SELF-TALK AND RESILIENCE: IMPACTS OF PERFORMANCE IN
UNDERGRADUATES
As
3G
-2ol£,
A Thesis submitted to the faculty of
San Francisco State University
In partial fulfillment of
the requirements for
the Degree
Master of Arts
In
Psychology: Social Psychology
by
Zaviera Bonita Reyes
San Francisco, California
August 2016
Copyright by
Zaviera Bonita Reyes
2016
CERTIFICATION OF APPROVAL
I certify that I have read Self-Talk and Resilience: Impacts o f Performance in
Undergraduates by Zaviera Bonita Reyes, and that in my opinion this work meets the
criteria for approving a thesis submitted in partial fulfillment of the requirement for the
degree Master of Arts in Psychology: Social Psychology at San Francisco State University.
% J£JS
Seung Hee Yoo, Ph.D.
Assistant Professor of Psychology
Ezequiel Morsella, Ph.D.
Associate Professor of Psychology
SELF-TALK AND RESILIENCE: IMPACTS OF PERFORMANCE IN
UNDERGRADUATES
Zaviera Bonita Reyes
San Francisco, California
2016
While the factors are numerous, the mechanisms associated with the capacity for successful
outcomes despite challenging circumstances (i.e., resilience) remain underexplored. One
proposed mechanism is self-talk. Self-talk is a cognitive process that serves important
regulatory functions and is proposed to be influenced by individual’s dispositional
sensitivities to cues of reward and punishment. The role of self-talk in the relationship
between approach (BAS) and avoidance (BIS) predicting resilient outcomes was examined
across three studies with either a recalled or actual stressor. In Study 1, adults use of less
reassuring and greater persecuting self-talk mediated the relationship between avoidance
motivation (i.e., BIS) and less resilience while the use of greater reassuring self-talk
mediated the relationship between approach motivation (i.e., BAS drive and BAS funseeking) and greater resilience. In Study 2, the relationship between BAS drive was
replicated in students; yet, BIS predicted less resilience mediated only through the use of
less reassuring self-talk. In Study 3, the relationship between BIS and less resilience was
replicated from Study 2. Students’ use of motivational, positive, and reassuring self-talk
was associated with greater resilient outcomes whereas the use of critical self-talk styles
were associated with greater negative emotions pre-stressor, less resilience, greater anxiety,
and less positive emotions following an actual stressor. Neither motivation nor resilience
correlated with students’ performance scores but inadequate self-talk was associated with
higher scores on the actual stressor. Implications for the function of self-talk in a college
setting are discussed.
I certify that the abstract is a correct representation of the content of this thesis.
A u g u rt
Date
15.3-0*4
ACKNOWLEDGEMENTS
I would like to take this opportunity to thank my primary advisor Asst Prof. Seung Hee
Yoo who provided the guidance needed to encourage and refine my ambitious amount of
hypotheses into an impactful project. I also had the privilege of collaborating with my
secondary advisor, Prof. Ezequiel Morsella whose leadership, humility and rigor continues
to elevate the quality of my research and scholarship. Importantly, I wish to thank my
parents Debra and Sergio Reyes who both instilled the mindset to value success but not
view failure as catastrophic. Their insight and support on my doctoral path as a firstgeneration student has been tremendous. Lastly, I would like to sincerely thank my
boyfriend, Michael Huerta, who always inspires me to push myself and apply my research.
v
TABLE OF CONTENTS
List of Table............................................................................................................................viii
List of Appendices...................
ix
Introduction.................................................................................................................................1
Background.................................................................................................................... 1
Motivational Dispositions Predicting Resilience........................................................4
Self-Talk: A Predictor and Possible Indicatoro f Resilience....................................9
The Importance o f Students in Our Current Approach........................................... 12
The Present Research................................................................................................. 14
Method Study 1........................................................................................................................ 15
Participants.................................................................................................................. 15
Materials and Procedure............................................................................................15
Results Study 1 ........................................................................................................................ 18
Self-Talk as a Mediator between Avoidance (BIS) and Resilience fo r Adults....... 18
Self-Talk as a Mediator between Approach (BAS) and Resilience fo r Adults.......20
Adult Recalled Stressor Self-talk Scored with the STiA...........................................24
Discussion Study 1...................................................................................................................24
Method Study 2 ........................................................................................................................25
Participants..................................................................................................................25
Materials and Procedure........................................................................................... 26
TABLE OF CONTENTS CONTINUED
Results Study 2 ........................................................................................................................27
Self-Talk as a Mediator between Avoidance (BIS) and Resilience fo r Students....21
Self-Talk as a Mediator between Approach (BAS) and Resilience fo r Students....28
Student Recalled Stressor Self-talk Scored with the S T iA .......................................30
Discussion Study 2 ...................................................................................................................31
Method Study 3 ........................................................................................................................ 32
Participants..................................................................................................................32
Materials and Procedure............................................................................................32
Results Study 3 ........................................................................................................................ 35
Self-Talk as a Mediator between Avoidance (BIS) and Resilience fo r Students.... 3 5
Student Motivation Sensitivity and Resilience to an Actual Stressor.....................37
Student Self-Talk and Resilience to an Actual Stressor...........................................38
Student Actual Stressor Self-talk Scored with the STiA........................................... 39
General Discussion..................................................................................................................40
Conclusion............................................................................................................................... 46
References................................................................................................................................ 47
Tables........................................................................................................................................67
Appendix.................................................................................................................................. 69
LIST OF TABLES
Table
Page
1. Correlations with predictors and resilient outcomes in adults (recalled)
67
2. Correlations with predictors and resilient outcomes in students (recalled)....68
3. Correlations with predictors and resilient outcomes in students (actual)
viii.
68
LIST OF APPENDICES
Appendix
1. In class thought-listing task
Introduction
Background
Imagine you are on your way to be evaluated in a domain you are motivated to do
well in. You may say to yourself privately or out loud: “I am so bad when it comes
to .. .and hate getting critiques” or “I can do this.. .1 will use the feedback to improve for
the next round”. Self-evaluative statements such as these refer to the cognitive skill of
self-talk and likely influence whether one is able to ‘bounce back’ from stressors. While
it may not have been difficult to picture this situation, there was likely one style of self­
talk that appeared more or less helpful in meeting your goal. Just as there are differences
in how one responds to positive experiences there is also great variability in how
individuals evaluate and respond to adversity (Bowman, 2013; Rutter, 2012).
Even seemingly minor stressors can have an immediate and/or accumulating
negative impact on well-being (Almeida, 2005; Davis, Luecken & Lemery-Chalfant,
2009; DeLongis, Coyne, Dakof, Folkman, & Lazarus, 1982). As a result, resilience is not
limited to traumatic life events (Reyes et al., 2016b; Seery & Quinton, 2016). Although
stress can be harmful, the experience of stress or other negative emotions is vital in
strengthening flexible responses (Kashdan & Biswas-Diener, 2014) that diminish the
likelihood of viewing stressors as catastrophes. While not new, this claim that a life
devoid of stress robs the individual of the opportunity to build resources and practice
skills key in adaptively responding to every day struggles and life changing events
(Lazarus & Folkman, 1984) has received growing interest. Barber (2013, para. 3)
captures the importance of experiencing adversity with the following analogy: “a
straight-A student [or] an untested employee is like an untried soldier, liable to break
down from real world difficulties and challenges”. Despite the frequent use and
regulatory nature of self-talk in regards to stressful life events, the following project is the
first to examine how self-talk may be shaped by one’s sensitivity to rewards and
2
punishment and lead to resilient outcomes. By drawing on findings from reinforcement
sensitivity theory and the self-talk framework in spots, I propose an in integrated model
for the study of mechanisms underlying one’s capacity for resilience.
Both self-talk and resilience researchers have been prolific in their empirical
contributions; however, distinct populations and a multitude of definitions for what
constitutes resilience or self-talk has strained the dialogue that sustains scientific
progress. Paradoxically, resilience has been described as ‘ordinary magic’ (Masten, 2011)
yet primarily examined among traumatic event survivors (Jones, Wojcik, Sweeting, &
Silver, in press; Masten & Osofsky, 2010; Yehuda & Flory, 2007). Similarly, athletic
populations (Hardy, 2006; Hatzigeorgiadis, 2006; Mahoney & Avener, 1977; Van Raalte
et al., 1994) dominate the self-talk literature despite self-talk reported in 80%
(Brinthaupt, Benson, Kang, & Moore, 2015) to 96% of adults (Winsler, Feder, Way &
Manfra, 2006). In a study on undergraduates discussing a recent stressful event (Reyes et
al., 2015), we observed self-talk spontaneously occur in 70% of the conversations.
Limiting the study of resilience and self-talk to these non-representative
populations perpetuates the current trend in the field of social Psychology whereby
phenomena are not examined in a way that captures what occurs in the real world
(Funder, 2015). As a result of the sensational nature of the phenomena and individuals
studied, there is a paucity of theoretically guided research particularly in the resilience
literature.
To best appreciate the complex yet basic human adaptive behavior known as
resilience it is helpful to begin with a brief overview of the dominant views in the
literature. Three central perspectives have advanced the resilience literature to this point.
Each view has contributed substantially and discrepancies pertain largely to the questions
poised, timeframe of stressor, and sample under investigation. The oldest view describes
resilience as a trait. Credited as the first in Psychology to use the term, Jack Block (1950)
defines the stable disposition of individuals to enact “motivational control and
resourceful adaptation” as falling on a spectrum between ego-resiliency and ego-
3
brittleness (Block & Kremen, 1996, p. 351). For the most part, this perspective has
received substantial criticism and researchers demarcate themselves from this static
conceptualization by abstaining from the term ‘resiliency’ due to the connotation it has as
a fixed trait. It is yet unclear as to whether the preliminary identification of
neurobiological mechanisms that confer resilience will be in support or refute the fixed
nature of resilience due to environment interactions (Russo, Murrough, Han, Chamey, &
Nestler, 2012) and the proposal by Walker and colleges (2016) that it is unlikely any
single biomarker can effectively categorize varying levels of resilience.
A more widely accepted view proposed by developmental researchers refers to
resilience as a dynamic process (Luthar, Cicchetti & Becker, 2000; Masten 2014) that
integrates individual, societal, and familial factors (Werner, 2005). This definition
emphasizes the examination of enduring stressors and how protective factors unfold over
time. Protective factors within the individual include cognitive skills and dispositions
whereas societal and familial factors involve external sources of support (Werner, 1993).
One final way to view resilience is as an outcome. Researchers examining acute
stressors, typically in adulthood, categorize resilience as an outcome or a person’s
adaptive response to a specific stressor (Mancini & Bonanno, 2006). Some researchers
argue the distinction between a process and outcome primarily reflects one’s hypothesis
and study design. In contrast, Yates, Egeland & Sroufe (2003) affirm resilience is
inextricably tied to a child’s developmental story and thus can only be considered a
process—not an outcome. While the authors agree resilience is a dynamic construct
shaped by experiences, the present studies were conducted within a brief period of time
and therefore best fit the definition of resilience as an outcome. Furthermore, the
conceptualization of resilience as an outcome lends itself best to identifying general
resilience mechanisms associated with a variety of positive traits and developmental
processes (Kalisch, Muller, & Tuscher, 2015). As a result I adopted the definition of
resilience as “an outcome or capacity for successful adaptation despite challenging
4
circumstances” (Masten, Best, & Garmezy, 1990, p. 426) and expand it to encompass
stressful life events.
