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Clinical Psychological Science
2016, Vol. 4(3) 401 –417
© The Author(s) 2015
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DOI: 10.1177/2167702615601001
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Empirical Article
Could the acute stress of a traumatic event actually pro-
mote psychological health? Previous research has focused
almost exclusively on the potential of traumatic experi-
ences to initiate a process of posttraumatic growth
(Tedeschi & Calhoun, 2004). However, the possibility that
people can experience psychological improvement—a
reduction in preexisting distress—as a direct conse-
quence of a traumatic event has been ignored, perhaps
understandably. Indeed, on its face, the prospect seems
absurd. Yet a growing literature has documented that
stressful experiences, as well as painful ones, promote
various beneficial social outcomes. For example, induc-
ing stress in a laboratory increases trust, trustworthiness,
and sharing behavior (von Dawans, Fischbacher,
Kirschbaum, Fehr, & Heinrichs, 2012) and also improves
social cognition (Smeets, Dziobek, & Wolf, 2009).
Furthermore, painful experiences, when shared with oth-
ers, can serve as “social glue,” prompting a greater sense
of solidarity and bonding (Bastian, Jetten, & Ferris, 2014).
These controlled laboratory experiments dovetail with a
considerable literature on the aftermath of mass traumas.
After such events, there is a collective and immediate
outpouring of support, both emotional and material, to
help survivors cope with the disaster (Norris etal., 2002;
Solnit, 2009). These effects, well documented in the his-
torical and sociological literatures, have been variously
described as a “post-disaster utopia” (Wolfenstein, 1957),
“a paradise built in hell” (Solnit, 2009), and a “city of
comrades” (Prince, 1920). Consistent with laboratory
research, postdisaster communities have been character-
ized by a high degree of internal solidarity, an increase in
601001CPXXXX10.1177/2167702615601001Mancini et al.Social Support, Improvement, and Virginia Tech
research-article2015
Corresponding Author:
Anthony D. Mancini, Pace University, Department of Psychology, 861
Bedford Rd., Marks Hall, Rm. 33, Pleasantville, NY 10570
E-mail: amancini@pace.edu
Can People Benefit From Acute Stress?
Social Support, Psychological
Improvement, and Resilience After the
Virginia Tech Campus Shootings
Anthony D. Mancini1, Heather L. Littleton2, and
Amie E. Grills3
1Pace University; 2East Carolina University; and 3Boston University
Abstract
People’s responses to acute stress are largely thought to comprise four prototypical patterns of resilience, gradual
recovery, chronic distress, and delayed distress. Here we present evidence of an additional response pattern:
psychological improvement. Female survivors of the Virginia Tech shootings (N = 368) completed assessments before
the shootings and at 2, 6, and 12 months post-shooting. Latent growth mixture modeling revealed distinct trajectories
of resilience, chronic distress, delayed distress, continuous distress, and improvement. Although resilience was the
most common pattern (56%–59%), a trajectory of substantial improvement in anxiety and depression symptoms also
emerged among 13.2% and 7.4% of the sample, respectively. In support of this pattern, improvement was distinctively
associated with marked increases in perceived social support and gains in interpersonal resources. Findings suggest
a more complex understanding of the impact of mass trauma and a key role for dynamic changes in social support
following acute stress.
Keywords
trauma, improvement, social processes, latent growth mixture models, resilience
Received 3/19/15; Revision accepted 7/22/15
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402 Mancini et al.
helping behaviors, and a reduction in conflict among sur-
vivors (Solnit, 2009).
Strengthened social relationships are a key resource in
times of acute stress. Indeed, the perceived absence of
supportive relationships is one of the strongest predictors
of posttraumatic stress disorder (Brewin, Andrews, &
Valentine, 2000). Perceptions of support appear to dimin-
ish the sense of threat following a potentially traumatic
event, protecting against depression, anxiety, and post-
traumatic stress disorder symptoms (Charuvastra &
Cloitre, 2008). However, in addition to buffering the
effects of stressful events, strong social relationships are
directly associated with well-being (Argyle, 2001; Diener
& Seligman, 2002). For example, using the present data,
we have previously reported that supportive social rela-
tionships, measured prior to a traumatic event, predicted
anxiety and quality of life following exposure to the
trauma (Grills-Taquechel, Littleton, & Axsom, 2011).
However, the influence of positive changes in social sup-
port that occur in response to a traumatic event has not
been well explored. That is, social support may not only
protect people from pathological reactions to stressful
events but also may exert positive effects on well-being
through improved social relationships. If this is the case,
then the prosocial effects of an acute stressor may, in
some cases, result in improved psychological function-
ing. Although this possibility has been advanced previ-
ously (e.g., Updegraff & Taylor, 2000), psychological
improvement has been substantially neglected as a pos-
sible outcome; almost no previous investigations have
examined it directly using prospective (pre-event) data.
Methodological Issues
There are at least two key reasons for the neglect of
improvement as a possible response to acute stress. The
first is that to document improvement, researchers must
assess exposed persons before the acute stressor occurs.
However, such pre-event assessments are rare in trauma
research, and the considerable majority of prior research
is instead based on data collected after a traumatic event
has occurred. This is problematic for a number of rea-
sons. In the absence of pre-event assessments, it is impos-
sible to determine the precise impact of a mass trauma or
other acute stressor on people’s functioning. For exam-
ple, although the most common reaction to mass trauma
is a resilient one (Bonanno, Brewin, Kaniasty, & La Greca,
2010), it is possible that some people who appear resil-
ient have actually seen improvements in their functioning
as a result of the acute stressor and are thus not properly
described as resilient. Although improvement seems con-
tradictory to our understanding of traumatic events, it
cannot be logically excluded without pre-event data.
A second key factor is that the vast majority of prior
research has focused on the average response to acute
stress, and, on average, people will experience an
increase in distress following a traumatic event (Bonanno
etal., 2010). As a result, the possibility of improvement or
of other responses will necessarily be obscured in studies
that examine average longitudinal responses to acute
stress (Bonanno & Mancini, 2012). Until recently, the
capacity to address this shortcoming was limited. Early
efforts to distinguish longitudinal patterns of adjustment
relied on rudimentary statistical techniques (e.g., arbi-
trary cut points to distinguish one pattern from another).
However, the development and growing use of methods
such as latent growth mixture modeling, which identifies
patterns of change based on distributional properties and
empirical criteria (Muthén, 2004), has stimulated a wealth
of research on distinct trajectories of adjustment after
exposure to acute stress (Bonanno, Westphal, & Mancini,
2011).
Prior Evidence of Improved
Functioning After Acute Stress
Using these new techniques and leveraging data col-
lected before the marker event, researchers have, in fact,
documented improvement, particularly among military
samples. It is interesting that these improvement patterns
have been neglected by the researchers themselves, often
relegated to a few sentences in the discussion section of
the article or ignored entirely (Mancini, 2014). For exam-
ple, in a study of U.S. military personnel deployed to
Kosovo, Dickstein and colleagues identified a group of
soldiers with high levels of posttraumatic stress disorder
symptoms before deployment and a sharp reduction dur-
ing and after their deployment (Dickstein, Suvak, Litz, &
Adler, 2010). They described this pattern, which charac-
terized 9% of the sample, as “unrealized anxiety” and
considered it a reflection of a “stress-reactive disposition.”
