Evidence map›Paper›PMID 38063940›Full record

ArticleJournal of medical systems2023

Developing an Artificial Intelligence-Driven Nudge Intervention to Improve Medication Adherence: A Human-Centred Design Approach.

Jennifer Sumner, Anjali Bundele, Hui Wen Lim, Phillip Phan, Mehul Motani, Amartya Mukhopadhyay

Abstract read
In one paragraph

Article in Journal of medical systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jennifer SumnerMedical Affairs - Research Innovation & Enterprise, Alexandra Hospital, National University Health System, Singapore, Singapore. Jennifer_sumner@nuhs.edu.sg.
Anjali BundeleMedical Affairs - Research Innovation & Enterprise, Alexandra Hospital, National University Health System, Singapore, Singapore.
Hui Wen LimMedical Affairs - Research Innovation & Enterprise, Alexandra Hospital, National University Health System, Singapore, Singapore.
Phillip PhanJohns Hopkins Carey Business School and the Department of Medicine, Baltimore, USA.
Mehul MotaniDepartment of Electrical & Computer Engineering, National University of Singapore, Singapore, Singapore.
Amartya MukhopadhyayMedical Affairs - Research Innovation & Enterprise, Alexandra Hospital, National University Health System, Singapore, Singapore.

Funding

National University Health System health services research seed grant NUHSRO/2020/092/RO5+6/HSRG-Mar20/01
6 · The paper itself

Abstract

To improve medication adherence, we co-developed a digital, artificial intelligence (AI)-driven nudge intervention with stakeholders (patients, providers, and technologists). We used a human-centred design approach to incorporate user needs in creating an AI-driven nudge tool. We report the findings of the first stage of a multi-phase project: understanding user needs and ideating solutions. We interviewed healthcare providers (n = 10) and patients (n = 10). Providers also rated example nudge interventions in a survey. Stakeholders felt the intervention could address existing deficits in medication adherence tracking and were optimistic about the solution. Participants identified flexibility of the intervention, including mode of delivery, intervention intensity, and the ability to stratify to user ability and needs, as critical success factors. Reminder nudges and provision of healthcare worker contact were rated highly by all. Conversely, patients perceived incentive-based nudges poorly. Finally, participants suggested that user burden could be minimised by leveraging existing software (rather than creating a new App) and simplifying or automating the data entry requirements where feasible. Stakeholder interviews generated in-depth data on the perspectives and requirements for the proposed solution. The participatory approach will enable us to incorporate user needs into the design and improve the utility of the intervention. Our findings show that an AI-driven nudge tool is an acceptable and appropriate solution, assuming it is flexible to user requirements.

Indexed as

Artificial IntelligenceSoftwareEmotionsHealth PersonnelHumansMedication AdherenceBehaviour changeDesign thinkingMedication adherenceQualitative research

Identifiers

PMID38063940
PMCPMC10709244

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.