Evidence map›Paper›PMID 39247845›Full record

ArticleIEEE journal of translational engineering in health and medicine2024

GoBot Go! Using a Custom Assistive Robot to Promote Physical Activity in Children.

Rafael Morales Mayoral, Ameer Helmi, Samuel W Logan, Naomi T Fitter

Abstract read
In one paragraph

Article in IEEE journal of translational engineering in health and medicine, 2024. 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

4 authors.

Rafael Morales MayoralCollaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University Corvallis OR 97331 USA.ORCID 0009-0007-1205-9690
Ameer HelmiCollaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University Corvallis OR 97331 USA.ORCID 0000-0002-2551-6252
Samuel W LoganDisability and Mobility Do-it-Yourself Co-OpOregon State University Corvallis OR 97331 USA.ORCID 0000-0001-8153-0967
Naomi T FitterCollaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University Corvallis OR 97331 USA.ORCID 0000-0002-6759-5948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Children worldwide are becoming increasingly inactive, leading to significant wellness challenges. Initial findings from our research team indicate that robots could potentially provide a more effective approach (compared to other age-appropriate toys) for encouraging physical activity in children. However, the basis of this past work relied on either interactions with groups of children (making it challenging to isolate specific factors that influenced activity levels) or a preliminary version of results of the present study (which centered on just a single more exploratory method for assessing child movement). This paper delves into more controlled interactions involving a single robot and a child participant, while also considering observations over an extended period to mitigate the influence of novelty on the study outcomes. We discuss the outcomes of a two-month-long deployment, during which [Formula: see text] participants engaged with our custom robot, GoBot, in weekly sessions. During each session, the children experienced three different conditions: a teleoperated robot mode, a semi-autonomous robot mode, and a control condition in which the robot was present but inactive. Compared to our past related work, the results expanded our findings by confirming with greater clout (based on multiple data streams, including one more robust measure compared to the past related work) that children tended to be more physically active when the robot was active, and interestingly, there were no significant differences between the teleoperated and semi-autonomous modes in terms of our study measures. These insights can inform future applications of assistive robots in child motor interventions, including the guiding of appropriate levels of autonomy for these systems. This study demonstrates that incorporating robotic systems into play environments can boost physical activity in young children, indicating potential implementation in settings crafted to enhance children's physical movement.

Indexed as

ExerciseRoboticsChildFemaleHealth PromotionHumansMalePlay and PlaythingsAssistive roboticschild-robot interactionphysical activity promotion

Identifiers

PMID39247845
PMCPMC11379442

What OpenQuestion holds

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LicenceCC BY
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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.