Although the scientific literature contains numerous reports of the statistical accuracy of systems for self-monitoring of blood glucose (SMBG), most of these studies determine accuracy in ways that may not be clinically useful. We have developed an error grid analysis (EGA), which describes the clinical accuracy of SMBG systems over the entire range of blood glucose values, taking into account 1) the absolute value of the system-generated glucose value, 2) the absolute value of the reference blood glucose value, 3) the relative difference between these two values, and 4) the clinical significance of this difference. The EGA of accuracy of five different reflectance meters (Eyetone, Dextrometer, Glucometer I, Glucometer II, Memory Glucometer II), a visually interpretable glucose reagent strip (Glucostix), and filter-paper spot glucose determinations is presented. In addition, reanalyses of a laboratory comparison of three reflectance meters (Accucheck II, Glucometer II, Glucoscan 9000) and of two previously published studies comparing the accuracy of five different reflectance meters with EGA is described. EGA provides the practitioner and the researcher with a clinically meaningful method for evaluating the accuracy of blood glucose values generated with various monitoring systems and for analyzing the clinical implications of previously published data.

Background-The Internet has become a major component to health care and has important implications for the future of the health care system. One of the most notable aspects of the Web is its ability to provide efficient, interactive, and tailored content to the user. Given the wide reach and extensive capabilities of the Internet, researchers in behavioral medicine have been using it to develop and deliver interactive and comprehensive treatment programs with the ultimate goal of impacting patient behavior and reducing unwanted symptoms. To date, however, many of these interventions have not been grounded in theory or developed from behavior change models, and no overarching model to explain behavior change in Internet interventions has yet been published.

IDDM subjects who believe they have reduced awareness of hypoglycemia are generally correct. They have a history of more moderate and severe hypoglycemia, are less accurate at detecting BG < 3.9 mmol/l, and prospectively experience more moderate and severe hypoglycemia than do aware subjects. Neither disease duration nor level of glucose control explains their reduced awareness of hypoglycemia. Reduced-awareness individuals may benefit from interventions designed to teach them to recognize all of their potential early warning symptoms.

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Hypoglycemia can lead to various aversive symptomatic, affective, cognitive, physiological, and social consequences, which in turn can lead to the development of possible phobic avoidance behaviors associated with hypoglycemia. On the other hand, some patients may inappropriately deny or disregard warning signs of hypoglycemia. This study presents preliminary reliability and validity data on a psychometric instrument designed to quantify this fear: the hypoglycemic fear survey. The instrument was found to have internal consistency and test-retest stability, to covary with elevated glycosylated hemoglobin, and to be sensitive to a behavioral treatment program designed to increase awareness of hypoglycemia.