Does your mindfulness benefit others? A systematic review and meta-analysis of the link between mindfulness and prosocial behaviour

Abstract

Mindfulness‐based meditation practices have received substantial scientific attention in recent years. Mindfulness has been shown to bring many psychological benefits to the individual, but much less is known about whether these benefits extend to others. This meta‐analysis reviewed the link between mindfulness – as both a personality variable and an intervention – and prosocial behaviour. A literature search produced 31 eligible studies (N = 17,241) and 73 effect sizes. Meta‐analyses were conducted using mixed‐effects structural equation models to examine pooled effects and potential moderators of these effects. We found a positive pooled effect between mindfulness and prosocial behaviour for both correlational (d = .73 CI 95% [0.51 to 0.96]) and intervention studies (d = .51 CI 95% [0.37 to 0.66]). For the latter, medium‐sized effects were obtained across varying meditation types and intensities, and across gender and age categories. Preliminary evidence is presented regarding potential mediators of these effects. Although we found that mindfulness is positively related to prosociality, further research is needed to examine the mediators of this link and the contexts in which it is most pronounced.

Full text

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Donald, J. N., Sahdra, B. K., Van Zanden, B., Johannes Duineveld, J., Atkins, P. W. B.,
Marshall, S., & Ciarrochi, J. (in press, accepted July 12, 2018). Does Your Mindfulness Benefit
Others? A Systematic Review and Meta-analysis of the Link between Mindfulness and Prosocial
Behavior. British Journal of Psychology.
Does Your Mindfulness Benefit Others? A Systematic Review and Meta-analysis of the Link
Between Mindfulness and Prosocial Behavior
Abstract
Mindfulness-based meditation practices have received substantial scientific attention in recent
years. Mindfulness has been shown to bring many psychological benefits to the individual, but
much less is known about whether these benefits extend to others. This meta-analysis reviewed
the link between mindfulness – as both a personality variable and an intervention – and prosocial
behavior. A literature search produced 31 eligible studies (N = 17,241) and 73 effect-sizes. Meta-
analyses were conducted using mixed-effects structural equation models to examine pooled effects
and potential moderators of these effects. We found a positive pooled effect between mindfulness
and prosocial behavior for both correlational (d = .73 CI 95% [.51 - .96]) and intervention studies
(d = .51 CI 95% [.37 - .66]). For the latter, medium-sized effects were obtained across varying
meditation-types and intensities, and across gender and age categories. Preliminary evidence is
presented regarding potential mediators of these effects. Although we found that mindfulness is
positively related to prosociality, further research is needed to examine the mediators of this link
and the contexts in which it is most pronounced.

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Interest in the psychological effects of meditation has increased rapidly in recent decades
(Sedlmeier et al., 2012). Meditation practices based on the cultivation of nonjudgmental awareness
– or mindfulness – have been at the forefront of this interest, originally in clinical contexts, but
more recently as an enabler of well-being and positive functioning among non-clinical populations
(Khoury, Sharma, Rush, & Fournier, 2015). Indeed, popular interest in mindfulness meditation is
now such that it represents a “billion-dollar business” serving millions of people around the world
(Wieczner, 2016).
Central to the appeal of so-called ‘modern’ mindfulness practices is their dissociation from
any particular belief system, arguably making them attractive to a broad spectrum of the population
in secular Western societies (Monteiro, Musten, & Compson, 2014). There is indeed an
accumulating body of evidence that mindfulness-based meditation practices provide a range of
benefits for the individual, including attenuations in depression and anxiety symptoms (Khoury et
al., 2013), and improvements in well-being and mental health (Keng, Smoski, & Robins, 2011;
Khoury et al., 2015), cognitive abilities (Chiesa, Calati, & Serretti, 2011) and physical health
(Keng et al., 2011).
However, in recent times, some have suggested that the benefits of the modern mindfulness
movement may be confined to the individual, particularly because secular mindfulness meditation
programs tend not to focus on moral or ethical elements of individuals’ choices or behaviour –
elements that were central to the traditions from which these meditative practices emerged
(Monteiro et al., 2014). If this is the case, the modern mindfulness movement may, paradoxically,
serve to reinforce individuals’ sense of self, rather than transcend it (Monteiro et al., 2014). In
contrast, the Eastern contemplative traditions, most notably various sects of Buddhism, which have
partly inspired the proliferation of mindfulness interventions in the West, have for millennia

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emphasized the links between the practice of mindfulness and the promotion of prosocial behaviors
(Dalai Lama and Ekman, 2008). A key question, then, is whether secular mindfulness supports the
enactment of prosocial behaviors, or whether the benefits of mindfulness are limited to the
individual. Recent narrative reviews indicate that mindfulness is indeed linked with various kinds
of prosocial behavior (e.g., Condon, 2017; Berry & Brown, 2017), but there is a need to more
systematically examine this emergent line of research.
The present paper provides a systematic review and a meta-analysis of the empirical
research on the links between mindfulness and prosocial behavior. We focus on mindfulness as
both a personality trait and an intervention, in an effort to provide a multi-method test of our
research question. A key advantage of examining links between mindfulness as a personality
construct and prosocial behavior is that we can explicitly measure mindfulness – and therefore
isolate its effects – in a way that is more difficult in intervention research, where mindfulness
meditation often also seek to cultivate prosocial emotions, personal values and intrinsic
motivations, and also vary considerably in their design and methods (Chiesa & Serretti, 2011;
Khoury et al., 2013). To test the directionality and causal relations between our two constructs of
interest, we then review findings from intervention studies in this research domain. For both
individual difference and intervention studies, we explore potential moderators of obtained effects,
and lastly examine potential mediating variables. Our overarching goal is to gather and evaluate
the relevant empirical studies in this rapidly developing field and provide evidence-based
recommendations for future research.
Mindfulness
Mindfulness has been defined as an open and nonjudgmental awareness of one’s present-
moment experience (Kabait-Zinn, 1992; Ryan & Brown, 2003). It describes a way of engaging

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with one’s experience, wherein one’s attention is directly oriented to sensations, thoughts and
emotions occurring moment-by-moment. This conceptualization of mindfulness, emanating from
Buddhist traditions, is different from other approaches to mindfulness, such as Langer’s version
(e.g, Langer, Bashnerr, & Chanowitz, 1985), where mindfulness is described as the process of
actively seeking out and generating novelty in one’s moment-by-moment experience. The latter
conceptualisation involves mental elaboration and sense-making in a way that Buddhist
conceptualisations of mindfulness do not (Chiesa, 2012; Siegling & Petrides, 2014).
Multiple measures of mindfulness derived from Buddhist philosophy have been
developed in recent years, each based on related but distinct conceptualisations of the construct
(for a review, see Siegling & Petrides, 2014). Differences in such measures largely pertain to the
dimensionality of mindfulness. For example, some scholars view mindfulness as a
unidimensional construct, characterised by an attention to and awareness of moment-by-moment
experience (Brown & Ryan, 2003). Others view mindfulness as a bi-dimensional construct,
distinguishing between attentional and affective components (e.g., Bishop et al., 2004;
Cardaciotto, Herbert, Forman, Moitra, & Farrow, 2008). Still others have operationalized
mindfulness as comprising multiple facets, such as observing, acting with awareness, describing
present-moment experience, non-judging and non-reactivity (Baer, Smith, Hopkins,
Krietemeyer, & Toney, 2006).
Despite these differences, there is evidence that all these measures of mindfulness
converge upon a common, underlying construct, broadly consistent with the Kabat-Zinn et al.
(1994) definition, and psychometrically distinct from Langer’s definition of the construct
(Siegling & Petrides, 2014). In the present review, we therefore included all such measures of
mindfulness, including single, bi-factor, and multi-faceted measures.

