A Cyclical Time Concept Increases the Perceived Predictability of the Future and Reduces the Perceived Risk of Unlikely,but not Likely Risks

Abstract

Time can be perceived in linear terms, but also in cyclical terms. For example, people may think about the progress of time in terms of years, moving linearly from 2025 to 2026 and further onwards or they may think about time in cyclical terms, following the four seasons in an eternal cycle. We argue that when time is perceived as cyclical, similarities across time are more salient. For example, the four seasons always repeat themselves in the same order. Based on the assumption that similarities across time allows prediction about the future occurrence or non-occurrence of events based on their past (non-)occurrence than dissimilarities, we hypothesize that an experimentally induced cyclical time perception leads people to see the future as more predictable and therefore as less risky. Importantly, we also hypothesize this only applies to uncommon risks, but not to common risks. After all, when people adopt a cyclical time perspective, this allows them to confidently predict that uncommon risks are unlikely to occur in the near future, given their non-occurrence in the past. In contrast, this should not have the same effect for common risks that are likely to occur both in the past and present. We report two pilot studies and three preregistered experiments (total N = 1555) that test these predictions. Experiment 1 shows that the future appears more predictable when people adopt a cyclical time concept. Experiment 2 replicates this and shows it reduces the perceived risk of unlikely threats. Finally, Experiment 3 replicates this but shows time concept does not affect the perceived risk of mundane threats. Together, these studies suggest that a linear versus cyclical time perception affects perceived risks, because it affects how people use knowledge of the past to predict the future.

Keywords

Perspectives on time temporal perspective cyclical time perceived risk judgment and decision making cultural differences

An unavoidable consequence of the passing of time is risk. The more time passes, the more opportunities there are for things to go wrong and therefore the higher the risks (Johnson et al., 2020; Keren & Roelofsma, 1995; Rachlin et al., 1986, 1994; Stevenson, 1986). In studying how people perceive risks as they occur in time, most psychological research focuses on how people weigh and perceive information about risks and uncertainty. Most notably, Prospect Theory provides a probability weighting function that models the overweighting of small and underweighting of large probabilities, leading to an exaggerated concern with unlikely risks (Kahneman & Tversky, 1979).

In contrast, much less attention has been devoted to focusing on how people perceive the time in which that risk and uncertainty takes place. Here, we focus on the distinction between linear and cyclical perspectives on time. Time can be represented in a linear manner as moving from the past via the present to the future following an irreversible and unidirectional path, without returning to previous states. But time can also be perceived in a cyclical manner. A cyclical view of time suggests that events recur, following some pattern (Graham, 1981; Müller & Giesbrecht, 2006; Overton, 1994). In many cases, this is objectively true. For example, the four seasons do indeed return in the same order across time in a cyclical manner given the course of the sun around the moon.

Earlier human civilizations often perceived time in cyclical terms, possibly because their perception of time was grounded in astronomical observations. But their cyclical time perspective extended much beyond the (objectively true) one-year cycle of the earth around the moon. The Babylonians, for example, believed that the universe moves in a cycle of 36,000 years at the end of which history would start anew and all historical events would re-occur, roughly as they had in the past. Such beliefs were not uncommon in the classical era, where people believed human history consists of reoccurring cycles (Roeckelein, 2008).

Christianity reduced reliance on a cyclical time perspective, likely because of the central role afforded to the death and resurrection of Jesus – a singular act of God to sacrifice his only son to forgive the original sin, not a repeating series of sacrifices of a variety of sons to address various sins – is incompatible with a cyclical time perspective. Also, the Christian view of history, running from creation to the end of days via a single divine plan, is irreconcilable with a cyclical time perspective. This may be one reason why most people today in the West predominantly think in linear terms about time. Indeed, it has been argued that this tendency is weaker in East Asia and other cultures, where people are more likely to switch between linear and cyclical time perspectives (Loewe, 1999; Yamada & Kato, 2006).

That said, Westerners are also not necessarily stuck in a linear perspective. As already mentioned, people regularly switch to cyclical perspectives on time, such as when thinking of the four seasons. Indeed, experimental inductions of a cyclical perspective on time have been shown to increase reliance on cyclical (versus linear) time perspectives and to influence subsequent decisions – supporting the idea that perspective on time are malleable (Tam & Dholakia, 2014; Xu et al., 2023). Such experimental manipulations of a cyclical time concept can also affect subsequent psychological functioning. Tam and Dholakia (2014) found for example that it can affect the amount of money that people save and Xu and colleagues (2023) found it can affect the likelihood of making pro-environmental choices.

