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Treatment as a moderator and executive function as a mediator of the effect of a mindfulness ecological momentary intervention for generalized anxiety disorder

Published online by Cambridge University Press:  15 October 2024

Nur Hani Zainal*
Affiliation:
Department of Psychology, National University of Singapore, Kent Ridge, Singapore Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
Michelle G. Newman
Affiliation:
Department of Psychology, The Pennsylvania State University, University Park, PA, USA
*
Corresponding author: Nur Hani Zainal; Email: [email protected]
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Abstract

Background

Theory and research indicated that executive functioning (EF) correlated with, preceded, and stemmed from worry in generalized anxiety disorder (GAD). The present secondary analysis (Zainal & Newman, 2023b) thus determined whether EF domains mediated the effect of a 14-day (5 prompts/day) mindfulness ecological momentary intervention (MEMI) against a self-monitoring control (SM) for GAD.

Method

Participants (N = 110) diagnosed with GAD completed self-reported (Attentional Control Scale, GAD Questionnaire, Perseverative Cognitions Questionnaire) and performance-based tests (Letter-Number Sequencing, Stroop, Trail Making Test-B, Verbal Fluency) at baseline, post-treatment, and one-month follow-up (1MFU). Causal mediation analyses determined if pre-post changes in EF domains preceded and mediated the effect of MEMI against SM on pre-1MFU changes in GAD severity and trait repetitive negative thinking (RNT).

Results

MEMI was more efficacious than SM in improving pre–post inhibition (β = −2.075, 95% [−3.388, −0.762], p = .002), working memory (β = 0.512, 95% [0.012, 1.011], p = .045), and set-shifting (β = −2.916, 95% [−5.142, −0.691], p = .010) but not verbal fluency and attentional control. Within groups, MEMI but not SM produced improvements in all examined pre–post EF outcomes except attentional control. Only pre–post improvements in inhibition mediated the effect of MEMI against SM on pre-1MFU reductions in GAD severity (β = −0.605, 95% [−1.357, −0.044], p = .030; proportion mediated = 7.1%) and trait RNT (β = −0.024, 95% [−0.054, −0.001], p = .040; proportion mediated = 7.4%). These patterns remained after conducting sensitivity analyses with non-linear mediator-outcome relations.

Conclusions

Optimizing MEMI for GAD might entail specifically boosting inhibition plausibly by augmenting it with dialectical behavioral therapy, encouraging high-intensity physical exercises, and targeting negative emotional contrast avoidance.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

Executive function (EF) is defined as a collection of advanced cognitive processes to manage purpose-guided actions and thoughts, encompassing abilities such as adaptability, memory, and planning (Friedman & Miyake, Reference Friedman and Miyake2017). EF has been theorized to include inhibitory control (or inhibition; managing undesired or unhelpful behaviors), shifting (cognitively transitioning between various tasks), and working memory (WM; processing real-time inputs while attending to the task at hand; Miyake & Friedman, Reference Miyake and Friedman2012) in related yet dissociable ways (Rodríguez-Nieto et al. Reference Rodríguez-Nieto, Seer, Sidlauskaite, Vleugels, Van Roy, Hardwick and Swinnen2022). Verbal fluency (VF) has been further recognized as a distinguishable EF component, connecting to more specialized language-based WM domains (Gustavson et al., Reference Gustavson, Panizzon, Franz, Reynolds, Corley, Hewitt and Friedman2019). Relatedly, attentional control (AC; subjective ability to maintain stable focus on the task at hand) has been posited to underpin EF, as it is closely related to meta-cognitive processes (Drigas & Karyotaki, Reference Drigas and Karyotaki2017). Since problems with EF and AC are linked to various biopsychosocial issues (Lawson, Hook, & Farah, Reference Lawson, Hook and Farah2018; Woon, Farrer, Braman, Mabey, & Hedges, Reference Woon, Farrer, Braman, Mabey and Hedges2017; Yang, Shields, Guo, & Liu, Reference Yang, Shields, Guo and Liu2018), developing efficacious interventions to enhance EF outcomes is crucial.

Mindfulness-based interventions (MBIs) have been theorized as potentially efficacious for EF by possibly enhancing resting-state functional connectivity between brain regions linked to EF (Taren et al., Reference Taren, Gianaros, Greco, Lindsay, Fairgrieve, Brown and Creswell2017). Further, intentionally focusing on the current moment without judgment and fully accepting emotions could aid in reorienting attention to the task and intended aims (Lutz et al., Reference Lutz, Slagter, Rawlings, Francis, Greischar and Davidson2009), possibly enhancing AC and EF. Concordant with these propositions, a qualitative review observed that even brief MBIs could strengthen inhibition and WM EF domains (Zhou, Liu, & Deng, Reference Zhou, Liu and Deng2020). Extending that report, a meta-analysis of 111 randomized controlled trials (RCTs) found that MBIs v. active controls produced small-to-medium efficacy on executive attention, WM, inhibition, and set-shifting but did not differentially affect VF (Zainal & Newman, Reference Zainal and Newman2024b). Together, enhanced AC and EF might function as change mechanisms of the impact of MBIs on clinical outcomes, such as reductions in depression and anxiety symptoms (Blanck et al., Reference Blanck, Perleth, Heidenreich, Kröger, Ditzen, Bents and Mander2018; Spijkerman, Pots, & Bohlmeijer, Reference Spijkerman, Pots and Bohlmeijer2016).

Mediation research offers invaluable perspectives into proxy change mechanisms, frequently recognized as the central methodology in the exploration of how or why MBIs or other therapies work (Kazdin, Reference Kazdin2007). It determines whether a mediator variable statistically elucidates the link between treatment and its outcome. The implication is that enhancing our grasp of how MBI change mechanisms occur enables clinicians to focus more precisely on essential EF elements while eliminating ineffective targets. Such efforts might lead to more effective treatments that offer quicker and stronger clinical enhancements (Maddock & Blair, Reference Maddock and Blair2021).

Only a few RCTs examined EF as a mediator of the effect of MBIs. In Noone and Hogan (Reference Noone and Hogan2018), performance-based EF did not mediate the effect of MBI on critical thinking and associated skills in undergraduates. Relatedly, in a cross-sectional study, higher trait mindfulness predicted more positive affect and less negative affect via better self-reported EF in everyday contexts in undergraduates (Short, Mazmanian, Oinonen, & Mushquash, Reference Short, Mazmanian, Oinonen and Mushquash2016). However, both studies recruited unselected undergraduates. Unselected samples are problematic since task-based EF and AC have been shown to correlate frequently with high levels of psychiatric symptoms (Abramovitch, Short, & Schweiger, Reference Abramovitch, Short and Schweiger2021).

Improvement in AC and EF could plausibly be a proxy change mechanism of an MBI, and such changes would precede the alleviation of worry and other repetitive negative thinking (RNT) tendencies for people with generalized anxiety disorder (GAD). Attentional control theory (ACT; Eysenck & Derakshan, Reference Eysenck and Derakshan2011) and the cognitive model (Hirsch & Mathews, Reference Hirsch and Mathews2012) posit that EF and associated issues, such as biased attention toward threat and unhelpful interpretations, generate excessive and uncontrollable worry (core GAD symptoms). Buttressing ACT, a meta-analysis showed negative correlations between rumination and both inhibition (Pearson's r = −0.23) and set-shifting (r = −0.19; Yang, Cao, Shields, Teng, and Liu, Reference Yang, Cao, Shields, Teng and Liu2017). Supporting the cognitive model, compromised set-shifting, inhibition, WM, and inductive reasoning abilities predicted GAD diagnosis and increased symptom severity after nine years among community adults (Zainal & Newman, Reference Zainal and Newman2018).

Additionally, scar theories (McEwen & Gianaros, Reference McEwen and Gianaros2011; Ottaviani et al., Reference Ottaviani, Thayer, Verkuil, Lonigro, Medea, Couyoumdjian and Brosschot2016) posit that worry and RNT trigger persistent activation and disturbance of interconnected neuroendocrine and immune regulatory systems that may build up allostatic load over time. Allostatic load is defined as the gradual deterioration of the hypothalamic-pituitary-adrenal axis (HPA) and related systems across time (McEwen & Seeman, Reference McEwen and Seeman1999), potentially impacting EF-implicated brain areas (Juster, McEwen, & Lupien, Reference Juster, McEwen and Lupien2010). Concurring with scar theories, heightened excessive worry and other GAD symptoms predicted future EF declines (Zainal & Newman, Reference Zainal and Newman2021), and increased inflammation consistently mediated this prospective association in separate samples (Zainal & Newman, Reference Zainal and Newman2022a, Reference Zainal and Newman2022b). Collectively, since AC and EF issues are bidirectionally related to pathological worry and other RNT habits, MBIs might be efficacious for GAD by improving AC and EF as proxy change mechanisms.

On that note, typical MBIs included 8–16 weeks of mindfulness-based stress reduction (MBSR; Kabat-Zinn, Reference Kabat-Zinn1990) and mindfulness-based cognitive therapy (MBCT; Williams, Russell, & Russell, Reference Williams, Russell and Russell2008), coupled with daylong meditation retreats (Creswell, Reference Creswell2017). Nevertheless, research uniformly showed that most people with GAD would not seek out and attend traditional face-to-face psychotherapy (including MBIs; e.g. Olfson, Blanco, Wall, Liu, & Grant, Reference Olfson, Blanco, Wall, Liu and Grant2019), and some of them would instead prefer to solve their mental health struggles independently (Goetter et al., Reference Goetter, Frumkin, Palitz, Swee, Baker, Bui and Simon2020; Rackoff, Fitzsimmons-Craft, Taylor, Wilfley, & Newman, Reference Rackoff, Fitzsimmons-Craft, Taylor, Wilfley and Newman2023). Scalable, evidence-based mental health apps (or ecological momentary interventions; EMIs) might somewhat solve this issue (Marciniak et al., Reference Marciniak, Shanahan, Rohde, Schulz, Wackerhagen, Kobylinska and Kleim2020). EMIs use experience sampling methods to offer individualized assistance in real-time by recognizing a person's inner and outer contexts and emotional struggles (Henry et al., Reference Henry, Hansen, Chimoff, Pokstis, Kiderman, Naim and Brotman2024). Mindfulness EMIs (MEMIs), particularly those with mood-tracking attributes, exhibited modest yet notable efficacy against self-monitoring placebos (SM) on GAD symptoms (cf. recent meta-analysis by Linardon et al., Reference Linardon, Torous, Firth, Cuijpers, Messer and Fuller-Tyszkiewicz2024). These findings suggested that a MEMI against SM might reduce GAD symptoms and RNT tendencies by enhancing AC and EF.

