Correspondence concerning this article should be addressed to Barbara L. Fredrickson, Department of Psychology, Davie Hall, CB 3270, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599. ude.cnu@flb
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The publisher's final edited version of this article is available at J Pers Soc Psychol
Abstract
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, interest, 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 positive 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; Moskowitz, 2003; Ostir, Markides, Black, & Goodwin, 2000]. Indeed, a recent meta-analysis of nearly 300 findings concluded that positive 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 positive 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 moment; 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 opportunities, becoming successful, healthy, and happy in the months and years to come. Thus, the personal resources accrued, often unintentionally, through frequent experiences of positive emotions are posited 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.
The key hypotheses of the broaden-and-build theory have received empirical support from multiple laboratories. First, the broaden hypothesis holds that positive emotions broaden people’s attention and thinking. Experiments have shown that, relative to neutral and negative states, induced positive emotions widen the scope of people’s visual attention [Fredrickson & Branigan, 2005; Rowe, Hirsh, & Anderson, 2007; Wadlinger & Isaacowitz, 2006], broaden their repertoires of desired actions [Fredrickson & Branigan, 2005], and increase 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 empirical 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 longitudinal 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 treadmill 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. Meditation, 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 people 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 meditators 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 meditation practice increases positive affect is also supported by at least one experience sampling study [Easterlin & Cardeña, 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 meditation [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 broadened 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, including LKM, are not simply vehicles for improving emotion experiences. 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 themselves 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 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 enhancing positive emotions.
LKM involves a range of thoughts and visualizations, and it directly evokes only select positive emotions [i.e., love, contentment, and compassion] and carries some potential to evoke negative 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 distress. 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 consequential personal resources. In designing our experiment, we grappled with selecting the most appropriate comparison condition. 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 concerns 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 demand, delivery format, and expectation of improvement, we address 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 completed an initial survey that assessed their life satisfaction, depressive 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 meditation practice. About 2 weeks after the workshop ended, participants completed a final survey that reassessed their life satisfaction, 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, Schkade, 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 questions, 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, produced 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, increase 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, because 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.
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Figure 1
Conceptual model depicting predicted causal paths between loving-kindness meditation, change in positive emotions, change in resources, and change in life satisfaction.
Method
Participants
The study was conducted at the Compuware Corporation, a large business software and information technology services company in Detroit, Michigan. All full-time employees working at Compuware’s Detroit headquarters [approximately 1,800 individuals, 38% female, 34% ethnic minorities] received an e-mail message from Compuware executives inviting them to participate in the study.1 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, χ2[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 compositions 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, χ2[1, N = 180] = 10.9, p = .001. There was also a trend towards loss of married participants, χ2 [1, N = 178] = 3.2, p = .07. These groups, however, were lost equally between conditions [waitlist = 64% female, meditators = 67% female], χ2[1, N = 139] = .17, p = .69, [waitlist = 56% married, meditators = 60% married], χ2[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, removing their data did not alter the pattern of findings reported here.
Table 1
Participant Demographics
Participant characteristicIntent-to-treatPer-protocolCompletersaN195175139% providing demographic informationb88.293.9100.0% in meditation group49.243.448.2% female59.860.865.5Agec414141Education levelcBachelor’s degreeBachelor’s degreeBachelor’s degree% married60.559.857.7Incomec [$]>85,000>85,000>85,000Depressiond [CES–D, full scale] Baseline16.115.415.9 Posttest12.712.412.8Life satisfaction [SWLS] Baseline4.124.174.10 Posttest4.424.464.50% White [non-Hispanic]73.773.372.6
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Note. CES–D = Center for Epidemiological Studies—Depression Measure [Radloff, 1977]. SWLS = Satisfaction With Life Scale [Diener, Emmons, Larsen, & Griffin, 1985].
aFor exclusion criteria, see Methods section.
bTwenty-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.
cValue reported is median.
dTo 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.
In addition to providing access to the participant pool, Compuware 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 participants 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.
Procedure
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 wellness courses, specifically, the potential to reduce stress and improve 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 by phone.
Within the week following orientation, interested employees logged on to a secure website, gave consent to participate in the 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 questionnaire. After data collection was completed, participants received debriefing information explaining more about the details of the study.2 Approximately 2 months later, meditation classes began for the waitlist control group. No further data were collected at that time.
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.
LKM Workshops
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 experience practicing and teaching LKM. The median number of sessions attended was five [M = 4.3, SD = 1.8]. At the first session, participants were given a CD that included three guided meditations 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 meditation, 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.3
Measures
Cognitive Resources: T1 and T2
Mindfulness and Awareness Scale
The Mindfulness and Awareness Scale [Brown & Ryan, 2003] assesses awareness of 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. [αT1 = .86, αT2 = .89].
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 disagreement [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” [αT1 = .84, αT2 = .81], and pathways thinking [belief that there are multiple ways to achieve one’s goals], including “There are lots of ways around any problem” [αT1 = .84, αT2 = .83].
