The Quiet Ego: A Meta-Analytical Review

The QE construct stands at the crossroad of four mutually enriching characteristics: inclusive identity, perspective-taking, detached awareness, and growth-mindedness (Bauer & Wayment, 2008). In combination, the QE characteristics are theorized to generate a self that embraces two primary aspects: balance and growth. Balance, primarily facilitated by perspective-taking and inclusive identification, involves weighing individual and collective concerns. Growth, primarily facilitated by detached awareness and a growth mindset, emphasizes psychosocial development in the long run. Together, these features are expected to yield an attitude that consistently considers not only one’s own social, personal and developmental concerns but also those of others, thereby promoting healthy psychosocial integration (Wayment & Bauer, 2017, 2018; Wayment et al., 2014, 2018).

To assess the QE, Wayment et al. (2014) introduced the Quiet Ego Scale (QES). This is a 14-item questionnaire (rated on a scale ranging from 1 = strongly disagree to 5 = strongly agree) that produces a single score, with higher scores indicating stronger QE characteristics. The QES encompasses all four characteristics of QE. The QE characteristic inclusive identity measures the extent to which individuals feel a sense of belonging to all living beings. Sample items include “I feel a connection to all living things.” Perspective-taking encompasses the ability to transcend one’s own reality, to see the world through the eyes of others, and to feel compassion for them. Sample items include “Before criticizing somebody, I try to imagine how I would feel if I were in their place.” Detached awareness reflects a form of attention rooted in the present moment, leading to a more open-minded and less-judgmental approach towards oneself and others. Sample items include “I find myself doing things without paying much attention” (Reversed). Finally, growth-mindedness is characterized by a striving for a psychosocially meaningful development over time. Sample items include “I think it’s important to have new experiences that challenge how you think about yourself and the world” (Wayment et al., 2014). All studies in this meta-analysis used the full 14-item QES, except for one, which employed a four-item version from the scale’s preliminary phase. This shorter version also covered all four QE characteristics and demonstrated high convergence with the full scale (Wayment et al., 2018). To our knowledge, no other instruments comprehensively measure the higher-order QE construct.

Psychosocial functioning is a multifaceted concept that refers to how individuals manage their internal (psychological) and external (social) worlds, with outcomes ranging from psychopathology to human flourishing. Impairments in psychosocial functioning, such as poor self-regulation, unstable relationships, or a lack of self-worth, play a key role in diagnosing mental health disorders (e.g., American Psychiatric Association, 2022; Ro & Clark, 2009; World Health Organization, 2016). In contrast, optimal psychosocial functioning involves positive elements that enable individuals and communities to flourish, a term closely tied to the "good life" (e.g., Seligman, 2011; Seligman & Csikszentmihalyi, 2000). The definition of the "good life", however, has evolved over time. Traditional self-centered views, rooted in philosophical traditions such as hedonism and eudaimonia, frame the good life either as the pursuit of pleasure, satisfaction, and happiness or as a personally meaningful, engaging, and purposeful existence, respectively (Ryan & Deci, 2001). Contemporary perspectives on human flourishing have broadened to include intersystemic dimensions. For instance, Rusk and Waters (2015) propose a psycho-social systems approach to cultivating well-being, which also includes virtues and relationships (e.g., ethics, prosocial behavior). Likewise, Christen et al. (2017) or Lee and Mayor (2023) emphasize the importance of a good life that also aligns with the well-being of societies and the planet. Thus, from an intersystemic perspective, psychosocial functioning involves both positive and negative indicators with implications not only for personal well-being but also for societal and environmental well-being.

The VOA framework proposed by Bauer (2021) provides a valuable lens for operationalizing psychosocial functioning within an intersystemic understanding of human flourishing. It distinguishes three value facets. Value orientation refers to desires (e.g., values, motives, needs, aspirations, goals, attitudes, preferences, etc.) that orient a person’s thoughts, emotions, or behaviors. Value actualization is the lived expression of these orientations, including value perspectivity and value fulfillment. Value perspectivity refers to practical wisdom (e.g., internal psychosocial resources, skills or abilities) reflecting how individuals manage their thoughts, emotions, or behaviors wisely or think in complex and coherent ways about concerns of the self and others. Value fulfillment refers to well-being, including hedonic or eudaimonic elements, indicating one’s individual sense of satisfaction or meaningfulness in life. Within VOA, human flourishing is conceptualized as the culmination of coherent value facets leading to the manifestation of personally meaningful goods within a psychosocial context. For example, a person may hold a desire to promote tolerance (value orientation) and succeed in living according to this value (value fulfillment), which may lead to experiences of pleasure or purpose. However, the depth and complexity with which this value is approached (i.e., value perspectivity) play a crucial role. A simplistic stance such as “People can do what they want as long as it doesn’t affect me” may fall short of promoting intersystemic human flourishing, in contrast to a more reflective and engaged stance that involves recognizing injustice and advocating for equal treatment (for more information, see Bauer, 2021).

