WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 1

What Drives Increases in Hindsight Impressions after the Reception of Biased Media

Content?

Marcel Meuer1, Ina von der Beck2, Steffen Nestler3 and Aileen Oeberst1,2

1 Department of - University of Mainz, Germany

2 Leibniz-Institut für Wissensmedien, Tübingen, Germany

3 Department of Psychology - University of Münster, Germany

© 2021, American Psychological Association. This paper is not the copy of record and may not exactly replicate the final, authoritative version of the article. Please do not copy or cite without authors' permission. The final article will be available, upon publication, via its DOI:

https://doi.org/10.1037/xap0000353

Author Note

Marcel Meuer https://orcid.org/0000-0003-1648-5359

Ina von der Beck https://orcid.org/0000-0002-0849-5541

Steffen Nestler https://orcid.org/0000-0001-9724-2441

Aileen Oeberst https://orcid.org/0000-0002-1094-9610

Ina von der Beck is now at the Head Office of German Research Foundation, Bonn.

Aileen Oeberst is now at the Department of Psychology, University of Hagen, Germany. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 2

This research was funded by the German Research Foundation to Aileen Oeberst (OE

604/3-1) and Steffen Nestler (NE 1485/8-1). All authors declare that they have no conflicts of interest. All procedures performed in the present study were in accordance with the ethical guidelines specified in the APA Code of Conduct as well as the authors’ national ethics guidelines. The research was approved by the Research Ethics Committee of the Leibniz-

Institut für Wissensmedien, Tübingen, Germany, case number LEK 2015/011. Preregistration, study material and data are openly accessible on the Open Science Framework

(https://osf.io/drmf3/). The authors would like to thank Marieke von Elert, Lena Scholz,

Louisa Spielvogel and Maria Zuleger for data collection.

Correspondence should be addressed to: Marcel Meuer, University of Mainz, Binger

Str. 14-16, 55122 Mainz, e-mail: [email protected] WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 3

Abstract

Prior research has shown that reading biased media content (e.g., Wikipedia articles) can increase recipients’ hindsight . It remained unclear, however, which features of the biased texts led to such an increase. We examined this question in a longitudinal experimental study

(N = 190). Specifically, we tested whether repeated exposure to already known information

(H1), a more coherent presentation of the information (H2), or the presentation of novel information (H3) affected readers’ hindsight impressions of likelihood, inevitability, and foreseeability. To this end, participants initially learned about an event by reading several short news, and, one week later, received one of several summarizing texts, which systematically varied in the information contained. We found empirical support for the unique effect of mere repeated exposure and receiving novel information. Since media coverage of meaningful events is usually highly repetitive but also often comprising novel information, our findings contribute to a better understanding of how hindsight bias may publicly persist or even increase over time.

Keywords: hindsight bias, reception, causal models, Wikipedia

WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 4

Public Significance Statement

After learning about an event outcome, people often mistakenly believe that the outcome was more likely, more inevitable, and more foreseeable than they had before learning it. Our study demonstrates that reading media content which itself is suggestive of the event outcome can increase these impressions through repetitive coverage and provision of novel information.

This finding is relevant as increased hindsight impressions are associated with increased responsibility and blame attributions. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 5

What Drives Increases in Hindsight Impressions after the Reception of Biased Media

Content?

On 14 April 1912, the RMS Titanic, which was publicly billed “unsinkable”, hit an iceberg, and sank, claiming the lives of over 1500 passengers and crew members. One hundred years later, the Saturday Evening Post explores its 1912 editorial on the great tragedy, headlining “The Inevitable Tragedy of the Titanic” and blaming the British and

American governments for the disaster (Nilsson, 2012). Knowing the outcome of an event can make a big difference in how this event is perceived: Oftentimes, people overestimate in hindsight what they knew in foresight. Once they have learned about an event outcome, they tend to perceive it as more likely, more inevitable, and more foreseeable than they did in foresight. This hindsight bias, the erroneous overestimation of what one actually knew before an event happened, is a robust and pervasive phenomenon that has been extensively studied

(see Christensen-Szalanski & Wilham, 1991; Guilbault et al., 2004 for meta-analyses; see

Pohl & Erdfelder, 2017; Roese & Vohs, 2012 for reviews).

Recent research has shown that people’s individual hindsight bias even extends to a collective level: A field study documented hindsight bias in specific articles of Wikipedia, the largest collaborative compendium of world knowledge (Oeberst et al., 2018). Reading such biased articles, in turn, further increased readers’ already existing hindsight bias about the respective event (Oeberst et al., 2014, 2018; von der Beck et al., 2017). What remains unclear, however, is what exactly leads to such an additional increase in hindsight bias after the reception of biased media content. This is an important research question as it may inform our theorizing about cognitive mechanisms that affect the extent to which people succumb to hindsight bias. Ultimately, knowing the factors that foster hindsight bias in the context of media reception may help to find strategies to reduce hindsight bias during the perception of significant events. To elaborate on this question, we report a longitudinal study that WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 6 systematically tested the impact of three features of biased media content that may affect recipients’ hindsight impressions.

Hindsight Bias after the Reception of Biased Media Content

Research on hindsight bias has demonstrated that an event is perceived as more likely, foreseeable, and inevitable once it has occurred (Fischhoff, 1975; Guilbault et al., 2004). In other words, hindsight bias focuses on the effect of knowledge about an event on evaluations of that event. In the real world, however, learning about an event is rarely the last piece of information as people may be motivated to gather information from various sources in order to understand what happened (Blank & Nestler, 2007; Louie, 2005; Nestler et al., 2008;

Pezzo, 2003; Roese & Olson, 1996; Yopchick & Kim, 2012). Elections, for instance, often come along with voter analyses after the fact, and disasters typically elicit elaborations on who is to blame. People might follow the media coverage of the event or catch up on the topic by reading summarizing texts on the internet (e.g., Wikipedia articles).

Since hindsight bias is robust and pervasive (Guiltbault et al., 2004; Pohl et al., 2002), it is likely shared among authors of such information sources, and media content thus is likely biased as well. Oeberst and colleagues (2018) examined hindsight bias in the context of

Wikipedia and found that hindsight bias had entered Wikipedia articles about disasters:

Hindsight article versions that existed eight weeks after the respective disasters unfolded were more suggestive of the event than foresight article versions that were available immediately before the disasters took place.

