstein LH, Richards JB, Saad FG, Paluch RA, Roemmich JN, & Lerman C (2003). Comparison between two measures of delay discounting in smokers. Experimental and Clinical Psychopharmacology, 11(2), 131–138. doi: 10.1037/1064-1297.11.2.131 [DOI] [PubMed] [Google Scholar]
  16. Gamble B, Moreau D, Tippett LJ, & Addis DR (2019). Specificity of Future Thinking in Depression: A Meta-Analysis. Perspect Psychol Sci, 14(5), 816–834. doi: 10.1177/1745691619851784 [DOI] [PubMed] [Google Scholar]
  17. Griffiths A, Hill R, Morgan C, Rendell PG, Karimi K, Wanagaratne S, & Curran HV (2012). Prospective memory and future event simulation in individuals with alcohol dependence. Addiction, 107(10), 1809–1816. doi: 10.1111/j.1360-0443.2012.03941.x [DOI] [PubMed] [Google Scholar]
  18. Hall PA, & Fong GT (2003). The effects of a brief time perspective intervention for increasing physical activity among young adults. Psychology & Health, 18(6), 685–706. doi: 10.1080/0887044031000110447 [DOI] [Google Scholar]
  19. Hallford DJ, Austin DW, Takano K, & Raes F (2018). Psychopathology and episodic future thinking: A systematic review and meta-analysis of specificity and episodic detail. Behav Res Ther, 102, 42–51. doi: 10.1016/j.brat.2018.01.003 [DOI] [PubMed] [Google Scholar]
  20. Haner M, & Rude S (2015). Establishing the Reliability and Validity of a Performance Measure of Big Picture Appraisal. Cognitive Therapy and Research, 39(5), 709–719. doi: 10.1007/s10608-015-9688-2 [DOI] [Google Scholar]
  21. Johnson MW, & Bickel WK (2008). An algorithm for identifying nonsystematic delay-discounting data. Exp Clin Psychopharmacol, 16(3), 264–274. doi: 10.1037/1064-1297.16.3.264 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kleim B, Graham B, Fihosy S, Stott R, & Ehlers A (2014). Reduced Specificity in Episodic Future Thinking in Posttraumatic Stress Disorder. Clin Psychol Sci, 2(2), 165–173. doi: 10.1177/2167702613495199 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Koffarnus MN, & Bickel WK (2014). A 5-trial adjusting delay discounting task: accurate discount rates in less than one minute. Exp Clin Psychopharmacol, 22(3), 222–228. doi: 10.1037/a0035973 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Mischel W, Shoda Y, & Rodriguez MI (1989). Delay of gratification in children. Science, 244(4907), 933–938. doi: 10.1126/science.2658056 [DOI] [PubMed] [Google Scholar]
  25. Nederhof AJ (1985). Methods of Coping with Social Desirability Bias - a Review. European Journal of Social Psychology, 15(3), 263–280. doi:DOI 10.1002/ejsp.2420150303 [DOI] [Google Scholar]
  26. Paulhus DL, & John OP (1998). Egoistic and moralistic biases in self-perception: The interplay of self-deceptive styles with basic traits and motives. Journal of Personality, 66(6), 1025–1060. doi:Doi 10.1111/1467-6494.00041 [DOI] [Google Scholar]
  27. Peters J, & Buchel C (2010). Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions. Neuron, 66(1), 138–148. doi: 10.1016/j.neuron.2010.03.026 [DOI] [PubMed] [Google Scholar]
  28. Posner MI, & Rothbart MK (2000). Developing mechanisms of self-regulation. Development and Psychopathology, 12(3), 427–441. doi:Doi 10.1017/S0954579400003096 [DOI] [PubMed] [Google Scholar]
  29. Robinson MD, & Neighbors C (2006). Catching the mind in action: Implicit methods in personality research and assessment Handbook of Multimethod Measurement in Psychology. (pp. 115–125). [Google Scholar]
  30. Rude SS, Wenzlaff RM, Gibbs B, Vane J, & Whitney T (2002). Negative processing biases predict subsequent depressive symptoms. Cognition & Emotion, 16(3), 423–440. doi: 10.1080/02699930143000554 [DOI] [Google Scholar]
