The Observed Mindful Behaviours scale

The Observed Mindful Behaviours scale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Observed Mindful Behaviours scale Larissa Bartlett, Rohan Puri, Amanda Neil, Craig Hassed, Jakob Hohwy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6755370/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective . To offer another lens to study mindfulness, particularly how mindfulness influences behaviours and social relationships, this paper reports the creation of the Observed Mindful Behaviours (OMB) scale. The OMB responds to limitations in current evidence including the reliance on self-report data. Methods . A 9-item observer-report scale was refined and tested in two samples (N=200) using item response theory and confirmatory factor analysis. Survey data from 190 dyads (N=380) were used to test construct validity of the refined scale. Spearman’s correlations tested a proposed nomological network for observed mindful behaviours. Regression models assessed the strength of observed correlations. Results. A 3-dimensional structure of the 9-item OMB was confirmed (RMSEA=0.098, w t =0.88). Criterion validity was supported by good alignment with trait mindfulness (β=0.42, R 2 =0.15) and interpersonal mindfulness (β=0.17, R 2 =0.12). Construct validity tests showed congruence with empathy and divergence from psychological inflexibility, but prosocial intentions, distress, anger reactivity or psychological capital were discriminant constructs. Conclusions . The new OMB scale detects the extent to which a person known to the rater (family, friend or colleague) behaves in a way that is noticeably attentive, aware and accepting (or mindful). Alignment with behavioural drivers (empathy, acceptance) but not behavioural states (distress, anger, intentions), or psychological capital, helps clarify what the OMB assesses. The OMB can be used to triangulate and strengthen self-reported findings and help examine how mindfulness comes across to others. Figures Figure 1 Figure 2 INTRODUCTION There is encouraging evidence that mindfulness influences prosocial behaviours (Berry et al., 2020; Donald et al., 2019; Malin, 2023) and positive relationships in work, leadership and health-care contexts (Arendt et al., 2019; Beach et al., 2013). This line of research extends common narratives of mindfulness to include a focus not just on how we feel, but how we behave in social settings. This more expansive lens is in keeping with traditional teachings in Buddhism (Thera, 1998), in which the way of mindfulness as a form of mental discipline is fundamental to living with wisdom (intentionality and broad perspective) and moral conduct (action, speech and livelihood). Despite its roots being about living with wisdom and morality, mindfulness is a construct that is largely conceptualised in research as an internal quality. Variously described in the literature, it can be thought of as a tendency for certain attitudinal and attentional processes which create a way of being, characterised by present-centered attention, awareness of internal states and circumstances, with an attitude of open heartedness and curiosity (Baer et al., 2009; Chems-Maarif et al., 2025; Kabat-Zinn, 2013). Variations on this conceptualisation have informed the development of self-report questionnaires used in research to assess the extent to which participants are mindful (Goldberg et al., 2017; Nilsson & Kazemi, 2016). The conceptualisation and measurement of interpersonal mindfulness has evolved the focus of these self-report mindfulness measures from being on the self in general, to the self in social settings (Khoury et al., 2022; Pratscher et al., 2018). The use of interpersonal mindfulness measures in research has contributed to our understanding of the positive influence of an individual’s mindfulness on personal relationships (e.g. Morin et al., 2024) and work dynamics (e.g. Reina et al., 2023). However, self-report measures necessarily rely on the views of the respondent, about how they feel and behave in social engagements, so findings may be subject to responder bias (Goldberg et al., 2017; Kreplin et al., 2018). An additional approach for assessing the impacts of mindfulness beyond the self is to ask about behaviours that are noticeable to others and congruent with the construct of mindfulness, as measured by self-report. This approach is aligned with research into other trait-like qualities (e.g. personality; Brauer & Proyer, 2019), and is premised on evidence that self-reported mindfulness aligns with, but does not exactly mirror, how one’s mindfulness is perceived by others (Bartlett et al., 2016; May & Reinhardt, 2018). Bartlett et al. (2021) developed a novel Observed Mindfulness Measure (OMM), by adapting items used in self-report mindfulness questionnaires for observer-report. The assessed construct was defined as the noticeable tendency of another person to be mindful: attentive to and aware of current experience, and displaying an attitude of curiosity, openness and acceptance . The nine-item questionnaire had good psychometric properties for a three-dimensional construct – attentiveness, awareness, and acceptance – with a common latent variable. The validation study used dyadic data formed by the views of one person about themselves (the participant) and the views of another person nominated by the participant about the typical behaviour of that participant (the observer), to test correspondence of OMM with self-reported mindfulness and other related constructs. The construct validity of the OMM was supported, but some limitations were identified. Notably, a ceiling effect in the attentiveness dimension (the only dimension in which items were negatively worded)limited the measure’s potential to detect positive change., Further, the OMM’s use of gendered terms is exclusory; and not best practice in health research (Scott et al., 2025). In addition, clarification of the construct being assessed by the scale may enable greater insight into what it means to behave mindfully. Further, the second-person, behavioural perspective presents a valuable opportunity to study whether qualities such as mindful attentiveness, awareness, and acceptance are instrumental in driving behaviour (Bartlett et al., 2021; Goldberg et al., 2017; Varela & Shear, 1999). The second-person, behavioural perspective taken with the OMM presents a different lens through which to study whether qualities such as mindful attentiveness, awareness, and acceptance are instrumental in driving prosocial behaviours (Goldberg et al., 2017; Varela & Shear, 1999). We propose the approach taken with the OMM may help elucidate if, when, and how a person’s mindfulness can exert a flow-on, or external effect, on other people. For example, as proposed by van der Schans et al. (2022, p. 3) “ During an interaction, higher levels of mindfulness should help to (1) notice distracting thoughts, emotions and behavioral inclinations, (2) diminish the automatic influence of such reactions on attention and behavior, and (3) redirect attention to the interaction and interaction partner. … In short, trait mindfulness might increase ‘presence’ in the interaction and promote its quality .” In support of this notion, interview data collected by Simonsson et al. (2023) from sitting members of the UK Parliament showed that cultivating trait mindfulness through a supported program “ enabled politicians to better deal with the demands and stresses of political work, to reconnect with themselves and be more grounded, and … to relate to other politicians and their viewpoints in a more humane and constructive way.” (p.1362). While internally felt, these outcomes can impact the quality of day-to-day life for political peers, and likely to others (constituents, staff, media) involved in their social interactions. Used to facilitate the direct assessment of this kind of ‘mindful presence’, the viability of a research instrument measuring observable mindful behaviours could be considerably wider in scope than being used purely for triangulation purposes. For instance, building on work by Beach et al. (2013), if people can quantitatively rate a treating physician’s behaviour as more or less mindful, it would be possible to directly examine the influence of that physician’s mindful behaviours on their patients’ quality of care and health outcomes. In work or familial contexts, colleague or partner ratings using this approach could also help explain how being mindfully aware comes across to others, and to investigate the flow-on effects of mindfulness-based interventions on relationships and performance. However, before this wider application can be considered, the limitations of the OMM noted above need to be addressed and the revised measure should be established as valid and reliable. Further, because the items in the original measure all elicit responses about noticeable behaviours of the observed person, rather than their internal experiences, we propose a better name for the measure would be the Observed Mindful Behaviours (OMB) scale. This paper reports the refinement of the original OMM and the creation of the OMB. Structural integrity and item performance. As reported by Bartlett et al. (2022), two of the three attentiveness items of the OMM were bounded at the top. The attentiveness items in the original scale were all negatively worded (i.e. ‘does not do this’), while items in the other two dimensions were positively worded (i.e. ‘does this’). Contemporary scale development theory proposes that mixing up the direction, or orientation, of items facilitates the respondents’ attention; but conversely, using a common orientation throughout a scale helps avoid mistakes and reduce responder burden (DeVellis & Thorpe, 2022). We propose having a common positive orientation across all items might improve the response distribution of the attentiveness data (Lietz, 2010). Nomological network. In the initial development of the OMM (Bartlett et al., 2021), criterion validity was pragmatically based on a strong self-other agreement score (ICC 0.45) with the unidimensional Mindful Attention and Awareness Scale (Brown & Ryan, 2003). Further work was called for to understand convergence of the measure with other self-report mindfulness instruments. Of particular interest is the degree of agreement with data generated by multidimensional measures of trait mindfulness (e.g. FFMQ; Baer et al., 2006) and interpersonal mindfulness (e.g. IMS; Pratscher et al., 2018). Importantly, a measure of observable mindful behaviours should produce data with a similar distribution to a self-reported mindfulness measure. As was reported by Adnoy et al. (2023), using a multi-dimensional measure can help untangle which – and how – different aspects of mindfulness drive social acting. Plotting variance between self and other reports at whole scale and subscale level can then support study into the impact of internal qualities of mindfulness on behaviour (Duan & Li, 2016). To establish construct validity (Haig, 2023), we propose testing hypothesized relationships with established constructs that are theoretically and empirically shown to either positively or negatively correlate with behaving mindfully. Two key mechanisms that help explain how mindfulness supports wisdom and moral acting include decentering, or the ability to step back and hold a wide view of the context in which experiences are occurring; and re-perceiving, or the ability to accept current experience and re-frame perceptions accordingly (Adnoy et al., 2023; Guo, 2024). A lack of these abilities can result in psychological inflexibility, or the tendency to attempt to control or avoid difficult or unwanted circumstances and experiences (Ong et al., 2024). This inflexibility interferes with the ability to deploy adaptive coping in response to stressful events (Tindle et al., 2022) and is associated with low cooperation as well as poor social and emotional health (Zhang et al., 2023). A consistent negative correlation has been reported between trait mindfulness and psychological inflexibility (Curtiss & Klemanski, 2014). Trait mindfulness is also negatively associated with perceived, or acute stress and psychological distress (Keng et al., 2011), an indicator of chronic stress-related mental and physical health problems (Biggs et al., 2017). Both acute and chronic stress impede the capacity for perspective taking, a component of empathy (Brown et al., 2021; Nitschke & Bartz, 2023). Further, unrelieved stress can exacerbate anger and aggression, hyperarousal, substance use, sleep problems and lack of cognitive clarity, all of which are more or less salient to others (Whitehouse et al., 2022). There is considerable evidence linking higher trait mindfulness with lower stress, and for supporting positive social interactions in high stress contexts, such as through constructive engagement (Orosz et al., 2023) and non-violent communication (Simonsson et al., 2023; Sofer, 2018). In organisational psychology, positive psychological capital (PsyCap: a composite of hope, self-efficacy, resilience and optimism) is associated with positive work engagement, performance and leadership (Luthans & Youssef-Morgan, 2017). The assessment of PsyCap is used in research for investigating the role of psychological resources in identifying, setting and achieving personal and professional goals (Luthans & Broad, 2022). There is convergence between self-reported mindfulness and PsyCap (Roche et al., 2014) with emerging evidence suggesting that PsyCap mediates the influence of trait mindfulness on prosocial behaviour in work settings (Liu et al., 2024). The overall objective of the current project was to create the Observed Mindful Behaviours (OMB) scale, for collecting second-person, quantitative data and advancing understanding of the social and behavioural correlates of mindfulness. First, we aimed to improve the structural integrity and item performance of the original OMM to create the OMB (Aim 1). The first hypothesis tested (H1) was that the OMB data would retain a clear three-dimensional structure and the psychometric performance of attentiveness items would improve following refinement. Next we aimed to test the construct validity of the OMB (Aim 2). To progress Aim 2, we tested the following hypotheses. Hypothesis 2: Tests of self-other agreement will show that total OMB scores would be significantly convergent with total scores for trait and interpersonal mindfulness (H2a) and variation will be observed in agreement between the observer and self-reported measures at subscale level (H2b). Hypothesis 3: Construct validity would be supported by correlations between OMB total scores showing convergence with self-reported psychological capital (H3a), empathy (H3b) and prosocial intentions (H3c), and divergence with psychological inflexibility (H3d), psychological distress (H3e) and anger reactivity (H3f). METHODS This study was approved by the [REMOVED] Human Research Ethics Committee (Ref. 28461) and was funded by the [REMOVED]. Methods for developing quantitative scales for use in social sciences research were followed throughout (Beaujean, 2014; DeVellis & Thorpe, 2022). Participants Sample demographics are reported in Table 1. To test the psychometric properties of the revised scale (Aim 1), two separate samples provided data via Prolific, an online participant recruitment portal. Inclusion criteria were being 18 years or older, with a 98% completion rate for previous Prolific studies and English language fluency. The two samples were recruited concurrently using Prolific (www.prolific.com, [date accessed: 3 rd March 2023]) with automatic 1:1 sequential assignment. Participants were compensated for the time taken to complete the 10-minute survey at approximately £14.63 per hour. Prolific sample 1 (n=99) were presented with the original measure with corrected gender terms (O), Prolific sample 2 (n=101) were presented with the revised measure (R), with the corrected gender terms and positively oriented attentiveness items (see ‘Procedures’ and Table 2). To test the construct validity of the resultant OMB scale (Aim 2), data were collected online from a purposefully recruited community sample using REDCap surveys hosted at the University of [REMOVED]. This sample was comprised of 190 participant-observer dyads (N=380), aged 18 years or older and fluent in English. Recruitment was via open invitation to join a mindfulness research project, promoted via University of [REMOVED] AND [REMOVED] University student engagement and social media pages. Interested respondents were directed to the study registration page, where information for participants and their observers was available for download. After providing informed consent, participants were asked to nominate a person who they interact with at least 2-3 times a week, and who would be prepared to receive an invitation to complete an online survey with some questions about themselves and about their paired participant’s behaviours. Participants entered the first name and email address for their nominated observer and a personalised invitation to join the study (with a unique link to the paired survey) was automatically sent to that email address. Observers who followed the link were provided study information and asked to consent to the research conditions then do the survey. All data were stored on password protected secure servers and were de-identified prior to analysis. Both members of the participant-observer dyads needed to provide complete data to be included in analyses. Neither member of the dyads had access to the others’ data and were not provided with information about their participation or responses. Table 1. Participant characteristics for analysis samples Participant characteristics Prolific samples Community dyadic sample Sample 1 O Sample 2 R Participants Observers (n=99) (n=101) (n=190) (n=190) Age (Mean years, SD) 28.1 (8.00) 29.1 (9.08) 29.1 (11.9) 36.1 (15.1) Sex (Mean, SD) Male 49 (49.5%) 63 (62.4%) 37 (19.5%) 82 (43.2%) Female 47 (47.5%) 36 (35.6%) 145 (76.3%) 101 (53.2%) Other 3 (3.0%) 2 (2.0%) 8 (4.2%) 7 (3.7%) Reporting about (n, %) Colleague 10 (10.1%) 3 (3.0%) - 5 (2.6%) Friend 37 (37.4%) 41 (40.6%) - 45 (23.7%) Family 52 (52.5%) 57 (56.4%) - 139 (73.2%) Familiarity (Mean, SD) 58.2 (23.7) 58.3 (24.1) 74.5 (19.6) 63.1 (27.4) Training = yes (n, %) 58 (58.6%) 51 (50.5%) 150 (79.0%) 116 (61.1%) Familiarity = self-reported familiarity with mindfulness (scale 1 to 100); Training = self-reported exposure to mindfulness practices and teachings (yes/no) Procedure Three revisions were made to items in the Attentiveness dimension of the original measure published by Bartlett et al. (2022), to produce the OMB (Aim 1). First, gendered terms were replaced with non-gendered terms; next an excluded item from the Attentiveness dimension in the original item set was returned to re-test fit and performance, and lastly the items were re-written to orient them in positive language. The items for the original measure with the additional item (O), and the version with revised wording and orientation (R) are shown in Table 2. Data distributions, factor structure, and item performance of the two scales were examined using Prolific samples 1 and 2. Table 2. Items of the observed mindfulness measure (OMM) and the observed mindful behaviours (OMB) scale. Measures Construct validity (Aim 2) was tested using rank order