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Seton Hall UniversityeRepository @ Seton HallSeton Hall University Dissertations and Theses(ETDs) Seton Hall University Dissertations and Theses
Summer 8-3-2018
Dispositional Mindfulness and PositivePsychological Processes in Older Adults: ExecutiveFunctioning, Positive Reappraisal and Meaning inLife.Kristen Wesbecher
Follow this and additional works at: https://scholarship.shu.edu/dissertations
Part of the Counseling Psychology Commons
Recommended CitationWesbecher, Kristen, "Dispositional Mindfulness and Positive Psychological Processes in Older Adults: Executive Functioning, PositiveReappraisal and Meaning in Life." (2018). Seton Hall University Dissertations and Theses (ETDs). 2561.https://scholarship.shu.edu/dissertations/2561
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Dispositional Mindfulness and Positive Psychological Processes in Older Adults:
Executive Functioning, Positive Reappraisal and Meaning in Life.
by
Kristen Wesbecher
Dissertation Committee
Daniel Cruz, Ph.D., ABPP
Minsun Lee, Ph.D.
Matthew Graziano, Ph.D.
Adriana Dunn, Ph.D.
Submitted in partial fulfillment of the requirements for the degree
Doctor of Philosophy
Department of Professional Psychology and Family Therapy
Seton Hall University
December 18th, 2017
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© 2018 Kristen Wesbecher
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ABSTRACT
Although dispositional mindfulness has been associated with positive outcomes in the
broader mental health literature, less is known about dispositional mindfulness in older adults as
it relates to factors important in successful aging, such as meaning in life. This study investigated
the relationship between dispositional mindfulness and meaning in life, while taking into
consideration older adults’ available cognitive resources and use positive reappraisal. The
primary purpose of this study was to determine if the relationship between dispositional
mindfulness and meaning in life was mediated by executive function and positive reappraisal.
Additionally, this study examined the moderation effect of perceived level of stress.
To investigate processes within a proposed theoretical framework, a sample of older
adults (N=47) were assessed across various measures, including dispositional mindfulness,
meaning in life, perceived stress, positive reappraisal as well as a number of executive functions
(i.e., working memory, cognitive flexibility and inhibition). Dispositional mindfulness
significantly predicted use of positive reappraisal strategies, but was not found to play a
significant role in the executive functions or the presence of meaning in life. Stress did not
moderate the relationship between dispositional mindfulness and executive functions.
Limitations, implications and future directions are discussed.
Keywords: Mindfulness, meaning in life, executive functioning, positive reappraisal
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ACKNOWLEGEMENTS
First, I would like to thank my dissertation chair, Dr. Daniel Cruz. Dr. Cruz has been a tireless
supporter of my development since the moment we met, and for this I am truly grateful. He went
above and beyond the role of dissertation chair to help with each aspect of this project, including
the conceptualization, collection and writing. Additionally, thank you to Drs. Minsun Lee and
Matthew Graziano for providing me with your valuable, supportive guidance and thoughtful
feedback throughout this project.
I would like to express my deepest gratitude to Drs. Laura Palmer and Adriana Dunn who have
provided a constant source of support and inspiration throughout my journey as a doctoral
student. I could not have asked for better role models and feel so very lucky to have you in my
life. Dr. Palmer, your dedication and support of my growth is truly unmatched by all others. I
cannot wait to share many more successes with you. Dr. Dunn, I am so grateful for your
unwavering encouragement, patience and willingness to share your wisdom (and food!). Thank
you so much for always being there for me.
Thank you to Sue Lippy, who generously allowed me to pursue data collection within her
communities. Additionally, I am grateful to Pam Kaczor and Ursula Mell who went out of their
way to help with recruitment. Thank you Yubelky Rodriguez, for helping me collect data and
sharing your own sense of joy in working with older adults. Lastly, a very special thank you to
my lab mate and close friend, Christina Mastropaolo who provided support when it was needed
the most.
Mom, thank you for being my real-life hero. You inspire me each and every day to continue
pursuing my dreams. To my close family and friends, who have always been my greatest
sources of laughter, encouragement and motivation, thank you from the bottom of my heart.
Aleks, words cannot express how thankful I am to you. Your love and faith in me literally
carried me through this project. My success is your success and I would not be here today
without you.
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TABLE OF CONTENTS
page
ABSTRACT .....................................................................................................................................4
ACKNOWLEGEMENTS ................................................................................................................6
LIST OF TABLES .........................................................................................................................10
LIST OF FIGURES .......................................................................................................................11
CHAPTER ONE ............................................................................................................................12
Introduction .............................................................................................................................12 Meaning in Life ...............................................................................................................12 Positive Reappraisal ........................................................................................................14 Socioemotional Selectivity Theory .................................................................................15 Dispositional Mindfulness ...............................................................................................17 Statement of the Problem ................................................................................................19 Mindfulness to Meaning Theory .....................................................................................19 Purpose of this Study .......................................................................................................20 Research Questions .........................................................................................................20 Statement of Hypotheses .................................................................................................20
Definitions of Terms & Operational Definitions ....................................................................21 Dispositional Mindfulness ...............................................................................................21 Executive Function ..........................................................................................................21 Positive Reappraisal ........................................................................................................22 Meaning in Life ...............................................................................................................22 Perceived Stress ...............................................................................................................23
CHAPTER TWO ...........................................................................................................................24
Age Related Decline in Cognitive Functioning ...............................................................24 Age Related Increase in Wellbeing .................................................................................25 Improvement in Emotion Regulation ..............................................................................25 The Paradox of Aging .....................................................................................................26 Socioemotional Selectivity Theory .................................................................................27 The Role of Self-Referential Processing .........................................................................28 Cognitive Control Model (CCM) ....................................................................................29 Perceived Stress ...............................................................................................................30 Mindfulness .....................................................................................................................31 Mindfulness to Meaning Theory .....................................................................................36
CHAPTER THREE .......................................................................................................................38
Methodology ...........................................................................................................................38 Participants ......................................................................................................................38
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Procedure .........................................................................................................................39 Measures ..........................................................................................................................40 Covariates ........................................................................................................................48
Design .....................................................................................................................................48 Analyses ..........................................................................................................................49
Research Questions .................................................................................................................49 Statement of Hypotheses ........................................................................................................49
CHAPTER FOUR ..........................................................................................................................51
Results.....................................................................................................................................51 Characteristics of Participants .........................................................................................51 Preliminary Analyses .......................................................................................................52 Primary Analysis .............................................................................................................54 Initial Hypothesized Model .............................................................................................56 Revised Model .................................................................................................................58 Supplemental Analysis ....................................................................................................59 Mediation Analyses .........................................................................................................59 Moderated Mediation Analyses .......................................................................................60
CHAPTER FIVE ...........................................................................................................................61
Discussion of Results ..............................................................................................................61 Preliminary Analyses .......................................................................................................61 Primary Analyses .............................................................................................................62 Explanation of Findings ..................................................................................................64 Construct measurement ...................................................................................................66 Statistical Power ..............................................................................................................69 Sample Selection .............................................................................................................70 Clinical Implications .......................................................................................................71 General Limitations .........................................................................................................72 Future Directions .............................................................................................................73 Conclusion .......................................................................................................................74
References ......................................................................................................................................76
APPENDIX A ................................................................................................................................99
Informed Consent ...................................................................................................................99
APPENDIX B ..............................................................................................................................101
Letter of Solicitation .............................................................................................................101
APPENDIX C ..............................................................................................................................102
Procedure Script ....................................................................................................................102
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APPENDIX D ..............................................................................................................................103
IRB Approval ........................................................................................................................103
Appendix E ..................................................................................................................................104
Proposal Approval ................................................................................................................104
APPENDIX F...............................................................................................................................105
Measures ...............................................................................................................................105
APPENDIX G ..............................................................................................................................111
Figure 1. Conceptual Model ..........................................................................................111 Figure 2. Results of Revised SEM Model .....................................................................112 Figure 3. Mediation model with PROCESS .................................................................113
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LIST OF TABLES
Table page
Table 1 Demographic characteristics of participants ....................................................................51
Table 2 Means and Standard Deviations of Major Study Variables .............................................53
Table 3 Correlations between Major Study Variables ..................................................................54
Table 4 Regression Weights for Hypothesized Model ..................................................................57
Table 5 Regression weights for revised model .............................................................................58
Table 6 Results from moderated mediation analyses ....................................................................60
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LIST OF FIGURES
Figure page
Figure 1. Conceptual model depicting proposed relationship between variables used to
guide research hypotheses................................................................................................111
Figure 2. Mediation model depicts executive functioning and positive reappraisal as
mediators between dispositional mindfulness and meaning in life. Model was
adjusted for IQ and processing speed; e = error. .............................................................112
Figure 3. Mediation model depicts executive functioning and positive reappraisal as
mediators between dispositional mindfulness and meaning in life using PROCESS
model 4. Model was adjusted for IQ and processing speed. ............................................113
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CHAPTER ONE
Introduction
By 2030 the number of individuals 65 years of age or older is expected to approach 70
million, or 20% of the United States population (Administration on Aging, 2014). More globally,
estimates predict that by 2050, the proportion of the world’s population over 60 will double,
from 900 million to 2 billion (World Health Organization, 2016). This phenomenon is in part,
driven by improvements in longevity, which continue to steadily increase at a rate of 3 months of
life per year (National Institute on Aging, 2015). Therefore, as the population continues to age,
understanding older adults’ protective factors in health and wellness will become increasingly
important.
The importance of delineating older adults’ protective factors is underscored by their
more frequent experience with changes in independence, chronic pain, bereavement, and
socioeconomic status that threaten overall wellbeing (World Health Organization, 2016). One
point of intervention to promote wellbeing is improving health factors. Interestingly, older
adults with vascular risk factors such as coronary heart disease have higher rates of depression
than those who are medically well. Conversely, untreated depression is associated with increased
cardiovascular morbidity and mortality (Lichtman et al., 2009). That said, although improving
physical health is crucially important to aging in place, factors related to psychological wellbeing
should also be considered.
Meaning in Life
Meaning in life is one factor that fosters wellbeing and reduces distress in people’s lives.
According to Steger (2012), meaning in life refers to “the web of connections, understandings,
and interpretations that help us comprehend our experience and formulate plans directing our
energies to the achievement of desired future,” implying that meaning in life refers to extent to
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which we comprehend and see significance in our lives, as well as the degree to which we
subscribe to an overarching goal for that life (p. 65). Theoretically, meaning in life is said to be
comprised of two existential and one cognitive component (Heintzelman & King, 2014). From
an existential perspective, a meaningful life is one that has a sense of purpose and significance.
Cognitively, a meaningful life makes sense to the person who is living it (i.e., it is easily
understood and somewhat predictable) (Baumeister & Vohs, 2002). Meaning in life is associated
with a variety of positive outcomes. For example, self-reports of meaning in life are associated
with higher quality of life, (Krause, 2007), self-reported subjective sense of health (Steger,
Mann, Michels, & Cooper, 2009) and decreased stress (Ishida & Okada 2006). In addition,
meaning in life is associated with lower rates of psychological disorders (Owens, Steger,
Whitesell, & Herrera, 2009) and increased adaptive coping strategies after injury (Thompson,
Coker, Krause, & Henry, 2003).
While meaning in life is important for people of all ages, this may be especially true for
older adults. Sources of meaning in life are altered considerably in older adulthood, which often
requires individuals to reflect and make new meaning of current life circumstances. Changes in
major life roles (e.g., death of a spouse, retirement, change in mobility status, etc.) may
precipitate contemplation about one’s life purpose. This contemplation can either lead to a sense
of meaning and fulfillment, or a sense of regret and/or despair. (Erikson & Erikson, 1998).
Specific to older adults, research has shown that meaning in life predicts slower age-related
cognitive decline and decreased risk for Alzheimer disease (Boyle, Barnes, Buchman & Bennett,
2009) and decreased mortality (Krause, 2009). Therefore, as an index of psychological and
physical health, meaning in life may be particularly relevant to older adults.
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Positive Reappraisal
One way we may be able to increase the experience of a meaningful life is through active
cognitive reframing, such as positive reappraisal. Keeping that in mind, when a stimulus that was
originally appraised as threatening is reinterpreted as benign or even meaningful, it is recognized
as an emotion regulation strategy called positive reappraisal. More generally, literature defines
emotion regulation as an internal process that influences the intensity, duration and type of
emotion experienced in accordance with one’s short and long-term goals (Gross & Thompson,
2007). There are several different kinds of emotion regulation strategies. Ochsner and Gross
(2005) suggest a distinction between behavioral regulation (e.g., suppressing expressive
behavior) and cognitive regulation. Cognitive regulation relies on attentional control (e.g.,
purposeful inattention to negative emotional stimuli, performing distracting tasks, etc.) or on
cognitive change. Cognitive change strategies include the controlled regulation of an ongoing
emotional response, such as positive reappraisal (i.e., modifying of how one appraises a situation
so as to alter its emotional impact).
Positive reappraisal is an active coping strategy that “involves direct contemplation of the
stressor and its context;” it is not a defense mechanism used to repress negative emotion or deny
reality (Garland, Farb, Goldin & Fredrickson, 2015, p. 13). Therefore, unlike suppression,
positive reappraisal has been shown to attenuate stress physiology, including neuroendocrine and
cardiovascular factors (Bower, Low, Moskowitz, Sepah & Epel, 2008). For example, relative to
a different type cognitive emotion regulation (i.e., distancing), increasing positive emotion
through reappraisal results in shortened cardiac inter-beat interval paired with reduced blood
pressure (Shiota & Levenson, 2012). This cardiovascular response profile has been previously
associated with a “challenge” rather than a “threat” mindset (Tomaka, Blascovich, Kibler, &
Ernst, 1997). Hence, positive reappraisal is an adaptive rather than avoidant strategy that works
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to enhance top-down, prefrontal regulation during meaning making (Ochner & Gross, 2005).
Given its “active” stance, it is not surprising that positive reappraisal has been found to reduce
distress during a number of stressful life experiences, including health-related issues such as
cancer and myocardial infarction, as well as more global stressors such as natural disasters
(Nowlan, Wuthrich & Rapee, 2015).
Socioemotional Selectivity Theory
In general, older adults show improvements relative to younger adults in emotional
wellbeing (Ngo, Sands, Isaacowitz, 2016). For example, older adults report greater social support
and fewer daily hassles (Fiksenbaum, Greenglass & Eaton, 2006) as well as more satisfying
social lives (Luong, Charles & Fingerman, 2011). Moreover, older adults demonstrate lower
levels of physiological reactivity in response to negative experiences (Levenson, Carstensen,
Friesen & Ekman, 1991) and have lower rates of disorders implicated in emotion dysregulation
such as depression and anxiety (Kessler, Amminger, Aguilar-Gaxiola, Alonso, Lee & Ustun,
2007). Thus, current research points to the conclusion that older adults experience more social
and emotional wellbeing than their younger counterparts.