The egotism-transcending features of the QE are rooted in several psychological domains, including, among others, social and developmental psychology (Bauer & Wayment, 2008). Demographic backgrounds shape individuals’ psychosocial realities and may, in turn, influence how QE is associated with various aspects of psychosocial functioning. To better understand the construct’s scope, we focused particularly on the moderating effects of sample demographics—specifically culture, age, gender, and education—rather than on methodological or other study characteristics, such as publication year or measurement reliability. The theoretical rationale for examining whether QE correlates vary by these demographic factors is outlined below. Methodological and other study characteristics were examined in exploratory moderator analyses. An overview of the included studies and their relevant sample characteristics is provided in Table 1.

In the present meta-analysis, the association between the QE and various aspects of psychosocial functioning was examined. Additionally, demographic moderators of this association were explored. The meta-analysis was guided by the following research questions.

The titles, abstracts, and keywords of all articles in the literature databases PsycInfo, ERIC, and PubMed were searched by using the search string “Quiet Ego” in April 2025. The search was not limited by any additional filters to ensure that no work on the relatively new QE construct, including both published and unpublished studies like dissertations, was missed. Instead, all materials underwent manual screening according to predefined inclusion criteria. For the inclusion of any published or unpublished studies missed by the standardized databases, an additional exploratory search via cross-references was conducted. In total, 98 titles and abstracts were screened for eligibility. Figure 1 summarizes the literature search process.

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Every accessible study identified through the literature search was screened for the following inclusion criteria: (1) article published in the English language, (2) no targeted recruitment of participants with disorders or disabilities, (3) presence of original empirical data, (4) unduplicated data, (5) inclusion of a QES assessment or a non-confounded implementation of a QE intervention, (6) report of a standardized effect size for the bivariate relation between the QE and any aspects of psychosocial functioning, along with the corresponding sample size, and (7) consistent information on effect size data across different article sections (e.g., tables and text).

After removing duplicate records from the initial literature search conducted in July 2024, 83 articles were independently screened based on their titles and abstracts by the first author and a trained undergraduate psychology student. As a result, 52 articles were excluded for not meeting one or more criteria. The Interrater Agreement (IA), assessed as the percentage of agreement between coders, was high (95.18%) for this step. The corresponding authors of any inaccessible publications that met the inclusion criteria during the article screening process were contacted via email. 29 accessible full texts of eligible abstracts were independently obtained, screened (IA = 93.1%) and coded (IA = 95.15%) using the same inclusion criteria. Any disagreements between the coders were resolved through discussion. Due to limited evidence, all effect sizes derived from interventional study designs (i.e., Liu, 2022; Liu et al., 2022a; Wayment et al., 2015, 2019b), except for reported pre-intervention correlations between relevant study variables, were excluded. After the initial exclusion of six studies, one was reinstated following the provision of missing effect size data, and two additional studies were added through exploratory cross-referencing, resulting in 26 eligible articles for the meta-analysis. An updated literature search conducted in April 2025 yielded one additional potentially relevant record based on its abstract, but it was excluded because the full text could not be retrieved.

A total of 273 effect sizes were included in the present meta-analysis. A standardized coding sheet was developed based on predefined instructions. To address the first research question, Types of Psychosocial Functioning were differentiated based on whether the construct associated with the QE reflected a positive indicator (e.g., benevolence, mindfulness, purpose) or a negative indicator (e.g., social dominance orientation, rumination, stress). The category neutral was used when constructs could not be clearly classified. Adapting the VOA framework for the present meta-analytic purpose, where possible, QE correlates were further categorized into Domains of Psychosocial Functioning based on the value facet reflected by the associated construct (i.e., value orientation, value perspectivity and value fulfillment). For constructs encompassing more than one aspect the domain various was added as a coding option. Generativity, for example, reflects such a construct, often operationalized as a mix of all three value facets, encompassing not only conscious concerns about social responsibility (value orientation) and an understanding of one's impact on future generations (value perspectivity) but also a sense of eudaimonic well-being through satisfaction resulting from meaningful contributions in life (value fulfillment; see McAdams et al., 1993). Additionally, to make sure that no other aspects of psychosocial functioning are overlooked solely because none of the dimensions applies to the measurement being categorized (e.g., trait-like constructs such as the Big Five personality traits, social environment factors such as social support/strain or behavioral outcomes like physical/verbal aggression) the domain other was coded.