correlations and regression models using observer-reported OMB data and participant-reported measures of constructs in the proposed nomological network of observable mindful behaviours. The following construct measures were administered. Observed Mindfulness Measure (OMM) fit indices as published were: RMSEA=0.042, c 2 =0.005, TLI=0.987, CFI=0.992, w t =0.91; and reliability indices for the subscales were: Attentiveness w t =0.82; Awareness w t =0.87; Acceptance w t =0.75 (Bartlett et al., 2021). Trait mindfulness was measured using 12-items from the Five-Facet Mindfulness Questionnaire (FFMQ-15; Gu et al., 2016). Based on evidence that the Observing facet of the FFMQ is more informative in intervention research than in cross-sectional analyses (Rudkin et al., 2018), only the items that load onto the other four dimensions (Acting with awareness, Non-judging, Non-reacting and Describing) were included in the survey. The 27-item Interpersonal Mindfulness Scale (IMS; Pratscher et al., 2018) was completed by both members of each participant-observer dyad. McDonald’s Omega coefficients were: FFMQ data (whole scale: w t ==0.85, Describe: w t =0.80, Act aware: w t ==0.73, Non-react: w t ==0.73, Non-judge: w t ==0.85) and IMS data (whole scale: w t ==0.92, Act aware: w t =0.89, Presence: w t ==0.90, Non-judge: w t ==0.73, Non-react: w t =0.81). Prosocial acting was assessed with the 4-item Prosocial Behavioural Intentions Scale (PBIS; Baumsteiger & Siegel, 2019). PBIS data (w t ==0.85) was hypothesized to correlate positively with OMB data. Indicators of empathy , including perspective taking and discomfort in social engagement were measured using 8 items (two dimensions) of the Brief Interpersonal Reactivity Index (B-IRI; Ingoglia et al., 2016). We hypothesised perspective taking (w t ==0.79) would be positively correlated with OMB data, whilst discomfort in social engagement (w t =0.89) would be negatively correlated. Psychological inflexibility was measured using the 7-item Acceptance and Action Questionnaire (AAQ-2; Bond et al., 2011), and PsyCap (hope, optimism, resilience and efficacy) in relation to interpersonal relationships was measured using the 12-item Compound Psychological Capital questionnaire (CPC-R; Dudasova et al., 2021). Internal consistency was good for both the AAQ-2 (w t =0.96) and CPC-R (w t ==0.93) data. We hypothesized participants’ AAQ-2 would be negatively correlated, and CPC-R data would be positively associated with their paired observers’ responses to the OMB. The 6-item Kessler measure of psychological distress (K6; Kessler et al., 2002) and the 5-item Dimensions of Anger scale (DAR-5; Forbes et al., 2014) were used to test hypothesized divergence of stress-related constructs with the OMB. Internal consistency was good for K6 data (w t =0.92) and satisfactory for DAR-5 data (w t ==0.80). Psychological distress is an established outcome of chronic or unmanaged stress; and anger reactivity provides information about behavioural and emotional regulation. Demographic data included age, gender identification, country of residence, familiarity with mindfulness (on a scale of 1-100), dyadic relationship (friend, colleague or family) and self-reported exposure to mindfulness training. Data analyses Participant characteristics were summarised descriptively (Table 1). Boxplots were used to check data distributions. Factor analyses (CFA) were conducted using the Psych (Revelle, 2014) and lavaan packages in R (Rosseel, 2012) to confirm the factor structure of scale data. Criteria used to assess goodness of fit were Root Mean Squared Error of Approximation (RMSEA 0.9), Cronbach’s alpha (α > 0.7) and McDonald’s omega reliability coefficient (w t => 0.7). Item responsiveness theory modelling (IRT) was conducted at factor level using generalised partial credit model for ordinal, polytomous data (Beaujean, 2014). The a-score from IRT models denotes discrimination (values around and above 1 are desired). The b-scores (illustrated by the multi-colour curves in the item characteristic curve plots) refer to how precise the information provided by each response option is. Flat curves indicate poor precision, clear and ordered peaks indicate good precision. Internal consistency was assessed using McDonald’s omega test for all scale data prior to analyses (Zinbarg et al., 2005). Spearman’s Rho was applied to produce a correlation matrix for all assessed constructs, with the Benjamini-Hochberg False Discovery Rate multiple comparisons correction applied (Benjamini and Hochberg, 1995). Linear regression models were then used to test the influence of demographic factors and the hypotheses for Aim 2, that observer-reported OMB scores would be positively correlated with participants’ self-reported trait and interpersonal mindfulness. Finally, we ran a test of moderation to understand whether observers higher in self-reported mindfulness were more discerning in their OMB ratings. RESULTS Aim 1. Structural integrity and item performance . Data distributions. The data from Prolific samples 1 and 2 (Supplementary Figure S.1.) showed variability in the response distribution in O and R data. Eight out of the 10 items in the Original measure had a median of 4 (out of possible 5). One of the Attentiveness items (OMM-4) was bounded at the top, with an IQR that included the maximum score. Six of the 10 items in the Revised measure had a median of 4, and four a median of 3, and no items had the maximum score included in the IQR. Item performance. IRT modelling on the attentiveness factor showed the Revised items had better discrimination, precision and information about ability than the negatively worded Original items (Supplementary Table S.1). The additional attentiveness item (OMM10) that was returned for testing purposes, showed poor discrimination and precision in both samples and was dropped from structural analyses. Item probability functions and test information for the three retained Attentiveness items in the Original and Revised measures are illustrated in item characteristic curve plots (Fig. 1 ). Structural analysis. Confirmatory factor analysis (CFA) was run on the 9-item Original and Revised scale data (as set out in Table 2 ). While the information parameters were similar, the fit indices (TLI, CFI, α and ω t ) were all closer to 1 for the Revised scale (OMB) than for the original scale. Comparison of models showed no significant statistical difference (χ 2 diff = 0.463). Our first hypothesis (H1) was therefore supported. The resulting OMB was then used for further testing. Structural re-analysis. CFA confirmed the 3-factor structure for the OMB in data provided by the community sample. Fit indices for the modelled data are reported in Table 3 . Figure 2 shows item-factor loadings, factor-factor correlations, and variance explained. Table 3 Fit statistics from Confirmatory Factor Analysis for the original and revised 9-item OMM Sample Model RMSEA χ 2 p CFI TLI α ω t Prolific 1 O 0.098 0.00 0.91 0.86 0.80 0.86 Prolific 2 R 0.098 0.00 0.92 0.88 0.82 0.88 Community dyadic sample OMB 0.070 0.00 0.97 0.95 0.88 0.91 RMSEA: Root Mean Squared Error of Approximation; CFI: Comparative Fit Index; TLI: Tucker Lewis Index; α: Cronbach’s alpha coefficient of internal reliability; ω: McDonald’s Omega coefficient of test reliability. O: original Observed Mindfulness Measure as published by Bartlett et al (REF), adjusted with non-gendered terms; R: revised OMM items with attentiveness items reworded for positive orientation; OMB: the Observed Mindful Behaviours scale (same as R). Aim 2. Construct validity. Reliability coefficients for each of the nomological network constructs and Spearman’s Rho correlations with OMB scores are presented in Table 4 . Summary scores for each variable tested are in Supplementary Table S.2. Results supported our criterion validity hypothesis (H2a) as the observer-reported OMB total scores were robustly and positively correlated with their paired participants’ trait mindfulness (r = 0.35, p < 0.001) and interpersonal mindfulness (r = 0.28, p < 0.001) scores. Table 4 Correlations between nomological network constructs and OMB total and subscale scores Variable ω t α n r s p Total OMB 0.91 0.88 190 Empathy (overall IRI) 0.85 0.74 186 0.19 < 0.001 Personal discomfort (IRI) 0.89 0.85 186 -0.24 0.003 Perspective taking (IRI) 0.79 0.73 186 0.08 0.016 Psychological inflexibility (AAQ) 0.96 0.93 186 -0.31 < 0.001 Trait mindfulness (FFMQ-SF) 0.85 0.78 186 0.35 < 0.001 Interpersonal mindfulness (IMS) 0.92 0.91 186 0.28 < 0.001 Psychological capital (CPC-R) 0.93 0.90 186 0.22 0.919 Anger reactivity (DA5) 0.8 0.74 186 -0.26 0.417 Psychological distress (K6) 0.92 0.87 186 -0.29 0.637 Prosocial behavioural intentions (PBIS) 0.85 0.78 186 0.03 0.718 McDonald’s Omega coefficient (ωt) and Cronbach’s alpha coefficient (α) provide an indication of internal consistency and scale reliability; r s : Spearman rank order correlations with p-values. Table 5 presents correlations between the self-report mindfulness data (FFMQ-SF, IMS) and the OMB data at subscale level, with variability in the strength of associations, as hypothesized. The OMB Attentiveness subscale data was convergent with the FFMQ Act with Awareness (r = 0.32), Non-react (r = 0.15) and Describe (r = 0.19) subscales, and with the IMS Awareness of Self (r = 0.23), Non-reactivity (r = 0.21) and Presence (r = 0.32) subscales. The OMB Awareness subscale converged with FFMQ Act with Awareness (r = 0.22) and Describe (r = 0.31), and with IMS Awareness of Self (r = 0.22), Non-reactivity (r = 0.21) and Presence (r = 0.25). The OMB Acceptance subscale also converged with FFMQ Act with Awareness (r = 0.19), Non-react (r = 0.28) and Describe (r = 0.19), and with IMS Non-reactivity (r = 0.24) and Presence (r = 0.16). Acceptance was the only OMB subscale that significantly converged with IMS Nonjudgmental acceptance (r = 0.15). Non-significant associations were noted across the board between OMB subscale data and FFMQ Non-judge data. The robustness of associations to identified covariates was assessed using linear regression (Supplementary Tables S.3 and S.4). OMB ratings were not influenced by observers' exposure to self-guided ( p = 0.985) or teacher-led mindfulness training ( p = 0.915), gender ( p = 0.427) or age ( p = 0.143). Further, the observer category (friend, family, spouse, colleague) did not reveal any significant influence on OMB ratings ( p’s > 0.223). However, OMB ratings were influenced by observer mindfulness (IMS, β = 0.15, p < 0.001, R 2 = 0.11). Our final regression models show OMB ratings were positively correlated with participants’ trait mindfulness (FFMQ, β = 0.42, p < 0.001, R 2 = 0.15), and with participants’ interpersonal mindfulness (IMS, β = 0.17, p < 0.001, R 2 = 0.12). Moderation analysis found no interaction effect of observer mindfulness and participant mindfulness on OMB scores (β = 0.00, p = 0.563). Table 5 Matrix of correlations between the subscales of three mindfulness measures: OMM, FFMQ-SF and IMS Variable number and label ω t α n 1 2 3 1 OMM Attentiveness 0.83 0.83 190 < 0.001 < 0.001 2 OMM Awareness 0.77 0.76 190 0.59 < 0.001 3 OMM Acceptance 0.78 0.77 190 0.57 0.53 4 FFMQ Act with awareness 0.73 0.72 186 0.32* 0.22* 0.19* 5 FFMQ Non-judge 0.85 0.84 186 0.14 0.10 0.13 6 FFMQ Non-react 0.73 0.73 186 0.15* 0.12 0.28* 7 FFMQ Describe 0.80 0.78 186 0.19* 0.31* 0.19* 8 IMS Awareness of self and others 0.89 0.87 186 0.23* 0.22* 0.11 9 IMS Nonjudgmental acceptance 0.73 0.69 186 0.04 0.08 0.15* 10 IMS Nonreactivity 0.81 0.77 186 0.21* 0.21* 0.24* 11 IMS Presence 0.90 0.85 186 0.32* 0.25* 0.16* McDonald’s Omega coefficient (ωt) and Cronbach’s alpha coefficient (α) provide an indication of internal consistency and scale reliability; r s = Spearman rank order correlations. Values in the lower triangle are correlation coefficients and in the top triangle are p-values. In nomological network tests, OMB data converged with the overall score for empathy (r = 0.19, p < 0.001) (H3b), with results pointing to a stronger alignment with personal discomfort in social situations (r=-0.24, p < 0.001) than perspective-taking (r = 0.08, p = 0.016). Results also support the hypothesized negative association of OMB data with psychological inflexibility scores (r=-0.31, p < 0.001) (H3d). However, the expected congruence of OMB scores with psychological capital (H3a) (r = 0.22, p = 0.919) and prosocial intentions (H3c) (r = 0.03, p = 0.718) was not supported. Also, non-significant correlations between the OMB scores and psychological distress (r=-0.29, p = 0.637) (H3e) and anger reactivity (r=-0.26, p = 0.417) (H3f) were observed. DISCUSSION This was a two-part study, that involved first testing a revised version of the original Observed Mindfulness Measure as published in (Bartlett et al., 2021 ) to address limitations in the measure, including the identified ceiling effect in the attentiveness dimension. After determining changes to be made to the original instrument, the first Aim for the project involved confirming the factorial structure of the new Observed Mindful Behaviours (OMB) scale in a separate dyadic sample, then assessing its construct validity. The resulting OMB is a 9-item observer-report instrument that shows good psychometric properties and clear associations with qualities that comprise individual and interpersonal mindfulness and psychological flexibility. The scale appears robust to variability in the level of mindfulness, age, and gender of respondents. There was no evidence of a ceiling effect. OMB scores showed consistent, moderate sized positive correlation with paired participants’ trait and interpersonal mindfulness scores. The positive correlation with participants self-reported empathy were also robust, as were the negative correlations with participants’ psychological inflexibility. However, the OMB did not converge significantly with behavioural constructs in the hypothesized nomological network – psychological capital, anger reactivity, psychological distress – and was not associated with prosocial behavioural intentions. The implications of these results and potential applications for the new measure are discussed. Scale refinement. Three revisions to the original measure (Bartlett et al., 2021 ) were tested to see if they improved item performance while retaining the three-dimensional scale structure (Aim 1). These revisions comprised use of gender-neutral terminology, re-testing a previously discarded item, and positively framing all items in the Attentiveness dimension. Our IRT analysis showed the returned item did not perform well and was again discarded from the item set. In contrast, the IRT models and item characteristic curves for the other three revised Attentiveness items showed better performance and more information about ability than in the original measure. The other revisions were supported by improved distributions and good psychometric performance of data collected by the OMB. However, we acknowledge that the distribution of OMB data from the separate community sample showed a trend for scores to be towards the top of the range. This could be a reflection of the mean self-reported mindfulness ratings in our sample, which were higher than normative scores (Asensio-Martinez et al., 2019 ). A finding that could be explained by the fact that 79% participants and 61% observers having engaged with formal mindfulness training. It is also feasible people with higher mindfulness may have been more likely to volunteer for this study. In terms of the performance of the OMB, we note the comparability of its relative goodness of fit (RMSEA = 0.07, CFI = 0.97) with fit indices reported in the development papers for the FFMQ-SF (RMSEA = 0.05 to 0.06; CFI = 0.95 to 0.96) (Bohlmeijer et al., 2011 ), and the IMS (RMSEA = 0.05; CFI = 0.91) (Pratscher et al., 2018 ). Collectively, the structural, item performance and distribution suggest the new OMB has satisfactory psychometric properties. Validity . In criterion validity tests, OMB scores corresponded with trait and interpersonal mindfulness scores. This means that Observer OMB ratings were higher when their paired Participant’s self-reported mindfulness ratings were higher. However, the magnitude of association was moderate at best, which indicates that the OMB, FFMQ-SF and IMS scales measure related but discrepant constructs. This result helps clarify the construct validity of the OMB, as a measure of noticeable behaviours that are attentive, aware and accepting, not the internal states that may be driving them . In the regression models, where known covariates (age, gender, engagement with mindfulness training) were accounted for, the relationships between OMB scores and FFMQ and IMS scores were shown to be robust, and to account for between 11% and 15% variance. This result indicates a meaningful relationship in behavioural and psychological research (Brydges, 2019 ). Further, while OMB ratings were sensitive to the self-reported interpersonal mindfulness of observers, there was no interaction effect of the observers’ IMS and participants’ FFMQ-SF scores on OMB results. The reported results support the criterion validity of the OMB. Multi-dimensional measures present the opportunity to investigate relationships between and effects on constructs at a more granular level than using overall total scores (Duan & Li, 2016 ). Indeed some facets of mindfulness have been noted already to differentially influence social behaviours (Adnoy et al., 2023 ). As expected, there was some variability in the strength of association between the three OMB dimensions (Attentiveness, Awareness and Acceptance) when tested against the FFMQ-SF subscales (Act with awareness, Nonjudging, Nonreacting and Describing) and the IMS subscales (Awareness of self and others, Nonjudgmental acceptance, Nonreactivity and Presence). We posit this variability may be helpful for gaining a better understanding of the factors that drive mindful acting, and may also help determine aspects of mindfulness that are dispositional and/or cultivated (Duan & Li, 2016 ). To illustrate: the awareness subscales of FFMQ and IMS were significantly and positively associated with both the OMB attentiveness and awareness sub-scales, but not with OMB acceptance. This helps clarify how being mindfully aware comes across to others. Similarly, non-reactivity in the FFMQ and IMS instruments were both significantly associated with OMB acceptance and attentiveness, but not OMB awareness. Thus, it may be mindful attentiveness and acceptance are responsible for being noticeably non-reactive, rather than mindful awareness. Previous research has identified the non-judging facet of the FFMQ to be more aligned with flexibility in cognition and emotional experience, while acting with awareness, describing and non-reactivity aligned with presence and openness to experience (Adnoy et al., 2023 ). It is plausible that non-judging involves cognitive and emotional processes that are internal, and therefore not observable to others; while being present and open when engaging with others are indeed noticeable behaviours. Such mechanistic conclusions cannot be supported in the current data, however we propose the OMB can be used to help explore the relationships reported between mindfulness, prosociality and moral acting (Berry et al., 2020 ; Donald et al., 2019 ; Malin, 2023 ). Based on our hypotheses, construct validity would be supported by correlations