In our digital media age, entertainment is everywhere and always available (these days most easily via our smartphones). The entertainment (media) industry is constantly growing and increasing its revenues and a driving force for many technological innovations. Also, people spend a significant amount of time and money on entertainment. Hence, it is safe to say that entertainment media play an important role both on the societal as well as the individual level. However, entertainment media have always had a bad reputation. One of the most well-known early examples for modern electronic media is the successful 1985 popular science book “Amusing Ourselves to Death: Public Discourse in the Age of Show Business” by Neil Postman. This disdainful view on entertainment is also prevalent in academic research. In a textbook chapter from 2004 on entertainment research in media psychology, Peter Vorderer used the term “academic disapproval of entertainment” (German original: “Vom akademischen Missfallen an der Unterhaltung”, p. 545). Of course, part of the story is the focus on (potential) negative effects of entertainment media in the public and academic discourse, e.g., on violence and addiction. But the discomfort with researching entertainment runs deeper than that. What Vorderer addresses in his textbook chapter is that doing research on (media) entertainment always faces some sort of legitimation pressure. Key aspects in this are that a) many people find it difficult to imagine that it is possible to do serious research on a topic like entertainment and b) people explicitly or implicitly question the relevance of this type of research. Notably, this relevance question also has wider implications. In an interesting discussion piece by Okdie and colleagues published in Perspectives on Psychological Science in 2014, the authors lay out “Why Psychologists Should Study Media”. So, even our field of media psychology as a whole feels an essential need for self-justification.

The articles cited before are 11 and 21 years old and, thus, ancient from the perspective of the rapidly changing subjects of study in these areas. Still, reservations towards these lines of research continue to exist. How can media psychologists and entertainment researchers address these implicit or explicit attitudes towards their field? A first step is to identify where the disapproval, disdain, or discomfort come from. In a second step, we can then think about how to respond to that. As stated before, a key issue is the question of relevance. Here, it is important to define what we mean by relevance. If we relate relevance to economic success, societal impact, or importance on an individual level, media entertainment can be deemed very relevant. Related to that is the (mis)conception that research on a “lighthearted” subject like entertainment cannot be “serious”. However, this is one of many false dichotomies that afflict entertainment research, and the replication crisis has shown that also research on serious issues can be low in rigor or quality. Another argument that is often made when it comes to studying entertainment is that “research is mesearch”, indicating that many people who study (particular types of) media entertainment are also heavy users. Apart from the obvious fact that this is not always true, this is a) not necessarily a bad thing and b) often also true for other areas of research. For example, many researchers who study political communication or engagement are also highly politically interested (or even active).

Against this background, this position paper presentation has multiple goals. Expanding on the arguments laid out here, I first want to discuss why entertainment research frequently faces the question why and how it matters, and then provide suggestions on how we can answer this question. I will base my suggestions for that on a combination of industry, survey, and (web) tracking data. In doing so, I also want to encourage researchers, especially early-career researchers, to pursue their interests, regardless of how their research topic might be viewed by others. At the same time, I will provide a critical perspective, addressing challenges and risks in entertainment research and what the field can improve on, such as the development and adoption of innovative methods (Breuer et al., 2020). Finally, I also want to take a longitudinal perspective to talk about entertainment research and its relevance in the current media landscape, including the role of AI, and compare this to previous decades.

References

Breuer, J., Wulf, T., & Mohseni, M. R. (2020). New Formats, New Methods: Computational Approaches as a Way Forward for Media Entertainment Research. Media and Communication, 8(3), 147–152. https://doi.org/10.17645/mac.v8i3.3530

Okdie, B. M., Ewoldsen, D. R., Muscanell, N. L., Guadagno, R. E., Eno, C. A., Velez, J. A., Dunn, R. A., O’Mally, J., & Smith, L. R. (2014). Missed Programs (You Can’t TiVo This One): Why Psychologists Should Study Media. Perspectives on Psychological Science, 9(2), 180–195. https://doi.org/10.1177/1745691614521243

Vorderer. P. (2004). Unterhaltung [Entertainment]. In R. Mangold, P. Vorderer, & G. Bente (Eds.), Lehrbuch der Medienpsychologie [Media Psychology Textbook], pp. 543-564. Hogrefe.

We should have confidence in scientific claims only when they can be replicated under identical conditions. Yet, large-scale replications in media psychology remain rare. The field has been slow to integrate replication as standard practice. In this position paper, I argue that replication is critical not only for strengthening theoretical claims but also for identifying the boundary conditions of a finding.

Over the past four years, I have conducted 10 replications of online privacy studies, providing insights into the potential and limitations of replication in media psychology. In this talk, I will (re)introduce the concept of replication, discuss key findings from my replications studies, as well as methodological, theoretical, and practical lessons learned.

Why Replicating Media Psychology Research?

