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When Chatting About Negative Experiences Helps-and When It Hurts: Distinguishing Adaptive Versus Maladaptive Social Support in Computer-Mediated Communication


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Does talking to others about negative experiences improve the way people feel? Although some work suggests that the answer to this question is “yes,” other work reveals the opposite. Here we attempt to shed light on this puzzle by examining how people can talk to others about their negative experiences constructively via computer-mediated communication, a platform that people increasingly use to provide and receive social support. Drawing from prior research on meaning-making and self-reflection, we predicted that cueing participants to reconstrue their experience in ways that lead them to focus on it from a broader perspective during a conversation would buffer them against negative affect and enhance their sense of closure compared with cueing them to recount the emotionally arousing details concerning what happened. Results supported this prediction. Content analyses additionally revealed that participants in the reconstrue condition used the word “you” generically (e.g., you cannot always get what you want) more than participants in the recount condition, identifying a linguistic mechanism that supports reconstrual. These findings highlight the psychological processes that distinguish adaptive versus maladaptive ways of talking about negative experiences, particularly in the context of computer-mediated support interactions.
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When Chatting About Negative Experiences Helps—and
When It Hurts: Distinguishing Adaptive Versus
Maladaptive Social Support in Computer-Mediated
David S. Lee, Ariana Orvell, Julia Briskin, Taylor Shrapnell, Susan A. Gelman, Ozlem Ayduk, Oscar
Ybarra, and Ethan Kross
Online First Publication, January 10, 2019.
Lee, D. S., Orvell, A., Briskin, J., Shrapnell, T., Gelman, S. A., Ayduk, O., Ybarra, O., & Kross, E.
(2019, January 10). When Chatting About Negative Experiences Helps—and When It Hurts:
Distinguishing Adaptive Versus Maladaptive Social Support in Computer-Mediated
Communication. Emotion. Advance online publication.
When Chatting About Negative Experiences Helps—and When It Hurts:
Distinguishing Adaptive Versus Maladaptive Social Support in
Computer-Mediated Communication
David S. Lee
University of Michigan, Ann Arbor, and The Ohio State
University, Columbus
Ariana Orvell, Julia Briskin, Taylor Shrapnell,
and Susan A. Gelman
University of Michigan, Ann Arbor
Ozlem Ayduk
University of California, Berkeley Oscar Ybarra and Ethan Kross
University of Michigan, Ann Arbor
Does talking to others about negative experiences improve the way people feel? Although some work
suggests that the answer to this question is “yes,” other work reveals the opposite. Here we attempt to
shed light on this puzzle by examining how people can talk to others about their negative experiences
constructively via computer-mediated communication, a platform that people increasingly use to provide
and receive social support. Drawing from prior research on meaning-making and self-reflection, we
predicted that cueing participants to reconstrue their experience in ways that lead them to focus on it from
a broader perspective during a conversation would buffer them against negative affect and enhance their
sense of closure compared with cueing them to recount the emotionally arousing details concerning what
happened. Results supported this prediction. Content analyses additionally revealed that participants in
the reconstrue condition used the word “you” generically (e.g., you cannot always get what you want)
more than participants in the recount condition, identifying a linguistic mechanism that supports
reconstrual. These findings highlight the psychological processes that distinguish adaptive versus
maladaptive ways of talking about negative experiences, particularly in the context of computer-mediated
support interactions.
Keywords: emotion regulation, coping, meaning-making, social support, computer-mediated communi-
Supplemental materials:
The advent and proliferation of computer-mediated communi-
cation technologies (e.g., text messaging, chat rooms, social me-
dia) has rapidly changed the way people interact. According to a
Pew Research Center survey published in 2018, 68% of all U.S.
adults use at least one social media platform to interact with others,
with about three-quarters of them using it on a daily basis (Smith
& Anderson, 2018). Moreover, teens now report that texting is the
most common way they communicate with their friends (Lenhart,
Smith, Anderson, Duggan, & Perrin, 2015).
Emerging evidence indicates that much of these computer-
mediated communications involve providing and receiving social
support (e.g., Ellison, Steinfield, & Lampe, 2007; Kross et al.,
2013; Oh, Ozkaya, & LaRose, 2014; Park et al., 2016; Valenzuela,
Park, & Kee, 2009; Wright, 2016). For example, one study indi-
cated that 68% of teens receive support from friends through social
media during tough times (Lenhart et al., 2015). Data from the Pew
Internet and American Life Project (Fox, 2011) revealed that
almost one in five adult Internet users in the United States reported
having received support online the last time they had a health
Despite the frequency with which people exchange social sup-
port with others via computer-mediated communication methods,
no studies that we are aware of have examined whether certain
ways of chatting with others via these technologies are more
David S. Lee, Department of Psychology, University of Michigan, Ann
Arbor, and Department of Psychology, The Ohio State University, Colum-
bus; Ariana Orvell, Julia Briskin, Taylor Shrapnell, and Susan A. Gelman,
Department of Psychology, University of Michigan, Ann Arbor; Ozlem
Ayduk, Department of Psychology, University of California, Berkeley;
Oscar Ybarra and Ethan Kross, Department of Psychology, University of
Michigan, Ann Arbor.