The current study was a secondary analysis of an RCT for GAD. In prior reports, a 14-day MEMI, compared to SM, reduced RNT and GAD severity (Zainal & Newman, Reference Zainal and Newman2024c, Reference Zainal and Newman2023b) and enhanced various empathy domains (Zainal & Newman, Reference Zainal and Newman2024a) to a greater degree from pre-treatment to one-month follow-up (1MFU). Two new hypotheses based on theory and evidence reviewed were tested. Hypothesis 1 predicted that a MEMI would significantly outperform SM in enhancing pre-post AC, inhibition, set-shifting, VF, and WM. Hypothesis 2 predicted that the effect of a MEMI against SM on reducing pre-1MFU GAD severity and trait RNT would be significantly mediated by improved pre-post AC, inhibition, set-shifting, VF, and WM.

Method

Study design

The Pennsylvania State University Institutional Review Board granted ethical permission to conduct our study. Our pre-registered RCT (NCT04846777 and https://osf.io/7g4su) used a mixed design involving two treatments (MEMI and SM) and three time points (pre-randomization, post-intervention, and 1MFU). Online Supplementary Appendix A offers an extensive summary of the methodology, detailing compensation details, power analysis, and pre-randomization measures. Figure 1 presents the CONSORT (Consolidated Standards of Reporting Trials) diagram illustrating participant flow from enrollment through study completion (Montgomery et al., Reference Montgomery, Grant, Mayo-Wilson, Macdonald, Michie, Hopewell and Group2018).

Figure 1. CONSORT flowchart of participant recruitment and progress.

Note: CONSORT, Consolidated Standards of Reporting Trials; GAD, generalized anxiety disorder; GADQ-IV, GAD questionnaire- fourth edition; MEMI, mindfulness ecological momentary intervention; SMP, self-monitoring app or placebo.

Eligibility criteria

Individuals were recruited from the subject pool and local community via initial screening of GAD criteria based on the Generalized Anxiety Disorder Questionnaire-IV (GADQ-IV; Newman et al., Reference Newman, Zuellig, Kachin, Constantino, Przeworski, Erickson and Cashman-McGrath2002), a minimum age of 18 years, and ownership of an iPhone or Android smartphone. They also had to be actively seeking treatment but not presently receiving any intervention (e.g. psychotropic medications) for mental health. Relatedly, they had to be meditation-naïve and report no prior experience with structured mindfulness practices. Those who consented were invited to participate in a 30-minute clinical interview using the Anxiety and Related Disorders Interview Schedule for DSM-5 (ADIS-5; Brown & Barlow, Reference Brown and Barlow2014) to confirm Diagnostic and Statistical Manual-Fifth Edition Text Revision (DSM-5-TR; American Psychiatric Association, 2022) GAD diagnosis. Exclusion criteria were presence of substance abuse disorders, suicidal thoughts, manic episodes, or psychotic disorders.

Participants

We enrolled a total of 110 participants diagnosed with GAD and meeting study eligibility criteria; 42 were randomly assigned to SM and 68 to MEMI. Table 1 presents the attributes of recruited participants. There was no between-group difference in baseline diagnoses (alcohol use disorder, anorexia nervosa, binge-eating disorder, major depressive episode [current or recurrent], obsessive-compulsive disorder [OCD], panic disorder, post-traumatic stress disorder [PTSD], social anxiety disorder [SAD], substance use disorder).

Table 1. Sociodemographic data of study participants in the mindfulness ecological momentary intervention (MEMI) and self-monitoring app (SM) (N = 110)

Note. GAD-Q-IV, generalized anxiety disorder questionnaire-fourth edition; OCD, obsessive-compulsive disorder; PTSD, post-traumatic stress disorder.

Pre–post mediator measures

AC

The Attentional Control Scale (ACS; Derryberry & Reed, Reference Derryberry and Reed2002) comprised 20 self-assessed items, combining a 9-item attentional focus measure with an 11-item attentional shifting subtest. It demonstrated strong convergent validity (agreement with related measures), good predictive validity (Judah, Grant, Mills, & Lechner, Reference Judah, Grant, Mills and Lechner2014), satisfactory discriminant validity (differentiation from unrelated constructs; Williams, Rau, Suchy, Thorgusen, & Smith, Reference Williams, Rau, Suchy, Thorgusen and Smith2017), and high retest reliability (Abasi, Mohammadkhani, Pourshahbaz, & Dolatshahi, Reference Abasi, Mohammadkhani, Pourshahbaz and Dolatshahi2017). The alpha (internal consistency) values in the present study were .87, .90, and .90 at pre-randomization, post-intervention, and 1MFU, respectively. Higher scores denoted better AC skills.

Inhibition

The Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, Reference Delis, Kaplan and Kramer2001) Color-Word Inhibition Test (CWIT) Condition 3, a modification of the classic Stroop test (Stroop, Reference Stroop1935), measured performance-based inhibition. Participants viewed a matrix of 50 color words with three ink colors (blue, red, and green). They were directed to verbalize the ink color as quickly and accurately as possible and to abstain from naming the word. The CWIT offers an advantage in measuring inhibition by eliminating the confounding effect of triggering symptoms with emotional words (Hsu & Davison, Reference Hsu and Davison2017). CWIT scores were correlated with GAD symptoms (Beaudreau et al., Reference Beaudreau, Hantke, Mashal, Gould, Henderson and O'Hara2017; Dorenkamp, Irrgang, & Vik, Reference Dorenkamp, Irrgang and Vik2023). The D-KEFS CWIT had good reliability and construct validity in assessing EF (Delis, Kramer, Kaplan, & Holdnack, Reference Delis, Kramer, Kaplan and Holdnack2004; Homack, Lee, & Riccio, Reference Homack, Lee and Riccio2005). Higher scores were indicative of poorer performance.

Set-shifting

The paper-based Trail Making Test-B (TMT-B) assessed set-shifting, attention, and processing speed (Army Individual Test Battery, 1944). Participants were required to alternately connect numbers and letters sequentially in ascending order as quickly as possible, with the assessor recording their completion time or speed (Spreen & Strauss, Reference Spreen and Strauss1998). The TMT-B had good retest reliability (Bracken, Mazur-Mosiewicz, & Glazek, Reference Bracken, Mazur-Mosiewicz and Glazek2019) and strong convergent validity (Osuka, Kojima, Sakurai, Watanabe, & Kim, Reference Osuka, Kojima, Sakurai, Watanabe and Kim2020; Plotnik et al., Reference Plotnik, Doniger, Bahat, Gottleib, Gal, Arad and Heled2017). Higher TMT-B scores indicated poorer set-shifting skills.

VF

VF was assessed via the D-KEFS VF subtest, comprising three progressively challenging subtests (Delis et al., Reference Delis, Kaplan and Kramer2001). This encompassed Letter Fluency (swiftly naming words beginning with a designated letter), Category Fluency (swiftly naming words within a specified domain), and Category Switching (promptly transitioning between semantic domains). The D-KEFS VF subtest evidenced good psychometric reliability and construct validity (Suchy & Brothers, Reference Suchy and Brothers2022). Participants were allotted 1 min in each test to generate as many words as possible. Higher sum scores on these subtests indicated better VF ability.

WM

Letter-number sequencing (LNS) in the Wechsler-Adult Intelligence Scale Fourth Edition (WAIS-IV; Wechsler, Reference Wechsler2008) was used because it is considered the best WM assessment (Crowe, Reference Crowe2000; Salthouse, Reference Salthouse1996; Shelton, Elliott, Hill, Calamia, & Gouvier, Reference Shelton, Elliott, Hill, Calamia and Gouvier2009). The evaluator verbally presented a sequence of alphanumeric strings at a pace of about one string per second. Participants were instructed to listen and reiterate successively longer alphanumeric strings by verbalizing the numbers before the letters in ascending order (Reynolds, Reference Reynolds1997). LNS captured WM, auditory processing speed, attention span, and cognitive manipulation. It has strong internal consistency, retest reliability, and construct validity (Vora, Varghese, Weisenbach, & Bhatt, Reference Vora, Varghese, Weisenbach and Bhatt2016). The sum of correct responses from all three trials was calculated, and higher scores reflected better WM ability.

Pre-1MFU outcome measures

GAD severity

GAD symptom severity was evaluated using the 16-item GAD-Q-Dimensional assessment, which closely resembled and was adapted from the GAD-Q-IV (Newman et al., Reference Newman, Zuellig, Kachin, Constantino, Przeworski, Erickson and Cashman-McGrath2002) but consistently used 9-point Likert scale response options (e.g. 0 = Never to 8 = Almost Every Day). The first eight items assessed individuals' levels of trait anxiety, with respondents evaluating the extent, frequency, intensity, and manageability of their worry across their lifetime. The subsequent eight questions posed similar queries regarding the preceding half-year (α values: .96, .97, .97).

Trait RNT

The 45-item Perseverative Cognitions Questionnaire (PCQ) measured enduring cognitive attributes associated with brooding, obsessive thinking, and worry (Szkodny & Newman, Reference Szkodny and Newman2019). Participants rated items on a 6-point Likert scale (0 = Strongly Disagree to 5 = Strongly Agree). The PCQ has six factors: anticipating adverse outcomes, exploring reasons and meanings, perceiving lack of control, preparing for the future, ruminating on past events, and thoughts incongruent with one's ideal self. The overall score was determined by summing items of each subscale. It had robust retest reliability over two weeks, strong convergent and discriminant validity (Szkodny & Newman, Reference Szkodny and Newman2019), and good cross-cultural equivalence (Zainal, Newman, & Hong, Reference Zainal, Newman and Hong2021; α values = .96, .97, .97).

Group arms

MEMI

MEMI participants accessed a video featuring the principal researcher, a doctoral-level clinical psychologist. The video taught them to use evidence-supported components in accordance with the principles derived from MBSR (Kabat-Zinn, Reference Kabat-Zinn1990). They were introduced to the concept of mindfulness and given precise guidance to immerse themselves in their immediate environment and actively participate in meaningful activities. This portion was designed to give them the capability of open monitoring and acceptance, improving their capacity to concentrate on intricate details. Following that, the video therapist guided unhurried diaphragmatic breathing techniques with a practical demonstration of the optimal procedure. This segment encompassed instructions on cultivating tranquility via optimized breathing routines and nurturing mindfulness qualities such as non-reactive observation and non-judgment, borrowing inspiration from the principles of MBCT (Segal, Williams, & Teasdale, Reference Segal, Williams and Teasdale2002). Subsequently, the video therapist stressed integrating mindfulness into daily activities. The instructional material explicitly asked them to consistently review and actively participate in mindfulness via MEMI exercises (online Supplementary Appendix B).