Concepts of Time and Perceived Risk

Here, we test the hypothesis that a cyclical time concept increases the perceived predictability of the future and therefore affects concern with risks. We base this prediction on the notion that because a cyclical time concept points to the repetition of events across time (Jones & Coviello, 2005), it highlights the regularity of routine activities (Ruscher, 2012) and thus creates a notable similarity between past, present, and future (Moser et al., 2012; Yamada & Kato, 2006). For example, the cyclical time concept associated with the four seasons highlights the fact that every year summer is preceded by spring and followed by autumn. This focus of a cyclical time concept on predictable, recurring elements of a one-year cycle thus creates clear expectation what a concrete year might look like. Like 2023 and 2024, it is likely that 2025 will also feature winter, spring, summer, and autumn. In comparison, a linear concept of time focuses attention on on-recurring elements and therefore is intrinsically unpredictable. As a result, a cyclical time concept makes one specific future year appear to be more similar to the overarching category of other years. Therefore, following work on the representativeness heuristic, that future year should be seen as likely to also be similar and therefore inherently more predictable, compared to when that future year is seen through the lens of a linear time concept (Kahneman & Tversky, 1972; Tversky & Kahneman, 1974; Tversky et al., 1982). Experiment 1 tests this idea by experimentally manipulating reliance on a cyclical (versus linear) time concept and measuring how this affects the perceived predictability of the future. We expect that a cyclical time concept increases perceived predictability.

Given this increase in perceived predictability, we hypothesize that a cyclical time concept reduces the perceived risk associated with uncommon and unlikely threats, such as nuclear meltdowns or terrorist attacks. After all, if a cyclical time concept increases the perceived similarity between the past, present, and future, then it also allows for a more confident extrapolation from the non-occurrence of unlikely, uncommon threats in the past to their expected non-occurrence in the future. For example, a cyclical time perspective allows one to extrapolate that given that there were no nuclear meltdowns or terrorist attacks in one's home-town in either spring, summer, fall or winter of past year, they will also likely not occur in the upcoming spring, summer, fall, or winter. Experiment 2 tests this idea by replicating Experiment 1 and extending it by measuring the perceived risk of such threats. We expect that a cyclical time concept decreases the perceived risk of these uncommon and unlikely threats.

For the same reason that leads us to formulate the above prediction, we also predict that a cyclical time concept does not reduce concern with common and mundane threats, such as the common cold (sore throat, runny nose, fever). After all, if a cyclical time concept points to the similarity between the past, present, and future, then it leads people to extrapolate from the common occurrence of such mundane threats in the past to their equally likely common occurrence in the future. For example, if one got the common cold about once every season, then one might extrapolate also getting the common cold in each of the future seasons. Hence, it will not reduce perceived risk. Showing this moderation not only identifies an important boundary condition of the predicted effect, but it also points to its mechanism: a cyclical time concept affects perceptions of risk because it facilitates extrapolating from the past to the future. Experiment 3 tests this idea by replicating Experiment 2 and extending it by measuring the perceived risk of both uncommon and common threats. We expect that a cyclical time concept only decreases the perceived risk of uncommon, but not of common threats.

An assumption behind these three predictions is that participants can intuitively grasp both time concepts and that both concepts are mentally available. After all, if people are inflexibly stuck in one of the two concepts of time and the alternative concept of time is dismissed at hand, then an experimental induction of the alternative time concept is likely to hit a brick wall and have no effect – or may even produce resistance and lead people to reaffirm their original, dominant time concept. After all, classic studies into ease of retrieval suggest that subjective difficulty in responding to a task designed to make one construct mentally available tends to produce the opposite effect because participants infer from that difficulty in responding to the task that the requested information is chronically unavailable (Schwarz, 1998, 2011; Wänke et al., 1995; Winkielman et al., 1998). Following that logic, difficulty in responding to an instruction to adopt one time perspective might lead participants in reaffirm the opposite perspective. For this reason, we first test in two pilot studies spontaneous differences in time concept and measure the degree to which participants agree with linear and cyclical time concepts. Although we do not formulate strong predictions, we expected that although people would likely favor a linear concept of time, a cyclical concept of time is not rejected out of hand by most participants.