The Socioemotional Selectivity Theory (SST) provides an explanation for this
phenomenon, asserting that adults’ motivational goals, governed largely by the recognition that
time is limited and life is finite, are responsible. Specifically, when people are young and free of
major distress/mental illness, they typically view time as expansive, and therefore prioritize
motivational goals related to knowledge and novelty. Conversely, older adults who view time as
limited, prioritize motivational goals related to emotional wellbeing and the preservation of life’s
meaningful experiences over time (Carstensen, 2006).
According to SST, greater emphasis on emotionally salient goals leads to a greater focus
on, attention to, and memory for positive information (Carstensen, Mikels & Mather, 2006). This
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phenomenon, is termed the “positivity effect,” and refers to the observation that older adults
attend to and remember more positive and less negative stimuli compared to younger adults
(Knight et al., 2007). As an example, in one study where older adults were shown positive,
negative, and neutral stimuli followed by a timed delay, older adults recalled an increased
amount of positive information compared to younger adults (Charles, Mather & Carstensen,
2003). Important to understand is that the observed positive effects in cognitive processing are
understood as the way in which older adults accomplish their positive emotional goals; that is, it
is motivational in nature (Reed & Carstensen, 2012).
Cognitive Control. The Cognitive Control Model (CCM) broadens the scope of SST by
emphasizing the “top-down” nature of the positivity effect and asserts that the accomplishment
of positive emotional goals is best achieved when one has adequate higher-order cognitive
resources to direct towards them (Mather, 2012). In order to achieve positive emotional goals,
older adults must engage in emotional regulation, which requires sufficient cognitive control
abilities (Ochsner & Gross, 2005). The term cognitive control refers to broad set of cognitive
processes that allow information processing and behavior to vary adaptively from one moment to
the next, depending on current goals (Lezak, Howieson, Bigler & Tranel, 2012). Cognitive
control encompasses a number of skills including, but not limited to, the ability to: (1) selectively
attend to relevant information while also filtering out distractors (selective attention and
interference suppression); (2) mentally manipulate information that is currently being held in
one’s mind (working memory); (3) flexibly switch between tasks (set-shifting); and (4) inhibit
inappropriate response tendencies (response inhibition) (Lezak et al., 2012). They are also
known as executive functions.
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Research has shown that older adults with intact executive functioning skills more
frequently display the positivity effect when recalling emotional stimuli (Mather & Knight,
2005). For example, when manipulating one’s available resources in a divided attention task (i.e.,
decreasing available cognitive control resources), older adults do not display the positivity effect.
With that in mind, CCM posits that older adults who are able to direct cognitive resources (i.e.,
working memory, set-shifting and response inhibition abilities) towards positive emotional goals
are more likely to successfully orient their attention and memory towards positive stimuli (i.e.,
engage emotion regulation strategies), and consequently, achieve a more meaningful, emotional
experience (Mather & Knight, 2005).
Stress. Although older adults typically experience less negative emotion in some
situations, older adults may display increased negative emotion (Mroczek & Almeida, 2004) and
arousal in emotionally stimulating situations (Uchino, Birmingham & Berg, 2010). Labouvie-
Vief, Gilet and Mella (2014) state that in highly arousing, stressful situations, age related
cognitive decline (i.e., diminished processing speed, working memory, executive functioning and
episodic memory) may hinder the accomplishment of positive emotional goals. Specifically,
increased stress may impede the accomplishment of positive emotional goals by depleting the
cognitive resources (i.e., working memory, set-shifting and response inhibition abilities) needed
to successfully engage in emotion regulation strategies. Therefore, uncovering factors that
withstand common stressors of aging and also contribute to older adults’ cognitive control in
order to increase meaning in life is an overarching goal of this study. One proposed factor is
dispositional mindfulness.
Dispositional Mindfulness
Mindfulness is conceptualized and studied in a variety of contexts. Most commonly, it is
examined as it naturally occurs and varies across the population as an aspect of personality (i.e.,
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trait or disposition). It is also studied as a temporarily induced state (i.e., experimental
manipulation) in meditators and through clinical intervention (e.g., 8 week course of MBSR)
(Ostafin, Robinson & Meier, 2015). Therefore, an important distinction is made between
dispositional mindfulness and the state of mindfulness, in that, the state of mindfulness is
understood as a mode of awareness characterized by present centered attention to one’s current
experience that is free of preoccupation, while dispositional mindfulness reflects the propensity
towards exhibiting such nonjudgmental awareness naturally (Garland 2007; Quaglia, Brown,
Lindsay, Creswell & Goodman, 2015).
Mindfulness is particularly salient for older adults’ wellbeing. For example, mindfulness
has been shown to positively impact aspects of physical health including improved immune
function, reduced blood pressure and cortisol levels (Carlson, Speca, Faris & Patel, 2007). It has
also been shown to produce positive effects on psychological wellbeing (Chiesa & Serretti,
2009), enhance cognitive functioning in older adults (Jha, Krompinger & Baime, 2007), and
slow cognitive impairment in Alzheimer’s disease (Quintana-Hernandez et al., 2016).
Mindfulness may also lead to increased cognitive and emotional control. For example,
expert meditators perform significantly better than novices on tasks of selective and sustained
attention (van den Hurk et al., 2010) and show greater cortical thickness in the frontal cortices
(Lazar et al., 2005). Mindfulness has also been shown to counter normal age-related decline
thereby providing support for the role of mindfulness as a buffer against the neurobiological
cascades of aging (Pagnoni & Cekic, 2007). Lastly, dispositional mindfulness is associated with
neural recruitment of the cortico-subcortical circuitry engaged in emotional regulation (Way,
Creswell, Eisenberger & Lieberman, 2010). Taken together, evidence of mindfulness’ role in
increased cognitive and emotional functioning suggests it may help older adults shift cognitive
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processing and accomplish positive emotional goals, even in the face of more emotionally
complex and/or arousing situations.
Statement of the Problem
Dispositional mindfulness has been associated with positive outcomes in the broader
mental health literature. However, less is known about dispositional mindfulness in older adults
and how it may be relevant to factors important to successful aging, such as meaning in life. In
order to begin to answer these questions (Garland, Farb, Goldin & Fredrickson, 2015) recently
advanced the Mindfulness to Meaning Theory, which attempts to explain the process by which
mindfulness decreases stress and promotes meaning in life through successful emotional
regulation.
Mindfulness to Meaning Theory
Focusing on mindfulness and meaning in life, the Mindfulness to Meaning Theory
(MMT) explores specific ways in which dispositional mindfulness leads to increased meaning in
life through positive emotion regulation. MMT posits that increased dispositional mindfulness
leads to increases in meaning in life through a process of promoting positive reappraisal in
stressful contexts (Garland et al., 2015). In brief, the MMT asserts that mindfulness allows one
to decenter from stress appraisals into a metacognitive state of awareness. This state then
broadens attention control to previously unnoticed (and likely more positive) information, which
accommodates reappraisal (i.e., reframing) of stressful events that then reduces distress. To
illustrate, a change in mobility status may be initially interpreted as terrible, but later reappraised
as the catalyst for healthy lifestyle changes and a source of gratitude for one’s intact abilities.
Reappraisal then motivates future behavior and promotes deeper sense of purpose over time
(Garland et al., 2017). Ultimately, the more we are able to engage in this type of process, the
more likely it will continue to occur, which leads to reduced stress and enhanced wellbeing.
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Taken together, the proposed study hypothesized that increased dispositional mindfulness will
lead to more frequent use of positive reappraisal as well as improved executive functions. This
in turn, will lead to greater meaning in life. Furthermore, the relationship between dispositional
mindfulness and executive functioning is hypothesized to weaken as stress increases.
Purpose of this Study
This study investigated the relationship between dispositional mindfulness and meaning
in life, while taking into consideration older adults’ available cognitive resources and use of
positive reappraisal. The primary purpose of this study was to determine if the relationship
between dispositional mindfulness and meaning in life was mediated by executive function and
positive reappraisal. Additionally, this study examined the moderation effect of perceived level
of stress between dispositional mindfulness and executive functioning. To the researcher’s
knowledge, no studies have been conducted that examine the implications of MMT related to
older adults. Overall, the current study aimed to integrate what is known about normal aging
with what is known about positive psychological processes related to mindfulness.
Research Questions
• Question 1: Does dispositional mindfulness predict increased meaning in life?
• Question 2: Is the relationship between dispositional mindfulness and meaning in life
mediated by executive functioning and positive reappraisal?
• Question 3: Is the proposed model moderated by stress, such that higher levels of stress
weaken the ability of individuals with greater dispositional mindfulness to direct
cognitive resources towards positive emotional regulation, thus resulting in less
meaning in life?
Statement of Hypotheses
• Hypothesis 1(a): Dispositional mindfulness will positively correlate with presence of
meaning in life.
• Hypothesis 1(b): Executive functioning and positive reappraisal will positively correlate
with presence of meaning in life.
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• Hypothesis 2 (a): Dispositional mindfulness will be positively correlated with positive
reappraisal.
• Hypothesis 2 (b): Dispositional mindfulness will be positively correlated with executive
functioning.
• Hypothesis 3 (a): The relationship between dispositional mindfulness and presence of
meaning in life will be mediated by positive reappraisal and executive
functioning.
• Hypothesis 4 (a): The mediational effect of dispositional mindfulness and executive
functioning will be moderated by perceived stress.
Definitions of Terms & Operational Definitions
Dispositional Mindfulness
While the state of mindfulness is characterized by an attentive, nonjudgmental awareness
of cognition, emotion, and sensation without fixation on thoughts of past and future (Garland,
2007), dispositional mindfulness reflects one’s natural propensity towards exhibiting such
nonjudgmental awareness. Simply put, dispositional mindfulness refers to the degree of day-to-
day mindful attention that varies in individuals (Brown & Ryan, 2003). Therefore, dispositional
mindfulness typically concerns the general quality and frequency of “open or receptive attention
to and awareness of ongoing evens and experience” over time (Brown & Ryan, 2003, p. 245).
The Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003) was developed to assess
naturally occurring variations in mindfulness and was used to measure dispositional mindfulness
along one factor: awareness/attention.
Executive Function
Executive function processes include a broad class of mental operations that help us
organize incoming information for tasks such as decision making or problem solving, and
includes neurocognitive skills such as working memory, set shifting and response inhibition
(Lezak et al., 2012). Working memory is understood as a system that works to register, recall and
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mentally manipulate information within short-term memory (Baddeley, 1995). Digit span tests
are commonly used with the digits forward component used to assess basic auditory attention
and the backward and sequencing components used to assess working memory. Working
memory was assessed through participants’ performance on Digit Span, a subtest of the
Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008). Set shifting is
defined as our ability to flexibly switching between tasks. Set-shifting was assessed through
participants’ performance on Trial Making Test (Parts A & B) (Reitan, 1958). Lastly, response
inhibition is the ability to inhibit inappropriate response tendencies (Lezak et al., 2012) and was
assessed using the Stroop Color and Word Test (Golden, 1978).
Positive Reappraisal
When confronted with threat, the brain activates a physiological response involving
autonomic, neuroendocrine, metabolic, and immunologic changes that are intended to facilitate
adaptation to one’s environment (Lupien, McEwen, Gunnar & Heim, 2009). Engaging in
cognitive reappraisal allows one to modify the consequences of the stress response through
reshaping the meaning of the stressor and subsequently, the behavioral responses to it. Specific
to this study, positive reappraisal therefore, is understood an adaptive process by which stressful
events are redefined as benign, valuable or beneficial (Garland, Gaylord & Park, 2009). It was
measured with the Cognitive Emotion Regulation Questionnaire (CERQ; Garnefski et al., 2001).
Meaning in Life
The current literature base on the topic of meaning in life has produced a variety of
definitions. The current study takes the position that meaning in life is best understood as the
presence of (Presence of Meaning in Life; PML), meaning in life. (Steger, Frazier, Oishi &
Kaler, 2006). PML is defined as the extent to which individuals see significance or meaning in
their lives, whereas search for meaning (Search for Presence of Meaning in Life; SML) refers to
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the pursuit of a meaningful existence (Bodner, Bergman & Cohen-Fridel, 2014). Therefore,
meaning in life was measured only using the PML subscale of the Meaning in Life
Questionnaire, (MLQ; Steger et al., 2006).
Perceived Stress
Perceived stress refers to the feelings or thoughts a given person has about how much
stress they are under at any given point in time (Cohen, Kamarck & Mermelstein, 1983). The
construct of perceived stress incorporates the following: feelings regarding the ability to control
and predict one’s life, how often one has to deal with daily hassles, the amount of unwanted
change present, and one’s confidence in their own ability to overcome a stressor given the
resources available. Simply put, perceived stress refers to how an individual feels about the
general stressfulness of their life and their ability to handle it; it was measured using the
Perceived Stress Scale (PSS; Cohen, Kamarak, & Mermelstein, 1983).
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CHAPTER TWO
Age Related Decline in Cognitive Functioning
With aging comes some degree of cognitive decline (Christensen, 2001) and while some
aspects of cognition remain grossly intact (e.g., procedural memory, vocabulary, storage of
general knowledge; Rog & Fink, 2013), changes in brain structure and function (e.g., decreased
white matter density and cortical thinning) are associated with normal age declines (Der,
Allerhand, Starr, Hofer & Deary, 2009). As such, normal aging is commonly associated with
decreases in aspects of cognitive efficiency (i.e., the level of difficulty an individual can perform
a task with a certain amount of accuracy) through reductions in abilities such as processing speed
and working memory capacity (Rog & Fink, 2013).
Slowed processing speed (i.e., the rate at which tasks of varying difficulty can be
performed) is suspected to mediate cognitive efficiency by restricting the speed at which
cognitive processes can be executed (Park & Reuter-Lorenz, 2009). Reduced processing speed
also impacts the quality and accuracy of older adults’ performance on cognitive tasks (Finkel,
Reynolds, McArdle & Pedersen, 2007). The consequences of reduced processing include
decreased working memory (Finkel, Reynolds, McArdle & Pedersen, 2007). In turn, changes in
working memory are related to decreased ability to suppress processing of irrelevant stimuli (i.e.,
inhibitory mechanisms of selective attention). This in turn, can lead to attentional impairments
that account for deficits in various aspects of executive performance including set-shifting and
cognitive flexibility (Park & Reuter-Lorenz, 2009).
Taken together, aging is associated with declines in executive functioning. Executive
functions are carried out by the coordinated activation of multiple brain areas within the
“cognitive control network.” This network includes the dorsolateral prefrontal cortex, medial
prefrontal cortex (including the anterior cingulate cortex), parietal cortex, and cerebellum
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(Bellebaum & Daum, 2007; D’Esposito, 2007). Important to note, the Prefrontal Cortex (PFC)
supports executive functioning by actively “maintaining rules online” in order to evaluate
incoming information, as well as internal states to guide response selection toward a current goal
(Miller & Cohen, 2001).