between OMB total scores showing convergence with measures of psychological capital (H3a), empathy (H3b) and prosocial intentions (H3c), and divergence with psychological inflexibility (H3d), psychological distress (H3e) and anger reactivity (H3f). This proposed nomological network was based on previously reported moderate sized within-person correlations between self-reported mindfulness, empathy and psychological inflexibility (Guo, 2024 ), PsyCap (Ali et al., 2021 ; Liu et al., 2024 ), distress (Carpenter et al., 2019 ) and anger reactivity (Richard et al., 2022 ). Participants’ empathy scores were significantly and positively correlated with the observers’ OMB ratings. Empathy is understood to be an antecedent of prosocial behaviours and has been used as a proxy in mindfulness research to understand social effects of mindfulness (Donald et al., 2019 ; Van Doesum et al., 2013 ). The differential association between empathy subscales suggests higher OMB data may detect discomfort in social settings, but is less able to detect the more internal process of perspective taking. Construct validity was further supported by the robust negative correlation between OMB and the measure of psychological inflexibility. Defined as a rigid responding to inner experiences (e.g. thoughts, feelings) in ways that interfere with well-being and the pursuit of valued actions (Hayes et al., 2006 ), psychological inflexibility is, by definition, nearly anti-thetic to the intentional awareness and acceptance qualities of mindfulness (Ong et al., 2024 ). The AAQ used in this study has frequently been included in the nomological networks for testing the validity of self-reported mindfulness measures (Baer et al., 2009 ; Chems-Maarif et al., 2025 ). The magnitude of the OMB:AAQ-2 correlation was lower than observed in self-report data; again potentially explained by the kinds of information observers have access to, relative to the person being observed (Varela & Shear, 1999 ). However, the OMB did not show the expected positive correlation with prosocial behavioural intentions or psychological capital, or the negative correlations with psychological distress and anger reactivity. While strong associations with self-reported mindfulness have previously been found with these constructs, our findings concur with Malin ( 2023 ) who concluded the relationship between mindfulness and prosocial behaviour is not straightforward. Potentially our results could help show that the reactivity associated with anger and distress may not translate into action in people with higher levels of mindfulness. This explanation is in keeping with decentering and reperceiving, core skills associated with mindfulness which enable non-attachment, or not being in ‘the thrall’ of emotions, and greater capacity for flexible or adaptive responding (Adnoy et al., 2023 ; Biggs et al., 2017 ; Guo, 2024 ). A unique contribution of the OMB is that it detects how behaviours are enacted in social engagements, rather than the internal drivers for those behaviours. Our results only partly support the construct validity hypotheses developed for this study. However, they are in accordance with the focus of the OMB on the nature of observable behaviours, rather than intentions, and help clarify the construct that the new scale is measuring. The observer-report OMB appears to provide valid data relating to the extent to which another known person behaves in a way that is consistent with the qualities that characterise self-reported mindfulness. In line with others work (Berry et al., 2020 ; Hölzel et al., 2011 ) our OMB data indicate the self-regulatory processes of directing attention to, and accepting what is occurring in the present moment support the capacity for non-reactivity. The OMB could be used in research investigating mechanisms driving external, beneficial effects of mindfulness found through other methods in clinical practice (Braun et al., 2018 ; Epstein et al., 2003 ), in schools (Montero-Marin et al., 2022 ; Tudor et al., 2022 ) and in workplaces (Arendt et al., 2019 ; Sutton, 2023 ). Limitations and future research. Measurement in mindfulness research has its complexities and there are diverging views on the conceptualisation and operationalisation of the construct (Van Dam et al., 2017 ). These differences are steeped in theoretical/historical literature (e.g. Buddhist teachings vs psychological sciences); timing (e.g. state vs trait) and function (e.g. dispositional vs cultivated). However, in developing the OMB we have followed guidance by Sauer et al. ( 2012 ) and included items relating to behaviours, attitudes and cognitions (e.g. The person seems aware of their own emotions when interacting with others ) , rather than felt experiences such as calm or peace that may arise as a result of higher mindfulness. We acknowledge that our FFMQ-SF instrument was not the full scale as published by Baer et al. ( 2006 ), however to minimise responder burden the briefer measure was selected, based on validation work conducted by Gu et al. ( 2016 ). Confidence in the contribution of OMB data will benefit from establishing associations with other measures of trait mindfulness, such as the Mindful Awareness and Acceptance Scale (Brown & Ryan, 2003 ) or the Freiberg Mindfulness Inventory (Walach et al., 2006 ). Further, a mixed methods study combining OMB and interview data from dyadic participants with and without exposure to mindfulness training would be very informative. Such future work could provide valuable contextual and phenomenological data to clarify if and how the internal quality of mindfulness influences outcomes beyond the self, into social and performance domains. In our community sample, around 80% of participants and two-thirds of observers had previously engaged in formal mindfulness training, which is not likely to be representative of the general population. To address this self-selection bias, future research using community samples should aim to include more participants and observers with no formal mindfulness training. The single-observer design in the current study also may be susceptible to rater-specific biases, which could be overcome using multiple observers to rate the same participant. Future iterations of the OMB could be augmented with items that detect the non-judging facet of trait mindfulness, that can help better understand the contribution of acceptance in social interactions and behaviours. Lastly, to confirm the investigative utility of the OMB, controlled longitudinal studies are required, as its test-retest reliability and sensitivity to change still need to be proven. CONCLUSIONS The OMB supersedes the Observed Mindfulness Measure and can be used to provide researchers another perspective with which to study behaviours associated with mindfulness. The new OMB scale detects the extent to which a person known to the rater (family, friend or colleague) behaves in a way that is noticeably attentive, aware and accepting (or mindful). Alignment with behavioural drivers (empathy, acceptance) but not behavioural states (distress, anger, intentions), or with psychological capital, helps clarify what the OMB assesses. OMB data, which can be collected inexpensively and at scale, can be used to triangulate and strengthen self-reported findings and help examine how mindfulness comes across to others. The variable correlations between OMB subscales and facets of self-reported trait and interpersonal mindfulness suggest different aspects of mindfulness are more or less evident in social interactions, and may help build a better understanding of the mechanisms driving prosocial behaviours and moral acting. Declarations Author contributions All authors made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; drafted the work or revised it critically for important intellectual content; approved the version to be published; and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Conflicts of interest The authors have no relevant financial or non-financial interests to declare. The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Ethical approvals The study was approved by the [REMOVED] Human Research Ethics Committee (REF: [REMOVED]) and conducted in accordance with the National Statement on Ethical Conduct in Human Research 2023. Consent Informed consent to participate in the research and for the publication of research outputs was obtained from all participants via an online form. Funding Partial financial support was received from a philanthropic fund held by the [REMOVED]. Data availability The data used in this study and the analysis code will be made available by the corresponding author for research purposes on reasonable request. References Adnoy, T., Solem, S., Hagen, R., & Havnen, A. (2023). An empirical investigation of the associations between metacognition, mindfulness experiential avoidance, depression, and anxiety. BMC Psychol , 11 (1), 281. https://doi.org/10.1186/s40359-023-01336-7 Ali, M., Khan, A. N., Khan, M. M., Butt, A. S., & Shah, S. H. H. (2021). Mindfulness and study engagement: mediating role of psychological capital and intrinsic motivation. Journal of Professional Capital and Community , 7 (2), 144-158. https://doi.org/10.1108/jpcc-02-2021-0013 Arendt, J. F. W., Pircher Verdorfer, A., & Kugler, K. G. (2019). Mindfulness and Leadership: Communication as a Behavioral Correlate of Leader Mindfulness and Its Effect on Follower Satisfaction [10.3389/fpsyg.2019.00667]. Frontiers in Psychology , 10 , 667. Asensio-Martinez, A., Masluk, B., Montero-Marin, J., Olivan-Blazquez, B., Navarro-Gil, M. T., Garcia-Campayo, J., & Magallon-Botaya, R. (2019). Validation of Five Facets Mindfulness Questionnaire - Short form, in Spanish, general health care services patients sample: Prediction of depression through mindfulness scale. PLOS ONE , 14 (4), e0214503. https://doi.org/10.1371/journal.pone.0214503 Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using Self-Report Assessment Methods to Explore Facets of Mindfulness. Assessment , 13 (1), 27-45. https://doi.org/10.1177/1073191105283504 Baer, R. A., Walsh, E., & Lykins, E. L. (2009). Assessment of Mindfulness. In Clinical Handbook of Mindfulness (pp. 153-168). Springer. Bartlett, L., and Lovell, P., and Otahal, P., & and Sanderson, K. (2016). Acceptability, Feasibility, and Efficacy of a Workplace Mindfulness Program for Public Sector Employees: a Pilot Randomized Controlled Trial with Informant Reports. Mindfulness , 1--16. https://doi.org/10.1007/s12671-016-0643-4 Bartlett, L., Martin, A., Sanderson, K., & Neil, A. (2022). Observed Mindfulness Measure (OMM). In O. N. Medvedev, C. U. Krageloh, R. J. Siegert, & N. N. Singh (Eds.), Handbook of Assessment in Mindfulness Research (pp. 1-17). Springer Link. https://doi.org/10.1007/978-3-030-77644-2_89-1 Bartlett, L., Martin, A. J., Bruno, R., Kilpatrick, M., Sanderson, K., & Neil, A. L. (2021). Is Mindfulness a Noticeable Quality? Development and Validation of the Observed Mindfulness Measure. Journal of Psychopathology & Behavioral Assessment , 44 , 165-185. https://doi.org/10.1007/s10862-021-09936-6 Baumsteiger, R., & Siegel, J. T. (2019). Measuring Prosociality: The Development of a Prosocial Behavioral Intentions Scale. J Pers Assess , 101 (3), 305-314. https://doi.org/10.1080/00223891.2017.1411918 Beach, M. C., Roter, D., Korthuis, P. T., Epstein, R. M., Sharp, V., Ratanawongsa, N., Cohn, J., Eggly, S., Sankar, A., Moore, R. D., & Saha, S. (2013). A multicenter study of physician mindfulness and health care quality. Ann Fam Med , 11 (5), 421-428. https://doi.org/10.1370/afm.1507 Beaujean, A. A. (2014). Latent Variable Modeling Using R: A Step-by-Step Guide (1st ed.). Routledge. https://doi.org/10.4324/9781315869780 Berry, D. R., Hoerr, J. P., Cesko, S., Alayoubi, A., Carpio, K., Zirzow, H., Walters, W., Scram, G., Rodriguez, K., & Beaver, V. (2020). Does Mindfulness Training Without Explicit Ethics-Based Instruction Promote Prosocial Behaviors? A Meta-Analysis. Pers Soc Psychol Bull , 46 (8), 1247-1269. https://doi.org/10.1177/0146167219900418 Biggs, A., Brough, P., Drummond, S., Quick, J. C., & Cooper, C. L. (2017). Lazarus and Folkman's Psychological Stress and Coping Theory. In (pp. 349-364). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781118993811.ch21 Bohlmeijer, E., ten Klooster, P. M., Fledderus, M., Veehof, M., & Baer, R. (2011). Psychometric properties of the five facet mindfulness questionnaire in depressed adults and development of a short form. Assessment , 18 (3), 308-320. https://doi.org/10.1177/1073191111408231 Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., & Zettle, R. D. (2011). Preliminary psychometric properties of the Acceptance and Action Questionnaire–II: A revised measure of psychological inflexibility and experiential avoidance. Behavior Therapy , 42 (4), 676-688. https://doi.org/10.1016/j.beth.2011.03.007 Brauer, K., & Proyer, R. T. (2019). Dyadic Effects. In V. Zeigler-Hill & T. K. Shackelford (Eds.), Encyclopedia of Personality and Individual Differences (pp. 1-5). Springer International Publishing. https://doi.org/10.1007/978-3-319-28099-8_656-1 Braun, S. E., Kinser, P. A., & Rybarczyk, B. (2018). Can mindfulness in health care professionals improve patient care? An integrative review and proposed model. Translational Behavioral Medicine , iby059-iby059. https://doi.org/10.1093/tbm/iby059 Brown, C. L., West, T. V., Sanchez, A. H., & Mendes, W. B. (2021). Emotional Empathy in the Social Regulation of Distress: A Dyadic Approach. Personality and Social Psychology Bulletin , 47 (6), 1004-1019. https://doi.org/10.1177/0146167220953987 Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology , 84 (4), 822-848. https://doi.org/10.1037/0022-3514.84.4.822 Brydges, C. R. (2019). Effect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology. Innov Aging , 3 (4), igz036. https://doi.org/10.1093/geroni/igz036 Carpenter, J. K., Conroy, K., Gomez, A. F., Curren, L. C., & Hofmann, S. G. (2019). The relationship between trait mindfulness and affective symptoms: A meta-analysis of the Five Facet Mindfulness Questionnaire (FFMQ). Clin Psychol Rev , 74 , 101785. https://doi.org/10.1016/j.cpr.2019.101785 Chems-Maarif, R., Cavanagh, K., Baer, R., Gu, J., & Strauss, C. (2025). Defining Mindfulness: A Review of Existing Definitions and Suggested Refinements. Mindfulness , 16 (1), 1-20. https://doi.org/10.1007/s12671-024-02507-2 Curtiss, J., & Klemanski, D. H. (2014). Teasing apart low mindfulness: Differentiating deficits in mindfulness and in psychological flexibility in predicting symptoms of generalized anxiety disorder and depression. Journal of Affective Disorders , 166 , 41-47. https://doi.org/https://doi.org/10.1016/j.jad.2014.04.062 DeVellis, R. F., & Thorpe, C. T. (2022). Scale development: theory and applications (Fifth edition. ed., Vol. 26). SAGE. Donald, J. N., Sahdra, B. K., Van Zanden, B., Johannes Duineveld, J., Atkins, P. W. B., Marshall, S., & Ciarrochi, J. (2019). Does Your Mindfulness Benefit Others? A Systematic Review and Meta-Analysis of the Link Between Mindfulness and Prosocial Behavior. British Journal of Psychology , 110 (1), 101-125. https://doi.org/10.1111/bjop.12338 Duan, W., & Li, J. (2016). Distinguishing Dispositional and Cultivated Forms of Mindfulness: Item-Level Factor Analysis of Five-Facet Mindfulness Questionnaire and Construction of Short Inventory of Mindfulness Capability. Front Psychol , 7 , 1348. https://doi.org/10.3389/fpsyg.2016.01348 Dudasova, L., Prochazka, J., Vaculik, M., & Lorenz, T. (2021). Measuring psychological capital: Revision of the Compound Psychological Capital Scale (CPC-12). PLOS ONE , 16 (3), e0247114. https://doi.org/10.1371/journal.pone.0247114 Epstein, D. H., Hawkins, W. E., Covi, L., Umbricht, A., & Preston, K. L. (2003). Cognitive-behavioral therapy plus contingency management for cocaine use: findings during treatment and across 12-month follow-up. Psychol Addict Behav , 17 (1), 73-82. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1224747/pdf/NIHMS2061.pdf Forbes, D., Alkemade, N., Mitchell, D., Elhai, J. D., McHugh, T., Bates, G., Novaco, R. W., Bryant, R., & Lewis, V. (2014). Utility of the Dimensions of Anger-5 (DAR-5) Scale as a Brief Anger Measure. Depression and Anxiety , 31 (2), 166-173. https://doi.org/10.1002/da.22148 Goldberg, S. B., Tucker, R. P., Greene, P. A., Simpson, T. L., Kearney, D. J., & Davidson, R. J. (2017). Is mindfulness research methodology improving over time? A systematic review. PLOS ONE , 12 (10). https://doi.org/10.1371/journal.pone.0187298 Gu, J., Strauss, C., Crane, C., Barnhofer, T., Karl, A., Cavanagh, K., & Kuyken, W. (2016). Examining the factor structure of the 39-item and 15-item versions of the Five Facet Mindfulness Questionnaire before and after mindfulness-based cognitive therapy for people with recurrent depression. Psychological Assessment , 28 (7), 791-802. https://doi.org/10.1037/pas0000263 Guo, L. (2024). The Correlation Between Mindfulness, Decentering, and Psychological Problems: A Structural Equation Modeling Meta-Analysis. Mindfulness , 15 (8), 1873-1895. https://doi.org/10.1007/s12671-024-02395-6 Haig, B. D. (2023). Repositioning Construct Validity Theory: From Nomological Networks to Pragmatic Theories and Their Evaluation by Explanatory Means. Perspectives on Psychological Science , 17456916231195852. https://doi.org/10.1177/17456916231195852 Hayes, S. C., Luoma, J. B., Bond, F. W., Masuda, A., & Lillis, J. (2006). Acceptance and commitment therapy: Model, processes and outcomes. Behaviour Research and Therapy , 44 (1), 1-25. Hölzel, B. K., Lazar, S. W., Gard, T., Schuman-Olivier, Z., Vago, D. R., & Ott, U. (2011). How Does Mindfulness Meditation Work? Proposing Mechanisms of Action From a Conceptual and Neural Perspective. Perspectives on Psychological Science , 6 (6), 537-559. https://doi.org/10.1177/1745691611419671 Ingoglia, S., Lo Coco, A., & Albiero, P. (2016). Development of a Brief Form of the Interpersonal Reactivity Index (B-IRI). Journal of Perssonality Assessment , 98 (5), 461-471. https://doi.org/10.1080/00223891.2016.1149858 Kabat-Zinn, J. (2013). Full Catastrophe Living: How to cope with stress, pain and illness using mindfulness meditation . Piatkus. https://doi.org/10.1002/shi.88 (1996) Keng, S. L., Smoski, M. J., & Robins, C. J. (2011). Effects of mindfulness on psychological health: a review of empirical studies. Clin Psychol Rev , 31 (6), 1041-1056. https://doi.org/10.1016/j.cpr.2011.04.006 Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S. L. T., Walters, E. E., & Zaslavsky, A. M. