Sullivan H.W.,10903 New Hampshire Ave |
Sullivan H.W.,U.S. National Institutes of Health |
Rutten L.J.F.,U.S. National Institutes of Health |
Hesse B.W.,U.S. National Institutes of Health |
And 3 more authors.
Preventing Chronic Disease | Year: 2010
Introduction: The Common Sense Model of illness representations posits that how people think about an illness affects how they try to prevent the illness. The purpose of this study was to determine whether prevention representations vary by cancer type (colon, lung, and skin cancer) and whether representations are associated with relevant behaviors. Methods: We analyzed data from the Health Information National Trends Survey (HINTS 2005), a nationally representative survey of American adults (N = 5,586) conducted by telephone interview. Results: Respondents reported that all 3 types of cancer can be prevented through healthy behaviors; however, fewer did so for colon cancer. More respondents reported screening as a prevention strategy for colon cancer than did so for lung or skin cancer. Representations were associated with colon cancer screening, smoking status, and sunscreen use. Conclusion: Representations of cancer were associated with relevant health behaviors, providing a target for health messages and interventions.
Sullivan H.W.,10903 New Hampshire Ave |
O'Donoghue A.C.,10903 New Hampshire Ave |
Aikin K.J.,10903 New Hampshire Ave
Journal of the American Board of Family Medicine | Year: 2014
Background: In 2006, the US Food and Drug Administration reorganized the approved label format and content for prescription drugs -also known as the prescribing information (PI). This research examines primary care physicians' use of the new PI and how it may influence their perceptions about prescription drugs.Methods: A total of 500 physicians responded to an Internet survey that displayed an interactive PI for a fictitious combination pain relief/heart attack-reducing drug. The physicians answered questions about perceived risk, perceived benefit, and intention to prescribe that focused on either the treatment indication or the prevention indication.Results: Physicians viewed PI sections in order, most often viewing sections relevant to safe use, such as Warnings and Precautions and Dosage and Administration. When asked to think about the drug's efficacy, many viewed the Clinical Studies section. Viewing certain PI sections was associated with greater perceived risk and lower perceived benefits and intention to prescribe.Conclusions: These results suggest that the information in the PI could affect physician decision making and do not support further reorganization of the PI. (J Am Board Fam Med 2014;27:694-698.).
Seidman S.J.,10903 New Hampshire Ave |
Guag J.W.,10903 New Hampshire Ave
BioMedical Engineering Online | Year: 2013
Background: The use of radiofrequency identification (RFID) in healthcare is increasing and concerns for electromagnetic compatibility (EMC) pose one of the biggest obstacles for widespread adoption. Numerous studies have documented that RFID can interfere with medical devices. The majority of past studies have concentrated on implantable medical devices such as implantable pacemakers and implantable cardioverter defibrillators (ICDs). This study examined EMC between RFID systems and non-implantable medical devices.Methods: Medical devices were exposed to 19 different RFID readers and one RFID active tag. The RFID systems used covered 5 different frequency bands: 125-134 kHz (low frequency (LF)); 13.56 MHz (high frequency (HF)); 433 MHz; 915 MHz (ultra high frequency (UHF])) and 2.4 GHz. We tested three syringe pumps, three infusion pumps, four automatic external defibrillators (AEDs), and one ventilator. The testing procedure is modified from American National Standards Institute (ANSI) C63.18, Recommended Practice for an On-Site, Ad Hoc Test Method for Estimating Radiated Electromagnetic Immunity of Medical Devices to Specific Radio-Frequency Transmitters.Results: For syringe pumps, we observed electromagnetic interference (EMI) during 13 of 60 experiments (22%) at a maximum distance of 59 cm. For infusion pumps, we observed EMI during 10 of 60 experiments (17%) at a maximum distance of 136 cm. For AEDs, we observed EMI during 18 of 75 experiments (24%) at a maximum distance of 51 cm. The majority of the EMI observed was classified as probably clinically significant or left the device inoperable. No EMI was observed for all medical devices tested during exposure to 433 MHz (two readers, one active tag) or 2.4 GHz RFID (two readers).Conclusion: Testing confirms that RFID has the ability to interfere with critical medical equipment. Hospital staff should be aware of the potential for medical device EMI caused by RFID systems and should be encouraged to perform on-site RF immunity tests prior to RFID system deployment or prior to placing new medical devices in an RFID environment. The methods presented in this paper are time-consuming and burdensome and suggest the need for standard test methods for assessing the immunity of medical devices to RFID systems. © 2013 Seidman and Guag; licensee BioMed Central Ltd.