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The Kama Muta Model of Being Moved
New Evidence from Intraindividual Cross- correlations between Continuous Measures
Anders Kuvaas Herting Candidate 29
Submitted as final thesis at the Institute of Psychology University of Oslo
Fall 2021
Page 2 of 66 Abstract
Title: The Kama Muta Model of Being Moved New Evidence from Intraindividual Cross- correlations between Continuous Measures
Author: Anders Kuvaas Herting
Supervisor: Prof. Thomas Wolfgang Schubert
In recent years, several theoretical accounts of the emotional experience commonly called “being moved” have been developed. Kama muta theory argues that being moved constitutes a distinct positive emotion that is elicited by the appraisal of a sudden intensification of a communal sharing relationship. The current thesis addresses the nature of being moved and whether kama muta theory provides a more accurate account than its contemporary alternatives. A previous study in which participants rated various items continuously while watching videos was replicated and extended on with the principal difference that cross-correlations this time were measured within participants and then averaged across participants (rather than the other way around). The sample in the current work consisted of 457 native English speakers over the age of 18 from the USA. It was predicted that being moved would (i) co-occur with social closeness, positive affect, bodily warmth, and goosebump, (ii) co-occur with appraised closeness to a greater extent than with appraised morality, (iii) co-occur with positive affect to a greater extent than with negative affect, and (iv) co-occur with bodily warmth to a greater extent than with goosebumps. All predictions except prediction ii regarding the difference between co-occurrence with appraisals of closeness and appraisals of morality were supported. The thesis concludes that kama muta theory is probably right about some of its claims regarding being moved, but that other claims still need more research. The current results as well as the state of recent evidence point towards that being moved does constitute a distinct positive emotion. Regarding appraisals, it is concluded that the current results cannot resolve whether kama muta theory is right and that more research using inventive designs is needed to resolve this issue. A few future directions, in particular regarding appraisals, are proposed. The research was done in collaboration between the author and supervisor Prof. Thomas Schubert with helpful comments from members of the Kama Muta Lab at the Institute of Psychology and was a contribution to the Being moved- project at the research group for social psychology.
Page 3 of 66 Table of Contents
Abstract ... 2
Table of Contents ... 3
The Kama Muta Model of Being Moved: Evidence from Intraindividual Cross-correlations between Continuous Measures ... 6
Overview of the Thesis ... 7
Note on Terminology ... 7
Recent Scientific Accounts of Being Moved ... 8
Being Moved by Communal Sharing: Kama Muta Theory ... 9
Being Moved by Positive Core Values ... 11
Being Moved as Mixed Affect ... 12
Being Moved by Outstanding Morality: Elevation Theory ... 13
Kama Muta Theory, Other Accounts, and the Folk Concept ... 14
Original Empirical Work: A Replication and Extension Study ... 15
Predictions ... 16
1. Schubert and Colleagues’ (2016) Findings Will Replicate ... 17
2. Time Series of Being Moved Will Cross-correlate Positively with Positive Affect, and this Cross-correlation will be Greater than the Cross-correlation between Time Series of Being Moved and Time Series of Negative Affect... 17
3. Time Series of Being Moved Will Have Higher Cross-correlations with Time Series of Social Closeness than with Time Series of Morality ... 18
Theoretical and Methodological Considerations ... 19
Method ... 21
Overview ... 21
Participants ... 21
Materials ... 22
Stimuli ... 22
Measures ... 23
Procedure ... 24
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Data Preparation ... 25
Computing Cross-Correlation Functions ... 27
Inferential Statistics ... 29
Results ... 30
Confirmatory Analyses ... 30
Sensations-triad ... 31
Appraisals-triad ... 31
Valence-triad ... 32
Exploratory Analyses ... 32
Following up on Differences Between Videos ... 32
Exploratory Mixed Model of Appraisals ... 33
Comparison of Cross-Correlations Calculated Within Participants to Those Calculated on Averaged Data ... 34
Discussion ... 37
Appraisals ... 38
Closeness and Morality May Load on an Underlying Factor ... 38
The Appraisals May Be Consequences, Not Antecedents ... 40
Future Directions Regarding Appraisals ... 41
Valence ... 42
Sensations ... 43
Warmth ... 44
Goosebumps ... 45
Benefits of Measuring Correlations at the Intraindividual Level ... 47
Limitations ... 48
Soundness of Measures ... 48
Representativeness of Stimuli ... 50
Other Methodological Limitations ... 51
Future Directions ... 52
Conclusion ... 53
References ... 56
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Appendices ... 64
Appendix 1: Details about Sensitivity Analysis ... 64
Appendix 2: Links to and Synopses of Videos ... 64
Thai Medicine ... 64
Marina Abramovic ... 64
Two Orphans ... 64
Appendix 3: Exploratory mixed model (Written by the supervisor) ... 65
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The Kama Muta Model of Being Moved: Evidence from Intraindividual Cross-correlations between Continuous Measures
The emotional experience commonly called “being moved (to tears)” or “feeling touched”—for example when witnessing events such as surprising reunions, receiving unexpected help or gifts, or encountering cute juvenile animals—is probably familiar to most people. Research on this and related feelings has a long tradition (for a summary, see Zickfeld, Schubert, Seibt, & Fiske, 2019), dating at least back to Darwin’s (1872a) discussion of tender emotions. Being moved is labelled and understood in many cultures, typically experienced as positive, and has a common phenomenology that includes feeling warm in the body, goosebumps, and tears (Fiske et al., 2019; Zickfeld, Schubert, Seibt, Blomster, et al., 2019).
In recent years, there has been a surge of interest in being moved, and a few new attempts at a precise theoretical account of the experience have emerged. These broadly agree about the sensations of being moved (goosebumps, chills, a lump in the throat, warmth or tingling in the chest, and moist eyes) and that the experience is generally positive, but there are differences between them regarding whether being moved is a distinct emotion or a state of mixed emotions, the role of negative affect in experiences of feeling moved, which appraisals elicit the
experience, and (although less discussed) the motivations and behavioral tendencies that being moved forms.
One of the contemporary accounts of being moved, kama muta theory, is under scrutiny in this thesis—sometimes in isolation, but it is also compared against other accounts of being moved were that is found relevant. According to kama muta theory, “being moved” itself is a vernacular label that people often put on the experience of a distinct positive emotion that there is no accurate vernacular label for, but that researchers have labelled “kama muta” (Fiske et al., 2019; Seibt, Schubert, Zickfeld, & Fiske, 2017; Zickfeld, Schubert, Seibt, Blomster, et al., 2019;
Zickfeld, Schubert, Seibt, & Fiske, 2019). Kama muta is theorized to be elicited by the appraisal of a sudden intensification of a communal sharing relationship—or as put it in lay terms: a sudden sense that two or more people are becoming more like one.
Page 7 of 66 Overview of the Thesis
This thesis aims to determine the soundness of kama muta theory as an accurate account of being moved as well as to understand the nature of being moved and the mechanisms and functions of its appraisals, sensations, and valence better. The empirical work is a replication and extension of a quantitative study of the nature of being moved that supported several predictions from kama muta theory (Schubert et al., 2016). The goals of the new study was (i) to see if the results would replicate when taking a statistical fallacy found in the original study into account, (ii) to test additional predictions drawing on kama muta theory that were not included in the original study, and (iii) to make a statement about the statistical fallacy that the current research addressed. (The last aim was also considered important since the research is scheduled to be published, but it does not take up a major part of the thesis).