Regarding the second research question and theoretical arguments that cultural orientations, gender differences, age-related developmental stages and educational contexts may have an impact on QE associations, differences specific to culture, gender, age and education were also considered and coded for each included article. To operationalize cultural orientation, an individualism index was calculated based on the coded country where the majority of the sample permanently resides or—if this information was unavailable—the country in which the study was conducted, using Hofstede’s country comparison tool (The Culture Factor Group Oy, 2025). A score below 50 indicates a more collectivistic cultural orientation, while a score above 50 indicates a more individualistic one. Table 2 provides an overview of the coded moderator variables in relation to the research questions, while Table 3 presents additional methodological characteristics coded for exploratory analyses (e.g., study design, measurement reliability, etc.).

Since all included studies reported a zero-order Pearson correlation (r) between the QE and various aspects of psychosocial functioning, this meta-analysis utilized the correlation coefficient itself as the effect size for the meta-analytic integration. Effects sizes with inverted directions were recoded, to ensure that positive effect sizes indicate a positive association between higher QE scores and the respective aspect of psychosocial functioning. All correlations underwent Fisher’s Z-to-r-transformation to approximate a normal sampling distribution (Lipsey & Wilson, 2001) and were back-transformed for reporting in this manuscript. Taking into consideration that correlations may be influenced by measurement errors, the effect sizes were adjusted for measurement unreliability using Spearman’s correction for attenuation (Hunter & Schmidt, 2004) whenever reliabilities of the measurements were available. In cases where reliabilities were not reported, the correlations remained uncorrected. Additionally, given the expected contrasting associations between the QE and positive versus negative indicators of psychosocial functioning, as well as their potential to skew results, three separate datasets were created. These include an adjusted total dataset—where the direction of effect sizes for negative indicators was reversed—and two split datasets containing only positive or only negative indicators of psychosocial functioning, respectively. The neutral category, which included only three effect sizes, was not considered independently. To ensure comparability and transparency, analyses were conducted and reported separately for each of the three datasets.

To synthesize the effects, robust variance estimation (RVE; Hedges et al., 2010; Tanner-Smith & Tipton, 2014; Tanner-Smith et al., 2016) was applied to address the dependency among effect sizes originating from the same study. Before meta-analytic integration, effect sizes were examined for influential outliers using Cook’s values (Cook & Weisberg, 1982; Viechtbauer & Cheung, 2010). An outlier (Collier et al., 2020) was identified, and although further sensitivity analyses indicated that it was unlikely to skew the results, the effect size was removed from the dataset. Considering the anticipated heterogeneity in findings, random-effect models were employed for meta-analytic integration to account for residual heterogeneity between samples (Raudenbush, 2009). A weighted least squares approach (Hedges et al., 2010; Tanner-Smith & Tipton, 2014) was utilized for estimating mean effect sizes and conducting meta-regression models. The degree of heterogeneity among study-average effects was assessed using τ² (Deeks et al., 2019). Additionally, I² was used in order to indicate the proportion of variance attributed to true effects rather than sampling error (Borenstein et al., 2017).

Moderator variables were entered in regression models as predictors for the correlation between the QE and various aspects of psychosocial functioning. To mitigate multicollinearity resulting from the potential intercorrelation of moderators, mean effect sizes for each level of every moderator were computed in separate regression analyses. Furthermore, confidence intervals and heterogeneity indicators of effect sizes were analyzed. In the cases of normal distribution, continuous moderators were included in the meta-regression in their original form. Otherwise, they had been log-transformed beforehand to obtain normal distributions (Tabachnick & Fidell, 2013). A significant result indicates that as the value of the continuous moderator increases, the QE associations become stronger or weaker, depending on the direction of the slope. Categorical moderators with more than two levels had been dummy-coded first, using the moderator level with the lowest effect size as a reference level. For example, to represent the five Domains of Psychosocial Functioning, four dummy variables were created for the moderator levels of value orientation, value perspectivity, value fulfillment, various and other with the latter serving as the reference category (implicitly represented when all four dummy variables are 0). A significant result indicates that QE associations vary in strength for the respective moderator level compared to the reference category. If moderator levels have degrees of freedom below four, only the mean value is reported without the confidence interval or indices of heterogeneity. These levels are also excluded from significance tests in moderator analyses due to the potential unreliability originating from the small number of observations (Fisher et al., 2017). In general, effect sizes that lack information on specific moderators, such as the sex distribution in the sample, were not considered in the corresponding moderator analysis.