David S. Lee, Julia Briskin, Ozlem Ayduk, Oscar Ybarra, and Ethan
Kross conceived and designed the study. David S. Lee, Julia Briskin, and
Taylor Shrapnell performed the study. David S. Lee, Oscar Ybarra, Ethan
Kross, and Ariana Orvell analyzed the data. David S. Lee, Oscar Ybarra,
Ethan Kross, and Ariana Orvell wrote the article. All authors provided
feedback on the final draft.
Correspondence concerning this article should be addressed to David S.
Lee, Department of Psychology, The Ohio State University, Columbus,
1827 Neil Avenue, Columbus, OH 43210. E-mail:
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
© 2019 American Psychological Association 2019, Vol. 1, No. 999, 000
effective at facilitating emotion regulation than others. Addressing
this issue is important, because prior research suggests that it is
possible for people to reflect on negative experiences in different
ways that have direct implications for how they think, feel and
behave (e.g., Gross, 1998; Kross & Ayduk, 2011, 2017; Nolen-
Hoeksema, Wisco, & Lyubomirsky, 2008; Wilson & Gilbert,
2008). In the current research, we build on this work to examine
the processes that facilitate adaptive social support via computer-
mediated communication.
Processes Distinguishing Adaptive Versus Maladaptive
Social Support
Psychologists have long been interested in identifying the pro-
cesses that distinguish adaptive versus maladaptive forms of self-
reflection (e.g., Kross, Ayduk, & Mischel, 2005; Nolen-Hoeksema
et al., 2008; Ochsner & Gross, 2008; Wilson & Gilbert, 2008).
According to one line of work within this research tradition (see
Kross & Ayduk, 2017 for a review), one mechanism that deter-
mines whether self-reflection leads people to feel better or worse
is whether they focus on recounting the emotionally arousing
features of their negative experience or reconstruing their experi-
ence by thinking about it in a broader context that promotes insight
and closure (Kross & Ayduk, 2011, 2017; Rude, Mazzetti, Pal, &
Stauble, 2011; Schartau, Dalgleish, & Dunn, 2009). Specifically,
whereas recounting has been consistently linked with negative
outcomes such as increased negative emotional and physiological
reactivity (Bushman, 2002; Glynn, Christenfeld, & Gerin, 2002;
Kross & Ayduk, 2008), reconstruing has been consistently asso-
ciated with more beneficial outcomes such as improved emotional
and physiological reactivity and enhanced sense of closure (Ayduk
& Kross, 2010; Gross, 1998; Gruber, Harvey, & Johnson, 2009;
Rude et al., 2011; Schartau et al., 2009).
Drawing from this
research, we hypothesized that whether talking to others about
negative experiences is helpful or harmful should depend critically
on whether people recount or reconstrue their negative experi-
ences during their conversations.
Indirect evidence supporting this prediction comes from two
domains. First, research on corumination and the social sharing of
emotion literatures indicate that focusing excessively on discuss-
ing the negative content of one’s experiences (i.e., what happened
and what one felt) perpetuates negative emotional responses (e.g.,
Rimé, 2009; Rose, 2002; Rose, Carlson, & Waller, 2007). How-
ever, this prior work is less clear on how talking to others about
one’s distressing experience can be beneficial. For instance, re-
search on corumination has not examined the ways in which
people can adaptively discuss their negative experience with oth-
ers. Although Nils and Rimé (2012) showed that prompting people
to positively reframe their negative feelings during conversations
is beneficial, the participants discussed their reactions to watching
distressing film clips rather than highly stressful autobiographical
experiences. Thus, whether the benefits of engaging in a
perspective-broadening reconstrual also explain how people can
talk to others adaptively about their negative experiences without
becoming overwhelmed by negative affect has not been explored.
Second, some research has examined the role that cognitive
reappraisal strategies play in interpersonal contexts (e.g., Butler et
al., 2003; Richards, Butler, & Gross, 2003). However, most of
these studies focused on how trying to remain calm and dispas-
sionate or thinking about positive aspects of one’s relationship
compare with expressive suppression or an uninstructed control
condition in terms of its implications for rapport with one’s con-
versation partner (Butler et al., 2003) and what people remember
from their conversations (Richards et al., 2003). Although these
studies have revealed positive effects of cognitive reappraisal
strategies (e.g., willingness to affiliate with conversation partner),
they focus on different reappraisal operations, a different compar-
ison strategy (e.g., expressive suppression), and different outcome
variables from the current work.
Linguistic Trace of Reconstrual
Our second goal was to examine whether we could identify a
linguistic trace of reconstrual in people’s conversations about their
negative experiences. Several recent studies indicate that when
people try to make meaning out of negative events through writing,
they use the word “you” generically to situate their experience in
a context that extends beyond the self and describe it as a more
normative phenomenon that others share (e.g., “In life, you don’t
always get what you want”; Orvell, & Kross, & Gelman, 2017a,
2017b). For example, in one study, Orvell and colleagues (2017a)
found that participants who were instructed to make meaning out
of their negative experience (vs. relive it) used generic-you sig-
nificantly more in their essays, which in turn led them to report
feeling more psychologically distant from their event (Orvell et al.,
2017a). Thus, to the extent that reconstruing negative experiences
involves thinking broadly about one’s experiences from a less
egocentric perspective (i.e., more psychologically distant), we
predicted that cueing participants to reconstrue (vs. recount) their
experience should also lead them to use generic-you more during
their conversations.