More importantly, reading such biased articles can affect recipients’ individual hindsight bias: Oeberst et al. (2014) and von der Beck et al. (2017) provided participants with different versions of the Wikipedia article about the nuclear power plant in Fukushima

Daiichi, Japan. Participants read either the unbiased foresight article version or the biased hindsight article version from 8 weeks after the catastrophe, containing a thorough causal WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 7 elaboration of the incident. Even though all participants already knew about the disaster, reading the biased (but not the unbiased) article version increased participants’ perceived likelihood of the nuclear catastrophe (i.e., their hindsight bias). In a later study, this effect was replicated with a widely unknown event that allowed for the inclusion of a genuine foresight condition (Oeberst et al., 2018). Here, participants either received no outcome knowledge

(foresight), outcome knowledge with basic causal information (hindsight) or the biased

Wikipedia article about the event containing detailed information about the outcome and its potential antecedents (hindsight plus). Beyond the classic hindsight bias (i.e., foresight vs. hindsight), the authors found an even higher hindsight bias for participants who had read the biased Wikipedia article (i.e., foresight vs. hindsight plus).

Together, the studies suggest that people’s initial hindsight bias (i.e., after learning about an event) is further increased after the reception of media content that itself contains hindsight bias. It is still an open question, however, what causes this effect of media reception, as there are several potential candidates.

Features of Biased Media Content That May Facilitate Hindsight Bias

To understand how the reception of biased media content may increase recipients’ individual hindsight bias, it is reasonable to consider research on the underlying mechanisms of the emergence of the phenomenon in the first place. When it comes to the perception of events, causal reasoning processes are considered to be a crucial factor for hindsight bias to occur (Blank & Nestler, 2007; Louie, 2005; Nestler et al., 2008; Pezzo, 2003; Roese & Olson,

1996; Yopchick & Kim, 2012). Causal Model Theory (Nestler et al., 2008) attributes hindsight bias to an unbalanced causal model of the event: In an effort to explain the occurrence of an event (e.g., a catastrophe) after the fact, people search for antecedents.

However, this evidence sampling is biased as event knowledge serves as a retrieval cue for event-consistent antecedents (Slovic & Fischhoff, 1977). Consequently, event-consistent WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 8 antecedents are more frequently retrieved and given more weight compared to event- inconsistent antecedents (Roese & Olson, 1996). As a result, the representation of the event – and what led to it – does not represent the actual foresight perspective, but, unbeknownst to the person succumbing to hindsight bias, is geared towards the event one already knows about. The event appears to be more inevitable or likely than it actually was in foresight

(Nestler et al., 2008). This, in turn, may likewise increase people’s perception of foreseeability of the event outcome as events that are causally determined can oftentimes also be predicted (Blank et al., 2008)1.

Naturally, causal reasoning processes such as the sampling, evaluation and integration of information are dynamic. A once established causal model may be altered if additional information is acquired. Therefore, reading biased media content may increase recipients’ individual hindsight bias by fostering an even more unbalanced causal representation of the respective event. Specifically, we propose three features of biased media content through which causal modelling may be additionally biased. First, repeated exposure of the very same

(biased) information may already suffice to strengthen an initial causal model. Second, biased media content about a past event may provide a more coherent representation of the event, which readers had lacked before. And third, the article may provide novel information which adds to readers’ prior causal model. In the following, we will outline in more detail, how each of these features could increase recipients’ impressions of likelihood, inevitability, and foreseeability of events.

Repeated Exposure

An increase in people’s hindsight bias could emerge without the provision of any novel information, since merely thinking about a topic (based on already known information)

1 As long as causal antecedents are known and not too complex (see Blank et al., 2008 and Nestler et al., 2010, for a comprehensive elaboration of the components of hindsight bias and their differentiation). WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 9 may suffice to induce stronger attitudes about it (Tesser, 1978). Interestingly, this thought- induced polarization is particularly pronounced for people, who already have a well- developed knowledge structure (e.g., a pre-existing causal representation of an event;

Chaiken & Yates, 1985). Thus, repeated exposure to information may facilitate such polarization processes, in which recipients, in terms of causal model theory, devalue event- inconsistent information or reinterpret them as consistent thereby giving even more weight to event-consistent antecedents (Chaiken & Yates, 1985). Consequently, the causal model of the event would be even more biased than before reading the very same information, thus increasing hindsight bias.

In addition, repeated exposure may foster hindsight bias even without the assumption of causal modelling. According to the truth effect, one is much more convinced that ambiguous information (e.g., assertions whose veracity is uncertain - such as that the sinking of the RMS Titanic could have been prevented) is true after having heard it multiple times

(Hasher et al, 1977; see Dechêne et al., 2010, for a meta-analysis). This effect is considered to be mediated by the metacognitive experience of processing fluency – the subjective feeling of ease while processing information (Hansen et al., 2008). In other words, the perceived ease of processing already known (vs. novel) information is misattributed to its veracity. Processing fluency, in turn, has been discussed to increase hindsight bias, particularly in terms of impressions of foreseeability (Birch et al., 2017; Roese & Vohs, 2012). Therefore, by increasing the subjective feeling of ease of processing through the repetition of already known information, biased media content may foster an increase in hindsight bias.

Text Coherence

Oftentimes, we learn about current events by reading information that is distributed over time (e.g., a news ticker, various news reports across time) and that comes from different sources (e.g., internet, radio, TV, newspaper). Thus, people have to assemble information WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 10 pieces and integrate them on their own. When later reading a summarizing media report, people may be provided with a more coherent account of the event. Text coherence, in turn, which describes the “extent to which relations between ideas in a text are explicit”

(McNamara, 2001, p. 51), has been shown to increase text comprehension (McNamara &

Kintsch, 1996; McNamara et al., 1996). Interestingly, coherence may be achieved without the presentation of novel factual information: Merely the structuring of the very same information as well as the use of meaningful connective devices (i.e., transitional words such as “thereby” “in the meantime” and “because”) may provide novel insights, by making causal relationships more explicit (Bamberg, 1983; McNamara, 2001; Pennington & Hastie, 1986).

Hence, an easy to understand and thoughtfully structured information presentation may facilitate causal reasoning about the event in question, and, particularly in the case of biased media content, may foster an outcome-consistent causal model.

Furthermore, just as with repeated exposure, text coherence may contribute to an increase in hindsight bias even in the absence of causal modelling: Not only repeated exposure but also a coherent presentation of information promotes the metacognitive experience of processing fluency (Alter & Oppenheimer, 2009; Winkielman et al., 2012), which, in turn, may increase hindsight bias (Birch et al., 2017; Roese & Vohs, 2012).

