Understanding Phenomena in the Real World: The Case for Real Time Data Collection in Health Services Research

Abstract

Understanding the environmental and behavioural predictors of wellbeing is a key driver of health and social care research. Research set in the social world examines the relationships between behavioural, cognitive, emotional and environmental factors, linking these to disease or social ills with the aim of providing better preventive or treatment services. Much of this research is based on retrospective measurement tools, such as questionnaires or interviews. However, retrospective accounts are prone to bias arising from the influence of the participant's current affective state on autobiographical memory and error-inducing heuristic strategies related to memory. Participant introspection also biases self-reports of behaviour and symptoms. This essay offers a critical examination of the advantages of ecological momentary assessment (EMA) methods over retrospective accounts in understanding social phenomena. Advantages of EMA include collection of longitudinal data from a representative part of the participant's daily experience, in real time and in the participant's natural environment. EMA accounts are gathered more closely in time to the event and are less biased by heuristic, autobiographical memory strategies. Real-time longitudinal data may be combined from a range of devices or forms of data collection; for example, self-report can be linked with objective physiological data. EMA allows testing of within-person variation in variables of interest in a way that is difficult to achieve using retrospective measures and between-person (group level) designs. EMA approaches provide not just more data, but better data than previously, allowing the application of more powerful analytic techniques to critical, real life questions than ever before.