Age Related Increase in Wellbeing
Despite the fact that aging is associated with declines in executive functioning, older
adults seem to experience higher levels of emotional wellbeing as they age (Ngo, Sands,
Isaacowitz, 2016). For example, older adults report higher levels of satisfaction with family
(Charles & Piazza, 2009), fewer stressors (Aldwin, Jeong, Igarashi & Spiro, 2014) less negative
emotion (Charles, Reynolds & Gatz, 2001) as well as more satisfying interpersonal relationships
(Luong, Charles, & Fingerman, 2010) compared to younger adults. As discussed in the first
chapter, increased emotional wellbeing may be related to older adults’ tendency to attend more
readily to positive over negative information relative to younger adults (Carstensen, Mikels, &
Matger, 2006). For example, studies using eye-tracking technology to examine visual attention
have found age-related positivity effects, in that older adults tend to look away from angry or sad
faces and direct their attention toward happy faces. In contrast, younger adults focus more on
fearful faces (Isaacowitz, Waldinger, Goren, & Wilson, 2006). Thus, older adults tend to
disengage more readily from negative stimuli within their environments compared to younger
adults. Again, this phenomenon, termed the “positivity effect,” refers to the observation that
older adults attend to and remember more positive and less negative stimuli compared to younger
adults (Carstensen & Mikels, 2005).
Improvement in Emotion Regulation
The positivity effect appears to assist older adults in regulating their emotions during
unavoidable interactions with negative stimuli. For example, in an experimental study in which
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older and younger adults watched disgusting videos of surgical operations, younger adults
showed no difference between the control condition (i.e., just viewing with no instructions
termed “natural viewing”) and the increasing emotional reaction condition. Conversely, older
adults showed no difference between the control condition and the decreasing emotion reaction
condition. The authors concluded that older adults tend to focus away from negative content,
whereas younger adults tend to amplify their negative emotions during natural viewing
(Kunzmann, Kupperbusch, & Levenson, 2005). This study suggested that older adults more
readily disengage from negative content as a form of emotion regulation. Similarly, in a study
where participants were asked to remark on negative comments directed toward them, younger
adults were more likely to retaliate with disparaging remarks, whereas older adults made fewer
and less negative remarks. Moreover, the younger adults were more likely to dwell on negative
information than older adults (Charles & Carstensen, 2008). Taken together, not only do older
adults disengage from negative content, they tend to naturally diminish negative affect once
induced.
The Paradox of Aging
Many of the same executive functioning processes used to regulate attention, memory
and thoughts in non-emotional contexts are also used in the regulation of emotion (Ochner &
Gross, 2008). For example, prefrontal systems responsible for emotion regulation including the
dorsal and lateral regions of the PFC, have also been linked to selective attention and working
memory. Similarly, ventral regions of the PFC implicated in response inhibition are also
implicated in the regulation of emotion (Hölzel et al., 2011). Of note, emotion regulation, and
positive reappraisal in particular, is associated with increased activity in the PFC and decreased
activation in the amygdala, a brain region important in emotional processing. This top down
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regulation of the amygdala by the PFC is recognized as a classical neural signature of cognitive
reappraisal (Banks, Eddy, Angstadt, Nath & Phan, 2007).
The paradoxical relationship between declines in cognitive functioning and improvement
in emotion regulation across aging gives rise to a number of theoretical models. For instance,
while lateral brain structures tend to decline with age, medial brain structures are known to
remain relatively intact (Fjell et al., 2009; Lalanne, Rozenberg, Grolleau, & Piolino, 2010).
According to Martins and Mather (2016) the maintenance of medial areas of the prefrontal cortex
may be key to the conservation of emotion regulation despite declines in the lateral PFC.
Another perspective is provided by the Socioemotional Selectivity Theory (SST; Carstensen,
Isaacowitz, & Charles, 1999), which suggests that changes in motivation explain the paradoxical
relationship between cognitive and emotional functioning.
Socioemotional Selectivity Theory
SST postulates that there are two primary motivational goals related to human behavior
and temporal perspective: those dedicated to emotional meaningfulness and hedonic experience,
and those dedicated to the acquisition of knowledge and information gain. Younger adults who
view time as more expansive are likely to prioritize knowledge acquisition and novelty, whereas
older adults who view their time as more limited, are motivated to prioritize positive emotion-
related goals (Carstensen et al., 1999). Stated differently, people change their perspective as the
constraints of the finality of life become increasingly present. These changes in perspective allow
older adults to navigate their environments in such a way, that they more frequently avoid
negative experiences. This results in a higher ratio of meaningful experiences and greater
emotional wellbeing. Since older adults prioritize emotionally salient goals, SST posits that this
emphasis leads to greater attention to, and memory for, positive over negative information when
compared to their younger counterparts. Greater attention to and memory for positive
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information is what leads to the positivity effect described early and is best understood as the
way in which older adults accomplish their positive emotional goals (Reed & Carstensen, 2012).
To compliment this perspective from a neurocognitive standpoint, we can draw from the
Fronto-amygdalar Age-related Differences in Emotion Theory (FADE; Davis, Dennis, Daselaar,
Fleck & Cabeza, 2008). FADE postulates that older adults’ tendency to prioritize positive
emotional experiences is made possible through the PFC’s exertion of cognitive control to inhibit
amygdala responses to negative stimuli (St. Jacques, Bessette-Symons & Cabeza, 2009). This is
supported by observations of decreased activation within the amygdala, as well as a greater
tendency to recruit more of the prefrontal cortex (Gunning-Dixton et al., 2003) when perceiving
negative stimuli in older, compared to younger adults. FADE provides a unique prospective and
sound explanation for the role of motivation in increased wellbeing despite age-related cognitive
changes. As an example, if the amygdala were truly less responsive (due to changes in brain
structure/function rather than top-down control) a difference in responses across valences and
contexts would be observed. However, amygdala responses have been shown to be largely intact
for older adults in response to positive stimuli (Erk, Walter, & Abler, 2008).
The Role of Self-Referential Processing
While lateral executive brain structures and functions associated with the prefrontal
cortex tend to decline with age, medial prefrontal brain structures involved in self-referential
processing remain generally intact (Gutchess, Kensinger, Yoon & Schacter, 2007). According to
Martins and Mather (2016), areas of the PFC that are well maintained, namely the mPFC, may
help sustain emotion regulation function in late life despite observed declines in lateral regions of
the PFC. Research regarding the posterior-to-anterior shift (PASA), which describes a pattern of
decreased activity in posterior brain regions such as the occipital lobe and medial temporal lobe,
coupled with increased activity in anterior brain regions such as the PFC during aging, supports
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this idea (Davis et al., 2008). Specifically, enhanced self-referential processing may be due to
increases in frontal activity seen in PASA.
As such, older adults engage in more self-referential processing (by recruiting the mPFC)
during thinking of positive rather than negative information, and this activity is predictive of
later memory for the encoded information (Gutchess, Kensinger & Schacter, 2007). Conversely,
younger adults engage more readily in self-referential processing of negative stimuli and have
better memory for negative self-referential information during post-tests (Martins & Mather,
2016). Thus, findings suggest that older adults tend to selectively process positive information
more self-referentially, whereas younger adults tend to process negative information more self-
referentially (Leshikar, Park & Gutchess, 2015). Keeping this in mind, Martins and Mather
(2016) posit that by selectively increasing the self-relevance of positive, but not negative
emotional situations, medial brain structures lead to increases in wellbeing. Importantly, these
brain areas have been associated with the interpretation and elaboration of emotional information
in a personal or meaningful way (Amodio & Frith, 2006; Qin & Northoff, 2011). Both changes
in motivation as well as the maintenance of medial areas of the prefrontal cortex are likely
contributory and may even complement one another in a reciprocal manner. Regardless, it
appears that older adults likely attend to more positive stimuli and more readily engage in
positive meaning making.
Cognitive Control Model (CCM)
Regardless of the mechanisms behind the observed paradox in aging, research has
established that emotional regulation requires intact cognitive resources (Mather, 2012). As such,
recent discussions of increased wellbeing in older adults have begun to incorporate the role of
cognitive functioning and its influence on the positivity effect. Emphasizing the top-down nature
of the positivity effect (i.e., effortful processing of information from higher order brain regions),
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CCM asserts that older adults’ positive goals are implemented with the help of executive
function resources (Nashiro, Sakaki & Mather, 2012). More specifically, in order to achieve
goals and engage in emotional regulation, sufficient resources are needed to successfully orient
attention and memory to positive material. CCM asserts that older adults with intact executive
functioning will show the greatest bias towards positive stimuli as well as the most successful
emotion regulation strategies.
To highlight the role of executive functioning in emotion regulation for older adults,
Knight et al. (2007) focused on selective visual attention and found that during a divided
attention condition (as compared to a full attention control condition), older adults’ tendency to
avoid negative stimuli seen in the control condition was reversed, in that older adults spent more
time attending to negative information. As such, compared with younger adults, older adults
limited resources were more likely to be draw to negative stimuli when they were distracted
(Knight et al., 2007). Therefore, executive functioning is believed to be a central resource used
to shift cognitive processing and attain positive emotional goals.
Perceived Stress
While older adults have decreased negative responses to minimally arousing situations,
high arousal, emotionally complex situations that place increased demands on one’s cognitive
resources, leads to increased reactivity (Ngo, Sands, & Isaacowitz, 2016). Therefore, as
executive functions become overwhelmed secondary to decline, older adults become more
vulnerable to the negative effects of high levels of stress. In support of this, Hess and Ennis
(2012) found that when older adults displayed higher levels of reactivity (measured by systolic
blood pressure), their cognitive performance suffered in comparison to younger adults. This
finding provides evidence of depleted cognitive resources as task difficulty and stress increases.
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Older adults have decreased negative response to low-arousal situations but increased
emotional reactivity in highly arousing contexts that place demands on cognitive resources.
Consequently, whereas older adults regulate low levels of negative distress quite well, they have
greater difficulty when they experience chronic distress (Wrzus et al., 2012). This pattern of
decreased emotion regulation in the face of increased stress can be illustrated using positive
reappraisal. For example, when confronted with a stressor in the midst of a depressive episode,
the associated narrowing of attention to thoughts and other environmental stimuli that confirm
one’s dysphoric outlook serve to perpetuate negative thinking (Garland et al., 2015). As attention
and interpretational biases intensify with time, attempts to positively reappraise events become
less and less frequent, leaving depressed individuals more depressed (Garland, Gaylord & Park,
2009). One potential factor that may buffer against the effects of stress in order to preserve
available cognitive resources and promote emotion regulation is mindfulness.
Mindfulness
At its core, mindfulness is a mode of awareness characterized by present centered
attention to one’s current experience that is free from preoccupation (Garland, Gaylord & Park,
2009). Generally, mindfulness is associated with a number of positive benefits. To start,
mindfulness-based interventions have been largely efficacious in the treatment of a number of
clinical disorders such as anxiety and depression that are associated with negative emotional
experience (Hofmann, Sawyer, Witt, & Oh, 2010). Mindfulness has also been shown to
positively influence aspects of physical health including improved immune function and reduced
cortisol levels (Carlson, Speca, Faris & Patel, 2007). Lastly, it has also shown to produce
positive effects on psychological wellbeing (Chiesa & Serretti, 2009) and to enhance cognitive
and emotional functioning in older adults (Foulk et al., 2014; Fountain-Zaragoza & Prakash,
2017; Jha, Krompinger & Baime, 2007).
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Mindfulness, Attention, and Working Memory. Mindfulness also cultivates attention
regulation and improves cognition (Tang, Holzel & Posner, 2015; Zeidan, Johnson, Diamond,
David, Goolkasian, 2010). Many mindfulness practices emphasize focused attention through
instructions such as the following: “Focus your entire attention on your incoming and outgoing
breath. Try to sustain your attention there without distraction. If you get distracted, calmly
return your attention to the breath and start again” (Smith & Novak, 2003, p. 77 as cited in Hozel
et al., 2011). Directions such as these highlight focus on conflict monitoring, or executive
attention in mindfulness, which involves the focus of attention on an object while disregarding
distractors.
Neuroimaging research shows that the anterior cingulate cortex (ACC) is associated with
executive attention by assisting in the detection of conflicts during information processing (van
Veen & Carter, 2002). When engaged in mindfulness meditation, activation of the ACC
contributes to the maintenance of attention by alerting brain systems implementing top-down
regulation to resolve internal conflict (Hozel et al., 2011). Several neuroimaging studies provide
evidence of the involvement of the ACC in meditation. For example, Holzel et al. (2007)
illustrated that compared with age, gender, and education-matched controls, experienced
meditators showed greater activation in the rostral ACC (Holzel et al., 2007). This finding
suggests an effect of meditation practice on ACC activity. A similar effect (greater rostral ACC
activation in meditators compared with controls) was identified when individuals engaged in a
mindfulness practice while awaiting unpleasant electric stimulation (Gard et al., 2011).
Related to attention is working memory, which refers to the ability to selectively maintain
and manipulate goal-relevant information without getting distracted by irrelevant information
(Lezak et al., 2012). Jha, Stanley, Kiyonaga, Wong, and Gelfand (2010) examined the effects of
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mindfulness practice emphasizing open monitoring (i.e., directing attention to any object that
arises without reacting, and then letting thoughts related to the object pass) on working memory
capacity in a cohort of pre-deployment military personnel (U.S. Marines). Over the course of the
pre-deployment period, working memory capacity, as assessed by the operation span task (OS
PAN; Unsworth, Heitz, Schrock, & Engle, 2005), decreased in the control group which did not
receive mindfulness training. Notably, mindfulness prevented this working memory capacity
decline, which is a pattern that was observed among participants that underwent periods of high
stress. Moreover, working memory capacity at the end of the pre-deployment period was
predicted by the amount of mindfulness practice in which participants engaged. Taken together,
mindfulness may improve cognitive function.
Mindfulness and Emotion Regulation. Literature also suggests that mindfulness
practice leads to improvement in emotion regulation (Ochsner & Gross, 2005). For example,
mindfulness leads to decreased negative mood (Jha et al., 2010) and reduced reactivity to
repetitive thoughts (Feldman, Greeson, & Senville, 2010). Moreover, in a seven -week
mindfulness training program, healthy adults shown a reduction in emotional interference (e.g.,
the delay in reaction time after being presented with affective versus neutral pictures) compared
to those who followed a relaxation protocol and those in a wait-list control group (Ortner, Kilner
& Zelazo, 2007).
Research has also established that the practice of mindfulness leads to the reduction,
regulation and transformation of negative emotions. For example, Creswell, Way, Eisenberger,
and Lieberman (2007) used fMRI to show that dispositional mindfulness predicted greater
prefrontal cortical activation and reduced bilateral amygdala activation. They also demonstrated
that these two regions increasingly correlated in a negative direction during affect labeling
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relative to control tasks. Taken together, findings indicate that high levels of dispositional
mindfulness in adults lead to more effective down regulation of limbic brain regions involved in
negative emotion. Stated differently, dispositional mindfulness is linked to reduced negative
arousal due to decreased activity in brain regions dedicated to emotional processing. Relatedly,
mindfulness also promotes increased voluntary exposure to unfavorable negative experience. For
example, Niemiec and colleagues (2010) found that higher dispositional mindfulness predicted
less suppression of thoughts related to death, a greater willingness to engage in thoughts of
death, and less defensiveness in response to self-relevant threat. Lastly, Hill and Updegraff
(2012) found that higher dispositional mindfulness predicted lower emotional liability and
dysregulation in daily life. Taken together, research demonstrates that dispositional mindfulness
promotes a greater ability to withstand stressful experiences over a greater period of time, less
suppression and intensity of negative affect, and more effective down-regulation of negative
emotion.