Among Danish soldiers deployed to Iraq (Bo Andersen,
Karstoft, Bertelsen, & Madsen, 2014), an improvement
trajectory (“low-fluctuating”) was also identified in 7.5%
of the soldiers, though the authors did not discuss the
pattern in the article. Another study using earlier waves
of these data also identified a group of soldiers who
experienced distinct patterns of “temporary benefit” from
their combat experiences (Berntsen et al., 2012). Still
another example is found in Bonanno and colleagues’
(2012) examination of trajectories of adjustment among
U.S. soldiers deployed to Iraq and Afghanistan. They
found an improvement trajectory from before to after
deployment among 9% of the sample. And most recently,
Nash and colleagues (2014) found a marked improve-
ment pattern (9.0%) among one cohort of Marines
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Social Support, Improvement, and Virginia Tech 403
deployed to Afghanistan. Consistent with the role of
social factors, the authors speculated that improvement
in predeployment distress may be, in part, a consequence
of “unit cohesion.” Nevertheless, in spite of growing evi-
dence for this pattern, it has been neglected as a phe-
nomenon in its own right, and theories as to why people
might experience improvements in psychological adjust-
ment following an acute stressor are generally absent.
On the other hand, theorists in the area of posttrau-
matic growth have long argued for the possibility of
“positive psychological change experienced as a result
of the struggle with a highly challenging life circum-
stance” (Tedeschi & Calhoun, 2004, p. 1). The idea of
posttraumatic growth bears superficial parallels to the
improvement pattern. However, the proposed improve-
ment trajectory is fundamentally distinct from posttrau-
matic growth for two key reasons. First, posttraumatic
growth depends on people’s perception that they have
experienced growth, which, some evidence suggests,
reflects a motivated positive illusion rather than an
objective improvement in functioning (e.g., Frazier etal.,
2009; McFarland & Alvaro, 2000). Second, it hinges
on the idea that growth results from one’s “struggle”
(Tedeschi & Calhoun, 2004). By contrast, the improve-
ment trajectory is derived from objective change on an
index of psychological functioning and does not imply a
preceding period of elevated distress. The person who
improves does not experience a long-term benefit from
being traumatized but rather immediate improvements
that are conditioned by the stressful event itself.
Group Versus Solitary Exposure
Under what circumstances is improvement possible?
Although improvement has been documented following
divorce and bereavement (Bonanno etal., 2002; Mancini,
Bonanno, & Clark, 2011), we propose that there is a criti-
cal difference between experiencing an isolated and
highly threatening acute stressor as an individual (e.g.,
sexual assault) and as a group (e.g., a school shooting,
military deployment, or terrorist attack). When an acute
stressor is experienced by a group, the stressor will mobi-
lize cooperative, mutually supportive, and potentially syn-
ergistic prosocial behaviors among exposed persons and
increase the sense of connectedness to others (Hawdon &
Ryan, 2011). These positive social effects may not only
mitigate distress but also directly contribute to well-being
(Hawdon, Räsänen, Oksanen, & Ryan, 2012).
Present Study
In the present study, we examined the possibility that mass
trauma can promote psychological improvement for some
survivors. We tested this hypothesis among a sample of
female students who were exposed to an exceptionally
stressful event, the Virginia Tech campus shootings, the
most deadly civilian shooting in U.S. history. The attack
lasted for more than 2 hours and resulted in the deaths of
33 people (including the gunman) and the wounding of
25 others (Associated Press, 2007). Classrooms were locked
down and the entire campus immobilized during and for
some time after the shootings. Despite the enormity of the
shootings, the event was isolated and short-lived. The
shooter no longer posed a threat in the days and weeks
that followed. Thus, although students, faculty, and staff
undoubtedly had to contend with a deep sense of loss and
an increased sense of vulnerability following the shoot-
ings, they also potentially experienced a changed social
landscape, characterized by an increased sense of con-
nectedness, trust, and cooperation.
Indeed, the intense media attention to the event also
brought a tremendous outpouring of support from across
the nation and worldwide, as well as led to strong feel-
ings of pride, solidarity, and collective mourning within
the community. For example, a memorial was quickly
erected on campus, and gifts and messages were left for
the individuals killed and wounded. In the months fol-
lowing, a memorial fund was established for the victims
and their families, and a university-wide initiative of ser-
vice to the community was established. These efforts to
memorialize the dead and provide support to the living
are widely found after mass traumas. After 9/11, for
example, people throughout New York City lit candles
outside of their homes, and makeshift memorials could
be found throughout the city. We hypothesized that this
increased sense of social connection could ameliorate
preexisting distress and result in improved psychological
functioning.
To test this possibility, we utilized data from a longitu-
dinal study of college women who were exposed to the
VT campus shootings (Littleton, Axsom, & Grills-
Taquechel, 2009). Participants in this study were drawn
from a multiuniversity study of sexual victimization that
was ongoing at the time of the campus shootings. Thus,
information about participants’ psychological adjustment
prior to the shooting was available, as was information
from post-shooting assessments at 2, 6, and 12 months.
Because of this longitudinal prospective design, we could
directly assess change (or lack of it) following the shoot-
ing. We measured psychological adjustment using assess-
ments of anxiety and depression, reasoning that they
would capture general elements of distress in response to
the shootings (e.g., Marshall, Schell, & Miles, 2010). To
model anxiety and depression over time, we employed
latent growth mixture modeling (LGMM), a technique
that groups individuals into unique patterns of intraindi-
vidual change and provides empirical criteria (model fit)
for determining the legitimacy of these patterns (Muthén,
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404 Mancini et al.
2004). We conducted separate analyses for anxiety and
depression, but we expected that participants would be
grouped into similar patterns for both outcomes.
Based on previous research and theory (Bonanno &
Mancini, 2012), we also anticipated a number of distinct
response patterns. The shootings left survivors with a
clear risk of posttraumatic stress disorder. Thus, we
expected that some would show a marked stress
response, with an elevation in anxiety and depression
symptoms following the shootings and a persistent
course. Despite the clear risk, it is well established that
resilience is the modal response to acute stress (Bonanno
etal., 2011), and we therefore expected most of the sam-
ple to demonstrate low levels of depression and anxiety
both before and after the shootings. Most relevant to our
focus, we expected that some participants would improve
in their anxiety and depression symptoms and that this
improvement would be related to gains in social relation-
ships, which we indexed by using measures of perceived
social support and interpersonal resource gain (Hobfoll,
Tracy, & Galea, 2006). We expected that improved par-
ticipants, relative to other trajectory patterns, would
report marked increases in perceived social support from
before to after the shootings and a greater degree of
interpersonal resource gain after the shootings. We fur-
ther expected that these gains would not simply be a
consequence of lower levels of exposure to the shoot-
ings, because the presence of acute stress is key to these
prosocial outcomes.
Method
Participants
Participants were 368 women who completed at least
one of two online surveys administered at 2 and 6
months post-shooting regarding adjustment following
the VT campus shooting. Participants were drawn from
a sample of 843 female VT students who had completed
a multiuniversity survey of sexual victimization during
the same academic semester as the shooting or the pre-
vious academic semester. Participants were 19.4 years of
age on average (SD = 1.3 years, range = 18–27 years)
when they completed the initial survey. In all, 86% char-
acterized their ethnicity as White/European American,
5% as Asian American, 3% as Black/African American,
2% as Latina, and 2% as multiethnic; a further 1% did not
indicate their ethnicity or marked other. There were few
differences between women who completed the first
post-shooting survey and those who did not (Littleton
et al., 2009), with women who completed the survey
being slightly older, t(831) = 3.16, p < .005, d = 0.23, and
reporting somewhat less social support, t(840) = 3.09,
p< .005, d = 0.22, than noncompleters of this survey. We
also compared differences between participants who
completed all four assessments and those with at least
one missing assessment. According to independent sam-
ples t tests and chi-square analyses, participants who
completed each wave of data collection, as compared
with those who missed at least one wave, did not differ
in age (p = .53), White ethnicity (p = .52), baseline social
support (p = .94), baseline anxiety (p = .97), baseline
depression (p = .13), anxiety trajectory (p = .38), or
depression trajectory (p = .61).
Procedure
Complete study procedures have been detailed else-
where (e.g., Littleton, Axsom, & Grills-Taquechel, 2011).