Given the potential impact of publication bias on meta-analyses, which is an underrepresentation of effect sizes close to zero, visual and statistical analyses were performed. These analyses included funnel plots (Peters et al., 2008). Egger's regression test (Egger et al., 1997) trim-and-fill (Duval & Tweedie, 2000), and FAT-PET-PEESE using RVE (Alinaghi & Reed, 2018). FAT-PET-PEESE is a conditional meta-regression approach used to adjust for publication bias and other small-study effects. After testing for funnel asymmetry (FAT), a regression analysis of effect size on study precision is performed (PET) to assess whether a true effect exists, distinct from zero. PEESE is an extension of PET that further adjusts the true effect size based on the relationship between effect size and precision (see Alinaghi & Reed, 2018). Publication bias analyses were performed once for individual effect sizes across articles (assuming independence) and once for the aggregate effect sizes by article.

Of the 26 articles included findings from 41 independent samples were analyzed. These comprised 273 effect sizes derived from a total of 13,391 participants. Sample sizes ranged from 37 to 1117, with a median of 303. The publication years of the included articles ranged from 2015 to 2024, with a median publication year of 2019, indicating a sustained and consistent interest in the QE construct within scientific research since its introduction in 2015. Regarding the split datasets, 25 articles reported QE correlations with positive indicators of psychosocial functioning (191 effect sizes), while 18 articles reported correlations with negative indicators (79 effect sizes). For more details on the number of articles reporting QE associations within specific Domains of Psychosocial Functioning and the corresponding effect sizes, see Table 2.

The average percentage of females in the included samples was approximately 68% (SD = 13.56). Regarding the remaining gender composition, most studies reported only the percentage of females or both female and male percentages. Only a few studies reported missing gender data (i.e., Bauer & Weatherbie, 2023; Wayment et al., 2015) or included a non-binary category (i.e., Al-Kire et al., 2022; Gilbert et al., 2022; Kondili et al., 2022; St. Arnaud & Sharpe, 2023), each with relatively low representation. The mean age across samples varied from 18 to 50 (M = 25.58, SD = 10.71) with the median age being 19.41 years. Geographically, the distribution showed little variance, with about 81% of the effect sizes originating from studies conducted in the United States, 8% in Canada, 9% in Italy and 1% each in Singapore and Spain. Calculated individualism index scores ranged from 43 to 72 with a mean of 60.22 (SD = 4.48). For reference, the United States, for example, have an individualism index of 60. Regarding ethnic composition, approximately 62% of the effect sizes came from samples predominantly White/European, 15% from samples with no clear predominant ethnicity and 1% from predominantly Asian samples. About 22% of the effect sizes were from studies lacking ethnicity information. In terms of educational levels, there was minimal variability as well, with approximately 77% of the effect sizes deriving from samples with tertiary education or higher, 4% from samples with secondary education or lower, 7% from studies without clear categorization and 12% from studies without available educational data.

About 82% of the effect sizes were derived from studies conducted in field settings, around 3% from studies conducted in laboratory settings and in approximately 15% of cases, setting information was not explicitly provided. Reliability estimates for the QE ranged from α = 0.68 to 0.91, with a median of α = 0.77. For the psychosocial functioning constructs associated with the QE, reliability estimates ranged from α = 0.49 to 0.97, with a median of α = 0.84. The QE correlates were categorized into positive indicators of psychosocial functioning in about 70% of cases and negative indicators of psychosocial functioning in about 29% of cases. Fewer than 1% of the measurements (i.e., religious affiliation, entheogenic classic psychedelic use, sales performance) were coded as neutral. Among the QE correlates, around 31% reflected desire-related aspects (value orientation), 17% wisdom-related aspects (value perspectivity) and 22% well-being-related aspects (value fulfillment). Additionally, about 20% of the QE correlates reflected more than one of the aforementioned domains (various) and around 10% could not be clearly categorized (other).