Summary and Overview of Studies

In summary, we predict that a cyclical concept of time increases the perceived predictability of the future and thus reduces the perceived risk of uncommon threats, but not of common threats. After conducting two pilot studies testing spontaneous, baseline differences in time concept, we report three preregistered experiments that test the central hypotheses that a cyclical time concept (compared to a linear time concept) increases the perceived predictability of the future (Experiment 1), therefore reduces perceived risk of uncommon threats (Experiment 2), but not the perceived risk of mundane, common threats (Experiment 3). Across these studies, we report how we determined sample size, all data exclusions, all manipulations, and all measures in each study. To avoid nonnaïveté, participants were barred from participating in more than one study (Chandler et al., 2015). All participants provided informed consent. Studies were conducted consisted with guidelines of the German Psychological Society DGPS (Deutsche Gesellschaft für Psychologie, 2018). Data, materials, code, and preregistrations for all four studies are available at: https://researchbox.org/2699&PEER_REVIEW_passcode = LQOZBR

Pilot Studies 1 and 2

To get a sense of the degree to which people spontaneous recognize and rely on a linear versus cyclical time concept, we first conducted two exploratory pilot studies, in both the USA and China.

Method

Participants in Pilot Study 1 were 398 Americans (186 women, 212 men, mean age 36.2 years, 80.9% White, 6.3% Black, 6.0% Asian, 6.8% other) recruited via Cloud Research and participants in Pilot Study 2 were 400 Chinese (277 women, 123 men; M_age = 30.27, SD_age = 8.07) recruited via Credamo. In both studies, we preregistered a sample size of 400 (but received two fewer observations in Pilot Study 1 due to reasons beyond our control) to obtain an estimate of the distribution of participants’ concept of time that is within 5% of the true distribution.

Procedure

After signing informed consent, participants indicated their agreement with two statements: whether time is like “an arrow or a line. It always moves forward and never repeats itself” or is like “a wheel or a cycle. It keeps going in circles and repeating itself,” both between Strongly disagree (1) and Strongly agree (7). Participants also indicated using a forced choice whether they relied on a linear, a cyclical, or both time concepts, or another time concept (with open query). For exploratory purposes, we also administered in Pilot Study 1 the Short-Ten-Item Personality measure and a two-item measure of political ideology. These did not correlate (alpha corrected) with time perspective and are not further discussed.

Results

Americans agreed more strongly with a linear (M = 4.98, SD = 1.80) than a cyclical (M = 3.69, SD = 1.95) time perspective, t_paired(397) = 7.41, p < .0001, d = 0.37, 95%CI_d [.27; .47]. The same was the case for the Chinese, who also agreed more strongly with a linear (M = 5.35, SD = 1.60) than a cyclical (M = 3.61, SD = 1.79) time perspective, t_paired(399) = 11.08, p < .0001, d = 0.55, 95%CI_d [.45; .66]. Nonetheless, in both samples we found substantial variation. Only 13.3% of the Americans and 7.2% of the Chinese strongly agreed (7) with the linear and strongly disagreed (1) with the cyclical time statements. Similarly, although a majority of 51.8% of Americans and 63.2% of Chinese indicated they used a linear time concept on the forced-choice item, substantial minorities relied on a cyclical time concept (23.6% of Americans, 16.3% of Chinese) or both concepts (22.4% of Americans, 20.0% of Chinese; with 2.3% and 0.5% indicating another concept).

Experiment 1 – A Cyclical Time Concept Increases Perceived Predictability

Pilot data suggest that although agreement with a linear concept of time is stronger than with a cyclical time concept, a substantial minority is open to a cyclical time concept. Building on this, our next experiments focus on the main research question and test whether inducing a cyclical time concept affects the perceived predictability and risk associated with the future.

Method

Participants and Design

357 Americans were recruited via Cloud Research (214 women, 143 men, mean age 35.6 years, 79.6% White, 8.4% Black, 5.9% Asian, 6.2% other) and randomly assigned to either the linear or cyclical time perspective condition. We preregistered a sample size of 356, to obtain 95% power to detect a small-to-medium effect size of d = .35, but received one additional observation.

