RESUMEN
Accurate prevalence data on illnesses are of paramount importance for medical decision-making, healthcare planning, and the appropriate allocation of healthcare resources. When assessing the prevalence of any illness or health condition, it is important to base prevalence data on an assessment of the general population at large and not on selected groups of the population. Previous estimates of the prevalence of lower urinary tract symptoms (LUTS) have used postal surveys, telephone and in-person interviews, and, more recently, the Internet. Determining the mode of data collection for a research study is dictated by several factors, including target population, topic sensitivity, timeliness, and available resources. The purpose of this report is to document the rationale for conducting a large prevalence study of LUTS and its impact on patient outcomes using Internet- or Web-based surveys. A brief overview of important survey considerations is provided, and previous survey methods used in assessing the prevalence of LUTS discussed. The research objectives and sampling approach used in the EpiLUTS study in the USA, the UK and Sweden are presented, with a discussion of the advantages and disadvantages of this Internet-based sampling approach in relation to other epidemiological methods.
Asunto(s)
Internet , Prostatismo/epidemiología , Calidad de Vida , Trastornos Urinarios/epidemiología , Adulto , Anciano , Métodos Epidemiológicos , Europa (Continente)/epidemiología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estados Unidos/epidemiologíaRESUMEN
The authors explore how to define a welfare spell and how well surveys measure welfare spells. By comparing survey and administrative data from the Work Pays Demonstration Project in California on the receipt of Aid to Families with Dependent Children (AFDC), they find that a substantial amount of administrative churning occurs in administrative data. Through a mixing model of several break lengths, the authors find that a single definition of a break in welfare is not applicable to all respondents. Additionally, it appears that there is substantial variation in the break lengths respondents utilize. Finally, the authors show that the complexity of defining an accurate break in spells creates difficulties for detecting biases in survey responses.