To summarize, women, 18 years and older, initially
received course credit to take part in a multiuniversity
online survey of women’s negative sexual experiences.
As part of this survey, measures were completed regard-
ing current depressive and anxiety symptoms and social
support. At approximately 2 and 6 months post-shooting,
all VT women with a valid email address (n = 820) were
sent an email inviting them to participate in an online
survey related to risk and resilience following the shoot-
ing. A total of 368 people (44.8%) responded to at least
one of these two post-shooting surveys and were also
invited via email to complete a 12-month post-shooting
survey. Participants were given the choice to be compen-
sated with a gift card or a donation to the VT shooting
memorial fund for each completed survey and were
entered in a drawing to receive a larger monetary com-
pensation for the 12-month survey (the shooting memo-
rial fund was closed at the time of the 12-month survey).
Based on the available sample, response rates to each
survey invitation were as follows: 2 months, 81.4% (n =
298), 6 months, 71.6% (n = 263), 12 months, 70.1% (n =
258). All surveys were approved by the university institu-
tional review board, and the post-shooting surveys were
approved by a university committee developed to ensure
ethical conduct in shooting-related research.
Measures
Anxiety symptoms. To assess the affective dimension
of anxiety, participants completed the five-item Emo-
tional subscale of the Four Dimensional Anxiety Scale
(Bystritsky, Linn, & Ware, 1990), which assesses current
(state) anxious affect (e.g., “feeling uneasy,” “feeling ner-
vous,” “feeling irritable”). For each item, participants
indicated how often they have felt in the described man-
ner in the past week on a 5-point scale bounded by 1
(not at all) and 5 (extremely), and scores are summed to
derive a subscale total. Prior research supports the mea-
sure’s internal consistency and validity (Bystritsky etal.,
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Social Support, Improvement, and Virginia Tech 405
1990; Stoessel, Bystritsky, & Pasnau, 1995). In the current
study, Cronbach’s alpha for the Emotional subscale at
each assessment ranged from .85 to .86.
Depressive symptoms. To assess depressive symptoms,
participants completed the Center for Epidemiologic
Studies Depression Scale (CES-D; Radloff, 1977). The
CES-D is a 20-item, self-report measure of primarily the
affective component of depressive symptoms (e.g., “I felt
sad”). For each item, individuals indicated how often
they had felt that way in the past week on a 4-point scale
bounded by 0 (rarely or none of the time/less than one
day) and 3 (most or all of the time/5–7 days). Scores are
summed and can range from 0 to 60 with scores of 21 or
above suggestive of clinical levels of current depression
in college samples (Shean & Baldwin, 2008). Prior
research supports the measure’s internal consistency, test–
retest reliability, and validity (Radloff, 1977; Weissman,
Sholomskas, Pottenger, Prusoff, & Locke, 1977). Cron-
bach’s alpha in the current sample across assessments
ranged from .87 to .92.
Exposure, loss, and perceived threat. Several items
were administered to evaluate participants’ level of expo-
sure to the shooting, loss of loved ones in the shooting,
and perceived threat during the shooting incident. These
items were administered at the 2-month post-shooting
survey or at the 6-month post-shooting survey for partici-
pants who did not complete the 2-month survey. Partici-
pants completed several yes/no questions regarding their
direct exposure to several aspects of the shooting (e.g., if
they were on campus during the shooting, if they heard
gunfire). Scores on these questions were summed to cre-
ate an overall index of exposure. In addition, participants
were placed into a high exposure group if they were in
one of the buildings where the shooting occurred, heard
gunfire, or saw individuals who had been wounded or
killed. Participants were also asked if they knew anyone
who was killed in the shooting (yes/no item) and, if so,
to indicate their relationship with that person. Partici-
pants who indicated that a shooting victim was a friend
or close friend, as opposed to reporting a more casual
relationship with a victim (e.g., acquaintance, classmate,
friend of a friend, professor), were categorized as having
lost a friend in the shooting (friend loss). Finally, partici-
pants completed 5-point scale items regarding the extent
they believed that their own life (self-threat) and that of
loved ones were in danger during the shooting incident
(other-threat). This scale was bounded by 0 (not at all/no
chance you or others would be killed) and 4 (completely/
felt convinced you or others would be killed). Responses
at or above the midpoint of the scales for other- and self-
threat were recoded into binary variables (0 = no threat,
1 = threat).
Interpersonal resource gain. Participants were
administered 27 items from the Conservation of Resources
Evaluation (Hobfoll, 2001) to assess resource loss and
gain following the shooting. Items were selected based
on prior research following mass trauma (e.g., Hobfoll
etal., 2006). For the 2-month post-shooting survey, par-
ticipants were asked the extent to which they had lost or
gained each resource since the shooting, and for the sub-
sequent assessments they were asked how much they
had lost or gained each resource since the previous
assessment. Ratings were made on a 5-point scale
anchored by –2 (great deal of loss) and 2 (great deal of
gain). A gain score was created by recoding responses as
2 (great deal of gain), 1 (some gain), and 0 (no gain).
Principal axis factoring of these items resulted in three
interpretable factors: sense of self/optimism gain, inter-
personal resource gain, and self-control gain. In the cur-
rent study, summed scores from the nine-item
Interpersonal Resource Gain subscale were examined
(e.g., intimacy with one or more family members, time
with loved ones). Cronbach’s alpha for this subscale
across assessments ranged from .83 to .86.
Social support. The Multidimensional Scale of Per-
ceived Social Support (MSPSS; Zimet, Dahlem, Zimet, &
Farley, 1988) was administered to assess perceived social
support. The MSPSS is a 12-item measure of perceived
social support adequacy with three scales assessing sup-
port from family, friends, and a significant other. A sam-
ple item is, “There is a special person around when I am
in need.” For each item, individuals indicate the extent to
which they agree with the statement on a 7-point Likert-
type scale bounded by 1 (very strongly disagree) and 7
(very strongly agree). In the present study, a mean item
score for the overall measure was calculated to evaluate
overall perceived social support. Prior research supports
the internal consistency and factor structure of the mea-
sure (Zimet etal., 1988). Cronbach’s alpha of the scale in
the current sample ranged from .93 to .96.
Data analysis
LGMMs were conducted with Mplus 7.11 to identify dis-
crete growth trajectories (or classes), and a robust full-
information maximum-likelihood estimation procedure
was employed to handle missing data (Enders, 2001;
Graham, 2009). The percentages of missing data for post-
shooting surveys were 19.6% (2 months), 29.4% (6
months), and 30.0% (12 months). LGMMs use empirical
criteria to identify distinct trajectory patterns. Although a
substantial improvement over prior methods, mixture
models nevertheless possess limitations that must be
borne in mind when developing the analysis plan. One
significant limitation is that the models may not
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406 Mancini et al.
accurately describe real mixture distributions but instead
diagnose nonnormality that can result from various fac-
tors, including measurement error. To address the poten-
tial for arbitrary trajectory solutions, two separate LGMMs
were conducted on different dependent measures (anxi-
ety and depression scores). If similar trajectory solutions
emerged for both dependent measures, that would cross-
validate the results for each dependent measure. In addi-
tion, we made specific a priori predictions with respect to
auxiliary information (the hypothesized relationship of
trajectory pattern to social relationship variables), which
would provide additional support for the model. In deter-
mining the optimal trajectory solution, conventional indi-
ces were relied on to determine the relative fit of different
multiclass models, but theoretical interpretability and tra-
jectory distinctiveness were also used as criteria for model
selection. Finally, standard techniques were used to max-
imize the likelihood of identifying the optimal trajectory
solution, including varying the number of random start-
ing values and employing the optseed procedure to
ensure that the best log-likelihood value was replicated
(Jung & Wickrama, 2008).
