Evidence map›Paper›PMID 42990795›Full record

ArticleFrontiers in digital health2026

Design and formative usability evaluation of a prototype integrated digital health platform for chronic care support.

Kekayan Nanthakumar, Kunal Gupta, Alireza F Nia, Sergio Dempsey, Nastaran Saffaryazdi, Alaeddin Nassani, Elizabeth Broadbent, Merryn Tawhai, Gonzalo Maso Talou

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Kekayan NanthakumarAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Kunal GuptaAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Alireza F NiaAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Sergio DempseyAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Nastaran SaffaryazdiAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Alaeddin NassaniDepartment of Computer Science and Engineering, University of Aizu, Aizuwakamatsu, Japan.
Elizabeth BroadbentDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, Psychological Medicine, The University of Auckland, Auckland, New Zealand.
Merryn TawhaiAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Gonzalo Maso TalouAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Chronic care management platforms often support only one or two core pillars of care, such as patient monitoring, patient activation, and data-driven care coordination. This fragmentation can limit the continuity of support and reduce the usefulness of shared patient data among patients, coaches, and clinicians. Method: This study describes the design, software architecture, and formative usability evaluation of the Digital Health Navigator (DiNa) platform, an integrated system designed to bring together the core pillars of chronic care management. DiNa combines wearable and self-reported monitoring, a large language model-powered embodied conversational agent, and a coordinator dashboard within a single modular ecosystem. DiNa was implemented as an Android application, a web-based coordinator dashboard, a microservices backend, and wearable integrations with a smartwatch and a continuous glucose monitor. The embodied conversational agent supports goal setting, logging, reminders, and knowledge-grounded education through coaching informed by motivational interviewing and cognitive behavioural therapy. We conducted moderated laboratory think-aloud usability sessions with 10 relatively young healthy volunteers familiar with digital health tracking. Participants explored the application and completed structured tasks, including setting goals, logging meals with an image, reviewing history, interacting with the coach, and viewing trends. Results: Outcomes included task performance, the System Usability Scale (SUS), a brief NASA Task Load Index (NASA-TLX), three acceptability items, and a reflexive thematic analysis of interviews. Participants completed the core tasks in a facilitated session, and a small number of critical breakdowns were observed and quantified. Mean SUS was 76.1 (SD 15.0), indicating generally good usability. Overall, the NASA-TLX workload averaged 26.7, with mental demand and effort higher than the other subscales and the remaining subscales low. Acceptability ratings indicated moderate early acceptability, with perceived usefulness rated more positively than near-term use or recommendation. Qualitative analysis identified five themes, including burdensome and sometimes unclear logging workflows, uneven goal setting, a friendly but occasionally generic coach, interface elements that reduced confidence, and a strong interest in integration with existing devices and applications. Discussion: These findings provide early evidence that an integrated platform combining continuous sensing, conversational coaching, and clinician-facing coordination is technically feasible and usable in a controlled setting with healthy volunteers, and they identify the workflow refinements needed before evaluation in clinically representative populations.

Indexed as

chronic care managementchronic disease managementconversational agentsdigital healthembodied conversational agenthealth coachinglarge language models

Identifiers

PMID42990795
PMCPMC13735224

What OpenQuestion holds

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Registered trials

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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.