Document Detail

Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks.
MedLine Citation:
PMID:  23476715     Owner:  NLM     Status:  In-Data-Review    
. 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. . 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. . 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. . 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.
Rasoul Sali; Hamidreza Roohafza; Masoumeh Sadeghi; Elham Andalib; Hassan Shavandi; Nizal Sarrafzadegan
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Publication Detail:
Type:  Journal Article     Date:  2013-02-07
Journal Detail:
Title:  Computational and mathematical methods in medicine     Volume:  2013     ISSN:  1748-6718     ISO Abbreviation:  Comput Math Methods Med     Publication Date:  2013  
Date Detail:
Created Date:  2013-03-11     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101277751     Medline TA:  Comput Math Methods Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  601640     Citation Subset:  IM    
Industrial Engineering Department, Sharif University of Technology, P.O. Box 11365-9466, Tehran, Iran.
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