Research that implements distinct and sometimes contradictory interpretations of
what it means to be resilient invariably leads to issues with how best to capture it. On a
fundamental level there exists a debate concerning whether resilience is an observable
phenomenon. Jutersonke & Kartas (2012) point out that “resilience is part of the external
observer’s vocabulary used to make sense of what is being observed, rather than a term
that is necessarily meaningful to the individuals involved” (pg. 4). The following series
of studies takes special care to define resilience in such a way as to promote the study of
tangible positive outcomes such as performance, adaptive emotion regulation, and active
engagement with one’s environment. Importantly, the prospective goal of this work is to
identify mechanism associated with resilience. Specifically, to test whether learnable
cognitive skills such as self-talk can be practically applied in academia and beyond.
In the past few decades researchers have proposed numerous factors associated
with resilience. External protective factors include perceived social support (Sarkar &
Fletcher, 2014; Werner, 1993), intermittent exposure to brief periods of adolescent stress
(Meichenbaum, 1977; Romeo, 2015), and socioeconomic status (Garmezy, 1985).
Internal protective factors include an internal locus of control (Rotter, 1966), sense of
belonging (Bozak, 2013; Gonzalez & Padilla, 1997), positive emotionality (Tugade &
Fredrickson, 2004) and self-efficacy (Lee et al., 2013). What remains less understood,
and presumably fewer in number, are the mechanisms underlying how these often
overlapping factors promote resilient outcomes. In the present study, I propose
motivational dispositions (e.g., approach and avoidance sensitivities) and self-talk as two
factors related to individuals’ capacity to navigate stressful situations and achieve
resilient outcomes.
Motivational Dispositions Predicting Resilience
Stressful events are inherently emotional (Lazarus, 1999) and to make sense of
emotions necessitates an understanding of one’s motivation (Lazarus, 1991). Individual
5
differences in motivational dispositions contribute to one’s view of a potentially aversive
situation as an opportunity as opposed to an obstacle. Individuals’ naturally appraise
situations on a challenge—threat continuum and these appraisals reinforce behavioral
approach or avoidance sensitivities. As noted by Elliot (2006), this dual set of action
tendencies (e.g., approach/appetitive and avoidance/inhibitory) was identified in the
infancy of Western Psychology by William James (1890) who observed the powerful
reinforcing nature of pleasure and the inhibitory power of pain. Since this early work,
there has been an undulating and enduring interest across disciplines to understand the
impetus for appetitive and aversive motivation conceptualized through valence-based
processes (Lewin, 1935; Miller, 1944) and overt-behaviors (Schneirla, 1959).
The approach-avoidance distinction has appeared in various forms evolving to
integrate new evidence and theoretical perspectives. Some conceptualizations germane to
the study of resilience include the need for achievement/avoidance of failure (Atkinson,
1957), challenge/threat responses (Lazarus & Folkman, 1984; Tomaka, Blascovich,
Kibler, & Ernst, 1997), promotion and prevention focus (Higgins, 1997), and selfregulatory systems embedded in discrepancy reducing/enlarging feedback loops (Carver,
2006; Carver & Scheier, 1998). A highly influential neurophysiological based theory
concerning these differences is the original (Gray, 1972) and revised (Gray &
McNaughton, 2000) Reinforcement Sensitivity Theory (RST). Gray and colleagues
postulate that dispositional variations in behavior correspond to the sensitivity of adaptive
neural systems in responses to reinforcing and punishing events. In a comprehensive
review by Pickering & Corr (2008), the foundation of RST is described as based on short­
lived expressions of emotion and overt behavior in response to relevant environmental
cues. Accordingly, these responses become a relatively stable part of one’s emotional and
behavioral repertoire. Following revisions to the RST, behavioral avoidance is associated
with the behavioral inhibition system (BIS) which serves to detect reward-punishment
conflict and direct action towards the fight-flight-freeze system (FFFS) which is sensitive
to aversive stimuli such as signals of punishment—formerly ascribed to the BIS— and
6
non-reward (Berkman, Leiberman, & Gable, 2009; Corr, 2004). The behavioral approach
system (BAS) is associated with the pursuit and sensitivity towards reward, exploration,
and impulsivity and non-punishment (Laricchiuta & Petronsini, 2014).
In the present study, I will focus on the BIS and BAS systems. Originally
proposed to function separately, either the BIS or the BAS controlled one’s behavior at
any given time; however, the scarcity of empirical support led to the examination of
interactive influences between these two systems (Bijttebier, Beck, Claes &
Vandereycken, 2009; Mortensen, Lehn, Evensmoen, & Kaberg, 2015).
While extensive in the research the RST inspired, there remain several caveats
within the approach-avoidance framework that must be addressed before making a claim
about motivational disposition influence on self-talk and resilience. Despite the
orthogonal nature suggested by these dual action-sets, converging evidence along with
the joint-subsystems hypothesis (Corr, 2001, 2002) suggest the BIS and BAS systems are
interdependent (as opposed to independent) systems and are not exclusively tied to either
positive or negative affect (Aarts, Custers, & Holland, 2007; Carver, 2004). For example,
BAS activated goal pursuit can lead to one experiencing frustration and anger over
perceived or actual failure. Furthermore, situations can interact with individual
differences in disposition. Situations become more demanding when there is a mismatch
between a person’s dispositional motivation (i.e., BIS/BAS sensitivity) and their
environment (Cohen & Roth, 1984; Miller & Mangagn, 1983).
In an academic context, a mismatch may be beneficial and can arise from faculty
involvement which is associated with increased persistence and greater social integration
particularly in four-year institutions (Braxton, Sullivan, & Johnson, 1997; see Tinto, 1998
for review). For example, a student who typically doesn’t raise his hand during class
may, in response to a relevant positive external stimulus such as encouragement from a
graduate student, become motivated to engage with the small group of students around
him during class thereby reinforcing approach-related behaviors. Results and practical
examples such as these demonstrate that motivational dispositions facilitate a greater
7
accessibility for emotions and behavioral patterns that are crucial in evaluating
potentially aversive situations as manageable. As a result, approach or avoidance
sensitivities can facilitate or antagonize one’s capacity for resilience.
Recent research finds that motivation sensitivities influence one’s emotional and
behavioral experience leading to individual differences in resilient outcomes. As Carver
(2006) notes, the approach system is sensitive to the pursuit, motivation, and experience
of positive emotions as a result of obtaining incentives. This sensitivity to positive
emotions likely relates to one’s capacity to cultivate positive emotions which bolsters
resilience by creating a buffer against stressors (Tugade & Fredrickson, 2004).
Additionally, approach sensitivity functions as a means to identify and create plans to
achieve one’s goals (Corr, 2008) and is generally attributed to adaptive functioning
(Elliot, 1999).
The avoidance system has less established links to resilience in the literature yet
observations such as a student not raising her hand for fear of looking stupid or a
professor avoiding meetings due to scrutiny encouraged me to examine this empirically.
In contrast to the approach systems’ sensitivity to the pursuit of goals, the avoidance
system is activated through impeded goals which promotes increased vigilance
(McGregor, Gailliot, Vasquez, & Nash, 2007). The avoidance system centers on anxiety
associated with a sensitivity to threat or punishment (Carver, 1994) that exacerbates
negative feelings about the situation and the self—both of which serves to deplete one’s
capacity for resilience. To further compound this, avoidance-related goals “represent the
absence of a negative outcome or end state” (Hiempel, Elliot, & Wood, 2006, p. 1295).
Simply put, avoidance sensitive individuals maintain a hypervigilance to negative
internal and external cues that are prolonged through an inability to accurately and
effectively engage with a stressful encounter.
The implications of the relationship between motivation and resilience is highly
relevant to a student population. Van Beek and colleagues (2013) found that among
university students, behavioral avoidance sensitivity was associated with academic
8
bumout (i.e., intention to quit one’s studies, and exhaustion) whereas behavioral
approach activation was associated with study engagement. Additionally, behavioral
avoidance is associated with increased rumination and more pronounced response to
negative emotions (Leen-Feldner, Zvolensky, Feldner & Lejuez, 2004). Avoidance
sensitivity was also proposed as a mediator between students’ perfectionism and their use
of maladaptive coping styles (Randles, Flett, Nash, McGregor, & Hewitt, 2010). Most
recently and in support of the current project, approach sensitivity was associated with
the experience of greater positive affect which serves as a protective factor contributing
to resilience in undergraduate and graduate students (Corral-Frias, Nadel, Fellous &
Jacobs, 2016). The current study sought to not only re-examine in detail (e.g., through
including all BIS/BAS subscales) these associations between dispositional motivation
sensitivities and resilience, but to also explore whether self-talk could mediate the
relationships for both approach and avoidance sensitivity students.
As the two base dimensions of personality (Gray 1972), approach and avoidance
motivation systems are likely associated with consistent patterns of thoughts, feelings,
and behaviors manifested via self-talk. Motivational dispositions have been proposed as
antecedents of self-talk (Van Raalte, Vincent, & Brewer, 2016; Zourbanos, Papaioannou,
Argyropoulou, & Hatzigeorgiadis, 2014) that work in concert with situational factors
(Hardy, Oliver, & Tod, 2009) to shape and meet goals. Given the aforementioned
relationship between avoidance and approach with either halting or pursuing goals, I
argue these sensitivities are distilled in one’s self-talk. Differences in goal-related self­
talk have also be attributed to students’ self-regulated learning and emotion regulation
(Wolters, 2003). Importantly, self-talk strategies shaped through one’s motivational
disposition are frequently implemented in a college setting (Wolters, 1998; Reyes et al.,
2015; Reyes & Yoo, 2016a)
9
Self-Talk: A Predictor and Possible Indicator of Resilience
The study of self-talk has experienced considerably less attention than one might
expect with regard to resilience given the important self-regulatory role it facilitates and
the implications self-regulation has beyond performance enhancement. As discussed
earlier, this gap in the literature concerning the study of self-talk and resilience may be a
result of conceptual ambiguity coupled with a majority of self-talk findings coming from
disparate populations across developmental, clinical and sports psychology. To-date, the
present studies are the first to acknowledge the mediating role of self-talk in motivation
contributing towards resilience. While once presumed to diminish after early childhood
(Vygotsky, 1987), converging evidence suggests self-talk is maintained throughout early
adulthood. Duncan and Cheyne (1999, 2002) found that self-talk regularly occurred
among undergraduates and was most frequent during difficult tasks which highlights the
enduring function of self-talk to aid in self-regulation and problem solving long after
childhood.