Savoring Beliefs Inventory
The Savoring Beliefs Inventory [Bryant, 2003] assesses one’s tendency to enjoy pleasant experiences 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, αT1 = .88, αT2 = .92; savoring the present, αT1 = .88, αT2 = .89; savoring the future, αT1 = .87, αT2 = .91].
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; αT1 = .82, αT2 = .79].
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” [αT1 = .73, αT2 = .74].
Psychological well-being
We measured five additional psychological resources using subscales of Ryff’s [1989] broader psychological 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” [αT1 = .76, αT2 = .80]; environmental mastery, with items like “I often feel overwhelmed by my responsibilities” [reverse scored; αT1 = .78, αT2 = .80]; autonomy, with items like “I am not afraid to voice my opinions, even when they are in opposition to the opinions of most people” [αT1 = .72, αT2 = .77]; self-acceptance, with items like “I like most parts of my personality” [αT1 = .88, αT2 = .86]; and purpose in life, with items like “My daily activities often seem trivial and unimportant to me” [reverse scored; αT1 = .80, αT2 = .80].
Social Resources: T1 and T2
Dyadic Adjustment Scale
The Dyadic Adjustment Scale [Spanier, 1976] measures social support as the amount of emotional 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 [αT1 = .81, αT2 = .81] and social support received [αT1 = .83, αT2 = .83].
Positive relations with others
Our third index of social resources 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; αT1 = .81, αT2 = .81].
Physical Resources: T1 and T2
Illness symptoms
This self-report measure assesses 13 common 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; αT1 = .82, αT2 = .84].
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 satisfaction with their lives and circumstances. Participants indicate agreement with each item on a 7-point scale, including “So far I have gotten the important things I want in life” [αT1 = .88, αT2 = .90].
Center for Epidemiological Studies—Depression Measure
We assessed depressive symptoms with the Center for Epidemiological Studies—Depression Measure [Radloff, 1977]. We excluded 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” [αT1 = .86, αT2 = .88].
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 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, interest, love, pride, guilt, sadness, shame, fear, and surprise. Participants also reported whether they had engaged in “meditation, 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.
DRM: T2
We used the DRM [Kahneman et al., 2004] to assess participants’ 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 episode to provide ratings from 0 [not at all] to 4 [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/meditating.” They also responded “yes” or “no” to the question, “Were you interacting with anyone [including on the phone, in a teleconference, etc]?”
Results
Overview of Data Analytic Strategy
Given the complexity of the data set, we performed a range of analyses, which we forecast here.4 As a manipulation check, we used t tests 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 trajectory model. In the path-analysis portion of the model, baseline positive emotions and slope of change in positive emotions predicted 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.5
Results were analyzed separately in three samples:
individuals who adhered to the study requirements described above [our “complete data” sample, n = 139];
an intent-to-treat sample [n = 195], comprising all of the participants who were successfully randomly assigned to experimental condition; and
a per-protocol sample [n = 175], comprising [a] all of the participants successfully randomly assigned to the waitlist control condition [n = 98] and [b] those participants assigned to LKM who received a predetermined “minimum 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 discussed.
Manipulation Check
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, meditators and control participants did not differ in duration of meditative 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 the Study?
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 individual. Experimental condition, week in the study, and their interaction were included as predictors. The model also included random effects for the intercept, which represented each participant’s level of positive emotions at baseline, and for the impact of week in the study, which represented each participant’s change in positive emotions over time. Both random effects were significant [intercept variance = 0.34, SE = 0.05, p < .0001; week variance = 0.002, SE = 0.0006, p = .0002], indicating that participants 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, Curran, & 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 study.
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Figure 2
Positive emotions by experimental condition.
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.
Table 2
Impact of Loving-Kindness Meditation on Specific Positive Emotions
EmotionExperimental conditionWeekExperimental condition × weekEstimateSEpEstimateSEpEstimateSEpAmusement−0.1120.125.37−0.0120.009.200.0400.014.003Awe−0.1630.123.19−0.00030.010.970.0460.014.001Contentment0.0360.120.76−0.0020.011.830.0430.016.006Gratitude−0.0100.141.940.00060.010.960.0350.014.01Hope−0.1390.127.28−0.0060.010.550.0440.015.003Interest−0.4210.136.002−0.0220.011.050.0600.016.0002Joy0.00050.124.997−0.0130.010.210.0370.014.01Love0.0600.134.66−0.0090.010.330.0360.014.009Pride−0.2490.1369.07−0.0160.010.150.0480.014.0008
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We tested an additional growth model that examined compassion over the duration of the study. Neither the main effects for experimental 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 meditation practice each week as a fixed effect, time-varying predictor, along with time and experimental condition. To allow us to examine 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 “meditation, 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 3.6
Table 3
Impact of Experimental Condition, Week, and Time Spent Meditating on Positive Emotions
PredictorEstimateSEpIntercept2.7170.075