Exploratory and Confirmatory Bayesian Networks Identify the Central Role of Non-judging in Symptoms of Depression
Open accessAbstract
Objectives: Depression is a highly heterogeneous disorder, and meta-analyses of mindfulness-based interventions show moderate efficacy for reducing depressive symptoms. However, the mechanisms governing their efficacy remain unclear, highlighting the need for hypothesis-generating analyses to guide future research. Methods: We used Bayesian network analysis in three cross-sectional samples (N = 1135) of undergraduates and participants from the community to identify links between individual symptoms of depression and specific facets of mindfulness. In two exploratory studies, we assessed depression using the Patient Health Questionnaire (n = 384) or the Depression Anxiety and Stress Scale (n = 350) and mindfulness using the Five-Facet Mindfulness Scale. Results: Across these samples and measures, exploratory analyses indicated that non-judging was a central bridge between facets of mindfulness and symptoms of depression. We confirmed this finding in a pre-registered replication (n = 401) using a recently developed confirmatory testing framework for network analysis. Non-judging was consistently a central bridge in the networks and specifically linked to the symptoms of depression related to feelings of failure and worthlessness. Conclusions: These findings provide strong evidence that non-judging is an essential feature of mindfulness in the context of depression and provides direction for future research testing mindfulness-oriented treatment prescriptions for depression. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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Claims the paper makes
12 of 28 cited sources checked · 9 supported · 1 flagged · accuracy not yet measured
- Interpretationcitation
Consistent with another recent network analysis, the findings underscore the potential importance of non-judging in the context of depression.
“Consistent with another recent network analysis (Medvedev et al., 2021), our findings underscore the potential importance of non-judging in the context of depression.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Medvedev et al., 2021 source
- Findingown data
In sample 3, the pre-registered primary hypotheses that non-judging would bridge mindfulness and depressive symptoms were confirmed.
“We tested the specific hypotheses generated in the exploratory stages of the analysis, which confirmed our pre-registered primary hypotheses that non-judging would bridge mindfulness and symptoms of depression.”
Quote in the paperSubstantial claim - Findingown data
Evidence was inconclusive for the secondary hypothesis that 'Feeling bad about yourself' on PHQ-8 was more strongly associated with non-judging than 'Feeling down, depressed, or hopeless' (BF = 1.033).
“There was inconclusive evidence for the secondary hypothesis that the symptom of “Feeling bad about yourself” on the PHQ-8 was more strongly associated with non-judging than “Feeling down, depressed, or hopeless” (BF = 1.033)”
Quote in the paperNot a substantial claim - Findingown data
In sample 3, centrality of awareness in the PHQ-8 network was confirmed (BF = 9.915).
“We also confirmed the centrality of the awareness facet of mindfulness in the PHQ-8 network (BF = 9.915)”
Quote in the paperNot a substantial claim - Findingown data
Evidence was inconclusive for the secondary hypothesis that 'I felt I wasn't worth much as a person' on DASS-21 was more strongly associated with non-judging than 'I found it difficult to work up the initiative to do things' (BF = 1.357).
“and for the secondary hypothesis that the symptom of “I felt I wasn’t worth much as a person” on the DASS-21 depression subscale was more strongly associated with non-judging than the symptom of “I found it difficult to work up the initiative to do things” (BF = 1.357).”
Quote in the paperNot a substantial claim
- Findingown data
Pre-registered exploratory comparisons showed that strengths of individual associations were not meaningfully different in the vast majority of cases.
“The pre-registered exploratory comparisons between the networks showed that the strengths of individual associations were not meaningfully different in the vast majority of cases (Supplementary Figures 1 and 2), suggesting that the associations within the networks were likely to be similar.”
Quote in the paperNot a substantial claim - Findingown data
There was only anecdotal evidence for the secondary hypothesis that the association between 'Poor appetite or overeating?' and the describe facet was null (BF = 0.447).
“We found only anecdotal evidence to support our secondary hypothesis that the association between “Poor appetite or overeating?” and the describe facet was null (BF = 0.447).”