Self-talk is broadly defined as a cognitive process that represents an individual’s
thoughts about themselves, others, and their world (Calvete & Cardenoso, 2002). Implicit
in this definition is that self-talk is by nature self-directed and evaluative. Self-talk can be
spoken overtly (aloud) or privately in one’s head and includes the following series of
actions in response to emotionally evocative situations: (1) interpret one’s feelings and
perceptions, (2) regulate and change one’s self-evaluations, and (3) provide the self with
reinforcement/critique/instruction (Hackfort & Schwenkmezger, 1993). Along with this,
self-talk is proposed to convey information under a different form (i.e., words) that can
be reframed and utilized as a self-regulatory strategy (Kross et. al, 2014; Morin, 1993).
Additional support for the relationship between self-talk and resilience comes
from the notion that “resilience cannot be separated from self-regulatory mechanisms”
(Benight & Cieslak, 2011, pg. 52). The idea that self-talk informs us of emotions,
thoughts and ideas that we already have may seem inconsequential; however, talking to
oneself is an important cognitive ability influencing attention and appraisal processes to
10
meet cognitive and emotional demands (Hatzigeorgiadis, Zourbanos, Galanis, &
Theodorakis, 2011; Lazarus, 1991; Meichenbaum, 1977). The present studies aimed to
explore the empirically congruous, yet scarcely integrated, relationship between self-talk
and resilience among college students.
Previous examinations of self-talk focused on two overlapping dimensions:
valence (positive or negative) and function (instructional or motivational). In addition to
discussing the frequency and specific dimensions of each self-talk strategy we refer to the
array of reassuring and motivational cues as positive self-talk and those associated with
self-critical and destructive cues as negative self-talk. Positive forms of self-talk are
typically associated with increased self-efficacy (Pintrich, 2004; Reyes & Yoo, 2016a),
task interest (Sansome, Wiebe, & Morgan, 1999), emotion regulation ability (Brackett,
Palomera, Mojsa-Kaja, Reyes, & Salovey, 2010; Fredrickson, 1998, 2001; Kross et al.,
2014; Reyes et al., 2015), and the experience of positive emotion states regardless of
situational experience (Oliver, Markland & Hardy, 2010; Reyes & Yoo, 2016b).
In contrast, negative forms of self-talk are most commonly associated with threat
appraisals (Chen & Jackson, 2005), less perceived social support (Zourbanos et al.,
2011), increased anxiety (Cacioppo, Glass & Merluzzi, 1979; Shi, Brinthaupt, & McCree,
2014) and less resilience (Reyes & Yoo, 2016b). Within the athletic literature, key
differences between the effectiveness of specific types of self-talk have been
documented. Motivational self-talk is most useful when there is a long-term goal or
endurance is needed whereas instructional self-talk implements the skills and strategy of
talking oneself through steps that focus or direct attention and work best during tasks that
are precision based (Hatzigeorgiadis et al., 2011). This increased effectiveness attributed
with fitting self-talk to meet situational demands is referred to as the task-matching
hypothesis (Hardy et al., 2009; Theodorakis et al., 2000). To complement this, although
assessed as a trait, Waugh and colleagues (2011) found resilience was associated with
greater flexibility in emotional responding. It follows that the concept of fit as opposed to
a rigid adherence to a single style of self-talk is likely a powerful predictor of resilience.
11
Self-talk represents a self-schema reinforced by internal and external influences
that speaks to—possibly unbeknownst to the individual— one’s capacity to respond to
stressful events (i.e., resilience). Resilience necessitates an interdisciplinary study (Luthar
& Zelazo, 2003) and is not an ‘all-or-nothing’ phenomenon which lends itself to being
examined in one’s self-talk. Self-talk carries with it an integration of views concerning
one’s capacity and expectations. Although self-talk is largely referred to as an
intrapersonal process, the bidirectional social influences of significant others (i.e., faculty
members, mentors, and family) have been manifested in the academic experiences for
both students and instructors. In a rare examination of university teachers, Hall &
Smotrova (2013) found that professors who engaged in self-talk during stressful
situations that occurred during lectures (i.e., technical difficulties or unexpected
distractions) elicited greater empathy from students, whereas instructors who did not
utilize overt self-talk evoked disengagement from their students. Similarly, an eight-year
longitudinal study among students and teachers conducted in Australia revealed it was the
‘simple things’ such as being attuned to students’ perspectives and needs, engaging in
positive influences, and being accessible that made an impact on students’ resilience,
well-being and academic engagement (Johnson, 2008).
While these results were obtained from a sample of adolescents, the relationship
between instructor and student can remain highly impactful for undergraduate and
graduate students given the transitions, unique set of demands and independence
associated with the college experience. Exposure to positive experiences through mentors
can also ameliorate previous negative experiences (Day, 2006). In-line with this, self-talk
represents a potent and socially influenced indicator of one’s ability to pursue or abandon
goals. The impact of one’s inner monologue captured overtly or covertly carries with it
appraisals of oneself and one’s world that have the propensity to surface in conversations
(Reyes et al., 2015) and indicate to others—and sometimes ourselves—our capacity to
achieve a resilient outcome.
12
Perhaps most critical to this notion of self-talk as an index of resilience involves
the articulation of self-talk as a marker of psychological fitness. Self-talk is frequently
included in psychological interventions such as cognitive behavioral therapy (Kendall &
Treadwell, 2007; Lotfi, Eizadi-fard, Ayazi, & Agheli-Nejad, 2011; Meichenbaum, 1977)
and as a result has been empirically linked with a host of psychological disorders among
student populations including social anxiety, depression, and test-taking anxiety. As the
shift from a purely deficit based model of mental health in Psychology gave rise to the
study of resilience (Southwick, Bonanno, Masten, Panter-Brick, & Yehuda, 2014), the
authors propose a similar conceptualization for self-talk. I begin by examining self-talk as
not only an indicator of maladaptive self-regulatory strategies and irrational beliefs, but
also as an index of one’s capacity for resilience. In-line with other researchers, our use of
self-talk refers to both automatic and deliberate self-statements (Hardy et al., 2009) that
can reveal important individual differences through the language with which a person
describes views of their world and their capacity to respond to situations—both of which
are hallmarks of resilience. It is with this in mind that the examination of self-talk can
also be in service of developing an accurate means to measure the complex relationship
between one’s thoughts, feelings and behaviors that either enhances or diminishes one’s
likelihood to achieve positive outcomes as a result of stressful life events.
The Importance of Students in our Current Approach
Resilience research can benefit tremendously from examining a college
population that experience a myriad of evaluation based transient stressors. A lack of
interest in identifying which patterns of behavior work in conjuncture with students
environmental and personal characteristics come at great financial and personal cost.
According to the US Department of Education, $9.1 billion was spent by state taxpayers
from 2003 to 2008 to fund the education of students who did not return after their second
year. Tinto argues (1999) that research into the culture of institutions are also crucial in
promoting student success. A prerequisite for success in college involves initiative, self­
regulation, and autonomy (Chemers, Hu & Garcia, 2001) all of which have strong
13
empirical ties to resilience, motivation, and self-talk. In the study of academic
achievement in college students, attention has largely focused on the importance of
personality and various coping styles (Austin, Saklofske, & Mastoras, 2010; Komarraju,
Karau, & Schmeck, 2009; MacCann, Fogarty, Zeidner, & Roberts, 2011; Poropat, 2009).
The results of such research are credited with demonstrating academic success is not
purely contingent on intelligence (Richardson, Abraham, & Bond, 2012). A unique
feature embedded in the college environment which these works fail to capture, and what
is robustly evident in self-talk, is the importance of being able to seek out and be open to
feedback. Just as resilience serves as a basic adaptation response, self-talk represents a
flexible skillset that can be implemented by students and promoted via institutions to
successfully respond to a variety of stressors.
Undergraduates are called to navigate an environment that encompasses “both
social and academic systems” (Tinto, 1975, pg. 92) which present a greater challenge for
students unfamiliar with academia (e.g., first-generation, transfer students, international
students). The following series of studies involves recruitment of San Francisco State
University (SFSU) students which provided a robust sample with which to examine
resilience as 30% of incoming freshman are first-generation students. College involves
selecting a major, initiating life-long mentorships, managing time and interacting with
peers and a rotation of tenured and untenured faculty—all of which expose students to the
opportunity to fail and restructure goals. Given this, the authors propose the function of
self-talk to guide resilience to achieve goals is particularly salient in a college population.
14
The Present Research
In the following studies, I examined the relationship between motivational
systems (e.g., approach/avoidance behavioral dispositions) and resilience. This work is
based on parallel but previously unintegrated research that find approach motivation
(Chamey, 2004; Corral-Frias et al., 2016) and reassuring self-talk (Masten, 2001; Neff,
Rude, & Kirkpatrick, 2006) are associated with resilience whereas avoidance motivation
(Bijttebier et al., 2009; Markarian et al., 2013) and critical self-talk (Gilbert, Baldwin,
Irons, Baccus, & Palmer, 2006) are associated with poor psychophysiological
functioning. Through a novel synthesis of existing results, I propose the following model
whereby motivational dispositions are related to one’s capacity to achieve resilient
outcomes through the use of reassuring or critical forms of self-talk.
This theory was examined in three studies that assessed resilience in response to
everyday stressors. In the initial study with adults, the model was tested using a thoughtlisting exercise about a recent stressful event and questionnaires that assessed general
motivational dispositions, self-talk used during setbacks, qualitative self-talk, and
resilience. For the second study, this model was directly replicated in an undergraduate
sample who also recalled a recent stressful life event. In the final study, I examined the
impacts of these relationships before and after an actual stressor in an undergraduate
population with additional outcome measures such as well-being, anxiety, and perceived
stress.
The two previously untested hypotheses across studies were that during stressful
life events (a) behavioral approach (BAS) sensitivity would lead to greater resilience
whereas behavioral inhibition (BIS) sensitivity would lead to decreased resilience, and
(b) the link between these motivation systems and resilience is mediated by the types of
self-talk one engages in during times of stress.
In response to the scarcity of empirically tested mechanisms within the resilience
literature, the overarching aim of the current project is to determine whether self-talk
15
presents an alternative and previously untested cognitive skill that contributes to both
protective and risk factors associated with resilient outcomes in undergraduates. Given
the importance of self-talk in our model, its accurate assessment is vital. To supplement
surveyed self-talk, I created the Self-Talk in Action (STiA; Reyes et al., 2015) coding
device. The STiA is amenable to self-reported and behavioral self-talk and available upon
request.
Study 1
To establish the relationship between motivation sensitivity and resilience,
participants’ reassuring and critical self-talk during setbacks, dispositional sensitivity of
behavioral approach system (BAS) and behavioral inhibition system (BIS), resilience,
and positive and negative affect were compiled using established questionnaires. It was
predicted that avoidance sensitivity would be negatively correlated with resilience and
mediated via critical forms of self-talk; whereas, approach sensitivity would be positively
correlated with resilience and mediated via reassuring self-talk styles.
Method
Participants. 180 M-Turk participants in the United States were recruited
through Amazon Mechanical Turk and completed the online study for $0.50. Data from
22 participants who failed to follow direction of the thought-listing task or contained
substantial missing data were removed from analysis. In addition, three participants were
excluded due to rating the stressful event as ‘not at all stressful’ or being more than three
standard deviations from mean avoidance sensitivity or mean approach sensitivity. The
remaining participant total was 155 adults (77.2% Female, 63.9%, Male 35.5%,
Transgender .6%, Mage = 33.7, SD= 11.1 years).