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Further, mindfulness has been studied as both a trait and a state. Trait mindfulness
describes a general disposition toward present-centred awareness and attention, while state
mindfulness relates to variations in states of present-centred awareness and attention (Brown &
Ryan, 2003). Whilst state and trait mindfulness are thus conceptually distinct, they are closely
related. Individuals who are high on trait mindfulness also tend to have higher levels of
mindfulness at any given moment in time. Several studies have found support for this, with trait
and state mindfulness typically correlated between .40 and .50 with one another (e.g., Brown &
Ryan, 2003; Tanay & Bernstein, 2013; Weinstein, Brown, & Ryan, 2009). In the present review,
we therefore included studies of both trait mindfulness (i.e., via correlational studies) and
interventions aimed to cultivate mindful states (i.e., via intervention studies).
In considering studies of mindfulness interventions and prosocial behavior, we included a
relatively broad range of mindfulness-based interventions. Mindfulness-based interventions have
developed in a relatively diverse way, with some focusing more narrowly on mindfulness (i.e.,
self-regulated attention, curiosity and acceptance of one’s moment-by-moment experience), and
others combining the teaching of mindfulness skills with the cultivation of prosocial emotions such
as kindness, empathy, and compassion (Galante, Galante, Bekkers, & Gallacher, 2014; Keng et
al., 2011). The latter type of intervention typically starts by training mindful attention and
acceptance of present-moment experience, before moving into the conscious cultivation of
prosocial emotions as a core focus of the intervention (see Galante et al., 2014 for a review). In
the present review, we included both types of studies (i.e., ‘mindfulness-only’ and ‘mindfulness-
plus-prosocial-emotion’), but report results for both study-types separately.
Prosocial behavior

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Prosociality is said to be a central feature of human adaptive success, as it fosters
cooperation and cohesion among groups (Fehr & Fischbacher, 2003). Prosocial behavior has been
defined as “voluntary behavior intended to benefit another” (Eisenberg, Fabes, & Spinrad, 2007,
p. 646). As such, prosocial behavior can be distinguished from affective responses to another’s
suffering such as empathic concern, as well as from cognitive responses such as the capacity to
take another’s perspective or appraisals of deservingness, which may or may not lead to actions
aimed at benefitting others (Eisenberg et al., 2007). Additionally, the motivation for the act is not
considered in determining whether a behavior is prosocial or not (Penner & Orom, 2010). Prosocial
behavior may be motivated by altruism, in which case the act is undertaken with no expectation of
personal reward (Eisenberg et al., 2007). However, in many cases, prosocial behavior may be
engendered from non-altruistic motivations such as conforming to norms or rules (Baumeister &
Bushman, 2007), adhering to one’s sense of fairness, or enhancing status and reputation (Eisenberg
et al., 2007). Finally, prosocial behavior is an act intended to benefit another: whether or not it
does provide the intended benefits, or any kind of benefit at all, is seen as irrelevant to classifying
an act as prosocial (Eisenberg et al., 2007).
How might mindfulness foster prosocial behavior?
Theories of how mindfulness operates have emerged from a relatively diverse body of
behavioral, cognitive and neuroscientific studies (for reviews see Gu, Strauss, Bond, & Cavanagh,
2015; Hölzel et al., 2011; and Vago & Silbersweig, 2012). There are a number of proposed
mechanisms by which mindfulness might increase prosociality. First, mindfulness might foster
prosocial behavior by increasing individuals’ capacity to sustain and direct attention (Condon,
2017). Studies have demonstrated that mindfulness training leads to increases in sustained
attention (for a review, see Chiesa et al., 2011). In social contexts, greater attentional capacities

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may increase the likelihood that an individual observes the needs of others, meaning they are more
likely to respond to them (Brown & Ryan, 2003; Condon, 2017).
Second, mindfulness practices are associated with greater awareness of bodily sensations,
or interoceptive awareness (Hölzel et al., 2011; Vago & Silbersweig, 2012). There is evidence that
meditation training increases activity in the insula, a brain region involved in interoceptive
awareness (Farb et al., 2007). The insula is also involved in processing others’ emotional
experiences (see Singer, Critchley, & Preuschoff, 2009 for a review), meaning that greater
interoceptive awareness may increase individuals’ awareness of the needs of others in the social
environment.
Third, mindfulness may change an individual’s affective experience. Cameron and
Fredrickson (2015) found that dispositional mindfulness was associated with more positive
emotions such as love/closeness, joy, gratitude, and interest; and fewer negative emotions such as
anger, fear, guilt and stress. These emotions were in-turn associated with, respectively, greater and
lesser self-reported helping behavior (Cameron & Fredrickson, 2015). There is also evidence that
meditators, relative to non-meditators, display the activation of neural networks associated with
prosocial emotions (Lutz, Brefczynski-Lewis, Johnstone, & Davidson, 2008).
Fourth, mindfulness may enhance affect regulation, meaning that the experience of
negative emotions, such as personal distress when faced with the suffering of another, are less
likely to inhibit compassionate and behaviorally flexible responses to such situations (Condon,
2017; Donald, Atkins, Parker, Christie, & Ryan, 2016), and individuals are more likely to respond
with inter-personal warmth and kindness (Fredrickson et al., 2008), and act in values-consistent
ways (Donald, Atkins, Parker, Christie, & Guo, 2016). Consistent with this, reductions in
emotional interference (assessed as the delay in reaction time after being presented with affective