Multiple analyses were conducted to address the research questions of this meta-analysis and to explore methodological factors contributing to the heterogeneity observed in effect sizes. Table 2 presents the overall mean effect size and variations in mean effect sizes across different levels of moderator variables, sorted by the research questions they address. Results of all exploratory moderator analyses are presented in Table 3. The heterogeneity measurements τ² ranged between 0.003 and 0.098, and I² ranged between 42.53 and 96.56. Together, these ranges indicate moderate to substantial between-study variation attributable to real heterogeneity rather than chance, suggesting potential moderation by third variables in QE correlations (Deeks et al., 2019). If certain levels of moderators were coded but not listed in the tables, it is because either no or only one study reported the respective data. To avoid redundancy, categorical moderator variables with only one level (e.g., publication type, study design, test order, effect size type) are not reported in a separate column, as their mean effect sizes are identical to the overall effect sizes in the corresponding datasets. The absence of confidence intervals, measurements of heterogeneity or results of tests for moderator analyses suggests that the available evidence was insufficient (df < 4) for conducting the respective analysis.

Due to lack of data, methodological variables including study design, test order, setting, effect size type and effect size direction could not be considered in moderator analyses. In terms of publication year and sample size, none of the analyses across the three datasets reached statistical significance, suggesting that QE associations were robust across these factors. In both the total dataset and the split dataset for positive indicators, significant moderator analyses revealed that QE associations were substantially higher when standardized tests were used to measure an aspect of psychosocial functioning and when a greater number of items were included. Regarding reliability aspects, QE associations did not differ significantly in these datasets. The same analyses for negative indicators did not show statistical significance for test standardization, item number or reliability with regard to the coded aspects of psychosocial functioning, but were significant for QE reliability. The unstandardized negative slope (b = − 1.072, p = 0.030) suggests that the more precise the measurement of the QE, the higher the negative association between the QE and negative indicators of psychosocial functioning (see Table 3 for results).

The funnel plots in Fig. 2 do not directly suggest a publication bias, as they display a symmetrical, inverted funnel shape where effect sizes from smaller studies are widely scattered at the bottom, and those from larger studies are more narrowly clustered at the top (Sterne & Egger, 2001). A test for funnel plot asymmetry (Egger et al., 1997), which assesses the null hypothesis of funnel plot symmetry, confirmed the absence of a publication bias only on the study level (z = 1.191, p = 0.234) but not on the effect size level (z = 2.323, p = 0.020). Nonetheless, after correcting for potential publication bias using the trim-and-fill method, the overall effect remained highly significant at both levels with only a variation from the original effect in the second decimal place. Additionally, PET analyses showed non-significant slopes at both the study and effect size levels, indicating that small study effects are not likely driving the results. Subsequent PEESE analyses, prompted by significant PET intercepts at both levels, revealed highly significant intercepts, suggesting true effects after adjusting for potential publication bias. Additionally, non-significant PEESE-slopes imply that there is no significant relationship between effects and study precision, further reinforcing the robustness of the results. These findings collectively suggest minimal evidence for the presence of a publication bias. Since all effect sizes were obtained exclusively from journal articles, it was not possible to additionally examine the impact of publication type through moderator analyses.

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As expected (RQ 1), QE demonstrated significant positive associations with various aspects of healthy psychosocial functioning, particularly key elements of intersystemic human flourishing, yielding a substantial overall effect across these aspects. In terms of value orientation, the QE was positively linked to humanistic and intrinsically motivated aspirations in life, such as prosocial (e.g., Bistricky et al., 2024; Howell & Buro, 2017; Vecina et al., 2023), pro-environmental (Wayment et al., 2014), and growth-oriented goals (Liu et al., 2022b; Wayment & Bauer, 2018). Conversely, the QE showed negative associations with materialistic and extrinsically motivated tendencies, including social dominance orientation (e.g., Al-Kire et al., 2022; Boin & Voci, 2019), materialism (Watson, 2018), and psychological entitlement (e.g., Howell & Buro, 2017). Intrinsically motivated values can contribute to psychosocial functioning by offering inherent satisfaction or pleasure through autonomy, competence, nurturance or relatedness, whereas extrinsically motivated values can be detrimental by focusing on obtaining social approval or material rewards, meeting others' expectations or avoiding potential sanctions (for more information, see Schwartz, 2012). Regarding value actualization, QE was positively associated with the presence—and negatively associated with the absence—of aspects of wisdom and well-being. These included, for example, higher levels of emotional intelligence (Liu et al., 2021), resilience (Bernabei et al., 2024), psychological well-being (Bernabei et al., 2024; Liu et al., 2022b), and compassion satisfaction (Buonomo et al., 2021; Wayment et al., 2019b), as well as lower levels of rumination (Collier & Wayment, 2018), expressive suppression (Wayment et al., 2014), psychopathological symptoms (Collier et al., 2020), and perceived stress (Liu et al., 2021). Together, these results align with and extend the previous findings from Bauer and Weatherbie (2023).