Materials and procedure. Participants first completed a baseline assessment of
positive emotions (a =
.8 3 )
and negative emotions (a =
.8 0 )
measured with the
10
item
International Positive and Negative Affect Schedule Short Form (I-PANAS-SF;
Thompson,
2 0 0 7 ).
Positive emotions included Inspired, Attentive, Determined, Active,
and Alert (M preposEmot =
3 .1 2 ,
SD =
.8 1 )
and negative emotions included Ashamed,
16
Nervous, Hostile, Upset, and Afraid (M preNegEmot =
1 .2 9 ,
SD =
.4 9 ).
Participants then
completed a thought-listing task (adapted from Cacioppo, Hippel, & Ernest
1997)
where
they were asked to recall a recent stressful life event (within the past six months). Once
they had a situation in mind, they were asked to continue to a different screen and
prompted to describe the stressful situation in detail. Participants then rated how stressful
the situation was for them on a scale of 1 (not at all stressful) to 5 (very stressful).
Participants generally reported very stressful events
(MstressRate
= 4 .6 3 , SD = .56). On a
separate screen participants were then presented with five text boxes with ample space to
list their thoughts about the self-generated stressor using the following prompt:
Now that you have ONE recent very stressful experience in mind, please describe
any thoughts you had about yourself which can be positive, negative and/or
neutral DURING the stressful situation. Ignore grammar, spelling, and
punctuation. Please be completely honest as your responses remain anonymous.
Below are the text boxes fo r you to record the thoughts you had about yourself.
Simply enter the first thought you had in the first box, the second in the second
box, etc. You can enter up to 5 thoughts, one thought per box.
Immediately after the thought-listing task, participants’ positive
(MpostPosEmo
=
3 .0 7 ,
SD = .88) and negative emotions
(M p0stNegEmo = 1 .6 1 ,
SD =
.7 7 )
were
assessed again as an additional indicator of resilience or the ability to ‘bounce back’ from
the thought-listing task concerning a salient and recent stressor. Following this,
participants completed randomly presented surveys to assess motivational disposition,
self-talk, resilience, and the experience of positive and negative emotions following a
thought-listing task. Motivational disposition was assessed using the Behavioral
Inhibition Sensitivity/Behavioral Approach Sensitivity Scale (BIS/BAS; Carver & White,
1994)
which consists of 2 4 items (four are filler items) rated on a four-point scale ranging
17
from 1 (very true fo r me) to 4 (very false fo r me) with all but two items reverse-scored so
that higher mean scores indicated stronger behavioral avoidance sensitivity. Behavioral
approach was divided into three subscales, BAS drive (M>m? = 2.82, SD = .65), BAS
reward (MReward = 3.46, SD = .43), and BAS fun seeking (MFmSeek = 2.91, SD = .65).
There was only one avoidance subscale BIS (MAvoid = 3.12, SD = .50). BAS drive (a =
.82) which consists of 4 items and is related to goal persistence including (e.g., “I go out
o f my way to get things I want”), BAS reward responsiveness (a = .65) consists of 5 items
related to excitement at doing things well and winning (e.g., “ When I get something I
want, Ifeel excited and energized”), BAS fun seeking (a = .74 ) consists of 4 items
related to the willingness to seek out and spontaneously approach potentially rewarding
experience (e.g., “/ crave excitement and new sensations”). The BIS subscale (a = .76)
consists of 7 items and is associated with punishment sensitivity (e.g., “Criticism or
scolding hurts me quite a bit”).
Resilience was assessed using the 25 item, well-validated Connor-Davidson
Resilience Scale (CD-RISC; Connor & Davidson, 2003) which assesses a variety of
resilience promoting behaviors. These items include “Having to cope with stress can
make me stronger”, “/ am not easily discouraged by failure”, and “During times o f
stress/crisis, I know where to turn fo r help” anchored on a 5 point Likert-scale 0 (Not true
at all) to 4 (True nearly all the time) with raw scores ranging from 1-100. Our sample of
adults had lower than average resilience scores comparable to other US adult samples,
MResiie = 66.04, SD = 15.53.
Self-talk was assessed two ways to capture general tendencies during stressors
and the presence or absence of actual self-talk response regarding a self-generated
stressful experience. The Functions of Self-Criticizing/Attacking and Self-Reassuring
Scale (FSCRS; Gilbert, Hempel, Miles, & Irons, 2004) which measures individual’s
critical and reassuring self-evaluations in the context of a setback or stressor (e.g., ‘when
things go wrong for me’) was used as a general assessment. Self-critical and selfreassuring statements coincide with well-studied and characterized dimensions of self­
18
talk including motivation and valence. This scale consists of 22 items containing two
self-critical subscales and one self-reassuring subscale in response to the prompt ‘ When
things go wrong fo r me: ’ rated on a 5-point Likert scale from 0 (Not at all like me) to 4
(Extremely like me). Inadequate self-talk (a = .87) consists of 9 items (e.g., “I remember
and dwell on my failings ”, “Ifeel beaten down by my own self-critical thoughts ”). Hated
self-talk (a = .86) consists of 5 items (e.g., “I call myself names”, “I have a sense o f
disgust with m yself’). Reassuring self-talk (a = .90) consists of 8 items (e.g., “I am gentle
and supportive with m yself’, “I encourage myself fo r the future ”). Higher mean scores
are associated with greater reassuring self-talk (M^eas = 2.07, SD = .89), inadequate self­
talk (Mi„ad = 2.27, SD - .90), and hcucu self-talk (MHated = 1.06, SD = 1.00) respectively.
The Self-Talk in Action coding scheme was used to detect the type and frequency
of self-talk cues present in free responses concerning self-evaluative thoughts about a
self-generated stressful experience. Each thought was scored for the following self-talk
cues: presence or absence of any self-talk cue, de/motivational self-talk (e.g., “I am
capable of helping my child” or “I am going to fail”), instructional self-talk (e.g., “I told
myself to stay calm and keep control”), and positive/negative self-talk (e.g., “I am good
at what I do” or “I’m so dumb for not studying earlier”).
Results
Self-talk as a mediator of the relationship between avoidance sensitivity and
resilience for adults.
To test my initial hypotheses that avoidance sensitivity would be negatively
correlated with resilience and this relationship would be mediated by self-talk, I first
conducted partial correlations between avoidance motivation and resilience while
controlling for positive baseline affect and found that avoidance motivation was
negatively correlated with resilience (r = -.35, p < .001) (see Table 1 for relationships
between predictors and resilient outcomes without controls). Baseline positive affect was
controlled for in all subsequent pathways to rule out the possibility that my findings are a
result of general positive emotions which are highly correlated with resilience.
19
To test my second hypothesis about the role of self-talk, mediation analysis were
conducted to examine whether the relationship between avoidance motivation and
resilience were mediated by reassuring or critical self-talk. Behavioral avoidance (i.e.,
BIS) was entered in the model as a predictor and resilience as the dependent variable with
all three styles of self-talk (i.e., reassuring, inadequate, and hated) entered simultaneously
as mediators. Exploratory data analysis revealed no issues with collinearity in the self­
talk styles given all VIFs < 2 which is the most conservative estimate of variance
inflation factors among predictors.
As shown in Figure 1, avoidance sensitivity was associated with less reassuring
self-talk, b* = -.45, p < .001 and reassuring self-talk led to a greater capacity for
resilience, b* = .66, p < .001 (after controlling for other forms of self-talk: b* = .57, p <
.001). In contrast, greater avoidance sensitive motivation was associated with increased
hated self-talk, b* = .24,p = .002 which led to decreased resilience, b* = - A \ ,p < .001
(after controlling for other forms of self-talk: b* = -.20, p < .01). Furthermore, the
strength of the relationship between avoidance motivation and resilience experienced a
73% reduction and decreased from b* = -.33, p < .001 to b* = -.09,/? = .22.
To determine the proportion of the relationship between avoidance motivation and
resilience that was mediated through these two self-talk styles, the PROCESS macro
(Hayes, 2015) was used to conduct bootstrap analysis with 5000 resamples. Inadequate
self-talk was not found to be a significant contributor to this relationship [-.03, .23] as the
95% confidence interval of the standardized indirect effect contained zero. Given the
positive and negative relationships in this model, there were negative indirect effect for
reassuring self-talk [-39, -.19] and hated self-talk [-.12, -.01] in this sample of adults.
20
Figure 1. Reassuring self-talk and Hated self-talk mediated the relationship between
avoidance motivation and resilience in adults (Study 1)
[LLCI: -.39, ULCI: -.19]
-.45s
Avoidance
Motivation
Reassuring
Self-talk
.66** (.57**)
-.33** (-.09)n
Inadequate
Self-talk
CONTROLLING FOR
B a s e l in e P o s it iv e
A ffect
Hated
Self-talk
[LLCI: -.12. ULCI: -.01
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for the remaining factors.
*p< .01, **p< .001
Self-talk as a mediator in approach motivation and resilience for adults
To test my first hypothesis that approach sensitivity would be positively
correlated with resilience and this relationship would be mediated by self-talk, I began
with a partial correlation between approach drive motivation and resilience while
controlling for baseline positive affect (r = .37,p < .001) (see Table 1 for relationships
between predictors and resilient outcomes without controls). In order to rule out the
possibility that results were boosted by general positive emotions, baseline positive affect
was controlled for across all subsequent pathways.
To test my second hypothesis concerning the role of self-talk, mediation analysis
were conducted to test whether the relationship between approach drive motivation and
21
resilience were mediated by reassuring or critical self-talk. Behavioral approach drive
(i.e., BAS drive) was entered in the model as a predictor and resilience as the dependent
variable with all three styles of self-talk (i.e., reassuring, inadequate, and hated) entered
simultaneously as mediators. As stated previously, exploratory data analysis revealed no
issues with collinearity in the self-talk styles given all VIFs < 2 which is the most
conservative estimate of variance inflation factors among predictors
As displayed in Figure 2, approach drive sensitivity was associated with less
reassuring self-talk, b* = .31, p < .001, and reassuring self-talk led to a greater capacity
for resilience, b* = .60,/? < .001 (after controlling for other forms of self-talk: b* = .51, p
< .001). Furthermore, the strength of the relationship between approach drive motivation
and resilience experienced a 45% reduction and decreased from b* = .38 ,p < .001 to b* =
.21, p < .001.
To determine the proportion of the relationship between approach drive
motivation and resilience that was mediated through reassuring self-talk, the PROCESS
macro (Hayes, 2015) was used to conduct bootstrap analysis with 5000 resamples.
Reassuring self-talk was a significant mediator of the relationship between approach
drive motivation and resilience as the 95% confidence interval of the standardized
indirect effect did not include zero [.09, .27]. Inadequate self-talk [-.05, 01] was not a
significant mediator in this model nor was hated self-talk [-.00, .08].
22
Figure 2. Reassuring self-talk partially mediated the relationship between approach drive
motivation and resilience in adults (Study 1)
[LLCI: .09. ULCI: .27]
3 X **,
Approach Drive
Motivation
Reassuring
Self-talk
.60** (.51**)
.38** (.21**)
Inadequate
Self-talk
L QNTROLIING FOR
B a selin e P ositive
A ffect
Hated
Self-talk
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for the remaining factors.
