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This study aimed to identify factors contributing to anxiety at induction of anaesthesia in children. One hundred and twenty children aged five to twelve years and scheduled for surgery requiring general anaesthesia were included. Children were interviewed and assessed prior to surgery. Parents completed anxiety measures prior to surgery and were interviewed after the induction of anaesthesia. The level of children's anxiety was determined at the time of induction of anaesthesia by the modified Yale Preoperative Anxiety Scale. Factors associated with increased levels of anxiety in the children included increased number of people in the room at induction of anaesthesia; longer waiting time between admission at the hospital and induction of anaesthesia; negative memories of previous hospital experiences; and having a mother who does not practise a religion. Suggestions for implementation of the findings and for future research are provided.

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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.