Design of an ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms

INTRODUCTION Idiopathic Environmental Intolerance (IEI) attributed to electromagnetic fields (EMF) refers to self-reported sensitivity mainly characterised by the attribution of non-specific physical symptoms to low-level EMF exposure emitted from sources such as mobile phones. Scientific studies have not provided evidence for the existence of IEI-EMF, but these studies did not resemble the real-life situation or suffered from poor exposure characterisation and biased recall of health symptoms. To improve existing methods for the study of IEI-EMF, an Ecological Momentary Assessment (EMA) study is designed. METHODS AND ANALYSIS The study is an EMA study in which respondents carry personal exposure metres (exposimeters) that measure radiofrequency (RF) EMF, with frequent assessment of health symptoms and perceived EMF exposure through electronic diary registration during five consecutive days. Participants will be a selection from an epidemiological study who report to be sensitive to RF EMF. The exposimeters measure electric field strength in 12 frequency bands. Diary questions include the occurrence and severity of 10 non-specific physical symptoms, mood states and perceived exposure to (sources of) EMF. The relationship of actual and perceived EMF exposure and mood with non-specific physical symptoms will be analysed using multilevel regression analysis with time-shift models. DISCUSSION The study has several advantages over previous studies, including assessment of personal EMF exposure and non-specific physical symptoms by an ecological method with a minimised chance of recall bias. The within-person design reduces confounding by time-stable factors (eg, personal characteristics). In the conduct of the study and the analysis and interpretation of its outcomes, some methodological issues including a high participant burden, reactivity, compliance to the study protocol and the potential of chance findings due to multiple statistical testing will be accounted for and limited as much as possible.