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:: Volume 9, Issue 2 (Spring 2021) ::
Shefaye Khatam 2021, 9(2): 35-47 Back to browse issues page
Predicting mindfulness effect on irritability with Bayesian models, regression and neural network
Elham PourAfrouz, Saeed Setayeshi *, Iman Allah Bigdeli, Mir Mohsen Pedram
Department of Energy and Physics, Amir Kabir University of Technology, Tehran, Iran , setayesh@aut.ac.ir
Abstract:   (567 Views)
Introduction: Artificial intelligence researchers are trying to implement human intelligence on the machine. This study aimed to develop an appropriate predictive computer model to evaluate the effectiveness of mindfulness-based cognitive therapy on irritability. Materials and Methods: The design of the present study is quasi-experimental with a pre-test and post-test method. 135 individuals who referred to Khane Mehr counseling center in Mashhad and participated in an 8-session mindfulness-based cognitive therapy (MBCT) course were included in this study. Totally, 11 MBCT courses were held and 10 to 14 people participated in each course. Participants completed the irritability questionnaire (Pourafrouz & et al.) at two stages (before treatment and after treatment). In order to examine the differences from pre-test to post-test in this research, the variance analysis of repeated measures was used. Results: There was a significant difference between pre-test and post-test irritability scores. The effect of mindfulness was 83%. To develop the prediction model, three Bayesian, regression, and neural network models were compared. The Bayesian model, with 93% accuracy test data, was considered the most appropriate model. Moreover, the Bayesian models with input and output clustering (85.7%), the Bayesian with classification (71.49%), and the sequential neural network (64.29%) were identified as suitable models to predict the effectiveness of 8-session mindfulness courses on reducing irritability. The Bayesian model with output clustering, one-output regression, and the Convulsions Neural Network did not have sufficient predictive accuracy for the effectiveness of mindfulness. Conclusion: Using cognitive modeling, we can predict the efficacy of mindfulness-based cognitive therapy on irritability.
Keywords: Mindfulness, Therapeutics, Counseling
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Type of Study: Research --- Open Access, CC-BY-NC | Subject: Bioinformatics in Neuroscience
References
1. Polk T , Seifert C. Cognitive Modeling (A Bradford Book) . 2002. [DOI:10.7551/mitpress/1888.001.0001]
2. Baer R A. Mindfulness training as a clinical intervention: A conceptual and empirical review. Clinical Psychology: Science and Practice. 2003; 10: 125-143. [DOI:10.1093/clipsy.bpg015]
3. Segal Zindel V, Teasdale John D , and Williams J. M. Mindfulness Based cognitive therapy for depression. New York: The Guilford Press. 2002.
4. Pour Afkari N. Semiotics of mental illness. Tehran: Azadeh. 2011.
5. Caldwell K, Harrison M, Adams M, Quin R, Greeson J. Developing Mindfulness in College Students through Movement Based Courses: Effects on Self-Regulatory Self-Efficacy, Mood, Stress, and Sleep Quality. J Am Coll Health. 2010; 58(5): 433-42. [DOI:10.1080/07448480903540481]
6. Van Vugt M, Taatgen N, Sackur J, Bastian M. Modeling mind-wandering: a tool to better understand distraction. Proceedings of the 13th International Conference on Cognitive Modeling. Groningen: University of Groningen. 2015; 252-57.
7. Moye A, Van Vugt M. A computational model of focused attention meditation and its transfer to a sustained attention task. Proceedings of the 15th International Conference on Cognitive Modeling. 2017; 43-48.
8. Pablo R, Gustavo D, Nazareth C, Carmelo V. Does mindfulness change the mind? A novel psychonectomeperspective based on Network Analys. 2019; [ https://doi.org/10.1371/journal.pone.0219793 [DOI:10.1371/journal.pone.0219793].]
9. PourAfrouz E, Setayeshi S, Bigdeli I, Pedram M. Making and standardizing the Psychometricof irritability questionnaire. Journal of Psychometric Research. Rouden Azad University. Spring 2019.
10. Lawrence S, Gamst G, Guarino A. Applied Multivariate Research. Design and Interpretation. Translation by Hassan Pasha Sharifi et al. Tehran: Roshd. 2017.
11. Hesaraki E. Machine learning. 2018. [https://blog.faradars.org/introduction-to-machine-learning/].
12. Koski T, Noble J. Bayesian Networks. Wiley Series in Probability and Statistics. 2009. [DOI:10.1002/9780470684023]
13. Krizhevsky A, Sutskever I, Hinton GE. Imagenet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems. 2012.
14. Denoyer L; Gallinari Deep Sequential Neural Network. Arxiv. 2014.
15. Grossman P, Niemann L, Schmidt S, Walach H. Mindfulness-based stress reduction and health benefits: A meta-analysis. Journal of Psychosomatic Research. 2004; 57. 1: 35-43. [DOI:10.1016/S0022-3999(03)00573-7]
16. Hofmann S, Sawyer A, Witt A, Oh D. The effect of mindfulness-based therapy on anxiety and depression: A meta-analytic review. J Consult Clin Psychol. 2010; 78. 2: 169-83. [DOI:10.1037/a0018555]
17. Brandmeyer T, Delorme A. Reduced mind wandering in experienced meditators and associated EEG correlates. Experimental Brain Research. 2016. [DOI:10.1007/s00221-016-4811-5]
18. Huang S, Li R, Huang F, Tang F. The potential for mindfulness-based intervention in workplace mental health promotion. Results of a randomized controlled trial. 2015; 10. 9: e0138089. [DOI:10.1371/journal.pone.0138089]
19. Black D, Peng C, Sleight A, Nguyen N, Lenz H, Figueiredo J. Mindfulness practice reduces cortisol blunting during chemotherapy: A randomized controlled study of colorectal cancer patients. Cancer. 2017. [DOI:10.1002/cncr.30698]


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PourAfrouz E, Setayeshi S, Bigdeli I A, Pedram M M. Predicting mindfulness effect on irritability with Bayesian models, regression and neural network. Shefaye Khatam. 2021; 9 (2) :35-47
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Volume 9, Issue 2 (Spring 2021) Back to browse issues page
مجله علوم اعصاب شفای خاتم The Neuroscience Journal of Shefaye Khatam
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