Web Survey Bibliography
This retrospective evaluation of a web-based survey posted from 1 to 30 September 2010 was to determine which diagnostic tools physicians are currently utilizing to diagnose polycystic ovary syndrome (PCOS). Responses from 262 IVF centres in 68 countries are included in the study. Providers used various diagnostic criteria to diagnose PCOS, including the Rotterdam criteria (82%), National Institutes of Health criteria (8%), Androgen Excess Society 2006 criteria (3%) and other classification systems (7%). Many providers utilized diagnostic tools not necessarily included in traditional classification systems: 58% of respondents evaluated LH/FSH ratio in addition to androgen concentrations to define patients with PCOS; physicians also commonly obtain measurement of anti-Müllerian hormone (22%) and impaired glucose tolerance (74%) in diagnosing PCOS. Many respondents (64%) felt that polycystic-appearing ovaries on ultrasound with anovulation and a normal serum prolactin should be adequate criteria to diagnose PCOS. In conclusion, while the majority of centres (82%) uses the Rotterdam criteria to diagnose PCOS, other criteria and diagnostic tools are commonly used in evaluating patients with suspected PCOS. This study highlights the need for continual re-evaluation of PCOS diagnostic criteria with an ultimate goal of developing a consensus definition for the disorder in the future.
Polycystic ovary syndrome (PCOS) is a common endocrine disorder with a heterogeneous constellation of clinical manifestations which primarily affects reproductive-aged women. This clinical heterogeneity has resulted in a challenging path to create universally accepted diagnostic criteria for PCOS. To determine which diagnostic tools physicians are currently utilizing to diagnose PCOS, we evaluated a web-based survey posted on IVF-Worldwide.com from 1 to 30 September 2010. Responses from 262 IVF centres in 68 countries are included in the study. Providers used various diagnostic criteria to diagnose PCOS, including the Rotterdam criteria (82%), National Institutes of Health criteria (8%), Androgen Excess Society 2006 criteria (3%) and another classification system (7%). Many providers utilized diagnostic tools not necessarily included in these traditional classification systems: 58% of respondents evaluated the LH/FSH ratio in addition to androgen concentrations to define patients with PCOS; physicians also commonly obtain measurement of anti-Müllerian hormone (22%) and impaired glucose tolerance (74%) in diagnosing PCOS; and 64% of all respondents felt that polycystic-appearing ovaries on ultrasound with anovulation and a normal serum prolactin should be adequate criteria to diagnose PCOS. In summary, while the majority of centres (82%) uses the Rotterdam criteria to diagnose PCOS, other criteria and diagnostic tools are commonly used in evaluating patients with suspected PCOS. This study highlights the need for continual re-evaluation of PCOS diagnostic criteria with an ultimate goal of developing a consensus definition for the disorder in the future.
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Web survey bibliography - 2013 (465)
- The role of gamification in better accessing reality and hence increasing data validity ; 2015; Bailey, P.; Kernohan, H.; Pritchard, G.
- Rewarding the Truth; 2015; Puleston, J.
- Tailored fieldwork design to increase representative household survey response: an experiment in the...; 2015; Luiten, A.; Schouten, B.
- Challenges with Online Research for Couples and Families: Evaluating Nonrespondents and the Differential...; 2015; Busby, D. M.; Yoshida, Ke.
- Do Incentives Commoditize Surveys Or Reinforce The Relationship Economy?; 2014; Murphy, L.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Developing an Inclusive Web Survey Design for Respondents with Disabilities; 2013; Jagger, J.; Schaad, A.; Davis, As.; Falcone, A. E.
- The Impact of Survey Communications on Response Rates and Response Quality; 2013; Barlas, F. M.; Falcone, A. E.; Bellamy, N. D.; Mack, A. R.
- The Smartphone Way to Collect Survey Data; 2013; Stapleton, C.
- A Glimpse Inside the Mind of a Respondent: Using Paradata to Improve Online Surveys; 2013; Pape, T.; Barron, S.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Mobile-Mostly Internet Users and Noncoverage in Traditional Web Surveys ; 2013; Antoun, C.; Couper, M. P.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Leuker kunnen wij het wel maken. Online vragenlijst design: standaard matrix of scrollmatrix (We can...; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- A dual-frame sampling methodology to address landline replacement in tobacco control research..; 2013; McMillen, R. C.; Winickoff, J. P.; Wilson, K.; Tanski, S.; Klein, J. D.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Measuring Mobile Phone Use: Self-Report Versus Log Data; 2013; Boase, J., Ling, R.
- How Sliders Bias Survey Data; 2013; Sellers, R.
- Does the first impression count? Examining the effect of the welcome screen design on the response rate...; 2013; Haer, R., Meidert, N.
- Survey Research Response Rates: Internet Technology vs. Snail Mail ; 2013; Lanier, P. A., Tanner, J. R., Totaro, M. W., Gradnigo, G.
- The impact of New Zealand's 2008 prohibition of piperazine-based party pills on young people'...; 2013; Sheridan, J., Dong, C. Y., Butler, R., Barnes, J.
- PRM144 – An adaptable methodology for the design, implementation and conduct of a web-based survey...; 2013; Yeomans, K., Kawata, A. K., Bassel, M., Burk, C. T., Daniels, S. R., Wilcox, T. K.
- The relationships among nurses' job characteristics and attitudes toward web-based continuing learning...; 2013; Chiu, Y.-L., Tsai, C.-C., Fan Chiang, C.-Y.
- Surveillance of patients post-endovascular abdominal aortic aneurysm repair (EVAR). A web-based survey...; 2013; Patel, A., Edwards, R., Chandramohan, S.
- How well do volunteer web panel surveys measure sensitive behaviours in the general population, and...; 2013; Erens, B., Burkill, S., Copas, A., Couper, M. P., Conrad, F.
- Tailoring mode of data collection in longitudinal studies; 2013; Kaminska, O., Lynn, P.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Community Life Survey: Summary of web experiment findings; 2013
- Does Stress Increase the Risk of Atopic Dermatitis in Adolescents? Results of the Korea Youth Risk Behavior...; 2013; Kwon, J. A., Lee, M., Park, E.-C., Park, S., Yoo, K.-B.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- Bringing usability to pretesting of Business Survey Web Forms in Statistics Finland; 2013; Rouhunkoski, J.
- How do we Know Cognitive Interviewing is Any Good?; 2013; Willis, G. B.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- Speeding in Web Surveys: The tendency to answer very fast and its association with straightlining; 2013; Conrad, F. G.; Zhang, Che.
- About the Institute of Public Health - Data aspect; 2013; Zaletel, M.
- Analyzing Paradata to Investigate Measurement Error; 2013; Yan, T., Olson, K.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Can timestamp analyses show the bottlenecks in web surveys?; 2013; Andreadis, I.
- Timing in a web based survey: an influential factor of the response rate; 2013; Paraschiv, D.-C.
- Achieving Synergy Across Survey Modes: Mail Contact and Web Responses from Address-Based Samples; 2013; Dillman, D. A.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Collecting Diary Data on Twitter; 2013; Richards, A., Dean, E., Cook, S.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Sentiment Analysis: Providing Categorical Insight into Unstructured Textual Data; 2013; Haney, C.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.