Enjoyable experiences go stale in three distinct temporal profiles, and the patterns of "hedonic decline" are stable across time and stimuli, within an individual

Identifying the temporal profiles of hedonic decline. Jeff Galak, Jinwoo Kim, Joseph P. Redden. Organizational Behavior and Human Decision Processes, Volume 169, March 2022, 104128. https://doi.org/10.1016/j.obhdp.2022.104128

Highlights

• Hedonic decline unfolds in three distinct temporal profiles (shapes): Flat, Steady Decline, Rapid Onset Decline.

• Hedonic decline temporal profiles are stable across time and stimuli, within an individual.

• Hedonic decline temporal profiles can be explained by variation in Need for Cognition.

• Hedonic decline temporal profiles have significant downstream consequences on future consumption choice and timing.

• Understanding how hedonic decline temporal profiles unfold can be of great benefit to individuals and to organizations.

Abstract: The unfortunate reality of the human condition is that enjoyable experiences become less enjoyable with time and repetition. This hedonic decline has been well documented across a variety of stimuli and experiences. However, previous work has largely ignored the possibility that the temporal profile of hedonic decline varies at the individual level. In the present work, we first identify three temporal profiles of hedonic decline: flat, steady decline, and rapid onset decline. We next demonstrate that these temporal profiles of hedonic decline are relatively stable across both stimuli and time for any given individuals. That is, a temporal profile observed for one stimulus can be used to predict the temporal profile of hedonic decline for a novel stimulus or the same stimulus at a future date. We further explore the psychological underpinnings of these differences and note that Need for Cognition, a stable personality trait, partially explains which individuals will be more likely to experience different temporal profiles. Finally, we demonstrate two important downstream consequences to these three different temporal profiles of hedonic decline: re-consumption choice and re-consumption timing. This work provides a first look into the various ways in which hedonic decline operates at an individual level and documents predictable heterogeneity in such tendencies, an important departure from previous research looking at hedonic decline in aggregate.

7. General discussion

Across five studies we demonstrate that hedonic decline tends to follow one of three distinct patterns: Rapid Onset Decline, Steady Decline, or Flat. Rapid Onset Decline is characterized by a fast initial decline in enjoyment that tapers off over time. Steady Decline is characterized by the opposite in that there is little hedonic decline at first, but then hedonic decline accelerates once a threshold is seemingly reached. Finally, Flat is characterized by little to no hedonic decline at all. These three temporal profiles consistently emerged across stimuli including food, music, art, and videos. Critically, ex ante, it is not obvious that these are the three temporal profiles that must emerge from such an investigation. Indeed, increases in enjoyment (of various temporal profiles), linear decreases in enjoyment, irregular and/or cyclical changes in enjoyment, or simply no clustering at all were all plausible as common profiles.

Instead, we consistently observed the same three temporal profiles of hedonic decline regardless of the stimuli. Critically, not only do these temporal profiles consistently appear across studies, they appear to be stable for an individual both across time and across stimuli. That is, if an individual is classified into one of these three temporal profiles, they will likely experience hedonic decline the same way both for the same stimulus sometime in the future, as well as a novel stimulus. This type of consistency has yet to be documented in any capacity in the literature on hedonic decline. Indeed, previous work has treated hedonic decline either as a monolith where all people experience hedonic decline the same way, or has allowed for individual variation primarily as a nuisance to statistically control for when modeling more general effects. The present work moves well beyond these prior findings by showing that people experience hedonic decline with predicable heterogeneity that is stable across time and stimuli.

This suggests that these three temporal profiles are fundamental to understanding how one experiences hedonically relevant stimuli over time. As far as we know, no fundamental theory in psychology argues that a given person should experience hedonic decline in generally the same way across stimuli. However, there is ample evidence for stable individual traits that could help account for this. Here, we explore just one such well-known trait, that of need for cognition (NFC in Studies 2 and 3). Of course, we expect that a multitude of other individual differences likely contribute to why a person experiences a particular type of hedonic decline. Potential candidates for future research here could include mindfulness (Bishop et al., 2004), optimal stimulation (Raju, 1980), variety seeking (van Trijp & Steenkamp, 1992), self control (Tangney et al., 2004), as well as many others.