Overview of Research
The present research examined how people can talk to others
about their negative experiences constructively in computer-
mediated communication. To do this, we randomly assigned par-
ticipants who recently experienced a negative interpersonal event
to discuss their experience via instant messenger with a confeder-
ate who cued them to either recount or reconstrue their experience.
Afterward, we assessed participants’ negative affect and closure
levels, and content analyzed transcripts of their conversations for
generic-you usage. Based on prior research on self-reflection (e.g.,
Kross & Ayduk, 2011, 2017), we predicted that cueing participants
to reconstrue their experience by focusing on it from a broader
perspective during a conversation would buffer them against neg-
ative affect and enhance their sense of closure compared with
cueing them to recount the emotionally arousing details regarding
what happened. We also hypothesized that cueing participants to
We note that the terms reconstrual, as we define in the current research,
and reappraisal are largely synonymous. Both refer to the concept of
changing the way one thinks about a stimulus, which can be done in
potentially infinite ways. Whereas reconstrual is used more frequently in
social psychology, growing out of the tradition of work on the importance
of “mental construal” (e.g., Kelly, 1955; Mischel, 1973; Mischel & Shoda,
1995; Ross, 1989; Trope & Liberman, 2003, 2010), reappraisal is more
commonly used in the coping and emotion regulation literature (Gross,
1998; Lazarus & Alfert, 1964; Lazarus & Folkman, 1984).
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reconstrue (vs. recount) their experience would lead them to use
generic-you more during their conversations.
Data Collection Overview and Participants
Data collection occurred across two phases (N
Sample 1a
Sample 1b
119). In Sample 1a, we sought to collect as much data
as we could in one semester, with the aim of collecting at least 30
participants per condition. After completing data collection for
Sample 1a, we analyzed the data and determined that more power
was needed to robustly test our predictions. Note that data collec-
tion for these studies occurred during a time of rapidly increasing
power recommendations (e.g., Simmons, Nelson, & Simonsohn,
2011). Thus, despite the fact that we observed significant findings
that were consistent with our predictions in Sample 1a, we erred on
the side of collecting more data with Sample 1b to ensure that we
were not capitalizing on error in a smaller sample. In Sample 1b,
we decided to roughly double data collection during the next
semester (see Murayama, Pekrun, & Fiedler, 2014 for a discussion
advocating this approach). The combined sample included 183
participants (150 females; M
22.39, SD
8.35; 49%
Caucasian, 26% Asian, 14% other, 9% African American, 2%
Because our main goal was to examine the processes involved in
support conversations that promote closure and meaning-making,
it was critical that we only recruit participants who were upset
about an ongoing source of distress. Thus, participants had to (a)
be in the midst of experiencing an ongoing conflict with another
person, (b) still be upset about it, and (c) be willing to talk about
it to qualify for inclusion in the study. Participants were compen-
sated $10. The University of Michigan Institutional Review Board
approved this study.
Procedure and Materials
Overview of procedure. One experimenter (the Facilitator),
blind to participants’ condition and the study hypotheses, guided
participants through the experiment. A second experimenter (the
Support-provider), blind to the study hypotheses, talked to partic-
ipants about their experience via an online instant messenger.
Phase 1: Baseline affect. After providing consent, partici-
pants responded to the following question, “How do you feel right
now?” usinga0(very bad) to 100 (very good) scale (M67.54,
SD 18.87).
Phase 2: Getting-acquainted session. Next, the Support-
provider initiated an “ice-breaking” conversation for 5 min (Yba-
rra et al., 2008) to help participants feel comfortable. The Support-
provider asked scripted questions (e.g., “How is your summer
going?”) and provided standardized responses (e.g., “That sounds
Phase 3: Manipulation. After the icebreaker, the Support-
provider transitioned to talking about the participant’s experience.
Participants were told: “Could you briefly tell me about [the
experience]? What happened? Who did it involve?” Pilot work
indicated that these “warm-up” questions were necessary to facil-
itate natural exchanges. In additon, two judges coded the response
to confirm that the emotional intensity of participants’ events (␣⫽
.93) did not differ across conditions usinga1(a little)to3(very)
After asking the above questions, the experimental manipulation
was administered. In the recount condition (N92), the Support-
provider asked five standardized questions that prompted partici-
pants to talk about what happened to them and what they felt
during their experience. In the reconstrue condition (N91),
participants were asked five standardized questions that prompted
them to focus on their experience from a broader perspective (see
Appendix for verbatim questions). The Support-provider followed
a standardized script to ensure that participants in each condition
were asked the same questions. These questions were theoretically
derived based on prior research that has carefully operationalized
these constructs (e.g., Kross & Ayduk, 2017). When asking these
questions, the Support-provider was instructed to acknowledge
participants’ situation with a standardized response (e.g., “I’m
sorry to hear that”) but not to provide any further feedback to
ensure that participants within each group received the same
To ensure that participants could respond to all questions, no
time limit was imposed (M
30.58, SD
Conversation length did not differ by condition (p.57). At the
end of the conversation, the Support-provider sent participants a
Web link to our dependent measures.
Phase 4: DVs.
Postconversation affect. Immediately following their conver-
sation, participants once again rated how they felt in that moment
by answering the question, “How do you feel right now?” using a
0(very bad) to 100 (very good) scale. We reverse-scored this item
(M38.52, SD 20.93) and standardized it along with the
negative affect items to create a single negative affect index (␣⫽
.61). Participants also rated how upset they felt (M4.84, SD
1.46) and how intense their emotions and physical reactions were
during the conversation (M4.27, SD 1.63), ona1(strongly
disagree)to7(strongly agree) scale.