*p < .01, **p < .001
To test my first hypothesis that fun-seeking approach sensitivity would be
positively correlated with resilience and this relationship would be mediated by self-talk,
I began with a partial correlation between approach fun-seeking motivation and resilience
while controlling for baseline positive affect (r = .34, p < .001) (see Table 1 for
relationships between predictors and resilient outcomes without controls). In order to rule
out the possibility that results were due by general positive emotions, baseline positive
affect was controlled for across all subsequent pathways.
To test my second hypothesis regarding the contribution of self-talk, mediation
analysis were conducted to reveal whether the relationship between approach fun-seeking
motivation and resilience were mediated via self-talk. Behavioral approach fun-seeking
23
(i.e., BAS fun-seeking) was entered in the model as a predictor and resilience as the
dependent variable with only reassuring self-talk as a mediator.
As shown in Figure 3, approach fun-seeking sensitivity was associated with
greater reassuring self-talk, b* = .18,/> < .001, and reassuring self-talk led to a greater
capacity for resilience b* = .61, p < .001. Furthermore, the strength of the relationship
between approach fun-seeking motivation and resilience experienced a 39% reduction
and decreased from b* = .3 \,p < .001 to b* = 2 \ , p < .001.
To determine the proportion of the relationship between approach fun-seeking
motivation and resilience that was mediated through reassuring self-talk, the PROCESS
macro (Hayes, 2015) was used to conduct bootstrap analysis with 5000 resamples.
Reassuring self-talk was a significant mediator in the relationship between approach funseeking motivation and resilience given the 95% confidence interval of the standardized
indirect effect of reassuring self-talk did not include zero [.03, .22].
Figure 3. Reassuring self-talk partially mediated the relationship between approach funseeking motivation and resilience in adults (Study 1)
[LLCI: .03, ULCI: .22]
Reassuring
Self-talk
Approach
Fun-Seeking
31** ( 19**)
Resilience
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for remaining factors.
*p < .01, **p < .001
24
STiA coded recalled stressor self-talk in adults.
The Self-Talk in Action (STiA) coding scheme was used to assess qualitative data
collected through the thought-listing task. Two well-trained independent coders including
the first author scored each thought participants reported about a self-generated recent
stressful life event. Overall, 69% of participants’ thoughts included at least one self-talk
cue with participants listing two self-talk cues on average out of five possible. The most
prevalent self-talk used was valence self-talk (n = 104) with a majority of participants
using negative (78%) as opposed to positive (21%) self-talk. Motivational (n = 69) self­
talk was the second most frequently used with 72% engaging in demotivational self-talk
and 28% utilizing motivational self-talk cues. Instructional self-talk was the least frequent
type of self-talk present in only 14% of participants’ self-talk about a recalled stressor.
Discussion
These preliminary results provide support for the theoretically rich but
understudied relationship between motivation sensitivity and resilience in a sample of US
adults. Importantly, my predictions were robust even when controlling for baseline
positive affect which is strongly associated with resilience (Cohn, Fredrickson, Brown,
Mikels, & Conway, 2009). The purpose of Study 1 was to examine motivation sensitivity
and its relationship to resilient outcomes through the use of self-talk in a general
population.
Regarding approach motivation sensitives, these results suggest greater
responsiveness to goal persistent cues (i.e., BAS drive sensitivity) and a stronger
inclination to seek out potentially rewarding experiences (i.e., BAS fun-seeking
sensitivity) are associated with an increased capacity for resilience as mediated through
the use of reassuring self-talk during times of stress. Additionally, reassuring self-talk
also contributed to the relationship between greater avoidance sensitivity and a
diminished capacity for resilience.
25
In terms of avoidance motivation sensitivities, predicting less resilient outcomes,
we found an increased responsiveness to cues of threat or punishment (i.e., BIS
sensitivity) was associated with less capacity for resilience and this relationship was
partially explained through the use of more persecuting self-talk and less reassuring self­
talk. Surprisingly, a lack of reassuring self-talk was a stronger potential contributor to a
diminished capacity for resilience than an increase of persecuting self-talk for avoidant
sensitive adults.
These results build from accumulating evidence that resilience is associated with
one’s ability to recruit positive emotions despite stress (Davidson, 2000; Whelton &
Greenberg, 2005) and suggest the tendency to promote positive feelings towards the self
during times of stress may similarly promote greater resilient outcomes across
motivational dispositions. In-line with this, self-compassion promoted through reassuring
self-talk is associated with a flexible ability to restructure stressful events in a more
manageable way (Allen & Leary, 2010). While my findings offer preliminary support for
the relationship between motivation sensitivity and resilient outcomes, there are a few
limitations that must be addressed prior to making any claims. First, as this is a newly
proposed model, further replications are needed to validate these results. Second, before
any claims regarding how applicable these relationships are in an academic context this
model must be tested in a student sample as there are a unique cocktail of stressors
associated the college experience that may reveal distinct motivation orientations and
self-talk styles.
Study 2
Method
Participants. Data was collected online from 151 San Francisco State University
Psychology undergraduates for course credit. Data from seven participants was removed
due to being beyond three standard deviations from the mean age. Additionally, six
participants were excluded from analysis due to rating the self-generated stressful event
as ‘not stressful’ or not completing the thought-listing task at all. This resulted in the
26
following set of participants (n = 138; 77.5% Female, 22.7% Male, .7% Transgender,
Mage = 23.4, S D - 3.8 years).
Materials and procedure. Presentation of materials were identical to that of
Study 1 and included the thought-listing task about a recent self-generated stressful life
event followed by a series of online questionnaires.
Participants in the student sample rated their self-generated events as ‘very
stressful’ MstressRateS = 4.59 from a scale of 1 (not at all stressful) to 5 (very stressful).
Baseline positive emotions (MpreposEmos - 2.85, SD = .86; a = .82) and negative emotions
(MpreNegEmoS = 1.52, SD = .67; a = 77) were assessed. Additionally, as an potential
indicator of resilience or the ability to ‘bouncing back’, the experience of positive
(MpostPosEmos = 2.78, SD = .96; a = .86) and negative emotions (Mp0stNegEmos = 1.83, SD =
.91; a =.82) immediately following the stressful thought listing task was also obtained.
As with the previous study, both qualitative and quantitative assessments of self­
talk were obtained. Free responses during the thought-listing task were scored for selftalk, using the STiA, specific to the self-generated stressful experience and scored on the
same dimensions as Study 1: motivational, instructional, valence, and frequency
dimensions. Self-report included the FSCRS which examines a general tendency to
engage in self-talk styles during stressors and included reassuring self-talk (a = 90;
MReasSTs= 2.31, SD = .94), inadequate self-talk (a = .88;
M i„ adSTs
= 2.10, SD = .97), and
hated self-talk (a = .82; A/HatedSTs = .97, SD = .98).
Behavioral approach systems subscales demonstrated acceptable reliability
ranging from .63 (BAS fun-seeking) to .73 (BAS drive). The Behavioral avoidance
system (BIS) showed greater reliability (a = .81). Participants’ motivational dispositions
were as follows: approach reward responsiveness (MRewards = 3.53, SD = .45),
avoidant/inhibitory (MAvoids = 3.12, SD = .52), approach fun-seeking (Mfuns = 3.08, SD =
.54) and approach drive
(Aforives =
2.86, SD = .58). As in previous studies, the CD-RISC
was psychometrically sound and demonstrated excellent reliability with an alpha of .92.
27
Our sample of college students had an average raw resilience score comparable to other
US college samples (MReSiieS= 68.23, SD = 15.08).
Results
Self-talk as a mediator of the relationship between avoidance sensitivity and
resilience for students.
To replicate findings concerning my hypothesis that avoidance sensitivity was
negatively correlated with resilience and this relationship was mediated by self-talk, I
first conducted partial correlations between avoidance motivation and resilience while
controlling for positive baseline affect and found that avoidance motivation was
negatively correlated with resilience (r = -.31, p < .001) (see Table 2 for relationships
between predictors and resilient outcomes without controls). Baseline positive affect was
controlled for in all subsequent pathways to rule out the possibility that the following are
a result of general positive emotions which are highly correlated with resilience.
To further test my second hypothesis about the mediating role of self-talk,
mediation analysis were conducted to examine whether the relationship between
avoidance motivation and resilience were mediated by reassuring or critical self-talk.
Behavioral avoidance (i.e., BIS) was entered in the model as a predictor and resilience as
the dependent variable with all three styles of self-talk (i.e., reassuring, inadequate, and
hated) entered simultaneously as mediators. Exploratory data analysis revealed no issues
with collinearity in the self-talk styles given all VIFs < 2.35 which is a conservative
estimate of variance inflation factors among predictors.
As displayed in Figure 4, avoidance sensitivity was associated with less
reassuring self-talk, b* = -.35,/? < .001, and reassuring self-talk led to increased capacity
for resilience b* = .66, p < .001 (after controlling for the other self-talk styles, b* = .55, p
< .001). Furthermore, the negative relationship between avoidance motivation and
resilience was attenuated by 83% and no longer statistically significant, b* = -.05,p = .53
reduced from b* = -.29, p < .001.
28
To determine the proportion of the relationship between avoidance motivation and
resilience that was mediated through reassuring self-talk, the PROCESS macro (Hayes,
2015) was used to conduct bootstrap analysis with 5000 resamples. This analysis
revealed reassuring self-talk was a significant mediator of the relationship between
avoidance motivation and resilience as the 95% confidence interval of the standardized
indirect effect did not include zero [-.35, -.10]. Given the standardized indirect pathways
of inadequate self-talk [-.26, .07] and hated self-talk [-.04, .14] contained zero, these were
not significant mediators in the proposed model.
Figure 4. Reassuring self-talk mediated the relationship between avoidance motivation
and resilience in students (Study 2)
[LLCI: -.35, ULCI: -.10
.35*5-
Avoidance
Motivation
Reassuring
Self-talk
.66** (.55**)
-.29** (-.05) ”*-
Inadequate
Self-talk
C ontrolling fo r
B a selin e P ositive
A ffect
Hated
Self-talk
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for the remaining factors.
*p< .01, **p< .001
Self-talk as a mediator of the relationship between approach sensitivity and
resilience for students.
29
To replicate my previous finding regarding my hypotheses that approach
sensitivity would be positively correlated with resilience and this relationship would be
mediated by self-talk, I started with a partial correlation between approach drive
motivation and resilience while controlling for baseline positive affect (r = .31, p < .001)
(see Table 2 for relationships between predictors and resilient outcomes without
controls). In order to account for a potential boosted effect due to general positive affect,
baseline positive affect was controlled for across all pathways.
To confirm my second hypothesis regarding the mediating role of self-talk,
mediation analysis were conducted to test whether the relationship between approach
drive motivation and resilience were mediated by reassuring or critical self-talk.
Behavioral approach drive (i.e., BAS drive) was entered in the model as a predictor and
resilience as the dependent variable with all three styles of self-talk (i.e., reassuring,
inadequate, and hated) entered simultaneously as mediators. As stated previously,
exploratory data analysis revealed no issues with collinearity in the self-talk styles given
all VIFs < 2.35 which is a conservative estimate of variance inflation factors among
predictors.