Media psychology evolves rapidly due to shifts in technology and user behaviors. Theories and empirical findings developed in one context may not hold in another, making replication essential for assessing generalizability of claims. Media psychology has yet to embrace replication as a standard routine. Theoretical models still often rely on single studies and thus risky empirical foundations. Replication therefore serves three functions: First, it provides a check on false positives, helping to identify results that may have emerged due to chance rather than robust effects. Second, it refines theories by revealing under what circumstances effects emerge. Third, it builds cumulative knowledge, allowing scholars to discern patterns rather than relying on isolated findings. Given media psychology’s applied nature, replicability is vital for informing policy, design, and interventions.

Ten Replications in Privacy Research

To contribute to the replication debate and strengthen privacy research, I systematically replicated ten key studies in privacy research. Although many studies explored the interplay of privacy and self-disclosure, foundational studies mostly predate major shifts in technology, platform policies, and public perceptions. Some were conducted over a decade ago, before the introduction of the GDPR and under different social media norms. Their assumptions, methods, and findings may no longer fully capture contemporary privacy dynamics.

In a first iteration, we replicated Krasnova et al.’s (2010) investigation of the privacy calculus, Dienlin and Trepte’s (2015) study on the privacy paradox, and Vitak’s (2012) analysis of the impact of the context collapse on privacy behavior. In a second iteration, we replicated Cho et al’s (2018) and Lutz et al’s (2020) investigation of privacy cynicism and Park’s (2013) study on the role of privacy literacy. In a third iteration, we replicated Hallam & Zanella’s (2017) study of the privacy calculus through the lens of construal level theory, and Litt’s (2013) survey study on privacy protection behaviors. In the final iteration, we replicated Zlatolas et al.’s (2015) and Masur & Scharkow’s (2016) studies on self-disclosure management on social media.

Across the ten replications, notable patterns emerged: Many effects replicated in direction and significance but with varying effect sizes, suggesting survey research is generally replicable, though notable variance remains unexplained. Further, the amount of replicated paths alone did often not determine overall study replication—at times, core hypotheses nonetheless failed. Given that we always replicated multiple studies in one survey, we examined the impact of analytical choices on the privacy concern–behavior link. Specification curve analyses revealed that key effects were highly contingent on measurement choices, often failing to replicate with alternative scales.

Toward a More Replication-Friendly Field

Our findings showed that successful replication does not necessarily confirm a theoretical model’s validity. Even when a study replicated (or not), it remained difficult to pinpoint the exact reasons for success (or failure), highlighting the need for further research that intentionally varies study characteristics. Our results further suggest that differences in time and context alone do not account for variations in outcomes. Subtle differences in measures can also play a crucial role.

Further, we experienced firsthand that despite their importance, journals and conferences still seemed to prioritize novel contributions, making the publication of replications more difficult. Further, when our replications failed to confirm widely accepted findings, we encountered skepticism or even critique, at times from original authors, reflecting the broader tensions surrounding replication in the field.

To better embed replication in media psychology, I argue that funding agencies and journals need to support and endorse replication research. Second, methodological transparency should be encouraged to facilitate replication. Third, the field must move beyond viewing replication as success or failure. Replication is not about scrutinizing individual scholars but a collective effort to enhance media psychology’s credibility. By embracing replication, the field can ensure its findings are not only innovative but also enduring and applicable across diverse contexts.

References

Choi, H., Park, J., & Jung, Y. (2018). The role of privacy fatigue in online privacy behavior. Computers in Human Behavior, 81, 42–51.

Dienlin, T., & Trepte, S. (2015). Is the privacy paradox a relic of the past? An in-depth analysis of privacy attitudes and privacy behaviors. European Journal of Social Psychology, 45(3), 285–297.

Hallam, C., & Zanella, G. (2017). Online self-disclosure: The privacy paradox explained as a temporally discounted balance between concerns and rewards. Computers in Human Behavior, 68, 217-227.

Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: Why we disclose. Journal of Information Technology, 25(2), 109–125.

Litt, E. (2013). Understanding social network site users’ privacy tool use. Computers in Human Behavior, 29(4), 1649-1656.

Lutz, C., Hoffmann, C. P., & Ranzini, G. (2020). Data capitalism and the user: An exploration of privacy cynicism in Germany. New Media & Society, 22(7), 1168–1187.

Masur, P. K., & Scharkow, M. (2016). Disclosure management on social network sites: Individual privacy perceptions and user-directed privacy strategies. Social media+ society, 2(1),

Park, Y. J. (2013). Digital literacy and privacy behavior online. Communication research, 40(2), 215-236.

Vitak, J. (2012). The impact of context collapse and privacy on social network site disclosures. Journal of Broadcasting & Electronic Media, 56(4), 451–470.