Closure. Next, participants responded to “As I was talking to
the research assistant about the event, I had a realization that led
me to experience a sense of closure,” ona1(strongly disagree)to
7(strongly agree) scale (M4.11, SD 1.66).
Content analyses. We coded participant’s conversations for
three types of information.
First, three judges coded participants’ portion of the conversa-
tion on the extent to which it contained recounting- (␣⫽.77; M
1.94, SD .73) and reconstruing (␣⫽.83; M.53, SD .59)
statements usinga0(not at all)to3(very much) scale, following
protocols used in prior research (Ayduk & Kross, 2010).
Second, two judges counted the number of times participants
used the word “you” generically following Orvell and colleagues
(2017a, 2017b). Discrepancies were resolved by a third coder (␣⫽
.99); generic-you tallies were converted to percent scores out of the
total word count.
Finally, to rule out the possibility that Support-providers were
more supportive to participants in one condition than the other, two
judges coded Support-provider’s utterances on the extent to which
they reflected supportiveness (␣⫽.94) ona0(not at all)to2
(very) scale.
Covariates. Because how much participants like the support-
provider can influence support outcomes (e.g., therapeutic alli-
ance; Martin, Garske, & Davis, 2000), we asked participants to
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rate “how much they liked” and “how close they felt” to the
Support-provider using 1 (not at all)to7(very much) scales (␣⫽
.78; M4.83, SD 1.28).
Analyses Overview
The two samples we collected had identical aims and core
In addition, sample did not moderate any results (all
ps.34), and controlling for it did not substantively alter any
results. Analyzing the data as separate versus combined samples
yielded the same pattern of results. Thus, we combined them to
enhance power and parsimony. Table 1 provides statistics for each
subsample analyses, the combined analysis, and an internal meta-
analysis of data from the two samples (see Braver, Thoemmes, &
Rosenthal, 2014; Maner, 2014).
We excluded seven participants (four reconstrue participants)
because of a computer malfunction (one), scheduling conflicts
(three), prior relationship with the Facilitator (one), low English
proficiency (one), and not following instructions (one). This left
176 participants. Including these participants did not substantively
alter the results. Table 1 presents all descriptive and inferential
Preliminary Analyses
Coders’ ratings of the emotional intensity of participants’ events
did not differ by condition, F(1, 173) .22, p.64. Moreover,
across conditions participants rated their Support-providers as
equally likable, F(1, 174) .42, p.52 and Support-providers’
utterances were rated by coders as equally supportive, F(1, 173)
.83, p.36. None of these variables moderated any of the results
(ps.51), and controlling for them did not substantively alter any
of the findings. Table 2 presents partial correlations among all key
variables (controlling for baseline affect).
Manipulation Check
Content analyses confirmed that our manipulation was effective:
Participants in the recount (vs. reconstrue) condition recounted
more (Ms2.73 vs. 1.98, SDs.38 vs. .70), F(1, 170) 75.51,
p.0001, and reconstrued less (Ms.25 vs. 1.39, SDs.41 vs.
.77), F(1, 170) 89.91, p.0001 during the conversation.
Primary Analyses
A 2 (Condition: Recount vs. Reconstrue) 2 (Time of State
Affect Assessment (i.e., “How do you feel right now?”) repeated-
measures analysis of variance (ANOVA) revealed a significant
Condition Time interaction, F(1, 173) 14.39, p.001, ␩␳
.077, indicating that participants in the recount condition felt
significantly worse after talking about their experience compared
with how they felt before the conversation, t(173) 4.91, p
.001, 95% confidence interval (CI) [5.63, 13.19], d.48. In
contrast, participants in the reconstrue condition were buffered
against experiencing increased negative affect after talking about
their experience, t(173) .47, p.64 (Figure 1).
Next, we performed a series of analyses of covariance (ANCO-
VAs; controlling for baseline affect) on the closure and additional
negative affect items. The results revealed that participants in the
reconstrue condition scored lower on the negative affect index and
higher on closure.
Finally, as expected, participants in the reconstrue condition
used generic-you more than participants in the recount condition.
Generic-you use was not significantly correlated with any of the
affect measures or closure, ps.25.
The present research examined how people can talk to others
about their negative experiences constructively during computer-
mediated supportive interactions. It generated two key findings.
First, participants who recounted their negative experience while
chatting with a confederate on instant messenger experienced a
significant increase in negative affect compared with baseline. In
contrast, participants who reconstrued their experience during their
instant messenger conversations were buffered against this in-
crease in negative affect despite spending just as much time talking
about their negative experience as recounting participants. They
also reported having more closure. These findings are consistent
with research indicating that venting negative experiences during
an offline social interaction exacerbates distress (Nils & Rimé,
2012; Rose, 2002) whereas reconstruing negative events during
self-refection facilitates successful emotion regulation (Kross &
Ayduk, 2017). Broadly, they suggest that a common set of mech-
anisms may underlie how people self-reflect on negative experi-
ences and how they talk about them with others in computer-
mediated communication.