Novel Information

It is almost trivial to note that media content may contain entirely new information about the event. Particularly if some time has passed – as was the case, for instance, in the studies about Fukushima (Oeberst et al., 2014; von der Beck et al., 2017) – it is likely that media content about the event contains information readers did not know before. If this novel information addresses causal links, in turn, it may add to recipients’ causal model and thus increase readers’ hindsight bias. On top of that, conjunction effects may come into play:

People prefer causal models that comprise two or more antecedents over explanations that WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 11 include only one (Abelson et al., 1987). Hence, an article that offers several coherent antecedents to the event may allow for conjunction effects that strengthen recipients’ causal model and hence increase hindsight bias (Nestler & von Collani, 2008).

Interestingly, in addition to causal information, even information that is not directly causally linked to the event (e.g., that there were 246 injuries and two deaths during the RMS

Titanic’s construction in Belfast) might subjectively be considered causally relevant in retrospect and thus be added to recipients’ causal model. Additionally, such background knowledge may complement the prior information base in a way that people get the impression of an internally consistent and exhaustive account on the event. This may, in turn, increase the overall persuasiveness of the narrative (Yale, 2013) and foster the plausibility of the biased causal model, and hence, increase hindsight bias.

Further Questions Concerning Hindsight Bias after Reading Biased Media Content

The initial three studies on the effect of reading biased media content on hindsight bias (Oeberst et al., 2014, 2018; von der Beck et al., 2017), which the present work follows up on, utilized a specific type of media content as study material: Wikipedia articles. As a worldwide online encyclopedia, Wikipedia is an important tool to look up information and obtain an overview of a topic. In contrast to classic media coverage, however, which usually takes place immediately after an event occurred, there are often days or even weeks in between first learning about an event and taking the time and interest to look up further information in Wikipedia. This delay between the occurrence of an event and reading a

Wikipedia article about it gives rise to two further questions regarding the effect of media reception on hindsight bias we would like to address in the present research.

First, there is only little research on the temporal development of hindsight bias after initially learning about an event (Guiltbault et al., 2004). While some studies suggest that hindsight bias may increase in the course of the immediate media coverage after the WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 12 occurrence of an event (Bryant & Brockway, 1997; Bryant & Guilbault, 2002; Oeberst et al.,

2018, Study 1), the literature is lacking research on how hindsight bias develops in the absence of novel input (e.g., in the time before looking up an event in Wikipedia). Taking classic processes into account, however, one might expect that people forget some information over the course of time (Ebbinghaus, 1885; Murre & Dros, 2015). In terms of hindsight bias, the absence of input may thus result in a fading of people’s biased causal model and, in turn, diminish their impressions of likelihood, inevitability and foreseeability of an event. In the present study, we therefore exploratorily address the temporal development of hindsight bias in the absence of novel input.

Second, one may wonder how the hindsight bias after reading a biased Wikipedia article relates to the initial bias directly after learning about the event. For instance, in

Oeberst et al. (2014) and von der Beck et al. (2017), participants gave their current hindsight impressions about a well-known event (i.e., the Fukushima nuclear disaster), read a biased

Wikipedia article about it, and again reported their hindsight impressions. While they found an increase in hindsight impressions after reading the biased article, they had no access to participants’ initial impressions immediately after learning about the event in March 2011.

Therefore, it remains unclear, whether the hindsight bias after reading the biased article is larger, equal, or even smaller than the initial hindsight bias. On the one hand, readers of biased articles could be even more biased since the article may provide novel insights that additionally bias the initial causal model (i.e., due to repeated exposure, coherent presentation, new information; see above). On the other hand, if hindsight bias indeed decreases over the course of time due to information, reading a biased article may either partially or entirely reactivate participants’ initial representation of the event, which would result in a hindsight bias of smaller or equal size, respectively. The present study thus WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 13 additionally compares hindsight impressions after reading a biased article to initial impressions after learning about the event.

The Present Research

We conducted a preregistered longitudinal experimental study to test which features of biased media content affected readers’ hindsight impressions. Specifically, we examined whether repeated exposure of information (H1), a coherent presentation of already known information (H2), and novel information (H3) led to an increase in recipients’ hindsight impressions of likelihood, inevitability and foreseeability of a given event. In addition, we set out to explore (a) whether hindsight impressions decrease over the course of time and in the absence of novel input, and (b) how hindsight impressions after reading biased media content relate to initial hindsight impressions (i.e., directly after learning about the event).

In order to test this, it needs the assessment of participants’ hindsight impressions at three points in time: Immediately after learning about the event (t1), after some time has passed prior to reading biased media content about the event (t2pre), and after reading the biased material (t2post). In line with our research question, all measures were thus assessed in hindsight. Participants initially learned about an event by reading several short news, and, one week later, read one of several summarizing texts, which systematically varied in the information contained. All materials as well as data and preregistration are openly accessible on the Open Science Framework (see https://osf.io/drmf3/).

Method

Participants and Design

Based on an à priori statistical power analysis with G*Power (Faul et al., 2007), we aimed at a final sample size of N = 180 in order to be able to detect small effects (f = 0.15,  WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 14

= .05, 1- = .80)2. As study material required in-depth text comprehension, we limited our sampling to native German speakers.

Two hundred thirteen German participants completed our lab study in exchange for course credits or a monetary reward of 8€/h. As preregistered, we excluded participants who had knowledge of the event or read its Wikipedia article before participating (n = 3), stated that that they did not read the study material (n = 4), or did not pass the two instructional manipulation checks included in the study (n = 16) 3. This led to a final sample size of N =

190 (143 female, 46 male, 1 divers, Mage = 24.94, SD = 5.81). The majority of the sample were university students (psychology: n = 120, other disciplines: n = 41). The experiment comprised of two sessions one week apart (+/- one day). We obtained participants’ hindsight impressions of the event in the first session (t1) and two more times in session two (t2pre, t2post). At t2, participants were randomly assigned to one of four experimental conditions

(repeated exposure, n = 47; text coherence, n = 50; novel information, n = 50; source information, n = 43, for exploratory purposes). Thus, we had a 3 (time of measurement, within-subjects) x 4 (text version, between-subjects) mixed design. Note that this design does not include a foresight condition, since all three times of measurement were given after learning about the event4.