Manipulation

After signing informed consent, participants saw an illustration of the concept of time. In the linear time condition, time was illustrated with an arrow pointing from the past to the future, with the years 2018 to 2024 above it and a red dot indicating the current date. Note that Experiments 1–3 were conducted in the spring of 2018, meaning that participants made estimates six years into the future. In the cyclical time condition, time was illustrated with a circle suggesting that time turns in the cycle of the seasons. To keep conditions otherwise equal, the same time span of 2018 to 2024 was illustrated and a similar red dot indicating the current date. See Figure 1. In addition, in the linear time condition participants read that “The years pass by without end, continuing further on the arrow of time, and never returning,” while participants in the cyclical time condition read that “This annual cycle of time keeps repeating itself without end, always returning back again.”

Figure 1.

Stimuli Used to Induce a Cyclical (Top) and Linear (Bottom) Time Concept Across Experiments 1–3.

Measures

Next, participants indicated the perceived predictability of the future, using four six-point Likert items anchored at very predictable vs. very unpredictable, very certain vs. very uncertain, very safe vs. very risky, and very secure vs. very insecure. These four items correlated well, α = .85, and were combined into one index, with higher scores corresponding to a higher perceived predictability.

Results

As predicted, an Analysis of Variance (ANOVA) showed that participants in the cyclical time condition perceived the future to be more predictable (M = 3.41, SD = 1.07) than did participants in the linear time condition (M = 2.89, SD = 1.01), F(1, 355) = 22.23, p < .0001, eta²_p = .059, d = 0.50, 95%CI_d [.29; .71], suggesting a medium-sized effect.

Experiment 2 – A Cyclical Time Concept Decreases Perceived Risk of Uncommon, Extreme Threats

Experiment 1 showed that an experimentally induced cyclical concept of time increases the perceived predictability of the future. Building on this, Experiment 2 tests the preregistered hypothesis that inducing a cyclical concept of time decreases perceived risk of uncommon and extreme threats such as nuclear accidents. We also aim to replicate the effect on predictability, already established in Experiment 1.

Method

Participants and Design

100 Americans were recruited via Cloud Research (58 women, 42 men, mean age 37.8 years, 81% White, 11% Black, 6% Asian, 2% other) and randomly assigned to the linear or cyclical time condition. Using G*Power, we determined that N = 72 provides 90% power to detect the effect observed in Experiment 1, but we rounded this up and preregistered a sample of N = 100.

Manipulation and Measures

We used the same procedure as in Experiment 1, including the same four-item measure of predictability (α = .93), but added a 6-item measure of risk concern, adapted from Johnson and Tversky (1983). Participants were provided with “some health risks,” including homicide, terrorism, war, nuclear accidents, drowning, and airplane crashes, and were instructed to “[f]ollow your intuition and indicate how concerned you currently feel about each of them,” between very unconcerned (1) and very concerned (6). These six items correlated well, α = .89, and were combined into one index of perceived risk.

Results

First, we replicated the findings of Experiment 1: An ANOVA showed that participants in the cyclical time condition perceived the future to be more predictable (M = 3.39, SD = 1.36) than did participants in the linear time condition (M = 2.58, SD = 0.99), F(1, 98) = 11.71, p < .001, eta²_p = .107, d = 0.682, 95%CI_d [.28; 1.09], suggesting a medium-sized effect.

Second, an ANOVA showed that participants in the cyclical time condition were less concerned with these uncommon threats (M = 2.81, SD = 1.17) than were participants in the linear time condition (M = 3.35, SD = 1.17), F(1, 98) = 5.33, p = .023, eta²_p = .052, d = -0.462, 95%CI_d [−.86; −.06], suggesting a medium-sized effect.

Experiment 3 – A Cyclical Time Concept Decreases Concern with Uncommon but Not with Mundane Threats

Experiment 3 extends on the findings of Experiment 2 by including common, mundane threats in addition to uncommon threats. We preregistered the hypothesis that inducing a cyclical concept of time decreases the perceived risk of extreme threats such as nuclear accidents (replicating Experiment 2) but not the risk of mundane threats such as social rejection.