Quote in the paperNot a substantial claim - Findingown data
There was a large degree of difference in confidence of the confirmatory analysis depending on the measure of depression.
“However, there was a large degree of difference in the confidence of the confirmatory analysis depending on the measure of depression.”
Quote in the paperNot a substantial claim - Findingown data
There was insufficient evidence to confirm the order of strength of specific associations between non-judging and depressive symptoms on the PHQ-8.
“Moreover, comparing mindfulness facets and symptoms on the PHQ-8, there was insufficient evidence to confirm the order of the strength of specific associations between non-judging and symptoms of depression.”
Quote in the paperNot a substantial claim - Findingown data
In sample 3, evidence for centrality of non-judging was much stronger with PHQ-8 (BF = 7,998.671) than with DASS-21 depression subscale (BF = 2.448).
“However, the evidence was much stronger for the centrality of non-judging when using the PHQ-8 to assess depression (Bayes Factor (BF) = 7,998.671) than when using the DASS-21 depression subscale (BF = 2.448).”
Quote in the paperNot a substantial claim - Findingown data
In sample 3, PHQ-8 and DASS-21 depression subscale scores were highly correlated (r = 0.783, 95% CI [0.742, 0.818]).
“While highly correlated in sample 3 (r = 0.783, 95% CI [0.742, 0.818]), symptoms of depression are phrased quite differently between the two scales.”
Quote in the paperNot a substantial claim - Findingown data
In sample 2, non-judging was the only bridge between mindfulness and the depressive symptoms 'I felt I wasn't worth much as a person' and 'I found it difficult to work up the initiative to do things' (0.289).
“Non-judging was the only bridge between mindfulness and the symptoms of depression “I felt I wasn’t worth much as a person” and “I found it difficult to work up the initiative to do things” (0.289).”
Quote in the paperSubstantial claim - Findingown data
The current investigation identified and confirmed the bridge centrality of non-judging for depressive symptoms across two distinct measures of depression.
“The current investigation identified and confirm the bridge centrality of non-judging for symptoms of depression across two distinct measures of depression.”
Quote in the paperSubstantial claim - Interpretationown data
Variability between samples highlights that consideration of the specific measure used may influence specific interrelations among mindfulness facets and depressive symptoms.
“This variability between samples highlights a critical element of the approach we took—namely, that consideration of the specific measure used may influence specific interrelations among facets of mindfulness and specific symptoms of depression.”
Quote in the paperSubstantial claim - Interpretationown data
The findings underscore how different measures of depression may influence conclusions drawn in relation to mindfulness.
“Our findings also underscore how different measures of depression may influence the conclusions drawn in relation to mindfulness.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 24
- May combine two claims. 22
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationResearch investigating changes in mindfulness during MBIs for depression generally shows moderate increases in mindfulness across all facets.
“Research investigating changes in mindfulness during MBIs for depression, generally shows moderate increases in mindfulness across all facets (Gu et al., 2016; Takahashi et al., 2019).”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites Gu et al., 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Takahashi et al., 2019 source
The Results ('Changes in process variables') report significant increases in observing and nonreactivity, with nonjudging increasing by follow-up, but no significant change in describing or acting with awareness. The Discussion explicitly says the findings support increases in only some aspects of mindfulness, contrary to the claim of increases across all facets. (LLM, conf=0.90)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Classified as probably not a substantial claim.
InterpretationcitationUniform treatment approaches may be misguided because of heterogeneity in depression symptom profiles.
“suggesting that uniform treatment approaches may be misguided (Fried & Nesse, 2015).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Fried & Nesse, 2015 sourceExperimental — accuracy not yet measured
Classified as probably not a substantial claim. May combine two claims.
PremisecitationNetwork analysis is an item-level approach that evaluates individual features of a construct rather than aggregate mean level, and has become an important tool for psychopathology research including depression.