Materials and Procedure

Participants were invited via mailing lists to a lab study about the perception of disasters. After reading legal and ethical information and providing informed consent, we

2 Note that we preregistered a minimum sample size of N = 164 as our initial calculations were based on the overall design of the study. However, the preregistered main analyses were actually grounded on separate 2x2 comparisons. Therefore, we post hoc adjusted the minimum sample size upwards. 3 In addition, we preregistered to exclude participants who spend less than M – 3SD time on the short news or the summarizing text. However, as standard deviations were large, the cut-off would have been a negative reading time, forcing us to discard this criterion. 4 To be transparent about the lacking foresight condition, we will avoid the term hindsight bias (which requires a foresight-hindsight comparison) and instead refer to increases in hindsight impressions in the methods and results section. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 15 presented an check to ensure that participants thoroughly read the study material and instructions. Subsequently, all participants read eight short, stand-alone information snippets about a Tongan ferry “Princess Ashika”, which sank in stormy seas on August, 5th,

2009, leading to 74 casualties. This event was chosen because it was rather unknown to students. Furthermore, the Wikipedia article about the ferry provided a rich source of information from which the different summarizing text versions could be generated. The snippets of information were presented in chronological order in a layout that resembled an online short news section. The first snippet informed about the sinking, followed by two passages about the immediate rescue actions. The remaining five passages gave an account of the investigations and the aftermath of the incident, the latest information being dated seven months after the sinking.

Directly after learning about the event, participants indicated their impression of foreseeability (6-item scale, slider from 0 – strongly disagree to 100 – strongly agree, e.g., “I would have foreseen that it would come to the sinking”, Cronbach’s  = .79), of inevitability

(7-item scale, slider from 0 – strongly disagree to 100 – strongly agree, e.g., “Sooner or later it had to come to the sinking”, Cronbach’s  = .69) and of the likelihood of the incident (on a slider from 0 – absolutely unlikely to 100 – absolutely likely). For the likelihood assessments, participants were asked to disregard their outcome knowledge, following the standard hindsight bias research (Fischhoff, 1975)5.

After providing demographic information (age, gender, university enrollment), participants indicated their prior knowledge about the sinking of the ferry, and they were asked whether they had actually read the short news (both serving as exclusion criteria).

5 Participants were not explicitly instructed to ignore outcome knowledge for the foreseeability and inevitability measure as the items were worded in past tense and thus already implied to take a foresight perspective (see Nestler et al., 2010; Oeberst et al., 2018; von der Beck et al., 2017 for a similar approach). WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 16

Finally, we implemented an instructional manipulation check to exclude participants who did not thoroughly read the study material (see Oppenheimer et al., 2009).

One week later, participants returned to the lab and provided another informed consent before the survey started once more with an attention check. We then made use of the same scales to assess participants’ current impression of foreseeability (Cronbach’s  = .88), inevitability (Cronbach’s  = .74) and likelihood of the incident (t2pre). As in session 1, participants were still asked to disregard their outcome knowledge for the assessment of the perceived likelihood. After an unrelated filler task (Mduration = 15.17 minutes, SD = 5.98), participants were randomly assigned to one out of four experimental conditions and received a summarizing text, which increasingly differed from the information provided in the short news at t1 in the following way (see Figure 1 for an overview).

Figure 1

Overview of Systematic Adaptions of the Summarizing Texts throughout Conditions

Note. Each experimental condition adds a unique feature, upholding the features of subordinate conditions.

Exemplary text passages are not original excerpts but simplified examples to illustrate the unique features of the texts. Italic font highlights the adaptions. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 17

In the repeated exposure condition, participants read the exact same sentences from the short news, which was only presented as one continuous text. In the text coherence condition, the informational content was identical to the repeated exposure condition, but text coherence was increased by including a brief introduction (without any novel information), section headings, and connective devices. In the novel information condition, participants received the coherent article from the text coherence condition with additional, causally relevant information about the investigation of the incident (e.g., “The former owner

Patterson Brothers Shipping Company Limited […] had already lost the ferry Ovalau II due to insufficient maintenance […]. Likewise, the Princess Ashika merely received a new coat of paint but no major overhaul before being sold to the Tonga Shipping Corporation.”) and irrelevant information (e.g., concerning the history of the ferry and the shipping company).

Finally, for exploratory purposes, we implemented the source information condition in which text of the novel information condition was presented in the typical Wikipedia article layout including Wikipedia’s logo. In fact, this was the original Wikipedia article that was available in the German Wikipedia on March 4th, 2014 and that we used for material development6.

After reading their respective texts, participants again provided their current impression of foreseeability (Cronbach’s  = .88), of inevitability (Cronbach’s  = .76), and of the likelihood of the ship’s sinking (t2post). Again, participants were asked to disregard their outcome knowledge for the assessment of the likelihood. Participants then judged the similarity between the short news (t1) and the summarizing text (t2) on a 6-point graphical overlap scale (adapted from Schubert & Otten, 2002), and were asked to describe the differences between the two texts – if they had perceived any. Furthermore, we assessed the

6 Except for a short passage about ongoing penal proceedings, which we deemed unsuitable for our study purposes, see https://de.wikipedia.org/w/index.php?title=Princess_Ashika&oldid=128155849. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 18 perceived intelligibility (1 – easy to understand to 5 – hard to understand), structure (1 - not structured at all to 5 – very structured) and coherence (1 - not coherent at all to 5 – very coherent) of the summarizing text and implemented an open question about the causal antecedents of the incident. Next, participants indicated whether they had already been familiar with the original Wikipedia article about the ferry and whether they had read the summarizing text (both serving as exclusion criteria). We then implemented another instructional manipulation check (also serving as an exclusion criterion). Additional measures for exploratory purposes may be extracted from the print version of the survey in the online supplemental material. After a full debriefing, participants had the chance to decide about the use of their data and were thanked.

Results

This section is organized as follows. First, we report several analyses checking whether the material was suitable to test our hypotheses. We then present preregistered analyses testing which of the three proposed text features affected hindsight impressions (i.e., t2pre-t2post comparisons). Please note that we had included a fourth, exploratory condition to test for an additional effect of providing source information. However, since we did not obtain any significant effects for this condition, we decided to report the respective analyses exclusively in the online supplemental analyses. Finally, we present additional exploratory analyses regarding the temporal development of hindsight impressions (i.e., t1-t2pre comparisons) and the relation of initial and final hindsight impressions (i.e., t1-t2post comparisons).