Second, we found that reconstruing participants spontaneously
used the word “you” generically more in their conversations than
recounting participants. This is noteworthy because prior research
indicates that generic-you serves as a linguistic marker for making
meaning (Orvell et al., 2017a, 2017b). Thus, these findings provide
converging evidence across an additional level of analysis indicat-
ing that reconstruing one’s experience during conversations helps
people make meaning out of their negative experiences. To our
knowledge, this is the first study to demonstrate how generic-you
functions in an interpersonal context, and thus may have important
implications for therapy. For example, clinicians and support-
providers could attend to people’s generic-you usage during con-
versations as a signal for whether they are effectively creating
meaning from a negative experience.
The two samples differed only in their exploratory scope. In Sample
1a, we collected exploratory data to examine how people felt one day after
the experiment. Because there were no reliable effects, we did not collect
these data in Sample 1b. In Sample 1b, we assessed participants’ preferred
coping strategy one week before the experiment to explore its impact on
coping (see online supplemental material for all exploratory measures and
We computed a negative affect composite index on a priori grounds
following prior work (Ayduk & Kross, 2010). However, because of its
moderate reliability (␣⫽.61), we also analyzed each item of this index
individually. These analyses revealed that the effects of condition were
significant on post-conversation affect (p.001), marginally significant
on upset feelings (p.07), and nonsignificant on affect intensity (p
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Importantly, the present research provides insight into how
effective social support can occur in nonface to face contexts—a
rapidly increasing context in which people give and receive sup-
port (Kross, 2017; Morris, Schueller, & Picard, 2015; Park et al.,
2016; Wright, 2016). To our knowledge, this is the first study to
examine how people can guide others to adaptively make sense of
their negative experience during online conversations.
Although support interactions that occur in computer-mediated
communications are devoid of nonverbal cues that can contribute
to successful support outcomes (e.g., touch; Jakubiak & Feeney,
2017), a growing number of studies corroborate the effectiveness
of remote interactions, including cognitive behavior therapy online
(e.g., Kessler et al., 2009) and online peer-to-peer platform inter-
actions (e.g., Morris et al., 2015). Given how frequently people
interact with others online and the various advantages that online
interactions can offer (e.g., increased accessibility to a wider range
of people across time and space, privacy, buffer against potential
stigma), we encourage scholars to further investigate this emerging
topic in future research. Such investigation seems timely given the
rapidly growing popularity of online therapy, and discussions
surrounding its effectiveness (e.g., Cohen & Kerr, 1999; Kessler et
al., 2009; Reynolds, Stiles, Bailer, & Hughes, 2013; Wagner,
Horn, & Maercker, 2014).
Our findings importantly also have implications for offline
social support interactions. Although people often talk to others
about their negative experiences (Rimé, 2009), whether this actu-
Table 1
Means, SDs, F Values (or Mann-Whitney U), Significant Levels for Univariate Analyses of Covariance (ANCOVAs)
statistics Internal
Recount Reconstrue F(or U)df p
295% CI Z95% CI
Recounting statements
Combined 2.73 (.38) 1.98 (.70) 75.51
170 .31 [.58, .92] 7.83
[1.00, 1.67]
Sample 1a 2.72 (.30) 2.43 (.52) 6.64
57 .10 [.06, .51]
Sample 1b 2.74 (.42) 1.73 (.67) 89.91
110 .45 [.79, 1.21]
Reconstruing statements
Combined .25 (.41) 1.39 (.77) 149.27
170 .47 [1.33, .96] 10.30
[1.54, 2.26]
Sample 1a .25 (.47) 1.22 (.82) 29.50
57 .34 [1.31, .61]
Sample 1b .25 (.39) 1.48 (.74) 134.82
110 .55 [1.48, 1.05]
Change in negative affect (postconversation
minus baseline)
Combined 9.41 (17.68) .90 (18.26) 15.84
172 .08 [5.00, 14.83] 3.97
[.31, .92]
Sample 1a 7.57 (19.32) .94 (16.06) 4.47
58 .07 [.46, 17.10]
Sample 1b 10.36 (16.87) 1.91 (19.43) 11.58
111 .09 [4.51, 17.08]
Negative affect composite
Combined .10 (.71) .10 (.73) 8.26
172 .05 [.06, .34] 7.18
[.20, .35]
Sample 1a .11 (.67) .13 (.67) 4.26
58 .07 [.01, .47]
Sample 1b .10 (.73) .08 (.76) 4.13
111 .04 [.004, .35]
Combined 3.77 (1.71) 4.46 (1.51) 8.68
172 .05 [1.18, .23] 3.06
[.17, .77]
Sample 1a 3.53 (1.63) 4.48 (1.46) 5.26
58 .08 [1.73, .12]
Sample 1b 3.90 (1.75) 4.45 (1.55) 4.53
111 .04 [1.24, .04]
Generic-you usage (percentage)
Combined .06 (.20) .33 (.63) U2926
170 .08 [.004, .001] 3.83
[.29, .90]
Sample 1a .02 (.07) .37 (.78) U313
57 .09 [.006, .001]
Sample 1b .09 (.24) .31 (.53) U1299.50
110 .30 [.004, .001]
Note.CIconfidence interval. Degrees of freedom vary because conversation data of two participants did not get recorded and because of one missing
value in the baseline mood measure.