“Network analysis—an item-level approach that evaluates individual features of a construct instead of their aggregate (i.e., mean level) has grown in popularity and has become an important tool for psychopathology research, including depression (Bringmann et al., 2015).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Bringmann et al., 2015 source
The Introduction (p. 2) contrasts the network approach’s focus on relations between individual symptoms with a focus on mean symptom levels, and the Conclusion (p. 2) describes its value for depression research. The paper does not establish that network analysis had grown in popularity or had already become an important tool across psychopathology research; it describes the approach as recently developed. (LLM, conf=0.83)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMindfulness training leads to greater dispositional mindfulness.
“Moreover, mindfulness training leads to greater dispositional mindfulness (Kiken et al., 2015).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Kiken et al., 2015 source
The Discussion reports that participants with greater increases in state mindfulness during the intervention also increased more in trait mindfulness. But it says the study design did not permit true causal conclusions, so the claim that training *leads to* greater dispositional mindfulness is stronger than the evidence supports. Page numbers were not provided. (LLM, conf=0.88)
Experimental — accuracy not yet measured
May combine two claims.
InterpretationcitationAddressing individual symptoms of depression is valuable because symptom profiles vary widely and heterogeneity can lead to misleading conclusions about interrelationships among constructs.
“There is significant value in addressing individual symptoms of depression because of the wide range of different symptom profiles for depression, where heterogeneity among individuals can lead to misleading conclusions about the interrelationships among constructs (Fried & Nesse, 2015).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Fried & Nesse, 2015 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMeta-analyses of specific manualized mindfulness-based interventions show moderate reductions in depressive symptoms.
“Meta-analyses of specific, manualized mindfulness based interventions (MBIs) such as mindfulness-based cognitive therapy and mindfulness-based stress reduction have shown moderate reductions in symptoms of depression (Chi et al., 2018; Galante et al., 2013).”
Quote in the paperNot a substantial claim2 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
PremisecitationDepression is heterogeneous, with symptom profiles differing widely between individuals.
“Depression is a heterogeneous psychological concern (Zimmerman et al., 2015), with symptom profiles differing widely between individuals”
- Also stated in: § Discussion · plain
“Prior work has highlighted the heterogeneity of depression symptoms (Fried & Nesse, 2015).”
Quote in the paperSubstantial claim1 of 2 sources checked- Also stated in: § Discussion · plain
May combine two claims.
PremisecitationMedvedev et al. (2021) found a strong inverse association between non-judgment and emotional distress, but did not examine specific depression symptoms.
“using network analyses, Medvedev et al. (2021) found a strong inverse association between the mindfulness facet of non-judgment and emotional distress; however, specific symptoms of depression were not examined.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Medvedev et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationNetwork perspective can provide insight into complex interrelations between different features of mindfulness cross-sectionally and before and after an intervention.
“The network perspective can also provide insight into complex interrelations between different features of mindfulness cross-sectionally (Heeren et al., 2021) as well as before and after an intervention (mindfulness-based stress reduction; Roca et al., 2019).”
Quote in the paperNot a substantial claim2 of 2 sources checkedMay combine two claims.
Findingown dataThe PHQ-8 showed robust evidence in favor of the hypothesis, while evidence for bridge centrality of non-judging with DASS-21 was much weaker.
“While the PHQ-8 showed robust evidence in favor of the hypothesis, the evidence supporting the bridge centrality of non-judging when assessing depression using the DASS-21 subscale was much weaker.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn sample 1, the describe facet had a bridge centrality of 0.143 and a positive association with the symptom 'Poor appetite or overeating?'
“Unexpectedly, we also found that the describe facet had a bridge centrality of 0.143 with a positive association with a “Poor appetite or overeating?””
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataComparing samples 2 and 3, there were no meaningful differences in edge strength between non-judging and DASS-21 depression subscale; of 66 total associations, only 2 (3%) were meaningfully different.
