Open Hearts Build Lives: Positive Emotions, Induced Through
Loving-Kindness Meditation, Build Consequential Personal Resources
Barbara L. Fredrickson
University of North Carolina at Chapel Hill
Michael A. Cohn
University of Michigan
Kimberly A. Coffey and Jolynn Pek
University of North Carolina at Chapel Hill
Sandra M. Finkel
University of Michigan
B. L. Fredrickson’s (1998, 2001) broaden-and-build theory of positive emotions asserts that people’s
daily experiences of positive emotions compound over time to build a variety of consequential personal
resources. The authors tested this build hypothesis in a field experiment with working adults (n⫽139),
half of whom were randomly-assigned to begin a practice of loving-kindness meditation. Results showed
that this meditation practice produced increases over time in daily experiences of positive emotions,
which, in turn, produced increases in a wide range of personal resources (e.g., increased mindfulness,
purpose in life, social support, decreased illness symptoms). In turn, these increments in personal
resources predicted increased life satisfaction and reduced depressive symptoms. Discussion centers on
how positive emotions are the mechanism of change for the type of mind-training practice studied here
and how loving-kindness meditation is an intervention strategy that produces positive emotions in a way
that outpaces the hedonic treadmill effect.
Keywords: emotions, meditation, positive psychology, broaden-and-build, mindfulness
A paradox surrounds positive emotions. On one hand, they are
fleeting: Like any emotional state, feelings of joy, gratitude, inter-
est, and contentment typically last only a matter of minutes.
Moreover, positive emotions are less intense and less attention-
grabbing than negative emotions (Baumeister, Bratslavsky,
Finkenauer, & Vohs, 2001) and are more diffuse (Ellsworth &
Smith, 1988). Yet on the other hand, research indicates that pos-
itive emotions contribute to important downstream life outcomes,
including friendship development (Waugh & Fredrickson, 2006),
marital satisfaction (Harker & Keltner, 2001), higher incomes
(Diener, Nickerson, Lucus, & Sandvik, 2002), and better physical
health (Doyle, Gentile, & Cohen, 2006; Richman et al., 2005).
People who experience frequent positive emotions have even been
shown to live longer (Danner, Snowdon, & Friesen, 2001; Mos-
kowitz, 2003; Ostir, Markides, Black, & Goodwin, 2000). Indeed,
a recent meta-analysis of nearly 300 findings concluded that pos-
itive emotions produce success and health as much as they reflect
these good outcomes (Lyubomirsky, King, & Diener, 2005).
How do they do this? How do people’s fleeting and subtle
pleasant states pave the way to their later success, health, and
longevity? Fredrickson’s (1998) broaden-and-build theory of pos-
itive emotions outlines a possible path: Because positive emotions
arise in response to diffuse opportunities, rather than narrowly-
focused threats, positive emotions momentarily broaden people’s
attention and thinking, enabling them to draw on higher-level
connections and a wider-than-usual range of percepts or ideas. In
turn, these broadened outlooks often help people to discover and
build consequential personal resources. These resources can be
cognitive, like the ability to mindfully attend to the present mo-
ment; psychological, like the ability to maintain a sense of mastery
over environmental challenges; social, like the ability to give and
receive emotional support; or physical, like the ability to ward off
the common cold. People with these resources are more likely to
effectively meet life’s challenges and take advantage of its opportu-
nities, becoming successful, healthy, and happy in the months and
years to come. Thus, the personal resources accrued, often uninten-
tionally, through frequent experiences of positive emotions are pos-
ited to be keys to later increases in well-being. Put simply, the
broaden-and-build theory states that positive emotions widen people’s
outlooks in ways that, little by little, reshape who they are.
Barbara L. Fredrickson, Kimberly A. Coffey, and Jolynn Pek, Depart-
ment of Psychology, University of North Carolina at Chapel Hill; Michael
A. Cohn, Department of Psychology, University of Michigan; Sandra M.
Finkel, Preventive Cardiology Services, University of Michigan.
This work was supported by National Institute of Mental Health Grant
MH59615 to Barbara L. Fredrickson, with additional financial and proce-
dural support from the Compuware Corporation (Detroit, Michigan). We
thank the leaders at Compuware who opened their minds and doors to the
study reported here and offer special thanks to the Compuware employees
who devoted their time and energy across months to participate in this
project. We acknowledge the contributions of Li Cai, Daniel Serrano, and
Patrick Curran in guiding us safely through new statistical terrain. Thanks
also go to Benjamin Figa for overseeing data collection; Jordana Adler and
Sid Tsai for assistance with data management and coding; and Tracey
Callison, Lahnna Catalino, and Bethany Kok for their comments. Finally,
Sandra M. Finkel wishes to acknowledge Ngawang Gehlek Rinpoche, her
personal mentor in loving-kindness.
Correspondence concerning this article should be addressed to Barbara
L. Fredrickson, Department of Psychology, Davie Hall, CB 3270, Univer-
sity of North Carolina at Chapel Hill, Chapel Hill, NC 27599. E-mail:
Journal of Personality and Social Psychology Copyright 2008 by the American Psychological Association
2008, Vol. 95, No. 5, 1045–1062 0022-3514/08/$12.00 DOI: 10.1037/a0013262
The key hypotheses of the broaden-and-build theory have received
empirical support from multiple laboratories. First, the broaden hy-
pothesis holds that positive emotions broaden people’s attention and
thinking. Experiments have shown that, relative to neutral and nega-
tive states, induced positive emotions widen the scope of people’s
visual attention (Fredrickson & Branigan, 2005; Rowe, Hirsh, &
Anderson, 2007; Wadlinger & Isaacowitz, 2006), broaden their rep-
ertoires of desired actions (Fredrickson & Branigan, 2005), and in-
crease their openness to new experiences (Kahn & Isen, 1993) and
critical feedback (Raghunathan & Trope, 2002). At the interpersonal
level, induced positive emotions increase people’s sense of “oneness”
with close others (Hejmadi, Waugh, Otake, & Fredrickson, 2008),
their trust in acquaintances (Dunn & Schweitzer, 2005), and their
ability to accurately recognize individuals of another race (Johnson &
Fredrickson, 2005). The empirical evidence is mounting, then, that
positive emotions broaden people’s attention and thinking in both
personal and interpersonal domains.
The second part of the theory, the build hypothesis, holds that
positive emotions set people on trajectories of growth that, over
time, build consequential personal resources. To date, the empir-
ical evidence for the build hypothesis has been largely indirect.
Prospective correlational studies have shown that people who, for
whatever reasons, experience or express positive emotions more
than others show increases over time in optimism and tranquility
(Fredrickson, Tugade, Waugh, & Larkin, 2003), ego-resilience
(Cohn, Fredrickson, Brown, Mikels, & Conway, 2008), mental
health (Stein, Folkman, Trabasso, & Richards, 1997), and the
quality of their close relationships (Gable, Gonzaga, & Strachman,
2006; Waugh & Fredrickson, 2006).
Here we present the first experimental evidence that directly tests
the build hypothesis. Such research has been virtually nonexistent (but
see Emmons & McCullough, 2003; King, 2001), largely because
resources are expected to accrue only after many experiences of
positive emotions over separate occasions, which necessitates a lon-
gitudinal design as well as a reliable, repeatable method for evoking
positive emotions. The well-documented hedonic treadmill effect
(Diener, Lucas, & Scollon, 2006) assures that emotion-elicitation
techniques used with success in the laboratory (e.g., film clips, gifts of
candy) would likely become inert if repeated daily. As the novelty of
an experience subsides, people’s emotions tend to revert to a trait-like
baseline. In this study, we sought to overcome this challenge by using
an induction based on meditation.
We suspected that meditation would outpace the hedonic tread-
mill for several reasons. First, it incorporates mindful attention,
which has been shown to undo hedonic adaptation (Schwarz,
Kahneman, & Xu, in press). Second, unlike watching a film or
receiving a gift, meditation practice is active and personalized.
Participants can lengthen the meditation, alter their focus, or
otherwise try to get more out of their practice, keeping it within a
range that is feasible but not boring. Most important, participants
can use the insights and psychological skills developed during
meditation practice in many situations and life domains. Medita-
tion, then, offers opportunities for enhanced emotions throughout
the day, not simply during meditations, per se.
Meditation and mindfulness, which are perhaps best known as
elements of Buddhist spiritual practice, have also proven to be
fruitful topics within empirical research on well-being (Baer, 2003;
Kabat-Zinn, 2003; Segal, Williams, & Teasdale, 2002; Wallace &
Shapiro, 2006). For instance, for more than 2 decades, Kabat-Zinn
and colleagues have reported evidence that meditation helps peo-
ple self-regulate stress, anxiety, chronic pain, and various illnesses
(for a review, see Kabat-Zinn, 2003). Building on the observation
that when formerly depressed individuals see their thoughts and
emotions from a wider perspective, they are more resistant to
relapse, Teasdale et al. (2000) developed a successful therapy that
combines mindfulness meditation with cognitive therapy.
More recently, Kabat-Zinn collaborated with Davidson et al.
(2003) to examine the affective, brain, and immunological effects
of beginning a meditation practice. Volunteers were randomly
assigned to either a waitlist control group (n⫽16) or an 8-week
mindfulness-based stress-reduction workshop (n⫽25), which
required a daily practice of guided meditation lasting about 1 hr.
As in past studies, trait anxiety was significantly reduced in the
meditation group. Both immediately after the training period and 4
months later, electroencephalogram monitoring revealed that med-
itators showed increases in left-sided anterior brain activation,
which has been repeatedly linked to greater positive, approach-
related emotions (for a review, see Davidson, 2000). Meditators
also showed a more robust and effective immune response to an
influenza vaccine administered at the end of the training period,
and the strength of this response was correlated with the magnitude
of left-sided anterior brain activation. The suggestion that medita-
tion practice increases positive affect is also supported by at least
one experience sampling study (Easterlin & Carden˜a, 1998).
Most empirical work on meditation has centered on mindfulness
meditation (e.g., Davidson et al., 2003; Teasdale et al., 2000). Because
we were particularly interested in evoking positive emotions, we
employed a related mind-training practice, loving-kindness medita-
tion (LKM). LKM is a technique used to increase feelings of warmth
and caring for self and others (Salzberg, 1995). Like other meditation
practices, LKM involves quiet contemplation in a seated posture,
often with eyes closed and an initial focus on the breath. Yet whereas
mindfulness meditation involves training one’s attention toward the
present moment in an open-minded (nonjudgmental) way, LKM
involves directing one’s emotions toward warm and tender feelings in
an open-hearted way. Individuals are first asked to focus on their heart
region and contemplate a person for whom they already feel warm
and tender feelings (e.g., their child, a close loved one). They are then
asked to extend these warm feelings first to themselves and then to an
ever-widening circle of others. Thus, LKM may well cultivate broad-
ened attention in addition to positive emotions. According to the
broaden-and-build theory, these two experiential consequences go
hand in hand.