To situate the present findings within the broader literature, existing meta-analyses on self-compassion (i.e., Ewert et al., 2021; MacBeth & Gumley, 2012; Marsh et al., 2018; Zessin et al., 2015) offer meaningful points of comparison due to conceptual overlaps with QE (e.g., Wayment et al., 2014), as well as similarities in outcome, study and sample characteristics. The association between the QE and positive indicators of psychosocial functioning is comparable in magnitude to those between self-compassion and specific aspects of positive functioning (Ewert et al., 2021; Zessin et al., 2015). The association between the QE and negative indicators is present but lower in magnitude than the associations found between self-compassion and specific aspects of negative psychosocial functioning (Ewert et al., 2021; MacBeth & Gumley, 2012; Marsh et al., 2018). However, it is important to note that the QE encompasses a mindful and compassionate approach not only toward oneself but also toward other living beings (Wayment et al., 2014). This led our meta-analysis to explore a broader range of psychosocial qualities, including desire-related constructs (e.g., values, motives) that orient one’s thoughts, feelings, and actions in ways that may support or hinder individual, societal, or environmental well-being. In contrast, the meta-analyses on self-compassion have focused on specific aspects of psychosocial functioning, such as coping and individual well-being. Additionally, unlike the meta-analysis by MacBeth and Gumley (2012), the present study was based solely on non-clinical populations. This may have limited the range of negative indicators of psychosocial functioning assessed, potentially attenuating observed negative associations between the QE and these variables.

The dataset's limited variability within the moderator categories allowed for moderator analyses only on the impact of the country’s individualism index (RQ 2.1), mean age (RQ 2.2), and gender distributions (RQ 2.3), but not on the effect of participants’ educational levels on QE associations (RQ 2.4). Regarding culture, rather than directly supporting the initial expectation—potentially biased by our own cultural lens—that collectivistic cultural orientations would better facilitate the expression of QE characteristics in aspects of healthy psychosocial functioning compared to individualistic ones, results indicate that QE associations are stronger in cultural contexts that are neither clearly individualistic nor collectivistic (RQ 2.1). This conclusion stems from the fact that the lowest individualism scores considered indicate a balanced cultural orientation. In retrospect, it seems plausible that to cultivate the QE’s unique feature of balancing concerns for the self and others evenly, an overly self-effacing perspective (typical of collectivist views) may be just as limiting as an overly self-serving one (characteristic of individualistic views). Despite the narrow range of scores (43–72), the individualism index reached statistical significance for the total dataset, underscoring the robustness of this finding. This contrasts with the meta-analyses by Ewert et al. (2021) and Zessin et al. (2015), which found no moderating effect of geographical region or differences between North American and European samples, respectively. This discrepancy may reflect conceptual differences between the constructs or suggest that comparing specific cultural orientations provides a more valid approach to understanding cultural impacts than broad regional classifications.

As age and gender did not yield any statistically significant findings in either of the datasets, it cannot be claimed that effect sizes are stronger for older as compared to younger participants (RQ 2.2), nor stronger for women as compared to men (RQ 2.3). Regarding age, the current findings align with those of MacBeth and Gumley (2012) and Zessin et al. (2015), but contradict Ewert et al. (2021) and Marsh et al. (2018), who observed age-related changes in the relationship between self-compassion and coping or psychological distress. In terms of gender, results are consistent with MacBeth and Gumley (2012) and Ewert et al. (2021), but diverge from Zessin et al. (2015), who found that a higher proportion of females was associated with a stronger relationship between self-compassion and well-being. These inconsistencies in findings may reflect increased societal changes, including greater awareness of mental health, social responsibility, and challenges to gender stereotypes (United Nations, 2015). Another possible reason for the non-significant moderating effects of age and gender in the present study is the limited representativeness of the sample, with half of participants aged 18–19 and nearly 70% being women.