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versus neutral pictures) have been shown to follow mindfulness training (Ortner et al., 2007).
Further, brain regions implicated in emotion regulation, including increased prefrontal cortical
activity, and reduced amygdala and threat-system activation, have been found to be positively
associated with dispositional mindfulness (Creswell, Way, Eisenberger, & Lieberman, 2007) and
meditation (Weng, Fox, Shackman, Stodola, et al., 2013). In-turn, affect-regulating behaviors such
as impulse control and modulating emotional states have been linked with prosocial behavior
across several studies (Eisenberg et al., 2007).
Fifth, mindfulness may enhance the expression of prosocial behavior by perceiving
thoughts as mental events rather than literal truths, meaning that judgements, assumptions and
biases are less likely to inhibit the expression of helping behavior (Condon, 2017). This process
has been described as “dereification” (Condon, 2017; Lutz et al., 2015), “reperceiving” (Shapiro,
Carlson, Astin, & Freedman, 2006), and “cognitive defusion” (Hayes et al., 1999). In support of
this, there is evidence that cognitive defusion predicts less avoidance behavior when facing
suffering, and a greater likelihood of approach behaviors, such as active coping and positive
reinterpretation (Donald, Atkins, Parker, Christie, & Guo, 2016).
Finally, it may be that mindfulness facilitates prosocial behavior by altering one’s sense of
self from a rigid entity that needs protecting, to one that is interdependent, flexible and non-
attached (Berry & Brown, 2017; Hölzel et al., 2011; Sahdra et al., 2016; Vago & Silbersweig,
2012). With less attachment to the self, individuals are more likely to respond helpfully to the
needs of others, including to out-group others (Berry & Brown, 2017). In support of this, studies
have shown that mindfulness is associated with less experiential attachment (Ciarrochi et al.,
2016), less defensiveness following threats to the self (Niemiec et al., 2010), and less inter-group
bias (Lueke & Gibson, 2015, 2016; Tincher, Lebois, & Barsalou, 2016).

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Despite considerable theorising, there has been relatively little empirical testing of the
possible mechanisms by which mindfulness might enhance prosociality. The present review
therefore sought to conduct a narrative review of the studies that measured mediators of the effects
of mindfulness interventions on prosocial behavior.
Moderators of the link between mindfulness and prosocial behavior
Modern approaches to meta-analytic techniques utilize moderation analyses to explain
potential sources of variation in effect sizes across studies (Borenstein, Hedges, Higgins, &
Rothstein, 2009). By understanding the variables that moderate the association of mindfulness with
prosocial behavior, mindfulness interventions can be targeted in a way that enhance their potential
impact on prosociality. We next consider moderators of both correlational and intervention studies.
Moderators of correlational effects
Measure of prosocial behavior. Self-report measures can be subject to social-desirability
and other biases, inflating correlations through the halo effects (Donaldson, Grant-Vallone, 2002).
Such effects may mean that mindfulness is more strongly linked to prosocial behavior when the
behavior is self-reported as opposed to rated by an observer.
Relationship with recipient of the prosocial act. There is substantial evidence that
individuals are more likely to help known others such as one’s mate, family member or a member
of one’s broader social network, than strangers, due to the ongoing nature of these relationships,
in which helping behaviors are mutually-beneficial (Maner & Gailliot, 2007). Based on this
theorizing, we might expect that mindfulness will have larger effects on helping behavior toward
known than unknown others. However, it may also be that mindfulness attenuates differences in
prosocial behavior toward known others and strangers. In support of this, mindfulness has also

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been shown to predict less inter-group bias (Berry et al., 2018; Lueke & Gibson, 2015, 2016;
Tincher et al., 2016).
Age. The capacity to take the perspective of others is a developmental process that is less
advanced among children and adolescents than adults (Kegan, 1982). It may be, therefore, that
mindfulness has differential effects on prosocial behavior for adolescents, emerging adults and
adults respectively. Indeed, some studies have shown relatively modest relations between
mindfulness and prosocial behavior among adolescents (Sahdra, Ciarrochi, Parker, Marshall, &
Heaven, 2015) and children (e.g., Flook, Goldberg, Pinger, & Davidson, 2015), while others have
found relatively large effects among adults (e.g., Geurtzen, Scholte, Engels, Tak, & Zundert, 2014;
Cameron & Fredrickson, 2015), as well as non-significant effects (e.g., Parent et al., 2010).
Gender. Research has shown that women are more likely to engage in prosocial acts than
men, though this may depend on the type of prosocial act (Espinosa & Kováˇ, 2015). Moreover,
some systematic reviews have found evidence of different effects of mindfulness interventions by
gender (e.g., Katz & Toner, 2013), while others have failed to find such gender differences (e.g.,
Sedlmeier et al., 2012). It is therefore important to consider whether mindfulness has differential
effects on prosociality in females and males.
Moderators of intervention effects
Type of mindfulness intervention. Our inclusive approach to studies of mindfulness
allowed us to examine differences in content across mindfulness-based interventions. A key
distinction in this regard is between mindfulness-based interventions that target other-oriented
positive emotions such as kindness, empathy, and compassion as their primary focus, and those
that target mindful-awareness of present-moment experience (Galante et al., 2014; Keng et al.,
2011). Because of their more direct focus on cultivating positive emotions toward others, other-

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focused compassion interventions may be more strongly predictive of prosocial behavior than
those targeting mindful-awareness alone (Weng, Fox, Shackman, & Stodola, 2013).
Intervention intensity. Mindfulness intervention research has developed in a diffuse way,
with a broad range of intervention formats, intensities and delivery-modes employed (for reviews,
see Chiesa & Serretti, 2011; Hofmann, Sawyer, Witt, & Oh, 2010; Khoury et al., 2013). In the
present context, there was considerable variation in the intensity of interventions studied, ranging
from brief, nine minute experimental inductions of mindfulness (e.g., Berry et al., 2018, Studies
2-4) to a month-long retreat (Montero-Marin, Puebla-Guedea, & Herrera-Mercadal, 2016). There
is meta-analytic evidence that intervention length makes a difference to the efficacy of mindfulness
interventions among healthy adults in relation to outcomes such as well-being, stress, anxiety and
depression (e.g., Khoury et al., 2015), while other meta-analyses have failed to find such effects
(Carmody & Baer, 2009). We therefore tested whether more intensive interventions had
differential effects upon prosociality relative to more brief interventions.
Type of control condition. Due to placebo effects, studies with waitlist controls are
expected to yield higher effect-sizes than those with specific and nonspecific active controls, and
there is evidence for this from mindfulness research across a range of outcome measures (for a
review, see Goyal et al., 2014). We therefore tested whether there were systematic differences in
effect-sizes between studies with waitlist controls, nonspecific active controls, and specific active
controls designed to serve as treatment-as-usual comparisons.
Randomization. Although non-randomization significantly limits the inferences that can
be drawn from an intervention study (Campbell & Stanley, 1966), we included both randomized
and non-randomized studies in this review, given the nascence of this field and the resultant value
in taking a maximally-inclusive approach. We conducted sensitivity analyses with non-