In LKM, people cultivate the intention to experience positive
emotions during the meditation itself, as well as in their life more
generally. Moreover, mind-training practices like LKM are thought to
not only shift people’s fleeting emotional states but also reshape their
enduring personality traits (Davidson et al., 2003), a coupling of
momentary with long-term gains fully compatible with the broaden-
and-build theory. We acknowledge that mind-training practices, in-
cluding LKM, are not simply vehicles for improving emotion expe-
riences. The primary goal within contemplative traditions is, instead,
to learn about the nature of one’s mind and dispel false assumptions
about the sources of one’s happiness (Dalai Lama & Cutler, 1998).
These insights can, in turn, shift people’s basic outlooks on them-
selves in relation to others, increasing empathy and compassion.
Approaching daily life with the new insights and outlooks developed
through mind-training practice is what is thought to enhance people’s
1046 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
emotion experiences. That said, the goal of the present study was to
test the build hypothesis, which required a means of reliably eliciting
positive emotions over the span of months. We saw LKM as a suitable
vehicle to meet this goal. Future empirical work is needed to test
whether the cognitive shifts outlined by scholars of contemplative
practices are indeed responsible for any success LKM has in enhanc-
ing positive emotions.
LKM involves a range of thoughts and visualizations, and it
directly evokes only select positive emotions (i.e., love, content-
ment, and compassion) and carries some potential to evoke nega-
tive emotions. Moreover, given the possibility of gradual shifts in
people’s outlooks and personality traits, we expected the positive
emotions generated by LKM to increase over time. Our study
involved daily assessments of time spent meditating and of a wide
range of discrete positive and negative emotions. This strategy
allowed us to determine whether (a) positive emotions, measured
directly, are responsible for any changes produced by LKM; (b)
different classes of positive emotions (low- vs. high-arousal, e.g.,
contentment vs. amusement; or self- vs. other-focused, e.g., pride
vs. love) are differentially induced by this practice; and (c) the
effects of LKM on positive emotions increase (because of practice)
or decrease (because of adaptation) over time.
We are aware of only one other field experiment that has tested
the effects of LKM. Carson et al. (2005) compared a group of
chronic pain patients who were taught LKM (n⫽18) with a group
receiving standard care (n⫽25). Results from this pilot trial
indicated that LKM reduced pain, anger, and psychological dis-
tress. The present study tests LKM in a larger sample, with a wider
variety of outcome measures. Most critically, it gathers detailed
data on positive emotions as a potential mediator of the benefits of
this form of meditation.
Overview of Empirical Strategy
We conducted a randomized, longitudinal field experiment to
test whether positive emotions, induced through LKM, build con-
sequential personal resources. In designing our experiment, we
grappled with selecting the most appropriate comparison condi-
tion. In laboratory research, we have used sham meditation (i.e.,
sitting with eyes closed) to achieve precise experimental control.
For a 7-week intervention that asked participants for a substantial
investment of time and effort, both ethical and face-validity con-
cerns led us away from this sort of placebo meditation. Another
approach is to choose a comparison condition that best addresses
the current state of knowledge in a given area. Our review of the
scientific literature had uncovered no published evidence that
LKM could produce sustained increases in positive emotions and
only limited and indirect evidence that positive emotions could
build personal resources. Given this embryonic state of evidence,
an appropriate initial comparison group would reflect treatment as
usual, which, outside the clinical literature, is perhaps better
phrased as life as usual. Thus, we chose a waitlist control design,
which can assess treatment efficacy while controlling for self-
selection, history, maturation, regression to the mean, and the
effects of repeated testing (Chambless & Hollon, 1998; Kazdin,
2003). Although the groups differ in terms of experimenter de-
mand, delivery format, and expectation of improvement, we ad-
dress these limitations procedurally and analytically to the extent
possible (see Discussion).
In the context of a workplace wellness program, we offered a
7-week meditation workshop to employees interested in stress
reduction and willing to respond to questionnaires and provide
daily, web-based reports of their emotions. All volunteers com-
pleted an initial survey that assessed their life satisfaction, depres-
sive symptoms, and status on a range of personal resources.
Volunteers were then randomly assigned to either our meditation
workshop or a waitlist control group (which received the same
workshop after the study ended). Over the next 9 weeks (including
1 week before and after the workshop), participants in both groups
completed daily reports of their emotion experiences and medita-
tion practice. About 2 weeks after the workshop ended, partici-
pants completed a final survey that reassessed their life satisfac-
tion, depressive symptoms, and status on the same personal
resources measured previously.
In addition to daily reports of emotion experiences, which may
well underestimate the frequency of emotion experiences, at the
time of the final survey, participants also completed a detailed
account of the emotions they experienced that particular day using
the day reconstruction method (DRM; Kahneman, Krueger, Sch-
kade, Schwarz, & Stone, 2004). The DRM is a survey method that
builds on the strengths of two older methods: time-use assessment
and momentary data capture (i.e., experience sampling). Like each
of these earlier methods, the DRM minimizes recall biases and
provides a comprehensive picture of daily experience. Participants
first reconstruct a detailed diary of “this morning” by dividing it
into sequences of episodes. Next, they complete a series of ques-
tions, including emotion reports, for each episode of their morning.
We predicted that participation in the 7-week LKM workshop
would increase individuals’ daily experiences of positive emotions,
over time across the 9 weeks of daily reporting and within the specific
morning targeted by the DRM. Drawing from the broaden-and-build
theory, we further predicted that increases in positive emotions, pro-
duced by LKM, would, in turn, build participants’ personal resources.
To test the generality of the build effect of positive emotions, we
targeted a wide range of personal resources, including cognitive
resources (e.g., mindfulness, the ability to savor positive experiences),
psychological resources (e.g., ego-resilience, environmental mastery),
social resources (e.g., positive relations with others, social support
given and received), and physical resources (e.g., illness symptoms,
duration of sleep). Finally, we investigated whether these resources
actually made a difference in participants’ lives. To do so, we tested
whether any increments in resources, in turn, contributed to changes
in overall life satisfaction, a judgment of fulfillment and well-being
that differs from positive affectivity in its global focus and cognitive
emphasis (Lucas, Diener, & Suh, 1996). As a secondary way to assess
whether newly built resources were consequential, we tested whether
they led to decreases in depressive symptoms. We distill this series of
predictions into the following overarching mediational hypothesis:
Hypothesis: Becoming skilled in LKM will, over time, in-
crease people’s daily experiences of positive emotions,
which, in turn, build a variety of personal resources that hold
positive consequences for the person’s mental health and
overall life satisfaction.
Figure 1 portrays the conceptual model that underlies the build
hypothesis as we tested it here. Note that this study does not
directly assess momentary changes in broadened cognition, be-
POSITIVE EMOTIONS BUILD RESOURCES
cause of the lack of valid measures that could be used repeatedly
and in the field, nor does it directly assess the cognitive shifts
produced by LKM that trigger positive emotions. As such, this
study evaluates positive emotions as a mechanism for the effects of
LKM but does not further decompose the mechanisms by which
LKM and positive emotions exert their influence.
The study was conducted at the Compuware Corporation, a
large business software and information technology services com-
pany in Detroit, Michigan. All full-time employees working at
Compuware’s Detroit headquarters (approximately 1,800 individ-
uals, 38% female, 34% ethnic minorities) received an e-mail
message from Compuware executives inviting them to participate
in the study.
The study was described as a scientific investigation
of “the benefits of meditation. . . [to] reduce stress.” The e-mail
included a link to a website where employees could learn more
about the project. The information made clear that the study was
being conducted by university researchers, that the results would
be confidential, and that the choice of whether to participate would
not affect their standing with their employer.
Two hundred two Compuware employees attended the study
orientation, gave their consent, and completed the initial survey.
Of these, 102 were assigned to the LKM group and 100 were
assigned to the waitlist control group. Participants were excluded
from analyses for the following reasons: (a) They violated random
assignment (n⫽7), (b) they failed to complete Time 2 measures
(n⫽27), (c) they were assigned to the meditation condition but
attended fewer than three of the six weekly classes (n⫽5), or (d)
they completed fewer than 30 of the 61 daily reports (n⫽24). In
total, 63 participants were excluded, 34 from the LKM group and
29 from the waitlist group. Attrition and disqualification affected
the LKM and waitlist groups equally,
(1, N⫽202) ⫽0.4, p⫽
.51, and was comparable with other studies on meditation (Carson
et al., 2005; Davidson et al., 2003; Teasdale et al., 2000). The final
sample, then, consisted of 139 participants, 67 of whom were in
the LKM group and 72 of whom were in the waitlist control group.
Demographic information is presented in Table 1. The compo-
sitions of the initial and completer samples were similar: Most
participants were female, most had bachelor’s or master’s degrees,
and the average age was 41 years (SD ⫽9.6). The completer
sample was 65.5% female, 73.7% White, 9.5% Black, 8.8% South
Asian, 6.6% East Asian, 0.7% Hawaiian/Pacific Islander, and
0.7% Hispanic. Male participants were disproportionately lost to
attrition and disqualification,
(1, N⫽180) ⫽10.9, p⫽.001.
There was also a trend towards loss of married participants,
N⫽178) ⫽3.2, p⫽.07. These groups, however, were lost
equally between conditions (waitlist ⫽64% female, meditators ⫽
(1, N⫽139) ⫽.17, p⫽.69, (waitlist ⫽56%
married, meditators ⫽60% married),
(1, N⫽137) ⫽.22, p⫽
.67, implying that married and male participant attrition related to
the study in general and not to LKM. Otherwise, the initial and
completer samples did not differ on demographic characteristics,
condition assignment, or depression and life-satisfaction scores
(p⬎.24). Four participants in the completer sample had a meditation
practice at the start of the study. Although these participants were
higher than others on positive emotions throughout the study, remov-
ing their data did not alter the pattern of findings reported here.
In addition to providing access to the participant pool, Compu-
ware supported this study in multiple ways. All study orientation
meetings and meditation workshop sessions were held during
business hours at Compuware’s Detroit office. The meditation
workshops were offered free of charge to all interested employees.
Compuware also provided employee release time so that partici-
pants could attend a study orientation meeting, six meditation
workshop sessions, and complete all web surveys during work
time, without loss of compensation.