Analyses were conducted in three steps. First, simple
growth models were used to determine the growth param-
eters for the LGMMs (Jung & Wickrama, 2008). Second,
successive class models were compared, starting with one
and adding additional classes (Muthén, 2004). Modification
indices were inspected to determine whether to retain the
default specifications of Mplus on correlated residuals,
error variances, residual variances, and covariances across
measurement occasions. In the third step, post hoc analy-
ses were conducted using the anxiety and depression class
variables. The focus of these analyses was the relationship
of trajectory assignment to social relationship variables.
But we first used chi-square analyses to examine whether
the anxiety and depression trajectory analyses assigned
participants to similar trajectory patterns. Next we exam-
ined whether participants who showed different patterns
of adjustment also showed different patterns of change in
perceived social support from pre-shooting to 12 months
post-shooting. One important issue for these analyses was
missing data for the repeated measures outcome (per-
ceived social support). Analyzing only participants with
complete data (i.e., all four waves) would sharply reduce
our sample and potentially introduce biases (Enders,
2011). Thus, we conducted two sets of repeated measures
analyses. We analyzed participants with complete data
using repeated measures ANOVA, and we used linear
mixed models, which use maximum likelihood estimates
to accommodate missing data. To further examine inter-
personal factors and trajectory assignment, we next exam-
ined self-reported gains in interpersonal resources by
trajectory grouping. We report complete data for these
analyses because maximum likelihood, which could be
used in a dummy-coded regression analysis, would
provide identical estimates to complete data analysis
(Allison, 2001). A final analysis explored whether trajec-
tory assignment was associated with measures of expo-
sure using chi-square and one-way ANOVA analyses.
Results
Adjustment trajectories
Measures of anxiety and depression were collected
before the shooting and at 2, 6, and 12 months post-
shooting. To identify patterns of change in depression
and anxiety symptoms, one-class models with intercept-
only, linear-only, and linear and quadratic growth param-
eters were compared using log-likelihood chi-square
testing to assess the fit of different model parameters. For
both anxiety and depression models, a linear and qua-
dratic model provided superior fit, according to log-
likelihood ratio chi-square testing (ps < .01). Consistent
with recommendations for model testing (Jung &
Wickrama, 2008), one- to five-class unconditional models
(i.e., no covariates) were compared. An ideal model was
considered to be one with lower values for the Akaike
(AIC), sample-size-adjusted Bayesian (SSBIC), and
Bayesian (BIC) information criterion indices, higher
entropy values, and significant p values for the paramet-
ric bootstrapped likelihood ratio rest (BLRT; Nylund,
Asparouhov, & Muthén, 2007) and the Lo–Mendell–Rubin
likelihood ratio test (LMR). The totality of these indices,
in combination with the interpretability and theoretical
coherence of a given class solution, guided the final
model selection (Muthén, 2003).
Anxiety trajectories. To identify anxiety trajectories,
we compared one- to five-class models with linear and
quadratic growth parameters. Based on model testing,
we fixed the variances for the slope and quadratic
parameters to zero but allowed the intercept variance to
be freely estimated. Information criterion and other
indices showed improved fit going from two (AIC =
6339.07, BIC= 6385.96, SSBIC = 6347.89, entropy = .71,
LMR p = .14, BLRT p < .001, smallest class = 21.8%) to
three (AIC= 6321.64, BIC = 6384.17, SSBIC = 6333.40,
entropy = .70, LMR p = .14, BLRT p < .001, smallest
class = 10.7%) to four classes (AIC = 6297.25, BIC =
6375.41, SSBIC = 6311.96, entropy = .70, LMR p = .02,
BLRT p < .001, smallest class = 8.0%). A five-class solu-
tion produced a class with 0.03% of participants and
thus was not considered. The four-class solution was
interpretable and consistent with theoretical expecta-
tions; thus, it was selected as optimal. A log-likelihood
ratio chi-square test confirmed that the four-class qua-
dratic model showed superior fit to a linear-only model
(p < .001). Next, a conditional model was tested in
which demographic covariates were allowed to predict
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Social Support, Improvement, and Virginia Tech 407
the growth parameters and trajectory class designation.
However, the inclusion of covariates resulted in unsta-
ble models that either did not converge or could not be
replicated using the optseed procedure (Jung & Wick-
rama, 2008). As a result, the unconditional model was
used in all subsequent analyses.
As shown in Figure 1, the four-class trajectory model
consisted of people who reported (a) low initial levels of
anxiety and no change across time (resilience; 56.1%),
(b) low levels of anxiety before the shooting and a sharp
increase to 12 months post-shooting (chronic distress;
22.8%), (c) high levels of anxiety both before and after
the shooting (continuous distress; 8.0%), and (d) high
levels of anxiety before the shootings and a sharp
decrease directly following and continuing to 12 months
post-shooting (improvement; 13.2%). These results pro-
vided support for the idea that people can report
improvements after acute stress. To extend the analyses
to an additional and highly relevant dimension of adjust-
ment, an identical analysis using depression as the
repeated outcome measure was conducted.
Depression trajectories. Model-fitting procedures were
again used to compare one to five class models. The vari-
ances for the slope and quadratic parameters were again
fixed to zero and the intercept variance freely estimated.
Information criterion and other indices showed improved
fit going from two (AIC = 8458.75, BIC = 8505.65, SSBIC=
8467.57, entropy = .68, LMR p = .13, BLRT p < .001, small-
est class = 28.9%) to three classes (AIC = 8406.71, BIC =
0
5
10
15
20
25
30
35
40
Pre-shooting 2 months 6 months 12 months
Depression
Improvement, 7.4%
Resilience, 58.6%
Chronic distress, 8.9%
Continuous distress, 15%
Delayed reaction, 10.1%
4
6
8
10
12
14
16
18
20
Pre-shooting 2 months 6 months 12 months
Anxiety
Improvement, 13.2%
Resilience, 56.1%
Chronic distress, 22.8%
Continuous distress, 8.0%
a
b
Fig. 1. Anxiety (a) and depression (b) trajectories.
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408 Mancini et al.
8469.24, SSBIC = 8418.48, entropy= .78, LMR p < .001,
BLRT p < .001, smallest class = 11.7%). Although the four-
class solution showed a slight decrement in fit according
to the Bayesian index and the LMR, there were small
improvements in the other measures of fit (AIC = 8397.66,
BIC = 8475.82, SSBIC = 8412.37, entropy = .79, LMR p =
.21, BLRT p < .001, smallest class = 5.6%) when compared
with the three-class solution. The five-class solution also
produced a slight decrement in fit according to the Bayes-
ian and lower levels of entropy, but improvements
according to the other indices (AIC = 8383.60, BIC =
8477.39, SSBIC = 8401.25, entropy = .75, LMR p = .12,
BLRT p < .001, smallest class = 7.4%) The functional
forms of the trajectories were again examined. The three-,
four-, and five-class models all identified a resilient trajec-
tory, an improvement trajectory, and a chronic distress
trajectory, but the five-class model also identified a
delayed distress trajectory. Because of the theoretical rel-
evance of this pattern and its distinctiveness from the
other patterns, we selec ted the five-class quadratic model
for depression. Log-likelihood ratio chi-square testing
confirmed that the quadratic model provided superior fit
over a linear-only model (p < .001). As with the model for
anxiety, inclusion of demographic covariates either
resulted in a nonidentified model or failed to improve
model fit, and thus an unconditional model was selected
as optimal.
As shown in Figure 1, the depression trajectories were
strikingly consistent with the anxiety trajectories, in terms
of both their functional form and their prevalence. The
largest group consisted of persons with low levels
of depression and who showed no change from pre-
shooting to 12 months post-shooting (resilience; 58.6%).