While a variety of psychological disorders characterized by emotional dysregulation such
as post-traumatic stress disorder (Shin et al., 2005) and generalized anxiety (Monk et al., 2008)
are associated with dysfunction in the frontal-limbic network (i.e., increased amygdala activation
and decreased PFC activation), mindfulness is associated with improved emotional regulation
and improved prefrontal control over amygdala responses. For instance, during mindfulness
meditation, experienced mindfulness meditators show greater activation in the dmPFC and ACC
compared with non-meditators (Holzel et al., 2007). In a similar vein, after participants
completed an 8-week mindfulness-based stress reduction course, Farb et al. (2007) found
increased activity in participants’ ventrolateral PFC, which was interpreted as improved
inhibitory control. Following engagement in a mindfulness-based stress reduction course, social
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anxiety patients showed a quicker decrease of activation in the amygdala (Goldin & Gross,
2010). Taken together, evidence suggests that mindfulness meditation involves the activation of
brain regions relevant to emotion regulation. Furthermore, research suggests that the activation
of these regions may be altered through mindfulness practice.
Mindfulness and Positive Reappraisal. Mindfulness may specifically promote positive
reappraisal. For example, in a large cross-sectional study of mindfulness and positive reappraisal,
including participants across five samples (e.g., college students, alcohol dependent adults and
chronic pain patients) dispositional mindfulness was correlated with positive reappraisal (r=.41)
even after controlling for positive affect (Hanley & Garland, 2014). Additionally, Garland,
Gaylord and Fredrickson (2011) conducted a prospective study of 339 adults in an eight-week
long mindfulness-based stress and pain management program. They found that increases in
dispositional mindfulness over the course of training correlated with increases in positive
reappraisal and most importantly, that this relationship was partially mediated by increases in
positive reappraisal. Similarly, a quasi-experimental study comparing university students
participating in a mindful communication course found that mindfulness training was associated
with significant increases in dispositional mindfulness, which was correlated with increases in
positive reappraisal compared to a standard communications curriculum condition (Huston,
Garland & Farb, 2011). Overall, research points to the conclusion that dispositional mindfulness
leads to increased positive reappraisal.
Findings are replicated in brief interventions. For example, in an experimental study of
brief mindfulness training, the degree of state mindfulness achieved during meditation was
positively associated with increases in reappraisal. Most importantly, path analysis revealed that
the indirect effect between brief mindfulness training and reappraisal was significant through
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state mindfulness (Garland, Hanyley, Farb & Froeliger, 2015). Another recent study found that
individuals who completed a short course of mindfulness training (MBCT) evidenced
significantly greater positive reappraisal abilities during an experimental negative mood
induction manipulation, compared to a matched control group or group of participants that who
are treated with cognitive-behavior therapy (Troy, Shallcross, Davis, & Mauss, 2013).
Mindfulness to Meaning Theory
Although important, exclusively focusing on the reduction of negative mental states and
behaviors does not fully explain the mechanisms underlying the benefits of mindfulness. For
example, studies examining the effects of mindfulness versus relaxation training have shown that
while both lead to reduced distress and more positive mood states, only mindfulness practices
lead to significant decreases in ruminative thoughts (Jain et al., 2007). Such findings highlight
the idea that one of mindfulness’ mechanisms of action may include positive cognitive coping
processes. Therefore, a comprehensive account of mindfulness should also take into
consideration how the practice of mindfulness leads to enhanced wellbeing and the use of
positive reappraisal to form meaning in the face of adversity.
The literature on this topic explains that in the nonjudgmental state afforded by
mindfulness, a person is more likely to realize and/or learn that thoughts are automatic and not
necessarily our reality (i.e., thoughts are not facts). As previously discussed, reappraisal of a
stressful life event is a process that requires an effortful attentional stance in order to shift away
from the stressor to its interpretive context. According to Garland, Gaylord and Park (2009)
mindfulness is a key factor that can lessen the impact of stressful life events through decentering,
(i.e., stepping back from thoughts, emotions and sensations) (Shapiro, Carlson, Astin &
Freedman, 2006). Through decentering, mindfulness is thought to provide a buffer from
automatic appraisals by clearing working memory (Teasdale & Chaskalson, 2011) and creating
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some “psychological space” for greater perspective taking and cognitive set shifting. Indeed,
mindfulness is associated with increased cognitive flexibility (Moore & Malinowski, 2009) and
the capacity to re-orient attention (Jha, Krompinger & Baime, 2007). In sum, the
nonjudgmental, metacognitive features of mindfulness are thought to disrupt negative emotional
reactions and subsequently expand attention to include previously unattended information
relevant to the stressor and its broader socio-environmental context.
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CHAPTER THREE
Methodology
This chapter will be divided into four subsections. First, the characteristics of the
participants will be described in detail. Second, procedures will be described regarding how data
was collected. Third, the psychometric properties of each instrument will be outlined. In the
fourth section, a description of the specific study design and analyses conducted to test the
hypotheses will be provided.
Participants
This study’s aim was to determine the relationship between dispositional mindfulness,
executive functioning, positive reappraisal and meaning in life among older adults. Therefore,
the study was limited to adults 65 and older. No other exclusion was made based on gender,
sexual orientation, race, or ethnicity. A convenience sample of self-selected participants was
recruited through solicitation using flyers (placed in mailboxes) at local continuing care
retirement communities (CCRCs). The Springpoint Communities are continuum of care
residential centers offering a broad spectrum of specialized housing, recreational and health care
services for adults. Residents range from individuals of independent living status to individuals
with moderate physical/ cognitive needs who reside in the assisted living component of the
facility. Participants in this study were residents from the independent living section of the
Springpoint communities. Solicitation materials included an overview of the study, as well as a
description of requirements of participation, time commitment required to participate, and
potential benefits and risks associated with participation. Participants arranged an appointment
time to participate (via telephone) and were reminded that they may withdraw at any time
leading up to and/or during that appointment.
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Procedure
Data was collected anonymously in order to protect the identity of individuals. More
specifically, this study utilized numbers to code data for the participants. A master list matching
codes to participants was kept by the principal investigator in a locked cabinet at Seton Hall
University and only the principal investigator had access to the master list. Participants were
informed that their names were not used in connection with the study and that their responses
were not linked to their identity. Information and data received from the measures was stored on
a password protected USB memory key, which was also kept in a locked secure location within
the principal investigator’s office. In addition, informed consent was kept separate from
responses to ensure anonymity. Interested parties who have questions or concerns about the
study were advised to contact the principal investigator or the Seton Hall University IRB with
any questions.
Participants varied in cognitive functioning between little to no impairment and mild
cognitive impairment due to age-related cognitive declines. However, no residents who lacked
capacity to consent participated in the study. In order to ensure this, immediately following
informed consent, participants were given the Mini-Mental State Examination (MMSE) at the
beginning of the assessment procedures. The MMSE is a tool that can be used to systematically
and thoroughly assess mental status. It is an 11-question measure that tests five areas of
cognitive function: orientation, registrations, attention and calculation, recall and language. The
maximum score is 30. A score of 23 or lower is indicative of cognitive impairment. If
participants obtained a score below 23, they were thanked for their participation and the study
was concluded. The following statement (see Appendix C) was read aloud as a script in such
instances: “Thank you for your participation in this study! I want to thank you for taking the
time to volunteer today. For some people this assessment is longer, while for others it is shorter.
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That being said, this concludes the end of our time together, as we have gathered all the
information we need.”
If participants received a score above 23, level of social support, SES and quality of
education were then assessed along with all demographic information such as age and ethnicity.
Next, participants were given the neuropsychological assessments. Specifically, participants
were given neuropsychological assessments in the following order: (1) Matrix Reasoning; (2)
Vocabulary (3) Coding; (4) Digit Span; (5) Trail Making Test (Parts A & B); (6) Stroop Color
and Word Test; and (7) Symbol Search. This specific order was chosen in order to separate the
tasks involving a speeded element (i.e., with instructions stating “complete as quickly as you
can”). Lastly, participants were given the self-report measures related to dispositional
mindfulness, positive reappraisal, meaning in life, and perceived stress. All neuropsychological
evaluations were scheduled through the primary investigator. However, a portion of the
evaluations were administered by a doctoral level research assistant. All evaluations were scored
and then entered into SPSS by the primary investigator.
Measures
The Mini-Mental State Examination (MMSE) was first used to establish capacity to
consent. Basic attention and working memory were measured using the Wechsler Adult
Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008) subtest of Digit span (e.g., Digit
Span Forward, Digit Span Backward, and Digit Span Sequencing). Inhibitory control was
measured using the Stroop Color and Word Test (Golden, 1978) and set-shifting was measured
using the Trailmaking Test (Parts A & B) (Reitan, 1979). Processing speed was measured by the
WAIS-IV (Wechsler, 2008) subtests of Coding and Symbol Search. Abbreviated intelligence
was measured using the Wechsler Abbreviated Scale of Intelligence-Second Edition-II (WASI-
II; Wechsler, 2011). The Mindful Attention Awareness Scale (MAAS; Brown & Ryan, 2003)
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was used to measure dispositional mindfulness. The Cognitive Emotion Regulation
Questionnaire (CERQ: Garnefski et al., 2001) was used to measure positive reappraisal.
Perceived stress was measured using the Perceived Stress Scale (PSS; Cohen, Kamarak, &
Mermelstein, 1983). Lastly the meaning in life questionnaire (MIL; Steger, 2006) was used to
measure meaning in life.
Mini Mental State Examination (MMSE). The MMSE is an 11-item psychometric
screening assessment of cognitive functioning that is used to screen patients for cognitive
impairment across a number of domains including orientation, attention, calculation, language
and immediate and delayed memory. An extensive normative data set is available for the MMSE
based on both age and education, which has been updated in the current manual (Folstein,
Folstein & McHugh, 1975). The most commonly used cut-off score for the MMSE is 23, with
scores lower than this suggested moderate-severe cognitive impairment. Scores between 27-30
represent “normal” cognitive functioning, whereas 21-26 typically indicates mild cognitive
impairment (Folstein et al., 2001). Test re-test reliability for the MMSE has been examined in
both cognitive impaired and intact adults. Results have produced stable coefficients typically
ranging from .79 to .98 (Folstein, Folstein & McHugh, 1975). Validity studies examining the
sensitivity and specificity of the MMSE have demonstrated adequate sensitivity in detecting
dementia. In a recent study comprised of older adults, the standard MMSE cut-off score of 23 or
below yielded a sensitivity of .66, specificity of .99 and an overall correct classification rate of
89% in detecting dementia.
Weschler Abbreviated Scale of Intelligence-Second Edition (WASI-II). The Wechsler
Abbreviated Scaled of Intelligence-Second Edition (WASI-II; Wechsler, 2011), a revision of
Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999) is an individually
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administered assessment of intelligence for participants aged 6 through 90 years old. It provides
composite scores that estimate Verbal Comprehension and Perceptual Reasoning Abilities. The
WASI-II was used to obtain an estimate of IQ scores quickly and effectively. Average reliability
coefficients were calculated for individual subtests as well as Full Scale IQ estimates based on
two and four subtests with Fisher’s z. Average reliability estimates for the adult sample for
individual subtests, Block Design, Vocabulary, Matrix Reasoning and Similarities were .91, .92,
.90 and .91, respectively. Average reliability estimates for the adult sample for the Verbal
Comprehension and Perceptual Reasoning Composite Scores were .95 and .94 respectively.
Average reliability estimates for the adult sample for Full Scale IQ estimates based on two and
four subtests were .94 and .97 respectively. Concurrent Validity was established with WASI,
WISC-IV, WAIS-IV and the KBIT-2.
Vocabulary (Wechsler, 2011) is a task of verbal comprehension that is designed to
measure participant’s word knowledge and verbal concept formation. Vocabulary includes 3
picture items and 28 verbal items. For picture items, participants are asked to name the objected
presented. For verbal items, the participants are asked to define words that are presented both
visually and orally. Matrix Reasoning (Wechsler, 2011) is a task of perceptual reasoning that is
designed to measure the ability to analyze and logically reason with abstract visual stimuli. This
subtest includes 23 items and involves the viewing of an incomplete matrix then selecting the
response option that completes the matrix or series. Together, Vocabulary and Matrix Reasoning
correlate with the full administration of Full Scale IQ using the WAIS-IV in the .90 range
(Sattler, 2008).
Weschler Adult Intelligence Scale (WAIS-IV). The WAIS-IV (Wechsler, 2008) is the
most recent revision of Wechsler’s intelligence tests for adults. It consists of 10 standard subtest
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and 5 supplemental subtests individually administered for participants between the ages of 16
and 90. The test yields of Full Scale IQ (FSIQ) score and four Index scores: The Verbal
Comprehension, Perceptual Reasoning, Working Memory and Processing Speed Indices. The
normative group of the WAIS-IV included 2,200 individuals and was demographically
representative of the U.S. population from the 2005 Census on the basis of age, gender, ethnicity,
geographic region, and education. Internal consistency was reported at .71 to .96 for the
individual subtests. Scores on each subtest can be compared with the normative sample by
transforming raw scores to scaled scores with known means and standard deviations. For the
purposes of this study, only the WAIS-IV Digit Span, Symbol Search and Coding subtests were
used.
The WAIS-IV Digit Span (Wechsler, 2008) subtest is a task of working memory
involving the use and mental manipulation of orally presented information. The specific subtest
of Digit Span is comprised of three separate tasks: Digit Span Forward (DSF) Digit Span
Backward (DSB) and Digit Span Sequencing (DSS) For DSF, the participant is read a sequence
of numbers and is asked to repeat the numbers in the same order. For DSB, the participant is read
a sequence of numbers and is asked to recall the numbers in reverse order. Lastly, for DSS, the
participant is read a sequence of numbers and is required to repeat the numbers in ascending
order.
The two subtests of the WAIS-IV Processing Speed Index, Coding and Symbol Search,
were used to assess information processing speed. Coding (Wechsler, 2008) is a task of
processing speed that involves visual perception and visual-motor coordination (Sattler, 2008).
Using a key, the participant copies symbols that are paired with numbers within a specified time
limit. Symbol Search (Wechsler, 2008) requires visual-motor coordination, psychomotor speed,
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attention and speed of mental operations. Working within a specified time limit, the participant
scans a search group and indicates whether one of the symbols in the target group matches.