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randomized studies both included and excluded from the analysis and examined differences in
effect-sizes between both sets of studies.
The present study
The primary aim of the present study was to provide a meta-analytic review of the research
on the association between mindfulness and prosocial behavior. Based on the theoretical
arguments and the empirical evidence discussed above, our hypotheses were as follows:
Hypothesis 1: Trait mindfulness will be positively correlated with prosocial behavior.
Hypothesis 2: Mindfulness-based interventions will increase prosocial behavior.
Hypothesis 3: Mindfulness-based interventions that cultivate positive, other-oriented emotions
will have a larger effect on prosocial behavior than those that cultivate mindfulness alone.
Method
Eligibility criteria
To be included in this review, studies needed to meet the following criteria: 1) Include
quantitative, not qualitative, measures of mindfulness and prosocial behavior. 2) Measure
prosocial behavior either through self-report (e.g., individual reports of their own incidence of
prosocial acts) or through other-report (e.g., teacher or peer reports of students’ prosocial
behavior). Prosocial attitudes and emotions, such as empathic concern and perspective-taking were
not included as outcome measures in this review, as they do not measure observable prosocial
behavior. 3) Include either a manipulation or a quantitative measure of mindfulness. 4) Assess the
relations between mindfulness and prosocial behavior, including either an effect-size (e.g.,
Cohen’s d), sufficient information to calculate one, or have a corresponding author provide such
information upon request. 5) Use an experimental (i.e., randomized controlled trial), longitudinal,
or cross-sectional study design. Intervention studies with no control condition (i.e., case series

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designs) were excluded from the review because there is no way of knowing whether observed
effects are a result of the intervention or an unrelated process (Kempen, 2011). 6) Full-text access
available in English.
Literature search
Literature searches were conducted in the PubMed, EMBASE, CENTRAL, PsychINFO,
and ProQuest Psychology databases in September, 2017. Three sets of search terms were
combined: (1) ‘mindful’* (for mindfulness and mindful), ‘meditat’* (for meditation and
meditative) and ‘contemplative’; (2) ‘prosocial’, ‘altruis’* (for altruistic and altruism),
‘compassion’* (for compassion and compassionate), ‘help’* (for help and helping) and ‘care’; and,
to capture the focus of this paper on behavioral rather than cognitive or affective responses; (3)
‘behav’* (for behavior and behavioral, as well as their UK-spelling equivalents), ‘responding’,
‘response’ and ‘action’. This search produced 13,167 studies.
Study selection
Titles and abstracts of studies identified from the database searches were independently
screened for eligibility by two authors. This process resulted in 196 studies. The full-text versions
of the remaining studies were then screened by the same two authors for eligibility, and differences
of opinion were resolved by consultation with three experienced mindfulness researchers. This
resulted in the identification of 30 studies for inclusion.
As a secondary step, the corresponding authors of the studies identified from the database
searches were emailed, seeking additional contributions (including unpublished data), consistent
with the study’s eligibility criteria. We received responses from 9 authors (within the one-month
response window specified), resulting in an additional 3 studies that met our eligibility criteria
(Parent, McKee, Rough, & Forehand, 2016; Parent, McKee, Anton, et al., 2016; Schonert-Reichl

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et al., 2015). Lastly, the reference lists of the articles identified from the literature search were
inspected for any additional relevant articles. This did not yield any further studies for inclusion.
On 15 October, 2017, we concluded the literature search, with a total of 33 included studies.
Data extraction
Two researchers independently extracted data from the included studies. The following
data were extracted: (1) publication author(s) and year; (2) study design (cross-sectional,
longitudinal or experimental); (3) number of participants; (4) cell-sizes (if experimental); (5) mean
participant age and gender; (6) instrument used to measure or manipulate mindfulness; (7)
instrument used to measure prosocial behavior; and (8) the statistical result measuring the
relationship between mindfulness and prosocial behavior. There was 98% consistency between the
two raters. These data, except for the effect sizes, are included in Table 1 of Supplementary
Material. Effect sizes for all included studies are displayed in Figures 1 and 2, below. A description
of the measures of mindfulness, mindfulness-based interventions and prosocial behavior included
in this review also appears in Table 1 of Supplemental Material.
Summary measures
All summary measures were converted to Cohen’s d using Rosenthal’s (1994) and (1991)
conversion formulas. Cohen’s d effect sizes were defined as .2 (small), .5 (medium), and .8
(large). Cohen’s d effect sizes from correlational studies were derived from Pearson’s r
coefficients, while those from intervention studies were derived from an odds-ratio, an eta-
squared statistic, an adjusted mean difference score (i.e., in pretest-postest-control group designs;
Morris, 2008), or a post-test-only mean difference (i.e., where baseline scores on the outcome
variable were not measured, as in in laboratory studies of brief mindfulness-based interventions).
This way, all available information for calculating effect sizes was used. In calculating Cohen’s d

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from pre-test-post-test-control group designs, we used standard deviations for each condition,
combining both pre-test and post-test standard deviations, per the methods outlined in Rosenthal
(1991; 1994). Where a study did not report the information needed to convert relevant summary
measures to Cohen’s d, we contacted the lead author to request this information. The authors of
six studies were contacted in relation to a total of nine effects. Three authors provided the
required information for five of these effects within the four-week window that was specified.
Of the three remaining studies, one study reported two effects as standardized regression
coefficients (Cameron & Fredrickson, 2015), so could not be precisely converted to Cohen’s d.
Using the methods outlined by Peterson & Brown (2005), Pearson’s r correlations were imputed
for these effects and sensitivity analyses were conducted to test whether the inclusion of these
imputed statistics changed the results of the meta-analysis. There was no evidence that inclusion
of these two effects, which were correlational, significantly changed the pooled effect-size for
correlational studies, relative to a model where they were excluded from the analyses (Δχ² = 2.57,
p = .283). The imputed data were therefore included in the present analyses. Finally, there were
two remaining studies that did not report effects that could be used, and we were unable to obtain
the required information from the authors (Kemeny et al., 2012; Lueke & Gibson, 2016). These
studies were dropped from the meta-analysis. The final analysis consisted of 31 studies and 73
effects.
Risk of bias in individual studies
To assess the risk of bias in studies using both experimental and cross-sectional designs,
the Strengthening the Reporting of Observational Studies in Epidemiology (von Elm et al., 2008)
guide and the Consolidated Standards of Reporting Trials (Schulz, Altman & Moher, 2010), or
CONSORT, statement were adapted. The risk of bias criteria included (a) description of participant

