Evidence map›Paper›PMID 42908812›Full record

ArticleFrontiers in digital health2026

Potential and limitations of socially assistive robots to support malnutrition care: a critical reflection by dietitians.

Janna W Alberts, Martijn H Vastenburg, Henk Herman Nap, Wijnand A IJsselsteijn

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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.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Janna W AlbertsHuman-Technology Interaction Group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands.
Martijn H VastenburgDonders Centre for Cognition, Radboud University, Nijmegen, Netherlands.
Henk Herman NapHuman-Technology Interaction Group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands.
Wijnand A IJsselsteijnHuman-Technology Interaction Group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nutrition is essential for the physical and psychological well-being and health of older adults. Malnutrition negatively affects both their physical and mental health and their overall quality of life. Dietitians face challenges in supporting older adults due to time constraints, which can limit the continuity of care. While previous research highlights the potential of assistive technologies to help reduce malnutrition, such as socially assistive robots (SARs), these approaches lack a holistic perspective and insufficiently address collaborative processes within the broader care network. This study presents the findings from a Research-through-Design (RtD) study in which eight dietitians from four practices participated in context-mapping sessions involving personas, generative design probes, ranking exercises, and speculative design activities to critically reflect on the potential role of socially assistive robots in supporting collaborative malnutrition care. The results were analyzed using reflexive thematic analysis. These results highlight key challenges in nutritional care, including the social nature of eating, the need for personalized support, and challenges within the care network. These findings informed potential roles for SARs, including reinforcing dietary advice, supporting shared decision-making, facilitating collaboration, and encouraging shared eating moments. Crucially, the findings suggest that the value of SARs depends less on adding new functionalities than on carefully positioning their role within collaborative nutritional care. This includes preserving older adults' autonomy, clearly allocating responsibilities between dietitians and technology, supporting meaningful engagement between consultations, and maintaining appropriate professional boundaries.

Indexed as

care networkcontextmappingdietitiansmalnutritionolder adultsresearch through designSARS

Identifiers

PMID42908812
PMCPMC13683615

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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.