Adopting the sensemaking perspective for chronic disease self-management

J Biomed Inform. 2015 Aug;56:406-17. doi: 10.1016/j.jbi.2015.06.006. Epub 2015 Jun 10.


Background: Self-monitoring is an integral component of many chronic diseases; however few theoretical frameworks address how individuals understand self-monitoring data and use it to guide self-management.

Purpose: To articulate a theoretical framework of sensemaking in diabetes self-management that integrates existing scholarship with empirical data.

Methods: The proposed framework is grounded in theories of sensemaking adopted from organizational behavior, education, and human-computer interaction. To empirically validate the framework the researchers reviewed and analyzed reports on qualitative studies of diabetes self-management practices published in peer-reviewed journals from 2000 to 2015.

Results: The proposed framework distinguishes between sensemaking and habitual modes of self-management and identifies three essential sensemaking activities: perception of new information related to health and wellness, development of inferences that inform selection of actions, and carrying out daily activities in response to new information. The analysis of qualitative findings from 50 published reports provided ample empirical evidence for the proposed framework; however, it also identified a number of barriers to engaging in sensemaking in diabetes self-management.

Conclusions: The proposed framework suggests new directions for research in diabetes self-management and for design of new informatics interventions for data-driven self-management.

Keywords: Chronic disease; Diabetes; Framework; Self-care.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Chronic Disease / psychology
  • Chronic Disease / therapy*
  • Cognition
  • Data Collection
  • Databases, Factual
  • Diabetes Mellitus / psychology
  • Diabetes Mellitus / therapy*
  • Health Behavior
  • Humans
  • Medical Informatics / methods
  • Models, Theoretical
  • Patient Participation
  • Problem Solving
  • Self Care*
  • User-Computer Interface