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eligibility criteria, (b) random allocation of study participants (intervention studies), (c) among
correlational studies, a psychometrically valid assessment of mindfulness (i.e., at least one
published study supporting reliability and validity of the instrument), (d) a psychometrically valid
assessment of prosocial behaviour, (d) valid assessment of prosocial behavior, (e) power
calculation reported and study adequately powered to detect hypothesized relations, and (f)
relevant covariates included in the analyses.
Two researchers independently rated studies on each of the above criteria, assigning either
a 1 (present and explicitly described) or a 0 (absent or inadequately described) to each. Ratings
were consistent between raters in 221 of the 234 cases. The 13 discrepancies were resolved by
discussion between the two researchers. Studies that met less than half of the criteria were
considered to have a high risk of bias (Higgins et al., 2011). Studies that met at least half of the
criteria were deemed as having a low risk of bias implying that results represent unbiased estimates
of the true effect (Higgins et al., 2011).
Meta-analytic procedures
We used a multi-level structural equation modelling approach to meta-analysis (see
Cheung, 2014, for an introduction to this method). This approach allows the researcher to fit
models with dependent effect sizes nested within studies (for example, multiple comparisons
within an experimental study, or multiple correlation coefficients within a cross-sectional study),
using latent variables (see Cheung, 2014). To do this, Level 2 (effect sizes within-study) as well
as Level 3 (between-study) sources of variance are estimated, using a structural equation
modelling (SEM) approach. In the SEM, studies are treated as ‘individuals’ and effect sizes are
treated as non-independent ‘variables’, thereby enabling nonindependence to be explicitly
estimated in the model (Cheung, 2014). A key advantage of this approach is that it enables the

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17
use of all available information from non-independent effect sizes within studies, in contrast to
many alternative approaches to handling dependence in meta-analyses, in which information is
lost (Ahn, Ames, & Myers, 2012; Cheung, 2014). Other notable advantages of this approach
include: handling missing covariates using the full information maximum likelihood approach,
rather than less precise ad-hoc approaches; placing flexible constraints on parameters; and
constructing more accurate confidence intervals using likelihood-based approaches (Cheung,
2014).
To estimate the degree of ‘true’ heterogeneity in pooled effect sizes, as opposed to variation
due to sampling error, the I2 statistic was used (Borenstein et al., 2009). As a rule of thumb, 25%,
50%, and 75% have been identified as low, medium, and high levels of heterogeneity respectively
(Higgins & Thompson, 2002). Following similar approaches elsewhere, moderation analysis was
conducted where I2 > 25%, and with a minimum of 4 effect sizes (Fu et al., 2011). For
completeness, we also report the τ statistic, which is the variance in effect sizes at the population
level (Cheung, 2015). For each moderation analysis, we calculated the proportion of variance
explained by the inclusion of the moderating variable (R2) and the chi-squared test of whether the
moderated model differed significantly from the model excluding the moderator (Borenstein et al.,
2009; Cheung, 2014). Because we modelled within-study and between-study sources of variation
separately, we report moderation (R2) and heterogeneity statistics (I2 and τ) for each level of
analysis.
To ensure that effects based on a relatively large sample had a greater influence on pooled
effects, effect sizes were weighted using the reciprocal of each effect’s sampling variance. We
utilized a three-level approach, which includes a random-effects component, a between-study fixed
effects component, and a within-study fixed effects component (Cheung, 2014).

MINDFULNESS AND PROSOCIAL BEHAVIOR
18
All analyses were conducted in R Version 3.1.2 (R Core Team, 2016) and meta-analyses
were conducted using the metaSEM package (Cheung, 2015). Unconditional mixed-effects
structural equation models were used to calculate the overall pooled effect size (pooled Cohen’s
d). For each pooled effect, 95% confidence intervals were calculated using a likelihood-based
approach (Cheung, 2014).
Results
Study characteristics
Of the 31 studies included in the meta-analysis, there were 12 correlational (n = 13,820)
and 21 intervention studies (n = 3,421), with a total of 17,241 participants.
1
Of the 12 correlational
studies, 10 were published and two were dissertations (McGarvey, 2010; Weltfreid, 2016). Of the
21 intervention studies, 18 were published, two were unpublished conference papers (Frost, 2016;
Reb, Junjie, & Narayanan, 2010), and one was a dissertation (Taylor, 2016). Nineteen out of the
21 intervention studies used a randomized controlled design, while two studies used a non-
randomized matched controlled design (McCall, Steinbeis, Ricard, & Singer, 2014; Montero-
Marin, et al., 2016). The interventions used can be classified into mindfulness-plus-prosocial-
emotions interventions (k = 9) and mindfulness-only interventions (k = 13).
2
Mindfulness-plus-
prosocial-emotions interventions ranged in length from 6 (Leiberg et al., 2011) to 36 hours (Taylor
et al., 2016). Mindfulness-only interventions ranged from 5-10 minutes (Berry et al., 2018;
Ridderinkhof, de Bruin, Brummelman, & Bögels, 2017) to 224 hours (Montero-Marin et al., 2016).
Control conditions for the 21 interventions studies were waitlist (k = 8), nonspecific active (k = 6)
and specific active (k = 7). The nonspecific active control interventions were goal-setting training
1
Two papers included both correlational and intervention studies, meaning they were counted twice in this
calculation (Berry et al., unpublished data; Ridderinkhof et al., 2017).
2
One study (Condon et al., 2013) included both a mindfulness-only and a compassion-focused intervention,
meaning it was counted twice in these calculations.

MINDFULNESS AND PROSOCIAL BEHAVIOR
19
(k = 2), memory training (k = 2) a mental imagery exercise (k = 1) and a writing task (k = 1).
Specific active controls were cognitive reappraisal training (k = 2), relaxation exercises (k = 2),
social responsibility training (k = 1), giving a speech on civic service (k = 1) and light exercise
training (k = 1). Study characteristics are summarised in Table 1 of the Supplemental Material.
Risk of bias and publication bias
Risk of bias assessment was conducted by study (n = 31). There was 98%
agreement between the two raters on risk of bias ratings, and all discrepancies were resolved by
discussion between the two raters. Six studies were rated as having a high risk of bias and 25
studies were rated as having a low risk of bias. Risk of bias did not moderate pooled effects for
either correlational (Δχ² = 1.34, p = .249, R2 = .09) or intervention studies (Δχ² = .72, p = .390, R2
= .12). Further, we assessed publication bias across studies using funnel plots, Egger’s test,
testing moderation by publication status, and moderation by the standard errors of effect sizes.
We found no evidence of publication bias for correlational studies, but some evidence among
intervention studies. Although several contemporary approaches to assessing publication bias
have been proposed, such as such as p-curve, p-uniform, PET-PEESE, 3PSM (for reviews, see
Carter, Schönbrodt, Hilgard, & Gervais, 2018; and McShane, Böckenholt, & Hansen, 2016), a
key advantage of the moderation tests we undertook is that they do not assume independence
among effect sizes, which was a significant issue in the data included in this review. The
complete results of the risk of bias and publication bias assessments are reported in Supplemental
Material.
Main analysis
Next, we ran an unconditional multilevel model and found support for both Hypotheses 1
and 2. As displayed in Table 1, dispositional mindfulness was positively associated with prosocial

