Headache interference as a function of affect and coping: an artificial neural network analysis.
Artificial neural networks present a technique for modeling relationships between variables in complex systems. The negative effects of headache are determined by many "biopsychosocial" elements that represent a complex system. Artificial neural networks may therefore be useful for examining psychological factors in headache. To test this hypothesis, we trained an artificial neural network to predict life-style interference attributed to headache from psychological measures of anger, depression, and coping appraisal and strategies. The artificial neural network demonstrated a better fit of the data than that obtained by multiple regression, and predicted interference levels to within 10% error for 80% of novel cases. Artificial neural networks may be a useful technique for examining psychological correlates of headache.
Cathcart
S
S
Department of Psychology, The University of Adelaide, South Australia.
Materazzo
F
F
D000223:Adaptation, Psychological; D000328:Adult; D000786:Anger; D003863:Depression / Q000523:psychology; D005260:Female; D006261:Headache / Q000523:psychology*; D006306:Health Surveys; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D010147:Pain Measurement; D010865:Pilot Projects; D012044:Regression Analysis; D012680:Sensitivity and Specificity