The second most prevalent pattern consisted of people
with elevated levels of depression that declined after the
shooting but remained elevated relative to the sample
(high continuous distress; 15%). As with the anxiety anal-
yses, a clear chronic distress emerged in which there was
a sharp increase in depression after the shootings that
continued to 6 months and abated at 12 months (chronic
distress; 8.9%). Moreover, a delayed reaction in which
initial modest elevations got substantially worse also
emerged (delayed reaction; 10.1%). Finally, and consis-
tent with the anxiety analyses, some participants saw a
substantial decrease in depression that remained lower at
12 months post-shooting (improvement; 7.4%).
Growth parameters for depression and anxiety.
Table 1 shows growth parameter estimates. As expected,
the improvement group showed a negative slope for
depression and anxiety symptoms (ps ≤ .07) and no qua-
dratic effects, indicating a linear decrease. By contrast,
the resilient group showed no linear or quadratic change,
indicating a stable level of anxiety and depression symp-
toms over time. The anxiety and depression chronic dis-
tress groups revealed significant positive slopes (ps <
.001) that were modified by significant negative quadratic
effects (ps < .01), indicating that the rate of increase sub-
sided over time and was concave. The delayed reaction
group also revealed a quadratic effect (p= .03), but it was
positive, indicating that the rate of growth was convex
and accelerated over time, as would be expected. The
continuous distress group for depression symptoms also
revealed a negative slope (p = .005) and a positive qua-
dratic effect (p = .04), indicating that the rate of change
also decreased and became convex.
Concordance of trajectory patterns. Although the
models for anxiety and depression symptoms each pro-
duced four similar trajectory patterns, it was unclear that
Table 1. Growth Parameter Estimates for Anxiety and Depression Models
Parameter Anxiety trajectories Depression trajectories
Class
Intercept Slope Quadratic Intercept Slope Quadratic
Est. (95% CI) Est. (95% CI) Est. (95% CI) Est. (95% CI) Est. (95% CI) Est. (95% CI)
Resilience 8.84***
(8.36, 9.33)
–0.37
(–0.98, 0.24)
0.11
(–0.08, 0.29)
9.79***
(8.79, 10.80)
0.25
(–0.84, 1.34)
–0.13
(–0.50, 0.24)
Improvement 15.20***
(13.54, 15.59)
–2.41†
(–4.62, –0.20)
0.15
(–0.50, 0.81)
26.81***
(23.49, 30.12)
–12.80**
(–20.76, –4.87)
2.44
(0.08, 4.80)
Chronic distress 9.54***
(8.57, 10.52)
4.32***
(2.51, 6.14)
–0.96**
(–1.52, –0.39)
9.86***
(7.29, 12.44)
20.72***
(16.18, 25.27)
–5.61***
(–7.18, –4.03)
Continuous distress 17.69***
(16.03, 19.35)
–0.14
(–1.82, 1.87)
0.06
(–0.05, 0.59)
29.92***
(26.77, 33.07)
–6.74**
(–10.70, –2.79)
1.80*
(–0.38, 3.22)
Delayed — — — 14.89***
(10.78, 18.99)
–4.81
(–11.05, 1.43)
3.12***
(0.74, 5.49)
Note: CI = confidence interval; est. = estimate.
†p = .07. *p < .05. **p < .01. ***p < .001.
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Social Support, Improvement, and Virginia Tech 409
class membership was concordant across the adjustment
trajectories. Thus, chi-square analyses were used to com-
pare the probability that participants were classified into
the same trajectory for anxiety and depression models.
This analysis revealed a significant, nonrandom distribu-
tion across the outcome patterns, χ2(9, N = 368) = 235.76,
p < .001. Follow-up analyses of individual cells compared
the frequency probability for each cell relative to chance
using Haberman’s (1978) standardized, adjusted residuals
statistic (HAR). Across 66.4% of the sample, there was
concordance for trajectory assignment for both anxiety
and depression symptoms. More than half of the sample
(51.4%) were classified as resilient on both outcome mea-
sures, a percentage substantially in excess of chance
probability, HAR = 10.9, p < .001. Persons classified as
improved on both outcome measures also occurred in
excess of chance (3.0%), HAR = 5.5, p < .001, as did per-
sons classified as continuous distress (6.0%), HAR = 8.9, p
< .001 and as chronic distress (6.0%), HAR = 8.0, p < .001.
Finally, persons classified in the delayed depression tra-
jectory were significantly more likely to be classified in
the chronic distress trajectory for anxiety (3.0%), HAR =
3.1, p < .01, a result that suggests that the five-class depres-
sion model split the chronic distress group into two dis-
tinctive and theoretically relevant patterns.
Is improvement associated with
changes in social relationships?
Across the two outcome measures of functioning, depres-
sion and anxiety, a clear trajectory of improvement was
identified. According to the hypothesis that acute stress
may have prosocial effects, participants who improved
were expected to report improved social relationships.
To address this question, two relevant measures of social
relationships were examined in relation to anxiety and
depression trajectory patterns: perceived social support
and interpersonal resource gain.
Anxiety trajectories and change in social support
Repeated measures ANOVA on complete data. A
repeated measures analysis of variance (ANOVA) with
perceived social support as the within subjects factor and
anxiety trajectory as the between-subjects factor was con-
ducted (see Table 2 for means and standard deviations
at each wave). This analysis revealed that social support
increased reliably over time, F(2.80, 483) = 4.19, p = .007,
ηp2 = 03. However, the main effect was qualified by a
two-way Time × Anxiety Trajectory interaction, F(8.39,
483) = 2.31, p = .02, ηp2 = .04, indicating this change in
social support varied according to trajectory. To clarify
this further, we conducted simple main effects analyses.
The anxiety improvement group demonstrated a substan-
tial and significant increase over time in social support,
F(3, 13) = 9.63, p = .001, ηp2 = .69, which represented a
large effect, according to conventional criteria (J. Cohen,
1988). The resilient group also showed an increase over
time in social support, F(3, 93) = 4.18, p = .01, ηp2 =
.12, but the magnitude of this effect was much smaller.
Neither the continuous distress nor the chronic distress
group showed significant change (ps < .26).
Linear mixed model on all data. Next we replicated
this analysis in a linear mixed model using the same
within-subjects (perceived social support) and between-
subjects (anxiety trajectory) factors. Mixed models use
maximum likelihood estimates to account for missing
data and therefore allow all participants to be included
in the analysis. This is particularly important in longi-
tudinal analyses, because eliminating incomplete cases
can introduce various biases (Enders, 2011). We used
a random intercept model and, based on model test-
ing, assumed a Toeplitz covariance matrix. Time, anxi-
ety trajectory class, and their interaction were treated
as fixed effects. Consistent with the repeated measures
ANOVA, this analysis revealed an almost identical main
effect for time F(3, 743.27) = 4.02, p = .007, as well as
a two-way Time × Anxiety Trajectory interaction, F(9,
740.97) = 1.90, p = .06, though the interaction was now
marginal. When we conducted analyses separately for
each anxiety trajectory, we again replicated the finding
that the anxiety improvement group showed a marked
increase in social support, F(3, 78.37) = 8.96, p < .001,
as did the resilient group, F(3, 433.03) = 5.87, p = .001.
By contrast, the chronic distress, F(3, 127.93) = 1.32, p=
.27, and the continuous distress, F(3, 65.53) = .43, p =
.73, groups showed no change in social support. Figure
2a shows the predicted means by anxiety trajectory and
measurement occasion.
Depression trajectories and change in social
support
Repeated measures ANOVA on complete data. We
applied the same analytic strategy to the depression
trajectories to assess the consistency of our findings. A
repeated measures analysis of depression trajectories
showed a main effect of time, F(2.79, 447.23) = 2.71, p =
.05, ηp2 = .02, and a significant two-way Time × Depres-
sion Trajectory interaction, F(11.18, 447.23) = 2.47, p =
.005, ηp2 = .06. Consistent with the results for anxiety, a
simple main effect of time also emerged for the depres-
sion improvement group, F(3, 21) = 9.07, p = .001, ηp2=
.56, and the resilient group, F(2.46, 312) = 3.81, p = .02,
ηp2 = .04, but not for the delayed or chronic distress
groups (ps > .20). It was somewhat surprising that the
continuous distress group for depression also experi-
enced an increase in social support, F(3, 72) = 4.75, p =
.004, ηp2 = .17.