“In comparing samples 2 and 3, there were no meaningful differences in edge strength between non-judging and the DASS-21 depression subscale; of the 66 total associations in the network, only 2 (3%) had meaningfully different associations.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataComparing sample 1 and sample 3, there were no meaningful differences in edge strength between non-judging and PHQ-8 depressive symptoms; of 78 total edges, only 6 (8%) were different.
“In comparing sample 1 and sample 3, there were no meaningful differences in edge strength between non-judging and symptoms of depression measured by the PHQ-8; of the 78 total edges of which only 6 (8%) were different.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThis primary hypothesis was preregistered, new data were collected, and the hypothesis was confirmed in a subsequent network analysis.
“We then preregistered this primary hypothesis (along with several secondary ones), collected new data, and confirmed this hypothesis in a subsequent network analysis.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataComparing association strengths between networks, individual associations remained similar, but there was substantial variability such that evidence for specific differences in magnitude was inconclusive.
“We did demonstrate that in comparing association strengths between networks, individual associations remained similar. However, there was substantial variability in association strengths such that the evidence to support specific differences in magnitude between associations was inconclusive.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFew differences were identified in comparing the networks, suggesting that associations remained relatively stable even across cross-sectional samples.
“It is worth noting that we identified few differences in comparing the networks, suggesting that associations remained relatively stable even across cross-sectional samples (as has been found by other researchers, for instance in the context of post-traumatic stress disorder, Duek et al., 2021).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Duek et al., 2021 source
May combine two claims.
Findingown dataIn sample 1, non-judging had a bridge centrality of 0.339 and awareness had a bridge centrality of 0.313, both negatively associated with depressive symptoms.
“The non-judging facet had a bridge centrality of 0.339, and the awareness facet had a bridge centrality of 0.313, with negative associations to symptoms of depression.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn sample 2, awareness was linked to the symptom 'I found it difficult to work up the initiative to do things' but was not central to the network.
“While awareness was linked to the symptom of depression “I found it difficult to work up the initiative to do things”, the facet was not found to be central to the network.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationThe relationship between different facets of mindfulness and symptoms of depression varies.
“the relationship between different facets of mindfulness and symptoms of depression varies (Medvedev et al., 2018).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Medvedev et al., 2018 source
Classified as probably not a substantial claim.
PremisecitationMindfulness is considered a multi-dimensional construct.
“Mindfulness is considered a multi-dimensional construct (Baer, 2011)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Baer, 2011 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationGreater self-reported dispositional mindfulness is associated with fewer depressive symptoms in both clinical and non-clinical samples.
“The relationship between dispositional mindfulness and depression has been relatively well established, with greater self-reported mindfulness associated with fewer symptoms of depression in both clinical (Gu et al., 2016) and non-clinical (Medvedev et al., 2018) samples.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Gu et al., 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Medvedev et al., 2018 source
Classified as probably not a substantial claim.
PremisecitationMindfulness can be measured through self-report as a trait.
“there is evidence that mindfulness can be measured through self-report as a trait (Truong et al., 2020), rather than reflecting only the state of mindfulness.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Truong et al., 2020 source
Classified as probably not a substantial claim.
Interpretationown dataFrom two exploratory analyses, the data-derived hypothesis was developed that non-judging serves as the most central bridge between mindfulness and depression when controlling for all other associations.
“From two exploratory analyses, we developed the data-derived hypothesis that non-judging serves as the most central bridge between mindfulness and depression when controlling for all other associations.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationNon-judging has been shown to mediate the relationship between self-criticism and depression.
“In the context of mindfulness, the facet of non-judging has been shown to mediate the relationship between self-criticism and depression (Rohde et al., 2014).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Rohde et al., 2014 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataData were collected during the COVID-19 pandemic, and it is possible that COVID-19-related experiences influenced the network structure, but this was not addressed in analyses.
“Of further note, these data were collected during the COVID-19 pandemic. It is possible that there were meaningful influences in COVID-19-related experiences (such as a loss due to COVID-19) that may have impacted the network structure. While we did not address the influence of the pandemic within the analyses, we do summarize some relevant data in Table 1.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe presence or absence of a concentration symptom may explain why the awareness facet was only central for the PHQ-8 network.
