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 ( = 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 ( = -2.075, 95% [-3.388, -0.762], = .002), working memory ( = 0.512, 95% [0.012, 1.011], = .045), and set-shifting ( = -2.916, 95% [-5.142, -0.691], = .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 ( = -0.605, 95% [-1.357, -0.044], = .030; proportion mediated = 7.1%) and trait RNT ( = -0.024, 95% [-0.054, -0.001], = .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.
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http://dx.doi.org/10.1017/S0033291724001958 | DOI Listing |
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November 2024
Department of Sciences and Technologies for Sustainable Development and One Health, Universita Campus Bio-Medico di Roma, 00128 Rome, Italy.
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November 2024
Department of Biology, Faculty of Medicine, Aix-Marseille University, INSERM UA16, 13015 Marseille, France.
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View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001, China.
In intelligent transportation systems, accurate vehicle target recognition within road scenarios is crucial for achieving intelligent traffic management. Addressing the challenges posed by complex environments and severe vehicle occlusion in such scenarios, this paper proposes a novel vehicle-detection method, YOLO-BOS. First, to bolster the feature-extraction capabilities of the backbone network, we propose a novel Bi-level Routing Spatial Attention (BRSA) mechanism, which selectively filters features based on task requirements and adjusts the importance of spatial locations to more accurately enhance relevant features.
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December 2024
Department of Industrial Engineering, Chosun University, Gwangju 61452, Republic of Korea.
In human activity recognition, accurate and timely fall detection is essential in healthcare, particularly for monitoring the elderly, where quick responses can prevent severe consequences. This study presents a new fall detection model built on a transformer architecture, which focuses on the movement speeds of key body points tracked using the MediaPipe library. By continuously monitoring these key points in video data, the model calculates real-time speed changes that signal potential falls.
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