Reliability coefficients for all subtests were obtained utilizing the split-half method with
Spearman-Brown correction and test-retest reliability were computed for speeded subtests (i.e.,
Coding and Symbol Search). Average coefficients across age groups ranged from .73 to .95 for
all core subtests. Digit Span coefficients ranged from .86 to .92 in adults aged 55-90. Similarly,
coefficients for Coding ranged from .86 to .89 and from .81 to .86 for Symbol Search.
Trailmaking Test (TMT). The Trailmaking Test (TMT Parts A & B; Reitan, 1979) is
included in the Halsetead-Reitan Battery (HRB) and is one of the most frequently used tests in
neuropsychology due to its high sensitivity to cognitive impairment (Mitrushina, Boone, Razni &
Elia, 2005). The test consists of two conditions: Part A and Part B. In part A, participants are
given a piece of paper with the numbers 1-25 scattered randomly across it in circles. They are
then asked to draw lines connecting the numbers in order as quickly as possible. In Part B,
participants are given a piece of paper with both numbers (1-13) and letters (A-L) scattered
randomly across it. They are then asked to draw a line, alternating in order between the numbers
and letters (e.g., 1-A-2-B, etc.) as quickly as possible. Two scores are yielded, each reflecting the
completion time (in seconds) of each condition. During administration, if a participant makes an
error in sequencing, they are corrected, which slows down overall performance time. Maximum
completion time is 180 seconds for Part A and 300 seconds for Part B.
Previous studies have documented its usefulness as a measure of visual-motor tracking
(Lezak, Howieson, Bigler & Tranel, 2012), sequencing abilities (Martin, Hoffman & Donders,
2003) as well as executive functioning (Burgess, 2010). Sanchez-Cubillo et al. (2009) suggested
that Part A measures mainly visuoperceptual abilities, while Part B measures working memory
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and task-switching ability. The Trailmaking test is a well validated measure of executive
functioning (Reitan & Wolfson, 1985). Specific to older adults, test-retest reliability with a one-
year interval ranged from .53 to .64 for Part A and from .67 to .72 for Part B (Mitrushina & Satz,
1991).
Stroop Color and Word Test. The Stroop Test measures the relative speed of reading
colors printed in incongruous ink (e.g., the word “blue” printed in red ink). The conflict
interference the situation creates is called the Stroop Effect, which is believed to measure
response inhibition. The specific version of the test used for this study, the Stroop Color-Word
Test (Golden; 1978), has 100 items presented in five columns of 20 items on three pages. The
version used consists of a word page (black printed words "red", "blue" and "green"), a color
page ("X" letter printed in red, blue and green) and color-word page with the words presented on
the first page with the colors printed on the second page, but colors and words do not match. The
score derived is the number of correctly identified items per page within a 45 second time limit.
Mindful Attention Awareness Scale. The Mindful Attention Awareness Scale (MAAS;
Brown & Ryan, 2003) is a 15-item self-report measure in which respondents indicate their level
of awareness and attention to present events and experiences. Participants rate items (e.g., “It
seems I am ‘running on automatic,’ without much awareness of what I’m doing” & “I find it
difficult to stay focused on what’s happening in the present”) on a 6-point Likert-type scale
ranging from 1 (almost always) to 6 (almost never) (Brown & Ryan, 2003). A mean rating score
is calculated with higher scores suggesting greater levels of mindfulness. The MAAS has
demonstrated good internal consistency across a wide variety of samples (.80 - .87) and test re-
test reliability over a 1-month time period (r = .81; Brown & Ryan, 2003).
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The MAAS has also demonstrated negative relationships with stress symptoms (Carlson
& Brown, 2005) as well as depressive symptoms, affect and rumination (Brown & Ryan, 2003).
Brown and Ryan (2003) also found that individuals who do not have prior meditation experience
vary considerably in their levels of mindfulness (i.e., there is natural variance in the population).
Additionally, Brown and Ryan (2004) found that meditators scored higher on the MAAS than
non-meditators and that there is a positive correlation between MAAS scores and length of time
meditating among meditators. Therefore, the MAAS is considered to be an instrument of trait or
dispositional mindfulness. Chronbach’s alpha for this study was .82.
Positive Reappraisal. The Cognitive Emotion Regulation Questionnaire (CERQ;
Garnefski & Kraaij, 2007) is a 36-item questionnaire consists of nine conceptually distinct
subscales made up of four items that refer to what one thinks after the experience of stressful life
events. The subscales include self-blame, other blame, rumination, catastrophizing, putting into
perspective, positive refocusing, positive reappraisal, acceptance, and planning. While the scale
in its entirety will be administered, positive reappraisal specifically, will be measured with the
four-item positive reappraisal subscale of the Cognitive Emotion Regulation Questionnaire.
Participants rate items on a 5-point Likert scale ranging from 1 (almost never) to 5 (almost
always). Individual subscale scores are obtained by summing the scores (ranging from 4 to 20).
Previous research has shown that all subscales have good internal consistencies ranging from .68
to .86 (Garnefski & Kraaij 2002). The positive reappraisal subscale is an internally consistent
subscale (alpha .85) which asks the respondent “how often they think they can become a stronger
person as a result of what has happened” or “look for positive sides to the matter to cope with
stressful events” (Garnefski, & Kraaij, 2002). Chronbach’s alpha for this study was .83.
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Meaning in Life Questionnaire. Presence of meaning in life will be measured with the
Meaning in Life Questionnaire, (MLQ; Steger, Frazier, Oishi & Kaler, 2006) which measures
MIL on two dimensions: the presence of, and search for meaning in life. Participants rate 5 items
on the two subscales purpose in life (e.g., “I have a good sense of what makes my life
meaningful”), and search for meaning in life (e.g., “I am seeking a purpose or missions for my
life”). Participants rate items on a scale ranging from 1 (absolutely untrue) to 7 (absolutely true).
Items are summed by subscale, which some reversed scored. Only the PML subscale will be
used in this study. Higher scores on the PML subscale indicate higher presence of meaning in
life, or the extent to which participants feel their lives are meaningful. During initial
development and validation Chronbach’s alphas were high for both PML and SML, .86 to .88.
Test- retest stability coefficients were good (.70 and .73) and showed good internal consistency
.88 and .93 for MLQ-P and MLQ-S, respectively. High convergent correlations (.61-.74)
between the MLQ and other measures indicated good construct validity (Steger et al., 2006).
Chronbach’s alpha for PML in this study was .77.
Perceived Stress Scale. Perceived stress will be measured using the Perceived Stress
Scale (PSS; Cohen et al., 1983; Cohen & Williamson, 1988), which specifically measures the
degree to which situations in a person’s life over the past month are appraised as unpredictable,
uncontrollable and overwhelming. Participants rate items (e.g., “In the past month how often
have you felt unable to control the important things in your life”) on a 5-point Likert scale
ranging from 0 (never) to 4 (very often). Positively worded items are reverse scored and ratings
are summed, with higher scores indicating more perceived stress. This is a widely used and well-
validated scale. During development of the scale, the authors reported both internal consistency
and test-retest reliability to be high, and significant convergent correlations with related
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constructs were obtained. For example, Chronbach’s alphas ranged from 0.84 to 0.86 (Cohen et
al., 1983). In a recent validation of the PSS in a sample of 778 older adults, the internal
consistency reliability of the scale was assessed by Cronbach’s alpha, and concurrent validity
was evaluated by examining the PSS relationship with gender, depression, anxiety, and PANAS.
The internal consistency coefficient was reported at .82 and there was support for both divergent
and concurrent validity (Cohen et al., 1983). Chronbach’s alpha for this study was .85.
Covariates
The following factors were included as covariates: intellectual functioning and processing
speed. Processing speed is a basic cognitive function that subserves many other higher-order
cognitive functions, including executive functioning. Thus, executive functioning is dependent
on processing speed, and has been shown to effect performance on neuropsychological tasks of
executive functioning (Lezak et al., 2012). In addition, Friedman et al. (2006) found updating
tasks (i.e., working memory) to be highly correlated with intelligence as measured by Wechsler
IQ tests. As such, although set-shifting and inhibition are frontally mediated and relatively
unaffected by IQ (Arffa, 2007), performance on tests of working memory are affected by IQ.
Therefore, in order to control for threats to validity, specifically confounding variables that
influence performance on tests of executive functioning, measures of both IQ and processing are
included in the battery. Although not a primary part of the research questions/hypothesis,
including these variables in the evaluation is essential in order to reduce the chance that the
observed effects are due to variables other than those intended. As such, the model will
statistically control the effect of variables not included in the study.
Design
The current study employed cross-sectional research design in order to make inferences
about the relationship between/among the study variables. More specifically, a cross-sectional
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design was chosen to help define the existence, and delineate characteristics of, the particular
phenomenon of interest. This study excluded the use of experimental manipulation of the study
variables and therefore cannot be used to describe a cause-and-effect relationship. Rather, this
design was used to study phenomena involving older adults and meaning in life.
Analyses
The hypotheses were tested using a mediation/moderation path analysis model with
Structural Equation Modeling. Dispositional Mindfulness was entered as the independent
(exogenous) variable, meaning in life as the dependent (endogenous) variable, perceives stress as
a moderator, and executive functioning measures and positive reappraisal as mediators. Given
the relatively small sample size, the data was later reanalyzed in order to explore the role of
power in the overall findings. All secondary analyses were conducted using a macro called
PROCESS (Hayes, 2013), a tool for path analysis-based mediation and moderation that utilizes
bootstrapping for effect size estimation (Hayes, 2013).
Research Questions
• Question 1: Does dispositional mindfulness predict increased meaning in life?
• Question 2: Is the relationship between dispositional mindfulness and meaning in life
mediated by executive functioning and positive reappraisal?
• Question 3: Is the proposed model moderated by stress, such that higher levels of stress
weaken the relationship between dispositional mindfulness and executive
functioning?
Statement of Hypotheses
• Hypothesis 1(a): Dispositional mindfulness will positively correlate with presence of
meaning in life.
• Hypothesis 1(b): Executive functioning and positive reappraisal will positively correlate
with presence of meaning in life.
• Hypothesis 2 (a): Dispositional mindfulness will be positively correlated with positive
reappraisal.
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• Hypothesis 2 (b): Dispositional mindfulness will be positively correlated with executive
functioning.
• Hypothesis 3 (a): The relationship between dispositional mindfulness and presence of
meaning in life will be mediated by positive reappraisal and executive
functioning.
• Hypothesis 4 (a): The mediational effect between dispositional mindfulness and
executive functioning will be moderated by perceived stress.
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CHAPTER FOUR
Results
The purpose of this chapter is to present the results of the study. The chapter begins with
a review of participant characteristics as well as the preliminary analyses and then proceeds to an
explanation of the primary hypotheses plan by providing a description of structural equation
modeling (SEM). In addition, an explanation for secondary analyses used given the small sample
size is provided.
Characteristics of Participants
The final sample was comprised of 47 older adults. Participant characteristics are
presented in Table 1. Ages ranged from 68 to 95 with a mean of 84 years. Approximately
seventy percent of the sample was female and thirty percent was male. The majority of the
participants in the current study were non-Hispanic White (87%) followed by Hispanic/Latino
(9%), Black/African American (2%) and Asian (2%). Most participants had Bachelor degrees
(40%), followed by Master degrees (30%), high school (13%) and Associates degrees (9%).
Table 1 Demographic characteristics of participants
Age, years 84.11 ±6.6
Female, % 70.2
Race/Ethnicity
Non-Hispanic White, % 87.2
Non-Hispanic Black, % 2.1
Hispanic White, % 2.1
Asian, % 2.1
Education, less Bachelors, % 21.3
Marital Status
Married, % 31.9
Widowed, % 53.2
Divorced, % 10.6
Single, % 4.3
Note. n = 47; Continuous variables are presented as mean ±standard deviation and categorical
variables are presented as percentage.
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Preliminary Analyses
Data screening involved a number of steps to examine accuracy of data entry, the
normality of distributions and multivariate outliers. First, frequencies were examined to assess
for out-of-range values. Across all variables, except for the age of two participants, no out-of-
range values were identified. Values were determined to be data entry errors and were corrected
to reflect accurate ages. All relevant variables were calculated and checks for missing data were
then performed. Across all variables, two participants had missing data for processing speed
(WAIS-IV PSI) and one had missing data for cognitive inhibition (Stroop Interference). Missing
data for PSI was related to difficulty with fine-motor task due to tremor disorders. Missing data
for cognitive inhibition was related to an inability to differentiate between the colors due to
color-blindness. As a result, both participants could not complete the measures. Missing data
comprised a small percentage of the data (<5%) and was therefore replaced with the mean of all
cases. All relevant variables were calculated again and checks for computation errors were
performed.
Next, scores in the data set were converted into standardized scores (e.g., Z score) to
determine whether there were outliers (z-scores ≥ 3.0). No univariate outliers were identified in
the sample. To identify multivariate outliers (i.e., cases that revealed unusual patterns of scores
in combination) a Mahalanobis distance statistic was used. Mahalanobis distance refers to the
distance of one variable from the centroid of the remaining ones where the centroid is the point
created by the means of all the variables (Field, 2013). Once the Mahalanobis distance statistic
was calculated, the criterion of 18.47 was set based on the degrees of freedom (df) and the
critical value of chi-square statistics. No multivariate outliers were identified. Lastly, for all
continuous variables, normality of the distributions was assessed; non-normality is defined as
skewness > 3.0 or kurtosis > 2.0 (Kline, 2004). All variables were within parameters.
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Means and standard deviations were obtained for all major study variables (Table 2).
With regards to self-report measures, participants’ perceived level of stress was measured by the
PSS (Cohen, 1983). High scores reflect higher levels of perceived stress. Presence of meaning in
life was measured using a subscale of the MIL (Steger et al., 2006). High scores indicate more
felt presence of meaning in life. Positive reappraisal was measured using a subscale of the CERQ
(Garnefski et al., 2001). Higher scores indicate greater tendency to use positive reappraisal
strategies. Dispositional mindfulness was measured using the MAAS (Brown & Ryan, 2003),
with higher scores indicating more trait mindfulness (Garland, 2007). Working memory was
measured using the Digit Span subtest of the WAIS-IV. Scores are presented as scaled scores
with a mean of 10 and a standard deviation of 3. Average scores fall between 8 and 11. Set-
shifting was measured using Trailmaking Test Part B and cognitive inhibition was measured
using the interference T-score of the Stroop test. Scores are presented as T-scores with a mean
of 50 and a standard deviation of 10. Average scores fall between 43 and 56.
Table 2 Means and Standard Deviations of Major Study Variables
Mean SD
Perceived Stress 14.89 6.92
Regulatory Processes
Positive Reappraisal 13.27 3.96
Working Memory 11.79 2.44
Set-Shifting 46.60 7.95
Cognitive Inhibition 53.70 9.35
Dispositional Mindfulness 4.64 0.65
Meaning in Life 27.51 4.78
Note. N=47
Additionally, the major study variables’ mean and standard deviation were examined to
ensure consistency with the standardization sample. All values were consistent with previous
validation studies. Internal consistency reliabilities were also obtained and consistent with
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previous research (range = .77-.85). Lastly, before testing the hypothesized relationships,
potential differences because of gender, ethnicity and relationship status were tested for the
major study variables, through separate Multivariate Analyses of Variance (MANOVA). Results
of the analysis revealed no significant multivariate differences on the outcome measures for
gender, ethnicity or relationship status.