Self-monitoring app (SM)

The SM video commenced with an introduction to self-awareness as the heightened recognition of one's feelings and thinking states. Subsequently, SM suggested that practicing self-observation and recording of thoughts emotional discomfort could potentially aid in nurturing more beneficial thought-feeling repertoires. It conveyed that self-observation by itself could reduce anxiety symptoms. The core foundation was derived and adapted from the rationale employed in a recent app-based intervention (LaFreniere & Newman, Reference LaFreniere and Newman2016, Reference LaFreniere and Newman2020). Therefore, it purposefully avoided any reference to the concept of mindfulness. SM avoided any directives to enhance awareness and perception of current experiences. Instead, it concentrated on monitoring distressing thoughts and feelings. Participants were not guided to focus exclusively on their ongoing tasks or be in the moment. Although SM participants were encouraged to observe distress-associated thoughts and feelings, we omitted any instructions regarding accepting cognitive-affective states as they arose. SM also did not offer guidance on techniques for regulating and optimizing breath or prolonging self-observation practices after the 14-day intervention phase ended (online Supplementary Appendix C). This placebo control approach sought to increase credibility of the SM and to prevent any potential amplification of between-group effect sizes observed with a no-treatment/waitlist control (Lutz, Offidani, Taraboanta, Lakhan, & Campellone, Reference Lutz, Offidani, Taraboanta, Lakhan and Campellone2022).

Procedures

Those meeting eligibility criteria completed a series of initial self-assessments and participated in behavioral tests capturing EF. After completing the 14-day intervention (with five prompts/day), all participants completed the same measures at post-intervention and 1MFU (six weeks from the start). Measures were counter-balanced to prevent order effects. To maintain assessor-blinding to randomized arms, assessors either physically left the room (before COVID-19) or instructed participants to mute their Zoom before accessing the designated video link (during and post-COVID-19). Participants installed the PACO mobile application, which came preloaded with MEMI or SM (https://github.com/google/paco). The assessor answered questions concerning protocols, such as upcoming appointments or technical problems regarding installing the PACO app on their mobile devices. Nonetheless, the assessor did not attend when participants were informed about their assigned treatment and its constituents. Participants were provided a MEMI or SM intervention rationale document automatically delivered via Qualtrics to uphold assessor-blinding. They received compensation in credit hours, monetary remuneration, or their mixture (online Supplementary Appendix A). On the seventh intervention day, the team conducted an assessment to verify whether participants had adhered to the instruction of completing a minimum of 56 out of 70 prompts.

Data analyses

Random forest imputation utilizing the missRanger R package was employed to address missing data, which accounted for 11% of the dataset (Mayer, Reference Mayer2023). To evaluate MEMI against SM concerning their effects on specific EF mediators, we applied an intent-to-treat approach similar to the primary efficacy analysis (Zainal & Newman, Reference Zainal and Newman2023b). This entailed a two-tiered multilevel model, which examined changes from pre-treatment to 1MFU in GAD severity or trait RNT, with group as the between-person factor. We utilized a counterfactual causal approach in multilevel mediation (online Supplementary Appendix A and VanderWeele, Reference VanderWeele2016).

The analysis examined three multiplicative routes: effect of treatment group assignment on the pre–post mediator (a path), pre-post mediator's effect on pre-1MFU outcome (b path), and treatment group effect on pre-1MFU outcome (c path or direct effect). Simultaneously adjusting for treatment group effect, the mediation effect is called the indirect effect (VanderWeele, Reference VanderWeele2016). Temporal precedence was set such that treatment assignment preceded the pre–post EF mediator, and the pre–post EF mediator preceded the pre-1MFU endpoint (Winer et al., Reference Winer, Cervone, Bryant, McKinney, Liu and Nadorff2016). Given the theoretical significance of each plausible mediator and their interconnectedness, we refrained from adjusting for additional mediators (Vansteelandt & Daniel, Reference Vansteelandt and Daniel2017). We displayed the non-standardized regression coefficients (β) with 95% confidence intervals (CIs) and used bootstrapping with 1000 resampling repetitions (Cheung & Lau, Reference Cheung and Lau2008). We performed sensitivity assessments using non-linear generalized additive multilevel models to examine the extent to which the observed results remained consistent (Imai, Keele, & Tingley, Reference Imai, Keele and Tingley2010). Effect size was calculated as proportion of the indirect effect in relation to the total effect (Wen & Fan, Reference Wen and Fan2015). For mediation analyses, we employed three R packages: intmed (Chan, Reference Chan2020), mgcv (Wood, Reference Wood2014), and mediation (Tingley, Yamamoto, Hirose, Keele, & Imai, Reference Tingley, Yamamoto, Hirose, Keele and Imai2014) as well as adapted published tutorials for our analyses (http://tinyurl.com/missRanger; http://tinyurl.com/codesintmed; http://tinyurl.com/codesmediation).

Results

Path a: random assignment predicting each pre–post EF mediator

MEMI v. SM had significantly stronger effects on enhancing pre-post inhibition (β = −2.075, p = .002), WM (β = 0.512, p = .045), and set-shifting (β = −2.916, p = .010), but not VF (β = −0.991, p = .547) and AC (β = 0.866, p = .337; Figure 2). MEMI yielded significant within-group pre-post improvements in inhibition (β = −3.958, p < .001), VF (β = 4.331, p = .004), WM (β = 0.551, p = .017), and set-shifting (β = −8.566, p < .001), but not AC (β = 1.201, p = .151). By comparison, SM produced significant within-group pre-post enhancements in inhibition (β = −2.276, p = .002) and set-shifting (β = −8.566, p < .001) but not VF (β = 4.179, p = .065), WM (β = 0.571, p = .103), or AC (β = 1.201, p = .151; Table 2).

Figure 2. Significant comparative efficacy of mindfulness EMI against SM on pre-post EF domains.

Note: EF, executive functioning; EMI, ecological momentary intervention; SM, self-monitoring placebo.

Table 2. Simple slope analyses of counterfactual mediation analysis of EF domains mediating the effect of MEMI against SM on pre-1MFU GAD severity

Note. * p < 0.05; ** p < 0.01; *** p < 0.001.

EF, executive functioning; MEMI, ecological momentary intervention; SM, self-monitoring control; 1MFU, one-month follow-up; β, unstandardized regression estimate; GAD, generalized anxiety disorder; LCI, lower limit of the 95% confidence interval (CI); UCI, upper limit of the 95% CI. All b path (mediator-outcome associations) models adjusted for the specific pre-post mediator.

Path b: pre–post EF predicting pre-1MFU change in GAD severity

Treatment group assignment did not significantly moderate the association of pre-post change in inhibition (β = 0.565, p = .057), VF (β = 0.011, p = .924), WM (β = −0.126, p = .867), set-shifting (β < 0.001, p = .999), and AC (β = −0.063, p = .760) predicting pre-1MFU change in GAD severity. Within the MEMI arm, pre-post improvements in inhibition (β = −5.072, p = .005), VF (β = −6.996, p < .001), WM (β = −6.798, p < .001), set-shifting (β = −6.193, p = .001), and AC (β = −6.148, p < .001) significantly predicted pre-1MFU declines in GAD severity (Table 2). However, within the SM arm, pre-post change in inhibition (β = −1.076, p = .627), VF (β = −1.083, p = .617), WM (β = −1.064, p = .622), set-shifting (β = 0.161, p = .944), and AC (β = −0.396, p = .849) did not significantly predict pre-1MFU change in GAD severity.

Path b: pre–post EF predicting pre-1MFU change in trait RNT

Treatment group assignment significantly moderated the association of pre-post inhibition (β = 0.036, p = .003) predicting pre-1MFU change in trait RNT. However, treatment group did not moderate the association of pre-post VF (β < 0.001, p = .832), WM (β = −0.042, p = .172), set-shifting (β = 0.007, p = .316), and AC (β = 0.003, p = .708) predicting pre-1MFU change in trait RNT. Within the MEMI arm, pre-post improvements in inhibition (β = −0.236, p = .002), VF (β = −0.309, p < .001), WM (β = −0.300, p < .001), set-shifting (β = −0.278, p < .001), and AC (β = −0.283, p < .001) significantly predicted pre-1MFU declines in trait RNT (Table 3). However, within the SM arm, pre-post change in inhibition (β = −0.100, p = .261), VF (β = −0.055, p = .521), WM (β = −0.076, p = .378), set-shifting (β = −0.059, p = .524), and AC (β = −0.028, p = .715) did not significantly predict pre-1MFU change in trait RNT.

Table 3. Simple slope analyses of counterfactual mediation analysis of EF domains mediating the effect of MEMI against SM on pre-1MFU trait repetitive thinking

Note. * p < 0.05; ** p < 0.01; *** p < 0.001.

EF, executive functioning; MEMI, ecological momentary intervention; SM, self-monitoring control; 1MFU, one-month follow-up; β, unstandardized regression estimate; LCI, lower limit of the 95% confidence interval (CI); UCI, upper limit of the 95% CI.

Indirect effect: treatment effect on pre-1MFU change in GAD severity via EF

The effect of MEMI compared to SM on reduced pre-1MFU GAD severity was significantly mediated by enhanced pre-post inhibition performance (β = −0.605, p = .030; proportion mediated = 7.1%). However, pre-post AC (β = −0.409, p = .340), set-shifting (β = −0.302, p = .236), VF (β = −0.046, p = .746), and WM (β = 0.045, p = .808) were non-significant mediators of the effect of MEMI against SM on decreased pre-1MFU GAD severity. Effect sizes ranged from 0.2% to 4.7% for non-significant mediation paths.

Indirect effect: treatment effect on pre-1MFU change in trait RNT via EF

The effect of MEMI compared to SM on decreased pre-1MFU trait RNT was significantly mediated by enhanced pre-post inhibition performance (β = −0.024, p = .040; proportion mediated = 7.4%). However, pre-post AC (β = 0.005, p = .900), set-shifting (β = −0.012, p = .222), VF (β = 0.003, p = .570), and WM (β = −0.008, p = .308) were non-significant mediators of the effect of MEMI against SM on reduced pre-1MFU trait RNT. Effect sizes ranged from 0% to 3.6% for non-significant mediation paths.

Discussion

Partially supporting Hypothesis 1, MEMI generated greater pre-post enhancements in inhibition, WM, and set-shifting but not VF and AC. Although there was no significant difference between MEMI and SM on increased VF, simple slope analysis revealed pre-post VF improvements in MEMI but not SM. Hypothesis 2 also received partial support, as pre-post improvement in inhibition uniquely mediated the effect of MEMI compared to SM on pre-follow-up reductions in GAD symptom severity and trait RNT. The combination of therapy elements in MEMI, such as acceptance, diaphragmatic breathing retraining, engagement with present activity, non-reactivity, and open monitoring, likely contributed to any observed differential efficacy over SM rather than any single component alone.