In fact, in a post-hoc analysis of our study demographics, we found that older participants were more likely to exhibit a Flat pattern than a Rapid Onset Decline pattern (see Supplemental Materials for details), yet no differences emerged for gender. This is largely consistent with the notion that older individuals tend to require a lower need for stimulation, a possible correlate of hedonic decline (Kish and Busse, 1968, Raju, 1980). There are likely many other demographic and psychological difference that help explain cluster membership, and we expect future work will uncover such differences to further our understanding of the antecedents of hedonic decline. In the present work, we limit ourselves to NFC to first document a novel antecedent to hedonic decline, and second to demonstrate that the three clusters we observe are not just random artifacts of our analytical approach. Rather, these groupings can be predicted, in part, by theory.

Finally, aside from documenting the existence and partial psychological underpinnings of three hedonic decline clusters, we show two critical downstream consequences: re-consumption behavior (Study 4a), and future consumption timing (Study 4b). For people with rapid hedonic decline (Rapid Onset Decline), the choice to re-consume a once enjoyable stimulus is decreased and delayed significantly after just a few exposures. The same is not true for those with little hedonic decline (Flat), as they are more willing to immediately re-consume a stimulus even after repeated exposure to it. In other words, in order to predict either re-consumption behavior or preference for future consumption timing for any given individual, it is not enough to know their initial enjoyment with a stimulus, nor even the number of previous consumption episodes of that stimulus. Rather, to predict re-consumption and preference for future consumption timing, one must also know which hedonic decline trajectory that person is likely to experience.

This research has important implications for our understanding of psychology in that it contributes to our growing understanding of how heterogeneity in experiences can help predict behavior at the individual level (Bolger et al., 2019). In the field of psychology, in particular, there has been limited work devoted to including heterogeneity of human experiences in theory and model development. This work demonstrates the clear importance of doing so, and is meant to be a steppingstone for those working to develop a larger theory of hedonic consumption. Critically, this work does much more than simply claim that people are different (which is largely self-evident), but rather it also identifies specific groups of people in terms of how they respond to hedonic stimuli. Our behavioral results (Studies 4a and 4b) also suggest that some people may naturally show less hedonic decline, making it easier for these Flat decliners to maintain their focus when listening to a speaker, performing a work task, or building expertise. Alternatively, these Flat decliners likely also find it difficult to exhibit self-control at other times such as eating an indulgent food, playing a video game, or spending money on a shopping spree.

This research has implications for practitioners as well. A firm that can identify the hedonic decline type for a person can then use it to predict future preferences. For instance, if a music streaming service sees a person drop a particular song from a playlist after a few plays, this may indicate a Rapid Onset Decliner who needs lots of variety in the future. Alternatively, if a person has been identified as a Flat type, then they are likely to keep using a product more in the long term (suggesting a firm should invest more to acquire and keep them). Given these benefits, we expect managers will find creative ways to identify one’s hedonic decline type. Possibilities include ongoing satisfaction surveys like many retailers and fast food companies offer on the back of receipts, the ongoing ratings of episodes as one watches a streaming series, or the length of time one spends on a media site before losing interest. Likewise, profiles may be built for individuals using other general measures, such as need for cognition, age, etc.

There is also the possibility of our work informing how future researchers should approach the study of hedonic decline more generally. As aforementioned, most research studying hedonic responses of any kind over time, generally assumes that all people follow a similar trajectory (linear) of hedonic decline. To the extent that our work shows this to be far from the case, there is a simple and specific prescription that all researchers should follow: ascertain if the research question of interest varies as a function of cluster membership. That is, much work in this space uses experimental manipulations to demonstrate a shift in overall hedonic decline. A simple addition to that research approach would be to first conduct a cluster analysis as done in this paper, and then test if any experimental manipulation varies as a function of cluster membership. In Supplemental Materials Study S5 we found that disrupting an experience slowed the rate of hedonic decline across all clusters, but this did not need to be the case. It was equally plausible that the disruption would only influence, say, the individuals in the Rapid Onset Decline cluster. For future work, we would encourage all researchers to understand if their interventions are universally applicable, or rather apply to only some subset of individuals. At a minimum, researchers should explore modeling results with individual-level random effects for the intercept, linear, and quadratic terms, and examine the histograms of the individual estimates. Doing so will yield greater insight into the underlying psychology of whatever is being studied.