Pearson correlation was used to evaluate potential linear relationships among the study
variables. The result of the correlation analysis is summarized in Table 3. These correlations
suggested significant relationships between perceived stress, positive reappraisal and meaning in
life. Executive functioning and dispositional mindfulness were unrelated to other study
variables. Additionally, because all significant correlations were below .85, there were likely no
multicollinearity issues (Kline, 2004).
Table 3 Correlations between Major Study Variables
PSS Pos-R WM SS Cog-I DM
Pos-R -.403**
WM -.190 -.025
SS -.109 .043 .397**
Cog-I .153 -.156 .002 .328**
DM -.007 .245 .046 -.065 -.176
MIL-P -.330* .288* .065 .138 .004 .097
Note. *p < .05 (2-tailed); **p < .01 (2-tailed). PSS = Perceived Stress; Pos-R= Positive Reappraisal,
WM= Working Memory, SS= Set-Shifting, Cog-I= Cognitive Inhibition, DM= Dispositional
Mindfulness, MIL-P= Presence of Meaning in Life.
Primary Analysis
Structural Equation Modeling. In the present study, I hypothesized associations among
the multiple variables (i.e., dispositional mindfulness, perceived stress, executive functioning,
positive reappraisal and meaning in life). Therefore, Structural Equation Modeling (SEM) was
used to test the correlational links between the variables. Specifically, hypotheses were tested
using a mediational path analysis model with SEM. Dispositional mindfulness was entered as the
independent variable, meaning in life as the dependent variable, and positive reappraisal and
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executive functioning as the mediational variables. Perceived stress was added as a moderator of
the relationship between the IV and executive functioning. Based on the N: q rule, which
describes the power, “. . . in terms of the ratio of cases (N) to the number of model parameters
that require statistical estimates (q)” (Fonseca, 2013, p. 12), a subject to parameter ratio of 12:1
is required for sufficient power in the current model. There are 5 measured variables in the
present model (1 independent variable, 2 mediators, 1 moderator and 1 dependent variables),
along with their 5 corresponding parameter error estimates. Thus, using the N: q rule, with 12
participants per each parameter (6), the minimum number of participants needed for sufficient
power was 72 participants. This is consistent with sample size empirical studies with SEM (e.g.,
Kim, 2005; Wolf, Harrington, Clark, & Miller, 2013).
In the present study, data collection was capped at 47 participants. There are a number of
reasons why this course of action was determined to be the most appropriate given the learning
objectives and overall goals throughout this learning process. To start, taking into account the
practical aspects of managing this project, concerns were raised about the study’s overall
feasibility. This study required an intensive time commitment dedicated to training research
assistants in standardized test administration, psychometric test properties and scoring. The
intensity of training required was underestimated. Even so, it was an extremely rewarding
experience to step into the role of teacher. Furthermore, it allowed for a fuller appreciation of
the comprehensive knowledge base and complexity of skill required for neuropsychological
evaluation. Additionally, this study strived to collect comprehensive neuropsychological data
through assessment of various covariates, a number of executive functions as well as the self-
report questionnaires. As a result, each evaluation required 2.5 hours of time for administration
and scoring. Again, time spent in data collection was underestimated; however, insight into the
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requirements of rigorous, quality research was gained. Keeping this in mind, the intensive time
commitment and knowledge gained were weighted against the overall goal of project completion
and scientific production.
Given the relatively small sample size, it was decided that the data would be later
reanalyzed in order to explore the role of power in the overall findings. All secondary analyses
were conducted using a macro called PROCESS (Hayes, 2013) in SPSS statistical software
(Version 24). PROCESS is a tool for path analysis-based mediation and moderation that utilizes
bootstrapping for effect size estimation (Hayes, 2013). Bootstrapping allows for resampling by
repeatedly taking subsamples from the original data collected and computing the effect size
within each subsample. This process is repeated thousands of times to estimate the shape of the
sampling distribution for the desired effect size. There are two key strengths to using the
PROCESS bootstrapping approach. First, it does not require a normal sampling distribution,
which allows for testing of effects in the presence of non-normality (Hayes & Preacher, 2014;
Hayes & Scharkow, 2013; Preacher & Hayes, 2004). Second, it can be used in smaller samples
because bootstrapping allows for greater statistical power while simultaneously minimizing the
type I error (Hayes & Preacher, 2014). Supplemental analyses using PROCESS will be
discussed following the primary analysis section.
Initial Hypothesized Model
The results of the tested hypothesized SEM model are summarized in Table 4. Overall
global fit indexes were poor suggesting that the hypothesized model could be improved, χ2(10) =
26.12, p = .004. The fit indexes and their respective values are: GFI = .87, CFI = .83, TLI = .64,
NFI = .77 and RMSEA = .19. The hypothesis that dispositional mindfulness positively correlates
with meaning in life was not supported (β = .01, p = .98). Executive functioning and positive
reappraisal did not significantly positively correlate with presence of meaning in life.
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Specifically, the direct effect of executive functioning on meaning in life resulted in the
following standardized β = .131, p = .346. The direct effect of positive reappraisal on meaning in
life was trending towards significance, but not significant, β = .281, p = .063.
Table 4 Regression Weights for Hypothesized Model
The second hypothesis proposed that dispositional mindfulness would positively
correlate with positive reappraisal and executive functioning. As predicted there was a
statistically significant relationship between dispositional mindfulness and positive reappraisal, β
= .275, p =.030. Conversely, this pattern was not observed for executive functioning, β = .017, p
=.566. To test mediational effects for executive functioning and positive reappraisal on the
relationship between dispositional mindfulness and meaning in life, the author examined
corresponding significance tests (p < .05) for tests of indirect effects. Mindfulness and meaning
in life were not mediated by either positive reappraisal (p = .171) or by executive functioning (p
= .089). The interaction between mindfulness and stress did not have a significant effect on
executive functioning, β = -.013, p = .483. Thus, mindfulness and meaning in life were
Parameter
Estimate Lower Upper p
Executive Functioning D. Mindfulness -.051 -- .137 .433
Executive Functioning D. Mindfulness .017 -.195 -- .566
Pos-Reappraisal Executive Functioning .219 -.217 .415 .153
Pos-Reappraisal D. Mindfulness .275 .044 .510 .030
Trails B Executive Functioning .248 -- .456 .232
Interference Executive Functioning .568 -- .744 .208
Digit Span Executive Functioning 1.458 1.141 -- .000
Meaning-IL Executive Functioning .131 -- .304 .346
Meaning-IL Executive Functioning .281 -.024 .580 .063
Meaning-IL D. Mindfulness -.002 -.318 .290 --
Note. n = 47
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independent of executive functioning and executive functioning was not significantly influenced
by the relationship between mindfulness and stress.
Revised Model
The original hypothesized model was limited in several ways. First, the model tested may
have been affected by the small sample size in the current study. The model was complex
particularly when compared against the sample size. Further, model statistics indicated that the
model was a poor fit, which may compromise interpretation of direct and indirect effects. To
examine if an alternative model could be produced, the author revised the model to improve fit.
The results of the revised model are found in Figure 2 and Table 5.
The model significantly improved with modification, χ2 (8) = 4.09, p = .85. The fit
indexes improved from the original model. The values were as follows: GFI = .97, CFI = 1.00,
TLI = 1.44, NFI = .87 and RMSEA = .01. While the model significantly improved, only the
relationship between mindfulness and positive reappraisal were significant (β = .280, p =.02).
Executive functioning did not mediate the relationship between mindfulness and meaning in life
(p= .332).
Table 5 Regression weights for revised model
Parameter
Estimate Lower Upper p
Executive Functioning D. Mindfulness .005 -.294 .446 .787
Pos.-Reappraisal D. Mindfulness .280 .044 .481 .021
Digit Span Executive Functioning .284 … .463 .232
Interference D. Mindfulness .272 … .442 .336
Trails B Executive Functioning 1.461 1.120 … .000
Meaning-IL Pos-Reappraisal .291 -.100 .536 .092
Meaning-IL Executive Functioning .134 … .463 .232
Note. n = 47
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Supplemental Analysis
As discussed, given that the final sample size was below expected power estimates
PROCESS was performed. In order to determine the appropriate sample size for this, power
analyses were conducted. The power of a statistical analysis refers to the likelihood that the test
would produce a statistically significant result, given that the variable outcome is in fact being
tested. Witte and Witte (2007) define statistical power of a hypothesis as the probability of
detecting an effect or rejecting the null hypothesis. Power analyses were conducted to data
collection to determine the appropriate sample size for a meaningful result using an F test. This
power analysis was conducted using the computer program G*Power which determined that with
3 predictors and an effect size of .25 an N of 47 was required at minimum (Erdfelder, Faul, &
Buchner, 1996).
Mediation Analyses
To examine dispositional mindfulness as a predictor of mediators (executive functioning
and positive reappraisal) and to examine executive functioning and positive reappraisal as a
mediator of the association between dispositional mindfulness and meaning in life, PROCESS
Model 4 was used (see Figure 4) (Hayes, 2013). Dispositional Mindfulness was entered as the
predictor variable (X; z-scored); presence of meaning in life was entered as the criterion variable
(Y; z-scored). Executive functioning and positive reappraisal were entered as the mediator
variables (M). The cognitive model included adjustment for covariates (IQ and Processing
Speed). A 95% confidence interval using 10,000 bootstrap resamples was computed.
In the proposed model, greater dispositional mindfulness did not predict increases in
meaning in life (path c β = 0.70, p = .51). Greater dispositional mindfulness also did not predict
increases in executive functioning or positive reappraisal (Executive functioning, path a β = -
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0.37, p = .30; Positive Reappraisal path a β = 1.37, p = .11). In sum, dispositional mindfulness
did not predict increases in meaning in life, executive functioning, or positive reappraisal.
Regarding executive functioning and positive reappraisal as predictors of meaning in life
(path b), increases in executive functioning did not predict increased meaning in life (path b β =
.79, p = .43), while there was a trend towards increased meaning in life via increased positive
reappraisal (path b β = 1.9, p = .06). In sum, the direct effect of dispositional mindfulness on
meaning in life remained insignificant. That said, accounting for meaning in life after
accounting for mediators was also insignificant (all path c’ ps >.05). Results can be found in
Figure 3.
Moderated Mediation Analyses
To determine if perceived stress moderates the association between dispositional
mindfulness and executive functioning in the model mentioned above. Hayes’ PROCESS macro
for Model 7 was used (see Figure 5). In a moderated mediation model, perceived stress was
entered as a moderator (W) of the association between dispositional mindfulness (X) and
executive functioning (M) in the mediation model described above. Overall, given dispositional
mindfulness lack of predictive ability for meaning in life, there was no evidence of moderated
mediation (Index of moderated mediation 95% CIs included zero; see Table 6).
Table 6 Results from moderated mediation analyses
Index of moderated mediation Evidence
of
moderated
mediation Model Mediator
Moderator
of Path A Index
Standard
Error
95% CI
Lower
95%
CI
Upper
Model
1
Executive
Functioning PSS -0.0199 0.0497 -.1843 0.0392 No
Note: n = 47.
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CHAPTER FIVE
Discussion of Results
This chapter will discuss the implications of the results presented in Chapter 4. First,
findings from preliminary analyses are addressed, including their relationship to the previous
literature and clinical implications. Second, the results from primary/supplemental hypothesis
testing are discussed, as well as their relationship to the previous literature. Next, a discussion of
clinical implications will be presented. Lastly, explanations for the results and limitations to the
current study are put forth.
This study investigated the relationship between dispositional mindfulness and meaning
in life, while taking into consideration older adults’ available cognitive resources and use of
positive reappraisal. The primary purpose of this study was to determine if the relationship
between dispositional mindfulness and meaning in life is mediated by executive function and
positive reappraisal. Additionally, this study examined the moderation effect of perceived level
of stress on the relationship between dispositional mindfulness and executive functioning. The
study utilized a cross-sectional design and structural equation modeling to answer the research
questions.
Preliminary Analyses
Preliminary analyses were conducted to first describe the sample and the variables, and to
determine whether to control for demographic categories in analyzing the primary hypotheses.
Using a series of MANOVAs, participants did not differ across the major study variables based
on the demographic categories (i.e., gender, ethnicity, educational attainment, marital status).
Additionally, the major study variables’ mean, standard deviation, and reliability coefficients
were examined to ensure consistency with the standardization sample. All values were consistent
with previous validation studies.
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Next, bivariate correlations were performed. Correlation analysis revealed that positive
reappraisal was positively correlated with meaning in life. Specifically, participants who engaged
in more positive reappraisal reported higher presence of meaning in life. Though correlations
have been made, causation cannot be implied. Even so, this finding is largely consistent with the
current literature and highlights the role of positive reappraisal as an active coping strategy that
promotes reengagement with stressful events in order to make new meaning (Garland, Gaylord
& Park, 2009).
Bivariate correlations also revealed that perceived stress was negatively correlated with
both positive reappraisal and meaning in life. Specifically, increased perceived stress was
associated with less frequent use of positive reappraisal as well as decreased presence of
meaning in life. Previous research on post-traumatic growth (see Tedeschi & Calhoun, 2004 for
review) points to a curvilinear relationship between stress and positive psychological outcomes,
such that higher levels of chronic stress overwhelm the system and make it more difficult to
engage in positive reappraisal (Helgeson, Reynold & Tomich, 2006). Of note, the mean statistic
for perceived stress in this study was 14.9, which corresponds to moderate levels of stress.
Qualitative analysis of the specific responses suggested that stress sources were chronic (e.g.,
chronic medical conditions, loss of independence) rather than acute (e.g., death of a loved one,
recent loss of a job/financial resource). Taken together findings are in line with research that
highlights the notion that high levels of chronic stress (as opposed to moderate) leads to
decreased adaptation (Seery, Holman & Silver, 2010).
Primary Analyses
It was hypothesized that dispositional mindfulness would positively correlate with
presence of meaning in life for older adults. Based on the results of the path analysis model with
SEM, H1 (a) was not supported. Next, I expected that executive functioning and positive
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reappraisal would positively correlate with presence of meaning in life. Executive functioning
and positive reappraisal did not significantly positively correlate with presence of meaning in life
H1 (b). Next, I predicted that dispositional mindfulness would be positively correlated with
positive reappraisal H2 (a) and executive functioning H2 (b). Based on the SEM analysis, as
predicted, there was a statistically significant relationship between dispositional mindfulness and
positive reappraisal. Conversely, this pattern was not observed for executive functioning.