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410 Mancini et al.
Linear mixed model on all data. We used the same
random intercept model for depression. This analysis
again showed a strong main effect of time, F(3, 727.15)=
4.12, p = .007. However, in contrast to the repeated
measures analysis for depression, the two-way Time ×
Depression Trajectory interaction was not significant,
F(12, 731.86) = 1.51, p = .12. Although this result was
unexpected, we suspected that the relatively smaller sam-
ple of depressed improved participants, compared with
the anxiety improved group, and the increased degrees
of freedom necessitated by the five-class depression
model may have weakened the power of the analysis to
detect the interaction effect.
Composite improvement trajectory. To address these
issues, we created a composite of the anxiety and
depressed improvement trajectories. A composite would
increase the sample of improved participants and pro-
vide a more robust measure of improvement. This
approach also allowed us to isolate the trajectory of pri-
mary interest and to reduce the degrees of freedom in
our analysis. Membership in this composite improvement
trajectory was established by a simple decision rule of
either being a member of the depression or the anxiety
trajectory or both. This resulted in 14.9% of the sample
being classified as improved. We used the composite tra-
jectory as the between-subjects factor (1 = improved, 0 =
all others) in a final repeated measures analysis.
We proceeded directly to the linear mixed model. We
used the same random intercept model, with time, com-
posite improvement trajectory, and their interaction
treated as fixed effects. This analysis showed a strong
main effect of time, F(3, 748.83) = 9.25, p < .001. More
important, the two-way interaction of Time × Composite
Trajectory interaction was highly significant, F(3,
748.83)= 4.85, p = .002, indicating that change in social
support varied according to whether the person was clas-
sified as improved. Figure 2b shows the predicted means
by trajectory and measurement occasion.
Reported gains and losses in interpersonal
resources. To further explore the relationship of
improvement to social relationships, we investigated self-
reported gains in interpersonal resources. Again, it was
Table 2. Descriptive Statistics by Anxiety Trajectory Class
Variable ImprovementaResilienceb
Continuous
distressc
Chronic
distressdF or χ2
Demographics
Age 19.50 (1.40) 19.21 (1.18) 19.71 (1.74) 19.73 (1.52) 3.68*
White ethnicity (%) 92.9 88.8 85.7 77.0 8.22*
Exposure measures
Self threat (%) 28.1 31.5 62.5 39.1 10.05*
Other threat (%) 87.5 74.2 100.0 84.4 11.62*
Friend loss (%) 31.0 26.5 41.4 37.8 5.22
High exposure (%) 26.2 30.5 41.4 27.0 2.40
Exposure sum 4.90 (3.05) 5.02 (2.83) 6.00 (3.13) 5.76 (2.58) 2.15†
Functioning measures
Anxiety, pre-shooting 16.09 (2.19) 8.91 (2.62) 18.06 (2.82) 9.48 (2.60) 179.35***
Anxiety, 2 mths 13.53 (3.60) 8.48 (2.41) 17.83 (2.88) 13.53 (3.60) 113.85***
Anxiety, 6 mths 11.77 (2.51) 8.54 (2.66) 17.80 (2.68) 15.07 (2.89) 127.07***
Anxiety, 12 mths 9.30 (2.62) 8.61 (2.25) 18.04 (2.51) 14.22 (2.54) 157.93***
Depression, pre-shooting 23.67 (8.12) 11.13 (6.66) 30.31 (9.73) 13.82 (8.73) 71.68***
Depression, 2 mths 18.93 (10.28) 9.91 (6.46) 24.87 (8.77) 19.03 (9.59) 44.06***
Depression, 6 mths 15.70 (6.97) 9.89 (6.93) 24.30 (7.29) 24.00 (8.69) 61.87***
Depression, 12 mths 12.07 (7.64) 10.45 (7.55) 27.83 (7.44) 22.75 (8.76) 58.35***
Social support, pre-shooting 5.34 (1.07) 5.79 (1.14) 5.13 (1.12) 5.50 (1.29) 4.35**
Social Support, 2 mths 5.79 (1.18) 5.93 (1.04) 5.07 (1.40) 5.63 (1.19) 4.65**
Social Support, 6 mths 5.83 (1.12) 6.12 (0.88) 5.42 (1.01) 5.59 (1.32) 5.71***
Social Support, 12 mths 6.11 (1.19) 5.98 (0.95) 5.27 (1.15) 5.32 (1.34) 7.58***
Interpersonal gain, 2 mths 7.22 (4.63) 6.43 (4.54) 6.04 (3.91) 5.25 (3.99) 1.71
Interpersonal gain, 6 mths 7.40 (4.09) 5.91 (4.13) 5.05 (3.51) 4.52 (3.77) 3.54**
Interpersonal gain, 12 mths 6.78 (5.52) 5.78 (4.21) 4.17 (2.98) 4.63 (3.60) 2.74*
Note: Mths = months. Values are means, with standard deviations in parentheses, unless otherwise indicated.
ans range from 27 to 42. bns range from 147 to 223. cns range from 20 to 29. dns range from 51 to 74.
†p < .10. *p < .05. **p < .01. ***p < .001.
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Social Support, Improvement, and Virginia Tech 411
expected that individuals in the improvement group,
when compared with the other trajectory patterns, would
report more gains in interpersonal resources at each
wave of data collection. To address this question, inter-
personal resource gains at 2, 6, and 12 months post-
shooting were examined across the anxiety and
depression trajectories and their composite. As shown in
Table 2, omnibus tests for the anxiety trajectories revealed
that there was significant group variation in interpersonal
gains at 6 months, F(3, 261) = 3.54, p = .015, and at
12months, F(3, 253) = 2.74, p = .04. Pairwise compari-
sons showed that, at 6 months post-shooting, the
improvement group (M = 7.40, SD = 4.09) reported more
interpersonal gains than the chronic distress group (M =
4.52, SD = 3.76, d = 0.73) and the continuous distress
group (M = 5.05, SD = 3.51, d = 0.61). Moreover, at
12 months post-shooting, the improvement group
reported more interpersonal resource gains (M = 6.77,
SD = 5.52) than the continuous distress group (M = 4.16,
SD = 2.98, d = 0.58) and marginally more than the chronic
distress group (M= 4.63, SD = 3.60, d = 0.46).
Analyses on the depression trajectory variable revealed
a similar, though somewhat attenuated, pattern of results.
Omnibus tests for the depression trajectories revealed
marginal effects at 2 months, F(4, 290) = 2.10, p = .08, and
at 6 months, F(4, 261) = 2.06, p = .09, and a significant
effect at 12 months, F(4, 256) = 6.10, p < .001. Pairwise
comparisons revealed that the improvement group
reported more interpersonal gains at 12 months (M =
7.65, SD = 6.0) than the continuous distress group (M =
4.90
5.10
5.30
5.50
5.70
5.90
6.10
6.30
6.50
Pre-shooting 2 months 6 months 12 months
Social Support
Anxiety Trajectory
Improvement
Resilience
Continuous distress
Chronic distress
4.90
5.10
5.30
5.50
5.70
5.90
6.10
6.30
6.50
Pre-shooting 2 months 6 months 12 months
Social Support
Composite Trajectory
All others
Improvement
a
b
Fig. 2. Change in social support by (a) anxiety trajectory and (b) composite improvement trajec-
tory. Error bars show 95% confidence intervals.
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412 Mancini et al.