Manipulation Check

We first needed to check whether the material was suitable to test our hypotheses. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 19

First, we descriptively examined whether participants found all summarizing texts to be overall intelligible, which they did, Mrepeated exposure = 1.55, SD = 0.80, Mtext coherence = 1.66,

SD = 0.96, Mnovel information = 1.68, SD = 0.91.

Second, to ensure that the summarizing texts were suggestive of the disaster, we trained ten independent raters, who were blind to experimental conditions and the research question, to judge the extent to which the summarizing texts suggested the occurrence of a disaster in general and to which extent they implied that a disaster was inevitable and foreseeable (on 5-point scales from “not at all” to “very much”). All three summarizing texts were rated to suggest the disaster, Mrepeated exposure = 3.40, SD = 0.97, Mtext coherence = 3.50, SD =

1.08, Mnovel information = 4.50, SD = 0.71, and implied that the disaster was inevitable, M = 2.90,

SD = 0.99, Mtext coherence = 3.00, SD = 1.33, Mnovel information = 3.90, SD = 0.99, and foreseeable,

Mrepeated exposure = 3.10, SD = 1.10, Mtext coherence = 3.40, SD = 1.17, Mnovel information = 4.30, SD =

0.67.Therefore, the summarizing texts qualified as suggestive of the occurrence of a disaster7.

Third, we tested whether the adaptions between the summarizing texts were perceived as intended. A linear contrast analysis (contrast weights: crepeated exposure = 1, ctext coherence = 0, cnovel information = -1) revealed that the overall perceived similarity between the short news (t1) and the summarizing text (t2) decreased across experimental conditions, t (144) = 4.51, p

< .001, d = 0.92, Mrepeated exposure = 4.85, SD = 0.88; Mtext coherence = 4.48, SD = 0.95; Mnovel information = 4.00, SD = 0.95. With regard to the manipulation of text coherence, we asked participants how structured and coherent they perceived the summarizing text to be. If the coherence manipulation was successful, these judgments should be higher in the text coherence than in the repeated exposure condition but should not differ between the text coherence and the novel information condition. Contrast analyses (contrast weights: crepeated

7 For comparison: To get a proxy for the suggestiveness, inevitability and foreseeability expressed by an unbiased foresight article, raters additionally judged four unrelated foresight Wikipedia articles about disasters utilized by Oeberst et al. (2018), Msuggestiveness = 1.55, SD = 0.26, Minevitability = 1.15, SD = 0.17, Mforeseeability = 1.50, SD = 0.44. WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 20

exposure = -1, ctext coherence = 0.5, cnovel information = 0.5) supported this pattern for both impressions of structure, t (144) = 4.24, p < .001, d = 0.75, Mrepeated exposure = 3.55, SD = 0.95, Mtext coherence

= 4.14, SD = 0.83, Mnovel information = 4.26, SD = 0.80, and coherence, t (144) = 2.25, p

= .026, d = 0.40, Mrepeated exposure = 3.68, SD = 0.86, Mtext coherence = 3.96, SD = 0.81, Mnovel information = 4.06, SD = 0.82. Next, testing the manipulation of the novel information condition, we asked for differences between the short news and the summarizing text. More participants in the novel information condition (72%) than in the text coherence condition (32 %) referred to additional information, ² (1) = 14.46, p < .001. No such difference was found between the repeated exposure (32%) and the text coherence condition, ² (1) < 0.01, p = .993. Hence, participants in the novel information condition effectively perceived the additional information.

Taken together, the materials proved suitable for the purposes of this study.

Effects of the Text Features on Hindsight Impressions - Analyses of t2pre-t2post Differences

To test which of the three text features had an impact on participants’ impressions, we examined the increases of hindsight impressions from directly before and after reading the summarizing text (see the left side of Table 1 for means and standard deviations of the t2pre- t2post increases and Figure 2 for a visualization of the results). This comparison provides the most internally valid test for the effect of the features, since changes from t2pre to t2post can be directly attributed to the reception of the text.

Unique Effect of Repeated Exposure (H1). If repeated exposure to already known information alone exerted an effect, we should obtain a significant increase in hindsight impressions for participants in the repeated exposure condition, who had read a summarizing text that contained the very same information as the short news section. We thus tested the t2pre-t2post increases against zero by computing a planned contrast for each of the three hindsight impressions (contrast weights: crepeated exposure = 1, ctext coherence = 0, cnovel information = 0). WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 21

Note that this contrast is comparable to a one sample t-test, but yields a more powerful test by determining the error term based on the pooled variance of all three experimental groups

(variances are all equal according to Levene’s test, Fs (2, 144) < 0.46, ps > .633). As expected, reading the exact same information twice increased participants’ impressions of inevitability, t (144) = 2.38, p = .019, d = 0.35, and foreseeability, t (144) = 2.26, p = .025, d

= 0.338. Participants’ perceived likelihood of the event, however, did not increase significantly, t (144) = 1.21, p = .230, d = 0.18. Hence, the reception of repeated information alone exerted an effect on two of the three hindsight impressions.

Table 1

Mean Increases in Likelihood, Inevitability, and Foreseeability (SDs) as a Function of

Experimental Text Condition

t2pre-t2post Increases t1-t2post Increases

Repeated Text Novel Repeated Text Novel Exposure Coherence Information Exposure Coherence Information

3.30 3.80 11.56 2.57 6.20 6.62 Likelihood (21.78) (17.99) (16.32) (26.65) (18.65) (17.54)

Inevitability 4.04 7.12 9.20 0.28 2.41 6.16 (11.03) (12.64) (11.15) (14.10) (13.81) (12.39)

Foreseeability 4.79 4.93 12.31 2.47 3.26 9.99 (12.77) (16.21) (14.31) (15.29) (17.47) (16.54)

Note. Hindsight impressions were given on slider scales from 0 (strongly disagree) to 100 (strongly agree). t2pre- t2post increases: impressions provided after reading one of the three summarizing texts in session 2 minus impressions provided before reading the text. t1-t2post increases: impressions provided after reading the summarizing text in session 2 minus impressions provided after reading the short news in session 1.