MINDFULNESS AND PROSOCIAL BEHAVIOR
20
behavior, with a medium-to-large effect size (d = .73 CI 95% [.51 - .96]), using the criteria
proposed by Cohen (1991). Further, as shown in Table 2, mindfulness-based interventions
predicted greater prosocial behavior, with a medium-sized pooled effect (d = .51 CI 95% [.37 -
.66]). These effect sizes were not statistically different from one another (d = .14, SE = .11, CI [-
.06, .35]).
Correlational effects
Individual study effect-sizes, along with pooled effect-sizes, are shown in Figure 1(a). As
the figure shows, there was consistency among effects, with all but three effects larger than zero
at the 95% CI level. There was a moderate level of heterogeneity across effects for the 12
correlational studies (I2 = .51), indicating that exploring potential moderators of these effects was
warranted (see Table 1)..
[INSERT TABLE 1 ABOUT HERE]
Measure of prosocial behavior. We found some support for the proposition that self-
reports of prosociality are larger than observer-ratings (Donaldson, Grant-Vallone, 2002), with
differences in the way prosocial behavior was measured moderating the association between
mindfulness and prosocial behavior but at the p < .10 level (Δχ² = 2.99; p < .08; R²_3 = 53%). As
shown in Table 1, mindfulness had a small-to-medium association with other-report measures of
prosocial behavior (d = .37, 95% CI [.19, .79]) and a large association with self-report measures
of prosociality (d = .89, 95% CI [.80, .98]), and the confidence intervals around these estimates
did not overlap.
Recipient of prosocial behavior. We next tested whether mindfulness was more strongly
related to prosocial behavior when the recipient of the prosocial act was known as opposed to
being a stranger and found support for this (Δχ² = 4.11; p < .05; R² = 46%). As Table 1 shows, the

MINDFULNESS AND PROSOCIAL BEHAVIOR
21
association between mindfulness and prosociality was large when the recipient was a known
person (d = .91, 95% CI [.76, 1.05]), and small-to-medium when they were a stranger (d = .38,
95% CI [.13, .63]). The 95% confidence intervals around these estimates did not overlap,
suggesting that replication studies would find a similar difference, with a relatively high likelihood
(Cumming & Maillardet, 2006). To explore the possibility that differences in helping behaviour
toward known versus unknown recipients were an artefact of the way in which prosocial behaviour
was measured (i.e., self- versus other-reports), we conducted supplementary analyses, with self-
report measures of prosociality included in the model as a secondary moderator. However, we did
not find evidence for this (Δχ² = 1.48; p = .223; R² difference = .171).
Age. Differences in subjects’ age moderated the relations between trait mindfulness and
prosocial behavior (Δχ² = 4.56; p < .05; R² = 77%). We found small effects for adolescents (d = .24,
95% CI [.01, .47]), medium-sized effects for emerging adults (d = .66, 95% CI [.55, .78]), and
large effects for adults (d = .94, 95% CI [.76, 1.12]).
3
Gender. In contrast with meta-analytic evidence that gender moderates the link between
mindfulness and other outcomes (e.g., Katz & Toner, 2013), and as shown in Table 1, we did not
find evidence for this in relation to prosocial behavior.
[INSERT FIGURE 1 ABOUT HERE]
Intervention effects
We found support for our second hypothesis, with a medium-sized pooled effect of
mindfulness interventions predicting increases in prosocial behavior, relative to controls. Figure
1(b) illustrates the effect sizes, and confidence intervals around each, for these studies.
3
There were no studies of trait mindfulness among pre-adolescents included in the review.

MINDFULNESS AND PROSOCIAL BEHAVIOR
22
We next tested our third hypothesis, that interventions that explicitly trained prosocial
emotions in addition to mindfulness would have larger effects on prosociality than those that
trained mindfulness alone. As shown in Table 2, effect-sizes from studies of these two
intervention-types were both medium-sized and non-different from one another. To test whether
these differences in intervention emphases lead to different effects on prosocial behavior, we
conducted sensitivity analyses with the mindfulness-plus-prosocial-emotions interventions (k = 9)
excluded from the analyses. The difference between the two models was non-significant (Δχ² =
0.095, p = .948, ΔR2 = .001), suggesting that combining the two intervention-types in subsequent
moderation analyses was warranted.
[INSERT TABLE 2 ABOUT HERE]
Table 2 shows that there was moderate heterogeneity associated with the pooled effect
between intervention studies (I2_3 = .53). Further, there was moderate heterogeneity associated
with the pooled effect across the ‘mindfulness-only’ studies (I2_3 = .63), but not between the
‘mindfulness-plus’ studies (I2_2 = .00). To be conservative, we conducted moderation analyses on
both intervention types combined, as it is possible that study samples were not representative of
the overall population, meaning that a low I2 statistic does not rule out the possibility that variation
in effects can be explained by third variables (Borenstein et al., 2009).
Results from the moderation analyses are presented in Table 2. We did not find evidence
that any of the variables we tested moderated intervention effects. Instead, we found consistent,
medium-sized effects of mindfulness interventions on prosociality across recipient relationship,
gender, age categories, intervention intensity, and type of control condition.
Mediation effects

MINDFULNESS AND PROSOCIAL BEHAVIOR
23
We identified five mindfulness studies that examined potential mechanisms of change. Lim
et al. (2015) tested for but did not find differences in empathic accuracy between individuals who
completed a three-week online mindfulness meditation program and those who undertook a
cognitive training program with the same format, suggesting that empathic accuracy could not be
a mediator of the effect of mindfulness meditation on prosociality (Lim et al., 2015). In another
study, Montero-Marin et al. (2016) tested whether individual differences in nonattachment
mediated the effect of a one-month Vipassana retreat on self-reported cooperativeness, but
similarly did not find support for this.
Most recently, Berry et al. (2018; Studies 2-4) tested the role of empathic concern, a
construct closely related to compassion, as a mediator of the effect of mindfulness meditation on
prosociality. Across three studies, the authors found that brief (9 minutes) mindfulness meditation
enhanced prosocial responding, and that these effects were consistently mediated by empathic
concern.
A further two studies of interventions combining mindfulness and prosocial emotions
examined potential mechanisms of change. Weng et al. (2013) found that increases in altruistic
behavior following mindfulness-based compassion meditation were associated with the activation
of neural networks associated with understanding others’ affective states, executive function and
the experience of positive emotions. Further, Reb et al. (2015) found that increases in altruistic
behavior following loving-kindness meditation was completely accounted for by increases in
positive affect.
Discussion
Relatively little is known about whether and how mindfulness – as both a personality
variable and as a meditative practice – enhances prosocial behavior. This review is timely, given