In examining for mediational effects, I hypothesized that the relationship between
dispositional mindfulness and presence of meaning in life would be mediated by positive
reappraisal and executive functioning H3 (a). Mindfulness and meaning in life were not mediated
by either of the proposed factors, which is not surprising given the lack of direct effect between
dispositional mindfulness and meaning in life. Lastly, I proposed that the mediational effect of
executive functioning would be moderated by perceived stress. The interaction between
mindfulness and stress did not have a significant effect on executive functioning and did not
support the hypothesis H4 (a). An explanation for null findings will now be discussed.
Overall, the majority of findings did not support the proposed hypotheses with one
notable exception: dispositional mindfulness was significantly related to positive reappraisal.
When entered into the model, as predicted, dispositional mindfulness significantly related to
positive reappraisal. This finding is consistent with literature that suggests mindfulness
facilitates flexible selection of new cognitive reappraisals (Garland et al., 2017). The
hypothesized mechanism through which this occurs is decentering (i.e., greater psychological
"space"), which is defined as the recognition that thoughts and feelings are merely components
of one’s true experience that remain separate from the self (Segal, Williams, & Teasdale, 2002).
This recognition allows for the broadening of attention to previously unnoticed information,
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which leads to more adaptive appraisals (Garland, Farb, Goldin & Fredrickson, 2015). In
support of the findings, research on older adults has suggested that mindfulness may capitalize
on their tendency to prioritize motivational goals related to the preservation of life’s meaningful
experiences through increased attentional control and emotion regulation abilities (Zaragoza &
Prakash, 2017).
Again, this study provided evidence that dispositional mindfulness promotes the use of
positive reappraisal strategies. While this study emphasized increased wellbeing in late life, a
large proportion of older adults still experience anxiety and depression (Nowland, Wuthrich &
Rappee, 2015). Additionally, late life is often associated with increased medical complications,
cognitive decline and changes in functional status, death of loved ones, as well as relocation
(Fikesenbaum, Greenglass & Eaton, 2006). In contrast, positive reappraisal, a meaning-based
coping strategy, is associated with improve physical health and psychological well-being in older
adults. Therefore, positive reappraisal can function as a valuable coping technique for older
adults, particularly as they cope with unavoidable stressors. Based on the findings, promoting
positive reappraisal through mindfulness (i.e., decrease maladaptive automatic responses to
environmental stimuli through greater mindfulness) may be particularly beneficial for older
adults.
Explanation of Findings
The majority of the hypotheses in the present study were noted supported. The lack of
proposed associations between the study variables was surprising given the previously discussed
literature on mindfulness, positive reappraisal, executive functioning and meaning in life
(Garland et al., 2009; Mather, 2012; van Vugt, 2015). In the presence of these null findings, two
possible explanations are plausible: (1) the findings may reflect the true state of these variables
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and (2) the findings do not reflect the true nature of the relationships and, instead, are influenced
by methodological issues (Kazdin, 2003).
Assuming the first explanation was true, the observed relationships, or lack-there-of, in
the present study would reflect their true state in nature (Kazdin, 2003). Indeed, while studies
have found that mindfulness is related to increases in positive reappraisal, meaning in life
(Garland et al., 2009), and executive functioning (Moynihan et al., 2013), the majority of
research to date has been done with younger adults. Research focusing on the relationship
between the executive functioning and mindfulness in older adults has produced more mixed
results. For example, many studies specific to older adults have found non-significant
associations between dispositional mindfulness, working memory, inhibition and quality of life
(Mallya & Fiocco, 2015) as well as both significant and non-significant associations between
mindfulness and set-shifting (Prakash et al., 2015).
In examining research that utilized interventions, mixed findings also exist. For example,
one study that evaluated improvements in attentional control via working memory following a
robust mindfulness intervention, found no significant improvements compared to a wait list
control group (O’Conner et al., 2014). In another study, there were no differences between TMT
part A and B or a verbal fluency task in a Mindfulness-base stress reduction group compared to
reading and relaxation comparison groups (Mallya & Fiocco, 2016). Similarly, though research
on dispositional mindfulness and stress in older adults has been established (Prakash et al.,
2015), positive reappraisal and presence of meaning in life (particularly as it relates to MMT) has
only been studied in younger populations. Taken together, it may be the case that the major study
variables are less salient for older adults.
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It may also be the case that that methodological limitations have contributed to the
observed findings. Assuming the second explanation is true (the findings do not reflect the true
nature of the relationships), the following methodological issues are worth considering: (1)
inadequate measurement of key variables, (2) insufficient statistical power, and (3) sample
selection. Each of these methodological issues is discussed below.
Construct measurement
Dispositional Mindfulness. To start, dispositional mindfulness did not predict executive
functioning or meaning in life. This finding is in contrast to the literature at large, which has
shown that mindfulness is associated with increased cognitive flexibility (Moore & Malinsowski,
2009), inhibition (Teper & Inzlicht, 2003) and working memory (Jha et al., 2010). Moreover,
dispositional mindfulness been showed to improve wellbeing (Creswell et al., 2012) and increase
meaning in life (Garland et al., 2017). Initial thoughts for this discrepant finding may relate to
the way in the current study defined and measured dispositional mindfulness. This study used the
MAAS to measure dispositional mindfulness across one factor: the frequency of open attention
to and awareness of events occurring throughout day-to-day consciousness (Brown & Ryan,
2003). The MAAS was chosen, in part, due to its emphasis on mindlessness (e.g., “I find myself
doing things without paying attention”), which is more easily understood and perhaps a more
common experience within the general population (Van Dam, Earleywine & Borders, 2010).
However, given what is known about decreases in attentional processing via normal aging
processes, it may have been more appropriate to use scales that measure dispositional
mindfulness along additional core factors. One example the Philadelphia Mindfulness
Questionnaire (PHLMS; Cardaciotto, Herbert, Forman, Moitra, & Farrow, 2008) which
measures dispositional mindfulness along two subscales: present moment awareness and
nonjudgmental acceptance. In support of this, Splevins et al. (2009) found that specific
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components of mindfulness conferred greater benefits than others in different domains. For
example, accepting was related to a reduction in depressive symptoms, while other facets were
not. Future studies should incorporate measures of dispositional mindfulness that focus on
additional components other than attention (i.e., acceptance, awareness).
Additionally, mindfulness was measured as a dispositional trait, rather than an
intervention induced state. Indeed, many of studies cited above examine the effects of
mindfulness interventions (Farb et al., 2010; Moore & Malinsowki, 2009). Training often
focuses on three different types: (1) focused attention meditation; (2) open monitoring meditation
without selective focus (Lutz, Slagter, Dunne, & Davidson, 2008); and (3) loving-kindness
meditation, which involves the cultivation of love and compassion toward oneself and others
(Fountain-Zaragoaza & Prakash, 2017). Perhaps a mindfulness-based intervention would show
more robust effects on the outcome measures. Future studies may wish to create and standardize
such training programs in randomized designs that include active comparison groups to better
characterize the benefits of mindfulness training moving forward.
Lastly, the particular items on the MAAS may have been inappropriate with an older
adult population. For example, sample items on the MAAS included: “I forget a person’s name
almost as soon as I’ve been told it for the first time” and “I drive places on ‘automatic pilot’ and
then wonder why I went there.” Extensive research suggests that normal aging is commonly
associated with decreases in the efficiency of information processing observed through
reductions in processing abilities such as short-term memory (Rog & Fink, 2013). These same
cognitive abilities are often affected in depression, which according to research occurs in
approximately 1 in 15 older adults over the course of 1 year (Mojtabai, & Olfson, 2004). As a
result, questions on the MAAS may be confounded by age related cognitive changes, particularly
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in a population of older adults whose mean age was 85. Lastly, given the fact that the
mindfulness data was slightly, though not significantly, negatively skewed, it seems likely that
older adults may have over reported dispositional mindfulness, perhaps in an effort to decrease
one’s experience with common cognitive changes associated with aging.
Executive functioning. Executive functioning was not significantly related to any of the
major study variables. This finding is also discrepant with previous research that indicates
executive functions are a precursor to successful engagement in emotion regulatory strategies
(Mather, 2012) and are enhanced through mindfulness (van Vugt, 2015). A possible explanation
relates to the fact that participants did not differ significantly across the major study variables
based on the demographic categories (i.e., gender, ethnicity, educational attainment, marital
status). This likely speaks to the heterogeneity of the sample population as ethnicity and
educational attainment do impact performance on cognitive testing in clinical settings (Manly,
2008). For example, cross-cultural variation in neuropsychological test performance has been
observed with regards to ethnicity (Schwartz et al., 2004) and early environmental factors (Byrd,
Miller, Reilly, Weber, Wall & Heaton, 2006). As an example, specific to this study, lower levels
of education have been shown to significantly impact performance on Trails A and B for older
adults, necessitating a separate set of norms (Tombaugh, 2004). Keeping that in mind, most
participants where non-Hispanic White and over 90% of the sample had above 12 years of
education. Heterogeneity may have impacted the observed findings.
Given the MAAS’s emphasis on attention, significant results for executive functioning
may have been more likely if the current study chose to use measures related to attentional
control. Attentional control is defined as the ability to effectively process information by
selecting relevant information while simultaneously ignoring irrelevant, interfering information
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in order to carry out one’s goal (Petersen & Posner, 2012). The concept of focusing on attention
control is underscored by research that documents age-related declines in various aspects of
attention, such as selective and sustained attention (Zaragozza & Prakash, 2016). This type of
attention is typically measured through computer-based visual search tasks such as the NIH
Toolbox Flanker Inhibitory Control and Attention Test (Slotkin et al., 2012). Other potential
options could have been the Conner’s Continuous performance test (CPT-III) or the Ruff 2 and 7
Selective Attention Test (Ruff & Allen, 1996), which have also been used in prior research.
Lastly, the measure of intelligence used may not have adequately controlled confounds.
This is because potential cognitive declines (i.e., discrepancies from premorbid intelligence
measures) were not obtained. It is possible that cognitive decline or the difference between
predicted and obtained IQ could be more sensitive measure particularly for high functioning
older adults. Future studies may wish to include a measure of premorbid functioning such as the
Wechsler Test of Adult Reading (WTAR; Wechsler, 2001).
Statistical Power
Another possibility is that the study had insufficient statistical power to detect a
difference that did in fact exist. Specific to structural equation modeling (SEM), many fit indices
are based on the large sample-size dependent goodness of fit tests (Kline, 2004). SEM’s ability
to recover model estimates with small samples is limited and increases the likelihood of
obtaining non-significant findings. Given the relatively small sample size N= 47, it is possible
that a real effect was missed by simply not taking enough data, especially given the model’s
complexity. However, it is important to note that other similar neuropsychological studies with
comparable sample sizes utilizing similar regression techniques have found similar findings (e.g.,
Londeree, Whitmoyer & Prakash 2016; Mallya & Fiocco 2015; Prakash, 2011; Fountain-
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Zaragoza). Moreover, bivariate correlations and beta values do not suggest that increased number
of participants would have yielded significant findings.
As a final note, additional tests known to be relatively robust to small sample sizes were
computed and did not yield improved results. As discusses previously, PROCESS, a
computational tool for path analysis-based mediation and moderation that utilizes a
bootstrapping approach to effect size estimation (Hayes, 2013; Preacher & Hayes, 2004) was
used. PROCESS can be used in smaller samples because bootstrapping confers greater
statistical power while minimizing the type I error rate (Hayes & Scharkow, 2013). Even so,
based on preliminary correlational findings, the overall model and findings were not expected to
improve. Largely consistent with the original SEM model, the findings did not support the
proposed hypotheses. This suggests that though power may be a potential contributing factor, it
is not necessarily the reason for the observed findings.
Sample Selection
An additional explanation for the observed results is sampling bias, which likely exerted
a greater impact on the results than the variables themselves. This research studied a
convenience sample of older adults. Those who volunteered to participate likely differ from the
population at large. Put differently, participants who took part in the study expressed interest in
cognitive testing and thus may share some inherently similar characteristics (e.g., stronger
cognitive functions, high levels of self-efficacy). Moreover, in examining the demographics of
the study participants, only approximately 20% had less than 16 years of education. In fact,
many participants had 18-20 years of education. Therefore, the current sample is only
representative of highly educated older adults. Moreover, mean full scale IQ (WASI-II 2-Subtest
IQ= 116) was in the high average range and 1 SD above the population mean. Taken together,
the study’s educated sample showed evidence of high cognitive reserve (i.e., resilience to age-
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related brain changes via education and occupational attainment) throughout testing (Stern,
2012). Therefore, the sample is restricted in terms of generalizability to the overall population.
This lowers the changes of observing a linear relationship between the cognitive measures and
other study variables. Regardless, this is a rare sample that deserves attention in future research
looking to highlight the protective role one’s life experiences in overall brain health.
In a similar vein, this sample, in comparison to their same-aged peers, performed above
expectation with regards to verbal and nonverbal reasoning abilities as well as on tests of
processing speed and executive functioning. Interestingly, the participants in the present sample
displayed higher than average meaning in life (MIL mean = 27) and above average utilization of
positive reappraisal based on a norm group of adults 65 years of age and older (Positive
reappraisal mean = 13.27). The participants also displayed moderate levels of dispositional
mindfulness based on guidelines provided by Loucks et al. (2016). Taken together, observation
of sample characteristics suggests that older adults in this sample more frequently engaged in
positive reappraisal and saw life as having a valued meaning and purpose. They also reported
being generally mindful. Taken together, it appears that the present sample displayed high levels
of all variables with less variation originally expected. This also impacts generalizability to the
general population.
Clinical Implications
In terms of clinical implications, results suggest that using mindfulness interventions with
older adults who are faced with stressors may be beneficial. In this study, older adults who were
higher in dispositional mindfulness more frequently used positive reappraisal strategies.
Though variability exists, individuals often face chronic stress (as opposed to acute) related to
caregiver burden, grief and the loss of one’s financial and physical independence in the context
of aging (Lavretsky & Newhouse, 2012). Therefore, providing mindfulness interventions to
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older adults may enhance their ability to reinterpret chronic stressors as benign or even
beneficial. For example, a mindfulness-based group geared towards caregivers of spouses with
neurodegenerative diseases such as Parkinson’s disease or Alzheimer’s disease may increase
acceptance via improved ability to positively reappraise.
Given evidence of the usefulness of positive reappraisal during acute stressors such as
medical illness (Garland et al., 2015), the current findings highlight the potential benefits of early
intervention with older adults. For example, research shows that continued mindfulness practice
over time leads to measurable improvements in mood and cognition (Zeidan, Johnson, Diamond,
David and Goolkasian, 2010). Taken together with the findings of this study, providing older
adults with opportunities for mindfulness practice (e.g., access to local classes, printed resources
or online materials/apps) may help to create a buffer against acute stressors when they do arise.
Lastly, though executive functioning was not predictive of increased meaning in life, it
appears that cognitive functions that normally decline with age, such as working memory, and
processing speed, are independent of one’s felt meaning in life. This is promising and suggests
that despite current functioning, older adults who are capable of learning dispositional
mindfulness techniques can engage in positive reappraisal during stressful events. Doing so
early, before individuals encounter life stressors is optimal, being that research shows that
dispositional mindfulness increased over time with consistent practice (Garland et al., 2017).