Method

Participants and Design

300 Americans were recruited via Cloud Research (145 women, 155 men, mean age 34.5 years, 76.3% White, 8.0% Black, 9.3% Asian, 6.3% other) and were randomly assigned to a 2 (Time Concept: linear vs. cyclical, between) $\times$ 2 (Type of Risks: extreme vs. mundane, within) mixed design. We set the sample size to 300 a priori based on the consideration that N = 146 would provide 80% power to replicate the effect found in Experiment 2, which we doubled (and then slightly rounded up) to account for the interaction. This decision followed Simonsohn (2014) who recommends doubling sample size per cell to test an interaction, under the assumption that the added factor (here: Type of Risks) eliminates the earlier-established effect (here: Time Concept).

Manipulation and Measures

The procedure was the same as in Experiment 2, except that in addition to concern for the risk of extreme threats measured in Experiment 2 (α = .86) we additionally measured concern for the risk of six mundane threats: physical appearance/ looks, whether friends like you, having the right partner, savings / finances, job security, and road traffic safety (α = .71).¹ These six items were constructed on the spot and based on the intuitive notion that many people experience occasionally may experience such threats. All twelve items were completed using the same six-point Likert scale. We also randomized the Presentation Order of the two types of threats (blockwise). We did not include the measure of predictability of Experiments 1 and 2.

Results

A 2 (Time Concept: linear vs. cyclical, between) $\times$ 2 (Type of Risks: common vs. uncommon, within) $\times$ 2 (Presentation Order) GLM on concern showed a main effect of type of risk, F(1, 296) = 122.81, p < .001, eta²_p = .29, showing that participants were more concerned with mundane, common threats (M = 3.81, SD = 0.88) than with the extreme, uncommon threats (M = 3.05, SD = 1.09). More importantly, this main effect was qualified by the predicted two-way interaction-effect with time-concept, F(1, 296) = 4.48, p = .035, eta²_p = .015. Separate one-sided t-tests showed that participants were less concerned with extreme risks in the cyclical (M = 2.93, SD = 1.08) than in the linear time condition (M = 3.18, SD = 1.10), t(298) = -1.93, p = .027, d = -0.22, 95%CI_dif [−.005; .490], replicating Experiment 2, but as predicted were equally concerned with mundane risks in the cyclical (M = 3.83, SD = 0.88) as in the linear time condition (M = 3.79, SD = 0.88), t(298) = 0.45, p = .326, d = 0.05, 95%CI_dif [−.17; .28]. Conducting the same tests using Bayesian analysis, we found weak support in favor of the hypothesis that a cyclical time concept reduced concerns with extreme risks (compared to linear time concept), BF₁₀ = 1.45, but evidence that it did not reduce concerns with moderate risks, BF₁₀ = 0.09 (Figure 2).

Figure 2.

Results of Experiment 3: Cyclical Time Concept Reduces Concern for Uncommon Risks Compared to Linear Time Concept, but Not Reduces Concern for Common Risks. Black Diamonds Indicate Means and Error Bars Represent 95% Confidence Intervals. Statistical Significance Is Indicated As: * p < .05 and ns p > .05.

General Discussion

Three preregistered experiments tested how a cyclical versus linear time concept affects perceived risks associated with the future. Consistent with our preregistered predictions, results showed that (compared to a linear time perspective) a cyclical time perspective leads people to see the future as more predictable (Experiments 1 and 2). As a result, a cyclical perception of time reduces the perceived risk of uncommon (Experiments 2 and 3), but not mundane risks (Experiment 3). Together, these studies show that how people perceive time affects their perception of the future. But a cyclical time perspective does not simply reduce concern with the future. Rather, it increases the degree to which people extrapolate from the past to the future, thus reducing concern with uncommon but not with common threats and risks.

Relation to the Literature

Our findings add to an emerging literature showing that experimental inductions of a cyclical perspective on time can affect judgments, but they also qualify or refine existing work. Most notably, Moser et al. (2012) found in a single study that participants in a cyclical time perspective condition did not differ in their concern with the risks of nuclear waste from participants in a linear time perspective condition, although that difference was marginally significant (p = .11) among participants with more malleable beliefs. Our findings suggest their finding may have been a false negative, given that our studies did show that link and had more statistical power (n = 178, n = 50, and n = 150 per cell in Experiments 1–3) than theirs (n ≈ 27 per cell).

Our findings also connect to previous research showing that a cyclical time concept produces more abbreviated and accurate estimates of affect duration (Ruscher, 2012). Both this earlier research and the current findings suggest that a cyclical time concept steers people's attention toward mundane routines and therefore reduces overreliance on the situationally focal yet uncommon catastrophes. In other words, a cyclical time concept helps in inhibiting people's unrealistic pessimism.