3.98, SD = 3.55, d = 0.74) and the delayed reaction group
(M = 2.71, SD = 2.49, d = 1.07). No pairwise differences
emerged at 2 and 6 months for the depression trajecto-
ries. A final step was to compare the composite improve-
ment trajectory against all others. This analysis was
consistent with previous results. The composite improve-
ment group reported marginally more interpersonal gains
at 6 months (M = 6.94, SD = 4.3) than all other trajectories
(M = 5.55, SD = 4.0, d = 0.33), t(260) = 1.90, p = .058, and
significantly more interpersonal gains at 12 months (M =
6.86, SD = 5.4) when compared with all other trajectories
(M = 5.25, SD = 3.92, d = 0.34), t(255) = 2.15, p = .03.
These results further indicated that improvement after an
acute stressor is associated with perceived gains in social
relationships and that the magnitude of this difference,
when compared with groups who did not improve, is
medium to large (J. Cohen, 1988).
Does improvement depend on low
levels of exposure?
A final focus was the potential role of exposure in the
improvement trajectory. Did survivors who improved
simply have less exposure to the shootings than other
participants? As shown in Table 2, chi-square analyses
were used to compare categorical exposure variables
with the probability of membership in a given anxiety
trajectory. For self-threat, there was a significant, nonran-
dom distribution across the anxiety trajectories, χ2(3, N =
368) = 10.05, p = .02. This analysis revealed that only the
continuous distress group was significantly more likely to
report a sense of self-threat, HAR = 2.9, p < .01. None of
the other trajectories showed a significant relation to self-
threat. A similar result emerged for other-threat. The con-
tinuous distress group was significantly more likely to
report a feeling of other-threat (100%), HAR = 2.6, p < .01,
and the resilient group was significantly less likely to
report a feeling of other-threat (74.2%), HAR = –3.0, p <
.001. But the improvement and other groups did not
show a significant relationship to other-threat. The
summed exposure variable showed a marginal omnibus
effect, but pairwise comparisons showed no significant
differences across groups (ps > .19). Neither friend loss
nor being categorized as high exposure differed across
the four outcome trajectories (ps > .15). When we repli-
cated these analyses using depression trajectory as the
grouping variable, we found an almost identical pattern
of results. There were no group differences for high
exposure, summed exposure, friend loss, or other threat
(ps > .10). Self-threat did differ across depression trajecto-
ries, χ2(4, N = 368) = 15.83, p = .003, with resilience being
less likely (29.8%), HAR = –2.6, p < .001 and chronic dis-
tress being more likely (68%), HAR = 3.6, p < .001, to
report self-threat. In sum, across exposure measures, the
improvement group did not differ from the other trajec-
tory groups, indicating that their level of exposure was
roughly comparable to the other groups.
Discussion
A wealth of evidence demonstrates that people cope with
acute stress in diverse ways (Bonanno, 2004). Most peo-
ple manage even the most severe stressors relatively well,
maintaining daily routines, seeing friends and family, and
experiencing positive emotions in spite of adversity
(Bonanno etal., 2011). Others experience acute psycho-
pathology (including depression, posttraumatic stress dis-
order, and complicated grief) or delayed reactions that
may require intervention, whereas still others experience
subclinical levels of distress that may take some time to
abate (Bonanno et al., 2011; deRoon-Cassini, Mancini,
Rusch, & Bonanno, 2010). It has been predominantly
assumed that these patterns comprise the universe of pos-
sible reactions. Conversely, the possibility that traumatic
events, in some cases, may promote adjustment has rarely
been considered, in spite of the fact that acute stress has
more complex effects than has previously been under-
stood (Updegraff & Taylor, 2000).
In the present study, a unique prospective dataset of
individuals exposed to the Virginia Tech campus shoot-
ing was used to test the possibility that some individuals
might experience psychological improvement following
a mass trauma. Although most individuals showed a resil-
ient response (56% to 59%), displaying low levels of anxi-
ety and depression both before and after the shooting,
some exhibited chronic distress and others a pattern of
continuous high distress. We also identified a subset of
individuals who experienced a delayed reaction in
depression symptoms (showing an initial pattern of con-
sistently low depression levels that increased from 2 to 12
months following the shooting). These reactions and
their prevalence were squarely consistent with previous
empirical and theoretical work on reactions to mass
trauma and acute stress (Andrews, Brewin, Philpott, &
Stewart, 2007; Bonanno etal., 2011).
More remarkable, however, were the findings that
some participants showed substantial improvements in
depression and anxiety. These individuals had elevated
levels of depression and anxiety before the shooting and
experienced a marked reduction soon after. These reduc-
tions were sustained a year after the shooting, suggesting
the positive effects were relatively long-lasting. No prior
research, to our knowledge, has empirically documented
such a reaction pattern among survivors of a mass trauma.
The improvement pattern was associated with substantial
increases in perceived social support and gains in social
resources, as predicted by the idea that acute stress pro-
motes stronger social relationships (von Dawans etal.,
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Social Support, Improvement, and Virginia Tech 413
2012) and altruistic behavior (Vollhardt, 2009). The prev-
alence of improvement (7% to 13%) was also consistent
with previous research on military samples (Bo Andersen
etal., 2014; Bonanno etal., 2012; Dickstein etal., 2010;
Nash et al., 2014), and did not appear to be simply a
consequence of low exposure. Moreover, irrespective of
adjustment trajectory, there was an overall increase in
perceived social support.
These findings provide new knowledge on the nature
of adjustment to acute stressors. The improvement trajec-
tory, which has little precedent in prior theorizing on
trauma and has received minimal attention in the previ-
ous studies that have identified it (Bo Andersen etal.,
2014; Bonanno etal., 2012; Dickstein etal., 2010; Nash
etal., 2014), appears to represent a new way of under-
standing people’s responses to mass trauma. A key point
is that improvement is distinct from posttraumatic growth,
the dominant framework for understanding positive psy-
chological change following traumatic events (Tedeschi
& Calhoun, 2004). Improved participants showed imme-
diate reductions in preexisting distress soon after the
shootings, as opposed to long-term benefits from being
traumatized.
Nevertheless, there were some suggestive parallels to
posttraumatic growth. For example, we found evidence
of perceived gains in interpersonal resources, a key
domain of posttraumatic growth (Tedeschi & Calhoun,
1996). An important point of difference, however, is that
these gains were concentrated among improved partici-
pants and were absent among those with chronic dis-
tress, as would be expected from traditional accounts of
posttraumatic growth (Tedeschi & Calhoun, 2004). In
contrast to theories of posttraumatic growth, our findings
therefore suggest that elevated and persistent distress is
an impediment to rather than a catalyst of growth.
Improvement has been observed previously in
response to individual-level acute stressors, notably
bereavement and divorce (Bonanno etal., 2002; Mancini
etal., 2011; Schulz etal., 2001), but we believe that a key
aspect of a mass trauma is that it afflicts large numbers of
people at once and therefore can mobilize mutually sup-
portive and cooperative behaviors on a broad scale. By
contrast, individual-level traumas, such as rape or assault,
would afford limited such opportunities and, in fact, at
times could increase one’s alienation from others (Brewin,
2003). Thus, mass traumas provide a unique opportunity
for shared painful experience (Bastian, Jetten, Hornsey, &
Leknes, 2014) and mutually reinforcing prosocial behav-
iors (von Dawans etal., 2012) that can, in turn, amelio-
rate preexisting distress and promote well-being (Argyle,
2001; Hawdon etal., 2012). Indeed, the broad impact of
shared human experience has likely been underesti-
mated (e.g., Boothby, Clark, & Bargh, 2014). The present
findings suggest that the distinction between solitary and
shared experience is worthy of far greater scrutiny than it
has received.