8 For all contrast analyses, Cohen’s d was calculated by the contrast value divided by the square root of the mean square error of the respective ANOVA (see Gallucci & Perugini, 2018). WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 22

Unique Effect of Text Coherence (H2). Since the summarizing texts of the experimental groups systematically add one feature (e.g., the text in the text coherence condition contains text coherence and repeated information), we need to examine the differences between the t2pre-t2post increases in the repeated exposure condition and the text coherence condition to test whether text coherence had a unique impact on participants’ hindsight impressions. That is, if text coherence was a relevant feature, the increase in participants’ hindsight impressions should be larger in the text coherence condition compared to the repeated exposure condition. Therefore, we compared the t2pre-t2post increases between both conditions with one planned contrast for each of the three hindsight impressions

(contrast weights: crepeated exposure = -1, ctext coherence = 1, cnovel information = 0). As with the analysis regarding the effect of repeated exposure, we included all three experimental groups and determined the error term based on the pooled variance to get a more powerful test (hence the weight 0 for the novel information condition). None of the analyses yielded a significantly larger increase in hindsight impressions in the text coherence compared to the repeated exposure condition, tlikelihood (144) = 0.13, p = .895, d = 0.03, tinevitability (144) = 1.30, p = .194, d = 0.26, tforeseeability (144) = 0.05, p = .963, d = 0.01. Thus, we did not obtain a unique effect of text coherence.

Unique Effect of Novel Information (H3). Applying the same logic as for the coherence hypothesis, the influence of novel information should result in a higher t2pre-t2post increase in participants’ hindsight impressions in the novel information condition compared to the text coherence condition. After all, the summarizing text in the novel information condition also contained the feature of text coherence. Thus, a larger increase in the novel information condition compared to the text coherence condition would be due to novel information. The contrast analyses (contrast weights: crepeated exposure = 0, ctext coherence = -1, cnovel WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 23

information = 1) yielded significantly higher t2pre-t2post increases in the novel information condition for impressions of likelihood, t (144) = 2.07, p = .040, d = 0.41, and foreseeability, t

(144) = 2.54, p = .012, d = 0.51, but not for inevitability, t (144) = 0.89, p = .374, d = 0.18.

Hence, receiving novel information uniquely exerted an effect on recipients’ hindsight impressions of likelihood and foreseeability.

Figure 2

Mean t2pte-t2post Increases (SEs) as a Function of Experimental Text Condition

Repeated Exposure Text Coherence Novel Information 16 14 12 10 8 6

Mean Mean Difference 4 2 0 Likelihood Inevitability Foreseeability

Combined Effect of the Conjunction of All Features (Exploratory). In addition to examining the unique effect that each of the three features unfolded, we were interested in the effect on hindsight impressions when all three features came together. This was the case for participants in the novel information condition, since the summarizing texts of each condition added a unique feature while upholding the features of subordinate conditions (i.e., the text in the novel information condition not only contained novel information but also repeated information and more text coherence, see Figure 1). Therefore, testing for a pure t2pre-t2post WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 24 increase in the novel information condition allows to test for a combined effect of the conjunction of all features (vs. comparing t2pre-t2post increases between the text coherence condition and the novel information condition as we did above to extract the unique effect of providing novel information). For exploratory purposes, we thus computed another set of contrast analyses (contrast weights: crepeated exposure = 0, ctext coherence = 0, cnovel information = 1). The analyses yielded a significant increase in all three hindsight impressions, tLikelihood (144) =

4.36, p < .001, d = 0.62, tInevitability (144) = 5.59, p < .001, d = 0.79, tForeseeability (144) = 6.00, p

< .001, d = 0.85. Therefore, the reception of a coherent text that provided both already known and entirely new information had a significant effect on recipients’ hindsight impressions – consistently across all three measures.

Analyses Regarding the Further Exploratory Questions

Decrease in Hindsight Impressions - Analyses of t1-t2pre Differences. For exploratory purposes, we examined whether hindsight impressions decreased over the course of one week. To this end, we computed t1-t2pre difference scores for each of the three measures and applied a one sample t-test to test the mean difference against zero. We did not consider the experimental text conditions for this analysis as the manipulation was implemented after the t2pre measurement and could thus not affect these measures. There was a significant decrease of impressions of inevitability, Md = -3.84, SD = 10.90, t (146) = 4.28, p

< .001, d = 0.35, and foreseeability, Md = -2.10, SD = 11.85, t (146) = 2.15, p = .033, d = 0.18, but not for impressions of likelihood, Md = -1.10, SD = 20.55, t (146) = 0.65, p = .519, d =

0.05. Thus, in the absence of novel input, hindsight impressions of inevitability and foreseeability decreased over time.

Relation of Initial and Final Hindsight Impressions - Analyses of t1-t2post

Differences. Now we turn to the question how hindsight impressions after reading the biased texts relate to initial hindsight impressions (i.e., directly after learning about the event). WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 25

Specifically, since participants’ hindsight impressions did indeed decrease over the course of one week, the effect of repeated exposure (on impressions of inevitability and foreseeability) or novel information (on impressions of likelihood and foreseeability), which we found in the t2pre-t2post comparison, may either lead to hindsight impressions that are larger, equal, or smaller than the initial impressions at t1. By comparing the changes in hindsight impressions from initially learning about the event to after reading the summarizing text (t1-t2post), we tested to which extent each feature affected the initial hindsight impressions (see the right side of Table 1 for means and standard deviations of the t1-t2post differences and Figure 3 for a visualization of the results).

Figure 3

Mean t1-t2post Differences (SEs) as a Function of Experimental Text Condition

Repeated Exposure Text Coherence Novel Information 16 14 12 10 8 6

Mean Mean Difference 4 2 0 Likelihood Inevitability Foreseeability

First, we examined how the effect of repeated exposure on participants’ impressions of inevitability and foreseeability relates to the respective initial hindsight impressions. To this end, we tested the t1-t2post differences in the repeated exposure condition against zero by WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 26 computing a separate planned contrast for impressions of inevitability and foreseeability

(contrast weights: crepeated exposure = 1, ctext coherence = 0, cnovel information = 0). Here, for neither of the two hindsight impressions did we obtain a significant difference, tinevitability (144) = 0.14, p

= .888, d = 0.02, tforeseeability (144) = 1.03, p = .306, d = 0.15. Participants’ impressions of inevitability and foreseeability after rereading the very same information did not differ from recipients’ initial level of these hindsight impressions at t1. Therefore, the significant t2pre-t2post effect of repeated exposure (see the section Unique Effect of Repeated Exposure (H1)) entirely reactivated participants’ initial hindsight impressions from one week earlier.