Moreover, other recent findings suggest that a cyclical time can also reduce the unrealistic optimism that people often display when they think about the future in linear terms, because it focuses attention on the continuation of financial burden (Tam & Dholakia, 2014). Combining these with our findings, we predict that although a cyclical time concept increases savings to deal with mundane challenges, it decreases savings to deal with uncommon or unlikely challenges. In other words, we propose that a cyclical time concept helps people build a more realistic perception of the future, by reducing both unrealistic pessimism and optimism. To test this, future research could take a further step and compare the effects of cyclical time concept on pessimism and optimism.

Xu et al. (2023) recently found that a cyclical time concept increases the likelihood of engaging in pro-environmental behavior because it increases the likelihood that people include the environment in the self. This reasoning is consistent with our notion that a cyclical time perspective increases perceived similarity between the past and future. At the same time, our findings suggest that the relation between time-concept and likelihood of engaging in pro-environmental behavior may be moderated by the type of risks associated with climate change that are salient. In particular, when focusing on more dramatic future risks associated with climate tipping points, such as the complete disappearance of the Arctic and Antarctic ice-sheets or a collapse of the Atlantic meridional overturning circulation (Armstrong McKay et al., 2022; Van Westen et al., 2024), a cyclical time concept may lead people to underestimate such risks, given their extreme dissimilarity with the present. This suggests that inducing a cyclical time concept is not always an effective way to increase pro-environmental concerns and in fact might produce the opposite effect, depending on what risks people perceive. Rather, a more productive approach may be to instead adopt a strong linear time focus and help people extrapolate the incremental consequences of continued emissions of greenhouse gasses (Lammers & Crusius, 2024).

In our research, we focused on the effect of conceptualization of time on perceived risk. An interesting question is whether causal paths may also lead in an opposite direction, meaning that people may be more inclined to shift toward cyclical concepts when risks and unpredictability are perceived to be high. Indeed, research into public and political discourse has noted that people are more inclined to draw historical analogies in times of crises and unpredictability (Brändström et al., 2004; Ghilani et al., 2017). Although this research does not make any explicit references to cyclical concepts of time, the finding connects to ours because it suggests that when risks are perceived to be high, people in response tend to draw comparisons across time and highlight the similarities between current and historic events, much like a cyclical time concept does.

Cultural Similarity

In contrast to earlier work (Loewe, 1999; Yamada & Kato, 2006), our two Pilot studies did not find evidence for the idea that reliance on cyclical time concepts is stronger in China than in the West. In fact, Chinese participants agreed equally strongly with a cyclical time concept as Americans, d = -0.04, 95%CI_d [−.18; .10], and even agreed more strongly with a linear time concept than Americans, d = 0.22, 95%CI_d [.08; .36]. We caution though against drawing strong conclusions from this. Most importantly, we did not collect these two studies to make cultural comparisons. The two studies were not collected simultaneously and – more importantly – differ in more ways than mere culture. For example, the participants in our Chinese sample were younger on average and more likely to be female, than the American participants (gender and age did not correlate with time perspective). Although we are not aware of literature directly comparing Chinese Credamo and American Cloud Research samples, descriptions of the typical samples provided by the two companies suggest that Credamo tend to oversample higher-educated participants more than does Cloud Research. With these caveats in mind, we note a possible explanation for this null-effect is that due to globalization, Chinese culture is becoming more Western (Hamamura et al., 2021) in particular among urbanized, younger generations (Zeng & Greenfield, 2015). In addition, given that people in Eastern cultures tend to perceive the future as more flexible and changeable than those in Western cultures (Briley, 2009; Ji et al., 2009), this may lead Chinese people to conceptualize time as a mobile, linear concept.

Limitations and Alternative Explanations

We find across three studies that inducing a cyclical time perspective by instructing participants to consider the seasons, rather than the years, reduces perceived risk. Future research may want to identify exceptions to this rule. One likely exception occurs when the risk is directly tied to elements in the time-cycle, such as the seasons. For example, people likely consider the risk of sun-burn to be higher when exposed to our cyclical time perspective manipulation during the summer – given that it can increase their awareness of the currently increased risks. Or they may perceive the risk of an increase of the price of fresh fruit to be higher at the end of summer (cf. Ma et al., 2025).