There are, of course, still some unanswered questions on which the present manuscript can only speculate. For instance, do these same hedonic decline clusters emerge for all stimuli? By design, all of our studies employed repetition in the form of repeating a discrete stimulus (e.g. a single song repeated, or a single type of food repeatedly consumed) to induce hedonic decline, but would we observe the same clusters for stimuli that are structurally different? For instance, videos provide a dynamic stimulus that unfolds in new ways over time. To explore this question, we ran a study in which participants watched a 13-minute nature documentary, and rated their enjoyment every 30 s (without stopping consumption, via an in-experience measure). Consistent with our other studies, we again found the same three clusters of hedonic decline, even for this longer continuous experience (Supplemental Materials Study S6). Beyond continuous versus discrete, another structural difference could be the duration of the experience. In all of our studies, the experiences were relatively short lived, lasting just minutes in totality. In contrast, other work has looked at longer, and perhaps more complex stimuli, such as full length movies or visits to museums (O'Brien, 2019). Indeed, such work has found little hedonic decline with repetition, which may reflect a shift in the mix of our three cluster types for longer and more complex experiences. We leave this and other related questions to future research.

There is also the question of how such clustering would unfold for negative or aversive stimuli. For instance, Nelson & Meyvis (2008) found similar results of the influence of breaks on hedonic decline for both negative and positive stimuli. This seems to suggest that people fundamentally experience similar diminishing hedonic responses to all types of stimuli, be they positive or negative. And yet, some recent work suggests that hedonic responses are not symmetric, at least in some domains. For instance, aversive experience are much more sensitive to hedonic contrasts than positive experiences (Voichek & Novemsky 2021). Might this mean that people experience negative stimuli fundamentally differently from positive stimuli, and thus group into different clusters than what we observed here? Or might there be less stability in clustering when considering clusters observed with a positive stimulus and then projected onto expected experiences with a negative stimulus? This too is an important question that we hope future researchers will tackle.

Going beyond consumption of stimuli, the field of hedonic adaptation has often focused on major life events. The most typical finding is that even after major events like the loss of a child or a change in employment, people’s overall hedonic experience (i.e., their wellbeing) returns to a set point after enough time has passed (Brickman et al., 1978, Lucas et al., 2003, Lucas et al., 2004). Our research, though robust to a variety of stimuli, is relatively mute on whether similar clusters of hedonic decline will emerge for such larger-scale, longer-term experiences focused on overall well-being. That is, following the loss of a job, people tend to initially experience an extreme negative response, which then returns to their pre-job loss levels with time. But does that hedonic adaptation occur uniformly for all individuals, or rather like in the present research, do some people experience little recovery, some rapidly recover, while others’ recovery occurs only after a prolonged period of extreme negativity. If future work documents such clusters for major life events, that would potentially allow for a stronger understanding of which types of individuals require more intense interventions following major negative life experiences to help them return to their pre-negative experience set points. After all, if some individuals experience Rapid Onset Decline (recovery, in this case), they may be less in need of clinical help than those who experience Flat or Steady Decline. Of course, for now, we can only speculate and hope that such questions will be answered with future research.

In sum, hedonic decline, though ubiquitous, is not quite as singularly determined as once believed. While some work has explored why some individuals could systematically differ in their hedonic decline (Chugani et al., 2015, Nelson and Redden, 2017, Redden and Haws, 2013), this research is very limited in scope and generally understudied. Further, none of this work considered how there might be systematic patterns across all people across all domains, which is exactly what more general theories of enjoyment would require. Moreover, these responses are similar across a variety of stimuli, and include both repetitive consumption and continuous consumption. We hope that our present work spurs future research both in the area of hedonic decline, as well as more broadly in the area of predictable heterogeneous psychological responses to all forms of stimuli for all types of people.