The thesis begins by introducing the phenomenon that is commonly called “being moved” and four contemporary models of this affective state. Next, it describes Schubert et al.
(2016), the study that the original empirical work replicated and extended on, its main
shortcomings, and how the new empirical work tried to overcome those. It goes on to describe the new study in detail and discuss the results and what they mean for kama muta theory and being moved. Next, a short section about the significance of improving on the methodology of Schubert et al. (2016) and takeaways from that is provided. The thesis ends with a discussion of limitations to the current empirical work, future directions, and a short conclusion.
Note on Terminology
Before diving into the thesis, some aspects of the terminology that is used should be explained and justified. Most importantly, it is inherently problematic to ask for a theoretical account of the experience often called “being moved”. Although many people have an idea about what this experience is like and may be able to think of some prototypical examples of it (e.g., being moved by seeing someone helping a stranger in need), the boundaries between it and other experiences that are similar yet qualitatively distinct are not given. Therefore, different accounts of being moved may disagree simply because they are not looking at exactly the same
phenomenon. It may be tempting to simply try to characterize experiences that people label
“being moved” or judge as “moving”, but this is a mistake since these lay terms also can denote experiences that clearly are different from the one in question, including awe, sadness, having
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strong emotions, or being under strong influence of (i.e., literally being moved by) emotions (Fiske, Schubert, et al., 2017). This thesis does not attempt to offer a solution to this problem.
(Kama muta theory does offer a solution, Fiske, Schubert, et al., 2017, but applying that solution would by definition make kama muta theory the most accurate account of being moved.) But the thesis tries to stay mindful of this problem in the discussion of kama muta and being moved.
Another issue to consider when discussing which account is more accurate is that some focus on the momentary mental state of being moved (i.e., what exactly is happening in the mind and body at moments of being moved; e.g, Cova & Deonna, 2014; Fiske, Schubert, et al., 2017) while others focus on describing episodes of being moved (e.g., Menninghaus et al., 2015, 2017), taking in the whole event from beginning to end and more of the surrounding context of
cognition and emotion. This thesis evaluates accounts by their description of the momentary mental state.
Other terms used in this thesis may also be more ambiguous than one might assume, but this cannot always be accounted for. As a rule of thumb, lay terms (other than being moved) in what follows are used to refer to the subjective experience that people label as such. For
example, “goosebumps” is used to refer to the experience labelled as such although this may be less precise than the more scientific “piloerection”.
Finally, note that the term “appraisal” in this thesis is used to refer simply to any cognitive evaluation of an event in the context of considered that it may be what elicits a particlular emotion. As a similar usage of the term seems common in research on being moved (Fiske et al., 2019; e.g. Fiske, Seibt, et al., 2017; Landmann et al., 2019; Menninghaus et al., 2015), this clarification may seem excessive. But it is mentioned since the term is used inconsitently (Scherer, 1999).
Recent Scientific Accounts of Being Moved
There is an ongoing discussion between a few recent theoretical accounts of being moved, four of which are described below. These accounts broadly agree about what being moved feels and looks like (sense of warmth, tears, goosebumps, chills, choked up, overall positive valence) and that being moved is associated with a sense of meaningfulness. Each account disagrees with some or all the others regarding which appraisals elicit the feeling (Cullhed, 2019; Landmann et al., 2019), whether being moved is a distinct emotion or a state of mixed positive and negative
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affect (Menninghaus et al., 2015; Schubert et al., 2017), and what behaviors and motivations the emotion creates. For brevity, the descriptions below are limited to the features of each account that makes it stand out from the other ones (i.e., they will not repeat what was just mentioned about sensations and overall positive valence).
Being Moved by Communal Sharing: Kama Muta Theory
According to kama muta theory, being moved constitutes a distinct positive emotion. It is theorized that there is no exact term for this emotion in everyday language, and the emotion has therefore been labeled “kama muta” (“Moved by love” in Sanskrit). The appraisal of this emotion is, according to the theory, the sudden intensification of a communal sharing relationship (Fiske, Schubert, et al., 2017). To understand what this means, it helps to first describe relational models theory, where the concept of communal sharing comes from.
The core idea in relational models theory is that human social relations fall into four types or vary along four dimensions: communal sharing, authority ranking, market pricing, and equality matching (Fiske, 1992, 2004). Communal sharing relationships are characterized by a sense of unity—or having a common essence—between the parties and sharing of resources according to need and ability. Communal sharing is especially strong between close friends and kin, in which interactions are driven by concern for each other's interests, rather than of personal gain, but there may also be a significant communal sharing component in relationships to more distant people of whom one has something in common, such as nationality or language—or being human. Authority ranking relationships are the relationships between legitimate superiors and their subordinates. This type of relationship is asymmetric in the sense that superiors treat their subordinates as such (but often also with respect and care, thus upholding their legitimacy) while subordinates look up to superiors and follow their guidance or orders. Equality matching relationships are characterized by the treatment of the involved parties as equals, sharing
resources, rights, and responsibilities equally rather than proportionally or according to need and ability. Finally, market pricing relationships are characterized by proportional transactions and include the way that people relate to each other on the market.
Human interaction is complex and multifaceted, and relationships can be characterized by different models at once or in different contexts. One may do a favor for a friend out of concern for them (communal sharing), but may also make economic tansactions with the same friend
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(market pricing) and believe that certain responsibilities ought to be shared equally (equality matching). As another example, it can be assumed that a healthy parent-child relationship would be characterized by both communal sharing and authority ranking.
To recap, kama muta theory postulates that the appraisal of being moved is the sudden intensification of a communal sharing relationship. Fiske and colleagues (2017) felt the need for an entirely new label for this emotion since “being moved” does not always describe all kama muta instances (and vice versa). At least sometimes, “being moved”, is used to describe the emotions sadness or awe or simply feeling very emotional or very affected by (i.e. literally moved by) strong emotions. They also show that kama muta also can appear in many experiences that involving the appraisal of a sudden intensification of a communal sharing relationship but that typically not referred to as “being moved”. For example, there may be a sudden intensification of communal sharing and a sense of kama muta when marching
synchronized in a marching band or military unit or when singing and moving in unison during a religious ceremony. (See Fiske, 2020 for a discussion of the problems with using lay terms as scientific constructs).
Kama muta is theorized to be universal and evolved through natural selection. According to the theory, kama muta is not just elicited by experiencing intensifications of communal sharing but also motivating people to maintain and invest in communal sharing relationships (Fiske, Seibt, et al., 2017). This makes kama muta into a social glue. Cultural practices like partaking in rituals, telling stories, wearing the same clothes, and sharing resources contribute to communal sharing and chances of feeling kama muta. Kama muta-moments, in turn, keeps the group motivated to take care of each other and work towards common goals. The emotion is pleasant and often preferred to enjoy along with others. This makes the social practices that elicit kama muta attractive to members of the group. Since cooperation is so central to survival and reproduction for humans, it is easy to see how an emotion like kama muta would be naturally selected for.