As referenced in Figure 5, greater drive sensitivity was associated with more
reassuring self-talk, b* = .31 ,P < .001, and reassuring self-talk led to a greater capacity
for resilience, b* = .54, p < .001 (after controlling for other forms of self-talk, b* = 53,/?
< .001). Moreover, the strength of the positive relationship between drive motivation and
resilience undertook a 34% reduction and decreased from b* = .34,/? < .001 to b* = .23, p
<. 001.
To determine the strength of reassuring self-talk as a mediator between approach
drive motivation and resilience, Hayes’ (2015) PROCESS macro was used to conduct
bootstrap analysis with 5000 resamples. Reassuring self-talk was a significant mediator
of the relationship between drive motivation and resilience with a 95% confidence
interval of the standardized indirect effect significant not containing zero [.03, .22],
30
Inadequate self-talk [-.00, .10] and hated self-talk [-.08, .01] did not fit the current model
as mediators.
Figure 5. Reassuring self-talk partially mediated the relationship between approach drive
motivation and resilience in students (Study 2)
[LLCI: .03, ULCI: .23]
.31
Approach Drive
Motivation
Reassuring
Self-Talk
.54** (.53**)
.35** (.23**)
Inadequate
Self-T=talk
B a se l in e P o sitive
A ffect
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for the remaining factors.
*p < .01, **p < .001
STiA coded recalled stressor self-talk in students.
As with the previous study, the Self-Talk in Action (STiA) coding scheme was
used to assess qualitative data collected with a thought-listing task. Two well-trained
independent coders including the first author scored each thought participants reported
about a self-generated recent stressful life event. Overall, 60% of participants’ thoughts
included at least one self-talk cue with an average of two self-talk cues out of five
possible across participants. The most prevalent self-talk used was valenced self-talk (n =
31
83) with a majority of participants using negative (72%) as opposed to positive (28%)
self-talk. Motivational (n = 65) self-talk was the second most common type of self-talk
with 65% of participants engaging in demotivational self-talk and 35% utilizing
motivational self-talk cues. Instructional self-talk was the least frequent type of self-talk
present in only 14% of participants’ self-talk about a recent stressor.
Discussion
As predicted, general relationships with regard to approach motivation systems
predicting a greater capacity for resilience and avoidance motivation systems as
appearing less conducive to resilience were replicated along with important key
differences associated with a US undergraduate sample. The primary aim of this study
was to replicate the findings in Study 1 regarding the mediating role of self-talk in
motivation sensitivity leading to individual differences in one’s capacity for resilience.
Among students, approach drive motivation (e.g., sensitivity to goal persistent
cues) predicted resilient outcomes partially through the use of reassuring self-talk during
stressful situations. Reassuring self-talk was the only significant contributor towards the
relationship between avoidance sensitivity and resilience. This finding is particularly
interesting given the association of avoidant sensitive students’ inability to bounce back
from stressors was linked with less reassuring self-talk—not an increase in either type
(e.g., inadequate or hated) of critical self-talk. This important distinction merits further
attention as it has implications for how best to aid students’ capacity to foster resilient
outcomes despite being inundated with social and performance feedback.
In corroboration of my finding, Neff and colleagues (2005) found students who
were more self-compassionate (e.g., used more reassuring self-talk) were better able to
reevaluate a disappointing grade and bounce back from failure. Beyond merely being a
feel-good strategy, reassuring self-talk is associated with more accurate self-appraisals
(Leary, Tate, Allen, Adams & Hancock, 2007) as opposed to critical forms of self-talk
which are associated with rumination and distorted judgements about the self and
situations (Desrosiers, Vine, Klemanski & Nolen-Hoeksema, 2013). All together, these
32
findings provide valuable insight but are limited by both a retrospective targeted stressor
and limited indices of resilient outcomes (e.g., affective response). To address these
limitations, the following study examines college students’ gearing up and response to an
actual stressor with additional outcomes relevant to resilience in a college population also
examined.
Study 3
Method
Participants. Data was collected from 121 San Francisco State University
Psychology undergraduates from three Psychology courses (social n = 25, cognitive n =
61, and statistics n - 35). Participants completed online and in-class assessments across
three to four sessions. Due to the multiple-part study there was substantial attrition which
resulted in missing data concerning demographic information and a total sample of 44
students (36.4% Female, 31.8% Male, Mage = 24.2, SD = 4.3 years, 31.8% unknown).
Materials and procedure. In order to track participants through the multiple part
study, participants used the last four-digits of their phone numbers (e.g., 9244) as an easy
to remember but distinct identification number. First, participants were directed to
complete a portion of the online assessment used in the previous two studies. This
included the same motivation questionnaire with a shortened version of the resilience
assessment used in the previous two studies. The BIS/BAS, as used in the previous
studies, consists of 4 subscales to capture the following dimensions of approach and
avoidance sensitivity: approach reward responsiveness (MReWardS2 = 3.43, SD = .45), funseeking (MfuuS2 - 3.05, SD = .50), avoidance (MAvoidS2 = 2.96, SD = .54) and approach
drive (MDnveS2 = 2.91, SD = .62). Alphas for all subscales ranged from .75 (fun-seeking)
to .81 (avoidance/approach drive).
The resilience assessment was a shortened version of the CD-RISC used in the
previous two studies (CD-RISC 10; Campbell-Sills & Stein, 2007) as per time constraints.
Raw scores ranged from 0 to 40 and used the same anchors as the 25 item CD-RISC.
Resilience assessed before participants’ exam or presentation (a = .90; MResUeS2pre =
33
27.18, SD = 6.06) was reflective of averages on the CD-RISC10 among US college
undergraduates.
Following this, the next data collection was in-class and occurred either the class
period before (as with the exam) or the day of (as with the presentation) but always prior
to participants’ stressor. During which participants received a packet that included two
questionnaires assessing state affect and anxiety and a thought-listing task. The thoughtlisting task was similar to what was used in the previous two studies but augmented to be
tailored to the time frame and type of stressor (See Appendix). As in the previous studies,
free-response data was analyzed for self-talk using the Self-Talk in Action (STiA) coding
scheme. The prompt for participants was as follows:
Please describe up to three thoughts you may have about yourself A T THIS
MOMENT right before your upcoming [exam/presentation]. These thoughts can
be positive, negative, and/or neutral. Ignore spelling or grammar and put only
one thought per box.
The number of thoughts were reduced from five to three to accommodate in-class time
constraints. Participants were also asked to rate typically how stressful their specific
stressor was (i.e., presentation givers rated how stressful presentations were—not how
stressful exams were). Out of participants with the exam stressor, 63% reported exams
were typically stressful situations as opposed to 71% of participants with a class
presentation as a stressor who reported presentations were typically stressful situations.
State positive and negative affect was also included to assess the experience of
positive (a = .80; MpreposS2 = 3.10, SD = .87) and negative (a = .86 ; M prenegS2 = 1.85, SD =
.68 ) emotions related to participants upcoming exam or presentation. Pre-stressor state
anxiety using the six item State Trait Anxiety Inventory (STAI-6 ; Marteau & Bekker,
1992) with a modified prompt referencing either participants’ upcoming exam or
presentation was also included in the packet. Responses were anchored on a 4-point
34
Likert scale from 1 (not at all) to 4 (very much) and demonstrated adequate reliability a =
.76 (Manxiety = 2.37, SD = .56).
Importantly, there was no statistical difference detected between the two
academic stressors (i.e., taking an exam versus giving a presentation) regarding the
experience of pre-stressor anxiety /(43) = -.23, p = .82 or pre-stressor negative affect
/(43) = ,4 \,p = .68 .
The next in-class portion occurred on the day of participants’ actual stressor. For
this second portion, packets included a state affect assessment and a shortened resilience
assessment distributed post-stressor. For participants taking an exam, packets were left at
the front of the class where exams were returned and participants were instructed about
the optional packets to be completed in-class right after their exam. For participants
giving a group presentation, the researcher distributed packets immediately following
each presentation and the packets were completed during the time the other group set up.
Each packet consisted of a state positive (MpostPosS2 = 3.12, SD = .99) and negative affect
(MpostNegS2 = 1.31, SD - .71) questionnaire with a prompt that referenced participants’
recent stressor (i.e., exam or presentation) and displayed excellent reliability (a = .87 for
both) along with the same 10 item resilience assessment participants’ completed prior to
their stressor which included resilience scores ranging from 0 to 40 (a = .83; MResueS2posi =
27.24, SD = 5.37).
The final data collection occurred online one to two weeks following participants’
completed exam/presentation and assessed self-talk in an identical fashion to the previous
two studies. Additionally, general perceived stress (PSS; Cohen, Kamarck, &
Mermelstein, 1983) and well-being were added (SPWB; Ryff & Keyes, 1995) to measure
additional outcomes related to resilience. As mentioned previously with regards to the
FSCRS, larger means indicating greater use of three types of self-statements during
difficult situations. For this sample, inadequate self-talk (a = .89; MinadS2 = 1.83, SD =
.93), reassuring self-talk (a = 90; MreassureS2 = 2.63, SD = .78), and hated self-talk (a = .83;
MhatedS2 = .66 , SD = .88) showed acceptable reliability. The Perceived Stress Scale (PSS)
35
is the most widely used measurement for the perception of stress and displayed good
reliability within our sample of college students (a = .82). The 14 item PSS was rated on
a 5 point-Likert scale of 0 (Never) to 4 ( Very often) in response to items including “In the
last month, how often have you felt nervous and “stressed”? and reverse scored items
such as “In the last month, how often have you felt that you were effectively coping with
important changes that were occurring in your life?”. Subjective well-being was assessed
using the Scale of Psychological Weil-Being (SPWB) which included 18 items that
resulted in a general well-being score including items such as “The demands o f everyday
life often get me down” (reverse scored) and “Ilike most aspects o f my personality” rated
on a six point-Likert scale from 1 (strongly disagree) to 6 (strongly agree). The SPWB
demonstrated excellent reliability (a = .86) with higher mean scores indicating greater
subjective well-being (Mwellbeings = 4.68, SD = .70). Finally, scores on participants’ exams
and presentations, scored on a range of 1 to 100, were also collected from the instructor
using a two person process to protect anonymity. Of the obtained students grades (n = 14)
the average was very high
(MstudentScores
= 90.5, SD = 7.26) and the implications for this in
our analysis are mentioned in the general discussion.
Results
Self-talk as a mediator of the relationship between avoidance sensitivity and
actual-stressor resilience for students.
To further examine my primary hypothesis that avoidance sensitivity was
negatively correlated with resilience and this relationship was mediated though self-talk, I
first conducted partial correlations between avoidance motivation and resilience while
controlling for positive baseline affect and found that avoidance motivation was
negatively correlated with resilience (r = -.48,/? = .003) (see Table 3). Additionally, due
to the smaller than expected sample size as a result of extensive attrition in the multiple
part study, a post hoc power analysis was conducted using G*Power version 3.0 (Faul,
Erdfelder, & Buchner, 2007). The alpha level used for this analysis was p < .05, with a
total of five predictors which revealed the current sample size was adequately powered
36
(power = .996). As with previous models, given the positive association between positive
affect and resilience baseline positive affect was controlled for in all subsequent
pathways.