  31. Rung JM, & Madden GJ (2018). Experimental reductions of delay discounting and impulsive choice: A systematic review and meta-analysis. J Exp Psychol Gen, 147(9), 1349–1381. doi: 10.1037/xge0000462 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Sanchez A, Everaert J, De Putter LM, Mueller SC, & Koster EH (2015). Life is … great! Emotional attention during instructed and uninstructed ambiguity resolution in relation to depressive symptoms. Biol Psychol, 109, 67–72. doi: 10.1016/j.biopsycho.2015.04.007 [DOI] [PubMed] [Google Scholar]
  33. Shipp AJ, Edwards JR, & Lambert LS (2009). Conceptualization and measurement of temporal focus: The subjective experience of the past, present, and future. Organizational Behavior and Human Decision Processes, 110(1), 1–22. doi: 10.1016/j.obhdp.2009.05.001 [DOI] [Google Scholar]
  34. Software M (2015). Inquisit 4: Millisecond Software. Retrieved from https://www.millisecond.com [Google Scholar]
  35. Steinberg L, Graham S, O'Brien L, Woolard J, Cauffman E, & Banich M (2009). Age differences in future orientation and delay discounting. Child Dev, 80(1), 28–44. doi: 10.1111/j.1467-8624.2008.01244.x [DOI] [PubMed] [Google Scholar]
  36. Story GW, Vlaev I, Seymour B, Darzi A, & Dolan RJ (2014). Does temporal discounting explain unhealthy behavior? A systematic review and reinforcement learning perspective. Front Behav Neurosci, 8, 76. doi: 10.3389/fnbeh.2014.00076 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Strathman A, Gleicher F, Boninger DS, & Edwards CS (1994). The Consideration of Future Consequences - Weighing Immediate and Distant Outcomes of Behavior. Journal of Personality and Social Psychology, 66(4), 742–752. doi:Doi 10.1037/0022-3514.66.4.742 [DOI] [Google Scholar]
  38. Sze YY, Stein JS, Bickel WK, Paluch RA, & Epstein LH (2017). Bleak Present, Bright Future: Online Episodic Future Thinking, Scarcity, Delay Discounting, and Food Demand. Clin Psychol Sci, 5(4), 683–697. doi: 10.1177/2167702617696511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Teuscher U, & Mitchell SH (2011). Relation between Time Perspective and Delay Discounting: A Literature Review. Psychological Record, 61(4), 613–632. doi:Doi 10.1007/Bf03395780 [DOI] [Google Scholar]
  40. Viviani R, Dommes L, Bosch JE, Stingl JC, & Beschoner P (2017). A Computerized Version of the Scrambled Sentences Test. Front Psychol, 8, 2310. doi: 10.3389/fpsyg.2017.02310 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wenzlaff RM (1993). The mental control of depression: Psychological obstacles to emotional well-being. Englewood Cliffs, NJ: Prentice Hall. [Google Scholar]
  42. Wenzlaff RM, & Bates DE (1998). Unmasking a cognitive vulnerability to depression: How lapses in mental control reveal depressive thinking. Journal of Personality and Social Psychology, 75(6), 1559–1571. doi:Doi 10.1037/0022-3514.75.6.1559 [DOI] [PubMed] [Google Scholar]
  43. Woods DL, Kishiyamaa MM, Lund EW, Herron TJ, Edwards B, Poliva O, … Reed B (2011). Improving digit span assessment of short-term verbal memory. J Clin Exp Neuropsychol, 33(1), 101–111. doi: 10.1080/13803395.2010.493149 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Zimbardo PG, & Boyd JN (1999). Putting Time in Perspective: A Valid Reliable Indivual-Difference Metric. Journal of Personality and Social Psychology, 77(6), 1271–1288. doi: 10.1037/0022-3514.77.6.1271 [DOI] [Google Scholar]
  45. Zimbardo PG, Keough KA, & Boyd JN (1997). Present time perspective as a predictor of risky driving. Personality and Individual Differences, 23(6), 1007–1023. doi:Doi 10.1016/S0191-8869(97)00113-X [DOI] [Google Scholar]

RESOURCES