Although saying that kama muta is universal, the theory aslo emphasizes that its expression and interpretation varies greatly between cultures, groups, people, and contexts (Fiske, Seibt, et al., 2017). Weak instances of kama muta are expected to be frequent day-to-day and contribute to making social encounters pleasant and wanted. Stronger kama muta may be felt when sharing an important memory or hugging a loved one after a long-lasting separation,
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perhaps labelled “nostalgia” and “love” respectively. In some cultures and social circles, strong kama muta can even be understood as a supernatural experience—it can feel like contact with a higher power like God.
The principal argument that experiences of kama muta constitute a distinct emotion is that the emotional experience of being moved and other kama muta experiences satisfy common definitions of the characteristics of an emotion (Fiske, Schubert, et al., 2017; Zickfeld, Schubert, Seibt, Blomster, et al., 2019). It is theorized to have a unique appraisal pattern (sudden
intensification of communal sharing), distinct bodily symptoms and phenomenology (including chills, piloerection, sense of warmth in the chest, and moist eyes or tears), valence (positive), expressions (including moist eyes, hand to the chest, and uttering “awww”), and motivational tendencies (to bond and care, i.e. to invest in communal sharing relationships). The underlying theorizing builds on an extensive review of the literature on being moved and associated concepts as well as anthropological research (Fiske, Schubert, et al., 2017; Zickfeld, Schubert, Seibt, & Fiske, 2019).
The distinct emotional and cognitive signature of kama muta has been supported by studies that asked participants in 15 different countries in more than 19 different languages to recall emotional experiences or watching videos that elicit different emotions and comparing the hypothesized characteristics of kama muta between episodes of being moved and associated emotions like awe, joy, and sadness (Seibt, Schubert, Zickfeld, Zhu, et al., 2017; Zickfeld, Schubert, Seibt, Blomster, et al., 2019). Also, in a study where participants self-reported their reactions to moving videos continuously, Schubert and colleagues (2016) found that “being moved” co-occurred very much with “social closeness” rated with the Inclusion of the Other in the Self-scale (Aron et al., 1992), which was meant to be an approximation of communal
sharing, but much less with happiness and sadness, supporting both that appraisals of communal sharing elicits being moved and that being moved is distinct from associated emotions.
Being Moved by Positive Core Values
Another account of being moved that has been developed over approximately the same time period as kama muta theory is that being moved is a distinct positive emotion elicited by the apprehension of positive core values made salient (hereby, the positive core values view; Cova &
Deonna, 2014; Deonna, 2020; Landmann et al., 2019). A positive core value has been defined as
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a value of central importance so that it cannot be put a price on (Cova & Deonna, 2014) and as a value that is important, intrinsic, and universal (Deonna, 2020). Since there are individual differences in what people value, the positive core values view predicts that different people will tend to be moved by somewhat different events (Cova & Deonna, 2014; Landmann et al., 2019).
Instead of having a specific action tendency, it is proposed that being moved functions to remind people about and make them consider what really matters to them and indirectly biasing their behavior in this way (Cova & Deonna, 2014).
The initial case for the positive core values-view consisted of a combination of armchair research and qualitative analysis of instances of being moved from 100 participants (Cova et al., 2017; Cova & Deonna, 2014; Deonna, 2011). Strick & van Soolingen (2018) found that people were more moved when positive values emerged in unfavorable circumstances (e.g., when somebody with no social network received help vs. when somebody with a good social network received help), arguing that the contrasting bad circumstance made the positive value more salient. Landmann and colleagues (2019) found that both appraisals of exceptional prosocial behavior and appraisals of exceptional effort (presumably making different types of core values salient) mediated being moved by videos, newspaper articles, and pictures with relationship, success, failure, separation, and reunion as main themes. The same studies found that being moved was moderated by having more prosocial values (operationalized as moral identity) but not by having more achievement values (operationalized as achievement motivation), providing some mixed evidence for the claim that how much one is moved by different types of events and appraisals depends on which values one inhabit.
Being Moved as Mixed Affect
A third recent account takes a different approach from kama muta theory and the positive core values-view. Menninghaus and colleagues (2015, 2017) described feeling moved, not as constituting a single emotion, but as a state involving simultaneous positive and negative
emotions in a context of social bonding (hereby the mixed affect view). Their view distinguishes between joyfully moving and sadly moving episodes, depending on the valence of the emotions that dominate. Accordingly, one would be joyfully moved by a childhood memory if it evoked mostly positive emotions but also some traces of negative ones, for example sadness from realizing that the happy childhood is over. A funeral could make one feel sadly moved due to a
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combination of dominating negative emotions and some positive emotions, for example feeling some joy when thinking of good memories of the lost one. Menninghaus and colleagues (2017) argued that although feeling moved comes in the joyful and sad varieties, the experience
nonetheless has positive valence. Like kama muta theory, this view also thinks that bonding and prosocial behavior are the motivational tendencies (Menninghaus et al., 2015).
Menninghaus and colleagues’ (2015, 2017) account is in many ways more descriptive and less functional than the two described before. The focus is on mapping episodes of being moved from beginning to end, including eliciting events, appraisals, involved emotions (in which being moved as a distinct emotion is not included), phenomenology, physiology, action
tendencies, and functions (Menninghaus et al., 2015). There is considerably less emphasis on the causal relationships between the components. Although they describe compatibility with social norms, self-ideals, and low sense of agency as appraisals in instances of being moved, it is not explicitly theorized how these appraisals are related to the emotional components of the state (e.g., whether some or all must be present). It is still interesting for the sake of discussion to consider whether Menninghaus and colleagues’ described appraisals elicit or contribute to the experience of being moved.
Menninghaus and colleagues’ approach to being moved leads to a different conclusion than the two previously described accounts, and this is largely due to a different starting point and some different methodological considerations and goals. They did not start with considering if being moved constitutes a distinct emotion but instead asked participants to recall an episode of being moved and explored their content including emotional content (but without being moved or similar concepts included as emotions in their questionnaires; Menninghaus et al., 2015).
Being Moved by Outstanding Morality: Elevation Theory
Elevation theory is not an attempted comprehensive theory of being moved, but it describes an experience that fits the folk psychological concept of being moved and is therefore included here as one account of the appraisals of being moved. Elevation is an emotion theorized to be elicited by appraisals of the great moral virtue others and characterized by warmth or tingling in the chest; chills and goosebumps; motivation to bond or help; and positive affect (Haidt, 2000, 2003). Judging from such descriptions, elevation is captured by the folk psychological folk being
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moved whether it is accurate to consider elevation a distinct emotion or not—in fact, the terms
“feeling moved” and “touched” has often been used to describe and operationalize elevation (Algoe & Haidt, 2009; Schnall et al., 2010; Siegel & Thomson, 2017). The research on elevation is vast and has been focused on how the emotion promotes optimism and prosocial behavior, with less scrutiny of the concept itself (for reviews see Pohling & Diessner, 2016; and Thomson
& Siegel, 2017).