“in particular, the presence/absence of a concentration symptom may explain why the awareness facet was only central for the PHQ-8 network.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitationIn sample 3, participants completed two different measures of depression within the same survey, which may lead to common methods bias.
“Additionally, in sample 3, participants completed two different measures of depression within the same survey, which may lead to a “common methods bias” where responses to one questionnaire influenced responses to the other questionnaire (Podsakoff et al., 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Podsakoff et al., 2012 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSelf-criticism has long been considered a central feature of depression.
“Self-criticism has long been considered a central feature of depression (Beck, 1964).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Beck, 1964 source
May combine two claims.
Study design and conductcitationA large proportion of sample 3 data (35%) was collected from MTURK, and quality of MTURK data has become increasingly poor since 2018, limiting conclusions.
“Also, a large proportion of sample 3 data (35%) was collected from MTURK. While we used attention checks and an open-ended response item to reduce the incidence of “bots,” automated, or inattentive responding, there is growing concern that the quality of MTURK data has become increasingly poor since 2018 (Chmielewski & Kucker, 2020), which limits the conclusions we can draw.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Chmielewski & Kucker, 2020 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningThe pre-registered confirmatory Bayesian network approach addresses some but not all limitations of network analysis.
“Our pre-registered confirmatory Bayesian network approach addresses some but not all the limitations of network analysis.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe Bayesian network approach does not remedy psychometric inadequacies such as low internal reliability of the observe facet nor does it account for construct validity of measures.
“The Bayesian network approach does not remedy psychometric inadequacies such as the low internal reliability of the observe facet nor does it take into account the construct validity of the measures (Epskamp, et al., 2017a, 2017b; Hallquist et al., 2019).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Epskamp, et al., 2017a, 2017b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Hallquist et al., 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningOne potential interpretation is that the PHQ-8 and DASS-21 depression subscale measure depression in somewhat different ways.
“One potential interpretation may be that the PHQ-8 and DASS-21 depression subscale measure depression in somewhat different ways.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenThe study has limitations including moderate sample size and majority undergraduate participants.
“The study has several limitations, including the moderate sample size and that the majority of participants were undergraduate students.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenLack of information regarding meditation experience in the samples is a limitation.
“our lack of information regarding meditation experience in our samples is a limitation that should be considered in future research.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
PremisecitationThe PHQ was developed as a brief screening assessment tool for depression, whereas the DASS was developed as an integrated measure of negative affect, though its depression measurement is distinct.
“The PHQ was specifically developed as a brief screening assessment tool for depression (Kroenke et al., 2009), whereas the DASS was developed as an integrated measure of negative affect, although the measurement of depression within the scale is distinct from the other scales (Henry & Crawford, 2005).”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe syntax, data, and replication preregistration for sample 3 are available.
“The syntax, data, and the replication preregistration for sample 3 are available at (https://osf.io/hvzrd/).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenAttention check questions were included and participants who answered any incorrectly were excluded from further participation.
“Several attention check questions were included in the survey, and participants who answered any of these incorrectly were excluded from further participation.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataInternal reliability of some mindfulness subscales was fairly low, which may have impacted findings.
“Additionally, the internal reliability of some of the mindfulness subscales was fairly low, which may have impacted our findings.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThese findings provide further evidence for the importance of non-judging in the context of depression and links to specific symptoms reflecting heightened self-criticism (e.g., feelings of failure or worthlessness).
“These findings provide further evidence for the importance of non-judging in the context of depression as well as links to specific symptoms reflecting heightened self-criticism (e.g., feelings of failure or worthlessness).”
Quote in the paperSubstantial claim
The paper relies on this without support.
Little existing work tests specific mechanisms of change within mindfulness-based interventions for depression.
“While promoting non-judging is a core feature of MBIs, there is little existing work testing specific mechanisms of change within MBIs for depression.”