Other potential theoretical propositions are considered to inform optimization efforts of MBIs for GAD. Pre-post enhancements in inhibition accounted for the effect of MEMI against SM on pre-follow-up GAD severity and RNT. Further, pre-post enhancements in inhibition mediated pre-follow-up decline in RNT more strongly in MEMI than SM. Since people with GAD experience their worries as uncontrollable (Hallion & Ruscio, Reference Hallion and Ruscio2013) and have negative beliefs about worry (LaFreniere & Newman, Reference LaFreniere and Newman2019), it may be necessary to improve inhibition skills to put a brake on worry and other perseverative cognitions. Relatedly, people with GAD worry in autopilot ways that heighten and prolong distress to avoid negative emotional contrasts, i.e. sharp rises from positive or neutral to negative affect states (cf. contrast avoidance theory; Newman & Llera, Reference Newman and Llera2011; Newman, Llera, Erickson, Przeworski, & Castonguay, Reference Newman, Llera, Erickson, Przeworski and Castonguay2013). Thus, MEMI might have fostered tolerance of intense surges in distress, relinquishing the usual disinhibited, reflexive urges to avoid or resist negative emotional contrasts and, instead, allowing these experiences to fully register in one's awareness by enhancing inhibition. Future studies should investigate this idea by examining the link between inhibition and contrast avoidance in GAD.

Additional issues in GAD could explain the salience of inhibition as a potential change mechanism (cf. attentional control theory; Eysenck, Derakshan, Santos, & Calvo, Reference Eysenck, Derakshan, Santos and Calvo2007). People with GAD (v. controls) displayed poorer decision-making on inhibition-based reinforcement learning tasks (White et al., Reference White, Geraci, Lewis, Leshin, Teng, Averbeck and Blair2017). Relatedly, higher clinician-assessed GAD severity was correlated with slower and less precise performance in the Stroop task (Hallion, Tolin, Assaf, Goethe, & Diefenbach, Reference Hallion, Tolin, Assaf, Goethe and Diefenbach2017). Inhibitory dyscontrol has been observed to be a correlate (Majeed et al., Reference Majeed, Chua, Kothari, Kaur, Quek, Ng and Hartanto2023), predictor (Zainal & Newman, Reference Zainal and Newman2018), and longitudinal outcome of increase in pathological worry (Zainal & Newman, Reference Zainal and Newman2023a, Reference Zainal and Newman2021). These problems might translate to ample opportunities for MEMI to remedy inhibition deficits in GAD, thereby alleviating future worry and other RNT. Further, pathological worry preceded and increased future inhibition deficits within individuals across time (cf. scar theories; Zainal & Newman, Reference Zainal and Newman2021). Thus, MEMI likely improved inhibition by teaching and reinforcing the skill of resisting the habit of worrying, ruminating, or obsessing (Gallant, Reference Gallant2016). Enhancing inhibition by focusing on the here-and-now instead of the past/future with perseverative cognitions may have led to pre-follow-up decreases in worry and other RNT propensities.

Why did MEMI yield stronger pre–post improvements in set-shifting and WM relative to SM? Perhaps MEMI liberated cognitive resources that were otherwise consumed by suppressing worry-related, task-irrelevant thoughts, leading to an overall enhancement in cognitive efficiency to deploy better set-shifting and updating WM skills (Course-Choi, Saville, & Derakshan, Reference Course-Choi, Saville and Derakshan2017; Jankowski & Holas, Reference Jankowski and Holas2020). The potential for MEMI to induce better meta-cognitive skills, such as non-identification with feelings and thoughts (McEvoy, Graville, Hayes, Kane, & Foster, Reference McEvoy, Graville, Hayes, Kane and Foster2017), could also explain these results. Further, these outcomes might make sense given how patients with (v. without) GAD continually exhibited worse WM task performance under threat conditions (Vytal, Arkin, Overstreet, Lieberman, & Grillon, Reference Vytal, Arkin, Overstreet, Lieberman and Grillon2016). When exposed to emotion-inducing distractions, they displayed reduced activity and white matter volume in WM-linked dorsolateral prefrontal cortex areas (Moon & Jeong, Reference Moon and Jeong2017) and struggled with cognitively retaining materials germane to present objectives (Moon, Sundaram, Choi, & Jeong, Reference Moon, Sundaram, Choi and Jeong2016; Yoon, LeMoult, Hamedani, & McCabe, Reference Yoon, LeMoult, Hamedani and McCabe2018). Together, MEMI might reverse worry-triggered set-shifting and WM deficits by freeing cognitive processing assets (cf. resource allocation theory; Levens, Muhtadie, & Gotlib, Reference Levens, Muhtadie and Gotlib2009) and instructing focus on the here-and-now and task-switching flexibility.

Nevertheless, set-shifting and WM did not mediate treatment effects. MBIs were also found to be more efficacious for accuracy (v. latency), set-shifting, and WM scores (cf. meta-analysis; Zainal & Newman, Reference Zainal and Newman2024b). It is possible that instead of the TMT-B, using other set-shifting measures based on accuracy rather than latency might have increased the chances of detecting a mediation effect. Likewise, WM measures apart from the WAIS-IV LNS might have been more sensitive for mediation purposes, such as the automated operation span task (Dubert, Schumacher, Locker, Gutierrez, & Barnes, Reference Dubert, Schumacher, Locker, Gutierrez and Barnes2016; Unsworth, Heitz, Schrock, & Engle, Reference Unsworth, Heitz, Schrock and Engle2005). Alternatively, the lack of mediation effects with set-shifting and WM might be due to the present RCT being underpowered to detect small effect sizes for these domains (cf. method paper by Qin, Reference Qin2024).

Although no between-group effects emerged, within-group analyses revealed notable pre-post improvements in VF in MEMI but not SM. These findings might be explained by evidence that brief MBIs could enhance verbal learning and memory via refinements in the ability to register information (Lueke & Lueke, Reference Lueke and Lueke2019). Relatedly, since VF is associated with aptitude to efficiently recall words linked to emotions (Hegefeld, Satpute, Ochsner, Davidow, & Nook, Reference Hegefeld, Satpute, Ochsner, Davidow and Nook2023), MEMI might have strengthened VF of emotion and non-emotion words more than SM (Edwards, Shivaji, & Wupperman, Reference Edwards, Shivaji and Wupperman2018). This interpretation could be understood in the context of struggles to recognize and describe emotions in GAD (Paniccia et al., Reference Paniccia, Gaudio, Puddu, Di trani, Dakanalis, Gentile and Di ciommo2020). To confirm these interpretations, experimental work is required to test these conjectures.

Unexpectedly, neither between- nor within-group effects on self-reported AC occurred. Although a prior cross-sectional study showed that higher AC mediated the inverse anxiety-mindfulness correlation (MacDonald & Olsen, Reference MacDonald and Olsen2020), such findings did not extend to our longitudinal RCT of MEMI for GAD. These outcomes might be accounted for by weak correlations between self-reported and performance-based AC measures (Snyder, Friedman, & Hankin, Reference Snyder, Friedman and Hankin2021). In addition, based on recent theoretical formulations (Prakash, Reference Prakash2021) and evidence of the efficacy of 8-week MBSR on AC (Chin et al., Reference Chin, Lindsay, Greco, Brown, Smyth, Wright and Creswell2021; Lee et al., Reference Lee, Wong, Chan, Zhang, Sun, Chan and Wong2021), lengthier and more rigorous forms of MEMI might be needed to improve AC for GAD. Alternatively, other measures, such as task-unrelated mind-wandering probes (Mrazek, Franklin, Phillips, Baird, & Schooler, Reference Mrazek, Franklin, Phillips, Baird and Schooler2013), might better capture the effect of brief MEMI on AC. Relatedly, based on a meta-analysis data of robust inverse relations between AC/EF and RNT (Mennies, Stewart, & Olino, Reference Mennies, Stewart and Olino2021), another AC measure, such as the self- or parent-reported Behavior Rating Inventory of EF (Gioia, Isquith, Guy, & Kenworthy, Reference Gioia, Isquith, Guy and Kenworthy2000; Guy, Isquith, & Gioia, Reference Guy, Isquith and Gioia2004), might have mediated treatment effects.

Interpreting results in light of the broader literature on the relations between RNT and AC/EF constructs is also essential. We tested how specific EF domains mediated the efficacy of MEMI on reductions in GAD severity and RNT. Our findings regarding treatment predictors or mediators might differ if other domain-specific RNT outcomes were examined, such as anger and depressive rumination (du Pont, Rhee, Corley, Hewitt, & Friedman, Reference du Pont, Rhee, Corley, Hewitt and Friedman2019) or job-related rumination (Cropley & Collis, Reference Cropley and Collis2020), which exhibited modest yet meaningful negative correlations with a global EF. Heterogeneity also exists in the literature, such that global EF was often (Abramovitch et al., Reference Abramovitch, Short and Schweiger2021), but not always (du Pont et al., Reference du Pont, Rhee, Corley, Hewitt and Friedman2019), linked to the internalizing symptom constructs that subsume worry.

Several limitations deserve consideration. First, future studies should examine additional factors that might explain outcomes and maximize the potential to identify differential mediator effects in the context of GAD, such as self-reported WM (Adamis & Olatunji, Reference Adamis and Olatunji2024) and performance-based composites of various domain-specific EF tasks (e.g. anti-saccade and go-no-go tasks; Gustavson et al., Reference Gustavson, Elman, Panizzon, Franz, Zuber, Sanderson-Cimino and Kremen2020). The proportion mediated estimate for inhibition was 7%, which might be considered a meaningful yet small effect size (Preacher & Kelley, Reference Preacher and Kelley2011). This magnitude prompts the question of alternative EF-related pathways through which MEMI v. SM affects the outcome (VanderWeele, Reference VanderWeele2013). Despite its sensitivity in correlating with worry symptoms in other samples with GAD (Beaudreau et al., Reference Beaudreau, Hantke, Mashal, Gould, Henderson and O'Hara2017; Dorenkamp et al., Reference Dorenkamp, Irrgang and Vik2023), the neutral CWIT measure of inhibition might not sufficiently capture inhibition skills needed to curtail experiential avoidance of negative emotions or thoughts inherent in our GAD sample. Future studies should thus assess the mediation potential of AC/EF using ambulatory assessments (Hernandez et al., Reference Hernandez, Hoogendoorn, Gonzalez, Jin, Pyatak, Spruijt-Metz and Schneider2023) or AC/EF tasks that capture emotional states (Kalanthroff, Reference Kalanthroff2024). The lack of tasks capturing emotional states might explain some of our null or small effect size findings. For instance, if the stimuli in the EF/AC tasks had been affect-based (e.g. emotional Stroop task; Smolker et al., Reference Smolker, Wang, Luciana, Bjork, Gonzalez, Barch and Banich2022) or if clients with GAD had performed the tasks under induced anxiety or other emotional states (Azab, Reference Azab2022) findings might have notably varied. Results might also have differed had other EF indices, such as cognitive flexibility (Baussay et al., Reference Baussay, Di Lodovico, Poupon, Doublet, Ramoz, Duriez and Gorwood2024) and self-regulation (Short et al., Reference Short, Mazmanian, Oinonen and Mushquash2016), been in the equation for all mediational analyses. Second, the 14-day intervention duration might have been inadequate to identify or generate mediation effects of all examined EF mediators, given null treatment effects on AC and VF. Eight-week MBI RCTs suggest that maximizing the detection of between-group differences in AC and VF could require more time and practice to improve present-mindedness and express emotions and thoughts more clearly (Chin et al., Reference Chin, Lindsay, Greco, Brown, Smyth, Wright and Creswell2021). Third, future research should explore whether ongoing mindfulness practices could have yielded any distinct mediation effects during follow-up without repeated guidance through MEMI. Fourth, the inferences drawn from our study may not apply to a broader population beyond White females, emphasizing the need for future digital mental health EMI RCTs to include more culturally diverse participants.

