E-epidemiology : adapting epidemiological methods for the 21st century

Abstract

The traditional methods in epidemiological data collection are both costly and time consuming and less convenient for longitudinal large-scale studies. During the last decades, epidemiological studies suffer from low response rates, indicating a need to revise methods used in epidemiological data collection. e-epidemiology is the science underlying usage of Information and Communication Technologies (ICT) in epidemiological studies and enable new possibilities for data collection. In this thesis four studies evaluating methods including mobile phones, the web and Interactive Voice Response (IVR) are described.

In study I, the feasibility of using an Internet-based hearing test combined with a web-based questionnaire was evaluated in a pilot study among Swedish hunters. The response rate was very low with a bias toward older individuals (40-60 years) who had access to the correct equipment at study start. Though a number of limitations, the hearing-test demonstrates a possibility of using the web in epidemiological data collection.

In study II, repeated measures of physical activity level (PAL) through a Java-based questionnaire in mobile phones were compared to a gold standard of measuring energy expenditure. The Java-based physical activity questionnaire sent repeatedly through mobile phones produced average PAL estimates that agreed well with PAL reference values, indicating that the method may be a feasible and cost effective method for data collection on physical activity.

Study III compared data collected through Short Message Service (SMS) to traditional telephone interviews in a population-based sample. Though the study produced very low response rate, the results on influenza vaccination status was not statistically significantly different from data collected through telephone interviews.

Study IV compared data on self-reports on infectious disease where the participants could choose between web and IVR. The web was more popular than IVR and attracted more men and younger individuals with a higher completed education compared to IVR. There was no statistically significantly difference of reported infections or Influenza-Like Illness (ILI) between the two techniques after adjusting for available confounders.

Studies I, III and IV were affected by low response rates, effecting both the validity and precision of the results. All studies were affected by bias and all but study II were probably confounded by age. The mechanisms behind these factors are important to evaluate further in order to understand how it affects the collected data. However, when possible to adjust for confounders, the techniques per se did not seem to influence data negatively compared to reference data. All studies were evaluated on a Swedish population with high access to the Internet and mobile phones, and the results might not be generalizable to populations with less access.

This thesis has demonstrated a fraction of the possibilities using ICT in epidemiological data collection and e-epidemiology is still in its youth. Once the techniques have been thoroughly evaluated, there are probably endless possibilities to ensure high quality data collection through methods adapted to a modern society.