Ecological Momentary Assessment Methodology in Chronic Pain Research: A Systematic Review

Highlights

• One hundred and five articles from 62 research projects were included in the review.

• Reviewed studies were heterogeneous in terms of protocol design.

• Protocol design features were not consistently reported.

• Reporting guidelines are intended to facilitate replicability and interpretation of results.

Abstract

Self-reported pain intensity assessments are central to chronic pain research. Ecological momentary assessment (EMA) methodologies are uniquely positioned to collect these data, and are indeed being used in the field. However, EMA protocols are complex, and many decisions are necessary in the design of EMA research studies. A systematic literature review identified 105 articles drawing from 62 quantitative EMA research projects examining pain intensity in adult chronic pain patients. Study characteristics were tabulated to summarize and describe the use of EMA, with an emphasis placed on various dimensions of decision-making involved in executing EMA methodologies. Most identified studies considered within-person relationships between pain and other variables, and a few examined interventions on chronic pain. There was a trend toward the use of smartphones as EMA data collection devices more recently, and completion rates were not reported in nearly one third of studies. Pain intensity items varied widely with respect to number of scale points, anchor labels, and length of reporting period; most used numeric rating scales. Recommendations are provided for reporting to improve reproducibility, comparability, and interpretation of results, and for opportunities to clarify the importance of design decisions.

Perspective

Studies that use EMA methodologies to assess pain intensity are heterogeneous. Aspects of protocol design, including data input modality and pain item construction, have the potential to influence the data collected. Thorough reporting on design features and completion rates therefore facilitates reproducibility, comparability, and interpretation of study results.