Next, we explored how the effect of providing novel information on participants’ impressions of likelihood and foreseeability (as obtained in the t2pre-t2post analyses) related to the respective initial hindsight impressions. If the effect of novel information alone led to hindsight impressions that were higher than the initial impressions, the t1-t2post increase in hindsight impressions should be larger in the novel information condition compared to the text coherence condition. Therefore, we compared the t1-t2post differences between both conditions with a planned contrast for participants’ impressions of likelihood and foreseeability (contrast weights: crepeated exposure = 0, ctext coherence = -1, cnovel information = 1). The contrast analyses yielded a significant effect for participants’ impressions of foreseeability, t

(144) = 2.04, p = .043, d = 0.41, but no effect for impressions of likelihood, t (144) = 0.10, p

= .921, d = 0.02. Thus, providing novel information increased recipients’ initial impressions of foreseeability at t1. There was, however, no effect of novel information on participants’ initial impressions of likelihood, and the significant t2pre-t2post effect on likelihood (see the section Unique Effect of Novel Information (H3)) therefore signifies a reactivation of participants’ initial t1 level.

Finally, we were interested in how the hindsight impressions after reading a biased text that contained all three features (i.e., a highly coherent text containing repeated and novel WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 27 information) related to the initial hindsight impressions after learning about the event. We thus computed another set of contrast analyses to test for a significant t1-t2post increase in the novel information condition, where the summarizing text combined all three features

(contrast weights: crepeated exposure = 0, ctext coherence = 0, cnovel information = 1). The analyses yielded a significant increase in all three hindsight impressions, tlikelihood (144) = 2.21, p = .029, d =

0.31, tinevitability (144) = 3.24, p = .001, d = 0.46, tforeseeability (144) = 4.28, p < .001, d = 0.61.

Therefore, the reception of a text that provided a coherent account with both repeated and novel information led to hindsight impressions that exceeded recipients’ initial hindsight impressions from one week earlier - consistently across all three measures.

Discussion

Prior studies have shown that initial hindsight impressions can increase after reading biased media content (Oeberst et al., 2014, 2018; von der Beck et al., 2017). In the present longitudinal study, we tested which features of such content foster increases in hindsight impressions by comparing judgments given immediately before and after reading a biased text on an event (t2pre vs. t2post). Furthermore, we compared hindsight impressions given directly after learning about the event with impressions given one week later before reading the text (t1 vs. t2pre) to explore whether hindsight impressions decrease over time without novel input. Finally, by comparing initial hindsight impressions with impressions reported after reading the text (t1 vs. t2post), we examined whether reading the biased text led to hindsight impressions that exceeded impressions reported directly after learning about the event.

Both reading already known information (H1) and receiving entirely novel information (H3) exerted a unique effect on readers’ hindsight impressions, but text coherence did not (H2). Specifically, repeated exposure alone increased readers’ impressions of inevitability and foreseeability of the event and providing novel information increased WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 28

impressions of likelihood and foreseeability (t2pre-t2post). Furthermore, we found that, in the absence of novel input, initial hindsight impressions (i.e., inevitability and foreseeability) decreased over the course of one week (t1-t2pre), and that the unique effects of repeated exposure and novel information both reactivated these initial impressions (t1-t2post). In fact, providing novel information even led to impressions of foreseeability that exceeded the t1 level, and when participants read a text that combined all three text features, we obtained impressions that were larger than the initial t1 impressions consistently on all three hindsight measures.

Repeated Exposure and Novel Information Affect Hindsight Impressions

The finding that receiving novel information increased readers’ hindsight impressions is in line with various research demonstrating that causal information elicits hindsight bias during the perception of events (e.g., Nestler et al., 2008, Yopchick & Kim, 2012).

Furthermore, the finding that merely repeating already known information sufficed to exert a hindsight effect even goes beyond past studies that always presented some kind of new

(oftentimes causal) information to examine the mechanisms behind hindsight bias (e.g., Nario

& Branscombe, 1995; Oeberst et al., 2018; Roese & Olson, 1996; Wasserman et al., 1991;

Yopchick & Kim, 2012). Importantly, these findings are highly relevant as real-world scenarios likely combine both text features: Media coverage during disasters (and other phenomena like elections) is highly repetitive but at the same time novel information on the topics keep steadily coming to light. Also, it is reasonable to assume that media coverage not only comprises these features, but also qualifies as biased: First, particularly during unexpected negative events with far-reaching consequences such as disasters, most information search and processing takes place after the event has occurred. As a result, the search for an explanation will yield predominantly event-consistent information, thereby providing a one-sided information base. Second, the need to find an explanation for negative WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 29 and consequential events is particularly high, hence triggering an even more pronounced one- sided search for information (Ash, 2009; Pezzo, 2003; Schkade & Kilbourne, 1991). Third, and not limited to unexpected events, the robustness and pervasiveness of hindsight bias

(Guilbault et al., 2004; Pohl et al., 2002; Pohl & Hell, 1996) suggests that authors of media content likewise routinely succumb to hindsight bias and translate it into their reports even if they had balanced information in the first place (Oeberst et al., 2018).

What remains unclear, however, is by which means exactly these text features exert an effect. Specifically, with regard to repeated exposure, rereading already known information may make it easier to develop a (biased) causal model of the event (Chaiken & Yates, 1985), but it could also operate in the absence of any causal reasoning, for instance, by increasing the perceived processing fluency (Roese & Vohs, 2012). And in terms of novel information, participants could either have added objectively causal information to the model of the event, or they may have added non-causal background information which they had evaluated to be causally relevant in retrospect (although answers to an open question about the conjectured causes of the incident suggest that background information was interpreted as widely irrelevant for the occurrence of the disaster since only one participant in the causal information condition referred to such information). Future research may aim to disentangle the specific mechanisms underlying the effect of both features.

Another point that needs to be addressed is that the analyses yielded inconsistent findings across the three hindsight measures. While repeated exposure exerted an effect on impressions of inevitability and foreseeability (but not likelihood), novel information increased impressions of likelihood and foreseeability (but not inevitability). There might be both methodological and theoretical reasons for these inconsistencies. On methodological grounds, the different operationalizations of the hindsight measures may have led to diverging results. Specifically, while impressions of inevitability and foreseeability were WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 30 assessed with multiple item scales, likelihood was assessed on a single item, which may have resulted in a comparably lower reliability and test power for the likelihood rating. Also, only for the likelihood measure – but not for the other two measures - participants were explicitly instructed to ignore the outcome knowledge (see footnote 5), which may have led participants to reconsider this particular judgment. However, both methodological points argue for a distinctiveness of the likelihood measure and would thus suggest a unique pattern of results for this dependent variable, which is not what we obtained. On theoretical grounds, taking into account that the most consistent effects were obtained on impressions of foreseeability, participants might have been more concerned with the question of responsibility and blame rather than the specific chain of antecedents that built up to the event: Particularly in the context of disasters, the desire to find someone to blame is enhanced (Walster, 1966).