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine , 32 (6), 959-976. Khoury, B., Vergara, R. C., & Spinelli, C. (2022). Interpersonal Mindfulness Questionnaire: Scale Development and Validation. Mindfulness (N Y) , 1-25. https://doi.org/10.1007/s12671-022-01855-1 Kreplin, U., Farias, M., & Brazil, I. A. (2018). The limited prosocial effects of meditation: A systematic review and meta-analysis. Scientific Reports , 8 (1), 2403. https://doi.org/10.1038/s41598-018-20299-z Lietz, P. (2010). Research into Questionnaire Design: A Summary of the Literature. International Journal of Market Research , 52 (2), 249-272. https://doi.org/10.2501/S147078530920120X Liu, N., Cao, Y., & Xu, H. (2024). Prosocial behavior associated with trait mindfulness, psychological capital and moral identity among medical students: a moderated mediation model. Front Psychol , 15 , 1431861. https://doi.org/10.3389/fpsyg.2024.1431861 Luthans, F., & Broad, J. D. (2022). Positive psychological capital to help combat the mental health fallout from the pandemic and VUCA environment. Organ Dyn , 51 (2), 100817. https://doi.org/10.1016/j.orgdyn.2020.100817 Luthans, F., & Youssef-Morgan, C. M. (2017). Psychological Capital: An Evidence-Based Positive Approach. Annual Review of Organizational Psychology and Organizational Behavior , 4 (1), 339-366. https://doi.org/10.1146/annurev-orgpsych-032516-113324 Malin, Y. (2023). Others in Mind: A Systematic Review and Meta-Analysis of the Relationship Between Mindfulness and Prosociality. Mindfulness , 14 (7), 1582-1605. https://doi.org/10.1007/s12671-023-02150-3 May, L. M., & Reinhardt, K. M. (2018). Self-Other Agreement in the Assessment of Mindfulness Using the Five-Facet Mindfulness Questionnaire. Mindfulness , 9 (1), 105-116. https://doi.org/10.1007/s12671-017-0749-3 Montero-Marin, J., Allwood, M., Ball, S., Crane, C., De Wilde, K., Hinze, V., Jones, B., Lord, L., Nuthall, E., Raja, A., Taylor, L., Tudor, K., Team, M., Blakemore, S. J., Byford, S., Dalgleish, T., Ford, T., Greenberg, M. T., Ukoumunne, O. C.,…Kuyken, W. (2022). School-based mindfulness training in early adolescence: what works, for whom and how in the MYRIAD trial? Evid Based Ment Health . https://doi.org/10.1136/ebmental-2022-300439 Morin, L., Laurin, J. C., Doucerain, M., & Grégoire, S. (2024). A Multilevel Diary and Dyadic Study Exploring the Link Between New Parents’ Mindfulness and Relationship Satisfaction. Mindfulness , 15 (9), 2330-2346. https://doi.org/10.1007/s12671-024-02437-z Nilsson, H., & Kazemi, A. (2016). Reconciling and Thematizing Definitions of Mindfulness: The Big Five of Mindfulness. Review of General Psychology , 20 (2), 183-193. https://doi.org/10.1037/gpr0000074 Nitschke, J. P., & Bartz, J. A. (2023). The association between acute stress & empathy: A systematic literature review. Neuroscience & Biobehavioral Reviews , 144 , 105003. https://doi.org/https://doi.org/10.1016/j.neubiorev.2022.105003 Ong, C. W., Barthel, A. L., & Hofmann, S. G. (2024). The Relationship Between Psychological Inflexibility and Well-Being in Adults: A Meta-Analysis of the Acceptance and Action Questionnaire. Behav Ther , 55 (1), 26-41. https://doi.org/10.1016/j.beth.2023.05.007 Orosz, G., Evans, K. M., Török, L., Bőthe, B., Tóth-Király, I., Sik, K., & Gál, É. (2023). The Differential Role of Growth Mindset and Trait Mindfulness in the Motivation of Learning from Criticism. Mindfulness , 14 (4), 868-879. https://doi.org/10.1007/s12671-023-02117-4 Pratscher, S. D., Wood, P. K., King, L. A., & Bettencourt, B. A. (2018). Interpersonal Mindfulness: Scale Development and Initial Construct Validation. Mindfulness , 10 (6), 1044-1061. https://doi.org/10.1007/s12671-018-1057-2 Reina, C. S., Mills, M. J., & Sumpter, D. M. (2023). A mindful relating framework for understanding the trajectory of work relationships. Personnel Psychology , 76 (4), 1187-1215. https://doi.org/10.1111/peps.12530 Revelle, W. (2014). psych: Procedures for Personality and Psychological Research (V1.7.8). In. Illinois: Northwestern University Richard, Y., Tazi, N., Frydecka, D., Hamid, M. S., & Moustafa, A. A. (2022). A systematic review of neural, cognitive, and clinical studies of anger and aggression. Curr Psychol , 1-13. https://doi.org/10.1007/s12144-022-03143-6 Roche, M., Haar, J. M., & Luthans, F. (2014). The role of mindfulness and psychological capital on the well-being of leaders. Journal of Occupational Health Psychology , 19 (4), 476. https://doi.org/10.1037/a0037183 Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software , 48 (2), 1-36. Rudkin, E., Medvedev, O. N., & Siegert, R. J. (2018). The Five-Facet Mindfulness Questionnaire: Why the Observing Subscale Does Not Predict Psychological Symptoms. Mindfulness , 9 (1), 230-242. https://doi.org/10.1007/s12671-017-0766-2 Sauer, S., Walach, H., Schmidt, S., Hinterberger, T., Lynch, S., Büssing, A., & Kohls, N. (2012). Assessment of Mindfulness: Review on State of the Art. Mindfulness , 4 (1), 3-17. https://doi.org/10.1007/s12671-012-0122-5 Scott, D., Derrett, S., Rupel, V. P., Jelsma, J., Gurung, G., Oduro, G. Y., & Withey-Rila, C. (2025). He/She/They - gender inclusivity in developing and using health-related questionnaires: a scoping review. Qual Life Res , 34 (1), 67-87. https://doi.org/10.1007/s11136-024-03765-2 Simonsson, O., Bergljottsdotter, C., Narayanan, J., Fisher, S., Bristow, J., Ormston, R., & Chambers, R. (2023). Mindfulness in Politics: A Qualitative Study on Mindfulness Training in the UK Parliament. Mindfulness , 1-9. https://doi.org/10.1007/s12671-023-02156-x Sofer, O. J. (2018). Say what you mean: A mindful approach to nonviolent communication . Shambhala Publications. Sutton, A. (2023). Cultivating Global Health: Exploring Mindfulness Through an Organisational Psychology Lens. Mindfulness . https://doi.org/10.1007/s12671-023-02228-y Tindle, R., Hemi, A., & Moustafa, A. A. (2022). Social support, psychological flexibility and coping mediate the association between COVID-19 related stress exposure and psychological distress. Sci Rep , 12 (1), 8688. https://doi.org/10.1038/s41598-022-12262-w Tudor, K., Maloney, S., Raja, A., Baer, R., Blakemore, S. J., Byford, S., Crane, C., Dalgleish, T., De Wilde, K., Ford, T., Greenberg, M., Hinze, V., Lord, L., Radley, L., Opaleye, E. S., Taylor, L., Ukoumunne, O. C., Viner, R., Team, M.,…Montero-Marin, J. (2022). Universal Mindfulness Training in Schools for Adolescents: a Scoping Review and Conceptual Model of Moderators, Mediators, and Implementation Factors. Prev Sci . https://doi.org/10.1007/s11121-022-01361-9 Van Dam, N. T., van Vugt, M. K., Vago, D. R., Schmalzl, L., Saron, C. D., Olendzki, A., Meissner, T., Lazar, S. W., Kerr, C. E., Gorchov, J., Fox, K. C. R., Field, B. A., Britton, W. B., Brefczynski-Lewis, J. A., & Meyer, D. E. (2017). Mind the Hype: A Critical Evaluation and Prescriptive Agenda for Research on Mindfulness and Meditation. Perspectives on Psychological Science , 13 (1), 36-61. https://doi.org/10.1177/1745691617709589 van der Schans, K. L., van Kraaij, J. A. M., & Karremans, J. C. (2022). Through mindful colored glasses? The role of trait mindfulness in evaluating interactions with strangers. Journal of Social and Personal Relationships . https://doi.org/10.1177/02654075221119770 Van Doesum, N. J., Van Lange, D. A. W., & Van Lange, P. A. M. (2013). Social mindfulness: Skill and will to navigate the social world. Journal of Personality and Social Psychology , 105 (1), 86-103. https://doi.org/10.1037/a0032540 Varela, F. J., & Shear, J. (1999). First-person Methodologies: What, Why, How? Journal of Consciousness Studies , 6 (2-3), 1-14. Walach, H., Buchheld, N., Buttenmüller, V., Kleinknecht, N., & Schmidt, S. (2006). Measuring mindfulness—the Freiburg Mindfulness Inventory (FMI). Personality and Individual Differences , 40 (8), 1543-1555. https://doi.org/10.1016/j.paid.2005.11.025 Whitehouse, J., Milward, S. J., Parker, M. O., Kavanagh, E., & Waller, B. M. (2022). Signal value of stress behaviour. Evolution and Human Behavior , 43 (4), 325-333. https://doi.org/10.1016/j.evolhumbehav.2022.04.001 Zhang, Y., Wang, Q., & Zhang, Y. (2023). The Impact of Mindful Communication on Cooperative Orientation: A Cross-Sectional Survey and an RCT Study. Mindfulness , 15 (1), 100-119. https://doi.org/10.1007/s12671-023-02278-2 Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s α, Revelle’s β, and Mcdonald’s ωH: their relations with each other and two alternative conceptualizations of reliability. Psychometrika , 70 (1), 123-133. https://doi.org/10.1007/s11336-003-0974-7 Additional Declarations No competing interests reported. Supplementary Files OMBSupplementarymaterialsblind.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6755370","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":465359172,"identity":"659975f2-de36-4db1-ba8b-7c58e93d2ae0","order_by":0,"name":"Larissa Bartlett","email":"data:image/png;base64,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","orcid":"","institution":"University of Tasmania","correspondingAuthor":true,"prefix":"","firstName":"Larissa","middleName":"","lastName":"Bartlett","suffix":""},{"id":465359173,"identity":"00447b12-3922-4e20-9c6e-edaa7be9306a","order_by":1,"name":"Rohan Puri","email":"","orcid":"","institution":"University of Tasmania","correspondingAuthor":false,"prefix":"","firstName":"Rohan","middleName":"","lastName":"Puri","suffix":""},{"id":465359174,"identity":"b6bc86de-340a-4eb2-af25-df2c0feafadd","order_by":2,"name":"Amanda Neil","email":"","orcid":"","institution":"University of Tasmania","correspondingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"","lastName":"Neil","suffix":""},{"id":465359175,"identity":"9c176232-4036-4513-881d-5d083c95626e","order_by":3,"name":"Craig Hassed","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Craig","middleName":"","lastName":"Hassed","suffix":""},{"id":465359176,"identity":"60f4edef-0955-4c5a-b802-91014d3047e8","order_by":4,"name":"Jakob Hohwy","email":"","orcid":"","institution":"Monash University","correspondingAuthor":false,"prefix":"","firstName":"Jakob","middleName":"","lastName":"Hohwy","suffix":""}],"badges":[],"createdAt":"2025-05-27 04:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6755370/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6755370/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83853255,"identity":"93e25c29-9b02-45f6-8951-bea9a2ec2058","added_by":"auto","created_at":"2025-06-03 16:43:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":117049,"visible":true,"origin":"","legend":"\u003cp\u003eItem characteristic curves showing probability function (upper figure) and test information (lower figure) for the OMM and OMB attentiveness items. Item Response Theory models used a generalised partial credit model for ordinal, polytomous data.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6755370/v1/9a9954a7b192cf15f41cc03a.png"},{"id":83853410,"identity":"6b8c8eab-d039-4354-9ca7-21b5a233b1f8","added_by":"auto","created_at":"2025-06-03 16:51:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82479,"visible":true,"origin":"","legend":"\u003cp\u003eTree-diagram from confirmatory factor analysis, where single-headed arrows connect latent variables (circles) to observed variables (rectangles) with numbers representing standardized factor loadings. Bi-directional arrows represent correlations between latent variables (Awr: Awareness; Att: Attention; Acc: Acceptance).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6755370/v1/951ac0feead3c18de67f61cb.png"},{"id":85073237,"identity":"605c70c7-eb71-425a-ad91-f5939338e624","added_by":"auto","created_at":"2025-06-20 16:00:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1141080,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6755370/v1/2a604b43-eb34-4c93-bd99-002a0ffc2289.pdf"},{"id":85072282,"identity":"c0e97461-6df8-4b0d-b444-51d7309d3d2e","added_by":"auto","created_at":"2025-06-20 15:52:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":100393,"visible":true,"origin":"","legend":"","description":"","filename":"OMBSupplementarymaterialsblind.docx","url":"https://assets-eu.researchsquare.com/files/rs-6755370/v1/b5eae74a4a68fbda9eedfc36.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Observed Mindful Behaviours scale","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThere is encouraging evidence that mindfulness influences prosocial behaviours (Berry et al., 2020; Donald et al., 2019; Malin, 2023) and positive relationships in work, leadership and health-care contexts (Arendt et al., 2019; Beach et al., 2013). This line of research extends common narratives of mindfulness to include a focus not just on how we feel, but \u003cem\u003ehow we behave\u0026nbsp;\u003c/em\u003ein social settings. This more expansive lens is in keeping with traditional teachings in Buddhism (Thera, 1998), in which the \u003cem\u003eway\u003c/em\u003e of mindfulness as a form of mental discipline is fundamental to living with wisdom (intentionality and broad perspective) and moral conduct (action, speech and livelihood).\u003c/p\u003e\n\u003cp\u003eDespite its roots being about living with wisdom and morality, mindfulness is a construct that is largely conceptualised in research as an internal quality. Variously described in the literature, it can be thought of as a tendency for certain attitudinal and attentional processes which create a way of being, characterised by present-centered attention, awareness of internal states and circumstances, with an attitude of open heartedness and curiosity (Baer et al., 2009; Chems-Maarif et al., 2025; Kabat-Zinn, 2013). Variations on this conceptualisation have informed the development of self-report questionnaires used in research to assess the extent to which participants are mindful (Goldberg et al., 2017; Nilsson \u0026amp; Kazemi, 2016).\u003c/p\u003e\n\u003cp\u003eThe conceptualisation and measurement of \u003cem\u003einterpersonal\u003c/em\u003e mindfulness has evolved the focus of these self-report mindfulness measures from being on the self in general, to the self in social settings (Khoury et al., 2022; Pratscher et al., 2018). The use of interpersonal mindfulness measures in research has contributed to our understanding of the positive influence of an individual\u0026rsquo;s mindfulness on personal relationships (e.g. Morin et al., 2024) and work dynamics (e.g. Reina et al., 2023). However, self-report measures necessarily rely on the views of the respondent, about how they feel and behave in social engagements, so findings may be subject to responder bias (Goldberg et al., 2017; Kreplin et al., 2018). An additional approach for assessing the impacts of mindfulness beyond the self is to ask about behaviours that are noticeable to others \u003cem\u003eand\u0026nbsp;\u003c/em\u003econgruent with the construct of mindfulness, as measured by self-report. This approach is aligned with research into other trait-like qualities (e.g. personality; Brauer \u0026amp; Proyer, 2019), and is premised on evidence that self-reported mindfulness aligns with, but does not exactly mirror, how one\u0026rsquo;s mindfulness is perceived by others (Bartlett et al., 2016; May \u0026amp; Reinhardt, 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBartlett et al. (2021) developed a novel Observed Mindfulness Measure (OMM), by adapting items used in self-report mindfulness questionnaires for observer-report. The assessed construct was defined as \u003cem\u003ethe noticeable tendency of another person to be mindful: attentive to and aware of current experience, and displaying an attitude of curiosity, openness and acceptance\u003c/em\u003e. The nine-item questionnaire had good psychometric properties for a three-dimensional construct \u0026ndash; attentiveness, awareness, and acceptance \u0026ndash; with a common latent variable. The validation study used dyadic data formed by the views of one person about themselves (the participant) and the views of another person nominated by the participant about the typical behaviour of that participant (the observer), to test correspondence of OMM with self-reported mindfulness and other related constructs. The construct validity of the OMM was supported, but some limitations were identified. Notably, a ceiling effect in the attentiveness dimension (the only dimension in which items were negatively worded)limited the measure\u0026rsquo;s potential to detect positive change., Further, the OMM\u0026rsquo;s use of gendered terms is exclusory; and not best practice in health research (Scott et al., 2025). In addition, clarification of the construct being assessed by the scale may enable greater insight into what it means to behave mindfully. Further, the second-person, behavioural perspective presents a valuable opportunity to study whether qualities such as mindful attentiveness, awareness, and acceptance are instrumental in driving behaviour (Bartlett et al., 2021; Goldberg et al., 2017; Varela \u0026amp; Shear, 1999).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe second-person, behavioural perspective taken with the OMM presents a different lens through which to study whether qualities such as mindful attentiveness, awareness, and acceptance are instrumental in driving prosocial behaviours (Goldberg et al., 2017; Varela \u0026amp; Shear, 1999). We propose the approach taken with the OMM may help elucidate if, when, and how a person\u0026rsquo;s mindfulness can exert a flow-on, or external effect, on other people. For example, as proposed by van der Schans et al. (2022, p. 3) \u0026ldquo;\u003cem\u003eDuring an interaction, higher levels of mindfulness should help to (1) notice distracting thoughts, emotions and behavioral inclinations, (2) diminish the automatic influence of such reactions on attention and behavior, and (3) redirect attention to the interaction and interaction partner. \u0026hellip; In short, trait mindfulness might increase \u0026lsquo;presence\u0026rsquo; in the interaction and promote its quality\u003c/em\u003e.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn support of this notion, interview data collected by Simonsson et al. (2023) from sitting members of the UK Parliament showed that cultivating trait mindfulness through a supported program \u0026ldquo;\u003cem\u003eenabled politicians to\u0026nbsp;\u003c/em\u003e\u003cem\u003ebetter deal with the demands and stresses of political work, to reconnect with themselves and be more grounded, and \u0026hellip; to relate to other politicians and their viewpoints in a more humane and constructive way.\u0026rdquo; (p.1362).\u003c/em\u003e While internally felt, these outcomes can impact the quality of day-to-day life for political peers, and likely to others (constituents, staff, media) involved in their social interactions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsed to facilitate the direct assessment of this kind of \u0026lsquo;mindful presence\u0026rsquo;, the viability of a research instrument measuring observable mindful behaviours could be considerably wider in scope than being used purely for triangulation purposes. For instance, building on work by Beach et al. (2013), if people can quantitatively rate a treating physician\u0026rsquo;s behaviour as more or less mindful, it would be possible to directly examine the influence of that physician\u0026rsquo;s mindful behaviours on their patients\u0026rsquo; quality of care and health outcomes. In work or familial contexts, colleague or partner ratings using this approach could also help explain how being mindfully aware comes across to others, and to investigate the flow-on effects of mindfulness-based interventions on relationships and performance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, before this wider application can be considered, the limitations of the OMM noted above need to be addressed and the revised measure should be established as valid and reliable. Further, because the items in the original measure all elicit responses about noticeable behaviours of the observed person, rather than their internal experiences, we propose a better name for the measure would be the Observed Mindful Behaviours (OMB) scale.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis paper reports the refinement of the original OMM and the creation of the OMB.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStructural integrity and item performance.