Our findings suggest potential modifications to the
dominant frameworks on social support and responses
to acute stress in at least two ways (e.g., Charuvastra &
Cloitre, 2008; S. Cohen & Wills, 1985). First, they question
the idea that mass traumas typically result in deteriora-
tion in social support, particularly when the disaster is
human-induced, as some theorists have suggested (e.g.,
Kaniasty & Norris, 2004). Second, the results suggest that
social support is a dynamic and changing quantity,
responsive to environmental conditions, as opposed to a
static quantity that is drawn on in times of need and buf-
fers our distress (S. Cohen & Wills, 1985), which has been
the traditional way social support that has been viewed.
Unfortunately, the vast majority of research on social sup-
port is conducted after an acute stressor has occurred
and thus cannot document changes in social support.
Given that we found increases in social support, the cur-
rent findings suggest that people are not merely passive
recipients of social support but instead may actively seek
to shape their social environments in accordance with
their immediate needs (Taylor, 2006). Indeed, among
individuals who improved in anxiety and depression, the
effect size increase in social support was impressively
large, whereas it was smaller for persons identified as
resilient. In this sense, social behavior may be properly
viewed as a homeostatic mechanism whose regulation is
controlled, like temperature or appetite, by the individual
(Taylor, 2006). When this regulation is effective, individu-
als may be able to protect themselves from the harmful
effects of acute stress.
Moreover, this regulation may not only buffer dis-
tress, it may also directly promote improvements in
psychological functioning. Existing theories offer little
explanation for this possibility. Why, then, would a sub-
set of participants improve in their psychological func-
tioning after the shooting? One possibility, of course, is
that the observed improvement trajectory merely
reflects the variable course of anxiety and depression
symptoms generally. We cannot preclude this possibil-
ity with the present data. However, note that the
improvement group, when compared with resilient
individuals, reported high levels of depression and
anxiety before the shooting and low levels of social
support. As their distress improved, their social support
did as well. Although this relationship is correlational,
we would argue that the mobilization of supportive
relationships served not only to protect them from dis-
tress but also to enhance well-being generally. Indeed,
strong and active social relationships have a robust
relationship to well-being, and are likely a sine qua non
of happiness generally (Diener & Seligman, 2002). After
mass traumas, communities tend to bind, grievances
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414 Mancini et al.
tend to be forgotten, and feelings of solidarity and com-
mon purpose tend to increase (Solnit, 2009), all of
which may contribute to well-being. As discussed ear-
lier, the prospective nature of our research design
allowed us to document these positive changes in
social support.
A complementary explanation for improvement is
found in research and theory on affect regulation after
painful experiences (Bastian, Jetten, Hornsey etal., 2014;
Leknes, Brooks, Wiech, & Tracey, 2008). The pain of a
mass trauma may have the ironic effect of disrupting a
preexisting syndrome of distress by providing a sense of
relief from current stressors. As Fritz (1961/1996) observed
decades ago, disasters “provide a temporary liberation
from the worries, inhibitions, and anxieties associated
with the past and the future because they force people to
concentrate their full attention on immediate moment-to-
moment, day-to-day needs” (p. 61). Consistent with this
perspective, recent research has demonstrated that relief
from pain has potent effects on mood, stimulating
increased positive and decreased negative affect (Franklin,
Lee, Hanna, & Prinstein, 2013), and may therefore coun-
teract preexisting negative mood states, as well as pro-
moting social behaviors and more adaptive coping
associated with positive emotion (Bonanno, 2004).
In the context of these findings, it is important to note
a number of limitations to the present study. A principal
limitation is that the sample was composed only of
women. Thus, the present results cannot be generalized
to men. However, recent research has found that men
also respond to acute stress with increased sharing and
cooperative behaviors (von Dawans etal., 2012) and thus
may also experience psychological benefits. Moreover,
research conducted with military samples, which are
largely men, have provided consistent evidence of psy-
chological improvement among a subset (usually 8% to
12%) of deployed soldiers (Bo Andersen et al., 2014;
Bonanno etal., 2012; Dickstein etal., 2010; Nash etal.,
2014). Another limitation is that our sample consisted of
traditional-aged college students, was largely White, and
differed slightly in baseline social support from the larger
pool of potential participants. The broader generalization
of these findings to more diverse samples is an important
topic for future research.
An additional limitation is that the relationship between
adjustment trajectory and change in social relationships
is correlational. Although we believe there is a compel-
ling rationale for a causal relationship, our research
design does not permit such an inference. As a result, the
direction of the relationship between social factors and
adjustment is unclear; nor can we rule out the possibility
that a third variable is responsible for the observed asso-
ciation. Nevertheless, on the basis of the theoretical ratio-
nale, we would argue that mutually reinforcing prosocial
behaviors induced by the acute stress of the shootings
led to improvements in psychological health among a
subset of survivors with high pre-event distress. Indeed,
individuals who did not see improvements in social rela-
tionships reported either worsening psychological symp-
toms or a continuation of existing distress. Nevertheless,
however plausible this rationale, it cannot be ruled out
that reductions in anxiety and depression led to increased
social behavior. Finally, we cannot rule out that the
observed trajectories reflect normative patterns of adjust-
ment to college and are unrelated to the shootings,
though, given their enormity, this possibility seems
unlikely.
The improvement pattern has a number of theoretical
and clinical implications. One clear implication is that
social factors are critical in the aftermath of an acute
stressor. Although this is certainly not new knowledge,
the present findings suggest that improving people’s
capacity to increase their stock of social resources—after
a mass trauma—can have potent effects that are both
ameliorative (in the case of the improvement trajectory)
and stress-buffering (in the case of the resilient trajec-
tory). The difference between this perspective and previ-
ous work on social support (e.g., S. Cohen & Wills, 1985)
is to some extent a matter of emphasis. The present find-
ings suggest that it is not just preexisting social resources
but the recruitment and utilization of existing and addi-
tional resources that is critical. This was particularly evi-
dent, for example, in the sharp distinction between the
improvement and continuous distress trajectories. At
baseline, both groups reported high levels of distress and
low levels of social support. However, at 12 months, the
improvement group had seen dramatic changes and was
eventually indistinguishable from the resilient group in
their social and psychological functioning. By contrast,
the continuous distress group showed no change in their
social relationships and remained mired in a syndrome of
distress. A better understanding of why the two groups
saw such sharply diverging trajectories is a critical topic
of future research. At a minimum, however, the present
research strongly suggests that a promising target of
intervention is the mechanisms and perceived availability
of social support. The most robust effects appear to occur
for interventions that target cognitions about social rela-
tionships (Masi, Chen, Hawkley, & Cacioppo, 2011).
Persons with more acute initial stress reactions and with
vulnerabilities to a perceived lack of social support (e.g.,
persons high in anxious or avoidant attachment;
Shallcross, Howland, Bemis, Simpson, & Frazier, 2011)
may therefore benefit from interventions that include a
focus on social cognitions. By the same token, given that
the majority of the sample were resilient or improved, the
present findings further underscore the dangers of blan-
ket early interventions designed to forestall posttraumatic
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Social Support, Improvement, and Virginia Tech 415
stress disorder reactions (Lilienfeld, 2007). Indeed, the
improvement trajectory offers a remarkable demonstra-
tion of natural recovery processes.
Jean Rhys (1966), in her novel Wide Sargasso Sea,
wrote, “When trouble comes they say close ranks.” In the
present study, we found that survivors of the Virginia
Tech shootings who drew closer to others also experi-
enced psychological improvement. The potential for
acute stressors to catalyze positive psychological change
and repair psychological distress, a process very different
from posttraumatic growth, merits more empirical scru-
tiny than it has received.
Author Contributions
A. D. Mancini developed the manuscript concept, performed
the data analyses, and had primary responsibility for drafting
the manuscript. H. L. Littleton and A. E. Grills developed the
larger study design, supervised data collection, and contributed
revisions to the manuscript. H. L. Littleton drafted a section of
the manuscript. All authors approved the final manuscript for
submission.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
Funding
This study was supported by National Science Foundation
Grant BCS-0737940.
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