Proponents of both kama muta theory and the positive core values-view have argued that elevation is not a distinct emotion but instead a special case of kama muta or being moved (Cova et al., 2017; Seibt, Schubert, Zickfeld, & Fiske, 2017). Here, it would be inaccurate to claim that elevation theory postulates that great moral virtue is the appraisals of experiences of being moved in general, but elevation theory will, in good faith, be viewed as a theory that elevation is a special type of being moved that is elicited by appraisals of great moral virtue.
Kama Muta Theory, Other Accounts, and the Folk Concept
Kama muta theory’s explanation of the folk concept of being moved has both large
commonalities and great differences with the other accounts. All four accounts agree that being moved is a highly social phenomenon often associated with events of great personal importance (Cova et al., 2017; Fiske et al., 2019; Haidt, 2000; Menninghaus et al., 2015). Since different accounts often explain why a given event elicits being moved equally well, the greatest controversy in the field of being moved regards appraisals. The accounts are also very similar with regards to sensations, overall valence, and action tendencies. Alongside the positive core values view and elevation theory, but unlike the mixed affect view, kama muta theory views being moved as constituting a distinct emotion (although elevation theory only describes instances of being moved that fit the elevation construct).
Kama muta theory is the only account among those described here that posits that the lay term “being moved” and the emotion that being moved constitutes are not identical. Proponents of kama muta theory have criticized other research for asking participants to recall instances of
“being moved” due to the concern that these may not all represent the same phenomenon. As an alternative solution, they have asked participants to report an event that may have involved kama muta and used a validated kama muta scale to test whether kama muta was evoked (such as an
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event where they shed tears due to something positive; (Zickfeld, Schubert, Seibt, Blomster, et al., 2019).
Kama muta theory is also the only account that posits that being moved is elicited specifically by the social closeness-aspects of an event. The positive core values-view, in contrast, allows for a much broader category of appraisals to elicit being moved. Proponents of that view have sometimes criticized kama muta theory for not being able to explain situations labelled being moved where a sudden intensification of communal sharing is hard to identify—
for example when people report to be moved by seeing great efforts to reach a goal (Landmann et al., 2019). Proponents of kama muta theory have responded to this by appealing to the previous point—that “being moved” does not always denote kama muta—and that the
experience labelled “being moved” in Landmann et al. (2019) is sometimes different from kama muta (Zickfeld, 2020). This argument has limited empirical evidence.
Original Empirical Work: A Replication and Extension Study
The original research presented in this thesis attempts to replicate a previous study on kama muta due to a statistical fallacy made in that study. Schubert et al. (2016) let participants continuously interact with rating scales while watching videos from YouTube that are described as very moving. Participants were assigned to rate only one variable, and the variables included were being moved, social closeness, warmth, goosebumps, crying, happiness, and sadness.
Participants’ current rating on the scales was collected continuously throughout the videos, resulting in time series. For each cell (variable x video) the participants’ time series were averaged, creating one time series per variable per video. They next detrended and reduced the resolution of the averaged time series. Finally, they computed cross-correlations with no lag between being moved and each of the other time series. Based on the cross-correlations, they made inferences about how the different variables do or do not co-occur with the self-reported level of being moved. Supporting kama muta theory, they found high cross-correlations between being moved and social closeness, warmth, goosebumps, crying, and happiness (was expected because kama muta is assumed to be positive); and varying cross-correlation between being moved and sadness, depending on how sad the moving climax of the video was.
Schubert et al. (2016) has a significant shortcoming: Its application relied on cross- correlating time series averaged across participants between groups. Interpretation of such data
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requires inferring intra-individual psychological processes from interindividual comparisons.
Both classic and recent methodological contributions have pointed out that this is often problematic (Borsboom et al., 2003; Fisher et al., 2018a; Hamaker, 2012). In the replication presented in this thesis, participants rated multiple items first, and cross-correlations were computed individually for each participant. Afterwards, the average intraindividual cross- correlations were computed, and different cross-correlations were compared. A part of the discussion section is focused on the value of this approach for the current study and for psychological research.
In addition to trying to replicate some of Schubert and colleagues’ (2016) findings, additional predictions were added in response to the new evidence and theorizing on being moved that has happened since Schubert et al.’s publication. The new predictions were considered exclusive to the kama muta account of being moved and added to test kama muta theory against alternative accounts.
Predictions
The predictions can be divided in two types based on their purpose and suitable statistical tests. It was predicted that the findings from Schubert et al. (2016) regarding the cross-correlation
between individual variables and being moved would replicate. These are all predictions that correlations will be greater than 0 and tests of the various claims from kama muta theory in isolation. The other type of predictions are those that one cross-correlation will be greater than another (e.g., being moved will have a greater cross-correlation with closeness than with morality). These are novel predictions in the current work and are (with one exception) tests of kama muta theory against alternative accounts of being moved. All predictions were
preregistered and can be found at https://osf.io/de32v/.
(Note that there were two predictions, that average being moved ratings would correlate positively with individual differences in Integration of Tenderness from the Affect Integration Inventory (Solbakken et al., 2017) and negatively with Difficulties Appraising Positive Feelings from the Perth Alexithymia Questionnaire (Preece et al., 2020) when controlling for individual differences in emotional reactivity, that are excluded from this thesis. These were excluded after a reviewer noted that it was unclear how relevant these individual differences were to the theme of the study. In the published version of the study, these predictions and the associated results
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will be included in the supplementary material. For now, it is mentioned for the sake of transparency that neither of these predictions were supported.)
1. Schubert and Colleagues’ (2016) Findings Will Replicate
Four of the items in the new study were identical to items in Schubert et al. (2016): being moved, closeness, warmth, and goosebumps. It was predicted that closeness, warmth, goosebumps, and would all have positive cross-correlations with being moved, replicating Schubert et al. But it was expected that the cross-correlations would overall be lower since Schubert et al.’s averaging of time series across participants should literally have averaged out noise in the continuous measurement.
It was also predicted that the cross-correlation between being moved and warmth would be greater than the cross-correlation between being moved and goosebumps, as in Schubert et al.
(2016). Although neither kama muta theory nor any other account of being moved seems to have a theoretical explanation for it, it has been found that bodily warmth has the highest correlation with being moved among the sensations measured in previous research (Zickfeld, Schubert, Seibt, Blomster, et al., 2019). This may be an indication that feeling warm has a special
significance in being moved over and above other sensations. Especially if replicated once again, this finding deserves some theoretical discussion.
2. Time Series of Being Moved Will Cross-correlate Positively with Positive Affect, and this Cross-correlation will be Greater than the Cross-correlation between Time Series of Being Moved and Time Series of Negative Affect
Schubert et al. (2016) included time series of happiness and sadness and an exploratory
prediction that happiness would be more closely associated with being moved than sadness since people typically describe the experience as positive. This was confirmed in 5 of their 6 videos, but not in the video labelled “Two Orphans” which stands out as being overall much sadder than the other videos in the study. The results in “Two Orphans” were the opposite: being moved cross-correlated greatly with sadness but not significantly with happiness. From this observation, Schubert and colleagues’ concluded that being moved is different from both happiness and sadness, supporting the notion that being moved is a separate emotion.
