Evidence map›Paper›PMID 42837519›Full record

ArticleJournal of medical Internet research2026

User Experiences With a Social Robot for Cardiometabolic Risk Assessment in a Community Setting in Uppsala, Sweden: Qualitative Semistructured Interview Study.

Solveig Dolores Bruchhof, Helle Mölsted Alvesson, Jonas Idevall Hagren, Katie Winkle, Laran Matta, Marcus Göransson, Steve McKeever, Meena Daivadanam

Abstract read
In one paragraph

Article in Journal of medical Internet research, 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

8 authors.

Solveig Dolores BruchhofDepartment of Women's and Children´s Health, Faculty of Medicine, Uppsala University, Dag Hammarskjölds väg 14B, Uppsala, Sweden, +46 72 999 97 20.ORCID http://orcid.org/0009-0008-3482-0169
Helle Mölsted AlvessonDepartment of Global Public Health, Karolinska Institutet, Stockholm, Sweden.ORCID http://orcid.org/0000-0001-6109-7203
Jonas Idevall HagrenDepartment of Women's and Children´s Health, Faculty of Medicine, Uppsala University, Dag Hammarskjölds väg 14B, Uppsala, Sweden, +46 72 999 97 20.ORCID http://orcid.org/0009-0007-1589-7577
Katie WinkleDepartment of Information Technology, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0002-3309-3552
Laran MattaDepartment of Women's and Children´s Health, Faculty of Medicine, Uppsala University, Dag Hammarskjölds väg 14B, Uppsala, Sweden, +46 72 999 97 20.ORCID http://orcid.org/0009-0006-3610-8728
Marcus GöranssonDepartment of Information Technology, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0009-0009-9650-7917
Steve McKeeverDepartment of Informatics and Media, Uppsala University, Uppsala, Sweden.ORCID http://orcid.org/0000-0002-1970-2884
Meena DaivadanamDepartment of Women's and Children´s Health, Faculty of Medicine, Uppsala University, Dag Hammarskjölds väg 14B, Uppsala, Sweden, +46 72 999 97 20.ORCID http://orcid.org/0000-0002-9532-6059

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiometabolic diseases (CMDs) are a major health concern worldwide, with people living in socioeconomically disadvantaged areas being disproportionately affected. Knowing one's risk status for developing a CMD can help individuals in delaying or preventing the disease. Innovative tools and strategies such as the use of AI-based technology are needed to improve inclusivity, cost-effectiveness, and sustainability of screening processes. Objective: This study aimed to assess users' perceptions of the usability and acceptance of the social robot "Furhat" for cardiometabolic risk assessment within a socioeconomically disadvantaged community in Uppsala, Sweden. Methods: In this qualitative study, 13 semistructured interviews were conducted with participants living in socially disadvantaged areas within Uppsala, after they completed a CMD risk assessment delivered by the social robot. The study was conducted in one of the socioeconomically disadvantaged areas in Uppsala from October 19 to 26, 2023. Participants were purposefully sampled at different community events via phone or on the street to achieve the desired variation regarding personal characteristics such as age, gender, or area of living. The used interview guide for this study consisted of questions regarding the demographics, participants' experiences with the robot screening, and suggestions for improvements. A framework analysis approach was applied to the data. Results: Two themes were developed. The first theme Conclusions: This study provides insights into users' perceptions of the usability and acceptance of a social robot for risk assessment in a community context, which can help inform the further development of this technology for health screening in a community context. In the future, the robot could be further developed to conduct risk assessments in multiple languages and offer a broader service to users, such as providing appropriate information related to healthy and active living.

Indexed as

Cardiovascular DiseasesRoboticsAdultAgedFemaleHumansInterviews as TopicMaleMiddle AgedQualitative ResearchRisk AssessmentSwedenartificial intelligencecardiometabolic diseaseFINDRISChealth innovationrisk assessmentsocial robotsocioeconomically disadvantagedtype 2 diabetes

Identifiers

PMID42837519
PMCPMC13641321

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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.