Evidence map›Paper›PMID 41935162›Full record

ArticleNPJ digital medicine2026

Developing psychosocial phenotypes to understand engagement with digital health technologies for heart failure.

Rachel Tunis, Namuun Clifford, Emily West, Elizabeth Heitkemper, Marissa Burgermaster, Kavita Radhakrishnan

Registry-linked trialAbstract read
In one paragraph

Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05056129 (Sensor-controlled Digital Game for Heart Failure Selfmanagement Behavior Adherence), which is not on this 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.

NCT05056129 narecruitingnot on this map

Sensor-controlled Digital Game for Heart Failure Selfmanagement Behavior Adherence: A Randomized Controlled Trial

TypeinterventionalSponsorUniversity of Texas at AustinRan2022 to 2026Enrolled200ConditionsHeart FailureArmsSensor-controlled digital game (SCDG), Sensor Only
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

6 authors.

Rachel TunisSchool of Information, The University of Texas at Austin, Austin, TX, USA. rtunis@utexas.edu.
Namuun CliffordSchool of Nursing, The University of Texas at Austin, Austin, TX, USA.
Emily WestSchool of Nursing, The University of Texas at Austin, Austin, TX, USA.
Elizabeth HeitkemperSchool of Nursing, The University of Texas at Austin, Austin, TX, USA.
Marissa BurgermasterDepartment of Nutritional Sciences, The University of Texas at Austin, Austin, TX, USA.
Kavita RadhakrishnanSchool of Nursing, The University of Texas at Austin, Austin, TX, USA.

Funding

Sensor-controlled digital game for heart failure self-management behavior adherence: A randomized controlled trialR01HL160692 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI RADHAKRISHNAN, KAVITA · 2022 to 2025
$2.8M
Precision Health Intervention Methodology Training in Self-Management of Multiple Chronic ConditionsT32NR019035 · NINR · UNIVERSITY OF TEXAS AT AUSTIN · PI STUIFBERGEN, ALEXA · 2020 to 2024
$995k
National Heart, Lung, and Blood Institute, United States R01HL160692NHLBI NIH HHS R01 HL160692NINR NIH HHS T32 NR019035
6 · The paper itself

Abstract

Digital health technologies (DHTs) such as wearables, smartphones, and connected devices have immense potential for supporting self-care in chronic disease management, yet engagement remains highly variable and is often measured by usage metrics alone. Guided by the AIM-ACT framework, this mixed-methods study examined how psychosocial and contextual factors shape DHT engagement among 146 adults with heart failure who completed a 6-month digital intervention involving multiple devices (ClinicalTrials.gov ID NCT05056129). Using k-medoids clustering of survey, ecological momentary assessment, and device-log data, we identified three distinct psychosocial phenotypes-Challenged Survivors, Activated Learners, Engaged Self-Regulators-reflecting differences in motivation, psychosocial resources, and interaction with DHTs. Qualitative interviews with 26 participants contextualized these phenotypes and revealed mechanisms linking psychosocial traits to DHT engagement quality. Findings underscore the value of psychosocial phenotyping for understanding heterogeneity in DHT engagement to inform the design of adaptive and equitable digital interventions that remain effective as they scale across diverse populations.

Identifiers

PMID41935162
PMCPMC13230796

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Registered trials

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.