Despite these limitations, several strengths were noteworthy. Our study adhered to rigorous CONSORT guidelines (Calvert, Brundage, Jacobsen, Schünemann, & Efficace, Reference Calvert, Brundage, Jacobsen, Schünemann and Efficace2013; Montgomery et al., Reference Montgomery, Grant, Mayo-Wilson, Macdonald, Michie, Hopewell and Group2018), thus leveraging the methodological strengths of RCTs to eliminate bias and confounding sources. A placebo control and assessor-blinding to random assignment were also included, further reducing the potential for confounding and selection biases. Also, because we controlled for focus on and monitoring of thoughts and emotions, which is a powerful treatment in and of itself, we can more confidently attribute differential treatment effects to unique components of mindfulness. The engagement rates were also high, with a dropout rate (11%) far lower than the 24–50% dropout rates observed in app RCTs (Linardon, Reference Linardon2023; Linardon & Fuller-Tyszkiewicz, Reference Linardon and Fuller-Tyszkiewicz2020). Further, the current study also enrolled a clinician-diagnosed sample with GAD, ensured adequate power, and incorporated a follow-up assessment.

In conclusion, MEMI was more efficacious than SM in enhancing pre-post inhibition, WM, and set-shifting, though it did not show superiority in AC and VF. Despite the lack of between-group differential efficacy, within-group analyses showed MEMI improved VF but not SM. Only inhibition mediated the effect of treatment on reductions in GAD severity and RNT. If replicated, the present study has possible practical applications in clinical contexts. Brief MEMIs for GAD might be optimized by prioritizing the targeting of inhibition rather than other EF domains. Several approaches could be tried to attain this goal. First, adding dialectical behavioral therapy components to MEMI by inviting clients to practice acceptance of life stressors and commit to inhibiting the urge to worry or ruminate might optimize brief MEMIs for GAD (Afshari et al., Reference Afshari, Jafarian Dehkordi, Asgharnejad Farid, Aramfar, Balagabri, Mohebi and Amiri2022; Vijayapriya & Tamarana, Reference Vijayapriya and Tamarana2023). Second and related, GAD should change the tendency to worry in order to create and maintain negative moods to avoid sharp rises in negative emotions (cf. contrast avoidance theory; Newman & Llera, Reference Newman and Llera2011; Newman et al., Reference Newman, Llera, Erickson, Przeworski and Castonguay2013). Plausibly, instructing clients with GAD to let go of worrying and allow experiences of emotional fluctuations, including negative emotional contrasts, via a higher-intensity version of MEMI might have a positive effect of improving inhibition. Third, as sustained worry induces wear-and-tear of physiological systems in ways that adversely affect EF over time (Zainal & Newman, Reference Zainal and Newman2022a, Reference Zainal and Newman2022b), MEMI should be merged with EF-enhancing physical exercise (cf. a meta-analysis; Moreau & Chou, Reference Moreau and Chou2019) among people with GAD. Fourth, future research should address the perennial inquiry of which subgroup with GAD would benefit most from inhibition-boosting exercises in conjunction with MEMI.

The current study received funding from the National Institute of Mental Health (NIMH) (R01 MH115128), the Pennsylvania State University RGSO Dissertation award, Penn State Susan Welch/Nagle Family Graduate Fellowship, the National University of Singapore (NUS) Development Grant, and the Association for Behavioral and Cognitive Therapies (ABCT) Leonard Krasner Student Dissertation Award.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291724001958.

Funding statement

The current study received funding from the National Institute of Mental Health (NIMH) (R01 MH115128), the Pennsylvania State University RGSO Dissertation award, Penn State Susan Welch/Nagle Family Graduate Fellowship, the National University of Singapore (NUS) Development Grant, and the Association for Behavioral and Cognitive Therapies (ABCT) Leonard Krasner Student Dissertation Award.

Competing interests

None.

