Clarity or Abstraction? Semantic Preferences for Health Data Representations Among Older Adults and Experts

As digital health moves into the homes, older adults are increasingly asked to make sense of everyday measurements (blood pressure, sleep), yet common Health Data Representations (HDRs) privilege clinical abstraction over everyday understanding. Misinterpretations can lead to anxiety, missed actions, and inequality. While usability work optimises interaction, semantic transparency, i.e. how a graph, colour, text, or number communicates “what something means to a user” in a self-management context, remains under-specified. We explored how older adults and domain experts interpret the same HDRs, examining where meanings align or differ and how design can bridge this gap. Using a sequential mixed-methods study with 27 participants, including expert think-aloud protocols and severity ratings on four conventional HDRs, followed by scenario-based workshops and co-design with older adults, we conducted a cross-group thematic synthesis. The findings surface three themes: (1) an intent–interpretation gap, where older adults seek actionable context while experts assume numeric/threshold sufficiency; (2) barriers such as semantic confusion in visual signposts, affordance breakdowns, and a recurrent trade-off between comfort-driven simplicity and information sufficiency; and (3) emotion and narrative, where ambiguity amplifies anxiety, and brief narrative summaries with redundant cues reassure and enhance understanding. We operationalise “Semantic mirroring”, a layered approach (surface, interpretive, action) that adapts to the user, goal, and context. We present a rapid protocol for participatory semantics testing combining co-design with simple quantitative indicators. The result is immediate, practical guidance for safer, more comprehensible, and more equitable HDRs, along with a foundation for a coherent semantic grammar for HDRs.