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In the original work presented here, the happiness and sadness-items were replaced by positive affect and negative affect-items. (The participants were asked to rate their levels of positive feelings and negative feelings in separate trials.) The rationale was that this would provide a more direct look into the involvement of positive and negative affect in being moved.
This relied on the assumption that positive and negative affect can, at least partially, be experienced independently of each other.
It was predicted that being moved, as most theoretical account would agree, would be positively cross-correlated with positive affect on average. Moreover, it was predicted that being moved would have greater cross-correlations with positive affect than with negative affect. This novel prediction was included to test kama muta theory against the account that being moved is a mental state that involves concurrent positive and negative affect (Menninghaus et al., 2015, 2017).
3. Time Series of Being Moved Will Have Higher Cross-correlations with Time Series of Social Closeness than with Time Series of Morality
Appraisals have been the topic of much of the disagreement about the nature of being moved (Cullhed, 2019; Landmann et al., 2019; Strick & van Soolingen, 2018). It is also in the account of the appraisal—a sudden intensification of a communal sharing relationship—kama muta theory diverges the most from alternative accounts. Testing hypotheses regarding appraisals of being moved is challenging because people are moved by compounded events that are typically compatible with multiple accounts (Zickfeld, 2020). In the recent accounts of being moved, positive core values (of which there are many); social norms, self-ideals, and low ability to influence the situation (it is not clear whether Menninghaus et al. (2015) suggest that these cause the feeling); and moral virtue has been proposed as appraisals of being moved.
In addition to creating time series of appraisals of closeness (as an approximation of communal sharing), as in Schubert et al., time series of appraisals of morality were also made in order to test the prediction that closeness appraisals would have a higher cross-correlation with being moved than morality appraisals. There were only enough resources to test against one other type of appraisals. Morality was chosen in order to try to support the claim that elevation can be explained as a special case of kama muta and since many displays of morality and
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prosocial acts clearly elicit being moved (Cova et al., 2017; Menninghaus et al., 2015; Seibt, Schubert, Zickfeld, & Fiske, 2017).
Note that no known account of being moved suggests that these appraisals should not be involved in being moved (Zickfeld, 2020), and the claim here was not that all moments of being moved should have higher closeness ratings than morality ratings. Seibt, Schubert, Zickfeld, and Fiske (2017) found that both morality appraisals and closeness appraisals predicted being moved and argued that this was because both measures were indicative of appraisals of communal sharing. The rationale for the prediction made here was that if kama muta theory is the most accurate account, closeness ratings should on average be higher than morality ratings when experiencing being moved. One can readily think of moments of being moved that would not typically (at least not obviously) be considered very moral, such as seeing a baby do something cute or sharing a special moment with a loved one. But, assuming kama muta theory, the same should not be true for appraisals of communal sharing (which the closeness item
operationalized). If measuring appraisals across representative samples of moments of being moved and humans (as the current study strived to), kama muta theory should predict that
appraisals of communal sharing should be higher than appraisals of morality and other appraisals often associated with being moved.
Since none of the other accounts claim that the appraisal of being moved is as specific as kama muta theory does, it seems to be only kama muta theory that can make a prediction about which appraisal will be more cross-correlated with being moved. Assuming the positive core values view, one of the appraisals would be more prominent if people tended to value either of morality or closeness more than the other one, but it is not at all clear whether that should be expected. Although elevation theory implies that one can experience a variant of being moved by appraisals of morality (Cova et al., 2017; Pohling & Diessner, 2016; Seibt, Schubert, Zickfeld, Zhu, et al., 2017; Thomson & Siegel, 2017), it also does not imply any prediction here as it is not a comprehensive theory of being moved.
Theoretical and Methodological Considerations
The methodology in the current work was relatively unfamiliar both to the author and the supervisor as well as to psychological research generally. There were thus many lively
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discussions regarding methodological and theoretical problems both during the early conception of the study and after looking at pilot data.
There was some discussion about what to expect regarding the relationships between variables that kama muta theory is not precise about. For example, kama muta theory says that kama muta is positive (Fiske, Schubert, et al., 2017), and it was therefore implied that being moved should always cross-correlate with positive affect. But regarding the relationship between being moved and negative affect, kama muta theory (like the other views of being moved as a positive emotion) says that negative affect can co-occur with being moved but does not have to.
This raised the question of whether the cross-correlation between being moved and negative affect should be predicted to be about zero or just to be lower than the cross-correlation between being moved and positive affect. On the one hand, one could reason that since kama muta comes both alongside and separate from negative affect, the co-occurence should on average be around 0. For this reason, it was at one point during the conception of the current work considered to predict that the cross-correlation between being moved and negative affect would be near 0 and to use equivalence testing to test this prediction (Lakens, 2017). But it was reasoned that since kama muta theory to date makes no statement regarding to what extent kama muta tends to go along with concurrent negative affect. Therefore, it was decided to make no other prediction about the cross-correlation with negative affect than that it would be smaller than the cross- correlation with positive affect.
A related theoretical assumption that is implicit in the method is that positive and
negative affect are not mutually exclusive. This has been heavily debated, but at least, one meta- analysis found medium effect sizes in studies that attempt to elicit mixed positive and negative valence (Berrios et al., 2015).
Regarding the method, it was a central aim to balance following the methods of Schubert et al. (2016) closely but also to adapt them to the within participants-design. All decisions made about data preparation and analysis are explained in the methods section. Since the research was to be published, it was also considered how to balance using unorthodox methods against being intelligible to other researchers. All decisions that were made has been tried to be accounted for in the method section.
Page 21 of 66 Method Overview
The study was correlational, and the correlations were measured between time series within the individual participants. The study consisted of three parts (referred to as triads), each using different participants and sets of items, but otherwise consisting of identical stimuli, procedures, and analyses. All participants rated being moved and two triad-specific items continuously while watching one out of three different videos from YouTube of about 3 minutes, resulting in three time series per participant. Participants in the first triad rated valence-items (valence-triad), second triad rated appraisals-items (appraisals-triad), and third triad rated physical sensations- items (sensations-triad). For each participant, the cross-correlation functions (CCF) between the being moved-time series and the two other time series were computed, resulting in two cross- correlation functions per participant. Next, the cross-correlation functions were converted into Fisher z-coefficients, resulting in one sample of z-coefficients per cross-correlation. These z- coefficients represented the magnitude of the participants’ cross-correlations and were the units of analysis in inferential tests of whether the two cross-correlations were different from each other in magnitude and whether they were different from 0. The three triads and the three different videos resulted in a total of 9 different cells.
Participants
Participants were recruited from the USA through Prolific. All participants were required to be at least 18 years old and native English speakers.
The target sample size was 40 participants for each cell (i.e., 120 per triad). This was decided in part based on a sensitivity analysis (details in Appendix 1) but mainly to ensure a large enough sample to allow for observing some of the interindividual variation in the cross- correlations. To reach about the target sample per cell, at least 120 participants were recruited per triad and the settings in Qualtrics were set to distribute the participants evenly between the three videos. This lead to slightly more than 40 participants per cell on average, with only minor variations (details in table 1).