References

Abasi, I., Mohammadkhani, P., Pourshahbaz, A., & Dolatshahi, B. (2017). The psychometric properties of Attentional Control Scale and its relationship with symptoms of anxiety and depression: A study on Iranian population. Iranian Journal of Psychiatry, 12, 109117.Google Scholar
Abramovitch, A., Short, T., & Schweiger, A. (2021). The C Factor: Cognitive dysfunction as a transdiagnostic dimension in psychopathology. Clinical Psychology Review, 86, 102007. doi:10.1016/j.cpr.2021.102007CrossRefGoogle Scholar
Adamis, A. M., & Olatunji, B. O. (2024). Specific emotion regulation difficulties and executive function explain the link between worry and subsequent stress: A prospective moderated mediation study. Journal of Affective Disorders, 348, 8896. doi:10.1016/j.jad.2023.12.029CrossRefGoogle Scholar
Afshari, B., Jafarian Dehkordi, F., Asgharnejad Farid, A. A., Aramfar, B., Balagabri, Z., Mohebi, M., … Amiri, P. (2022). Study of the effects of cognitive behavioral therapy versus dialectical behavior therapy on executive function and reduction of symptoms in generalized anxiety disorder. Trends in Psychiatry and Psychotherapy, 44, e20200156. doi:10.47626/2237-6089-2020-0156Google ScholarPubMed
American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (DSM-5) (DSM-5-TR ed.). Washington, DC: American Psychiatric Association Publishing.Google Scholar
Army Individual Test Battery (1944). Manual of directions and scoring. Washington, D.C.: War Department, Adjutant General's Office.Google Scholar
Azab, M. (2022). Generalized anxiety disorder (GAD): Etiological, cognitive, and neuroscientific aspects. An Update on Anxiety Disorders (pp. 1-46). doi:10.1007/978-3-031-19362-0_1.CrossRefGoogle Scholar
Baussay, A., Di Lodovico, L., Poupon, D., Doublet, M., Ramoz, N., Duriez, P., & Gorwood, P. (2024). The capacity of cognitive tests to detect generalized anxiety disorder (GAD): A pilot study. Journal of Psychiatric Research, 174, 94100. doi:10.1016/j.jpsychires.2024.04.006CrossRefGoogle ScholarPubMed
Beaudreau, S. A., Hantke, N. C., Mashal, N., Gould, C. E., Henderson, V. W., & O'Hara, R. (2017). Unlocking neurocognitive substrates of late-life affective symptoms using the Research Domain Criteria: Worry is an essential dimension. Frontiers in Aging Neuroscience, 9, 380. doi:10.3389/fnagi.2017.00380CrossRefGoogle ScholarPubMed
Blanck, P., Perleth, S., Heidenreich, T., Kröger, P., Ditzen, B., Bents, H., & Mander, J. (2018). Effects of mindfulness exercises as stand-alone intervention on symptoms of anxiety and depression: Systematic review and meta-analysis. Behaviour Research and Therapy, 102, 2535. doi:10.1016/j.brat.2017.12.002CrossRefGoogle ScholarPubMed
Bracken, M. R., Mazur-Mosiewicz, A., & Glazek, K. (2019). Trail Making Test: Comparison of paper-and-pencil and electronic versions. Applied Neuropsychology: Adult, 26, 522532. doi:10.1080/23279095.2018.1460371CrossRefGoogle ScholarPubMed
Brown, T. A., & Barlow, D. H. (2014). Anxiety and related disorders interview schedule for DSM-5 (ADIS-5L): Client interview schedule. New York, NY: Oxford University Press.Google Scholar
Calvert, M., Brundage, M., Jacobsen, P. B., Schünemann, H. J., & Efficace, F. (2013). The CONSORT Patient-Reported Outcome (PRO) extension: Implications for clinical trials and practice. Health and Quality of Life Outcomes, 11, 184. doi:10.1186/1477-7525-11-184CrossRefGoogle Scholar
Chan, G. (2020). intmed: Mediation analysis using interventional effects. R package version 0.1.2.Google Scholar
Cheung, G. W., & Lau, R. S. (2008). Testing mediation and suppression effects of latent variables: Bootstrapping with structural equation models. Organizational Research Methods, 11, 296325. doi:10.1177/1094428107300343CrossRefGoogle Scholar
Chin, B., Lindsay, E. K., Greco, C. M., Brown, K. W., Smyth, J. M., Wright, A. G. C., … Creswell, J. D. (2021). Mindfulness interventions improve momentary and trait measures of attentional control: Evidence from a randomized controlled trial. Journal of Experimental Psychology: General, 150, 686699. doi:10.1037/xge0000969CrossRefGoogle ScholarPubMed
Course-Choi, J., Saville, H., & Derakshan, N. (2017). The effects of adaptive working memory training and mindfulness meditation training on processing efficiency and worry in high worriers. Behaviour Research and Therapy, 89, 113. doi:10.1016/j.brat.2016.11.002CrossRefGoogle ScholarPubMed
Creswell, J. D. (2017). Mindfulness interventions. Annual Review of Psychology, 68, 491516. doi:10.1146/annurev-psych-042716-051139CrossRefGoogle ScholarPubMed
Cropley, M., & Collis, H. (2020). The association between work-related rumination and executive function using the Behavior Rating Inventory of Executive Function. Frontiers in Psychology, 11, 821. doi:10.3389/fpsyg.2020.00821CrossRefGoogle ScholarPubMed
Crowe, S. F. (2000). Does the letter number sequencing task measure anything more than digit span? Assessment, 7, 113117. doi:10.1177/107319110000700202CrossRefGoogle ScholarPubMed
Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). The Delis–Kaplan executive function system: Examiner's manual. San Antonio, NM: The Psychological Corporation.Google Scholar
Delis, D. C., Kramer, J. H., Kaplan, E., & Holdnack, J. (2004). Reliability and validity of the Delis–Kaplan Executive Function System: An update. Journal of the International Neuropsychological Society, 10, 301303. doi:10.1017/S1355617704102191CrossRefGoogle ScholarPubMed
Derryberry, D., & Reed, M. A. (2002). Anxiety-related attentional biases and their regulation by attentional control. Journal of Abnormal Psychology, 111, 225236. doi:10.1037/0021-843X.111.2.225CrossRefGoogle ScholarPubMed
Dorenkamp, M. A., Irrgang, M., & Vik, P. (2023). Assessment-related anxiety among older adults: Associations with neuropsychological test performance. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 30, 256271. doi:10.1080/13825585.2021.2016584CrossRefGoogle ScholarPubMed
Drigas, A., & Karyotaki, M. (2017). Attentional control and other executive functions. International Journal of Emerging Technologies in Learning, 12, 219233. doi:10.3991/ijet.v12i03.6587CrossRefGoogle Scholar
Dubert, C. J., Schumacher, A. M., Locker, L., Gutierrez, A. P., & Barnes, V. A. (2016). Mindfulness and emotion regulation among nursing students: Investigating the mediation effect of working memory capacity. Mindfulness, 7, 10611070. doi:10.1007/s12671-016-0544-6CrossRefGoogle Scholar
du Pont, A., Rhee, S. H., Corley, R. P., Hewitt, J. K., & Friedman, N. P. (2019). Rumination and executive functions: Understanding cognitive vulnerability for psychopathology. Journal of Affective Disorders, 256, 550559. doi:10.1016/j.jad.2019.06.026CrossRefGoogle ScholarPubMed
Edwards, E., Shivaji, S., & Wupperman, P. (2018). The Emotion Mapping Activity: Preliminary evaluation of a mindfulness-informed exercise to improve emotion labeling in alexithymic persons. Scandinavian Journal of Psychology, 59, 319327. doi:10.1111/sjop.12438CrossRefGoogle ScholarPubMed
Eysenck, M. W., & Derakshan, N. (2011). New perspectives in attentional control theory. Pers Indiv Differ, 50, 955960. doi:10.1016/j.paid.2010.08.019CrossRefGoogle Scholar
Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion (Washington, D.C.), 7, 336353. doi:10.1037/1528-3542.7.2.336CrossRefGoogle ScholarPubMed
Friedman, N. P., & Miyake, A. (2017). Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86, 186204. doi:10.1016/j.cortex.2016.04.023CrossRefGoogle ScholarPubMed
Gallant, S. N. (2016). Mindfulness meditation practice and executive functioning: Breaking down the benefit. Consciousness and Cognition, 40, 116130. doi:10.1016/j.concog.2016.01.005CrossRefGoogle ScholarPubMed
Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). TEST REVIEW behavior rating inventory of executive function. Child Neuropsychology, 6, 235238. doi:10.1076/chin.6.3.235.3152CrossRefGoogle Scholar
Goetter, E. M., Frumkin, M. R., Palitz, S. A., Swee, M. B., Baker, A. W., Bui, E., & Simon, N. M. (2020). Barriers to mental health treatment among individuals with social anxiety disorder and generalized anxiety disorder. Psychological Services, 17, 512. doi:10.1037/ser0000254CrossRefGoogle ScholarPubMed
Gustavson, D. E., Panizzon, M. S., Franz, C. E., Reynolds, C. A., Corley, R. P., Hewitt, J. K., … Friedman, N. P. (2019). Integrating verbal fluency with executive functions: Evidence from twin studies in adolescence and middle age. Journal of Experimental Psychology: General, 148, 21042119. doi:10.1037/xge0000589CrossRefGoogle ScholarPubMed
Gustavson, D. E., Elman, J. A., Panizzon, M. S., Franz, C. E., Zuber, J., Sanderson-Cimino, M., … Kremen, W. S. (2020). Association of baseline semantic fluency and progression to mild cognitive impairment in middle-aged men. Neurology, 95, e973e983. doi:10.1212/wnl.0000000000010130CrossRefGoogle ScholarPubMed
Guy, S. C., Isquith, P. K., & Gioia, G. A. (2004). Behavior Rating Inventory of Executive Function–Self-Report version: Professional manual (Vol. Psychological Assessment Resources). Lutz, Fl.Google Scholar
Hallion, L. S., & Ruscio, A. M. (2013). Should uncontrollable worry be removed from the definition of GAD? A test of incremental validity. Journal of Abnormal Psychology, 122, 369375. doi:10.1037/a0031731CrossRefGoogle Scholar
Hallion, L. S., Tolin, D. F., Assaf, M., Goethe, J., & Diefenbach, G. J. (2017). Cognitive control in generalized anxiety disorder: Relation of inhibition impairments to worry and anxiety severity. Cognitive Therapy and Research, 41, 610618. doi:10.1007/s10608-017-9832-2CrossRefGoogle Scholar
Hegefeld, H. M., Satpute, A. B., Ochsner, K. N., Davidow, J. Y., & Nook, E. C. (2023). Fluency generating emotion words correlates with verbal measures but not emotion regulation, alexithymia, or depressive symptoms. Emotion (Washington, D.C.), 23, 22592269. doi:10.1037/emo0001229CrossRefGoogle ScholarPubMed
Henry, L. M., Hansen, E., Chimoff, J., Pokstis, K., Kiderman, M., Naim, R., … Brotman, M. A. (2024). Selecting an ecological momentary assessment platform: Tutorial for researchers. Journal of Medical Internet Research, 26, e51125. doi:10.2196/51125CrossRefGoogle ScholarPubMed
Hernandez, R., Hoogendoorn, C., Gonzalez, J. S., Jin, H., Pyatak, E. A., Spruijt-Metz, D., … Schneider, S. (2023). Reliability and validity of noncognitive ecological momentary assessment survey response times as an indicator of cognitive processing speed in people's natural environment: Intensive longitudinal study. Jmir Mhealth and Uhealth, 11, e45203. doi:10.2196/45203CrossRefGoogle ScholarPubMed
Hirsch, C. R., & Mathews, A. (2012). A cognitive model of pathological worry. Behaviour Research and Therapy, 50, 636646. doi:10.1016/j.brat.2012.06.007CrossRefGoogle ScholarPubMed
Homack, S., Lee, D., & Riccio, C. A. (2005). Test review: Delis–Kaplan executive function system. Journal of Clinical and Experimental Neuropsychology, 27, 599609. doi:10.1080/13803390490918444CrossRefGoogle ScholarPubMed
Hsu, K. J., & Davison, G. C. (2017). Compounded deficits: The association between neuropsychological impairment and attention biases in currently depressed, formerly depressed, and never depressed individuals. Clinical Psychological Science, 5, 286298. doi:10.1177/2167702617692998CrossRefGoogle Scholar
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309334. doi:10.1037/a0020761CrossRefGoogle ScholarPubMed
Jankowski, T., & Holas, P. (2020). Effects of brief mindfulness meditation on attention switching. Mindfulness, 11, 11501158. doi:10.1007/s12671-020-01314-9CrossRefGoogle Scholar
Judah, M. R., Grant, D. M., Mills, A. C., & Lechner, W. V. (2014). Factor structure and validation of the Attentional Control Scale. Cognition and Emotion, 28, 433451. doi:10.1080/02699931.2013.835254CrossRefGoogle ScholarPubMed