Participants received monetary compensation for time spent on
study measures. They received $10 for completing the initial
survey, $20 for completing the final survey, and $1 for each daily
report. In addition, participants who completed daily reports for at
least 40 of the 61 days received a $10 bonus and a copy of a
popular book on meditation by Jon Kabat-Zinn (valued at $24.95).
The total possible payment for the study was $101, plus the book.
All study orientation sessions were held during employees’
lunch hour, in a large auditorium on Compuware premises. At
orientation, Barbara L. Fredrickson or Michael A. Cohn introduced
interested employees to the rationale for investigating the effects
of meditation on health and well-being. We sought to enhance
prospective participants’ investment in the study by describing
benefits of meditation already featured in the popular press and
regularly used to draw attendees to comparable workplace well-
ness courses, specifically, the potential to reduce stress and im-
prove health and well-being. We also described the timeline of the
study and the details of compensation and explained the value of
gathering data from a waitlist control group. We did not describe
LKM, the broaden-and-build theory, our hypotheses regarding
mediation by daily positive emotions, or other information that
might have created detailed expectancy or demand effects. Those
who could not attend an orientation session received information
Within the week following orientation, interested employees
logged on to a secure website, gave consent to participate in the
The population was limited to those Compuware employees with a
Compuware e-mail address. This included executives, developers, and
administrators, but not maintenance workers or cleaning staff.
Figure 1. Conceptual model depicting predicted causal paths between loving-kindness meditation, change in
positive emotions, change in resources, and change in life satisfaction.
1048 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
study, and responded to the initial (T1) survey (described below).
Participants learned their group assignment (meditation workshop
or waitlist control) only after completing the T1 survey.
The daily reporting phase of the study began 1 week following
orientation and continued for approximately 9 weeks. Each day,
participants visited our secure website to complete a short report
on their emotions and time spent in “meditation, prayer, or solo
spiritual activity” over the past day. After approximately 1 week of
baseline reporting, workshop classes and daily practice began for
the meditation group (described below). Daily reporting continued
for approximately 1 week after the meditation workshop ended.
After the daily reporting phase ended, the final (T2) survey
became available online. Participants visited our website a final
time and completed the same measures as at T1, followed by a day
reconstruction (described below) and a demographics question-
naire. After data collection was completed, participants received
debriefing information explaining more about the details of the
Approximately 2 months later, meditation classes began
for the waitlist control group. No further data were collected at that
The websites for the initial questionnaires and the daily reports
were available around the clock. The final survey was available only
between noon and 2:00 a.m., because of the specifics of the DRM.
Although participants were encouraged to complete the surveys at
work, they were asked to practice meditation at home. Participants
who missed more than three consecutive weekday report forms, or
who did not fill out the final survey, received an automated e-mail
reminder asking them to visit our website. The study team did not
otherwise initiate contact with participants.
The meditation training involved six 60-minute group sessions
(held over 7 weeks, because of religious holidays) with 20 –30
participants per group. All sessions were led by a stress-
management specialist (Sandra M. Finkel) with extensive experi-
ence practicing and teaching LKM. The median number of ses-
sions attended was five (M⫽4.3, SD ⫽1.8). At the first session,
participants were given a CD that included three guided medita-
tions of increasing scope, led by the workshop instructor. During
Week 1, participants practiced a meditation directing love and
compassion toward themselves. During Week 2, the meditation
added loved ones. During subsequent weeks, the meditation built
from self, to loved ones, to acquaintances, to strangers, and finally,
to all living beings. The first meditation lasted 15 min, and the
final one lasted 22 min.
Each workshop session included 15–20 min for a group medi-
tation, 20 min to check on participants’ progress and answer
questions, and 20 min for a didactic presentation about features of
the meditation and how to integrate concepts from the workshop
into one’s daily life. Participants were assigned to practice LKM at
home, at least 5 days per week, with the guided recordings. The
text of the guided meditations and week-by-week content outlines
are available by request from Sandra M. Finkel.
Cognitive Resources: T1 and T2
Mindfulness and Awareness Scale. The Mindfulness and
Awareness Scale (Brown & Ryan, 2003) assesses awareness of
We contacted participants who did not complete the T2 survey to
request demographic information and to make the debriefing information
Sandra M. Finkel can be reached by e-mail at smfinkel@med
Participant characteristic Intent-to-treat Per-protocol Completers
N195 175 139
% providing demographic information
88.2 93.9 100.0
% in meditation group 49.2 43.4 48.2
% female 59.8 60.8 65.5
41 41 41
Bachelor’s degree Bachelor’s degree Bachelor’s degree
% married 60.5 59.8 57.7
($) ⬎85,000 ⬎85,000 ⬎85,000
(CES–D, full scale)
Baseline 16.1 15.4 15.9
Posttest 12.7 12.4 12.8
Life satisfaction (SWLS)
Baseline 4.12 4.17 4.10
Posttest 4.42 4.46 4.50
% White (non-Hispanic) 73.7 73.3 72.6
Note. CES–D ⫽Center for Epidemiological Studies—Depression Measure (Radloff, 1977). SWLS ⫽Satis-
faction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985).
For exclusion criteria, see Methods section.
Twenty-three participants declined to provide demographic information. Median and percentage calculations
use only participants who provided data. Group-assignment data were available for all participants.
Value reported is median.
To facilitate comparison with previously published work, we report values that represent scores based on the
full CES–D scale, including both positively and negatively worded items. In subsequent analyses, we omit the
positively worded items to minimize conceptual overlap with positive emotions.
POSITIVE EMOTIONS BUILD RESOURCES
one’s circumstances, as well as tendencies towards automated,
“mindless” behavior or acting on “autopilot.” Participants indicate
the frequency of 15 behaviors on a 6-point scale (1 ⫽almost
always,6⫽almost never). Items include “I snack without being
aware of what I am eating” and “I could be experiencing some
emotion and not be conscious of it until some time later.” All items
are reverse-scored. (␣
Agency thinking and pathways thinking. We used the Trait
Hope Scale (Snyder et al., 1991; Snyder, Rand, & Sigmon, 2002)
to assess these two cognitive components of Snyder’s hope theory.
Participants use a 4-point scale to indicate agreement or disagree-
ment (1 ⫽definitely false,4⫽definitely true) with 10 items
divided between two subscales: agency thinking (belief that one
has been/will be personally able to achieve one’s goals), including
“I meet the goals I set for myself” (␣
pathways thinking (belief that there are multiple ways to achieve
one’s goals), including “There are lots of ways around any prob-
Savoring Beliefs Inventory. The Savoring Beliefs Inventory
(Bryant, 2003) assesses one’s tendency to enjoy pleasant experi-
ences in the moment (savoring the present), pleasurably anticipate
them beforehand (savoring the future), and pleasurably recall them
afterward (savoring the past). Participants indicate agreement on a
7-point scale with 24 items, including “It’s easy for me to rekindle
the joy from pleasant memories” and “When I think about a
pleasant event before it happens, I often start to feel uneasy or
uncomfortable” (reverse scored; savoring the past, ␣
⫽.92; savoring the present, ␣
the future, ␣
Psychological Resources: T1 and T2
Life Orientation Test. The Life Orientation Test—Revised
(Scheier, Carver, & Bridges, 1994) is a 6-item scale that assesses
generalized optimism as the belief that positive things are possible
in the future. Participants indicate agreement or disagreement on a
5-point scale (1 ⫽I agree a lot,5⫽I disagree a lot) with 10
statements (4 items are fillers), including “In uncertain times, I
usually expect the best” and “If something can go wrong for me,
it will” (reverse scored; ␣
Ego-resilience. The ego-resilience measure (Block & Kremen,
1996) assesses the ability to bounce back from adversity and
flexibly adapt to shifting demands. Participants indicate agreement
or disagreement on a 4-point scale with 14 items, including “I
quickly get over and recover from being startled” and “I like to do
new and different things” (␣
Psychological well-being. We measured five additional psycho-
logical resources using subscales of Ryff’s (1989) broader psycho-
logical well-being measure. Participants indicate agreement on a
6-point scale (1 ⫽strongly disagree,6⫽strongly agree) with seven
to eight items for each of the following five subscales: personal
growth, with items like “For me, life has been a continuous process of
learning, changing, and growth” (␣
mental mastery, with items like “I often feel overwhelmed by my
responsibilities” (reverse scored; ␣
with items like “I am not afraid to voice my opinions, even when they
are in opposition to the opinions of most people” (␣
.77); self-acceptance, with items like “I like most parts of my person-
⫽.86); and purpose in life, with items like “My
daily activities often seem trivial and unimportant to me” (reverse
Social Resources: T1 and T2
Dyadic Adjustment Scale. The Dyadic Adjustment Scale
(Spanier, 1976) measures social support as the amount of emo-
tional support the participant provides to and receives from close
others. Using a 5-point scale (0 ⫽not at all,4⫽an extreme
amount), participants respond to questions, including “On the
whole, how much do your friends and relatives make you feel
loved and cared for?” and “If one of your close friends got sick or
were injured in a car accident, how much could they count on you
to take care of them?” Items are divided into subscales for social
support given (␣
⫽.81) and social support received
Positive relations with others. Our third index of social re-
sources was drawn from Ryff’s (1989) psychological well-being
scale (see above). The 7-item subscale includes items like, “I know
that I can trust my friends, and they know they can trust me” and
“I often feel lonely because I have few close friends with whom to
share my concerns” (reverse scored; ␣
Physical Resources: T1 and T2
Illness symptoms. This self-report measure assesses 13 com-
mon symptoms of illness or poor health, including headaches,
chest pain, congestion, and weakness (Elliot & Sheldon, 1998).
Participants use a 7-point scale to rate the frequency of each
symptom over the past month (1 ⫽not at all,7⫽very frequently;
Sleep duration. This single item, extracted from the Pittsburgh
Sleep Quality Index (Buysse, Reynolds, Monk, Berman, & Kupfer,
1989), asks participants to respond to the question “During the past
month, how many hours of actual sleep did you get at night?”
Outcome Measures: T1 and T2
Satisfaction with life scale. We assessed cognitive evaluations
of life satisfaction with this five-item scale (Diener, Emmons,
Larsen, & Griffin, 1985). It assesses participants’ global satisfac-
tion with their lives and circumstances. Participants indicate agree-
ment with each item on a 7-point scale, including “So far I have
gotten the important things I want in life” (␣
Center for Epidemiological Studies—Depression Measure.
We assessed depressive symptoms with the Center for Epidemio-
logical Studies—Depression Measure (Radloff, 1977). We ex-
cluded the four positively worded items to minimize conceptual
overlap with positive emotions (see Moskowitz, 2003; Ostir et al.,
2000). On a 5-point scale, participants indicated how often they
had felt symptoms of depression in the past week (0 ⫽never,4⫽
most of the time), including “I felt that I could not shake off the
blues even with help from my family or friends” (␣
Emotions and Meditation Practice: Daily Assessments
During daily reports, participants completed the Modified
Differential Emotions Scale (mDES; Fredrickson et al., 2003).
