Longitudinal research has begun to embrace new technologies to supplement traditional data collection methods. New technologies are increasingly being used to improve the quality and quantity of different data, as well as collecting entirely new kinds of data. Smartphones, fitness trackers, or the ‘internet of things’ provide new data on study respondents, while linking to social media, smart meters and loyalty cards can generate additional information not available via traditional survey methods.
These new technologies offer potential advantages over questionnaire-based data collection in terms of the content and quality of data collected, the burden placed on respondents, and the cost of data collection. However, which of these benefits can be realised depends on the features of the technology, how it is used and, most importantly, the purpose of collecting the data in this way:
Is the aim to collect new content that cannot be reliably collected with survey questionnaires?
Or is it to collect more accurate or more detailed data?
If it’s the latter, is the full granularity that can be collected with some technologies actually required to address the research questions, or are we collecting data just because it’s there – and because we can? Researchers need to consider these key questions when collecting data using new technologies. By reflecting on why we would like to use these data, we can create more effective survey designs and gain a better understanding of how to mitigate the challenges that new technology presents.
For example, the passive measurement of health and other behaviours enabled by new digital technologies offers the possibility of capturing data less susceptible to the biases usually associated with self-reporting. But it creates new sources of bias in terms of who might participate and how well they engage.
Understanding how respondents engage with and use new technologies is also vital. This includes considering the barriers to using new technologies, what motivates an individual’s participation, what preferences respondents have that are relevant to that data collection method, and understanding biases in who participates and who doesn’t. As with any survey, full participation by all sample members is not achievable, but if we understand what stops people taking part we can design features of the data collection in such a way that barriers are reduced.
Technology evolves at a tremendous rate and new innovations can quickly become outdated – an issue when researchers want to compare longitudinal measures over time. Some technologies produce large volumes of data that require new methods and skills for handling, storage and analysis. Many studies using new technologies have thus far been on small samples, leaving open questions as to how to scale data collection up to large sample sizes.
A CLOSER report I wrote with my colleagues Dr Alessandra Gaia (City University) and Professor Michaela Benzeval (University of Essex) considers these and many other opportunities and challenges.
More research is needed on how we use new technology in longitudinal studies. We want to ensure that we’re keeping pace with technology and using these data appropriately to provide new insights in key research areas. We’re aware of the possibilities that are there, but we’re also aware of the challenges they bring with them.