Juster, R.-P., McEwen, B. S., & Lupien, S. J. (2010). Allostatic load biomarkers of chronic stress and impact on health and cognition. Neurosci Biobehavioral R, 35, 216. doi:10.1016/j.neubiorev.2009.10.002CrossRefGoogle ScholarPubMed
Kabat-Zinn, J. (1990). Full catastrophe living: Using the wisdom of your body and mind to face stress, pain and illness. New York: Dell Publishing.Google Scholar
Kalanthroff, E. (2024). Focused on the negative: Emotions and visuospatial attention in generalized anxiety disorder. Anxiety, Stress, and Coping, 37, 406418. doi:10.1080/10615806.2023.2262398CrossRefGoogle ScholarPubMed
Kazdin, A. E. (2007). Mediators and mechanisms of change in psychotherapy research. Annual Review of Clinical Psychology, 3, 127. doi:10.1146/annurev.clinpsy.3.022806.091432CrossRefGoogle ScholarPubMed
LaFreniere, L. S., & Newman, M. G. (2016). A brief ecological momentary intervention for generalized anxiety disorder: A randomized controlled trial of the worry outcome journal. Depression and Anxiety, 33, 829839. doi:10.1002/da.22507CrossRefGoogle ScholarPubMed
LaFreniere, L. S., & Newman, M. G. (2019). The impact of uncontrollability beliefs and thought-related distress on ecological momentary interventions for generalized anxiety disorder: A moderated mediation model. Journal of Anxiety Disorders, 66, 102113. doi:10.1016/j.janxdis.2019.102113CrossRefGoogle ScholarPubMed
LaFreniere, L. S., & Newman, M. G. (2020). Exposing worry's deceit: Percentage of untrue worries in generalized anxiety disorder treatment. Behavior Therapy, 51, 413423. doi:10.1016/j.beth.2019.07.003CrossRefGoogle ScholarPubMed
Lawson, G. M., Hook, C. J., & Farah, M. J. (2018). A meta-analysis of the relationship between socioeconomic status and executive function performance among children. Developmental Science, 21, e12529. doi:10.1111/desc.12529CrossRefGoogle ScholarPubMed
Lee, E. K. P., Wong, B., Chan, P. H. S., Zhang, D. D., Sun, W., Chan, D. C. C., … Wong, S. Y. S. (2021). Effectiveness of a mindfulness intervention for older adults to improve emotional well-being and cognitive function in a Chinese population: A randomized waitlist-controlled trial. International Journal of Geriatric Psychiatry, 37, 111. doi:10.1002/gps.5616Google Scholar
Levens, S. M., Muhtadie, L., & Gotlib, I. H. (2009). Rumination and impaired resource allocation in depression. Journal of Abnormal Psychology, 118, 757766. doi:10.1037/a0017206CrossRefGoogle ScholarPubMed
Linardon, J. (2023). Rates of attrition and engagement in randomized controlled trials of mindfulness apps: Systematic review and meta-analysis. Behaviour Research and Therapy, 170, 104421. doi:10.1016/j.brat.2023.104421CrossRefGoogle ScholarPubMed
Linardon, J., & Fuller-Tyszkiewicz, M. (2020). Attrition and adherence in smartphone-delivered interventions for mental health problems: A systematic and meta-analytic review. Journal of Consulting and Clinical Psychology, 88, 113. doi:10.1037/ccp0000459CrossRefGoogle ScholarPubMed
Linardon, J., Torous, J., Firth, J., Cuijpers, P., Messer, M., & Fuller-Tyszkiewicz, M. (2024). Current evidence on the efficacy of mental health smartphone apps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials. World Psychiatry, 23, 139149. doi:10.1002/wps.21183CrossRefGoogle ScholarPubMed
Lueke, A., & Lueke, N. (2019). Mindfulness improves verbal learning and memory through enhanced encoding. Memory and Cognition, 47, 15311545. doi:10.3758/s13421-019-00947-zCrossRefGoogle ScholarPubMed
Lutz, A., Slagter, H. A., Rawlings, N. B., Francis, A. D., Greischar, L. L., & Davidson, R. J. (2009). Mental training enhances attentional stability: Neural and behavioral evidence. Journal of Neuroscience, 29, 1341813427. doi:10.1523/jneurosci.1614-09.2009CrossRefGoogle ScholarPubMed
Lutz, J., Offidani, E., Taraboanta, L., Lakhan, S. E., & Campellone, T. R. (2022). Appropriate controls for digital therapeutic clinical trials: A narrative review of control conditions in clinical trials of digital therapeutics (DTx) deploying psychosocial, cognitive, or behavioral content. Frontiers in Digital Health, 4, 823977. doi:10.3389/fdgth.2022.823977CrossRefGoogle ScholarPubMed
MacDonald, H. Z., & Olsen, A. (2020). The role of attentional control in the relationship between mindfulness and anxiety. Psychological Reports, 123, 759780. doi:10.1177/0033294119835756CrossRefGoogle ScholarPubMed
Maddock, A., & Blair, C. (2021). How do mindfulness-based programmes improve anxiety, depression and psychological distress? A systematic review. Current Psychology, 42, 1020010222. doi:10.1007/s12144-021-02082-yCrossRefGoogle Scholar
Majeed, N. M., Chua, Y. J., Kothari, M., Kaur, M., Quek, F. Y. X., Ng, M. H. S., … Hartanto, A. (2023). Anxiety disorders and executive functions: A three-level meta-analysis of reaction time and accuracy. Psychiatry Research Communications, 3, 100100. doi:10.1016/j.psycom.2022.100100CrossRefGoogle Scholar
Marciniak, M. A., Shanahan, L., Rohde, J., Schulz, A., Wackerhagen, C., Kobylinska, D., … Kleim, B. (2020). Standalone smartphone cognitive behavioral therapy-based ecological momentary interventions to increase mental health: Narrative review. Jmir Mhealth and Uhealth, 8, e19836. doi:10.2196/19836CrossRefGoogle ScholarPubMed
Mayer, M. (2023). missRanger: Fast imputation of missing values (R package version 2.2.1) [Computer software]. https://cran.r-project.org/package=missRangerGoogle Scholar
McEvoy, P. M., Graville, R., Hayes, S., Kane, R. T., & Foster, J. K. (2017). Mechanisms of change during attention training and mindfulness in high trait-anxious individuals: A randomized controlled study. Behavior Therapy, 48, 678694. doi:10.1016/j.beth.2017.04.001CrossRefGoogle ScholarPubMed
McEwen, B. S., & Gianaros, P. J. (2011). Stress- and allostasis-induced brain plasticity. Annual Review of Medicine, 62, 431445. doi:10.1146/annurev-med-052209-100430CrossRefGoogle ScholarPubMed
McEwen, B. S., & Seeman, T. (1999). Protective and damaging effects of mediators of stress. Elaborating and testing the concepts of allostasis and allostatic load. Annals of the New York Academy of Sciences, 896, 3047. doi:10.1111/j.1749-6632.1999.tb08103.xCrossRefGoogle ScholarPubMed
Mennies, R. J., Stewart, L. C., & Olino, T. M. (2021). The relationship between executive functioning and repetitive negative thinking in youth: A systematic review of the literature. Clinical Psychology Review, 88, 102050. doi:10.1016/j.cpr.2021.102050CrossRefGoogle ScholarPubMed
Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions. Current Directions in Psychological Science, 21, 814. doi:10.1177/0963721411429458CrossRefGoogle ScholarPubMed
Montgomery, P., Grant, S., Mayo-Wilson, E., Macdonald, G., Michie, S., Hopewell, S., … Group, C.-S. (2018). Reporting randomised trials of social and psychological interventions: The CONSORT-SPI 2018 Extension. Trials, 19, 407. doi:10.1186/s13063-018-2733-1CrossRefGoogle ScholarPubMed
Moon, C. M., & Jeong, G. W. (2017). Functional and morphological alterations associated with working memory dysfunction in patients with generalized anxiety disorder. Acta Radiologica, 58, 344352. doi:10.1177/0284185116649794CrossRefGoogle ScholarPubMed
Moon, C.-M., Sundaram, T., Choi, N.-G., & Jeong, G.-W. (2016). Working memory dysfunction associated with brain functional deficits and cellular metabolic changes in patients with generalized anxiety disorder. Psychiatry Research: Neuroimaging, 254, 137144. doi:10.1016/j.pscychresns.2016.06.013CrossRefGoogle ScholarPubMed
Moreau, D., & Chou, E. (2019). The acute effect of high-intensity exercise on executive function: A meta-analysis. Perspectives on Psychological Science, 14, 734764. doi:10.1177/1745691619850568CrossRefGoogle ScholarPubMed
Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler, J. W. (2013). Mindfulness training improves working memory capacity and GRE performance while reducing mind wandering. Psychological Science, 24, 776781. doi:10.1177/0956797612459659CrossRefGoogle ScholarPubMed
Newman, M. G., & Llera, S. J. (2011). A novel theory of experiential avoidance in generalized anxiety disorder: A review and synthesis of research supporting a Contrast Avoidance Model of worry. Clinical Psychology Review, 31, 371382. doi:10.1016/j.cpr.2011.01.008CrossRefGoogle ScholarPubMed
Newman, M. G., Zuellig, A. R., Kachin, K. E., Constantino, M. J., Przeworski, A., Erickson, T., & Cashman-McGrath, L. (2002). Preliminary reliability and validity of the Generalized Anxiety Disorder Questionnaire-IV: A revised self-report diagnostic measure of generalized anxiety disorder. Behavior Therapy, 33, 215233. doi:10.1016/S0005-7894(02)80026-0CrossRefGoogle Scholar
Newman, M. G., Llera, S. J., Erickson, T. M., Przeworski, A., & Castonguay, L. G. (2013). Worry and generalized anxiety disorder: A review and theoretical synthesis of evidence on nature, etiology, mechanisms, and treatment. Annual Review of Clinical Psychology, 9, 275297. doi:10.1146/annurev-clinpsy-050212-185544CrossRefGoogle ScholarPubMed
Noone, C., & Hogan, M. J. (2018). A randomised active-controlled trial to examine the effects of an online mindfulness intervention on executive control, critical thinking and key thinking dispositions in a university student sample. BMC Psychology, 6, 13. doi:10.1186/s40359-018-0226-3CrossRefGoogle Scholar
Olfson, M., Blanco, C., Wall, M. M., Liu, S. M., & Grant, B. F. (2019). Treatment of common mental disorders in the United States: Results from the National Epidemiologic Survey on Alcohol and Related Conditions-III. Journal of Clinical Psychiatry, 80, e1e10. doi:10.4088/JCP.18m12532Google ScholarPubMed
Osuka, Y., Kojima, N., Sakurai, R., Watanabe, Y., & Kim, H. (2020). Reliability and construct validity of a novel motor-cognitive dual-task test: A Stepping Trail Making Test. Geriatrics & Gerontology International, 20, 291296. doi:10.1111/ggi.13878CrossRefGoogle Scholar
Ottaviani, C., Thayer, J. F., Verkuil, B., Lonigro, A., Medea, B., Couyoumdjian, A., & Brosschot, J. F. (2016). Physiological concomitants of perseverative cognition: A systematic review and meta-analysis. Psychological Bulletin, 142, 231259. doi:10.1037/bul0000036CrossRefGoogle ScholarPubMed
Paniccia, M. F., Gaudio, S., Puddu, A., Di trani, M., Dakanalis, A., Gentile, S., & Di ciommo, V. (2020). Alexithymia in parents and adolescents with generalised anxiety disorder. Clinical Psychologist, 22, 336343. doi:10.1111/cp.12134CrossRefGoogle Scholar
Plotnik, M., Doniger, G. M., Bahat, Y., Gottleib, A., Gal, O. B., Arad, E., … Heled, Y. (2017, 19-22 June 2017). Immersive trail making: Construct validity of an ecological neuropsychological test. Paper presented at the 2017 International Conference on Virtual Rehabilitation (ICVR).CrossRefGoogle Scholar
Prakash, R. S. (2021). Mindfulness meditation: Impact on attentional control and emotion dysregulation. Archives of Clinical Neuropsychology, 36, 12831290. doi:10.1093/arclin/acab053Google ScholarPubMed
Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods, 16, 93115. doi:10.1037/a0022658CrossRefGoogle ScholarPubMed
Qin, X. (2024). Sample size and power calculations for causal mediation analysis: A Tutorial and Shiny App. Behavior Research Methods, 56, 17381769. doi:10.3758/s13428-023-02118-0CrossRefGoogle ScholarPubMed
Rackoff, G. N., Fitzsimmons-Craft, E. E., Taylor, C. B., Wilfley, D. E., & Newman, M. G. (2023). Psychotherapy utilization by United States college students. Journal of American College Health, 18. doi:10.1080/07448481.2023.2225630CrossRefGoogle ScholarPubMed
Reynolds, C. R. (1997). Forward and backward memory span should not be combined for clinical analysis. Archives of Clinical Neuropsychology, 12, 2940. doi:10.1016/S0887-6177(96)00015-7CrossRefGoogle Scholar