The mDES asks participants to recall the past 24 hr and rate
1050 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
their strongest experience of each of 19 specific emotions on a
4-point scale (0 ⫽not at all,4⫽extremely). The emotions
listed were amusement, anger, awe, compassion, contempt,
contentment, disgust, embarrassment, gratitude, hope, joy, in-
terest, love, pride, guilt, sadness, shame, fear, and surprise.
Participants also reported whether they had engaged in “medi-
tation, prayer, or solo spiritual activity” since the last time they
filled out the survey (not necessarily the same 24-hr time span
as mDES responses). Both meditation and waitlist participants
responded to these questions.
We used the DRM (Kahneman et al., 2004) to assess partici-
pants’ time-varying emotion experiences during a specific day.
Because of time constraints, we limited our assessment to the
morning of the targeted day. We asked participants to divide their
morning—from the time they awoke until they completed
lunch—into a continuous series of episodes and to provide a
descriptive label for each episode. We allowed a maximum of
10 episodes. Thereafter, participants revisited each labeled ep-
isode to provide ratings from 0 (not at all)to4(extremely) for
the emotion adjectives from the mDES, as described above
(Fredrickson et al., 2003). For each episode, participants were
also asked “What were you doing?” followed by a checklist of
several activities that included “praying/worshiping/meditat-
ing.” They also responded “yes” or “no” to the question, “Were
you interacting with anyone (including on the phone, in a
Overview of Data Analytic Strategy
Given the complexity of the data set, we performed a range of
analyses, which we forecast here.
As a manipulation check, we
used ttests to confirm that participants in the LKM condition
were, in fact, meditating and were meditating more than the
control participants. A series of hierarchical linear models, with
time nested within individual—also known as growth models—
investigated the impact of experimental condition, passage of
time, and time spent meditating on self-reported emotions. An
additional set of analyses examined participants’ emotions
within a single morning, incorporating information about the
amount of time that participants had meditated over the course
of the study and whether they had meditated on the particular
morning in question.
We then tested the build hypothesis in a combined latent growth
curve and path-analysis structural equation model (SEM). The
growth curve for positive emotions from the hierarchical linear
model analyses was reparameterized as a SEM-based latent tra-
jectory model. In the path-analysis portion of the model, baseline
positive emotions and slope of change in positive emotions pre-
dicted change in the targeted resource, which then predicted
change in life satisfaction or depression. Each of the 18 resources
we measured was tested in a separate model.
Results were analyzed separately in three samples:
1. individuals who adhered to the study requirements de-
scribed above (our “complete data” sample, n⫽139);
2. an intent-to-treat sample (n⫽195), comprising all of the
participants who were successfully randomly assigned to
experimental condition; and
3. a per-protocol sample (n⫽175), comprising (a) all of the
participants successfully randomly assigned to the wait-
list control condition (n⫽98) and (b) those participants
assigned to LKM who received a predetermined “mini-
mum effective dose” of LKM training (at least three of
the six weekly loving-kindness sessions; n⫽77).
Analyses with the complete data sample are described below.
At the end of the section, analyses with the other samples are
Did Participants in the Meditation Condition Comply
With Instructions to Meditate?
Time spent in “meditation, prayer, or solo spiritual activity” was
assessed each day. As expected, during the baseline period, med-
itators and control participants did not differ in duration of med-
itative activity, t(135) ⫽⫺0.25, p⫽.80 (Ms⫽13 and 12
min/week, respectively). Beginning with Week 1 of the study, and
for each subsequent week, participants in the LKM group engaged
in significantly more meditative activity than did those in the
control group, averaging about 80 min/week, although this
dropped to about 60 min/week after the workshop ended.
Effects of LKM on Emotions
Did LKM Impact Positive Emotions Over the Course of
We averaged measurements for nine positive emotions—
amusement, awe, contentment, joy, gratitude, hope, interest, love,
and pride—within each day, and then we averaged these daily
means over the week to create a composite positive emotions
variable for each week of the study. Across weeks, this index score
had an average alpha coefficient of .94 (range ⫽.94 –.95).
The impact of LKM on positive emotions over time was tested
using hierarchical linear modeling, with time nested within indi-
vidual. Experimental condition, week in the study, and their inter-
action were included as predictors. The model also included ran-
dom effects for the intercept, which represented each participant’s
Preliminary analyses incorporated sex of participant as a predictor. It
did not significantly predict positive emotions, the impact of experimental
condition on positive emotions, or the impact of experimental condition on
positive emotions over time. In addition, it was not related to the constructs
we examine in subsequent models. For this reason, all reported analyses
collapse across male and female participants, and we do not consider the
impact of participant sex further.
We explored whether we might reduce the number of models tested by
considering the 18 different resources assessed as indicators of either one latent
“resources” factor, or four latent factors distinguished by type of resource (e.g.,
cognitive, psychological, social, and physical resources). However, confirma-
tory and exploratory factor analyses suggested that no such reduction was
warranted. The correlation matrix is available on request.
POSITIVE EMOTIONS BUILD RESOURCES
level of positive emotions at baseline, and for the impact of week
in the study, which represented each participant’s change in pos-
itive emotions over time. Both random effects were significant
(intercept variance ⫽0.34, SE ⫽0.05, p⬍.0001; week vari-
ance ⫽0.002, SE ⫽0.0006, p⫽.0002), indicating that partici-
pants varied in their baseline levels of positive emotions and
showed differing rates of change over time. The fixed effects for
experimental condition and week were not significant, but their
interaction was (b⫽0.041, SE ⫽0.011, p⫽.0004). Thus, neither
time nor condition alone predicted positive emotions, but over
time, a difference between conditions emerged (see Figure 2). We
probed the interaction by treating time as the focal predictor and
experimental condition as the moderating variable (Preacher, Cur-
ran, & Bauer, 2006). These analyses revealed that time did not
significantly predict positive emotions for control participants
(b⫽⫺0.008, SE ⫽0.0079, p⫽.31) but did significantly predict
positive emotions for participants in the LKM condition (b⫽0.03,
SE ⫽0.008, p⫽.0001). Thus, these results confirm that LKM
increased participants’ positive emotions over the course of the
We then tested similar growth models for each of the nine
positive emotions included in the composite. In all cases, neither
main effect was significant, but their interaction was significant.
(The sole exception to this was that interest also showed both main
effects; see Table 2.) These results suggest that the findings for the
composite positive emotions variable were not determined by any
single positive emotion and that it is appropriate to consider the
positive emotions collectively.
We tested an additional growth model that examined compassion
over the duration of the study. Neither the main effects for experi-
mental condition and week, nor their interaction (b⫽0.021, SE ⫽
0.016, p⫽.21), was significant. Visual inspection revealed the same
pattern for compassion as for the positive emotions, but the increase
over time for meditators was not statistically significant.
What Role Did Individual Effort Play in the Impact of the
Intervention on Positive Emotions?
The impact of LKM on positive emotions might be expected to
be a function not only of experimental condition but also of
individual effort put into daily practice. We tested a growth model
for positive emotions that included the number of hours of medi-
tation practice each week as a fixed effect, time-varying predictor,
along with time and experimental condition. To allow us to ex-
amine any changes in the impact of meditation practice on positive
emotions over the course of the study, we entered meditation
practice for each week of the study as a separate variable. We
deliberately left experimental condition in the model to test the
unique contribution of time spent meditating each week, above and
beyond the impact of participation in the workshop or interaction
with the meditation instructor. Unexpectedly, time spent in “med-
itation, prayer, or solo spiritual activity” significantly predicted
positive emotions during the baseline week before the workshops
began ( p⫽.05), even when we excluded the participants who
reported a preexisting meditation practice. After the first week of
meditation instruction, time spent in meditative activity predicted
positive emotions for all time points except Week 4 ( p⫽.08),
even after we controlled for the other predictors in the model.
These results are presented in Table 3.
To estimate the impact of LKM instruction and practice on
positive emotions, we tested a separate model with the meditators
alone. By excluding the control participants, who were not receiv-
ing LKM instruction, we avoided diluting the estimate for the
impact of “meditation, prayer, or solo spiritual activity” on posi-
tive emotions with non-LKM forms of spiritual practice. In this
model, 1 hr of meditation practice during Week 2 was associated
with a 0.06-unit increase in positive emotions (SE ⫽0.03, p⫽.06)
on the 5-point Likert scale described above. This value increased
steadily during Weeks 3–7 of the study. By Week 7, each hour of
meditation practice was associated with a 0.17-unit increase in
positive emotions (SE ⫽0.03, p⬍.0001). These data suggest that
the dose-response relationship between the practice of LKM and
the experience of positive emotions tripled over the course of the
study. Furthermore, even though meditation practice dropped after
the workshop ended in Week 7, 1 hr of meditation practice in
Week 8 still exerted approximately the same influence on positive
emotions as it had in Week 7 (b⫽0.18, SE ⫽0.05, p⫽.0004).
Did LKM Influence Negative Emotions Over the Course
of the Study?
We also examined the impact of LKM on negative emotions
over the course of the study. Negative emotions were indexed by
a composite of daily ratings for anger, shame, contempt, disgust,
embarrassment, guilt, sadness, and fear. Across weeks, this index
score had an average alpha coefficient of .85 (range ⫽.81–.90). As
described above for positive emotions, the model included exper-
imental condition, week in the study, Time ⫻Condition interac-
tion, and hours of meditation practice each week. None of the
predictors were significant. Thus, neither experimental condition,
week in the study, their interaction (b⫽⫺0.011, SE ⫽0.011, p⫽
.28), nor time spent meditating during any weeks of the study
(range p⫽.11–.74) significantly influenced the negative emotions
sampled in this study.
To address concerns about multicollinearity between experimental
condition and time spent meditating, we tested a separate model in
which number of hours of meditation practice was group mean-
centered. The pattern of significant findings was identical, except that
the impact of time spent meditating became nonsignificant for Week 3,
as well as Week 4. Table 3 reports the uncentered meditation time
values, for ease of interpretation.
Positive Emot ions
Figure 2. Positive emotions by experimental condition.
