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Understanding the use of contextual cues: design implications for medication adherence technologies that support remembering

Stawarz, Katarzyna ORCID:, Rodríguez, Marcela D, Cox, Anna L and Blandford, Ann 2016. Understanding the use of contextual cues: design implications for medication adherence technologies that support remembering. DIGITAL HEALTH 2 , p. 18. 10.1177/2055207616678707

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Objective: Forgetfulness is one of the main reasons of unintentional medication non-adherence. Adherence technologies that help people remember to take their medications on time often do not take into account the context of people’s everyday lives. Existing evidence that highlights the effectiveness of remembering strategies that rely on contextual cues is largely based on research with older adults, and thus it is not clear whether it can be generalized to other populations or used to inform the design of wider adherence technologies that support medication self-management. Understanding how younger populations currently remember medications can inform the design of future adherence technologies that take advantage of existing contextual cues to support remembering. Methods: We conducted three surveys with a total of over a thousand participants to investigate remembering strategies used by different populations: women who take oral contraception, parents and carers who give antibiotics to their children, and older adults who take medications for chronic conditions. Results: Regardless of the population or the type of regimen, relying on contextual cues—routine events, locations, and meaningful objects—is a common and often effective strategy; combinations of two or more types of cues are more effective than relying on a single cue. Conclusions: To effectively support remembering, adherence technologies should help users recognize contextual cues they already have at their disposal and reinforce relevant cues available in their environment. We show that, given the latest developments in technology, such support is already feasible.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
ISSN: 2055-2076
Date of First Compliant Deposit: 30 March 2020
Date of Acceptance: 19 October 2016
Last Modified: 05 May 2023 10:29

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