The visual analog scale allows effective measurement of preoperative anxiety and detection of patients' anesthetic concerns

The advent of managed care, reduction of costs, and advances in medical tec hnology place increasing demands on anesthesiologists. Preoperative anxiety may go unnoticed in an environment that stresses increased productivity. T he present study compares different methods for measuring preoperative anxi ety, identifies certain patient characteristics that predispose to high anx iety, and describes the quantity and quality of anxiety that patients exper ience preoperatively. Seven hundred thirty-four patients participated in th e study. We assessed aspects of anxiety by means of Visual analog scales (V AS) and the State Anxiety Score of the Spielberger State-Trait Anxiety Inve ntory (STAI). The mean STAI anxiety score was 39 +/- 1 (n = 486) and the me an VAS for fear of anesthesia was 29 +/- 1 (n = 539). Patients feared surge ry significantly more than anesthesia (P < 0.001). The VAS measuring fear o f anesthesia correlated well with the STAI score (r = 0.55; P < 0.01). Youn g patients, female patients, and patients with no previous anesthetic exper ience or a previous negative anesthetic experience had higher anxiety score s. Patients worried most about the waiting period preceding surgery and wer e least concerned about possible awareness intraoperatively. Factor analysi s of various anxiety items showed three distinct dimensions of fear: 1) the fear of the unknown 2) the fear of feeling: ill, and 3) the fear fur one's life. Among these dimensions, fear of the unknown correlated highest with the anxiety measuring techniques STAI and VAS. The simple VAS proved to be a useful and valid measure of preoperative anxiety. Implications: The study of qualitative aspects of anxiety reveals three distinct dimensions of pre operative fear: fear of the unknown, fear of feeling: ill, and fear for one 's life. Groups of patients with a higher degree of preoperative anxiety an d their specific anesthetic concerns can be identified using the visual ana log scale.