1052 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
Did LKM Influence Emotions Within a
The DRM provided data on participants’ emotional experiences
within the episodes of an ordinary morning. This offered a window
into the impact of our intervention on emotional experiences in
response to specific daily events, rather than emotions summarized
over an entire day. Five participants did not provide DRM data,
leaving 134 for analysis. There were 918 episodes recorded in
total, with each participant reporting a mean of about seven epi-
sodes (M⫽6.85, SD ⫽2.38). As with the daily reports, composite
scores of positive and negative emotions were computed by taking
the mean of positive items and negative items, respectively. Con-
sistent with the daily reports, participants reported higher positive
emotions (M⫽1.16, SD ⫽0.15) than negative emotions (M⫽
0.15, SD ⫽0.28). Positive and negative emotions were largely
uncorrelated (r⫽⫺.06, p⫽.09).
Multilevel random-coefficient regression modeling has been rec-
ommended for analyzing DRM data (Stone et al., 2006). We esti-
mated a series of models predicting positive or negative emotions for
a given episode from experimental condition, total number of hours
engaged in meditative activity over the course of the study, the time
of day of the episode, whether the episode included meditation,
whether the episode included social interaction, and the interaction
between social interaction and total hours of meditative activity. This
interaction term was included to explore whether LKM—which fo-
cused on kindness and compassion toward others— had a specific
influence on the participant’s response to interactions with others. All
quantitative predictors were mean centered.
We established that the best fitting unconditional models for
positive and negative emotions had significant random intercepts
(ps⬍.0001) and autoregressive covariance structures ( ps⬍
.0001), indicating that participants began the day with significant
variability in their levels of positive and negative emotions and
that temporally close measures of emotion were more highly
correlated than more distant measures. Time of day positively
predicted positive emotions (b⫽0.065, SE ⫽0.009, p⬍.0001),
whereas no time trend emerged for negative emotions (b⫽0.002,
SE ⫽0.003, p⫽.54). These findings are consistent with diurnal
rhythms of positive emotions, which have been found to peak at
noon (Stone et al., 2006). Experimental condition was not signif-
icant for either positive or negative emotions (b⫽0.067, SE ⫽
0.118, ns, and b⫽⫺0.082, SE ⫽0.048, ns, respectively).
We next tested the total number of hours spent in meditative
activity (over the previous 9 weeks) as a predictor of emotional
experiences during the episodes of the targeted morning.
effect of time spent meditating on positive emotions emerged, above
and beyond the effect of time (b⫽0.033, SE ⫽0.010, p⫽.0008).
This was not true for negative emotions (b⫽⫺0.005, SE ⫽0.004,
p⫽.2064). Hence, time spent in meditative activity over the previous
9 weeks was associated with more frequent positive emotions and no
change in negative emotions across episodes within the targeted
morning. We do not consider negative emotions further.
A small number of participants (n⫽9) indicated in their DRM
responses that they had engaged in meditative activity that morn-
ing. To assess whether the target day’s meditative activity alone
could account for the significant effects on positive emotions
reported above, we reran the models in two ways. First, we added
meditation at episode as a time-varying predictor to test the effects
of engaging in meditative activity on positive emotions experi-
enced during that same episode. Second, in place of the episode-
level predictor, we added a dummy variable indicating whether or
It is not surprising that experimental condition and time spent medi-
tating were highly correlated, r(139) ⫽0.71, p⬍.0001. Thus, we exam-
ined them separately as predictors of emotions within the morning targeted
by the DRM.
Impact of Loving-Kindness Meditation on Specific Positive Emotions
Experimental condition Week Experimental condition ⫻week
Estimate SE p Estimate SE p Estimate SE p
Amusement ⫺0.112 0.125 .37 ⫺0.012 0.009 .20 0.040 0.014 .003
Awe ⫺0.163 0.123 .19 ⫺0.0003 0.010 .97 0.046 0.014 .001
Contentment 0.036 0.120 .76 ⫺0.002 0.011 .83 0.043 0.016 .006
Gratitude ⫺0.010 0.141 .94 0.0006 0.010 .96 0.035 0.014 .01
Hope ⫺0.139 0.127 .28 ⫺0.006 0.010 .55 0.044 0.015 .003
Interest ⫺0.421 0.136 .002 ⫺0.022 0.011 .05 0.060 0.016 .0002
Joy 0.0005 0.124 .997 ⫺0.013 0.010 .21 0.037 0.014 .01
Love 0.060 0.134 .66 ⫺0.009 0.010 .33 0.036 0.014 .009
Pride ⫺0.249 0.1369 .07 ⫺0.016 0.010 .15 0.048 0.014 .0008
Impact of Experimental Condition, Week, and Time Spent
Meditating on Positive Emotions
Predictor Estimate SE p
Intercept 2.717 0.075 ⬍.0001
Experimental condition ⫺0.124 0.110 .26
Week ⫺0.010 0.008 .20
Experimental Condition ⫻Week 0.026 0.013 .04
Time Spent Meditating ⫺Baseline 0.167 0.086 .05
Time Spent Meditating ⫺Week 1 0.006 0.039 .88
Time Spent Meditating ⫺Week 2 0.083 0.032 .01
Time Spent Meditating ⫺Week 3 0.068 0.031 .03
Time Spent Meditating ⫺Week 4 0.045 0.026 .08
Time Spent Meditating ⫺Week 5 0.093 0.029 .002
Time Spent Meditating ⫺Week 6 0.107 0.028 .0001
Time Spent Meditating ⫺Week 7 0.144 0.029 ⬍.0001
Time Spent Meditating ⫺Week 8 0.130 0.048 .007
POSITIVE EMOTIONS BUILD RESOURCES
not participants meditated that day to test the effects of engaging
in meditative activity on positive emotions experienced that day.
Meditating during an episode predicted higher positive emotions
during that episode (b⫽0.39, SE ⫽0.17, p⫽.0207) but did not
change the effect of hours engaged in meditative activity over the
previous 9 weeks on positive emotions experienced that morning
(b⫽0.033, SE ⫽0.010, p⫽.0008). Meditating any time that
morning also predicted positive emotions experienced that morn-
ing (b⫽0.52, SE ⫽0.23, p⫽.0247) but also did not change the
effect of total hours meditated throughout the study (b⫽0.029,
SE ⫽0.010, p⫽.0031). Thus, we can attribute much of the
increase in positive emotions on this particular day to the time
participants had spent meditating over the last several weeks.
Taken together, these DRM findings indicate that (a) meditation
produces positive emotions during meditation practice; (b) these
positive emotions persist after the meditation session has ended;
and (c) over time, repeated LKM practice produces a cumulative
increase in positive emotions that appears on subsequent days,
whether or not the individual meditates on that day.
Previous research has shown that, in general, people experience
more intense positive emotions when interacting with others than
when alone (McIntyre, Watson, Clark, & Cross, 1991). We ex-
plored whether time spent meditating over the previous 9 weeks
differentially influenced participants’ experiences of positive emo-
tions, depending on whether they were interacting with others or
not. We tested a model with time of day, social interaction, time
spent meditating over the previous 9 weeks, and the interaction
of social interaction and time spent meditating as predictors. The
slope for social interaction was allowed to vary (Var
SE ⫽0.25, p⫽.0187), confirming that interacting with others
predicted positive emotions differentially across individuals. Be-
yond the effects of time and hours spent in meditation, episode-
level social interactions (b⫽0.232, SE ⫽0.059, p⬍.0001) and
the interaction between time spent meditating and social interac-
tions (b⫽0.014, SE ⫽0.006, p⫽.0363) predicted positive
emotions in that morning. That is, more time spent meditating was
associated with higher positive emotions, and this effect was
stronger during social interactions.
Testing the Build Hypothesis
We tested the full build hypothesis by combining a growth
model for positive emotions with an SEM path analysis. This
combined model used the strengths of growth modeling, which
considers individual trajectories of change over time, and path
analyses, which can examine direct and indirect effects in media-
tional models. The growth model for positive emotions was repa-
rameterized as a latent trajectory model in an SEM framework
(Curran & Hussong, 2003). Experimental condition and time spent
meditating during the week predicted positive emotions for each
week of the study. Time spent meditating was entered as a time-
varying predictor. An intercept and slope for positive emotions
over the course of the study were created by allowing the indica-
tors for positive emotions, representing positive emotions during
each week of the study, to cross-load on both intercept and slope
latent variables. The latent variable that reflected the intercept of
positive emotions, at baseline, was created by fixing factor load-
ings for the indicators to 1.0. The latent variable that reflected
change in positive emotions over the course of the study was then
created by specifying factor loadings that reflected week in the
study (0.0 ⫽baseline, 1.0 ⫽Week 1, 2.0 ⫽Week 2, etc.).
In the path-analysis portion of the model, the intercept, repre-
senting each participant’s initial level of positive emotions during
the baseline week, and slope, representing each participant’s rate
of change in positive emotions over time, predicted change in his
or her resources between T1 and T2, which then predicted change
in life satisfaction between T1 and T2. In other words, each
participant’s baseline level of positive emotions and individual rate
of change in positive emotions over the course of the study,
calculated within the latent trajectory portion of the model, became
predictors in the path-analysis portion of the models we tested.
Given our experimental design, only change in positive emotions
(i.e., slope) was predicted to build participants’ resources. Thus,
we predicted that the path from slope of positive emotions to
resources would be significant, but the path from baseline positive
emotions to change in resources would not. The resource variable
was a difference score that represented change between T1 and T2
in the specific resource featured within each model. We tested the
model for each resource assessed, and this was the only variable
that changed across models. Last, the life-satisfaction variable was
also a difference score, representing change in life satisfaction
between T1 and T2. Thus, the model examined whether initial
positive emotions and changes in positive emotions over the
course of the study predicted changes in resources over the course
of the study, which, in turn, predicted changes in life satisfaction
over the course of the study. Participants with greater increases in
positive emotions were hypothesized to exhibit greater increases in
resources and, in turn, life satisfaction. A diagram of the model
tested is depicted in Figure 3.
The model was tested for each of the 18 resources identified in
Table 4, using LISREL 8.80 (Jo¨reskog & So¨rbom, 1996). A
multitude of factors may be associated with individual trajectories
of change over time, therefore, it is rare for growth models or
combined growth and path-analysis models to fit well when as-
sessed using standard SEM fit indices, such as root-mean-square
error of approximation (Widaman & Thompson, 2003). For this
reason, it is noteworthy that each of the models we tested produced
an estimated root-mean-square error of approximation of less than
0.08 (range ⫽0.068 – 0.076), indicating an acceptable fit to
the data. Given that all of the models tested were acceptable fits to
the data, and that overall model fit was influenced by the fit of the
latent trajectory portion of the model (which was the same for each
resource), we examined the significance of the individual path
coefficients in the models for each resource to test the build
As predicted, the path from baseline positive emotions to change
in resources (Path A) was not significant for any of the resources,
indicating that change in resources over the course of the study
was not significantly affected by participants’ initial levels of
positive emotions (see Table 4). The paths from change in positive
emotions (i.e., slope) to change in resources (Path B) and from
change in resources to change in life satisfaction (Path C) are
central to the build hypothesis. These paths were significant for 9
of the 18 resources tested: mindfulness, pathways thinking, savor-
ing the future, environmental mastery, self-acceptance, purpose in
life, social support received, positive relations with others, and
illness symptoms. In other words, increases in positive emotions
over the course of the study were associated with significant
1054 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
increases in these resources, which were, in turn, associated with
significant increases in life satisfaction. Table 4 presents the pa-
rameter estimates for all path coefficients tested. The first two
columns of Table 5 present the amount of variance explained in the
changes in resource and life satisfaction variables when the pre-
dicted build paths were significant.