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAs reported by Bartlett et al. (2022), two of the three attentiveness items of the OMM were bounded at the top. The attentiveness items in the original scale were all negatively worded (i.e. \u0026lsquo;does not do this\u0026rsquo;), while items in the other two dimensions were positively worded (i.e. \u0026lsquo;does this\u0026rsquo;). Contemporary scale development theory proposes that mixing up the direction, or orientation, of items facilitates the respondents\u0026rsquo; attention; but conversely, using a common orientation throughout a scale helps avoid mistakes and reduce responder burden (DeVellis \u0026amp; Thorpe, 2022). We propose having a common positive orientation across all items might improve the response distribution of the attentiveness data (Lietz, 2010).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNomological network.\u003c/em\u003e\u003c/strong\u003e In the initial development of the OMM (Bartlett et al., 2021), criterion validity was pragmatically based on a strong self-other agreement score (ICC 0.45) with the unidimensional Mindful Attention and Awareness Scale (Brown \u0026amp; Ryan, 2003). Further work was called for to understand convergence of the measure with other self-report mindfulness instruments. Of particular interest is the degree of agreement with data generated by multidimensional measures of trait mindfulness (e.g. FFMQ; Baer et al., 2006) and interpersonal mindfulness (e.g. IMS; Pratscher et al., 2018). Importantly, a measure of observable mindful behaviours should produce data with a similar distribution to a self-reported mindfulness measure. As was reported by Adnoy et al. (2023), using a multi-dimensional measure can help untangle which \u0026ndash; and how \u0026ndash; different aspects of mindfulness drive social acting. Plotting variance between self and other reports at whole scale and subscale level can then support study into the impact of internal qualities of mindfulness on behaviour (Duan \u0026amp; Li, 2016).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo establish construct validity (Haig, 2023), we propose testing hypothesized relationships with established constructs that are theoretically and empirically shown to either positively or negatively correlate with behaving mindfully. Two key mechanisms that help explain how mindfulness supports wisdom and moral acting include decentering, or the ability to step back and hold a wide view of the context in which experiences are occurring; and re-perceiving, or the ability to accept current experience and re-frame perceptions accordingly (Adnoy et al., 2023; Guo, 2024). A lack of these abilities can result in psychological inflexibility, or the tendency to attempt to control or avoid difficult or unwanted circumstances and experiences (Ong et al., 2024). This inflexibility interferes with the ability to deploy adaptive coping in response to stressful events (Tindle et al., 2022) and is associated with low cooperation as well as poor social and emotional health (Zhang et al., 2023). A consistent negative correlation has been reported between trait mindfulness and psychological inflexibility (Curtiss \u0026amp; Klemanski, 2014).\u003c/p\u003e\n\u003cp\u003eTrait mindfulness is also negatively associated with perceived, or acute stress and psychological distress (Keng et al., 2011), an indicator of chronic stress-related mental and physical health problems (Biggs et al., 2017). Both acute and chronic stress impede the capacity for perspective taking, a component of empathy (Brown et al., 2021; Nitschke \u0026amp; Bartz, 2023). Further, unrelieved stress can exacerbate anger and aggression, hyperarousal, substance use, sleep problems and lack of cognitive clarity, all of which are more or less salient to others (Whitehouse et al., 2022). There is considerable evidence linking higher trait mindfulness with lower stress, and for supporting positive social interactions in high stress contexts, such as through constructive engagement (Orosz et al., 2023) and non-violent communication (Simonsson et al., 2023; Sofer, 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn organisational psychology, positive psychological capital (PsyCap: a composite of hope, self-efficacy, resilience and optimism) is associated with positive work engagement, performance and leadership (Luthans \u0026amp; Youssef-Morgan, 2017). The assessment of PsyCap is used in research for investigating the role of psychological resources in identifying, setting and achieving personal and professional goals (Luthans \u0026amp; Broad, 2022). There is convergence between self-reported mindfulness and PsyCap (Roche et al., 2014) with emerging evidence suggesting that PsyCap mediates the influence of trait mindfulness on prosocial behaviour in work settings (Liu et al., 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe overall objective of the current project was to create the Observed Mindful Behaviours (OMB) scale, for collecting second-person, quantitative data and advancing understanding of the social and behavioural correlates of mindfulness. First, we aimed to improve the structural integrity and item performance of the original OMM to create the OMB (Aim 1). The first hypothesis tested (H1) was that the OMB data would retain a clear three-dimensional structure and the psychometric performance of attentiveness items would improve following refinement. Next we aimed to test the construct validity of the OMB (Aim 2). To progress Aim 2, we tested the following hypotheses.\u003c/p\u003e\n\u003cp\u003eHypothesis 2: Tests of self-other agreement will show that total OMB scores would be significantly convergent with total scores for trait and interpersonal mindfulness (H2a) and variation will be observed in agreement between the observer and self-reported measures at subscale level (H2b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHypothesis 3: Construct validity would be supported by correlations between OMB total scores showing convergence with self-reported psychological capital (H3a), empathy (H3b) and prosocial intentions (H3c), and divergence with psychological inflexibility (H3d), psychological distress (H3e) and anger reactivity (H3f).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis study was approved by the [REMOVED] Human Research Ethics Committee (Ref. 28461) and was funded by the [REMOVED]. Methods for developing quantitative scales for use in social sciences research were followed throughout (Beaujean, 2014; DeVellis \u0026amp; Thorpe, 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSample demographics are reported in Table 1. To test the psychometric properties of the revised scale (Aim 1), two separate samples provided data via Prolific, an online participant recruitment portal. Inclusion criteria were being 18 years or older, with a 98% completion rate for previous Prolific studies and English language fluency. The two samples were recruited concurrently using Prolific (www.prolific.com, [date accessed: 3\u003csup\u003erd\u003c/sup\u003e March 2023]) with automatic 1:1 sequential assignment. Participants were compensated for the time taken to complete the 10-minute survey at approximately \u0026pound;14.63 per hour. Prolific sample 1 (n=99) were presented with the original measure with corrected gender terms (O), Prolific sample 2 (n=101) were presented with the revised measure (R), with the corrected gender terms and positively oriented attentiveness items (see \u0026lsquo;Procedures\u0026rsquo; and Table 2).\u003c/p\u003e\n\u003cp\u003eTo test the construct validity of the resultant OMB scale (Aim 2), data were collected online from a purposefully recruited community sample using REDCap surveys hosted at the University of [REMOVED]. This sample was comprised of 190 participant-observer dyads (N=380), aged 18 years or older and fluent in English. Recruitment was via open invitation to join a mindfulness research project, promoted via University of [REMOVED] AND [REMOVED] University student engagement and social media pages. Interested respondents were directed to the study registration page, where information for participants and their observers was available for download. After providing informed consent, participants were asked to nominate a person who they interact with at least 2-3 times a week, and who would be prepared to receive an invitation to complete an online survey with some questions about themselves and about their paired participant\u0026rsquo;s behaviours. Participants entered the first name and email address for their nominated observer and a personalised invitation to join the study (with a unique link to the paired survey) was automatically sent to that email address. Observers who followed the link were provided study information and asked to consent to the research conditions then do the survey. All data were stored on password protected secure servers and were de-identified prior to analysis. Both members of the participant-observer dyads needed to provide complete data to be included in analyses. Neither member of the dyads had access to the others\u0026rsquo; data and were not provided with information about their participation or responses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Participant characteristics for analysis samples\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"520\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipant characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProlific samples\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity dyadic sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eSample 1\u003cbr\u003e\u0026nbsp;O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eSample 2\u003cbr\u003e\u0026nbsp;R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eParticipants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eObservers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e(n=99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e(n=101)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e(n=190)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e(n=190)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eAge (Mean years, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e28.1 (8.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e29.1 (9.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e29.1 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e36.1 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eSex (Mean, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e49 (49.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e63 (62.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e37 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e82 (43.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e47 (47.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e36 (35.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e145 (76.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e101 (53.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eReporting about (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eColleague\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFriend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e37 (37.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e41 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e45 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFamily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e52 (52.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e57 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e139 (73.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eFamiliarity (Mean, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e58.2 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e58.3 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e74.5 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e63.1 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eTraining = yes (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e58 (58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e51 (50.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e150 (79.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e116 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 520px;\"\u003e\n \u003cp\u003eFamiliarity = self-reported familiarity with mindfulness (scale 1 to 100); Training = self-reported exposure to mindfulness practices and teachings (yes/no)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree revisions were made to items in the Attentiveness dimension of the original measure published by Bartlett et al. (2022), to produce the OMB (Aim 1). First, gendered terms were replaced with non-gendered terms; next an excluded item from the Attentiveness dimension in the original item set was returned to re-test fit and performance, and lastly the items were re-written to orient them in positive language. The items for the original measure with the additional item (O), and the version with revised wording and orientation (R) are shown in Table 2. Data distributions, factor structure, and item performance of the two scales were examined using Prolific samples 1 and 2.\u003c/p\u003e\n\u003cp\u003eTable 2. Items of the observed mindfulness measure (OMM) and the observed mindful behaviours (OMB) scale.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg 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width=\"640\" height=\"885\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConstruct validity (Aim 2) was tested using rank order correlations and regression models using observer-reported OMB data and participant-reported measures of constructs in the proposed nomological network of observable mindful behaviours. The following construct measures were administered.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eObserved Mindfulness Measure (OMM)\u0026nbsp;\u003c/em\u003efit indices as published were: RMSEA=0.042,\u0026nbsp;c\u003csup\u003e2\u003c/sup\u003e=0.005, TLI=0.987, CFI=0.992,\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.91; and reliability indices for the subscales were: Attentiveness\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.82; Awareness\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.87; Acceptance\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.75 (Bartlett et al., 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTrait mindfulness\u003c/em\u003e was measured using 12-items from the Five-Facet Mindfulness Questionnaire (FFMQ-15; Gu et al., 2016). Based on evidence that the Observing facet of the FFMQ is more informative in intervention research than in cross-sectional analyses (Rudkin et al., 2018), only the items that load onto the other four dimensions (Acting with awareness, Non-judging, Non-reacting and Describing) were included in the survey. The 27-item Interpersonal Mindfulness Scale (IMS; Pratscher et al., 2018) was completed by both members of each participant-observer dyad. McDonald\u0026rsquo;s Omega coefficients were: FFMQ data (whole scale: w\u003csub\u003et\u003c/sub\u003e==0.85, Describe:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.80, Act aware:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.73, Non-react:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.73, Non-judge:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.85) and IMS data (whole scale:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.92, Act aware:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.89, Presence:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.90, Non-judge:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e==0.73, Non-react:\u0026nbsp;w\u003csub\u003et\u003c/sub\u003e=0.81).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProsocial acting\u0026nbsp;\u003c/em\u003ewas assessed with the 4-item Prosocial Behavioural Intentions Scale (PBIS; Baumsteiger \u0026amp; Siegel, 2019). PBIS data (w\u003csub\u003et\u003c/sub\u003e==0.85) was hypothesized to correlate positively with OMB data. Indicators of \u003cem\u003eempathy\u003c/em\u003e, including perspective taking and discomfort in social engagement were measured using 8 items (two dimensions) of the Brief Interpersonal Reactivity Index\u0026nbsp;(B-IRI; Ingoglia et al., 2016). We hypothesised perspective taking (w\u003csub\u003et\u003c/sub\u003e==0.79) would be positively correlated with OMB data, whilst discomfort in social engagement (w\u003csub\u003et\u003c/sub\u003e=0.89) would be negatively correlated.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePsychological inflexibility\u003c/em\u003e was measured using the 7-item Acceptance and Action Questionnaire (AAQ-2; Bond et al., 2011), and PsyCap (hope, optimism, resilience and efficacy) in relation to interpersonal relationships was measured using the 12-item Compound Psychological Capital questionnaire (CPC-R; Dudasova et al., 2021). Internal consistency was good for both the AAQ-2 (w\u003csub\u003et\u003c/sub\u003e=0.96) and CPC-R (w\u003csub\u003et\u003c/sub\u003e==0.93) data. We hypothesized participants\u0026rsquo; AAQ-2 would be negatively correlated, and CPC-R data would be positively associated with their paired observers\u0026rsquo; responses to the OMB.\u003c/p\u003e\n\u003cp\u003eThe 6-item Kessler measure of \u003cem\u003epsychological distress\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(K6; Kessler et al., 2002) and the 5-item Dimensions of Anger scale (DAR-5; Forbes et al., 2014) were used to test hypothesized divergence of stress-related constructs with the OMB. Internal consistency was good for K6 data (w\u003csub\u003et\u003c/sub\u003e=0.92) and satisfactory for DAR-5 data (w\u003csub\u003et\u003c/sub\u003e==0.80). Psychological distress is an established outcome of chronic or unmanaged stress; and \u003cem\u003eanger reactivity\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eprovides information about behavioural and emotional regulation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDemographic data included age, gender identification, country of residence, familiarity with mindfulness (on a scale of 1-100), dyadic relationship (friend, colleague or family) and self-reported exposure to mindfulness training.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipant characteristics were summarised descriptively (Table 1). Boxplots were used to check data distributions. Factor analyses (CFA) were conducted using the Psych (Revelle, 2014) and lavaan packages in R (Rosseel, 2012) to confirm the factor structure of scale data. Criteria used to assess goodness of fit were Root Mean Squared Error of Approximation (RMSEA \u0026lt; 0.08), Comparative Fit Index (CFI close to 1), Tucker Lewis Index (TLI \u0026gt; 0.9), Cronbach\u0026rsquo;s alpha (\u0026alpha; \u0026gt; 0.7) and McDonald\u0026rsquo;s omega reliability coefficient (w\u003csub\u003et\u003c/sub\u003e=\u0026gt; 0.7). Item responsiveness theory modelling (IRT) was conducted at factor level using generalised partial credit model for ordinal, polytomous data (Beaujean, 2014). The a-score from IRT models denotes discrimination (values around and above 1 are desired). The b-scores (illustrated by the multi-colour curves in the item characteristic curve plots) refer to how precise the information provided by each response option is. Flat curves indicate poor precision, clear and ordered peaks indicate good precision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInternal consistency was assessed using McDonald\u0026rsquo;s omega test for all scale data prior to analyses (Zinbarg et al., 2005). Spearman\u0026rsquo;s Rho was applied to produce a correlation matrix for all assessed constructs, with the Benjamini-Hochberg False Discovery Rate multiple comparisons correction applied (Benjamini and Hochberg, 1995). Linear regression models were then used to test the influence of demographic factors and the hypotheses for Aim 2, that observer-reported OMB scores would be positively correlated with participants\u0026rsquo; self-reported trait and interpersonal mindfulness. Finally, we ran a test of moderation to understand whether observers higher in self-reported mindfulness were more discerning in their OMB ratings.