To achieve 120 participants per triad, 120 participants were first recruited, some were excluded based on preregistered criteria, and additional participants were recruited to “top up”
the sample. This was done in several iterations until the sample size reached the target. In total,
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149 participants were recruited for the valence-triad, out of whom 6 were excluded for failing an attention check embedded in the study (“Answer ‘somewhat like me’ to this question”), 1 due to technical issues, and 15 because they had cross-correlations between time series that were undefined or implausibly extreme (see “Procedure” below), so that 127 participants (49 female, 77 male, 1 other; age range: 18-72) remained. 177 were recruited for the appraisals-triad, out of whom 21 were excluded for failing the attention check, 2 due to technical difficulties, and 34 because of extreme or undefined cross-correlations, so that exactly 120 participants (70 male, 49 female, 1 other; age range 18-70) remained. 197 participants were recruited for the sensations- triad, out of whom 11 were excluded for failing the attention check, 4 due to technical
difficulties, and 61 for having extreme or undefined cross-correlations between time series, meaning that 121 participants remained. In total, 368 participants were included in the analyses (147 female, 218 male, 2 other, 1 preferred not to answer, age range 18-72, median age 32).
They were compensated with USD 3.25 in accordance with Prolific’s standards for ethical compensation (hjemmeside).
Materials Stimuli
Due to resource constraints, the current study could only use 3 out of the 6 videos that were used in Schubert et al. (2016). To capture the essence as well as some of the variation in the
experience, three moving videos were chosen from the six used in Schubert et al. (2016), namely
“Thai Medicine”, “Marina Abramović”, and “Two Orphans” (labels from Schubert et al.; links to and synopses of the videos are found in Appendix 2). Those were picked as they differ in
features theoretically relevant for the current work: “Two Orphans” has a tragic narrative compared to the two other videos (and was the only video that had higher cross-correlations between being moved and sadness than between being moved and happiness in Schubert et al., 2016), and “Marina Abramović” stands out for not depicting any outstanding moral or altruistic behaviour (to the best of our judgement). Hence, this small sample of stimuli should allow for comparing “joyfully moving” scenes with “sadly moving” scenes and the role of appraisals of morality in feeling moved. Note that Schubert et al. (2016) asked experts in Relational Models Theory to judge the relational dynamics of these videos who confirmed that they were judged as increasing in communal sharing over time.
Page 23 of 66 Measures
As in Schubert et al. (2016), the measures were single items that the participants were instructed to rate continuously throughout the video. The items were being moved, social closeness,
morality, positive affect, negative affect, bodily warmth, and goosebumps. Being moved, closeness, warmth, and goosebumps were identical to those items in Schubert et al. (2016) and therefore allowed for testing if Schubert et al.’s (2016) findings regarding those measures would replicate. As in Schubert et al. (2016), closeness was measured using a modified version of the Inclusion of the Other in the Self-scale (Aron et al., 1992). This is a visual scale in which the social closeness between people is represented as the degree to which two circles overlap. Due to the significant conceptual overlap between Inclusion of the Other in the Self and communal sharing, it was assumed that this item was a good approximation of appraisals of communal sharing. Inclusion of Other in the Self virtually be seen as a direct visual representation of communal sharing--with the overlap between the circles representing the unity between the parties. The morality item, asking participants to rate to what extent what they were seeing was
“morally good/right” was introduced in order to compare morality appraisals with closeness appraisals. Positive affect and negative affect (presented to participants as “positive emotions”
and “negative emotions”) replaced Schubert et al.’s (2018) happiness and sadness items. This was done as it was assumed that such measures would be reasonably valid and since we thought such more direct affect items would be more informative about the valence of being moved than Schubert et al.’s (2016) items.
Figure 1: Modified Version of the Inclusion of the Other in the Self-scale (Aron & Aron, 1992) Used to Measure Appraisals of Social Closeness and Assumed to be a Good Approximation of Communal Sharing.
Page 24 of 66 Procedure
The task was created in Qualtrics (qualtrics.com). Each participant watched one video three times in a row. To create time series, a rating scale that the participants were instructed to interact with continuously while watching the video was placed directly underneath the video player. Each participant was assigned one of the three triads of items. All participants rated how
“moved or touched” they felt on a scale from 1 (“not moved”) to 5 (“extremely moved”) during one of the viewings. During the other two viewings, participants in Triad 1 (appraisals) rated
“the degree of closeness between the main characters” (closeness, 7 point scale, using the Inclusion of Other in the Self-scale, Aron et al., 1992) and “how morally good/right you find the events that you see” (morality, 5 point scale). Participants in Triad 2 (valence) rated “the extent to which you have positive feelings” (positive affect) and “the extent to which you have negative feelings” (negative affect) on 5-point scales. Participants in Triad 3 (sensations) rated “whether you feel warm in the chest or another part of your body” (warmth, 3-point scale) and “whether you have goosebumps” (goosebumps, dichotomous). When the rating scale first appeared, the lowest option was selected. Each change of the rating was saved with a timestamp. From these, raw time series consisting of one value per second of the video for each participant were constructed. Order of items within a triad was random. To get a little familiar with the task, participants had to watch at least 20 seconds of a short somewhat amusing video that was not considered moving while rating their level of surprise before they proceeded to the actual trials.
Table 1 shows the means, standard deviations, and maximal values of the ratings (demonstrating that there was meaningful variation).
Page 25 of 66 Table 1
Mean ratings, average maximum ratings, and average standard deviation of the mean for the seven items rated.
Item Feeling moved
Close- ness
Morality Positive affect
Negative affect
Warmth Goose- bumps Video Scale 0 to 4 0 to 6 0 to 4 0 to 4 0 to 4 0 to 2 0 to 1
Thai N 131 43 43 43 43 45 45
Mean 2.26 3.15 2.09 1.50 1.26 0.90 0.39
Max 3.72 5.60 3.84 3.63 3.37 1.89 1.00
SD 1.22 1.80 1.50 1.44 1.38 0.70 0.43
Abra. N 119 41 41 41 41 37 37
Mean 1.81 2.95 2.03 1.52 0.66 0.88 0.34
Max 3.48 5.63 3.66 3.27 2.24 1.89 1.00
SD 1.27 2.06 1.26 1.20 0.82 0.73 0.39
Orph. N 119 36 36 43 43 40 40
Mean 1.80 3.32 2.09 1.17 0.82 0.92 0.34
Max 3.55 5.50 3.81 3.09 2.60 1.90 1.00
SD 1.05 1.64 1.27 1.01 0.80 0.62 0.40
Note. Video labels in the first column: Thai = Thai Medicine, Abra. = Marina Abramovic, Orph.
= Two Orphans. “Mean” is the mean rating given on the item, computed across participants.
“Max” is the mean of every participant’s highest rating on the item. “SD” is the participants’
average standard deviation of the mean on the item, computed by taking the square root of the average variance between participants.
Data Preparation
Following Schubert et al. (2016), the time series were detrended (i.e. for each time series, a general trend for the development of the rating throughout the duration of the video was computed and then subtracted from the time series) before cross-correlations were computed.