Theoretically, the results of the present meta-analysis indicate that the QE corresponds to the tools individuals need to flourish in an intersystemic sense. These include manifestations of (1) value orientation reflecting the desire for a good life in a psychosocial space, (2) value perspectivity indicating an individual’s ability to think complexly (i.e., from multiple perspectives and coherently) about oneself and others with humane concern and (3) value fulfillment, suggesting a genuine willingness to live in alignment with the aforementioned aspects, as reflected in measures of hedonic and eudaimonic well-being. Given the current dataset and meta-analytic methods, it is not yet possible to test whether QE relates simultaneously and independently to the three value facets as primary studies have yet to consistently assess and report correlations between QE and all three value facets in a standardized manner. Nevertheless, to the best of our knowledge, such meta-analytic evidence regarding intersystemic human flourishing has not been empirically demonstrated for any other psychological construct, which we find encouraging.

Methodologically, these findings underscore that capturing the QE’s added value beyond conceptually related constructs requires considering multiple aspects of an individual's intra- and interpersonal functioning. Specifically, its beneficial for QE research to examine not only its correlations with positive and negative indicators of psychosocial functioning, but also to further differentiate among and within dimensions of desire (self- vs. other-focused concerns), wisdom (intra- vs. interpersonal resources), and well-being (hedonic vs. eudaimonic aspects). Future primary studies that assess all three value facets and report intercorrelations would enable more nuanced theoretical insights into QE’s distinct relationship with intersystemic human flourishing.

Practically, this meta-analysis provides preliminary evidence suggesting that cultures with a balanced emphasis on both self and others—neither fully prioritizing self-expression nor self-sacrifice—may offer the most conducive conditions for the expression of QE characteristics across various aspects of healthy psychosocial functioning. The findings imply that sociopolitical views on what defines an ideal cultural representative could significantly influence the relationship between the QE and intersystemic human flourishing. However, due to a lack of research in countries with strong collectivist tendencies, we were unable to explore whether the moderating impact of cultural orientation on QE associations follows an inverted U-shaped pattern rather than a linear one. Additionally, questions remain regarding whether QE characteristics can be actively cultivated to causally impact intersystemic human flourishing, and about the broader applicability of the QE construct across demographic variables such as gender, age, and education, given the following limitations.

Meta-analyses inevitably rely on the available information of the studies they incorporate. The primary constraints arising from this dependence for the present study are highlighted to guide future studies on the QE construct. First, to address and explain the observed heterogeneity in effect sizes statistically, a substantial number of individual studies investigating relevant moderator variables are required. Over 80% of the studies included were conducted in the US, with half of the samples falling within the 18 to 19 age range (M = 25.58, SD = 10.71) and almost 78% of the participants having tertiary education. Consequently, most effect sizes reflect data from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) populations, resulting in limited statistical power to detect demographic moderators. While the findings of this meta-analysis still offer encouraging insights applicable to the above-mentioned cultural contexts, where living beyond ecological means is prevalent and sustainable social change is particularly crucial (Global Footprint Network, 2025) it is not possible to generalize beyond this context. This limitation is further highlighted by the inclusion criteria, which required studies to be published in English and excluded those targeting participants with disorders or disabilities. While these criteria did not affect study selection and align with standard systematic review practices, they nonetheless underscore the underrepresentation of marginalized cultural contexts and clinical populations in QE research. These groups, however, may be especially motivated or in greater need of improving psychosocial functioning. Expanding future research efforts in these areas could help determine whether effect sizes vary systematically (e.g., clinical vs. non-clinical; WEIRD vs. non-WEIRD) and contribute to a more comprehensive understanding of QE associations.

Second, this study has not explored potentially relevant moderators, such as socioeconomic status (SES), due to the lack of data collection or reporting on these variables in most primary research. Acknowledging the fundamental role of fulfilling basic needs in healthy human functioning (Narvaez & Noble, 2018) and the association between lower SES, insufficient provision of basic needs, and poorer health outcomes (Di Domenico & Fournier, 2014) future research should consider SES as a potential moderator of QE associations. For example, Tay and Diener (2011) conducted a survey involving over 60,000 participants across 120 countries, revealing that personal concerns, including competence and relatedness, significantly decrease when individuals struggle to meet their basic needs. Building on this, it is to be anticipated that lower SES, as compared to higher SES, negatively influences QE associations. However, to more fully understand the foundational precursors of the QE and its relationship with intersystemic human flourishing, research must adopt a broader biopsychosocial perspective. For example, Wayment et al. (2014) demonstrated that the QE correlates positively with Extraversion, Openness, and Agreeableness, and negatively with Emotionality, aggression, and hostility—suggesting potential trait-like underpinnings. Additionally, accumulating empirical evidence highlights the biological bases of personality (DeYoung, 2010; Soliemanifar et al., 2018). The biopsychosocial model of resilience proposed by Feder et al. (2019) may offer a valuable lens for investigating whether QE is similarly shaped by the interplay of biological and environmental factors across the lifespan, given that both QE and resilience are positioned as characteristic adaptations.

