EconPapers    
Economics at your fingertips  
 

The performance of an online osteoporosis detection system a sensitivity and specificity analysis

Shu Fang Chang, Chin Ming Hong and Rong Sen Yang

Journal of Clinical Nursing, 2014, vol. 23, issue 13-14, 1803-1809

Abstract: Aims and objectives To develop an online system for the detection of osteoporosis risk and to test its accuracy. Background Osteoporosis is a silent killer; usually, there are no symptoms, such as pain, until bone erosion and fracture occur. The risks of osteoporosis have been underestimated and neglected; as a result, osteoporosis can be as dangerous as heart diseases and cancers that lead to a healthcare crisis. Design Cross‐sectional study. Methods The study participants were individuals presenting for routine health examinations at a medical centre in Taiwan from 2006–2007. Women over 30 years of age who underwent dual‐energy X‐ray absorptiometry scanning for measurement of bone mineral density were eligible for this study. The system for osteoporosis detection and health risk, which was developed in this study, was analysed. Results The findings indicated a high sensitivity of 75%, specificity of 75%, positive predictive value of 75% and negative predictive value of 75%. In addition, the online osteoporosis detective system had a higher predictive power (24·2% vs. 11%) and a similar cut‐off point (33% vs. 27%) compared with the tool designed by the International Osteoporosis Foundation. Conclusion The online system for detection of osteoporosis risk had excellent reliability and validity. It performed well in predicting osteoporosis and the cut‐off point used for identifying the risk among women at risk of developing osteoporosis. Therefore, it is suitable for the Asian women and can help women achieve the goals of early detection and health promotion. Relevance to clinical practice Early detection is the only way to prevent osteoporosis. Professional nurses should apply effective technology to promote health care in community‐dwelling people.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/jocn.12209

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jocnur:v:23:y:2014:i:13-14:p:1803-1809

Access Statistics for this article

More articles in Journal of Clinical Nursing from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:jocnur:v:23:y:2014:i:13-14:p:1803-1809