Detrending is used in time series research to control for general trends in the data when studying variation at shorter time intervals (Shumway & Stoffer, 2017). The decision to detrend data
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depends on whether the relevant trends in the data are best understood as theoretically interesting or as noise (Jebb et al., 2015). The argument for detrending in Schubert et al. (2016) as well as here was that, for all the videos, the story line is created so that the emotional reactions of the audience steadily build up to a climax where they either remain or wears off more or less towards the end. (Unsurprisingly, there were some individual differences with regards to this.) Without detrending, cross-correlations would probably reflect the similarity between these general tendencies for each of the variables rather than correlation between changes in two variables during short time intervals. Following Schubert et al.’s (2016) rationale and procedure, it was assumed (and confirmed upon inspection of pilots’ time series) that, independently of the variable, the time series in general roughly take incomplete inverse U-shapes, with the highest point towards the end of the video and the series not returning to baseline. To approximately remove that trend, the time series were individually regressed on time in seconds (linear effect) and its square (quadratic effect), but without an intercept (i.e., trends pass through the origin at t
= 0 and rating = 0; Shubert et al. (2016) did not do this, but it was decided as participants’ ratings by default started at 0 and since there is presumably no emotional reactions at the very
beginning), and the residuals were used as the detrended time series.
After detrending, the time series were smoothened with a 9 second moving average, assuming that participants never precisely react in the moment they experience a change (Schubert and colleagues used a different solution to this: They reduced the resolution of the scale by taking the mean of the ratings at second 1, 2, and 3; 4, 5, and 6, etc.). This is different from the procedures in Schubert et al. (2016), but in that study the time series were already much smoother since they were all averages of the time series of 30 to 40 participants. The decision to use nine seconds was made after testing how different degrees of smoothing of the time series of the pilot participants and inspecting the results visually. Results of detrending and smoothing can be seen in Figure 2. The detrended and smoothed time series were used to compute cross-
correlations, as described next.
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Figure 2: Illustration of the datapreparation process before computing cross-correlations for one arbitrary participant in the valence triad. (a): the raw time series. (b): trends that were subtracted, (c): detrended time series before smoothing, (d): detrended time series after smoothing
Computing Cross-Correlation Functions
With the detrended and smoothed individual time series, intra-individual cross-correlation functions (CCFs) with zero lag between each participant’s time series of feeling moved and their other two time series were computed. Since there was no lag, the cross correlation-functions could be computed simply as if they were Pearson’s rs, with each second representing a unit of analysis. (But, importantly, they are not identical to Pearson’s rs and cannot be treated as such.
E.g., they do not rely on the assumption that data has a Gaussian distribution, and the obtained p-
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values were therefore not of interest.) As the purpose was to collect and sample the variation in intraindividual cross-correlations in the sample, it was not interesting to estimate whether the intraindividual cross-correlations themselves were statistically significant.
Next, the CCFs were converted into Fisher zs in order to allow for treating them as values on an interval scale that parametric statistics can be performed on. When scrutinizing the pilot data, it was found that some pilot participants got perfect or nearly perfect cross-correlations because they for example had made a single rating once at the end of the video for both variables instead of rating continuously. It was reasoned that given that participants should have been rating their items continuously second-by-second for around three minutes and could not have made virtually identical time series for two variables even if they tried to. For this reason, Fisher z-coefficients greater than 2.3 or smaller than -2.3 (corresponding to Pearson’s rs of +/- .95) were excluded. (After submitting this research to Cognition & Emotion, one reviewer pointed out that cross-correlations of this magnitude could occur, e.g. if a participant had not felt anything except for at the very end of the video. But, as was considered best practice, the research stuck to the pre-registered exclusion criteria.)
Another issue that was encountered in the pilot data was that some participants got undefined CCFs resulting from not having touched the rating during at least one of the viewings so that at least one variable had zero variability. Participants with such cross-correlations were also excluded. (There was some hesitancy before doing this since it could be argued to be more appropriate to replace the undefined values with .00 since there clearly was no association between the variables in those cases. But we followed the more conservative rationale that there should be variation in both variables for correlation to be meaningful.) In total, 21 participants were excluded from the valence-triad, 40 participants from the sensations-triad, and 8
participants from the appraisals-triad for the two reasons just described. Table 2 shows means and standard deviations for the Fisher z-coefficients by video and cross-correlation.
Table 2
Cross-Correlations Between Time Series in Each Item Triad for Individual Videos and On Average
Triad Cross-Correlation Between Respective Time Series
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Sensations
Moved - Warmth Moved - Goosebumps Warmth - Goosebumps Video M(z) SD(z) CCF M(z) SD(z) CCF M(z) SD(z) CCF N
Thai 0.46 0.43 .43 0.16 0.33 .16 0.18 0.37 .18 45 Abra. 0.48 0.31 .45 0.36 0.35 .34 0.36 0.40 .35 36 Orph. 0.45 0.36 .42 0.27 0.33 .26 0.18 0.31 .18 40 All 0.46 0.37 .43 0.25 0.34 .25 0.23 0.37 .23 121
Appraisals
Moved - Closeness Moved - Morality Closeness – Morality Video M(z) SD(z) CCF M(z) SD(z) CCF M(z) SD(z) CCF N
Thai 0.37 0.50 .36 0.37 0.47 .35 0.45 0.44 .42 43 Abra. 0.45 0.54 .42 0.23 0.46 .23 0.28 0.52 .27 41 Orph. 0.30 0.51 .29 0.33 0.34 .32 0.33 0.41 .32 36 All 0.38 0.52 .36 0.31 0.43 .30 0.36 0.46 .34 120
Valence
Moved - Pos. Affect Moved - Neg. Affect Pos.affect-Neg. affect Video M(z) SD(z) CCF M(z) SD(z) CCF M(z) SD(z) CCF N
Thai 0.53 0.50 .49 -0.20 0.33 -.20 -0.45 0.50 -.42 43 Abra. 0.45 0.59 .42 -0.05 0.47 -.05 -0.13 0.55 -.13 41 Orph. 0.29 0.44 .29 0.04 0.27 .04 -0.17 0.28 -.16 43 All 0.42 0.52 .40 -0.07 0.37 -.07 -0.25 0.48 -.25 127 Note. Video labels in second column: Thai=Thai Medicine, Abra.=Marina Abramovic, Orph=Two Orphans.
Inferential Statistics
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The hypotheses were tested by computing general linear models where the magnitude of the cross-correlations (i.e., their respective Fisher zs) were the dependent variable. For the hypotheses that one cross-correlation was greater than zero, only the zs from that cross- correlation was filtered in, and which video the participants watched was the only predictor (between subjects). The correlation was considered greater than 0 if the model had a positive and significant intercept. For the hypotheses that one cross-correlation would be stronger than
another one, the two cross-correlations were compared within participants, with assigned video as a between participants-factor to explore any differences between the videos. All tests were two-sided.
The results were initially somewhat confusing to work with, and may also be confusing to read, due to the unusual nature of the variables included. A few counterintuitive aspects of the results may be worth clarifying. First, the main effect of video (which video the participant watched) is informative in the tests against zero, but (presumably) not when testing whether two cross-correlations were different from each other. That is because, in the latter case, the
dependent variable includes z-values from both cross-correlations and the main effect of video cannot say anything about the effect on the cross-correlations separately or the difference between them. The interaction effect between video and which cross-correlation was looked at, on the other hand, does describe the effect of video on the difference between the two cross- correlations. For transparency and to follow convention, both the main effect of video and the mentioned interaction effect is reported.