Table 2
Partial Correlations (Controlling for Baseline Affect) for All Key Variables
Variables 12345678
1. Recounting statements
2. Reconstruing statements .40
3. Negative affect composite index .11 .21
4. Change in negative affect over time .14
5. Upset feelings .01 .25
6. Intense feelings .04 .01 .81
7. Closure .09 .29
.04 —
8. Generic-you usage (percentage) .16
.04 .10 .08 .03 .08 —
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ally helps them feel better remains unclear: Some studies suggest
talking to others to be beneficial (Frattaroli, 2006; Thoits, 1986)
while others have found the opposite (Nils & Rimé, 2012; Rose,
2002). Surely, discussing “what happened” is natural in support
conversations and may even be necessary to establish a context for
support provision to take place. However, our results suggest that
once this context is established, support providers should shift to
cueing support recipients to reconstrue their experience to prevent
negative affect from escalating (Rose, 2002). Thus, the current
findings also extend work on corumination by identifying a po-
tential way in which conversations can be structured to prevent
rumination and foster meaning-making.
Finally, the current findings contribute to research on emotion
regulation. Although cognitive reappraisal is largely considered to
be one of the most effective emotion regulation strategies (Gross,
2015), there are infinite ways in which people can engage in
reappraisal (e.g., positive reinterpretation, incremental mindset). A
growing number of scholars in recent years have proposed the
need to distinguish the different types of reappraisal processes
(e.g., Gross, 2015; Kross, 2015; Moser, Hartwig, Moran, Jen-
drusina, & Kross, 2014; Shiota & Levenson, 2009). The current
work addresses this issue by demonstrating how a specific type of
cognitive reappraisal process (i.e., perspective broadening) influ-
ences people’s capacity to make sense of their negative personal
experiences in an ecologically valid interpersonal context.
It is important to acknowledge that our study used confederates
to cue participants to recount or reconstrue their negative experi-
ence. This approach allowed us to reduce several sources of noise
that could have influenced the conversation outcomes—for exam-
ple, relationship-specific factors (e.g., closeness, expectations),
nonverbal feedback (e.g., tone of voice, nodding). However, given
that support outcomes are shaped by the dynamic interchange
between support recipients and support providers, future research
should examine how our findings generalize to spontaneous sup-
port interactions among dyads in daily life. In this vein, one
interesting direction for future research is to examine the implica-
tion of facilitating reconstrual for the support provider (Doré,
Morris, Burr, Picard, & Ochsner, 2017).
It is important to comment on the lack of correlations between
generic-you usage with negative affect and closure in this study.
These nonsignificant correlations are consistent with findings from
prior research, which likewise failed to find direct effects of
generic-you on negative affect and closure. Instead, prior work
revealed an indirect effect of generic-you usage on reduced neg-
ative affect and enhanced closure—generic-you predicted in-
creased levels of psychological distance which in turn predicted
less negative affect and higher levels of closure (Orvell et al.,
2017a). Although researchers agree that direct effects are not
required to establish indirect effects (Hayes, 2009; Rucker,
Preacher, Tormala, & Petty, 2011; Shrout & Bolger, 2002; Zhao,
Lynch, & Chen, 2010), an important question for future research is
to identify why generic-you does not influence affect and closure
Finally, given the low number of male participants in this study,
future research should seek to test whether our findings generalize
to diverse samples of individuals (McRae, Ochsner, Mauss, Ga-
brieli, & Gross, 2008). Future research should also examine po-
tential boundary conditions (e.g., self-esteem, habitual emotion
regulation patterns) to determine when and to whom cueing re-
construal is beneficial.
People often talk to others about their negative experiences, and
increasingly more so using computer-mediated communication
technologies. However, does talking to others in these modalities
help them make sense of their negative experiences? The present
research suggests that it depends on whether the conversation
allows people to reconstrue or recount their experience, and that
the same processes that help people to adaptively self-reflect on
their negative experience may also apply to when they talk to
others about it via computer mediated communication.
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reverse-scored so that higher scores on this scale reflect more negative
affect. Error bars indicate SEs.
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List of Questions Asked by Confederate While Discussing Distressing Personal Experience
Condition Questions
Recount 1. Can you tell me about what happened—what happened and what did you feel—from start to finish?
2. What went through your mind during the exact moment?
3. What stuck out the most at that moment?
4. What did (he/she/they) say and do?
5. How did this make you feel at that moment?
Reconstrue 1. Looking at the situation, could you tell me why this event was stressful to you?
2. Why do you think you reacted to (the event/the person) that way?
3. Why do you think (the other person in your experience) react that way?
4. Have you learned anything from this experience, and if so, would you mind sharing it with me?
5. In the grand scheme of things, if you look at the “big picture,” does that help you make sense of this experience? Why or why not?
Received August 28, 2017
Revision received October 2, 2018
Accepted October 19, 2018
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... The COVID-19 pandemic propelled billions of conversations that would otherwise have taken place face-to-face into remote meetings. Information and communication technologies (ICT), such as e-mail, Microsoft Teams, Zoom, and Ding Talk, are ubiquitous in the contemporary remote working environment [1]. Despite its positive potential that facilitates widespread and rapid information sharing and communications between employees at any time [2], the communication demands from ICT are continually increasing and oftentimes on any given day, possibly triggered by specific communication episodes of that day, due to the time-bound nature of remote communication episodes [10]. ...