Rodríguez-Nieto, G., Seer, C., Sidlauskaite, J., Vleugels, L., Van Roy, A., Hardwick, R., & Swinnen, S. (2022). Inhibition, shifting and updating: Inter and intra-domain commonalities and differences from an executive functions activation likelihood estimation meta-analysis. Neuroimage, 264, 119665. doi:10.1016/j.neuroimage.2022.119665CrossRefGoogle ScholarPubMed
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403428. doi:10.1037/0033-295X.103.3.403CrossRefGoogle ScholarPubMed
Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2002). Mindfulness-based cognitive therapy for depression: A new approach to preventing relapse. New York, NY: Guilford Press.Google Scholar
Shelton, J. T., Elliott, E. M., Hill, B. D., Calamia, M. R., & Gouvier, W. D. (2009). A comparison of laboratory and clinical working memory tests and their prediction of fluid intelligence. Intelligence, 37, 283. doi:10.1016/j.intell.2008.11.005CrossRefGoogle ScholarPubMed
Short, M. M., Mazmanian, D., Oinonen, K., & Mushquash, C. J. (2016). Executive function and self-regulation mediate dispositional mindfulness and well-being. Personality and Individual Differences, 93, 97103. doi:10.1016/j.paid.2015.08.007CrossRefGoogle Scholar
Smolker, H. R., Wang, K., Luciana, M., Bjork, J. M., Gonzalez, R., Barch, D. M., … Banich, M. T. (2022). The Emotional Word-Emotional Face Stroop task in the ABCD study: Psychometric validation and associations with measures of cognition and psychopathology. Developmental Cognitive Neuroscience, 53, 101054. doi:10.1016/j.dcn.2021.101054CrossRefGoogle ScholarPubMed
Snyder, H. R., Friedman, N. P., & Hankin, B. L. (2021). Associations between task performance and self-report measures of cognitive control: Shared versus distinct abilities. Assessment, 28, 10801096. doi:10.1177/1073191120965694CrossRefGoogle ScholarPubMed
Spijkerman, M. P. J., Pots, W. T. M., & Bohlmeijer, E. T. (2016). Effectiveness of online mindfulness-based interventions in improving mental health: A review and meta-analysis of randomised controlled trials. Clinical Psychology Review, 45, 102114. doi:10.1016/j.cpr.2016.03.009CrossRefGoogle ScholarPubMed
Spreen, O., & Strauss, E. (1998). A compendium of neuropsychological tests: Administration, norms and commentary (2nd ed.). New York: Oxford University Press.Google Scholar
Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643662. doi:10.1037/h0054651CrossRefGoogle Scholar
Suchy, Y., & Brothers, S. L. (2022). Reliability and validity of composite scores from the timed subtests of the D-KEFS battery. Psychological Assessment, 34, 483495. doi:10.1037/pas0001081CrossRefGoogle ScholarPubMed
Szkodny, L. E., & Newman, M. G. (2019). Delineating characteristics of maladaptive repetitive thought: Development and preliminary validation of the Perseverative Cognitions Questionnaire. Assessment, 26, 10841104. doi:10.1177/1073191117698753CrossRefGoogle ScholarPubMed
Taren, A. A., Gianaros, P. J., Greco, C. M., Lindsay, E. K., Fairgrieve, A., Brown, K. W., … Creswell, J. D. (2017). Mindfulness meditation training and executive control network resting state functional connectivity: A randomized controlled trial. Psychosomatic Medicine, 79, 674683. doi:10.1097/PSY.0000000000000466CrossRefGoogle ScholarPubMed
Tingley, D., Yamamoto, T., Hirose, K., Keele, L., & Imai, K. (2014). Mediation: R package for causal mediation analysis. Journal of Statistical Software, 59, 138. doi:10.18637/jss.v059.i05CrossRefGoogle Scholar
Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37, 498505. doi:10.3758/BF03192720CrossRefGoogle ScholarPubMed
VanderWeele, T. J. (2013). Policy-relevant proportions for direct effects. Epidemiology (Cambridge, Mass.), 24, 175176. doi:10.1097/EDE.0b013e3182781410CrossRefGoogle ScholarPubMed
VanderWeele, T. J. (2016). Explanation in causal inference: Developments in mediation and interaction. International Journal of Epidemiology, 45, 19041908. doi:10.1093/ije/dyw277Google ScholarPubMed
Vansteelandt, S., & Daniel, R. M. (2017). Interventional effects for mediation analysis with multiple mediators. Epidemiology (Cambridge, Mass.), 28, 258265. doi:10.1097/EDE.0000000000000596CrossRefGoogle ScholarPubMed
Vijayapriya, C. V., & Tamarana, R. (2023). Effectiveness of dialectical behavior therapy as a transdiagnostic treatment for improving cognitive functions: A systematic review. Research in Psychotherapy, 26, 662. doi:10.4081/ripppo.2023.662Google ScholarPubMed
Vora, J. P., Varghese, R., Weisenbach, S. L., & Bhatt, T. (2016). Test-retest reliability and validity of a custom-designed computerized neuropsychological cognitive test battery in young healthy adults. Journal of Psychology and Cognition, 1, 1119.CrossRefGoogle ScholarPubMed
Vytal, K. E., Arkin, N. E., Overstreet, C., Lieberman, L., & Grillon, C. (2016). Induced-anxiety differentially disrupts working memory in generalized anxiety disorder. BMC Psychiatry, 16, 62. doi:10.1186/s12888-016-0748-2CrossRefGoogle ScholarPubMed
Wechsler, D. (2008). Wechsler adult intelligence scale—fourth edition. San Antonio: Psychological Corporation.Google Scholar
Wen, Z., & Fan, X. (2015). Monotonicity of effect sizes: Questioning kappa-squared as mediation effect size measure. Psychological Methods, 20, 193203. doi:10.1037/met0000029CrossRefGoogle ScholarPubMed
White, S. F., Geraci, M., Lewis, E., Leshin, J., Teng, C., Averbeck, B., … Blair, K. S. (2017). Prediction error representation in individuals with generalized anxiety disorder during passive avoidance. American Journal of Psychiatry, 174, 110117. doi:10.1176/appi.ajp.2016.15111410CrossRefGoogle ScholarPubMed
Williams, J. M., Russell, I., & Russell, D. (2008). Mindfulness-based cognitive therapy: Further issues in current evidence and future research. Journal of Consulting and Clinical Psychology, 76, 524529. doi:10.1037/0022-006X.76.3.524CrossRefGoogle ScholarPubMed
Williams, P. G., Rau, H. K., Suchy, Y., Thorgusen, S. R., & Smith, T. W. (2017). On the validity of self-report assessment of cognitive abilities: Attentional control scale associations with cognitive performance, emotional adjustment, and personality. Psychological Assessment, 29, 519530. doi:10.1037/pas0000361CrossRefGoogle ScholarPubMed
Winer, E. S., Cervone, D., Bryant, J., McKinney, C., Liu, R. T., & Nadorff, M. R. (2016). Distinguishing mediational models and analyses in clinical psychology: Atemporal associations do not imply causation. Journal of Clinical Psychology, 72, 947955. doi:10.1002/jclp.22298CrossRefGoogle Scholar
Wood, S. (2014). mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML smoothness estimation (Version 1.29) [Computer software]. https://CRAN.R-project.org/package=mgcvGoogle Scholar
Woon, F. L., Farrer, T. J., Braman, C. R., Mabey, J. K., & Hedges, D. W. (2017). A meta-analysis of the relationship between symptom severity of Posttraumatic Stress Disorder and executive function. Cognitive Neuropsychiatry, 22, 116. doi:10.1080/13546805.2016.1255603CrossRefGoogle ScholarPubMed
Yang, Y., Cao, S., Shields, G. S., Teng, Z., & Liu, Y. (2017). The relationships between rumination and core executive functions: A meta-analysis. Depression and Anxiety, 34, 3750. doi:10.1002/da.22539CrossRefGoogle ScholarPubMed
Yang, Y., Shields, G. S., Guo, C., & Liu, Y. (2018). Executive function performance in obesity and overweight individuals: A meta-analysis and review. Neuroscience and Biobehavioral Reviews, 84, 225244. doi:10.1016/j.neubiorev.2017.11.020CrossRefGoogle ScholarPubMed
Yoon, K. L., LeMoult, J., Hamedani, A., & McCabe, R. (2018). Working memory capacity and spontaneous emotion regulation in generalised anxiety disorder. Cognition & Emotion, 32, 215221. doi:10.1080/02699931.2017.1282854CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2018). Executive function and other cognitive deficits are distal risk factors of generalized anxiety disorder 9 years later. Psychological Medicine, 48, 20452053. doi:10.1017/S0033291717003579CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2021). Within-person increase in pathological worry predicts future depletion of unique executive functioning domains. Psychological Medicine, 51, 16761686. doi:10.1017/S0033291720000422CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2022a). Inflammation mediates depression and generalized anxiety symptoms predicting executive function impairment after 18 years. Journal of Affective Disorders, 296, 465475. doi:10.1016/j.jad.2021.08.077CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2022b). Depression and worry symptoms predict future executive functioning impairment via inflammation. Psychological Medicine, 52, 36253635. doi:10.1017/S0033291721000398CrossRefGoogle Scholar
Zainal, N. H., & Newman, M. G. (2023a). Elevated anxious and depressed mood relates to future executive dysfunction in older adults: A longitudinal network analysis of psychopathology and cognitive functioning. Clinical Psychological Science, 11, 218238. doi:10.1177/21677026221114076CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2023b). A randomized controlled trial of a 14-day mindfulness ecological momentary intervention (MEMI) for generalized anxiety disorder. European Psychiatry, 66, e12. doi:10.1192/j.eurpsy.2023.2CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2024a). The effects of a brief, fully self-guided mindfulness ecological momentary intervention on empathy and theory-of-mind for generalized anxiety disorder: A randomized controlled trial. JMIR Mental Health, 11, e54412. doi:10.2196/54412CrossRefGoogle Scholar
Zainal, N. H., & Newman, M. G. (2024b). Mindfulness enhances cognitive functioning: A meta-analysis of 111 randomized controlled trials. Health Psychology Review, 18, 369395. doi:10.1080/17437199.2023.2248222CrossRefGoogle ScholarPubMed
Zainal, N. H., & Newman, M. G. (2024c). Which client with generalized anxiety disorder benefits from a mindfulness ecological momentary intervention versus a self-monitoring app? Developing a multivariable machine learning predictive model. Journal of Anxiety Disorders, 102, 102825. doi:10.1016/j.janxdis.2024.102825CrossRefGoogle ScholarPubMed
Zainal, N. H., Newman, M. G., & Hong, R. Y. (2021). Cross-cultural and gender invariance of transdiagnostic processes in the United States and Singapore. Assessment, 28, 485502. doi:10.1177/1073191119869832CrossRefGoogle ScholarPubMed
Zhou, H., Liu, H., & Deng, Y. (2020). Effects of short-term mindfulness-based training on executive function: Divergent but promising. Clinical Psychology & Psychotherapy, 27, 672685. doi:10.1002/cpp.2453CrossRefGoogle ScholarPubMed
Figure 0

Figure 1. CONSORT flowchart of participant recruitment and progress.Note: CONSORT, Consolidated Standards of Reporting Trials; GAD, generalized anxiety disorder; GADQ-IV, GAD questionnaire- fourth edition; MEMI, mindfulness ecological momentary intervention; SMP, self-monitoring app or placebo.

Figure 1

Table 1. Sociodemographic data of study participants in the mindfulness ecological momentary intervention (MEMI) and self-monitoring app (SM) (N = 110)

Figure 2

Figure 2. Significant comparative efficacy of mindfulness EMI against SM on pre-post EF domains.Note: EF, executive functioning; EMI, ecological momentary intervention; SM, self-monitoring placebo.

Figure 3

Table 2. Simple slope analyses of counterfactual mediation analysis of EF domains mediating the effect of MEMI against SM on pre-1MFU GAD severity

Figure 4

Table 3. Simple slope analyses of counterfactual mediation analysis of EF domains mediating the effect of MEMI against SM on pre-1MFU trait repetitive thinking

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