A limitation to our studies is that we did not include manipulation checks or process variables. Although our findings were consistent with our preregistered predictions, we lack empirical evidence testing it. One alternative explanation of our findings also raised in the literature is that a cyclical conceptualization leads to a more abstract construal of time, compared to a linear time concept (Liberman et al., 2002; Trope & Liberman, 2003). An abstract construal of time increases (over-)confidence in predictions because it reduces perceived complexity, shifts focus away from unexpected events, and instead creates the sense that events will happen exactly as expected (Nussbaum et al., 2006). On the one hand, we note that our manipulation works partially against this. After all, the cyclical time concept condition focused attention on the four seasons, which are relatively concrete and qualitatively clearly distinguishable concrete elements of time. In contrast, the linear time concept condition focused attention on calendar years, which (especially before experiencing them) may seem relatively indistinguishable and abstract. On the other hand, the four seasons are of course re-occurring elements, while the years are unique and non-re-occurring. And people are more likely to have an abstract construal if they focus attention on such re-occurring elements (Fujita et al., 2008; Kivetz & Tyler, 2007; Trope & Liberman, 2003). All in all, we thus believe that currently it is unclear whether abstraction is relevant to our effect and – if so – whether it acts as a causal or as a suppressing mechanism. Future research may want to disentangle time-concept and abstraction more systematically. For example, future studies could do so by orthogonally manipulating abstraction and time concepts. One way to do so, could be by comparing the effect of more concrete and more abstract inductions of time.

Another alternative explanation could be that because a cyclical time concept shifts attention to annually repeating events such as birthdays, holidays or the four seasons, it changes psychological functioning. One such way in which it could change thought is by inducing nostalgia – a powerful emotion that is also related to the experience of time and that can indeed be activated by memories of birthdays and holidays or other personally significant memories (Van Tilburg et al., 2019; Wildschut et al., 2006). Indeed, mapping onto the currently demonstrated effects of perceived predictability, a wealth of evidence indeed shows that nostalgia provides a sense of continuity, in part because it induces stronger abstract and holistic thinking (Hong et al., 2021, 2022; Sedikides et al., 2015). Relatedly, because a cyclical time concept shifts attention to the seasons, it may shift attention to nature, which has been shown increase feelings of autonomy, competence, self-determination and psychological well-being and thus likely with reduced worrying (Yang et al., 2022, 2024).

Clearly, although we based our prediction on the notion that a cyclical time perspective increases the perceived similarity and therefore predictability across time (Ji et al., 2009; Moser et al., 2012), we cannot rule out other mechanisms. It does not seem unlikely that these alternative mechanisms also contribute to the current finding. We propose that future research could investigate this and offer a mechanistic understanding of the relation between cyclical time concepts and other psychological processes associated with time, by measuring multiple process variables and testing their relative effect (but see Fiedler et al., 2011) or by orthogonally manipulating time perspective and possible confounding factors.

Future research could also improve on our design by including covariates such as risk tolerance or chronic anxiety. In addition, we note that we used a relatively simple design that compared common / mundane and uncommon risks as a fixed factor. Future work could use a more sophisticated design and treat the degree to which risks are common or uncommon (quantified on a continuous scale) as a random factor. In designing such future studies, we recommend that researchers use a stimulus sampling approach (Wells & Windschitl, 1999). Using such an approach, participants freely generate stimuli – in this case, common and uncommon risks – themselves (prior to adopting one of two time-concepts and evaluating their concern with these risks). This would offer a variety of benefits. Most importantly, it would avoid the artificial and potentially unrepresentative nature of our stimulus selection (Fiedler, 2011). But it would also avoid any idiosyncratic factors influencing our results. For example, it is possible that people differ in what they consider common and uncommon risks (for example, due to differences in life circumstances). A stimulus sampling approach would avoid such issues.

Conclusion

Three experiments show that a cyclical (versus linear) time concept increases the perceived predictability of the future and increases the degree to which people extrapolate from the past to the future, thus reducing people the perceived risk of uncommon but not of common threats and risks.

Footnotes

ORCID iDs

Joris Lammers

Zhengtai Liu

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

No generative AI was used in this research.

Data Availability Statement

All studies were preregistered. Preregistrations, materials, data, code, and output for all five studies are available at: https://researchbox.org/2699&PEER_REVIEW_passcode=LQOZBR

Notes

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