Results
Data are available at https://osf.io/de32v/. Cross-correlations between being moved and the other variables as well as exploratory between subjects cross-correlations (see “exploratory analyses”
below) are summarized in Figure 2.
Confirmatory Analyses
The analyses were unconventional—in particular the tests for difference between two cross- correlations—and the results may therefore be counterintuitive to read. In each confirmatory model, the dependent variable was the magnitude of the Fisher z-transformed cross-correlation
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functions. When comparing two cross-correlations (e.g., between being moved and goosebumps and between being moved and warmth), the independent variable predicted to have an effect is which of the two cross-correlation the z came from. Video was also included as an independent variable to explore whether the difference between the depended on which video the participants watched (i.e., the interaction effect between video and which cross-correlation it was). The main effect of video on the Fisher zs was considered uninformative (in the tests for difference between two cross-correlations) as it is literally the effect of video on the magnitude of the average between the two cross-correlation. Nonetheless, the main effect of video is reported for the sake of transparency and following convention.
Sensations-triad
The average cross-correlation with being moved was CCF = .43 (z = 0.46) for warmth and CCF
= .25 (z = 0.25) for goosebumps. As predicted, both were significantly greater than 0, F(2,118) = 183.94, p < .001 (warmth), F(2,118) = 71.80, p < .001 (goosebumps). The cross-correlation between being moved and warmth did not depend on which video the participants watched, F <
1, but cross-correlation between being moved and goosebumps did, F(2,118) = 3.47, p = .034, being highest for “Marina Abramović”, (M = 0.36) and lowest for “Thai Altruism”, (M = 0.16;
means in of Fisher zs).
As predicted, the difference between the two cross-correlations was also significant, F(5,236) = 19.86, p < .001. There was not a significant interaction between video and which cross-correlation was looked at F(5,236) = 1.94, p = .146, and no main effect of video on the cross-correlations, F(5,236) = 1.23, p = .293.
Appraisals-triad
On average, feeling moved cross-correlated about equally with closeness appraisals, CCF = .36 (z = 0.38) and morality appraisals, CCF = .30 (z = 0.31). As predicted (for closeness) and expected (for morality) both cross-correlation differed significantly from 0, F(2,117) = 61.71, p
< .001 (closeness), F(2,117) = 61.88, p < .001 (morality). Neither cross-correlation depended significantly on the video, F < 1 (closeness), F(2,117) = 1.02, p = .363 (morality; this was a little unexpected as one video was included due to being presumably “not too moral”).
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Contrary to our hypothesis, the two did not differ significantly, F(5,234) = 1.00, p = .318.
Video had no main effect on the cross-correlations, F < 1, and did not interact with which cross- correlation was looked at, F(5,234) = 1.51, p = .223.
Valence-triad
On average, being moved cross-correlated positively with positive affect, CCF = .40 (z = 0.42) and ever so slightly negatively with negative affect, CCF = -.07. (z = -0.07). Despite the small absolute size of the latter, both differed significantly from 0, F(2,124) = 87.03, p < .001 (positive affect), F(2,124) = 4.93, p = .028 (negative affect). The cross-correlation with positive affect did not depend on the video, F(2,124) = 2.35, p = .100, but the cross-correlation with negative affect did, F(2,124) = 4.64, p = .011, being negative and small to medium in “Thai medicine” (M = - 0.20), negative but very small in “Marina Abramovic” (M = -0.05), and positive but also very small in the sad video, “Two Orphans” (M = 0.04).
The difference in between the two cross-correlations was significant, F(5,248) = 79.01, p
< .001. Video had no main main effect of the Fisher z-coefficients, F < 1, but did interact significantly with which of the cross-correlations was looked at, F(5,248) = 6.11, p = .003. The latter is interpreted as meaning that the magnitude of the difference between the two cross- correlations depended on which video that the participants had watched.
Exploratory Analyses
Looking at the results from the confirmatory analyses sparked some additional questions that were further explored. In addition, it was explored whether including gender, age, and viewing order (order of the three viewings within the triad) had any effects in the preregistered models.
Neither of these variables predicted a significant share of the variance in any of the tests.
Following up on Differences Between Videos
The confirmatory analyses indicated that there were two variables—goosebumps and negative feelings—for which their cross-correlation with being moved varied significantly between videos. Six separate one-sample t-tests (one per video per cross-correlation) were conducted to explore whether the results from the confirmatory analyses regarding these two cross-
correlations would also be obtained when looking at the videos separately.
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For being moved and goosebumps, the cross-correlation was particularly small in “Thai- medicine” (M = 0.16, SD = 0.33) compared to “Marina Abramović” (M = 0.36, SD = 0.35) and
“Two Orphans” (M = 0.27, SD = 0.33; results expressed in Fisher z). Yet, it was greater than 0 in each video, “Marina Abramović”: t(35) = 6.09, p < .001; “Two Orphans”: t(39) = 5.06, p < .001;
“Thai Medicine”: t(44) = 3.25, p = .002.
For being moved and negative feelings, “Marina Abramović” had a tiny negative cross- correlation (M = -0.05, SD = 0.47), “Two Orphans” had a tiny positive cross-correlation (M = 0.04, SD = 0.27), and “Thai Medicine” had a somewhat greater negative cross-correlation (M
= -0.20, SD = 0.33). Only the latter one differed significantly from 0, “Marina Abramović”: t(40)
= 0.73, p = .472; “Two Orphans”: t(42) = 0.89, p = .376; “Thai Medicine”: t(42) = 3.97, p <
.001.
Finally, it was also found in the confirmatory analyses that video had an effect on the extent to which being moved had greater cross-correlations with positive affect than with negative affect. To explore whether the difference was nevertheless significant in each video, separate paired to sample t-tests with the two cross-correlations representing the two samples were conducted for each video. The results indicated that the difference withheld in each video,
“Marina Abramović”: t(40) = 5.15, p < .001; “Two Orphans”: t(42) = 3.22, p = .002; “Thai Medicine”: t(42) = 6.59, p < .001, although the difference was much greater in the joyful videos (“Thai Medicine” and “Marina Abramović”) than in the sad video (“Two Orphans”).
Exploratory Mixed Model of Appraisals
The confirmatory analyses found that time series of being moved were equally cross-correlated with both appraisals of closeness and appraisals of morality. In addition, there was a moderate cross-correlation between morality appraisals and closeness appraisals, CCF = .34, showing that sometimes appraisals of closeness and morality co-occur, but sometimes they do not. It could be that closeness appraisals and morality appraisals were about equally cross-correlated with being moved because one could be explained by the other or both could be explained by a third variable. (Seibt et al., 2017, argued that the same two variables both predicted being moved because they are both indicators of communal sharing.) As a final exploratory test, a mixed regression model that folded the steps done in the current correlational analyses into one model and allowed regressing feeling moved simultaneously onto appraisals of closeness and morality