General Limitations
There are several general limitations in this research. The first limitation is that a large
portion of the data was by self-report. Therefore, responses are subject to self-serving biases.
Prior research has noted that generally, individuals rate their lives as meaningful irrespective of
their current circumstances (Heizelman & King, 2013). Furthermore, responses to positive
reappraisal and dispositional mindfulness may be influenced by social desirability. A second
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limitation is the representativeness of the sample. The data was collected within continued care
retirement communities. The results based on this sample, with a greater portion of White,
affluent older adults does not generalize to older adults who reside in different areas of the U.S.,
or other types of independent living (private home, apartment, etc.). A third limitation is that
other variables may have accounted for or be linked to the results of the study. For example,
psychiatric and medical factors that influence cognitive functioning were not included in this
study. Fourthly, many of the participants in the study were older than the established norm
group. This was true for measures of intellectual functioning as well as some aspects of
executive functioning, such as cognitive inhibition and set-shifting. This was also true for some
self-report measures such as meaning in life. Lastly, as discussed previously, the majority of the
sample endorsed high levels of meaning in life, moderate levels of stress as well as having
generally high average performances on tests of intellectual functioning and executive
functioning. That said, restricted variability within the data may have limited the
representativeness of the sample to the general population.
Future Directions
Based on current findings, future research should examine the appropriateness of using
the MAAS when assessing for dispositional mindfulness in older adults. Given that mindfulness
is considered a multifaceted construct, it may also be useful to focus on examining which
components of mindfulness offer greatest cognitive and/or emotional benefit. Given that
dispositional mindfulness predicted positive reappraisal, future researchers may wish to further
investigate the proposed mechanism underlying the significant association between dispositional
mindfulness and positive reappraisal (i.e., decentering). Because positive reappraisal requires
some degree of meaning making, it may be fruitful to include qualitative data in future studies.
For example, capturing older adults’ changing relationship to decentering in the midst of creating
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new narratives could lead to a better understanding of the links between mindfulness and positive
reappraisal. More generally, investigating the efficacy of manualized treatments as well as more
broad-based lifestyle mindfulness interventions focused on facilitating positive reappraisal in
older adults is warranted. Lastly, though the proposed SEM model demonstrated that a one-unit
increase in the predictor variables did not significantly predict variance in meaning in life that
does not mean a relationship couldn’t exist. It could be that very low dispositional mindfulness,
positive reappraisal, and executive functions are deleterious for meaning in life. Rather than
being treated as linear variables that effect meaning in life incrementally, significant findings
may have been discovered if regression techniques that measure curvilinear relationships were
utilized. Future studies may explore this idea.
Conclusion
The purpose of the current study was to investigate the potential role of executive
functioning and positive reappraisal in mediating the relationship between dispositional
mindfulness and presence of meaning in life for older adults. The study’s design and initial
hypotheses were grounded in a conceptual model based on the previous literature. Based on this
model, dispositional mindfulness was proposed to increase meaning in life in older adults who
more frequently engaged in positive reappraisal and had the cognitive resources (i.e., executive
functions) available to do so. Moreover, based on this model, stress was proposed to weaken the
effect of dispositional mindfulness on executive functions. Bivariate correlations revealed a
positive association between positive reappraisal and meaning in life, as well as a negative
association between perceived stress, positive reappraisal and meaning in life. The overall
hypothesized SEM model was not supported, with one notable exception: dispositional
mindfulness was significantly related to positive reappraisal. This study adds to the body of
research examining positive psychological processes in older adults. Future studies should
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continue to explore the relationship between dispositional mindfulness and positive reappraisal
as it relates to indices of wellbeing and adjustment stressful life events (change in mobility
status, illness, etc.).
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APPENDIX A
Informed Consent
Linking Dispositional Mindfulness to Positive Psychological Processes in Older Adults:
Executive Functioning, Positive Reappraisal and Meaning in Life
Researcher’s Affiliation: Kristen Wesbecher is a student in the Counseling Psychology PhD
program in the Department of Professional Psychology and Family Therapy at Seton Hall
University.
Purpose: Some people think in the past, some think in the present, and others in the future. This
project’s goal is to see if the way people think (past, present or future) changes how much
meaning they feel is in their lives. It will also study the influence of stress and aging. If choosing
to participate, it will take about 30-45 minutes to complete.
Procedure: After reading this consent and agreeing to participate in this study, volunteers will
be scheduled to participate in an assessment that contains two parts: (1) a brief thinking skills
test; (2) a self-report (questions filled out by self) survey packet. They will be scheduled with
either Kristen Wesbecher, or her research assistant Yubelky Rodriguez. A third research
assistant, Sonay Culpepper will assist only with scheduling and the completion of the self-report
packet. The thinking tests will take up to 30 minutes while the self-report survey will take up to
15 minutes to complete.
The thinking skills tests include:
• The Wechsler Abbreviated Scale of Intelligence-which measures intelligence, or general
thinking ability.
• The Wechsler Adult Intelligence Scale-which measures speed of thinking and working
memory, or how well people can keep more than one thought in their mind at a time.
• The Stroop Color and Word Test- which measures inhibition, or the ability to stop
doing or thinking something that isn’t helpful in the moment.
• Trailmaking Test-which measures cognitive flexibility, or the ability to think in new
ways.
The self-report measures include:
• The Trait Mindful Attention Awareness Scale-which measures one’s ability to be in the
present moment without getting distracted.
• Cognitive Emotion Regulation Questionnaire –which measures the ability to think
about stressful situations as harmless or even good.
• Meaning in Life Questionnaire-which measures how much meaning and purpose
someone thinks their life has.
• Perceived Stress Scale-which measures the amount of stress in daily life.
Voluntary Participation: Participation in this study is voluntary. This means that you only
participate in the study if you choose to. If at any time participants wish to stop the study they
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may do so without penalty. The decision to participate will not impact any services at the
retirement community where you live.
Anonymity: In an effort to maintain anonymity (remain unknown), this research will not
include names anywhere on the testing materials. Participants will be given a code number and
two separate lists, which together can link participants to their ID number will be kept in
separate, locked drawers. Only Dr. Cruz, and Kristen Wesbecher will have access to the list of
participants.
Confidentiality: Data collected will not be reported individually, that is one by one. All data
will be combined so that no participants’ responses are seen alone. All materials collected will
be confidential. Completed responses will be kept in a secure location and will only be available
to Kristen Wesbecher and her research mentor Dr. Daniel Cruz, PhD. Data will be stored
electronically on a USB memory key and kept in a locked, secure office.
Risks: There is little risk to participating in the study. Some level of frustration (annoyance or
upsetting feeling) may be felt when participating in the brief neuropsychological evaluation,
which is designed to be challenging, or hard to all individuals. To minimize these risks,
participants will have a break(s) in order to lessen frustration. Participants will also be
reminded that they can withdraw from testing at any time.
Benefits: Although participants will not benefit directly from participating in this study,
responses will help to provide evidence about the influence of mindfulness (ability to be in the
present moment without getting distracted) in factors related a more enjoyable life as we get
older. Having a better understanding of the role of mindfulness in late life can inform
interventions aimed at successful aging.
Contact Information for Questions: If the volunteer has questions about the study, they may
be directed to Kristen Wesbecher, MS either in person or by phone at (845) 238-6206. Dr.
Daniel Cruz, PhD can be reached by email at [email protected] . Questions about the rights
of subjects may be directed in person to Dr. Ruzicka, Director of the Institutional Review
Board (IRB), or by telephone: 973-313-6314.
______________________ __________________ ____________
Name Signature Date
*Please note participants will be given a copy of the signed and dated Informed Consent Form.
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APPENDIX B
Letter of Solicitation
Dear Potential Participant:
Thank you for your interest in this research project. I am a student in the Counseling Psychology
PhD program in the Department of Professional Psychology and Family Therapy at Seton Hall
University who is interested in studying factors that make life more enjoyable as we get older.
Some people think in the past, some think in the present, and others in the future. This project’s
goal is to see if the way people think changes how much meaning they feel is in their lives. It
will also study the influence of stress and aging.
Before taking part in this study, participants will be asked questions through a test called “The
Mini-Mental State Examination” to measure current cognitive functioning (attention and
memory skills). If a score at or above what is needed to participate is achieved, the study then
asks people to fill out demographic questions about themselves like age, gender and what they
did for work. There are also four self-report surveys (questions you fill out on your own) that I
will describe below. Lastly, it involves participation in a short neuropsychological assessment (a
test done one on one with the researcher to measure thinking abilities) to look at executive
functioning (thinking skills like planning, organizing and remembering) that is also described
below. The study will take about 45 minutes.
The thinking skills tests include:
• The Wechsler Abbreviated Scale of Intelligence-which measures intelligence, or general
thinking ability.
• The Wechsler Adult Intelligence Scale-which measures speed of thinking and working
memory, or how well people can keep more than one thought in their mind at a time.
• The Stroop Color and Word Test- which measures inhibition, or the ability to stop
doing or thinking something that isn’t helpful in the moment.
• Trailmaking Test-which measures cognitive flexibility, or the ability to think in new
ways.
The self-report measures include:
• The Trait Mindful Attention Awareness Scale-which measures one’s ability to be in the
present moment without getting distracted.
• Cognitive Emotion Regulation Questionnaire –which measures the ability to think
about stressful situation as harmless or even good.
• Meaning in Life Questionnaire-which measures how much meaning and purpose
someone thinks their life has.
• Perceived Stress Scale-which measures the amount of stress in daily life.
Adults over the age of 65 are able to take this survey. Participation is voluntary and individuals
can stop at any time without bad results. The study is anonymous (information cannot identify
participants). Also, all information collected will be kept confidential (kept secret) and stored
in a secure location that will only be available to Kristen Wesbecher, Dr. Daniel Cruz, PhD as
well as her two research assistants Yubelky Rodriguez, MA and Sonay Culpepper, BA.
Thank you,
Kristen Wesbecher, M.S.
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APPENDIX C
Procedure Script
Script for telling volunteers that they do not qualify for the study based on their
performance on the Mini Mental State Examination needs to be submitted. See Below:
“Thank you for your participation in this study! I want to thank you for taking the time to
volunteer today. For some people this assessment is longer, while for others it is shorter. That
being said, this concludes the end of our time together, as we have gathered all the information
we need. ”
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APPENDIX D
IRB Approval
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Appendix E
Proposal Approval
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APPENDIX F
Measures
DEMOGRAPHIC INFORMATION
Please complete the following information, remembering that we cannot identify
anyone with this data.
1. Age: _______
2. Sex: _______ Female _______Male _______Other
3. Ethnicity
_______African-American
_______Asian-American
_______White
_______Hispanic American
_______Native American
_______Biracial/Multiracial (Specify: _________________)
_______Other (Specify:________)
4. Highest Level of Education
_______No High School
_______Some High School
_______High School Graduate
_______ Associate’s Degree/Trade School
_______Bachelor’s Degree
_______Master’s Degree
_______ Ph.D./M.D./J.D.
5. Occupation: ____________________
6. Marital Status: __________________
7. Average hours of exercise per week: _______________
8. Average hours of sleep per night: ________________
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Meaning in Life Questionnaire
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Cognitive Emotion Regulation Questionnaire
How do you cope with events?
Everyone gets confronted with negative or unpleasant events now and then and everyone responds to them in his or her own way.
By the following questions you are asked to indicate what you generally think, when you experience negative or unpleasant
events.
(almost)
never
some-
times
regu-
larly
often
(almost)
always
1. 1 feel that I am the one to blame for it 1 2 3 4 5
2. I think that I have to accept that this has happened 1 2 3 4 5
3. I often think about how I feel about what I have experienced 1 2 3 4 5
4. I think of nicer things than what I have experienced 1 2 3 4 5
5. I think of what I can do best 1 2 3 4 5
6. I think I can learn something from the situation 1 2 3 4 5
7. I think that it all could have been much worse 1 2 3 4 5
8. I often think that what I have experienced is much worse than what others have experienced 1 2 3 4 5
9. I feel that others are to blame for it 1 2 3 4 5
10. I feel that I am the one who is responsible for what has happened 1 2 3 4 5
11. I think that I have to accept the situation 1 2 3 4 5
12. I am preoccupied with what I think and feel about what I have experienced 1 2 3 4 5
13. I think of pleasant things that have nothing to do with it 1 2 3 4 5
14. I think about how I can best cope with the situation 1 2 3 4 5
15. I think that I can become a stronger person as a result of what has happened 1 2 3 4 5
16. I think that other people go through much worse experiences 1 2 3 4 5
17. I keep thinking about how terrible it is what I have experienced 1 2 3 4 5
18. I feel that others are responsible for what has happened 1 2 3 4 5
19. I think about the mistakes I have made in this matter 1 2 3 4 5
20. I think that I cannot change anything about it 1 2 3 4 5
21. I want to understand why I feel the way I do about what I have experienced 1 2 3 4 5
22. I think of something nice instead of what has happened 1 2 3 4 5
23. I think about how to change the situation 1 2 3 4 5
24. I think that the situation also has its positive sides 1 2 3 4 5
25. I think that it hasn’t been too bad compared to other things 1 2 3 4 5
26. I often think that what I have experienced is the worst that can happen to a person 1 2 3 4 5
27. I think about the mistakes others have made in this matter 1 2 3 4 5
28. I think that basically the cause must lie within myself 1 2 3 4 5
29. I think that I must learn to live with it 1 2 3 4 5
30. I dwell upon the feelings the situation has evoked in me 1 2 3 4 5
31. I think about pleasant experiences 1 2 3 4 5
32. I think about a plan of what I can do best 1 2 3 4 5
33. I look for the positive sides to the matter 1 2 3 4 5
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34. I tell myself that there are worse things in life 1 2 3 4 5
35. I continually think how horrible the situation has been 1 2 3 4 5
36. I feel that basically the cause lies with others 1 2 3 4 5
Thank you for filling out the questionnaire!
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APPENDIX G
Figure 1. Conceptual Model
Figure 1. Conceptual model depicting proposed relationship between variables used to guide
research hypotheses.
Dispositional
Mindfulness
Positive Reappraisal
Meaning in Life
Perceived Stress
Executive Functioning
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Figure 2. Results of Revised SEM Model
Figure 2. Mediation model depicts executive functioning and positive reappraisal as mediators
between dispositional mindfulness and meaning in life. Model was adjusted for IQ
and processing speed; e = error.
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Figure 3. Mediation model with PROCESS
Figure 3. Mediation model depicts executive functioning and positive reappraisal as mediators
between dispositional mindfulness and meaning in life using PROCESS model 4.
Model was adjusted for IQ and processing speed.
Executive
Functioning
Dispositional
Mindfulness Meaning in Life
a = -0.37, p = .30†
b = 0.79,
p = .43†
c = 0.70, p =.51 c’ = 0.03, p = .78
Positive Reappraisal a = 1.37, p = .11
†
b = 1.90 p = .06†