Third, both psychosocial functioning and the VOA framework are complex constructs, and while categorization is essential for synthesis, it can oversimplify and present challenges. Some studies provided only brief test descriptions—sometimes just a single sample item—limiting accurate classification. Moreover, wisdom-related elements under value perspectivity often relied on self-reports which likely reflect aspects of fulfillment-based well-being ("how wise I think I am") rather than true perspectivity-based wisdom ("how wise I actually am"). Additionally, self-oriented versus other-oriented desires were often examined in isolation, whereby concerns for oneself or others may only become problematic when there is an imbalance between the two. Finally, in the value fulfillment category, hedonic and eudaimonic well-being measures were combined, despite QE emphasizing eudaimonic aspects such as long-term meaning and purpose over short-term pleasure (Wayment & Bauer, 2017). Within the scope of this meta-analysis, it was not possible to account for participants’ individual value orientation—for example, whether they prioritize meaning over pleasure or include challenge or discomfort as part of fulfillment when measuring well-being—and this may have skewed effect sizes. Despite rigorous coding and independent screening, future research could improve meta-analyses like this by clearly defining construct operationalizations (e.g., by making study materials openly accessible), employing diverse methods to assess wisdom beyond self-report (e.g., moral decision tasks), assessing the balance between self- and other-oriented values (e.g., similar to the cultural individualism index), and accounting for one’s value orientation when measuring value actualization (e.g., by selecting measures of wisdom and well-being accordingly).

Fourth, due to the predominance of correlational study designs, causal conclusions cannot be drawn, and it remains unclear whether the QE promotes intersystemic human flourishing or vice versa. Nonetheless, brief QE interventions have shown promising results, including increased QES scores mediating improvements in flourishing (Liu, 2022; Liu et al., 2022a) and positive effects on personal well-being (Wayment et al., 2015, 2019b). However, limited interventional data prevented their meaningful inclusion in this meta-analysis. To establish causality, further longitudinal and experimental research with non-confounded QE interventions that assess QES score changes is needed. Building on the current findings, a critical next step is to explore whether QE can be intentionally cultivated to promote the enactment of flourishing-promoting values in daily life. This is particularly relevant given recent socio-political, technological, and environmental challenges like rising right-wing attitudes (Greven Thomas, 2016; Rodrik, 2021), ethical concerns around artificial intelligence (Qian et al., 2024; Tai, 2020), and climate disasters (e.g., IPCC, 2021). Future research might investigate, for example, whether priming QE characteristics, akin to cultural norm priming (e.g., Stephens et al., 2012), increases QES scores and subsequently intrinsic motivation to prioritize humanistic over materialistic goals. Ecological momentary assessment (Shiffman et al., 2008) may be utilized to track spillover effects, such as more sustainable or socially responsive behaviors throughout the day, as well as greater life satisfaction or a deeper sense of purpose over time. Extending interventions beyond human psychology, interdisciplinary research might also examine whether incorporating QE characteristics into artificial intelligence training or algorithmic design promotes more ethical and socially responsible technologies. These represent just a few promising directions for future inquiry.

In summary, to further enhance understanding of the QE and its role in intersystemic human flourishing, future research could: (1) ensure broader generalizability by diversifying samples beyond WEIRD cultures and including marginalized cultural contexts and clinical populations; (2) uncover potential dispositional roots by examining moderators such as SES and adopting a broader biopsychosocial perspective; (3) improve meta-analytic accuracy by clearly defining construct operationalizations, employing diverse methods to assess wisdom, evaluating the balance of self- and other-oriented value orientation, and measuring value actualization according to one’s value orientation; and (4) establish causal effects of the QE on intersystemic human flourishing through more longitudinal and experimental studies involving QE interventions (e.g., in contexts related to social change).