MINDFULNESS AND PROSOCIAL BEHAVIOR
24
recent debates about whether or not secular mindfulness supports the cultivation of ethical
behavior (e.g., Monteiro et al., 2014), and increasing research interest in the interpersonal effects
of mindfulness practice (see Berry & Brown, 2017; Condon, 2017).
We found support for our hypotheses that individual differences in mindfulness would be
linked to greater prosocial behavior (H1), and that mindfulness interventions would predict
increases in helping behaviors (H2). These effects were medium-sized, non-different from one
another, and provide converging, multi-method evidence for the links between mindfulness and
prosociality. In relation to our first hypothesis, our findings suggest that by having a non-
judgmentally aware disposition toward one’s experience, individuals are more likely to respond to
the needs of others in helpful ways. Preliminary mediation analysis indicates that this may happen
via increases in empathic concern, emotion regulation and positive affect.
Results from our moderation analyses provide a number of insights regarding the links
between trait mindfulness and helping behavior. First, we found that that mindfulness positively
correlated with both self- and other-reports of prosociality. Second, we found that trait
mindfulness was associated with more helping behavior toward known than unknown others, but
that both effects were positive and greater than zero. Notably, we did not find evidence that these
differences were an artefact of the way in which prosocial behaviour was measured (i.e., self-
versus other-reports). Our findings suggest that mindfulness may reinforce differences in
cooperation toward kin versus strangers that are consistently displayed by humans (Maner &
Gailliot, 2007). However, intriguingly, these findings run counter to a recent body of research
suggesting that mindfulness meditation serves to inhibit intergroup biases (Berry et al., 2018;
Lueke & Gibson, 2015, 2016; Tincher et al., 2016). Possible reasons for this are discussed below.

MINDFULNESS AND PROSOCIAL BEHAVIOR
25
Third, we found evidence that mindfulness was most strongly linked to prosociality among
adults as compared to emerging adults and adolescents. This finding is consistent with the idea
that perspective-taking ability develops with age and is more advanced among adults than children
(Kegan, 1982). However, it is notable that the mindfulness – prosociality link was positive for all
age-categories.
Regarding the links between mindfulness interventions and prosociality, we did not find
support for our third and final prediction (H3) that mindfulness interventions that focus on the
cultivation of prosocial emotions would have a larger effect on helping behavior than those that
focus only on cultivating mindful awareness. This suggests that mindfulness by itself is sufficient
to produce increases in helping behavior, and that there may not be benefits (in terms of prosocial
behavior) in combining positive, other-oriented emotions with mindfulness, beyond those
generated by training mindfulness alone. This explanation is consistent with results from the
correlational analyses, suggesting that non-judgmental awareness alone (measured using
instruments such as the Mindful Attention Awareness Scale, Brown & Ryan, 2003; and the Five
Facets of Mindfulness Questionnaire, Baer et al., 2006) fosters prosocial responding to another’s
suffering. More research is needed, however, to more robustly test this preliminary finding, for
example, by using more tightly controlled experimental designs.
Our review of mediation results from mindfulness intervention studies suggests that
mindfulness meditation enhances prosocial behaviors via increases in empathic concern – also
commonly studied as compassion (Goetz, Keltner, & Simon-Thomas, 2010) – and that
mindfulness-based compassion meditation may increase prosociality via greater emotion
regulation and positive affect. Although very little research has examined possible mediators of
the link between mindfulness interventions and prosociality, the evidence to-date does not support

MINDFULNESS AND PROSOCIAL BEHAVIOR
26
the role of more cognitive factors such as empathic accuracy in mediating the effects of
mindfulness meditation on prosociality (Lim et al., 2015).
Regarding moderators of intervention effects, we did not find differences in effect-sizes
between known and unknown recipients of helping behavior. This contrasts with findings from the
correlational studies, where differences ran along expected lines – with larger effects for known
relative to unknown others. It may be that the practice of mindfulness leads to states of mind that
are able to overcome intergroup biases, and there is a body of experimental evidence to support
this (Berry et al., 2018; Lueke & Gibson, 2016; Tincher et al., 2016). However, these experimental
effects are for measures that immediately followed mindfulness meditation. It may be, therefore,
that the effects of mindfulness meditation on intergroup biases is relatively short-lived, explaining
why they are not reflected across studies of trait mindfulness and prosociality. Further research is
needed to explore how mindfulness meditation influences prosociality toward known and
unknown others over time.
Consistent with findings from correlational studies, effect-sizes appeared larger for self-
than observer-report measures of prosociality, though these differences were not significant among
the intervention studies. Further, we did not find evidence that age or gender moderated
intervention effects. Instead, we found medium-sized effects across age and gender categories,
suggesting that mindfulness meditation facilitates prosocial responding across a spectrum of
individuals and helper-receiver relations.
We did not find evidence that variables relating to study design, namely intervention
intensity, type of control used, or randomization, moderated intervention effects. The results
regarding intervention intensity are surprising, as they suggest that relatively brief interventions
(i.e., less than 1 hour in duration) have similar-sized effects on prosociality as multi-session

MINDFULNESS AND PROSOCIAL BEHAVIOR
27
interventions lasting between 1 and 10 hours, up to a one-month intensive retreat (Montero-Marin,
Puebla-Guedea, & Herrera-Mercadal, 2016). It is likely that third variables, such as length of
follow up (i.e., longer treatments have longer follow-ups, which allows the mindfulness effects to
wear off), or variation in the sensitivity of the dependent variables across studies, account for these
results. Future research could explore whether this is the case.
Lastly, we found some evidence of publication bias among intervention studies. While
every effort was made to include null and unpublished data in this analysis, including by emailing
authors, searching abstracts, and consulting reference lists of included studies, we cannot rule out
the possibility that the effects for intervention studies may have been subject to the file-drawer
problem. Further intervention research in this domain should aim to adhere to research best
practice, including by publishing or registering intervention protocols ex-ante, and using
manualised protocols.
Limitations
Although this review used state-of-the-art meta-analytic methods, the nascence of this
research domain and diversity among included studies resulted in several limitations. First, it is
possible that non-significant effects were due to a lack of statistical power. Meta-analyses
generally substantially increase statistical power, especially where individual studies have
relatively low sample sizes and the number of studies included in the meta-analysis is large
(Borenstein et al., 2009). Further, in random-effects meta-analysis, the method used here, when
between-study variation is relatively low, the reduction in power due to random effects is minimal
(Borenstein et al., 2009). In the present study between-study variance was moderate for both
correlational (I²_3 = .51) and intervention studies (I²_3 = .53). Moreover, for the intervention
studies, where no evidence of moderation was found, power to detect actual effects of d = .30 was

