Evidence map›Paper›PMID 36158255›Full record

ArticleInternational journal of social robotics2022

Extended Interviews with Stroke Patients Over a Long-Term Rehabilitation Using Human-Robot or Human-Computer Interactions.

Yaacov Koren, Ronit Feingold Polak, Shelly Levy-Tzedek

Abstract read
In one paragraph

Article in International journal of social robotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

3 authors.

Yaacov KorenDepartment of Sociology and Anthropology, Tel-Aviv University, Tel-Aviv, Israel.
Ronit Feingold PolakRecanati School for Community Health Professions, Department of Physical Therapy, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Shelly Levy-TzedekRecanati School for Community Health Professions, Department of Physical Therapy, Ben-Gurion University of the Negev, Beer-Sheva, Israel.ORCID 0000-0002-5853-3235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Socially assistive robots (SARs) have been proposed to assist post-stroke patients in performing their exercise during their rehabilitation process, with the trust in the robot identified as an important factor in human-robot interaction. In the current study, we aimed to identify and characterize factors that influence post-stroke patients' trust in a robot-operated and a computer-operated rehabilitation platform during and after a long-term experience with the platform. We conducted 29 interviews with 16 stroke patients who underwent a long-term rehabilitation process, assisted by either a SAR or a computer interface. The intervention lasted 5-7 weeks per patient, for a total of 229 sessions over 18 months. By using a qualitative research method-extended interviews "in the wild" with stroke patients, over a long-term rehabilitation process-our study reveals users' perspectives regarding factors affecting trust in the SAR or in the computer interface during their rehabilitation process. The results support the assertion that SARs have an added value in the rehabilitative care of stroke patients; It appears that personal characteristics, such as age and gender, have an effect on the users' acceptance of a non-human operator as a practice assistant. Our findings support the notion that SARs augment rehabilitative therapies beyond a standard computer; Importantly, patients appreciated different aspects of the non-human operator in the two groups: In the SAR group, users preferred its functional performance over its anthropomorphized social skills; In the Computer group, users highlighted its contribution to the training of their memory skills. Supplementary Information: The online version contains supplementary material available at 10.1007/s12369-022-00909-7.

Indexed as

In the wildLong-term interactionQualitative methodsSocially assistive robot (SAR)Stroke rehabilitationTrust

Identifiers

PMID36158255
PMCPMC9483483

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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.