Six of the nine remaining resources showed significant paths
influencing life satisfaction (Path C) but were not significantly
influenced by change in positive emotions (Path B). These re-
sources were agency thinking, savoring the past, savoring the
present, optimism, personal growth, and autonomy. This suggests
that these six measures are indeed consequential resources, even
though increases in positive emotions did not significantly aug-
Did Changes in Positive Emotions Directly Influence Life
Satisfaction, in Addition to Their Indirect Influence
Through Built Resources?
We examined the possibility that changes in positive emotions
could exert a direct effect on increases in life satisfaction (Path D),
in addition to the indirect effects via built resources (Paths B and
C). To examine this, we tested a series of models that included a
direct effect from change in positive emotions to change in life
satisfaction. The “Path D” column in Table 4 presents the results
for this path coefficient. (In Table 4, the columns for Paths A, B,
and C report values for these path coefficients when Path D is not
in the model.) The direct effect from change in positive emotions
to change in life satisfaction was not significant for any of the
models tested, nor did the model fit significantly improve when
this path was included. For the nine resources that were found in
previous analyses to exhibit the predicted pattern of significant
build paths, these path coefficients remained significant when the
direct effect of change in positive emotions on change in life
satisfaction was included in the model. These results indicate that
changes in positive emotions only produced changes in life satis-
faction to the extent that they built personal resources. This further
underscores the conceptual distinction between transient experi-
ences of positive emotions and global judgments of life quality
(Cohn et al., 2008; Diener et al., 2006).
Did Experimental Condition and Time Spent Meditating
Directly Impact Resources and Life Satisfaction, in
Addition to the Impact They Exerted Via Their Influence
on Changes in Positive Emotion?
We also examined the possibility that experimental condition
and amount of time spent meditating directly influenced changes
in resources and life satisfaction, in addition to their indirect
influence via positive emotions. We tested this possibility in a new
series of models. For purposes of clarity, these paths are not
represented in Figure 3, but they entail direct effects from exper-
imental condition and from each week’s variable for time spent
meditating to both change in resource and change in life satisfac-
tion. These effects were generally nonsignificant, with values that
varied depending upon the path and the resource being tested.
There was one exception: The direct effect from time spent med-
itating in Week 2 to change in life satisfaction was significant for
each of the 18 resources tested (e.g., mindfulness, b⫽0.49, z⫽
2.47). Excluding this direct effect, there were other, isolated sig-
nificant effects, which represented a total of 4% of the 360 path
coefficients estimated, but there was no pattern to these effects,
and they did not exceed the percentage of path coefficients that
would be expected on the basis of chance alone. These results
suggest that experimental condition and time spent meditating
Figure 3. Combined latent trajectory and path-analysis model. Avg. daily pos. emo. ⫽average daily positive
emotion; PE ⫽positive emotion; SWLS ⫽Satisfaction With Life Scale (Diener, Emmons, Larsen, & Griffin, 1985).
POSITIVE EMOTIONS BUILD RESOURCES
exerted their influence on resources and life satisfaction because of
their impact on positive emotions.
Do Positive Emotions Influence Depressive Symptoms
Through the Same Mechanism (i.e., Built Resources) by
Which They Influence Life Satisfaction?
To explore whether positive emotions might beneficially influ-
ence measures of negative psychological adjustment through the
same mechanisms by which they influence life satisfaction, we tested
a series of models for which depressive symptoms was the ultimate
variable in the model, replacing life satisfaction. In these models,
change in positive emotions predicted change in the resource,
which, in turn, predicted change in depressive symptoms. Model
fit, as determined by root-mean-square error of approximation,
remained acceptable. In addition, the predicted build paths were
significant for the same nine resources for which these paths were
significant when life satisfaction was the ultimate variable in the
models. These findings suggest that increases in positive emotions
decrease depressive symptoms through the same mechanisms by
which they increase life satisfaction: built resources.
We also examined the possibility that positive emotion directly
influenced depressive symptoms, in addition to its indirect impact
via built resources. In the first set of models, we examined the
significance of the direct effect from change in positive emotions
to change in depressive symptoms (Path D). Unlike the results for
life satisfaction, this path was significant for all models tested. In
addition, the overall fit of the models significantly improved for all
18 resources when this path was included in the model ( p⬍
.0025). Even so, the predicted build paths remained significant for
eight of the nine previously significant resources. This pattern of
results suggests that increases in positive emotions influenced the
decline in depressive symptoms via both built resources and a
direct impact on depressive symptoms. The one resource for which
this was not the case was social support received, for which the
mediated build paths were not significant when Path D was in-
cluded. Table 6 presents the parameter estimates for these models.
The last two columns of Table 5 present the amount of variance
explained in the changes in resource and depressive symptoms
variables when the predicted build paths were significant. In a
second set of models, we examined the direct effects from exper-
imental condition and time spent meditating each week to the
changes in resources and depressive symptoms, for each of the
resources tested. Although isolated paths were significant, these
represented only 2.8% of the paths tested, and there was no
discernible pattern to which paths were significant.
To test for possible effects of differential participant completion
on our results, we repeated the analyses above using our intent-
to-treat and per-protocol samples. The impact of experimental
condition over time on positive emotions was not significant in
either the intent-to-treat, t(1380) ⫽1.37, p⫽.17, or per-protocol
Resource Models Tested With Life Satisfaction as Outcome Variable
Resource tested RMSEA (90% CI)
(137, N⫽139) Path A Path B Path C Path D
0.068 (0.051–0.083) 224.58 ( p⫽.00) ⫺0.10 (z⫽⫺1.17) 0.20 (z⫽2.04) 0.25 (z⫽3.04) 0.12 (z⫽1.24)
Agency thinking 0.074 (0.058–0.089) 241.15 ( p⫽.00) ⫺0.03 (z⫽⫺0.38) 0.17 (z⫽1.74) 0.36 (z⫽4.46) 0.11 (z⫽1.15)
0.071 (0.056–0.087) 234.24 ( p⫽.00) ⫺0.03 (z⫽⫺0.32) 0.22 (z⫽2.25) 0.24 (z⫽2.94) 0.12 (z⫽1.19)
Savoring the past 0.070 (0.053–0.085) 228.99 ( p⫽.00) 0.05 (z⫽0.51) 0.15 (z⫽1.52) 0.18 (z⫽2.17) 0.15 (z⫽1.49)
Savoring the present 0.071 (0.055–0.086) 232.88 ( p⫽.00) ⫺0.13 (z⫽⫺1.45) 0.18 (z⫽1.87) 0.30 (z ⫽3.72) 0.12 (z⫽1.19)
Savoring the future
0.072 (.056–0.087) 235.94 ( p⫽.00) ⫺0.06 (z⫽⫺0.74) 0.20 (z⫽2.08) 0.28 (z⫽3.38) 0.12 (z⫽1.22)
Optimism 0.075 (0.059–0.090) 243.70 ( p⫽.00) ⫺0.06 (z ⫽⫺0.70) 0.04 (z⫽0.38) 0.26 (z⫽3.10) 0.16 (z⫽1.64)
Ego-resilience 0.075 (0.059–0.090) 243.13 (p⫽.00) ⫺0.07 (z⫽⫺0.83) 0.25 (z⫽2.53) 0.14 (z⫽1.65) 0.14 (z⫽1.42)
Personal growth 0.073 (0.057–0.088) 237.88 ( p⫽.00) 0.00 (z⫽⫺0.05) 0.14 (z⫽1.42) 0.30 (z⫽3.75) 0.13 (z⫽1.37)
0.070 (0.054–0.086) 231.02 ( p⫽.00) 0.06 (z⫽0.66) 0.33 (z⫽3.37) 0.38 (z⫽4.86) 0.06 (z⫽0.64)
Autonomy 0.075 (0.059–0.090) 243.87 ( p⫽.00) ⫺0.08 (z⫽⫺0.94) ⫺0.01 (z⫽⫺0.07) 0.18 (z⫽2.15) 0.17 (z⫽1.72)
0.072 (0.056–0.088) 236.21 ( p⫽.00) ⫺0.08 (z⫽⫺0.92) 0.27 (z⫽2.77) 0.42 (z ⫽5.45) 0.05 (z⫽0.58)
Purpose in life
0.076 (0.060–0.091) 245.55 ( p⫽.00) 0.11 (z⫽1.30) 0.29 (z⫽2.95) 0.40 (z⫽5.09) 0.07 (z⫽0.71)
Social support given 0.071 (0.055–0.087) 233.63 ( p⫽.00) 0.16 (z⫽1.82) 0.15 (z⫽1.49) 0.15 (z⫽1.77) 0.15 (z⫽1.57)
Social support received
0.072 (0.056–0.087) 235.84 ( p⫽.00) ⫺0.09 (z⫽⫺0.98) 0.25 (z⫽2.54) 0.21 (z⫽2.54) 0.13 (z⫽1.28)
Positive relations with others
0.071 (0.055–0.086) 232.06 ( p⫽.00) ⫺0.01 (z⫽⫺0.10) 0.29 (z⫽2.97) 0.36 (z⫽4.54) 0.08 (z⫽0.79)
0.071 (0.055–0.086) 232.82 ( p⫽.00) ⫺0.09 (z⫽⫺1.01) ⫺0.24 (z⫽⫺2.47) ⫺0.20 (z⫽⫺2.37) 0.13 (z⫽1.27)
Duration of sleep 0.072 (0.057–0.088) 236.80 ( p⫽.00) ⫺0.11 (z⫽⫺1.22) ⫺0.14 (z⫽⫺1.35) 0.01 (z⫽0.14) 0.18 (z⫽1.78)
Note. RMSEA ⫽root-mean-square error of approximation; CI ⫽confidence interval. Parameter estimates are reported in standardized units. Path D was
tested in a separate set of models, for which the RMSEA values and parameter estimates for Paths A, B, and C were slightly different than those listed
above. For purposes of brevity, we have not presented these slightly different values when Path D was incorporated in the model.