Zlatolas, L. N., Welzer, T., Heričko, M., & Hölbl, M. (2015). Privacy antecedents for SNS self-disclosure: The case of Facebook. Computers in Human Behavior, 45, 158-167

Media environments are optimized to continuously engage users, e.g., with vast amounts of curated content and frictionless features (Flayelle et al., 2023). Many users thus report difficulties with ending media use at the right time (e.g., Schaffner et al., 2023). This sheds light on a longstanding blind spot: Many communication theories address media selection and processing, but how do recipients disengage from media use? The Appraisal Model of Media Use Disengagement (AMMD) proposes a process model of how media use sessions end across different analogue and digital media use types. It builds on conceptualizations of (media use) situations (e.g., Schnauber-Stockmann et al., 2024), appraisal models of media use (Bartsch et al., 2008; Reinecke & Meier, 2021), and motivation psychology (e.g., Fahr & Böcking, 2009). Empirical research on media use disengagement is scarce so far (for exceptions, see e.g., Rixen et al., 2023). The model, however, integrates related literature from the fields of entertainment research, human-computer interaction, persuasive communication, and information systems to inform its components and to secure its applicability to various types of media use. Next, the model and its components will be outlined, succeeded by open empirical questions.

Media use disengagement

Disengagement describes the situational act of terminating an ongoing media use session. The AMMD positions disengagement at the device- or application level of media use (i.e., turning off a device, closing an application; Meier & Reinecke, 2021), distinguishing disengagement from de-selection behaviours that occur within an ongoing session (e.g., swiping from one video to the next on social media). Importantly, disengagement can represent a behavioural adaption motivated to approach a new, alternative stimulus or to avoid the current media activity (Bartsch et al., 2008; Fahr & Böcking, 2009).

Cognitive appraisals and affective reactions

This motivation is informed by a continuous evaluation of one’s inner (e.g., emotions) and outer environment (e.g., content). Appraisal theories of emotion posit that cognitive representations of environmental events are formed and evaluated regarding personal concern, e.g., on the following criteria: intrinsic pleasantness, need and goal congruence, control, novelty, compatibility with norms and values (Yeo & Ong, 2024). If the event concerns the individual, the cognitive appraisal elicits an affective reaction. Arising emotions inform the motivation to maintain, approach or avoid those emotions and to make behavioural adjustments if necessary (Bartsch et al., 2008). Affective reactions may be manifold but come down to changes in core affect, that is, on the two continua of positive and negative affect (Kuppens et al., 2012). The AMMD thus predicts disengagement when certain thresholds are reached: When negative affect surpasses a threshold at some point during the media use session, disengagement serves as a behavioural adjustment to either avoid the negatively experienced media use or associated consequences, or to approach an alternative activity expected to be more positive or rewarding. Positive affect, conversely, can predict disengagement when it falls below a threshold during the media use session. In that case, disengagement represents an approach action towards other activities that are deemed more positive or rewarding.

Situation factors

The AMMD posits that said appraisals are elicited by situation factors. Conceptualizations of (media use) situations distinguish between media cues, external context cues, and user factors (e.g., Schnauber-Stockmann et al., 2024). A central determinant of media use disengagement lies in the media itself. The AMMD structures the many possible media cues along the device, application, feature, interaction, message levels of media use (Meier & Reinecke, 2021). Relevant examples are stimuli frequency and novelty, with overly redundant content making disengagement more likely by eliciting feelings of boredom (e.g., Rixen et al., 2023). Another type of situational cue lies in external context. Media use is embedded into temporal, spatial, technical, and social contexts, which often vary throughout media use sessions (e.g., time passing; Schnauber-Stockmann et al., 2024). Media use also coexists with concurrent or competing activities that are prevalent reasons for disengagement (Rixen et al., 2023; Schaffner et al., 2023). Finally, physiological and psychological user factors may influence disengagement through appraisal processes. Among those are psychological states including emotions, needs, goals, and mental resources (Schnauber-Stockmann et al., 2024). Those psychological states can be elicited by bodily needs and by trait characteristics of the user, such as personality (Schnauber-Stockmann et al., 2024). Beyond a more straightforward role for disengagement, user factors moderate the impact of media cues and external context cues on disengagement (Schnauber-Stockmann et al., 2024). External context cues, e.g., primarily become relevant for disengagement based on how media users perceive them (e.g., the appraisal that too much time has passed). The AMMD further postulates another moderating role of user factors, specifically of mental resources such as self-control or attention: These can influence how well recipients can translate cognitive appraisals and affective reactions into behavioural adaptation. Self-control, e.g., can help to convert feelings of guilt into disengagement (Reinecke & Meier, 2021).

Critically, there are exceptions to the proposed appraisal process of disengagement. In some cases, environmental cues can directly increase the probability of disengagement. Salient media or external context conditions can dictate disengagement, e.g., when the wifi connection stops or another person enters the room and turns off the radio.

Discussion

The AMMD is the first theoretical model to explain media use disengagement, considering various situation factors across different media use types. It posits that media cues, external context cues, and user factors can vary situationally. A situation factor is cognitively appraised by the media user if it personally concerns them. This elicits a positive or negative affective reaction. As soon as associated negative affect surpasses a threshold or positive affect falls below a threshold, disengagement occurs as a behavioural adaptation directed away from the media activity or towards new activities.

Future research can test the applicability of the AMMD across contexts and media use types. Furthermore, it can identify clusters of typical situations and patterns in the disengagement process, e.g., to determine the prevalence of positive versus negative experiences with disengagement. Studying the disengagement process can help elucidate how media use is embedded and experienced by users in daily life.