\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eAim 1. Structural integrity and item performance\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData distributions.\u003c/b\u003e The data from Prolific samples 1 and 2 (Supplementary Figure S.1.) showed variability in the response distribution in O and R data. Eight out of the 10 items in the Original measure had a median of 4 (out of possible 5). One of the Attentiveness items (OMM-4) was bounded at the top, with an IQR that included the maximum score. Six of the 10 items in the Revised measure had a median of 4, and four a median of 3, and no items had the maximum score included in the IQR.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eItem performance.\u003c/b\u003e IRT modelling on the attentiveness factor showed the Revised items had better discrimination, precision and information about ability than the negatively worded Original items (Supplementary Table S.1). The additional attentiveness item (OMM10) that was returned for testing purposes, showed poor discrimination and precision in both samples and was dropped from structural analyses. Item probability functions and test information for the three retained Attentiveness items in the Original and Revised measures are illustrated in item characteristic curve plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cb\u003eStructural analysis.\u003c/b\u003e Confirmatory factor analysis (CFA) was run on the 9-item Original and Revised scale data (as set out in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). While the information parameters were similar, the fit indices (TLI, CFI, α and ω\u003csub\u003et\u003c/sub\u003e) were all closer to 1 for the Revised scale (OMB) than for the original scale. Comparison of models showed no significant statistical difference (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ediff\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.463). Our first hypothesis (H1) was therefore supported. The resulting OMB was then used for further testing.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStructural re-analysis.\u003c/b\u003e CFA confirmed the 3-factor structure for the OMB in data provided by the community sample. Fit indices for the modelled data are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows item-factor loadings, factor-factor correlations, and variance explained.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFit statistics from Confirmatory Factor Analysis for the original and revised 9-item OMM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTLI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eα\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eω\u003csub\u003et\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProlific 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProlific 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity dyadic sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eRMSEA: Root Mean Squared Error of Approximation; CFI: Comparative Fit Index; TLI: Tucker Lewis Index; α: Cronbach\u0026rsquo;s alpha coefficient of internal reliability; ω: McDonald\u0026rsquo;s Omega coefficient of test reliability. O: original Observed Mindfulness Measure as published by Bartlett et al (REF), adjusted with non-gendered terms; R: revised OMM items with attentiveness items reworded for positive orientation; OMB: the Observed Mindful Behaviours scale (same as R).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAim 2. Construct validity.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eReliability coefficients for each of the nomological network constructs and Spearman\u0026rsquo;s Rho correlations with OMB scores are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Summary scores for each variable tested are in Supplementary Table S.2. Results supported our criterion validity hypothesis (H2a) as the observer-reported OMB total scores were robustly and positively correlated with their paired participants\u0026rsquo; trait mindfulness (r\u0026thinsp;=\u0026thinsp;0.35, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and interpersonal mindfulness (r\u0026thinsp;=\u0026thinsp;0.28, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) scores.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations between nomological network constructs and OMB total and subscale scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eω\u003csub\u003et\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eα\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003er\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal OMB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmpathy (overall IRI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal discomfort (IRI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerspective taking (IRI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological inflexibility (AAQ)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait mindfulness (FFMQ-SF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterpersonal mindfulness (IMS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological capital (CPC-R)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnger reactivity (DA5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological distress (K6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProsocial behavioural intentions (PBIS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eMcDonald\u0026rsquo;s Omega coefficient (ωt) and Cronbach\u0026rsquo;s alpha coefficient (α) provide an indication of internal consistency and scale reliability; r\u003csub\u003es\u003c/sub\u003e: Spearman rank order correlations with p-values.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents correlations between the self-report mindfulness data (FFMQ-SF, IMS) and the OMB data at subscale level, with variability in the strength of associations, as hypothesized. The OMB Attentiveness subscale data was convergent with the FFMQ Act with Awareness (r\u0026thinsp;=\u0026thinsp;0.32), Non-react (r\u0026thinsp;=\u0026thinsp;0.15) and Describe (r\u0026thinsp;=\u0026thinsp;0.19) subscales, and with the IMS Awareness of Self (r\u0026thinsp;=\u0026thinsp;0.23), Non-reactivity (r\u0026thinsp;=\u0026thinsp;0.21) and Presence (r\u0026thinsp;=\u0026thinsp;0.32) subscales. The OMB Awareness subscale converged with FFMQ Act with Awareness (r\u0026thinsp;=\u0026thinsp;0.22) and Describe (r\u0026thinsp;=\u0026thinsp;0.31), and with IMS Awareness of Self (r\u0026thinsp;=\u0026thinsp;0.22), Non-reactivity (r\u0026thinsp;=\u0026thinsp;0.21) and Presence (r\u0026thinsp;=\u0026thinsp;0.25). The OMB Acceptance subscale also converged with FFMQ Act with Awareness (r\u0026thinsp;=\u0026thinsp;0.19), Non-react (r\u0026thinsp;=\u0026thinsp;0.28) and Describe (r\u0026thinsp;=\u0026thinsp;0.19), and with IMS Non-reactivity (r\u0026thinsp;=\u0026thinsp;0.24) and Presence (r\u0026thinsp;=\u0026thinsp;0.16). Acceptance was the only OMB subscale that significantly converged with IMS Nonjudgmental acceptance (r\u0026thinsp;=\u0026thinsp;0.15). Non-significant associations were noted across the board between OMB subscale data and FFMQ Non-judge data.\u003c/p\u003e \u003cp\u003eThe robustness of associations to identified covariates was assessed using linear regression (Supplementary Tables S.3 and S.4). OMB ratings were not influenced by observers' exposure to self-guided (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.985) or teacher-led mindfulness training (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.915), gender (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.427) or age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.143). Further, the observer category (friend, family, spouse, colleague) did not reveal any significant influence on OMB ratings (\u003cem\u003ep\u0026rsquo;s\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.223). However, OMB ratings were influenced by observer mindfulness (IMS, β\u0026thinsp;=\u0026thinsp;0.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.11). Our final regression models show OMB ratings were positively correlated with participants\u0026rsquo; trait mindfulness (FFMQ, β\u0026thinsp;=\u0026thinsp;0.42, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.15), and with participants\u0026rsquo; interpersonal mindfulness (IMS, β\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.12). Moderation analysis found no interaction effect of observer mindfulness and participant mindfulness on OMB scores (β\u0026thinsp;=\u0026thinsp;0.00, p\u0026thinsp;=\u0026thinsp;0.563).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMatrix of correlations between the subscales of three mindfulness measures: OMM, FFMQ-SF and IMS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable number and label\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eω\u003csub\u003et\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eα\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMM Attentiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMM Awareness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOMM Acceptance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFFMQ Act with awareness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.19*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFFMQ Non-judge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFFMQ Non-react\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.28*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFFMQ Describe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.19*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMS Awareness of self and others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMS Nonjudgmental acceptance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.15*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMS Nonreactivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.24*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIMS Presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.25*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.16*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eMcDonald\u0026rsquo;s Omega coefficient (ωt) and Cronbach\u0026rsquo;s alpha coefficient (α) provide an indication of internal consistency and scale reliability; r\u003csub\u003es\u003c/sub\u003e = Spearman rank order correlations. Values in the lower triangle are correlation coefficients and in the top triangle are p-values.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn nomological network tests, OMB data converged with the overall score for empathy (r\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (H3b), with results pointing to a stronger alignment with personal discomfort in social situations (r=-0.24, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than perspective-taking (r\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;=\u0026thinsp;0.016). Results also support the hypothesized negative association of OMB data with psychological inflexibility scores (r=-0.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (H3d).\u003c/p\u003e \u003cp\u003eHowever, the expected congruence of OMB scores with psychological capital (H3a) (r\u0026thinsp;=\u0026thinsp;0.22, p\u0026thinsp;=\u0026thinsp;0.919) and prosocial intentions (H3c) (r\u0026thinsp;=\u0026thinsp;0.03, p\u0026thinsp;=\u0026thinsp;0.718) was not supported. Also, non-significant correlations between the OMB scores and psychological distress (r=-0.29, p\u0026thinsp;=\u0026thinsp;0.637) (H3e) and anger reactivity (r=-0.26, p\u0026thinsp;=\u0026thinsp;0.417) (H3f) were observed.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis was a two-part study, that involved first testing a revised version of the original Observed Mindfulness Measure as published in (Bartlett et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) to address limitations in the measure, including the identified ceiling effect in the attentiveness dimension. After determining changes to be made to the original instrument, the first Aim for the project involved confirming the factorial structure of the new Observed Mindful Behaviours (OMB) scale in a separate dyadic sample, then assessing its construct validity. The resulting OMB is a 9-item observer-report instrument that shows good psychometric properties and clear associations with qualities that comprise individual and interpersonal mindfulness and psychological flexibility. The scale appears robust to variability in the level of mindfulness, age, and gender of respondents. There was no evidence of a ceiling effect. OMB scores showed consistent, moderate sized positive correlation with paired participants\u0026rsquo; trait and interpersonal mindfulness scores. The positive correlation with participants self-reported empathy were also robust, as were the negative correlations with participants\u0026rsquo; psychological inflexibility. However, the OMB did not converge significantly with behavioural constructs in the hypothesized nomological network \u0026ndash; psychological capital, anger reactivity, psychological distress \u0026ndash; and was not associated with prosocial behavioural intentions. The implications of these results and potential applications for the new measure are discussed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eScale refinement.\u003c/b\u003e Three revisions to the original measure (Bartlett et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) were tested to see if they improved item performance while retaining the three-dimensional scale structure (Aim 1). These revisions comprised use of gender-neutral terminology, re-testing a previously discarded item, and positively framing all items in the Attentiveness dimension. Our IRT analysis showed the returned item did not perform well and was again discarded from the item set. In contrast, the IRT models and item characteristic curves for the other three revised Attentiveness items showed better performance and more information about ability than in the original measure. The other revisions were supported by improved distributions and good psychometric performance of data collected by the OMB. However, we acknowledge that the distribution of OMB data from the separate community sample showed a trend for scores to be towards the top of the range. This could be a reflection of the mean self-reported mindfulness ratings in our sample, which were higher than normative scores (Asensio-Martinez et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A finding that could be explained by the fact that 79% participants and 61% observers having engaged with formal mindfulness training. It is also feasible people with higher mindfulness may have been more likely to volunteer for this study. In terms of the performance of the OMB, we note the comparability of its relative goodness of fit (RMSEA\u0026thinsp;=\u0026thinsp;0.07, CFI\u0026thinsp;=\u0026thinsp;0.97) with fit indices reported in the development papers for the FFMQ-SF (RMSEA\u0026thinsp;=\u0026thinsp;0.05 to 0.06; CFI\u0026thinsp;=\u0026thinsp;0.95 to 0.96) (Bohlmeijer et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and the IMS (RMSEA\u0026thinsp;=\u0026thinsp;0.05; CFI\u0026thinsp;=\u0026thinsp;0.91) (Pratscher et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Collectively, the structural, item performance and distribution suggest the new OMB has satisfactory psychometric properties.\u003c/p\u003e \u003cp\u003e \u003cb\u003eValidity\u003c/b\u003e. In criterion validity tests, OMB scores corresponded with trait and interpersonal mindfulness scores. This means that Observer OMB ratings were higher when their paired Participant\u0026rsquo;s self-reported mindfulness ratings were higher. However, the magnitude of association was moderate at best, which indicates that the OMB, FFMQ-SF and IMS scales measure related but discrepant constructs. This result helps clarify the construct validity of the OMB, as a measure of \u003cem\u003enoticeable behaviours that are attentive, aware and accepting, not the internal states that may be driving them\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn the regression models, where known covariates (age, gender, engagement with mindfulness training) were accounted for, the relationships between OMB scores and FFMQ and IMS scores were shown to be robust, and to account for between 11% and 15% variance. This result indicates a meaningful relationship in behavioural and psychological research (Brydges, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Further, while OMB ratings were sensitive to the self-reported interpersonal mindfulness of observers, there was no interaction effect of the observers\u0026rsquo; IMS and participants\u0026rsquo; FFMQ-SF scores on OMB results. The reported results support the criterion validity of the OMB.