Model was a good fit for the data, and the predicted build-hypothesis paths (Paths B and C) were significant.
1056 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
samples, t(1380) ⫽1.58, p⫽.11, whereas it was significant in our
completer sample (discussed above). The impact of time spent
meditating on positive emotions remained significant in both sam-
ples, starting with the first week of instruction. The resources for
which we found significant build paths (paths from positive emo-
tion change to resource to life satisfaction; shown as Paths B and
C in Figure 3) generally showed the same significant paths in the
intent-to-treat and per-protocol samples. Positive emotions signif-
icantly predicted savoring the future only in the completer sample,
and change in ego resilience significantly predicted change in life
satisfaction and depression in the intent-to-treat and per-protocol
samples, even though it did not do so in the completer sample.
Overall, the hypothesis that positive emotions help people build
consequential personal resources was supported in the intent-to-
treat analysis. However, these analyses suggest that conclusions
about the efficacy of LKM may need to be restricted to individuals
who invest adequate effort in training and practice (approximately
70% in this sample).
The broaden-and-build theory (Fredrickson, 1998, 2001) states
that, over time, recurrent experiences of positive emotions allow
people to build consequential personal resources. The data reported
here provide the first experimental test of the build hypothesis. The
findings are clear cut: The practice of LKM led to shifts in people’s
daily experiences of a wide range of positive emotions, including
love, joy, gratitude, contentment, hope, pride, interest, amusement,
and awe. These increases in positive emotions were evident both
within the trajectories of change in daily emotions over the span of 9
weeks and within a detailed analysis of a given morning 2 weeks after
formal training ended. These shifts in positive emotions took time to
appear and were not large in magnitude, but over the course of 9
weeks, they were linked to increases in a variety of personal re-
sources, including mindful attention, self-acceptance, positive rela-
tions with others, and good physical health. Moreover, these gains in
personal resources were consequential: They enabled people to be-
come more satisfied with their lives and to experience fewer symp-
toms of depression. Simply put, by elevating daily experiences of
positive emotions, the practice of LKM led to long-term gains that
made genuine differences in people’s lives.
The conceptual model— drawn from the broaden-and-build theory
and depicted in Figure 1—is unambiguously supported by the evi-
dence reported here. Most important, positive emotions emerge as the
clear centerpiece of the model. LKM was beneficial precisely because
it helped people experience positive emotions; direct effects of LKM,
circumventing the hypothesized build paths, were virtually nonexist-
ent. Positive emotions emerged as the mechanism through which
people build the resources that make their lives more fulfilling and
help keep their depressive symptoms at bay.
These data also echo a message from our recent work that
unpacks the relationship between positive emotions and life satis-
faction (Cohn et al., 2008). Although both can be considered facets
of happiness or subjective well-being (Lucas et al., 1996), we
found positive emotions, and not life satisfaction, to predict change
in resources. Furthermore, the association between increased pos-
itive emotions and increased life satisfaction was fully mediated by
resource building. This suggests that people judge their lives to be
more satisfying and fulfilling, not because they feel more positive
emotions per se, but because their greater positive emotions help
them build resources for living successfully.
Variance Explained in Change in Resources and Change in Life Satisfaction and Depression for
Depression models (negative
⌬life satisfaction R
Mindfulness 0.06 0.06 0.06 0.22
Pathways thinking 0.05 0.06 0.05 0.15
Savoring the future 0.05 0.08 0.05 0.16
Environmental mastery 0.10 0.15 0.10 0.25
Self-acceptance 0.09 0.18 0.09 0.24
Purpose in life 0.08 0.16 0.08 0.29
Social support received 0.08 0.04 0.08 0.15
Positive relations with others 0.08 0.13 0.09 0.24
Illness symptoms 0.06 0.04 0.05 0.18
Note. The variance estimates reported for the life-satisfaction models is for models that include Paths A, B, and
C, but not D, because this path was not significant for any of the life-satisfaction models tested. The variance
reported for the depression models is for models that include Paths A, B, C, and D, because path D was
significant for each of the depression models tested. Direct effects from experimental condition and time spent
meditating to resource and life satisfaction/depression were not included in any of the models.
POSITIVE EMOTIONS BUILD RESOURCES
Nine of the eighteen resources we tested fit the hypothesized
build paths. Of the remaining nine, six showed changes in the
expected direction on the build paths (see Table 4). We speculate
that these six resources may be affected by positive emotions,
albeit less strongly or more slowly than other resources, and not
that the build hypothesis is categorically inapplicable to them.
The resources that did show significant build effects might be
loosely grouped into two categories. The first involves having a
loving attitude toward oneself and others and includes self-
acceptance, social support received, and positive relations with others.
The second involves a feeling of competence about one’s life and
includes pathways thinking, environmental mastery, purpose in life,
and ego-resilience (which was influenced by positive emotions, al-
though just shy of significantly influencing life satisfaction). We
speculate that increases in positive emotions may impact these re-
sources more rapidly and to a greater extent than others.
This study confirms yet again that positive emotions are more
than momentary good feelings. Laboratory experiments have doc-
umented that positive emotions broaden cognition (for a review,
see Fredrickson & Cohn, 2008). Now we have evidence from a
field experiment to document that positive emotions also place
people on trajectories of growth, leaving them better able to ward
off depressive symptoms and become ever more satisfied with life.
This experiment also carries the inspiring implication that people
can take deliberate action to cultivate meaningful experiences of
positive emotion and reap these benefits as a result.
This field experiment also further documents the benefits of
meditation. When people initiated a practice of LKM, they enjoyed
payoffs both immediately, in terms of self-generated positive emo-
tions, and over time, in terms of increased resources and overall
well-being. Meditators even experienced enhanced positive emo-
tions in ordinary life situations, especially those involving other
people. This substantiates the claim that this type of meditation
changes the way people approach life.
We found that the effects of LKM were specific to positive
emotions, without a comparable decrease in negative emotions.
This resembles the work of Teasdale et al. (2000), who anecdotally
reported that their mindfulness-based protocol does not reduce
negative emotions but, instead, alters responses to negative emo-
tions that can lead to depression (Segal et al., 2002). In contrast,
Carson et al. (2005) uncovered a marginal decrease in trait anger
in their pilot study of LKM. They also observed reductions in
anxiety and distress, but these may have been due to the study’s
central outcome of pain amelioration. Davidson et al. (2003) also
found a decrease in trait anxiety with mindfulness-based stress
reduction but only weak support for changes in negative emotion.
Future work will need to resolve these inconsistencies.
Another curious finding was the null effect of LKM on self-
ratings of compassion. In hindsight, we speculate that our sole
daily item for compassion (“In the past 24 hours, what is the most
sympathy, concern or compassion you have felt?”) may have
oriented respondents toward compassion felt in response to the
suffering of others, rather than kindness or equanimity per se. If
the suffering of others was not directly salient to participants on a
daily basis, increases on this particular item may have been lim-
Resource Models Tested With Depressive Symptoms (Negative Symptoms Only) as Outcome Variable
Resource tested RMSEA (90% CI)
(136, N⫽139) Path A Path B Path C Path D
0.070 (0.053–0.085) 227.53 ( p⫽.00) ⫺0.10 (z⫽⫺1.18) 0.20 (z⫽2.06) ⫺0.28 (z⫽⫺3.88) ⫺0.31 (z⫽⫺3.06)
Agency thinking 0.074 (0.059–0.090) 240.88 ( p⫽.00) ⫺0.03 (z⫽⫺0.39) 0.18 (z⫽1.77) ⫺0.27 (z⫽⫺3.41) ⫺0.30 (z⫽⫺3.25)
0.072 (0.056–0.087) 233.37 ( p⫽.00) ⫺0.03 (z⫽⫺0.31) 0.22 (z⫽2.23) ⫺0.17 (z⫽⫺2.02) ⫺0.31 (z⫽⫺3.22)
Savoring the past 0.069 (0.053–0.085) 226.33 ( p⫽.00) 0.05 (z⫽0.52) 0.16 (z⫽1.59) ⫺0.23 (z⫽⫺2.81) ⫺0.32 (z⫽⫺3.39)
Savoring the present 0.073 (0.057–0.088) 237.09 ( p⫽.00) ⫺0.13 (z⫽⫺1.46) 0.19 (z⫽1.89) ⫺0.42 (z⫽⫺5.62) ⫺0.27 (z⫽⫺3.04)
Savoring the future
0.072 (0.056–0.087) 233.93 ( p⫽.00) ⫺0.07 (z⫽⫺0.75) 0.21 (z⫽2.15) ⫺0.19 (z⫽⫺2.37) ⫺0.31 (z⫽⫺3.24)
Optimism 0.075 (0.059–0.090) 241.11 ( p⫽.00) ⫺0.06 (z⫽⫺0.70) 0.04 (z ⫽0.40) ⫺0.10 (z⫽⫺1.27) ⫺0.35 (z⫽⫺3.63)
Ego-resilience 0.075 (0.059–0.090) 242.45 ( p⫽.00) ⫺0.07 (z⫽⫺0.83) 0.25 (z ⫽2.53) ⫺0.02 (z⫽⫺0.25) ⫺0.35 (z⫽⫺3.45)
Personal growth 0.075 (0.059–0.090) 241.56 ( p⫽.00) 0.00 (z⫽⫺0.04) 0.14 (z ⫽1.45) ⫺0.35 (z⫽⫺4.58) ⫺0.30 (z⫽⫺3.35)
0.071 (0.056–0.087) 232.54 ( p⫽.00) 0.06 (z⫽0.69) 0.33 (z⫽3.39) ⫺0.37 (z ⫽⫺4.61) ⫺0.24 (z⫽⫺2.57)
Autonomy 0.072 (0.057–0.087) 243.07 ( p⫽.00) ⫺0.08 (z⫽⫺0.94) ⫺0.01 (z⫽0.07) ⫺0.08 (z⫽⫺0.98) ⫺0.35 (z⫽⫺3.66)
0.073 (0.058–0.089) 237.81 ( p⫽.00) ⫺0.08 (z⫽⫺0.93) 0.27 (z⫽2.78) ⫺0.35 (z⫽⫺4.36) ⫺0.25 (z⫽⫺2.71)
Purpose in life
0.076 (0.061–0.091) 246.05 ( p⫽.00) 0.12 (z⫽1.33) 0.29 (z⫽2.97) ⫺0.43 (z⫽⫺5.65) ⫺0.24 (z⫽⫺2.66)
Social support given 0.071 (0.055–0.087) 231.87 ( p⫽.00) 0.16 (z⫽1.81) 0.16 (z⫽1.59) ⫺0.06 (z⫽⫺0.69) ⫺0.35 (z⫽⫺3.58)
Social support received 0.072 (0.056–0.088) 234.70 ( p⫽.00) ⫺0.08 (z⫽⫺0.98) 0.25 (z⫽2.60) ⫺0.15 (z⫽⫺1.80) ⫺0.32 (z⫽⫺3.21)
Positive relations with
0.071 (0.055–0.086) 230.43 ( p⫽.00) ⫺0.01 (z⫽⫺0.08) 0.30 (z⫽3.02) ⫺0.35 (z⫽⫺4.33) ⫺0.25 (z⫽⫺2.71)
0.072 (0.056–0.088) 234.74 ( p⫽.00) ⫺0.09 (z⫽⫺1.02) ⫺0.24 (z⫽⫺2.40) 0.26 (z⫽3.17) ⫺0.29 (z⫽⫺3.09)
Duration of sleep 0.073 (0.057–0.088) 235.69 ( p⫽.00) ⫺0.10 (z⫽⫺1.11) ⫺0.15 (z⫽⫺1.48) ⫺0.13 (z⫽⫺1.50) ⫺0.37 (z⫽⫺3.87)
Note. RMSEA ⫽root-mean-square error of approximation; CI ⫽confidence interval. Parameter estimates are reported in standardized units.