Responsibility is, in turn, most closely linked to the foreseeability component of hindsight bias (Blank et al. 2008; Nestler et al., 2010) and recipients’ primary reasoning could thus have been rather metacognitive (who could have known what and when? – foreseeability) than causal (what led to which effect? – inevitability). There are certainly other potential factors that might be responsible for the diverging results and we think that it is an interesting next step for future research to investigate what determined those differences. Importantly, however, for both repeated exposure and novel information we obtained effects on two of the three hindsight measures, and taken together, we consider this to be a meaningful finding.

In contrast, we did not find any biasing effect of presenting information more coherently. One potential explanation for the lacking effect may lie in the information material provided to resemble the immediate media coverage after a disaster. Specifically, the short news section presented in the first session already contained much information and participants thus had already much data available to base their initial judgments upon. Such a starting point, however, may leave little room for increase, since text coherence may be WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 31 particularly beneficial, when prior knowledge is limited. Prior research regarding level of understanding, for instance, indicates that low-knowledge readers profit more from high- coherence texts than high-knowledge readers (McNamara & Kintsch, 1996; McNamara et al.,

1996). In addition, the short news was already presented in chronological order and, for the reason of feasibility, still provided only by one primary source (i.e., news agency

‘Globus.com’) via one medium (i.e., a webpage) within a short period of time (i.e., a few minutes). Thus, as compared to real-world scenarios in which we receive information about an event from several sources across a rather long period of time, increases in text coherence in the present study may have been rather small. Future research may provide initial information through multiple sources across several days to obtain a more powerful (and realistic) test of the effect of text coherence.

Temporal Development and Practical Implications

We set out to examine the effect of the three text features in a realistic setting, in which people receive quite a lot of information in the immediate media coverage after a disaster (i.e., short news at t1), and then, eventually, read a summarizing text like a Wikipedia article after some time has passed (i.e., biased text at t2). With one week between the two sessions, we realized a relatively long retention interval compared to other research and were thus able to examine the temporal development of hindsight impressions. While past research suggested that hindsight bias increases during the immediate media coverage (Bryant &

Brockway, 1997; Bryant & Guilbault, 2002; Oeberst et al., 2018, Study 1), our study is the first to report that hindsight impressions decrease over time when no further information is obtained (t1-t2pre), which might be attributed to people forgetting relevant information

(Ebbinghaus, 1885; Murre & Dros, 2015). In light of this decrease, we tested how the final hindsight impression after reading the biased text related to the initial impressions after learning about the event (t1-t2post). Here, we found that the unique effect of both repeated WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 32 exposure and novel information predominantly reactivated the initial hindsight impressions that people had forgotten over time. In other words, the process of forgetting information

(i.e., t1-t2pre decrease) may (somewhat) offset the biasing effect of media content (i.e., t2pre- t2post increase), whereby one must qualify this in case of important events (e.g., disasters), where people as recipients are confronted again and again with information regarding this event, making forgetting almost impossible.

Interestingly, however, the t2pre-t2post effect of reading biased texts may not only be concealed by memory processes, it may also be contingent on it: The more information one forgets over time, the more can potentially be reactivated in turn. Furthermore, it is plausible to assume that the effect of each text feature varies depending on the retention interval. For instance, while entirely novel information may be particularly useful when the initial causal model is relatively fresh and new information can be easily integrated, repeated exposure

(and potentially also text coherence) may especially exert an effect after a large part of the initial causal model has been forgotten. Future studies could investigate the role of forgetting processes by systematically varying the length of the retention interval.

Importantly, while the unique effects of repeated exposure and novel information predominantly caused hindsight impressions to maintain the initial t1 level, we found that when participants read biased media content that contained all three text features, they reported impressions that exceeded the initial level consistently on all three hindsight measures. This result goes beyond previous studies on the effect of reading biased media content on hindsight bias which had no access to participants’ initial impressions (Oeberst et al., 2014, 2018; von der Beck et al., 2017), and implies that biased hindsight impressions of a respective event may not only persist, they may also increase over time. This, in turn, may not only shape public opinion of the likelihood, inevitability and above all foreseeability of WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 33 an event but also of responsibility and accountability regarding the agents involved (e.g.,

Anderson et al., 1997; Carli, 1999; Hastie et al., 1999).

Limitations

In an effort to elucidate the potential features of biased media content that determine increases in hindsight impressions, all participants received outcome information (i.e., the sinking of the ferry) right at the beginning of the first session. Consequently, there was no foresight condition realized and we therefore did not measure hindsight bias per se (i.e., deviations of hindsight from foresight impressions). However, hindsight bias has been well established in the literature (see Christensen-Szalanski & Wilham, 1991; Guilbault et al.,

2004 for meta-analyses; see Pohl & Erdfelder, 2017; Roese & Vohs, 2012 for reviews), and the main objective of the present study was to investigate which features of biased texts, presented after the outcome is known, can affect judgments. In other words, although we cannot be sure whether our participants were biased as normatively defined, from a phenomenological point of view, it is a worthwhile endeavor to investigate, what determines increases in absolute hindsight impressions of likelihood, inevitability and foreseeability of an event, irrespective of any foresight impression.

In addition, it could also be argued that increases in hindsight impressions may be attributed to demand characteristics of the experimental setting - particularly in terms of the t2pre-t2post comparison where participants reported their impressions before and after reading the summarizing text. Although we cannot rule out that demand characteristics affected our results with certainty, we consider it rather unlikely that they alone led to the obtained results for at least two reasons. First, a demand characteristic explanation is consistent with any type of change, hence—without further assumptions—it cannot explain why we found an increase from t1/t2pre to t2post hindsight perceptions. Second, the approach can also not explain why we found increases in the repeated exposure and novel information condition, but not in the text WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 34 coherence condition which presented a summarizing text that was basically the crossover between the other two and thus should be equally impacted by demand characteristics.

Nevertheless, we think it is an important task for future research to account for this alternative explanation (e.g., by assessing a control group).

WHAT DRIVES INCREASES IN HINDSIGHT IMPRESSIONS? 35

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