The paper relies on this without support.
Promoting non-judging is a core feature of mindfulness-based interventions.
“While promoting non-judging is a core feature of MBIs, there is little existing work testing specific mechanisms of change within MBIs for depression.”
The paper relies on this without support.
Not all individuals respond to mindfulness-based interventions equally.
“Yet, not all individuals respond to MBIs equally.”
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Network analysis of PTSD and depressive symptoms in 158,139 treatment‐seeking veterans with PTSD
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Truong, Q. C., Krägeloh, C. U., Siegert, R. J., Landon, J., & Medvedev, O. N. (2020) · Mindfulness · doi:10.1007/s12671-020-01324-7 · Cited by 65 · see citing works
Takahashi, T., Sugiyama, F., Kikai, T., Kawashima, I., Guan, S., Oguchi, M., Uchida, T., & Kumano, H. (2019) · BioPsychoSocial Medicine · doi:10.1186/s13030-019-0145-4 · Cited by 61 · see citing works
A network approach to the five-facet model of mindfulness
Heeren, A., Lannoy, S., Coussement, C., Hoebeke, Y., Verschuren, A., Blanchard, M. A., Chakroun-Baggioni, N., Philippot, P., & Gierski, F. (2021) · Scientific Reports · doi:10.1038/s41598-021-94151-2 · Cited by 39 · see citing works
Does mindfulness change the mind? A novel psychonectome perspective based on Network Analysis
Roca, P., Diez, G. G., Castellanos, N., & Vazquez, C. (2019) · PLOS ONE · doi:10.1371/journal.pone.0219793 · Cited by 37 · see citing works
Oka, T., Tanahashi, T., Lkhagvasuren, B., & Yamada, Y. (2019) · BioPsychoSocial Medicine · doi:10.1186/s13030-019-0168-x · Cited by 25 · see citing works
Mindful attention regulation and non-judgmental orientation in depression: A multi-method approach
Rohde, K., Adolph, D., Dietrich, D. E., & Michalak, J. (2014) · Biological Psychology · doi:10.1016/j.biopsycho.2014.06.009 · Cited by 20 · see citing works
Pawłowska, S., Gierowski, J., Stonio, B., Juchniewicz, M., Ficek, M., Kruczkowski, M., & Szczerska, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-00195-9 · Cited by 3 · see citing works
Flagged first, then by citations
1 of the 33 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Networks of inflammation, depression, and cognition in aging males and females
Chalmers, R. A., Cervin, M., Choo, C. C., Baune, B. T., Trollor, J. N., Numbers, K. T., Sachdev, P. S., Brodaty, H., Kochan, N. A., & Medvedev, O. N. (2022) · Aging Clinical and Experimental Research · doi:10.1007/s40520-022-02198-6 · Cited by 30 · see citing works
Statistical evidence in psychological networks
Huth, K. B. S., Haslbeck, J. M. B., Keetelaar, S., van Holst, R. J., & Marsman, M. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02314-2 · Cited by 31 · see citing works
Big Five of Mindfulness and Personality: Cross-Cultural Network Analysis
Roemer, A., Cervin, M., Medvedeva, A., Bravo, A. J., & Medvedev, O. N. (2023) · Mindfulness · doi:10.1007/s12671-023-02293-3 · Cited by 16 · see citing works
“A network contains nodes and edges, with nodes being variables and edges pairwise associations (Rubin et al., 2021 ).”
Chalmers, R. A., Cervin, M., & Medvedev, O. N. (2022) · Springer eBooks · doi:10.1007/978-3-030-77644-2_70-1 · Cited by 10 · see citing works
Aldbyani, A., & Al-Harbi, M. F. O. (2026) · Mindfulness · doi:10.1007/s12671-026-02837-3 · Cited by 4 · see citing works
“Empirical work comparing Islamic-spiritual mindfulness interventions has found significant reductions in anxiety and depression through practices aligned with tazkiyah (Aldbyani, 2024; Querstret et al., 2018; Rubin et al., 2021).”