\u003c/p\u003e \u003cp\u003eMulti-dimensional measures present the opportunity to investigate relationships between and effects on constructs at a more granular level than using overall total scores (Duan \u0026amp; Li, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Indeed some facets of mindfulness have been noted already to differentially influence social behaviours (Adnoy et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As expected, there was some variability in the strength of association between the three OMB dimensions (Attentiveness, Awareness and Acceptance) when tested against the FFMQ-SF subscales (Act with awareness, Nonjudging, Nonreacting and Describing) and the IMS subscales (Awareness of self and others, Nonjudgmental acceptance, Nonreactivity and Presence). We posit this variability may be helpful for gaining a better understanding of the factors that drive mindful acting, and may also help determine aspects of mindfulness that are dispositional and/or cultivated (Duan \u0026amp; Li, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To illustrate: the awareness subscales of FFMQ and IMS were significantly and positively associated with both the OMB attentiveness and awareness sub-scales, but not with OMB acceptance. This helps clarify how being mindfully aware comes across to others. Similarly, non-reactivity in the FFMQ and IMS instruments were both significantly associated with OMB acceptance and attentiveness, but not OMB awareness. Thus, it may be mindful attentiveness and acceptance are responsible for being noticeably non-reactive, rather than mindful awareness. Previous research has identified the non-judging facet of the FFMQ to be more aligned with flexibility in cognition and emotional experience, while acting with awareness, describing and non-reactivity aligned with presence and openness to experience (Adnoy et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It is plausible that non-judging involves cognitive and emotional processes that are internal, and therefore not observable to others; while being present and open when engaging with others are indeed noticeable behaviours. Such mechanistic conclusions cannot be supported in the current data, however we propose the OMB can be used to help explore the relationships reported between mindfulness, prosociality and moral acting (Berry et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Donald et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Malin, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on our hypotheses, construct validity would be supported by correlations between OMB total scores showing convergence with measures of psychological capital (H3a), empathy (H3b) and prosocial intentions (H3c), and divergence with psychological inflexibility (H3d), psychological distress (H3e) and anger reactivity (H3f). This proposed nomological network was based on previously reported moderate sized within-person correlations between self-reported mindfulness, empathy and psychological inflexibility (Guo, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), PsyCap (Ali et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), distress (Carpenter et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and anger reactivity (Richard et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eParticipants\u0026rsquo; empathy scores were significantly and positively correlated with the observers\u0026rsquo; OMB ratings. Empathy is understood to be an antecedent of prosocial behaviours and has been used as a proxy in mindfulness research to understand social effects of mindfulness (Donald et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Van Doesum et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The differential association between empathy subscales suggests higher OMB data may detect discomfort in social settings, but is less able to detect the more internal process of perspective taking.\u003c/p\u003e \u003cp\u003eConstruct validity was further supported by the robust negative correlation between OMB and the measure of psychological inflexibility. Defined as a rigid responding to inner experiences (e.g. thoughts, feelings) in ways that interfere with well-being and the pursuit of valued actions (Hayes et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), psychological inflexibility is, by definition, nearly anti-thetic to the intentional awareness and acceptance qualities of mindfulness (Ong et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The AAQ used in this study has frequently been included in the nomological networks for testing the validity of self-reported mindfulness measures (Baer et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Chems-Maarif et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The magnitude of the OMB:AAQ-2 correlation was lower than observed in self-report data; again potentially explained by the kinds of information observers have access to, relative to the person being observed (Varela \u0026amp; Shear, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the OMB did not show the expected positive correlation with prosocial behavioural intentions or psychological capital, or the negative correlations with psychological distress and anger reactivity. While strong associations with self-reported mindfulness have previously been found with these constructs, our findings concur with Malin (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) who concluded the relationship between mindfulness and prosocial behaviour is not straightforward. Potentially our results could help show that the reactivity associated with anger and distress may not translate into action in people with higher levels of mindfulness. This explanation is in keeping with decentering and reperceiving, core skills associated with mindfulness which enable non-attachment, or not being in \u0026lsquo;the thrall\u0026rsquo; of emotions, and greater capacity for flexible or adaptive responding (Adnoy et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Biggs et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guo, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A unique contribution of the OMB is that it detects how behaviours are enacted in social engagements, rather than the internal drivers for those behaviours. Our results only partly support the construct validity hypotheses developed for this study. However, they are in accordance with the focus of the OMB on the nature of observable behaviours, rather than intentions, and help clarify the construct that the new scale is measuring.\u003c/p\u003e \u003cp\u003eThe observer-report OMB appears to provide valid data relating to the extent to which another known person behaves in a way that is consistent with the qualities that characterise self-reported mindfulness. In line with others work (Berry et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; H\u0026ouml;lzel et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) our OMB data indicate the self-regulatory processes of directing attention to, and accepting what is occurring in the present moment support the capacity for non-reactivity. The OMB could be used in research investigating mechanisms driving external, beneficial effects of mindfulness found through other methods in clinical practice (Braun et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Epstein et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), in schools (Montero-Marin et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tudor et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and in workplaces (Arendt et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sutton, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and future research.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMeasurement in mindfulness research has its complexities and there are diverging views on the conceptualisation and operationalisation of the construct (Van Dam et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These differences are steeped in theoretical/historical literature (e.g. Buddhist teachings vs psychological sciences); timing (e.g. state vs trait) and function (e.g. dispositional vs cultivated). However, in developing the OMB we have followed guidance by Sauer et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and included items relating to behaviours, attitudes and cognitions (e.g. \u003cem\u003eThe person seems aware of their own emotions when interacting with others\u003c/em\u003e\u003cb\u003e)\u003c/b\u003e, rather than felt experiences such as calm or peace that may arise as a result of higher mindfulness. We acknowledge that our FFMQ-SF instrument was not the full scale as published by Baer et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), however to minimise responder burden the briefer measure was selected, based on validation work conducted by Gu et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Confidence in the contribution of OMB data will benefit from establishing associations with other measures of trait mindfulness, such as the Mindful Awareness and Acceptance Scale (Brown \u0026amp; Ryan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) or the Freiberg Mindfulness Inventory (Walach et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Further, a mixed methods study combining OMB and interview data from dyadic participants with and without exposure to mindfulness training would be very informative. Such future work could provide valuable contextual and phenomenological data to clarify if and how the internal quality of mindfulness influences outcomes beyond the self, into social and performance domains.\u003c/p\u003e \u003cp\u003eIn our community sample, around 80% of participants and two-thirds of observers had previously engaged in formal mindfulness training, which is not likely to be representative of the general population. To address this self-selection bias, future research using community samples should aim to include more participants and observers with no formal mindfulness training. The single-observer design in the current study also may be susceptible to rater-specific biases, which could be overcome using multiple observers to rate the same participant.\u003c/p\u003e \u003cp\u003eFuture iterations of the OMB could be augmented with items that detect the non-judging facet of trait mindfulness, that can help better understand the contribution of acceptance in social interactions and behaviours. Lastly, to confirm the investigative utility of the OMB, controlled longitudinal studies are required, as its test-retest reliability and sensitivity to change still need to be proven.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThe OMB supersedes the Observed Mindfulness Measure and can be used to provide researchers another perspective with which to study behaviours associated with mindfulness. The new OMB scale detects the extent to which a person known to the rater (family, friend or colleague) behaves in a way that is noticeably attentive, aware and accepting (or mindful). Alignment with behavioural drivers (empathy, acceptance) but not behavioural states (distress, anger, intentions), or with psychological capital, helps clarify what the OMB assesses. OMB data, which can be collected inexpensively and at scale, can be used to triangulate and strengthen self-reported findings and help examine how mindfulness comes across to others. The variable correlations between OMB subscales and facets of self-reported trait and interpersonal mindfulness suggest different aspects of mindfulness are more or less evident in social interactions, and may help build a better understanding of the mechanisms driving prosocial behaviours and moral acting.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; drafted the work or revised it critically for important intellectual content; approved the version to be published; and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to declare. The authors have no conflicts of interest to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approvals\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the [REMOVED] Human Research Ethics Committee (REF: [REMOVED]) and conducted in accordance with the National Statement on Ethical Conduct in Human Research 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent to participate in the research and for the publication of research outputs was obtained from all participants via an online form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePartial financial support was received from a philanthropic fund held by the [REMOVED].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study and the analysis code will be made available by the corresponding author for research purposes on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdnoy, T., Solem, S., Hagen, R., \u0026amp; Havnen, A. (2023). An empirical investigation of the associations between metacognition, mindfulness experiential avoidance, depression, and anxiety. \u003cem\u003eBMC Psychol\u003c/em\u003e,\u003cem\u003e 11\u003c/em\u003e(1), 281. https://doi.org/10.1186/s40359-023-01336-7\u003c/li\u003e\n\u003cli\u003eAli, M., Khan, A. N., Khan, M. M., Butt, A. S., \u0026amp; Shah, S. H. H. (2021). Mindfulness and study engagement: mediating role of psychological capital and intrinsic motivation. \u003cem\u003eJournal of Professional Capital and Community\u003c/em\u003e,\u003cem\u003e 7\u003c/em\u003e(2), 144-158. https://doi.org/10.1108/jpcc-02-2021-0013\u003c/li\u003e\n\u003cli\u003eArendt, J. F. W., Pircher Verdorfer, A., \u0026amp; Kugler, K. G. (2019). Mindfulness and Leadership: Communication as a Behavioral Correlate of Leader Mindfulness and Its Effect on Follower Satisfaction [10.3389/fpsyg.2019.00667]. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e,\u003cem\u003e 10\u003c/em\u003e, 667.\u003c/li\u003e\n\u003cli\u003eAsensio-Martinez, A., Masluk, B., Montero-Marin, J., Olivan-Blazquez, B., Navarro-Gil, M. T., Garcia-Campayo, J., \u0026amp; Magallon-Botaya, R. (2019). Validation of Five Facets Mindfulness Questionnaire - Short form, in Spanish, general health care services patients sample: Prediction of depression through mindfulness scale. \u003cem\u003ePLOS ONE\u003c/em\u003e,\u003cem\u003e 14\u003c/em\u003e(4), e0214503. https://doi.org/10.1371/journal.pone.0214503\u003c/li\u003e\n\u003cli\u003eBaer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., \u0026amp; Toney, L. (2006). Using Self-Report Assessment Methods to Explore Facets of Mindfulness. \u003cem\u003eAssessment\u003c/em\u003e,\u003cem\u003e 13\u003c/em\u003e(1), 27-45. https://doi.org/10.1177/1073191105283504\u003c/li\u003e\n\u003cli\u003eBaer, R. A., Walsh, E., \u0026amp; Lykins, E. L. (2009). Assessment of Mindfulness. In \u003cem\u003eClinical Handbook of Mindfulness\u003c/em\u003e (pp. 153-168). Springer.\u003c/li\u003e\n\u003cli\u003eBartlett, L., and Lovell, P., and Otahal, P., \u0026amp; and Sanderson, K. (2016). Acceptability, Feasibility, and Efficacy of a Workplace Mindfulness Program for Public Sector Employees: a Pilot Randomized Controlled Trial with Informant Reports. \u003cem\u003eMindfulness\u003c/em\u003e, 1--16. https://doi.org/10.1007/s12671-016-0643-4\u003c/li\u003e\n\u003cli\u003eBartlett, L., Martin, A., Sanderson, K., \u0026amp; Neil, A. (2022). Observed Mindfulness Measure (OMM). In O. N. Medvedev, C. U. Krageloh, R. J. Siegert, \u0026amp; N. N. Singh (Eds.), \u003cem\u003eHandbook of Assessment in Mindfulness Research\u003c/em\u003e (pp. 1-17). Springer Link. https://doi.org/10.1007/978-3-030-77644-2_89-1\u003c/li\u003e\n\u003cli\u003eBartlett, L., Martin, A. J., Bruno, R., Kilpatrick, M., Sanderson, K., \u0026amp; Neil, A. L. (2021). Is Mindfulness a Noticeable Quality? Development and Validation of the Observed Mindfulness Measure. \u003cem\u003eJournal of Psychopathology \u0026amp; Behavioral Assessment\u003c/em\u003e,\u003cem\u003e 44\u003c/em\u003e, 165-185. https://doi.org/10.1007/s10862-021-09936-6\u003c/li\u003e\n\u003cli\u003eBaumsteiger, R., \u0026amp; Siegel, J. T. (2019). Measuring Prosociality: The Development of a Prosocial Behavioral Intentions Scale. \u003cem\u003eJ Pers Assess\u003c/em\u003e,\u003cem\u003e 101\u003c/em\u003e(3), 305-314. https://doi.org/10.1080/00223891.2017.1411918\u003c/li\u003e\n\u003cli\u003eBeach, M. C., Roter, D., Korthuis, P. T., Epstein, R. M., Sharp, V., Ratanawongsa, N., Cohn, J., Eggly, S., Sankar, A., Moore, R. D., \u0026amp; Saha, S. (2013). A multicenter study of physician mindfulness and health care quality. \u003cem\u003eAnn Fam Med\u003c/em\u003e,\u003cem\u003e 11\u003c/em\u003e(5), 421-428. https://doi.org/10.1370/afm.1507\u003c/li\u003e\n\u003cli\u003eBeaujean, A. A. (2014). \u003cem\u003eLatent Variable Modeling Using R: A Step-by-Step Guide\u003c/em\u003e (1st ed.). Routledge. https://doi.org/10.4324/9781315869780\u003c/li\u003e\n\u003cli\u003eBerry, D. R., Hoerr, J. P., Cesko, S., Alayoubi, A., Carpio, K., Zirzow, H., Walters, W., Scram, G., Rodriguez, K., \u0026amp; Beaver, V. (2020). Does Mindfulness Training Without Explicit Ethics-Based Instruction Promote Prosocial Behaviors? A Meta-Analysis. \u003cem\u003ePers Soc Psychol Bull\u003c/em\u003e,\u003cem\u003e 46\u003c/em\u003e(8), 1247-1269. https://doi.org/10.1177/0146167219900418\u003c/li\u003e\n\u003cli\u003eBiggs, A., Brough, P., Drummond, S., Quick, J. C., \u0026amp; Cooper, C. L. (2017). Lazarus and Folkman\u0026apos;s Psychological Stress and Coping Theory. In (pp. 349-364). John Wiley \u0026amp; Sons, Ltd. https://doi.org/10.1002/9781118993811.ch21\u003c/li\u003e\n\u003cli\u003eBohlmeijer, E., ten Klooster, P. M., Fledderus, M., Veehof, M., \u0026amp; Baer, R. (2011). Psychometric properties of the five facet mindfulness questionnaire in depressed adults and development of a short form. \u003cem\u003eAssessment\u003c/em\u003e,\u003cem\u003e 18\u003c/em\u003e(3), 308-320. https://doi.org/10.1177/1073191111408231\u003c/li\u003e\n\u003cli\u003eBond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., \u0026amp; Zettle, R. D. (2011). Preliminary psychometric properties of the Acceptance and Action Questionnaire\u0026ndash;II: A revised measure of psychological inflexibility and experiential avoidance. \u003cem\u003eBehavior Therapy\u003c/em\u003e,\u003cem\u003e 42\u003c/em\u003e(4), 676-688. https://doi.org/10.1016/j.beth.2011.03.007\u003c/li\u003e\n\u003cli\u003eBrauer, K., \u0026amp; Proyer, R. T. (2019). Dyadic Effects. In V. Zeigler-Hill \u0026amp; T. K. Shackelford (Eds.), \u003cem\u003eEncyclopedia of Personality and Individual Differences\u003c/em\u003e (pp. 1-5). Springer International Publishing. https://doi.org/10.1007/978-3-319-28099-8_656-1\u003c/li\u003e\n\u003cli\u003eBraun, S. E., Kinser, P. A., \u0026amp; Rybarczyk, B. (2018). Can mindfulness in health care professionals improve patient care? An integrative review and proposed model. \u003cem\u003eTranslational Behavioral Medicine\u003c/em\u003e, iby059-iby059. https://doi.org/10.1093/tbm/iby059\u003c/li\u003e\n\u003cli\u003eBrown, C. L., West, T. V., Sanchez, A. H., \u0026amp; Mendes, W. B. (2021). Emotional Empathy in the Social Regulation of Distress: A Dyadic Approach. \u003cem\u003ePersonality and Social Psychology Bulletin\u003c/em\u003e,\u003cem\u003e 47\u003c/em\u003e(6), 1004-1019. https://doi.org/10.1177/0146167220953987\u003c/li\u003e\n\u003cli\u003eBrown, K. W., \u0026amp; Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in psychological well-being. \u003cem\u003eJournal of Personality and Social Psychology\u003c/em\u003e,\u003cem\u003e 84\u003c/em\u003e(4), 822-848. https://doi.org/10.1037/0022-3514.84.4.822\u003c/li\u003e\n\u003cli\u003eBrydges, C. R. (2019). Effect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology. \u003cem\u003eInnov Aging\u003c/em\u003e,\u003cem\u003e 3\u003c/em\u003e(4), igz036. https://doi.org/10.1093/geroni/igz036\u003c/li\u003e\n\u003cli\u003eCarpenter, J. K., Conroy, K., Gomez, A. F., Curren, L. C., \u0026amp; Hofmann, S. G. (2019). The relationship between trait mindfulness and affective symptoms: A meta-analysis of the Five Facet Mindfulness Questionnaire (FFMQ). \u003cem\u003eClin Psychol Rev\u003c/em\u003e,\u003cem\u003e 74\u003c/em\u003e, 101785. https://doi.org/10.1016/j.cpr.2019.101785\u003c/li\u003e\n\u003cli\u003eChems-Maarif, R., Cavanagh, K., Baer, R., Gu, J., \u0026amp; Strauss, C. (2025). Defining Mindfulness: A Review of Existing Definitions and Suggested Refinements. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 16\u003c/em\u003e(1), 1-20. https://doi.org/10.1007/s12671-024-02507-2\u003c/li\u003e\n\u003cli\u003eCurtiss, J., \u0026amp; Klemanski, D. H. (2014). Teasing apart low mindfulness: Differentiating deficits in mindfulness and in psychological flexibility in predicting symptoms of generalized anxiety disorder and depression. \u003cem\u003eJournal of Affective Disorders\u003c/em\u003e,\u003cem\u003e 166\u003c/em\u003e, 41-47. https://doi.org/https://doi.org/10.1016/j.jad.2014.04.062\u003c/li\u003e\n\u003cli\u003eDeVellis, R. F., \u0026amp; Thorpe, C. T. (2022). \u003cem\u003eScale development: theory and applications\u003c/em\u003e (Fifth edition. ed., Vol. 26). SAGE.