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Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks
Joint Authors
Sarrafzadegan, Nizal
Shavandi, Hassan
Roohafza, Hamidreza
Andalib, Elham
Sali, Rasoul
Sadeghi, Masoumeh
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-02-07
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Objectives.
Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies.
Hence, the proper and accurate measurement of them is very important.
We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point.
Methods.
A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12).
A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale) and the GHQ score as a response variable.
In this model, GA is used in order to set some parameter of ANN for achieving more accurate results.
Results.
For each stressful life event, the number is defined as weight.
Among all stressful life events, death of parents, spouse, or siblings is the most important and impactful stressor in the studied population.
Sensitivity of 83% and specificity of 81% were obtained for the cut point 100.
Conclusion.
The SLE-revised (SLE-R) questionnaire despite simplicity is a high-performance screening tool for investigating the stress level of life events and its management in both community and primary care settings.
The SLE-R questionnaire is user-friendly and easy to be self-administered.
This questionnaire allows the individuals to be aware of their own health status.
American Psychological Association (APA)
Sali, Rasoul& Roohafza, Hamidreza& Sadeghi, Masoumeh& Andalib, Elham& Shavandi, Hassan& Sarrafzadegan, Nizal. 2013. Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-484120
Modern Language Association (MLA)
Sali, Rasoul…[et al.]. Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-484120
American Medical Association (AMA)
Sali, Rasoul& Roohafza, Hamidreza& Sadeghi, Masoumeh& Andalib, Elham& Shavandi, Hassan& Sarrafzadegan, Nizal. Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-484120
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-484120