Replicating my secondary hypothesis about the mediating role of self-talk,
mediation analysis were conducted to examine whether the relationship between
avoidance motivation and resilience were mediated by reassuring or critical self-talk.
Behavioral avoidance (i.e., BIS) was entered in the model as a predictor and resilience as
the dependent variable with all three styles of self-talk (i.e., reassuring, inadequate, and
hated) entered simultaneously as mediators. Exploratory data analysis revealed no issues
with collinearity in the self-talk styles given all VIFs < 2.57 which is only marginally
larger than 2 ; the most conservative estimate of variance inflation factors among
predictors.
As shown in Figure 6 , avoidance sensitivity was associated with less reassuring
self-talk, b* = -A 5 ,p < .001 and reassuring self-talk led to a greater capacity for
resilience, b* = .51 ,P < .01 (after controlling for other forms of self-talk: b* - .51 ,P <
.01). Furthermore, the strength of the relationship between avoidance motivation and
resilience experienced a 52% reduction and decreased from b* = -.48, p < .01 to b* = .09, p = .25.
To determine the proportion of the relationship between motivation and resilience
that was mediated through reassuring self-talk, the PROCESS macro (Hayes, 2015) was
used to conduct bootstrap analysis with 5000 samples. The analysis revealed reassuring
self-talk was a significant mediator given the 95% confidence interval of the standardized
indirect effect did not include zero [-.60, -.05]. Inadequate self-talk [-.47, .26] and hated
self-talk [-. 16, .29] did not fit the current model as mediators.
37
Figure 6. Reassuring self-talk partially mediated the relationship between avoidance
motivation and resilience in students (Study 3)
[LLCI: -.60, ULCI: -.05
- .4 5 * * '
Avoidance
Motivation
Reassuring
Self-Talk
.5 1 * ( .5 1 * )
- .4 8 * ( - .2 3 ) ” *
Inadequate
Self-Talk
C o n t r o l l in g
fo r
P re-S t r e sso r
P o s it iv e A f f e c t
Hated
Self-Talk
Note. All values are standardized regression coefficients. Values inside parenthesis are
regression coefficients after controlling for the remaining factors.
*p < .01 , **p < .001
Motivation with resilient outcomes as dependent variables.
As presented in Table 4, a correlational analysis was conducted to examine the
relationship between motivation orientations and outcomes associated with participants’
resilience outcomes resilience including well-being and general stress within the past
month. Additionally, pre-stressor anxiety and the experience of positive/negative
emotions pre and post stressor was evaluated and summarized below. Interestingly, we
found approach motivation systems were positively related to several resilience outcomes
but not our shortened resilience assessment specifically. Approach fun motivation (BAS
38
fun-seeking) was positively related to the experience of greater positive emotions post­
stressor; the experience of positive responses to rewards (BAS reward responsiveness)
was related to greater positive emotions pre-stressor, increased well-being, less anxiety
pre-stressor, and less negative emotions pre-stressor. Behavioral avoidance (BIS) was
associated with less resilience, greater stress in the past month, and marginally less
positive affect post-stressor and negative affect pre-stressor. While not displayed, none of
the motivation orientations were related to performance scores however participants’
scores obtained from professors were exceptionally high.
Table 4. Correlations between motivation and resilient outcomes in students (Study 3).
Well-being
Approach (Drive)
Approach (Fun)
Approach (Reward)
Avoid
.31
.30
.45**
-.29
Perceived
Stress
-.08
.02
-.03
.31*
prState
PA
prState
NA
.23
-.02
.49**
-.22
-.27
.05
-.32*
.31*
poState
State
Anxiety
PA
-.27
-.11
-.37*
.23
poState
NA
.19
.33*
.26
-.32*
.11
.18
.01
.02
Note, fp < ,06, *p < .05. **p < .01; STiA indicates scored self-talk.
prPA/NA = state positive affect pre stressor; poPA/NA = state positive affect post stressor
Self-talk with resilient outcomes as dependent variables.
As displayed in Table 5, a correlational analysis was conducted to examine the
relationship between self-talk styles used generally during stressful situations (via the
FSCRS) and self-talk used specifically by participants during an actual stressor (via the
STiA) with regard to resilient outcomes for college students including scores on
exam/presentation (both out of 100 points), well-being, general stress, pre-stressor
anxiety, and pre/post stressor affect. Reassuring self-talk was associated with increased
well-being, greater resilience, and the experience of more positive emotions pre/post
stressor and the experience of less negative emotions post-stressor. Inadequate self-talk
was associated with less resilience, less subjective well-being, greater experience of
negative emotions pre-stressor, but with higher performance scores. The positive
correlation between performance and inadequate self-talk was not included in the results
39
due to negatively skewed participant scores. Hated self-talk was associated with the
experience of more negative emotions pre-stressor, less positive emotions post-stressor,
greater pre-stressor anxiety, along with less subjective well-being and resilience.
Motivational self-talk was associated with greater resilience and subjective well-being.
Negative self-talk was associated with greater pre-stressor anxiety.
Table 5. Correlations between self-talk and resilient outcomes in students (Study 3).
Perceived prState
Stress
PA
47 **
.69**
-.53**
Well­
being
Reassure-Self
prState
NA
. 45**
poState
PA
poState
NA
-.20
.38*
-.24
.59**
.21
-.04
.23
.65**
.41*
-.21
.20
-.44*
-.47 **
.52**
-.21
.23
-.29
-.36*
.10
.09
Motivational5114
,36|
.38*
-.17
.14
-.26
-.28
.07
-.03
Instructional5114
-.26
.14
.02
.13
.09
-.14
-.05
FrequencySTiA
-.12
.06
.03
.03
.08
-.09
.21
Inadequate-Self
Hated-Self
PositiveSTlA
-.31
State
Anxiety
.35*
Note, tp < .06, *p < .05. **p < .01; STiA indicates scored self-talk.
prPA/NA = state positive affect pre stressor; Po PANA = state positive affect post stressor
STiA coded actual stressor self-talk in students.
The Self-Talk in Action (STiA) coding scheme was used to assess qualitative data
collected with a thought-listing task prior to participants’ exam or in-class presentation.
Two well-trained independent coders scored each thought participants reported about an
actual stressor. Overall, 70% of participants’ thoughts included at least one self-talk cue
with participants using 1 self-talk cue on average out of three possible. The most
prevalent self-talk used was valenced self-talk (n - 22 ) with a majority of participants
using positive (73%) as opposed to negative (27%) self-talk. Motivational (n = 20) self­
talk was the second most common type of self-talk with 70% engaging in motivational
self-talk and 30% utilizing de-motivational self-talk cues. Instructional self-talk was the
least frequent type of self-talk present in only 16% of participants’ self-talk about their
actual stressor.
40
General Discussion
Together this series of studies demonstrate that both approach and avoidance
systems are associated with either increased or decreased capacities for resilience
partially through individual differences in self-talk implemented during times of stress.
Importantly, these relationships are maintained for a general and student population
during a recalled and actual stressful experience even when accounting for general
positive mood/emotions.
Across all three studies my hypothesis concerning the potential role of self-talk in
the relationship between motivation sensitivity predicting greater or diminished capacity
for resilience was supported. In addition to this general support, there were subtle
differences that merit further review.
The most robust finding concerned avoidance sensitivity. Adults who were more
motivated by a fear of punishment or threat (e.g., avoidance sensitive) tended to engage
in less reassuring and more persecuting self-talk during challenging situations which
reduced their likelihood of achieving resilient outcomes. In-line with the coping
literature, this tendency to have behaviors guided by avoidance motivation is proposed to
both impede adaptive responses to stressors and exacerbate their negative impact (Carver,
Scheier, & Weintraub, 1989). In the student samples, there was not an influence of
critical forms of self-talk on the relationship between avoidance sensitivity and decreased
resilience; rather, it was the lack of reassuring self-statements during stressful situations
that was associated with avoidant sensitive students’ decreased capacity for resilience.
Given the attention directed towards negative aspects of themselves or their situation
facilitated by an avoidance sensitive motivational disposition, students’ appraisals of
stressors may become substantially more threatening (Troy & Mauss, 2011) without the
use of reassuring self-statements which serve to recalibrate perceptions to more
accurately reflect situational demands and personal competency.
41
Support for approach sensitivity as being positively related to a greater capacity
for resilience was also evident in both a general and undergraduate population. Among
adults and students, a sensitivity to goal persistent cues (e.g., approach drive motivation)
was associated with greater resilience partially through the tendency to engage in
reassuring self-talk during times of stress. These results compliment proposals that
motivation-based personality dispositions along with goal orientations shape one’s self­
talk (Hardy et al., 2009) and result in adaptive responses in the face of challenges.
Importantly, this process is argued to be crucial in successful aging (Rowe & Kahn,
1987). While approach drive motivation was related to resilience in Studies 1 and 2, it
was likely not related to our second sample of students in Study 3 due to a small sample
size which was nearly one third of the student sample in Study 2.
Only with adults was a greater spontaneous approach of potentially rewarding
experiences (e.g., approach fun-seeking) associated with an increased capacity for
resilience partially through the use of reassuring self-talk during stressors. This is in
contrast to literature that finds fun-seeking approach sensitivity as declining with age but
may be the result of adulthood generally supporting a greater independent use of time
than may be the case for undergraduates’ who often balance jobs and coursework.
General support for our results concerning approach motivation systems and resilience
comes from work that finds an individuals’ capacity for resilience is predicted by their
responsiveness to positive emotional rewards (Das, Cherbuin, Tan, Anstey, & Easteal,
2011; Markarian, Pickett, Deveson, Kakona, 2013; Tugade & Fredrickson, 2004).
Finally, examining reported self-talk during stressful situations and qualitative
assessments of self-talk richly adds to the understanding of self-talk and its relationships
with motivation sensitivity and resilience. In terms of qualitative results, the STiA allows
for the presence or absence of self-talk used during a stressor to be examined which is not
detected in surveyed self-talk. Students experiencing an actual stressor has the greatest
self-talk usage (70%), followed closely by adults recalling a stressor (69%) and lastly,
students recalling a stressor (60%). Across samples, valenced self-talk was most
42
frequently used followed by motivational and then instructional self-talk. The lack of
instructional self-talk may be largely due to the nature of participants generated and
actual stressors as not being precision based tasks (Van Raalte et al., 1995). Interestingly,
in the context of a recalled stressor, both students and adults engaged in greater negative
self-talk than positive self-talk. This relationship was different in the context of an actual
stressor. Students preparing for an exam/presentation used over double the amount of
positive self-talk as they did negative self-talk.
In terms of self-reported reassuring and critical forms of self-talk, adults engaged
in mostly inadequate self-talk whereas students utilized significantly more reassuring
self-talk. Hated self-talk was the least used strategy when managing stressful events. The
detail associated with using both surveyed (e.g., FSCRS) and qualitative assessments
(e.g., STiA) of self-talk reveal a more complete understanding this dynamic cognitive
skill associated with resilient outcomes.