MINDFULNESS AND PROSOCIAL BEHAVIOR
28
greater than 95% (assuming a sample-size of n = 25 per condition). A lack of power to detect actual
effects was therefore unlikely in this review. However, due to insufficient cell size, we were unable
to test the possibility that multiple moderating variables (e.g., measure of prosocial behavior,
relationship to the recipient, and age) combined in distinct ways to predict prosocial behavior.
A second limitation is that for nearly all studies included in this review, there was no
evidence provided that the sample was representative of the broader population from which the
sample was drawn. Third, and more specific to the present review, there was substantial diversity
in the mindfulness interventions included in this review. This diversity limits the inferences that
can be drawn from the pooled effects reported here.
Third, this review was not able to resolve the extent to which high levels of mindfulness,
versus increases in mindfulness, leads to more prosocial behaviour. This issue has been recently
highlighted as being generally overlooked in social psychology (Bless & Burger, 2016).
Experimental manipulations of mindfulness may lead to relatively high mindfulness, and this
may in turn cause prosocial behaviour. This is often the assumption of research studies in this
area. However, it may be that changes in mindfulness, rather than high levels of mindfulness lead
to prosocial outcomes. For example, increases in nonjudgmental awareness may signal safety
and the likelihood of social reward, which leads to prosocial behaviour – similar to findings from
studies of positive mood (Schwarz & Clore, 1983). Whilst teasing apart these different sources of
change in prosocial behaviour was beyond the scope of this review, Bless & Burger (2016)
suggest several ways of exploring this, including via pre-post measures of the independent
variable in an experiment (to isolate change effects), correlational analysis (to isolate level-
effects) and the use of longitudinal designs (to identify both level- and change-effects).
Conclusion

MINDFULNESS AND PROSOCIAL BEHAVIOR
29
We found converging, multi-method evidence for theoretical claims that mindfulness
increases the incidence of prosocial acts toward others, with medium-sized pooled effects for both
correlational and intervention studies. Interventions that trained mindfulness as their sole focus
had similar-sized effects on prosocial responding as those that combined mindfulness with
prosocial emotions, suggesting that non-judgmental awareness alone fosters helping behavior to a
similar degree as compassion-oriented meditation. Evidence to-date suggests that these effects
may occur via greater empathic concern, emotion regulation and positive affect. Lastly, we found
that mindfulness interventions had similar-sized effects on prosociality toward known and
unknown others, in-line with an emerging body evidence that mindfulness mediation reduces
intergroup biases. The results of the present review suggest that mindfulness fosters ethical and
cooperative behavior across a range of individual-difference and inter-personal contexts.

MINDFULNESS AND PROSOCIAL BEHAVIOR
30
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Figure 1(a). Forest plot showing effect sizes and 95% confidence intervals for each correlational
study plus pooled effects. Note. ES = effect-size.

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Figure 1(b). Forest plot showing effect sizes and 95% confidence intervals for each intervention
study plus pooled effects. Note. ES = effect-size.

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Table 1
Results of the Meta-Analysis and Moderator Analyses for Correlational Studies
95%
CI
ANOVA
Variable
k
#ES
n
d
Lower
Upper
I²_2
I²_3
Q-stat
Δχ²
R²_2
R²_3
Overall relationship
12
32
13,820
.73***
.51
.96
0.46
0.51
895.03
Measure of prosocial behavior
2.99†
0%
53%
Self-report
10
25
13,018
.89***
.80
.98
0.97
0.00
748.07
Observer-report
2
7
802
.37***
.19
.79
0.00
0.78
29.13
Relationship with
recipient
4.11*
0%
75%
Known person
6
20
11,695
.91***
.76
1.05
0.97
0.00
628.94
Stranger
3
8
1081
.38***
.13
.63
0.00
0.73
29.88
Age
4.56*
0%
77%
Adolescence (12-18)
2
4
753
.24***
.01
.47
0.18
0.43
10.25
Emerging adult (18-
25)
2
5
528
.66***
.55
.78
0.00
0.00
0.65
Adult (25+)
7
22
12259
.94***
.76
1.12
0.97
0.00
682.9
Gender
0.64
0%
0%

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45
Mixed gender (33%-
66%)
8
22
7575
.67***
.41
.92
0.47
0.49
588.56
Majority female
(66%+)
7
16
6245
.87***
.45
1.28
0.52
0.46
305.65
Note. k = number of studies; #ES = effect size; n = number of participants; d = Cohen’s d; I²_2 = non-error heterogeneity within studies; I²_3
= non-error heterogeneity between studies; R²_2 = Explained variance within studies; R²_3 = Explained variance between studies. † p < .10,
* p < .05, *** p < .001. ‘Mindfulness-only’ = interventions that solely train mindfulness; ‘Mindfulness-plus’ = Interventions that train both
mindfulness and prosocial emotions.

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Table 2
Results of the Meta-Analysis and Moderator Analyses for Intervention Studies
95% CI
ANOVA
Variable
k
#ES
n
d
Lower
Upper
I²_2
I²_3
Q-stat
Δχ²
R²_2
R²_3
Intervention studies
21
41
3,421
.51***
.37
.66
.00
.53
82.94
Intervention type
0.94
0%
0%
Mindfulness-only
13
30
2,834
.53***
.33
.72
.00
.63
72.71
Mindfulness-plus
9
11
587
.51***
.32
.69
.00
.00
10.22
Measure of prosocial behavior
0.61
0%
2%
Self-report
5
6
264
.61***
.35
.88
.00
.00
5.96
Observer-report
17
35
3157
.48***
.32
.64
.00
.55
76.35
Relationship with
recipient
0.25
37%
0%
Known person
5
10
722
.49***
.22
.79
.00
.09
11.69
Stranger
14
28
2577
.49***
.33
.66
.00
.58
65.52
Age
1.92
0%
21%
Childhood (< 12)
2
7
631
.55***
.39
.71
.00
.00
7.03
Adolescence (12-18)
3
8
708
.34***
.13
.56
.00
.28
9.28
Emerging adult (18-
25)
5
13
1028
.43***
.36
.50
.00
.21
12.79
Adult (25+)
8
9
736
.68***
.37
1.00
.00
.59
22.8

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47
Note. k = number of studies; #ES = effect size; n = number of participants; d = Cohen’s d; I²_2 = non-error heterogeneity within studies; I²_3
= non-error heterogeneity between studies; R²_2 = Explained variance within studies; R²_3 = Explained variance between studies. *** p <
.001. ‘Mindfulness-only’ = interventions that solely train mindfulness; ‘Mindfulness-plus’ = Interventions that train both mindfulness and
prosocial emotions.
Gender
0.14
0%
0%
Mixed gender (33-
66%)
10
21
1995
.52***
.27
.77
.00
.69
68.34
Majority female
(66%+)
7
15
1108
.54***
.48
.61
.00
.00
13.47
Intervention intensity
0.01
0%
0%
Less than 1 hour
6
18
2033
.54***
.25
.82
.00
.74
59.04
1-10 hours
7
13
1034
.51***
.34
.69
.06
.04
13.32
More than 10 hours
7
9
321
.55***
.30
.81
.00
.00
10.21
Control condition type
0.30
0%
0%
Waitlist
10
15
832
.40***
.23
.57
.00
.00
13.95
Non-specific active
7
14
1582
.52***
.25
.78
.00
.72
51.8
Specific active
7
12
1007
.53***
.36
.71
.00
.24
13.83
Allocation to condition
0.07
0%
2%
Non-randomized
4
5
226
.40***
.38
.83
.57
.00
11.8
Randomized
17
36
3195
.53***
.37
.68
.00
.52
70.38

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48