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Overwhelming remote communication episodes have become critical daily work demands for employees. On the basis of affective event theory, this study explores the effect of daily remote communication autonomy on positive affect and proactive work behaviors. We conducted a multilevel path analysis using a general survey, followed by experience sampling methodology, with a sample of 80 employees in China who completed surveys thrice daily over a two-week period. The results showed that daily remote communication autonomy increased positive affective reactions, which, in turn, enhanced proactive work behaviors on the same workday. Furthermore, positive day-level relationships leading to employee proactivity were only significant when the employees’ person-level general techno-workload was not high. The findings provide a new perspective for managing employees working under continuous techno-workload and demands for remote interactions.
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Purpose Although the concept of transformative gamification is mentioned in previous research, no research has provided a theoretically based explanation of how gamification can lead to transformative change. This paper aims to provide the explanation for the first time by combining storytelling elements with cognitive behavioural therapy logic and incorporating these into a framework to show the process of transformative behaviour change through gamification. The proposed framework not only furthers the theoretical understanding of transformative gamification services but also provides practical insight into design and implication of such services. Design/methodology/approach This paper is based on critical analysis and synthesis of literature from different fields of research such as transformative service research (TSR), gamification, game studies, social marketing, storytelling and journalism. Ergo, several propositions based on the extensive literature review are proposed and aggregated in a conceptual framework. Findings This paper argues that apart from game mechanics that are often considered as an inseparable aspect of gamification services, immersive storytelling and a mechanism to encourage reflection are the pivotal components of transformative gamification services. In addition, this paper suggests that although reflection and immersive storytelling are often considered as opposite sides of the spectrum, they can have a synergistic effect once they work in tandem in gamification services. Originality/value This paper proposes a novel framework and an operational definition for transformative gamification services. It contributes to TSR, gamification and health promotion research through differentiating this concept from similar concepts, such as mHealth, propelling gamification to a more meaningful and user-centric version and providing service researchers with a practical guide to make use of gamification as a tool to serve TSR.
... For example, Pennebaker (1995) and Niederhoffer and Pennebaker (2009) found that simply speaking has benefits for mental health (see also Ware et al., 2004 for a similar finding with mental health interventions). Speaking and listening are also included in the literature on social support (e.g., Lee et al., 2019), peer support (e.g., MacLellan et al., 2015;Mancini, 2019) and professional interventions (e.g., Gilburt et al., 2008). As such, it would seem essential for this element to be included among the mechanisms of social support. ...
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Objectives: To explore pediatric residents’ perspectives on humanism and how residency impacts humanism formation. Methods: We conducted a qualitative study with pediatric resident focus groups at Stanford. Transcripts were analyzed by two investigators using grounded theory. Subsequent literature review led us to adapt Cruess et al. 2015’s professional identity formation framework to describe development of a humanism identity in residency. Member check was done to verify themes and the adapted framework. Results: 32 pediatric residents participated. Five themes emerged: 1) Empathy, compassion, and respect are foundational elements of humanism. 2) Each resident had a unique view of humanism derived from personal values. 3) Residents felt that the terms excellence and resilience (Gold Foundation IECARES model) did not fit with their own definitions. 4) Residents felt that humanism is a central part of their practice and training. 5) The demands, structure, and culture of residency were often in conflict with promoting humanism in residents. Based on residents' perspectives, we modified the professional identity formation and socialization conceptual framework proposed by Cruess et al. 2015 to reflect humanism identity formation during pediatrics residency. The new framework emphasizes the increased power of the healthcare system and unconscious acquisition on humanism formation in residency as compared to medical school. Conclusions: Residents believe that humanism is a core part of practicing medicine and should be reinforced during residency training. Cruess' professional identity and socialization framework is a tool for a better understanding of the complexity of humanism development in residency.
Shortly before my wife, Lara, gave birth to our first child, we went through a parental rite of passage: baby boot camp. For a full day, we sat in an auditorium with other (mostly) excited soon-to-be parents, listening intently to experts teach us how to change diapers, warm bottles, and swaddle babies. Shortly before the session ended, the speaker turned to the topic of managing our emotions and the chatter in our heads. The first few months of parenthood will have lows, not just highs, the instructor cautioned. One piece of advice she offered for dealing with these difficulties? Vent. Reach out to your spouse or a friend, she said, and release your feelings.
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Do conversations end when people want them to? Surprisingly, behavioral science provides no answer to this fundamental question about the most ubiquitous of all human social activities. In two studies of 932 conversations, we asked conversants to report when they had wanted a conversation to end and to estimate when their partner (who was an intimate in Study 1 and a stranger in Study 2) had wanted it to end. Results showed that conversations almost never ended when both conversants wanted them to and rarely ended when even one conversant wanted them to and that the average discrepancy between desired and actual durations was roughly half the duration of the conversation. Conver-sants had little idea when their partners wanted to end and underestimated how discrepant their partners' desires were from their own. These studies suggest that ending conversations is a classic "coordination problem" that humans are unable to solve because doing so requires information that they normally keep from each other. As a result, most conversations appear to end when no one wants them to. conversation | social interaction | social judgment
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Although much research considers how individuals manage their own emotions, less is known about the emotional benefits of regulating the emotions of others. We examined this topic in a 3-week study of an online platform providing training and practice in the social regulation of emotion. We found that participants who engaged more by helping others (vs. sharing and receiving support for their own problems) showed greater decreases in depression, mediated by increased use of reappraisal in daily life. Moreover, social regulation messages with more other-focused language (i.e., second-person pronouns) were (a) more likely to elicit expressions of gratitude from recipients and (b) predictive of increased use of reappraisal over time for message composers, suggesting perspective-taking enhances the benefits of practicing social regulation. These findings unpack potential mechanisms of socially oriented training in emotion regulation and suggest that by helping others regulate, we may enhance our own regulatory skills and emotional well-being.