The Associations between Mindfulness Processes and Emotional Distress Symptoms: A Network Analysis
Li, P., Zhang, Y., Zhou, Y., Qiu, T., Fang, Y., & Chen, Z. (2024) · Mindfulness · doi:10.1007/s12671-024-02478-4 · Cited by 5 · see citing works
Zhu, H., Zeng, J., Liu, L., & Gong, J. (2025) · Mindfulness · doi:10.1007/s12671-025-02683-9 · Cited by 2 · see citing works
“This finding aligns with existing cross-sectional network analysis (Medvedev et al., 2021; Rubin et al., 2021) and meta-analytic evidence (Carpenter et al., 2019), solidifying Non-Judging ’s unique role in mitigating negative affect and psychological distress.”
A Network Analysis of Symptoms of Post-Traumatic Stress Disorder and Facets of Mindfulness
Rubin, M. (2024) · Trauma Care · doi:10.3390/traumacare4020013 · Cited by 2 · see citing works
“While network analyses have also examined facets of mindfulness alone [6] and in relation to mental health concerns like depression [7], to the best of our knowledge no research has examined PTSD symptoms and the facets of mindfulness in the context of network analysis.”
BackgroundSelf-citationChen, M., Xin, Z., He, M., Wang, Z., Li, Y., Hofmann, S. G., & Liu, X. (2025) · Mindfulness · doi:10.1007/s12671-025-02656-y · Cited by 1 · see citing works
“A recent cross-sectional network analysis further demonstrated that NONJ uniquely contributes to depressive symptoms in the general population and identified it as the most central bridge node between mindfulness and depression (Rubin et al., 2021).”
Visual Data Mining in Mental Health : Network Analysis of Mindfulness Processes and Anxiety Symptoms
Luo, H., Zhou, Y., Fang, Y., et al. (2024) · International Conference on Computer Information Science and Application Technology (CISAT) · doi:10.1109/cisat62382.2024.10695215 · Cited by 1 · see citing works
“Research indicates that specific mindfulness processes, such as “being aware of bodily sensations” and “non-judging,” show distinct associations with symptoms like eating disorders and depression [2], [3].”
BackgroundChalmers, R. A., Cervin, M., & Medvedev, O. N. (2025) · Springer eBooks · doi:10.1007/978-3-031-47219-0_70 · Cited by 1 · see citing works
Barbera, E. R., & Yalch, M. M. (2026) · Journal of Trauma & Dissociation · doi:10.1080/15299732.2025.2599754
“…awareness, non-judgment, and non-reactivity facets are all associated with lower anxiety, depression, and posttraumatic distress (Chopko et al., 2022; Desrosiers et al., 2013; Kalill et al., 2014; Martin et al., 2018; Medvedev et al., 2018; Rubin, 2024; Rubin et al., 2021; Schoorl et al., 2015).”
Network Analysis for Assessment in International Contexts
Adu, P., & Medvedev, O. N. (2026) · Springer eBooks · doi:10.1007/978-3-030-89738-3_6-1
- Authors
- Rubin, M., Papini, S., Dainer-Best, J., Zaizar, E. D., Smits, J. A. J., & Telch, M. J.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Rubin, Mikael
- Venue
- Mindfulness
- Published
- 2021-08-19
- Volume
- 12
- Issue
- 10
- Pages
- 2544-2551
- ISSN
- 1868-8527 (ISSN-L)
- 1868-8535
- PMC
- PMC8374114
- OpenAlex
- W3193295583
- Semantic Scholar
- 5869ec0bbf7f1a9255cb174acc03481e5429075c
- Cited by
- 13
- References
- 33
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 1 · 2022: 2
- FWCI
- 1.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Mindfulness (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Mindfulness and Compassion Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- depression, non-judgment, depressive symptoms, worthlessness, Bayesian network analysis, mindfulness-based interventions, therapeutic mechanisms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read under definition version 3 (extract-v3) on 2026-09-28.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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