Lastly, Study 3 examined additional resilient outcomes pertinent to students
including perceived stress, pre-stressor anxiety and affect, post stressor affect, well-being
and academic performance. Reassuring self-talk was associated with greater well-being,
resilience, and the experience of more positive emotions before and after a stressor.
Reassuring self-talk was also associated with less perceived stress and less negative
emotions following a stressor. Similarly, approach fun-seeking and approach reward
responsiveness were associated with greater positive emotions following a stressor.
Inadequate and hated self-talk were associated with less resilience, decreased well-being,
increased perceived stress, and greater negative emotional experiences pre-stressor. The
only motivation style positively associated with perceived stress was avoidance
sensitivity which was also associated with less resilience. While there was no relationship
between motivation orientations on performance scores, there was one self-talk style
related to higher performance. Inadequate self-talk was related to higher scores on the
exam or presentation; however, this result should be taken lightly given scores on the
43
exam and in-class presentation were on average an A- and therefore there was little
variability in the limited sample.
In summation, these findings further recent discoveries regarding the empirical
and theoretical intersection of motivation and resilience literatures (Corral-Frias et al.,
2016; van Beek, Kranenburg, Taris & Schaufeku, 2013) in three important ways: First,
unlike previous research, I examined relationships regarding all subscales of behavioral
approach and avoidance motivation sensitivity across a sample of adults and
undergraduates which remain understudied populations among resilience researchers.
Additionally, there is a paucity of researchers examining avoidance motivational
dispositions as influencing resilience despite a general avoidance disposition as being a
hindrance to problem-solving and behavioral optimization (Kalisch et al., 2015).
Second, the current research included several rich assessments such as a
retrospective and actual stressor and a qualitative assessment of participants’ self-talk
with the STiA. This in-depth analysis is essential as this is the first series of studies in
print to examine potential contributions of self-talk between motivation and resilience.
The importance of a qualitative assessment also adds to the ecological validity and
supports a more detailed examination about the efficacy of various dimensions of self­
talk across situations and individuals.
Third, and perhaps most importantly, a majority of studies in the resilience
literature emphasize the identification of factors associated with resilience as opposed to
mechanisms. Given that self-talk represents views about oneself and one’s capacity to
respond to both potential threats and rewards, it represents an important and previously
untested skillset that may underlie several previously identified overlapping factors
associated with resilience.
Despite these novel contributions, the present findings are limited in several ways.
Most prominently through the correlational design of these exploratory experiments.
These results suggest but cannot assume self-talk plays a causal role in resilience. Future
work should seek to replicate these findings through experimental manipulation keeping
44
in mind previous work regarding increased distress associated with mismatches between
motivation and decreased efficiency of inauthentic self-talk inductions. An additional
more ecologically valid approach would be to observe professors or academic
environments that promote distinct motivation orientations and/or self-talk.
There are also issues with regard to the inclusion of two distinct experienced
stressors and the substantial attrition associated with my multiple part study. The in-class
presentation was done in a group whereas the exam was an individual performance
assessment which may or may not have received varying degrees of social influence on
one’s motivation, self-talk, and resilience. Additionally, collapsing across stressors and
three academic classes may have obscured meaningful differences given the literature
supporting the importance of fit between motivation/self-talk and different situational
demands.
Also, students’ environment or the influence of instructors were not evaluated in
Study 3. Given the social implications of self-talk as well as situational demands, a
promotion or prevention focused environment fostered by the instructor may have
contributed to differences across classes. Modifications to the paradigm to include three
in-person assessments have already resulted in less attrition. Future research examining
students’ self-talk, motivation and resilience as moderated by their instructors or the type
of stressor encountered could provide valuable insight regarding academic engagement,
burnout and overall student well-being.
As a result of introducing empirical findings concerning self-talk styles there
tends to be an oversimplification that implies a single type of self-talk predicts adaptive
functioning across situations and individuals. Self-talk groupings I endorsed (e.g.,
positive, negative) and robust results regarding reassuring self-talk connotes an
endorsement of positive as opposed to negative self-talk styles. While this may be in-line
with the literature, it does not equate to a ‘one size fits all approach’ regarding a path
towards resilience.
45
For instance, the general overuse of positive self-talk may indicate a fragility in
responding to adverse situations. Among male undergraduates, those lower in hardiness
(a personality trait related to resilience) engaged in more positive self-talk during a low
stress situation and less positive self-talk during high stress situation compared to their
hardier counterparts (Allred & Smith, 1989). Further evidence comes from Wood and
colleagues (2009) who experimentally manipulated the self-talk of male and female
undergraduates and found the repetition of a positive self-statement which was
incongruent with self-views increased the discrepancy between low and high self-esteem
students. Additionally, critical self-talk can evoke certain negative feelings that lead to
increases in task persistence (Wolters, 1998). Theoretical support for this seemingly
counter-intuitive notion comes from Carver & Scheier’s (2001) control process theory
whereby a discrepancy enlarging feedback loop (e.g., avoidance motivation) can serve an
adaptive function when constrained by a discrepancy reducing feedback loop (e.g.,
approach motivation).
Indeed, it is likely the authenticity associated with agreement between one’s task
and disposition that leads to more robust behavioral response via self-talk usage.
Furthermore, it is the authentic endorsement of targeted self-statements that distinguishes
self-talk (e.g., “I can do this”) from general affirmations (i.e., “I am a beautiful and
unique snowflake”). Given the variability across students and stressors, the authors
caution future researchers from endorsing a single self-talk strategy and instead promote
the development of various self-talk styles. In doing so, self-talk can be most effectively
aid in the process of navigating everyday stressful events.
46
Conclusion
These studies unify past research that has found motivation sensitivities as an
antecedent of self-talk and self-talk as serving important self-regulatory functions. In
addition, the present studies extend previous associations between motivation and
resilience to examine subtle differences between approach and avoidance motivation
dispositions. In three studies I investigated the relationship between approach and
avoidance sensitive dispositional motivation and resilience and whether self-talk is a
potential mechanism underlying this relationship. My results suggest avoidance
motivation predicts a diminished capacity for resilience and is associated with less
reassuring self-talk. Specifically among adults, this relationship was also contributed
towards through the increased use of persecuting self-talk. Also replicated across both an
undergraduate and adult sample, approach motivation predicted a bolstered capacity for
resilience partially through the use of reassuring self-talk.
Further examination through qualitative analysis using the STiA coding system
revealed 60-70% of participants engaged in self-talk during either a recalled or actual
stressor. Implications for avoidance motivation and critical forms of self-talk as related to
less resilience, greater pre-stressor anxiety, greater general stress, and decreased well­
being affirm students’ as a robust population with which to elucidate these relationships.
Taken together, these results and the prevalence of self-talk in students (and adults)
suggest further tests of the proposed model as a means to inform interventions and
identify mechanisms underlying resilient outcomes.
47
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Theodorakis, Y. (2011). The social side of self-talk: Relationships
between perceptions of support received from the coach and athletes’ self-talk.
Psychology o f Sport and Exercise, 12(4), 407-414.
Zourbanos, N., Papaioannou, A., Argyropoulou, E., & Hatzigeorgiadis, A. (2014).
Achievement goals and self-talk in physical education: The moderating role of
percei ved competence. Motivation and Emotion, 38(2), 235-251.
67
Table 1. Correlations between predictors and resilient outcomes in adults (Study 1).
Approach (Drive)
Resilience
46**
Stress_PA
Stress_NA
.23*
-.05
Approach (Fun)
.33**
.07
-.01
Approach (Reward)
.40**
.20 *
-.02
Avoid
-.34*
-.23**
Reassure-Self
.72**
.47**
.21 *
_ 44 **
Inadequate-Self
-.41**
-.31**
.64**
Hated-Self
-.54**
-.30**
PositiveSTiA
.22 *
.21 *
-.12
Motivational51^
.30
.27**
-,18f
InstructionalSTiA
.04
.04
.06
FrequencySTiA
-.19*
-.20 *
-.02
Note, tp < .06, *p < .05, **p < .01; STiA indicates self-talk specific to a recalled stressor
PA = Positive Affect, NA = Negative Affect
68
Table 2. Correlations between predictors and resilient outcomes in students (Study 2).
Resilience
Stress_PA
Stress_NA
Approach (Drive)
.41**
.16
-.12
Approach (Fun)
.24*
.13
-.06
Approach (Reward)
.31**
.14
-. 19t
Avoid
-.36**
-,05t
.26**
Reassure-Self
.35**
-.26**
Inadequate-Self
.65**
_ 44**
-.22*
Hated-Self
-.39**
-.15
.33**
44 *$
Positive81**
.10
.04
-.29**
MotivationalSTiA
.19
.05
-.23**
Instructional51^
-.06
.03
.01
-.10
.02
.19
FrequencySTiA
Note, tp < .06? *p < .05. **p < .01; STiA indicates scored self-talk.
FA = Positive Affect NA = Negative Affect
Table 3. Correlations between predictors and resilient outcomes in students (Study 3).
Resilience
Stress_PA
Stress_NA
Approach (Drive)
.17
.20
.11
Approach (Fun)
.29
.33*
.18
Approach (Reward)
Avoid
Reassure-Self
.03
-.52**
.63**
.27
-.32*
.38**
.01
-.24
Inadequate-Self
Hated-Self
PositiveSTlA
-.50**
-.35*
.26
-.04
.23
-.21
.20
.10
.09
Motivational5’1''*
.07
-.03
Instructional57-14
.34*
<■>4
-.^4
-.14
-.05
FrequencySTl4
-.05
-.10
.21
Note, tp £ .06, *p < .05, **p < .01; STiA indicates scored self-talk,
PA = Positive Affect, NA = Negative Affect
.02
69
Appendix: Sample Thought Listing-Task (In-Class Part I)
Please describe up to three thoughts you may have about yourself
AT THIS MOMENT a week before your exam. These thoughts can be positive, negative,
and/or neutral. Ignore spelling or grammar and put only one thought per box.
Please put only one thought per box.
Thought 1:
Thought 2:
Thought 3:
70
Now we will ask you to complete a few questionnaires about how you are feeling.
INSTRUCTIONS: Read each item and then mark the appropriate answer in the space next
to the word. Indicate to what extend you feel RIGHT NOW a week before your exam. Use
the following scale to record your answers.
How 1Fee!
RIGHT NOW
Attentive
Nervous
Ashamed
Inspired
Alert
Hostile
Determined
Active
Upset
Afraid
NOT AT ALL
A LITTLE
MODERATELY
QUITE A
BIT
EXTREMELY
71
INSTRUCTIONS: Read each statement and then circle the most appropriate choice to the
right of the statement to indicate how you feel RIGHT NOW before your exam. There are
no right or wrong answers. Do not spent too much time on any one statement but give the
answer which seems to describe your present feelings about your upcoming presentation
best.
Not at All
1.1 feel calm
2.1 am tense
3.1 feel upset
4 . 1 am relaxed
5.1 feel content
6.1 am worried
1
1
1
1
1
1
S omewhat
2
2
2
2
2
2
Moderately
Very Much
3
3
3
3
3
3
4
4
4
4
4
4