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The current crisis in scientific psychology about whether our findings are irreproducible was presaged years ago by Tversky and Kahneman (1971), who noted that even sophisticated researchers believe in the fallacious Law of Small Numbers-erroneous intuitions about how imprecisely sample data reflect population phenomena. Combined with the low power of most current work, this often leads to the use of misleading criteria about whether an effect has replicated. Rosenthal (1990) suggested more appropriate criteria, here labeled the continuously cumulating meta-analytic (CCMA) approach. For example, a CCMA analysis on a replication attempt that does not reach significance might nonetheless provide more, not less, evidence that the effect is real. Alternatively, measures of heterogeneity might show that two studies that differ in whether they are significant might have only trivially different effect sizes. We present a nontechnical introduction to the CCMA framework (referencing relevant software), and then explain how it can be used to address aspects of replicability or more generally to assess quantitative evidence from numerous studies. We then present some examples and simulation results using the CCMA approach that show how the combination of evidence can yield improved results over the consideration of single studies. © The Author(s) 2014.
Is psychology headed in the right direction? In this essay, I share my views on the answer to this question. I begin by describing how recent advances in technology, heightened levels of interdisciplinary collaboration, a renewed emphasis on considering the broader implications of basic psychological research, and field-wide efforts to encourage optimal research practices have combined to tilt psychology’s trajectory upward. I then offer three suggestions for how to maintain the field’s upward slanting course: (a) collaborate more to build cumulative knowledge, (b) improve the way we communicate contextual factors in psychological research, and (c) examine the psychological effects of technology. I conclude by offering a single piece of advice for new researchers and a few closing comments.
Prior research indicates that children construe norms as general and construe preferences as individual. The current studies tested whether this expectation is built into how children interpret and use language. We focused on the pronoun you, which is ambiguous between a canonical interpretation (referring to the addressee) and a generic interpretation (referring to people in general). In Study 1, children (N = 132, ages 3–10 years) were asked a series of questions containing “you,” referring to either descriptive norms (e.g., “What do you do with bikes?”) or preferences (e.g., “What do you like to do with bikes?”). In Study 2, parents conversed with their children (N = 28, ages 2–4 years) about prescriptive norms (e.g., “What should you do with books?”) and preferences (e.g., “What do you like about books?”). In both studies, children’s choice of pronoun in their answer revealed whether they interpreted you in the questions as generic or canonical. Results indicated that children more often interpreted you as generic in the normative contexts (i.e., responded with generic you, e.g., “You read them”) and as canonical in the preference contexts (i.e., responded with I, e.g., “I read them”). This pattern emerged by early preschool, providing the first evidence that the distinction between norms and preferences directs young children’s interpretation and use of everyday language.
“You” is one of the most common words in the English language. Although it typically refers to the person addressed (“How are you?”), “you” is also used to make timeless statements about people in general (“You win some, you lose some.”). Here, we demonstrate that this ubiquitous but understudied linguistic device, known as “generic-you,” has important implications for how people derive meaning from experience. Across six experiments, we found that generic-you is used to express norms in both ordinary and emotional contexts and that producing generic-you when reflecting on negative experiences allows people to “normalize” their experience by extending it beyond the self. In this way, a simple linguistic device serves a powerful meaning-making function.
This manuscript discusses the development, impact, and several major research findings of studies in the area of social network support and health outcomes. The review focuses largely on the development of online social support networks and the ways in which they may interact with face-to-face support networks to influence physical and psychological health outcomes. The manuscript discusses this area, and it presents a research agenda for future work in this area from an Associate Editor’s perspective.
Throughout the life span, individuals engage in affectionate touch with close others. Touch receipt promotes well-being in infancy, but the impacts of touch in adult close relationships have been largely unexplored. In this article, we propose that affectionate touch receipt promotes relational, psychological, and physical well-being in adulthood, and we present a theoretical mechanistic model to explain why affectionate touch may promote these outcomes. The model includes pathways through which touch could affect well-being by reducing stress and by promoting well-being independent of stress. Specifically, two immediate outcomes of affectionate touch receipt—relational-cognitive changes and neurobiological changes—are described as important mechanisms underlying the effects of affectionate touch on well-being. We also review and evaluate the existing research linking affectionate touch to well-being in adulthood and propose an agenda to advance research in this area. This theoretical perspective provides a foundation for future work on touch in adult close relationships.
One of the fastest growing areas within psychology is the field of emotion regulation. However, enthusiasm for this topic continues to outstrip conceptual clarity, and there remains considerable uncertainty as to what is even meant by “emotion regulation.” The goal of this review is to examine the current status and future prospects of this rapidly growing field. In the first section, I define emotion and emotion regulation and distinguish both from related constructs. In the second section, I use the process model of emotion regulation to selectively review evidence that different regulation strategies have different consequences. In the third section, I introduce the extended process model of emotion regulation; this model considers emotion regulation to be one type of valuation, and distinguishes three emotion regulation stages (identification, selection, implementation). In the final section, I consider five key growth points for the field of emotion regulation.