\u003c/li\u003e\n\u003cli\u003eDonald, J. N., Sahdra, B. K., Van Zanden, B., Johannes Duineveld, J., Atkins, P. W. B., Marshall, S., \u0026amp; Ciarrochi, J. (2019). Does Your Mindfulness Benefit Others? A Systematic Review and Meta-Analysis of the Link Between Mindfulness and Prosocial Behavior. \u003cem\u003eBritish Journal of Psychology\u003c/em\u003e,\u003cem\u003e 110\u003c/em\u003e(1), 101-125. https://doi.org/10.1111/bjop.12338\u003c/li\u003e\n\u003cli\u003eDuan, W., \u0026amp; Li, J. (2016). Distinguishing Dispositional and Cultivated Forms of Mindfulness: Item-Level Factor Analysis of Five-Facet Mindfulness Questionnaire and Construction of Short Inventory of Mindfulness Capability. \u003cem\u003eFront Psychol\u003c/em\u003e,\u003cem\u003e 7\u003c/em\u003e, 1348. https://doi.org/10.3389/fpsyg.2016.01348\u003c/li\u003e\n\u003cli\u003eDudasova, L., Prochazka, J., Vaculik, M., \u0026amp; Lorenz, T. (2021). Measuring psychological capital: Revision of the Compound Psychological Capital Scale (CPC-12). \u003cem\u003ePLOS ONE\u003c/em\u003e,\u003cem\u003e 16\u003c/em\u003e(3), e0247114. https://doi.org/10.1371/journal.pone.0247114\u003c/li\u003e\n\u003cli\u003eEpstein, D. H., Hawkins, W. E., Covi, L., Umbricht, A., \u0026amp; Preston, K. L. (2003). Cognitive-behavioral therapy plus contingency management for cocaine use: findings during treatment and across 12-month follow-up. \u003cem\u003ePsychol Addict Behav\u003c/em\u003e,\u003cem\u003e 17\u003c/em\u003e(1), 73-82. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1224747/pdf/NIHMS2061.pdf\u003c/li\u003e\n\u003cli\u003eForbes, D., Alkemade, N., Mitchell, D., Elhai, J. D., McHugh, T., Bates, G., Novaco, R. W., Bryant, R., \u0026amp; Lewis, V. (2014). Utility of the Dimensions of Anger-5 (DAR-5) Scale as a Brief Anger Measure. \u003cem\u003eDepression and Anxiety\u003c/em\u003e,\u003cem\u003e 31\u003c/em\u003e(2), 166-173. https://doi.org/10.1002/da.22148\u003c/li\u003e\n\u003cli\u003eGoldberg, S. B., Tucker, R. P., Greene, P. A., Simpson, T. L., Kearney, D. J., \u0026amp; Davidson, R. J. (2017). Is mindfulness research methodology improving over time? A systematic review. \u003cem\u003ePLOS ONE\u003c/em\u003e,\u003cem\u003e 12\u003c/em\u003e(10). https://doi.org/10.1371/journal.pone.0187298\u003c/li\u003e\n\u003cli\u003eGu, J., Strauss, C., Crane, C., Barnhofer, T., Karl, A., Cavanagh, K., \u0026amp; Kuyken, W. (2016). Examining the factor structure of the 39-item and 15-item versions of the Five Facet Mindfulness Questionnaire before and after mindfulness-based cognitive therapy for people with recurrent depression. \u003cem\u003ePsychological Assessment\u003c/em\u003e,\u003cem\u003e 28\u003c/em\u003e(7), 791-802. https://doi.org/10.1037/pas0000263\u003c/li\u003e\n\u003cli\u003eGuo, L. (2024). The Correlation Between Mindfulness, Decentering, and Psychological Problems: A Structural Equation Modeling Meta-Analysis. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 15\u003c/em\u003e(8), 1873-1895. https://doi.org/10.1007/s12671-024-02395-6\u003c/li\u003e\n\u003cli\u003eHaig, B. D. (2023). Repositioning Construct Validity Theory: From Nomological Networks to Pragmatic Theories and Their Evaluation by Explanatory Means. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e, 17456916231195852. https://doi.org/10.1177/17456916231195852\u003c/li\u003e\n\u003cli\u003eHayes, S. C., Luoma, J. B., Bond, F. W., Masuda, A., \u0026amp; Lillis, J. (2006). Acceptance and commitment therapy: Model, processes and outcomes. \u003cem\u003eBehaviour Research and Therapy\u003c/em\u003e,\u003cem\u003e 44\u003c/em\u003e(1), 1-25.\u003c/li\u003e\n\u003cli\u003eH\u0026ouml;lzel, B. K., Lazar, S. W., Gard, T., Schuman-Olivier, Z., Vago, D. R., \u0026amp; Ott, U. (2011). How Does Mindfulness Meditation Work? Proposing Mechanisms of Action From a Conceptual and Neural Perspective. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e,\u003cem\u003e 6\u003c/em\u003e(6), 537-559. https://doi.org/10.1177/1745691611419671\u003c/li\u003e\n\u003cli\u003eIngoglia, S., Lo Coco, A., \u0026amp; Albiero, P. (2016). Development of a Brief Form of the Interpersonal Reactivity Index (B-IRI). \u003cem\u003eJournal of Perssonality Assessment\u003c/em\u003e,\u003cem\u003e 98\u003c/em\u003e(5), 461-471. https://doi.org/10.1080/00223891.2016.1149858\u003c/li\u003e\n\u003cli\u003eKabat-Zinn, J. (2013). \u003cem\u003eFull Catastrophe Living: How to cope with stress, pain and illness using mindfulness meditation\u003c/em\u003e. Piatkus. https://doi.org/10.1002/shi.88 (1996)\u003c/li\u003e\n\u003cli\u003eKeng, S. L., Smoski, M. J., \u0026amp; Robins, C. J. (2011). Effects of mindfulness on psychological health: a review of empirical studies. \u003cem\u003eClin Psychol Rev\u003c/em\u003e,\u003cem\u003e 31\u003c/em\u003e(6), 1041-1056. https://doi.org/10.1016/j.cpr.2011.04.006\u003c/li\u003e\n\u003cli\u003eKessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S. L. T., Walters, E. E., \u0026amp; Zaslavsky, A. M. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. \u003cem\u003ePsychological Medicine\u003c/em\u003e,\u003cem\u003e 32\u003c/em\u003e(6), 959-976.\u003c/li\u003e\n\u003cli\u003eKhoury, B., Vergara, R. C., \u0026amp; Spinelli, C. (2022). Interpersonal Mindfulness Questionnaire: Scale Development and Validation. \u003cem\u003eMindfulness (N Y)\u003c/em\u003e, 1-25. https://doi.org/10.1007/s12671-022-01855-1\u003c/li\u003e\n\u003cli\u003eKreplin, U., Farias, M., \u0026amp; Brazil, I. A. (2018). The limited prosocial effects of meditation: A systematic review and meta-analysis. \u003cem\u003eScientific Reports\u003c/em\u003e,\u003cem\u003e 8\u003c/em\u003e(1), 2403. https://doi.org/10.1038/s41598-018-20299-z\u003c/li\u003e\n\u003cli\u003eLietz, P. (2010). Research into Questionnaire Design: A Summary of the Literature. \u003cem\u003eInternational Journal of Market Research\u003c/em\u003e,\u003cem\u003e 52\u003c/em\u003e(2), 249-272. https://doi.org/10.2501/S147078530920120X\u003c/li\u003e\n\u003cli\u003eLiu, N., Cao, Y., \u0026amp; Xu, H. (2024). Prosocial behavior associated with trait mindfulness, psychological capital and moral identity among medical students: a moderated mediation model. \u003cem\u003eFront Psychol\u003c/em\u003e,\u003cem\u003e 15\u003c/em\u003e, 1431861. https://doi.org/10.3389/fpsyg.2024.1431861\u003c/li\u003e\n\u003cli\u003eLuthans, F., \u0026amp; Broad, J. D. (2022). Positive psychological capital to help combat the mental health fallout from the pandemic and VUCA environment. \u003cem\u003eOrgan Dyn\u003c/em\u003e,\u003cem\u003e 51\u003c/em\u003e(2), 100817. https://doi.org/10.1016/j.orgdyn.2020.100817\u003c/li\u003e\n\u003cli\u003eLuthans, F., \u0026amp; Youssef-Morgan, C. M. (2017). Psychological Capital: An Evidence-Based Positive Approach. \u003cem\u003eAnnual Review of Organizational Psychology and Organizational Behavior\u003c/em\u003e,\u003cem\u003e 4\u003c/em\u003e(1), 339-366. https://doi.org/10.1146/annurev-orgpsych-032516-113324\u003c/li\u003e\n\u003cli\u003eMalin, Y. (2023). Others in Mind: A Systematic Review and Meta-Analysis of the Relationship Between Mindfulness and Prosociality. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 14\u003c/em\u003e(7), 1582-1605. https://doi.org/10.1007/s12671-023-02150-3\u003c/li\u003e\n\u003cli\u003eMay, L. M., \u0026amp; Reinhardt, K. M. (2018). Self-Other Agreement in the Assessment of Mindfulness Using the Five-Facet Mindfulness Questionnaire. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 9\u003c/em\u003e(1), 105-116. https://doi.org/10.1007/s12671-017-0749-3\u003c/li\u003e\n\u003cli\u003eMontero-Marin, J., Allwood, M., Ball, S., Crane, C., De Wilde, K., Hinze, V., Jones, B., Lord, L., Nuthall, E., Raja, A., Taylor, L., Tudor, K., Team, M., Blakemore, S. J., Byford, S., Dalgleish, T., Ford, T., Greenberg, M. T., Ukoumunne, O. C.,\u0026hellip;Kuyken, W. (2022). School-based mindfulness training in early adolescence: what works, for whom and how in the MYRIAD trial? \u003cem\u003eEvid Based Ment Health\u003c/em\u003e. https://doi.org/10.1136/ebmental-2022-300439\u003c/li\u003e\n\u003cli\u003eMorin, L., Laurin, J. C., Doucerain, M., \u0026amp; Gr\u0026eacute;goire, S. (2024). A Multilevel Diary and Dyadic Study Exploring the Link Between New Parents\u0026rsquo; Mindfulness and Relationship Satisfaction. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 15\u003c/em\u003e(9), 2330-2346. https://doi.org/10.1007/s12671-024-02437-z\u003c/li\u003e\n\u003cli\u003eNilsson, H., \u0026amp; Kazemi, A. (2016). Reconciling and Thematizing Definitions of Mindfulness: The Big Five of Mindfulness. \u003cem\u003eReview of General Psychology\u003c/em\u003e,\u003cem\u003e 20\u003c/em\u003e(2), 183-193. https://doi.org/10.1037/gpr0000074\u003c/li\u003e\n\u003cli\u003eNitschke, J. P., \u0026amp; Bartz, J. A. (2023). The association between acute stress \u0026amp; empathy: A systematic literature review. \u003cem\u003eNeuroscience \u0026amp; Biobehavioral Reviews\u003c/em\u003e,\u003cem\u003e 144\u003c/em\u003e, 105003. https://doi.org/https://doi.org/10.1016/j.neubiorev.2022.105003\u003c/li\u003e\n\u003cli\u003eOng, C. W., Barthel, A. L., \u0026amp; Hofmann, S. G. (2024). The Relationship Between Psychological Inflexibility and Well-Being in Adults: A Meta-Analysis of the Acceptance and Action Questionnaire. \u003cem\u003eBehav Ther\u003c/em\u003e,\u003cem\u003e 55\u003c/em\u003e(1), 26-41. https://doi.org/10.1016/j.beth.2023.05.007\u003c/li\u003e\n\u003cli\u003eOrosz, G., Evans, K. M., T\u0026ouml;r\u0026ouml;k, L., Bőthe, B., T\u0026oacute;th-Kir\u0026aacute;ly, I., Sik, K., \u0026amp; G\u0026aacute;l, \u0026Eacute;. (2023). The Differential Role of Growth Mindset and Trait Mindfulness in the Motivation of Learning from Criticism. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 14\u003c/em\u003e(4), 868-879. https://doi.org/10.1007/s12671-023-02117-4\u003c/li\u003e\n\u003cli\u003ePratscher, S. D., Wood, P. K., King, L. A., \u0026amp; Bettencourt, B. A. (2018). Interpersonal Mindfulness: Scale Development and Initial Construct Validation. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 10\u003c/em\u003e(6), 1044-1061. https://doi.org/10.1007/s12671-018-1057-2\u003c/li\u003e\n\u003cli\u003eReina, C. S., Mills, M. J., \u0026amp; Sumpter, D. M. (2023). A mindful relating framework for understanding the trajectory of work relationships. \u003cem\u003ePersonnel Psychology\u003c/em\u003e,\u003cem\u003e 76\u003c/em\u003e(4), 1187-1215. https://doi.org/10.1111/peps.12530\u003c/li\u003e\n\u003cli\u003eRevelle, W. (2014). psych: Procedures for Personality and Psychological Research (V1.7.8). In. Illinois: Northwestern University\u003c/li\u003e\n\u003cli\u003eRichard, Y., Tazi, N., Frydecka, D., Hamid, M. S., \u0026amp; Moustafa, A. A. (2022). A systematic review of neural, cognitive, and clinical studies of anger and aggression. \u003cem\u003eCurr Psychol\u003c/em\u003e, 1-13. https://doi.org/10.1007/s12144-022-03143-6\u003c/li\u003e\n\u003cli\u003eRoche, M., Haar, J. M., \u0026amp; Luthans, F. (2014). The role of mindfulness and psychological capital on the well-being of leaders. \u003cem\u003eJournal of Occupational Health Psychology\u003c/em\u003e,\u003cem\u003e 19\u003c/em\u003e(4), 476. https://doi.org/10.1037/a0037183\u003c/li\u003e\n\u003cli\u003eRosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. \u003cem\u003eJournal of Statistical Software\u003c/em\u003e,\u003cem\u003e 48\u003c/em\u003e(2), 1-36.\u003c/li\u003e\n\u003cli\u003eRudkin, E., Medvedev, O. N., \u0026amp; Siegert, R. J. (2018). The Five-Facet Mindfulness Questionnaire: Why the Observing Subscale Does Not Predict Psychological Symptoms. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 9\u003c/em\u003e(1), 230-242. https://doi.org/10.1007/s12671-017-0766-2\u003c/li\u003e\n\u003cli\u003eSauer, S., Walach, H., Schmidt, S., Hinterberger, T., Lynch, S., B\u0026uuml;ssing, A., \u0026amp; Kohls, N. (2012). Assessment of Mindfulness: Review on State of the Art. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 4\u003c/em\u003e(1), 3-17. https://doi.org/10.1007/s12671-012-0122-5\u003c/li\u003e\n\u003cli\u003eScott, D., Derrett, S., Rupel, V. P., Jelsma, J., Gurung, G., Oduro, G. Y., \u0026amp; Withey-Rila, C. (2025). He/She/They - gender inclusivity in developing and using health-related questionnaires: a scoping review. \u003cem\u003eQual Life Res\u003c/em\u003e,\u003cem\u003e 34\u003c/em\u003e(1), 67-87. https://doi.org/10.1007/s11136-024-03765-2\u003c/li\u003e\n\u003cli\u003eSimonsson, O., Bergljottsdotter, C., Narayanan, J., Fisher, S., Bristow, J., Ormston, R., \u0026amp; Chambers, R. (2023). Mindfulness in Politics: A Qualitative Study on Mindfulness Training in the UK Parliament. \u003cem\u003eMindfulness\u003c/em\u003e, 1-9. https://doi.org/10.1007/s12671-023-02156-x\u003c/li\u003e\n\u003cli\u003eSofer, O. J. (2018). \u003cem\u003eSay what you mean: A mindful approach to nonviolent communication\u003c/em\u003e. Shambhala Publications.\u003c/li\u003e\n\u003cli\u003eSutton, A. (2023). Cultivating Global Health: Exploring Mindfulness Through an Organisational Psychology Lens. \u003cem\u003eMindfulness\u003c/em\u003e. https://doi.org/10.1007/s12671-023-02228-y\u003c/li\u003e\n\u003cli\u003eTindle, R., Hemi, A., \u0026amp; Moustafa, A. A. (2022). Social support, psychological flexibility and coping mediate the association between COVID-19 related stress exposure and psychological distress. \u003cem\u003eSci Rep\u003c/em\u003e,\u003cem\u003e 12\u003c/em\u003e(1), 8688. https://doi.org/10.1038/s41598-022-12262-w\u003c/li\u003e\n\u003cli\u003eTudor, K., Maloney, S., Raja, A., Baer, R., Blakemore, S. J., Byford, S., Crane, C., Dalgleish, T., De Wilde, K., Ford, T., Greenberg, M., Hinze, V., Lord, L., Radley, L., Opaleye, E. S., Taylor, L., Ukoumunne, O. C., Viner, R., Team, M.,\u0026hellip;Montero-Marin, J. (2022). Universal Mindfulness Training in Schools for Adolescents: a Scoping Review and Conceptual Model of Moderators, Mediators, and Implementation Factors. \u003cem\u003ePrev Sci\u003c/em\u003e. https://doi.org/10.1007/s11121-022-01361-9\u003c/li\u003e\n\u003cli\u003eVan Dam, N. T., van Vugt, M. K., Vago, D. R., Schmalzl, L., Saron, C. D., Olendzki, A., Meissner, T., Lazar, S. W., Kerr, C. E., Gorchov, J., Fox, K. C. R., Field, B. A., Britton, W. B., Brefczynski-Lewis, J. A., \u0026amp; Meyer, D. E. (2017). Mind the Hype: A Critical Evaluation and Prescriptive Agenda for Research on Mindfulness and Meditation. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e,\u003cem\u003e 13\u003c/em\u003e(1), 36-61. https://doi.org/10.1177/1745691617709589\u003c/li\u003e\n\u003cli\u003evan der Schans, K. L., van Kraaij, J. A. M., \u0026amp; Karremans, J. C. (2022). Through mindful colored glasses? The role of trait mindfulness in evaluating interactions with strangers. \u003cem\u003eJournal of Social and Personal Relationships\u003c/em\u003e. https://doi.org/10.1177/02654075221119770\u003c/li\u003e\n\u003cli\u003eVan Doesum, N. J., Van Lange, D. A. W., \u0026amp; Van Lange, P. A. M. (2013). Social mindfulness: Skill and will to navigate the social world. \u003cem\u003eJournal of Personality and Social Psychology\u003c/em\u003e,\u003cem\u003e 105\u003c/em\u003e(1), 86-103. https://doi.org/10.1037/a0032540\u003c/li\u003e\n\u003cli\u003eVarela, F. J., \u0026amp; Shear, J. (1999). First-person Methodologies: What, Why, How? \u003cem\u003eJournal of Consciousness Studies\u003c/em\u003e,\u003cem\u003e 6\u003c/em\u003e(2-3), 1-14.\u003c/li\u003e\n\u003cli\u003eWalach, H., Buchheld, N., Buttenm\u0026uuml;ller, V., Kleinknecht, N., \u0026amp; Schmidt, S. (2006). Measuring mindfulness\u0026mdash;the Freiburg Mindfulness Inventory (FMI). \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e,\u003cem\u003e 40\u003c/em\u003e(8), 1543-1555. https://doi.org/10.1016/j.paid.2005.11.025\u003c/li\u003e\n\u003cli\u003eWhitehouse, J., Milward, S. J., Parker, M. O., Kavanagh, E., \u0026amp; Waller, B. M. (2022). Signal value of stress behaviour. \u003cem\u003eEvolution and Human Behavior\u003c/em\u003e,\u003cem\u003e 43\u003c/em\u003e(4), 325-333. https://doi.org/10.1016/j.evolhumbehav.2022.04.001\u003c/li\u003e\n\u003cli\u003eZhang, Y., Wang, Q., \u0026amp; Zhang, Y. (2023). The Impact of Mindful Communication on Cooperative Orientation: A Cross-Sectional Survey and an RCT Study. \u003cem\u003eMindfulness\u003c/em\u003e,\u003cem\u003e 15\u003c/em\u003e(1), 100-119. https://doi.org/10.1007/s12671-023-02278-2\u003c/li\u003e\n\u003cli\u003eZinbarg, R. E., Revelle, W., Yovel, I., \u0026amp; Li, W. (2005). Cronbach\u0026rsquo;s \u0026alpha;, Revelle\u0026rsquo;s \u0026beta;, and Mcdonald\u0026rsquo;s \u0026omega;H: their relations with each other and two alternative conceptualizations of reliability. \u003cem\u003ePsychometrika\u003c/em\u003e,\u003cem\u003e 70\u003c/em\u003e(1), 123-133. https://doi.org/10.1007/s11336-003-0974-7 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6755370/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6755370/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/em\u003e. To offer another lens to study mindfulness, particularly how mindfulness influences behaviours and social relationships, this paper reports the creation of the Observed Mindful Behaviours (OMB) scale. The OMB responds to limitations in current evidence including the reliance on self-report data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/em\u003e. A 9-item observer-report scale was refined and tested in two samples (N=200) using item response theory and confirmatory factor analysis. Survey data from 190 dyads (N=380) were used to test construct validity of the refined scale. Spearman’s correlations tested a proposed nomological network for observed mindful behaviours. Regression models assessed the strength of observed correlations.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults.\u003c/strong\u003e\u003c/em\u003e \u0026nbsp;A 3-dimensional structure of the 9-item OMB was confirmed (RMSEA=0.098, w\u003csub\u003et\u003c/sub\u003e=0.88). Criterion validity was supported by good alignment with trait mindfulness (β=0.42, R\u003csup\u003e2\u003c/sup\u003e=0.15) and interpersonal mindfulness (β=0.17, R\u003csup\u003e2\u003c/sup\u003e=0.12). Construct validity tests showed congruence with empathy and divergence from psychological inflexibility, but prosocial intentions, distress, anger reactivity or psychological capital were discriminant constructs.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/em\u003e. The new OMB scale detects the extent to which a person known to the rater (family, friend or colleague) behaves in a way that is noticeably attentive, aware and accepting (or mindful). Alignment with behavioural drivers (empathy, acceptance) but not behavioural states (distress, anger, intentions), or psychological capital, helps clarify what the OMB assesses. The OMB can be used to triangulate and strengthen self-reported findings and help examine how mindfulness comes across to others.\u003c/p\u003e","manuscriptTitle":"The Observed Mindful Behaviours scale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-03 16:43:18","doi":"10.21203/rs.3.rs-6755370/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f4653ef-780a-4d2f-aa90-ea4eefe749c7","owner":[],"postedDate":"June 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-20T15:54:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-03 16:43:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6755370","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6755370","identity":"rs-6755370","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}