Model was a good fit for the data, and all predicted build-hypothesis paths (Paths B and C) were significant.
1058 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL
ited. We suggest that future work tailor measures of compassion to
more directly reflect the teachings of contemplative traditions.
A final puzzling finding was the initially lower level of positive
emotions in the meditation group. We speculate that this difference
reflects the difficulties of initiating any self-change effort, even if
those changes are self-chosen. Consider the parallel to the perennial
New Year’s resolution to lose weight to be healthier. At the peak of
a person’s motivation to shed pounds, he or she might join a local
gym. Then, days later, the person realizes that he or she must actually
go to the gym and exercise. Starting a meditation practice may
similarly involve a period of doing something unfamiliar, difficult,
and draining without immediate rewards. Contemplative traditions
have articulated five obstacles facing novice meditators, including
craving, anger, boredom, restlessness, and doubt (Kabat-Zinn, 2005).
These obstacles are thought to result from increased awareness of
challenging inner states that may be commonly present, although not
noticed during one’s typical busy and outward-directed focus. Indeed,
nearly all attrition occurred during the initial weeks, when participants
may not have been sufficiently “in shape” to feel competent at
meditation or derive benefits from it. Yet if people can endure these
first difficult weeks, meditation becomes more effective, and positive
emotions begin to accumulate and compound, changing people for the
Because we set out to develop a durable method of inducing
positive emotions, the dose-response results we documented are par-
ticularly inspiring. We found that the amount of positive emotions
participants gained per hour spent meditating increased over the
course of the study, tripling from the first week to the last. Rather than
becoming bored with or jaded to the effects of meditation, our
participants seemed to be building a dependable skill for self-
generating positive emotions again and again. These findings are
especially noteworthy given that most of our participants were novice
meditators and our meditation workshop lasted only 7 weeks.
Limitations and Future Directions
This study breaks new ground in several ways, which leaves ample
room for future research to probe or refine its findings. First, the
sample was predominantly White, educated, and motivated for self-
change. Mindfulness-based programs have shown widespread emo-
tional and medical benefits in diverse populations and for individuals
without prior interest in meditation (Kabat-Zinn, 1990), and it will be
important to determine whether the same holds true for LKM. Sec-
ond, the duration of the experiment was just over 10 weeks. In the
future, it will be important to investigate the extent to which the
resources endure beyond the end of the intervention or into periods of
heightened stress or negative emotions. We found that after the formal
workshop ended, time spent meditating and positive emotions de-
creased in tandem, even though meditation remained effective at
evoking positive emotions. Lyubomirsky, Sheldon, and Schkade
(2005) have argued that intentional activity is required to sustain gains
in happiness. Future research will benefit from assessing the duration
of gains or determinants of continued, independent practice. Finally,
the current experiment did not include daily measures of broadened
cognition, which would have allowed a more precise test of the
proposed links between positive emotions, broadened thinking, and
resources. Currently, no measures of broadening are valid, repeatable,
and administrable outside the lab, but once one has been developed
and validated, it will be an important contribution to this research
Another necessity in future work will be to move beyond self-
report data to eliminate concerns of shared method variance. Implicit
or behavioral measures, observer reports, and physiological markers
will be especially useful. Specifically, researchers can track changes
in emotions over time with implicit or behavioral measures of affect
(Payne, Cheng, Govorun, & Stewart, 2005) or positivity bias
(Carstensen & Mikels, 2005). In a more recent study of LKM, we
obtained observer reports from peers identified by study participants.
Preliminary analyses suggest that, as expected, observers judge med-
itators to be more helpful than control participants (Fredrickson,
2008). Romantic partners, supervisors and physicians would also be
fruitful informants in future research. Finally, in current and planned
work, we are investigating whether LKM produces changes in respi-
ratory sinus arrhythmia, progesterone, and oxytocin, each of which
has been linked to positive social relations (e.g., Brown et al., 2008;
Eisenberg et al., 1995; Holt-Lunstad, Birmingham, & Light, in press).
The comparison condition within this experiment was a waitlist
control group. Although typical for initial tests of psychological
interventions (e.g., Davidson et al., 2003; Teasdale et al., 2000),
this experimental design can inadvertently create experimenter
demand, expectation of improvement, or nonspecific effects re-
lated to delivery format. We address each possibility in turn: First,
the explicit focus on love and kindness may have created demand
to elevate self-reports of these emotions. However, our data indi-
cated that (a) LKM was associated with changes in many positive
emotions, not just the ones explicitly discussed; (b) guided med-
itations featured the terms “love” and “compassion” beginning in
Week 1, yet the profile of changes in self-reported positive emo-
tions (see Figure 2) shows that positive emotions did not signifi-
cantly increase until Week 3; and (c) self-reported positive emo-
tions fit into a full set of mediational pathways (see Figure 3),
which participants were unlikely to intuit and use to shape their
Second, simply participating in a meditation workshop
might create the expectation of improvement. These expectations
might give rise to positive emotions, such as hope and confidence,
a legitimate, though nonspecific, effect of the intervention. We
underscore that the increase in positive emotions evident in the
current study did not appear until Week 3 (see Figure 2), whereas
placebo responses typically emerge rapidly (Scott et al., 2007).
Third, nonspecific effects of delivery format, including contact
with a caring instructor, group interaction, and weekly work-
release time might also have contributed to increases in positive
emotions. However, we found that when controlling for group
assignment, time spent meditating still predicted increases in pos-
itive emotions. Even among participants who received the nonspe-
Another way experimenter demand might have produced the results is if
meditation participants gradually began to skip responding on days low in
positive emotions. Meditation participants did respond less frequently over
time (dropping from 5.2 to 4.6 responses per week), whereas waitlist partici-
pants did not, F(7, 132) ⫽3.75, p⫽.002. However, the week-by-week
correlations between positive emotions and response frequency were very low
in both groups. The sole significant correlation suggested that, if anything, the
highest positive emotions were reported by participants who responded most
frequently (i.e., least selectively). Also, recall that emotion measures were
analyzed using per-participant means for each week, meaning that frequent
responders did not contribute disproportionately to the data.
POSITIVE EMOTIONS BUILD RESOURCES
cific benefits, meditation itself—the proposed core of the inter-
vention—predicted positive change. We also examined whether
participants reported a boost in positive emotions on the day of
workshop sessions or the day after, comparing waitlist partici-
pants, LKM participants who did not attend that week’s workshop,
and LKM participants who did. The results did not differ from
chance, suggesting that the higher positive emotions reported by
LKM participants reflected a continuous upward trend, rather than
a temporary response to the one day each week that involved time
off of work, social support, and contact with the instructor. Over-
all, patterns in our data argue against spurious results arising from
our use of a waitlist control group. Now that LKM has shown
efficacy in increasing positive emotions and building personal
resources, future work will be able to directly control for nonspe-
cific effects and expectancies by comparing LKM with other
meditative or self-change techniques.
Another alternative explanation for our findings is that whatever
positive emotions our participants were feeling at T2 cast a rosy
glow over all their self-reports and artificially produced the ap-
pearance of growth in resources. The reports from the DRM
provided an estimate of positive emotions for the day the T2
measures were completed. We regressed that day’s positive emo-
tions on aggregate positive emotions over the 9 weeks of daily
reports (R⫽.69) and created a residual term, representing positive
emotions that were present at T2 and could have cast a rosy glow
over responses but that were not present during the time resources
were being built. We tested the residual variable in our mediational
models, in place of change in positive emotions over time. It did
not predict change in any of the resources. This suggests that
positive emotions experienced over time exerted a gradual, cumu-
lative effect, rather than simply biasing responding at the moment
participants were responding to T2 questionnaires.
One of the most deflating concepts facing positive psychology is
the hedonic treadmill (Brickman, Coates, & Janoff-Bulman, 1978):
Even though positive and negative events (e.g., winning the lot-
tery, becoming paraplegic) temporarily alter levels of happiness,
people quickly adapt to them and return to a fixed emotional
set-point. The hedonic treadmill, as classically stated, implies that
all efforts to improve happiness are doomed to failure. Yet more
nuanced research (Diener et al., 2006) indicates that adaptation is
not necessarily inevitable and may be strongest for negative affect
and weaker for positive affect and life satisfaction. The evidence
reported here reveals that one way to outpace the hedonic treadmill
is to begin a practice of LKM. Participants who invested an hour
or so each week practicing this form of meditation enhanced a
wide range of positive emotions in a wide range of situations,
especially when interacting with others. We find these data espe-
cially promising. LKM appears to be one positive emotion induc-
tion that keeps on giving, long after the identifiable “event” of
Positive emotions feel good, and feelings like love, joy, and
contentment can be valuable in and of themselves. Yet the
broaden-and-build theory posits that natural selection sculpted our
ancestors’ positive emotions to be useful in more far-reaching
ways as well. These desirable states built resources that gave our
ancestors’ an edge in circumstances that impinged on their sur-
vival. To our knowledge, this is the first experiment to provide
clear support for the build hypothesis. By random assignment, one
group of individuals began a mind-training practice that increased
their positive emotions and, in turn, their personal resources and
well-being. Just as the broaden-and-build theory predicts, then,
when people open their hearts to positive emotions, they seed their
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Received April 27, 2007
Revision received April 26, 2008
Accepted June 3, 2008 䡲
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1062 FREDRICKSON, COHN, COFFEY, PEK, AND FINKEL