Evidence map›Paper›PMID 40642214›Full record

SynthesisFrontiers in neurology2025

Psychometric properties of technology-assisted matching paradigms in post-stroke upper limb proprioceptive assessment: a scoping review.

Guiyi Gu, Ruixuan Lin, Roy Rongyue Zeng, Tiev Miller, Jack Jiaqi Zhang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology, 2025. 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

5 authors.

Guiyi Gu *Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Ruixuan Lin *Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Roy Rongyue ZengDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Tiev MillerDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.
Jack Jiaqi ZhangDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Proprioceptive impairments affect 34-64% of post-stroke patients, impacting motor recovery and daily activities. Technology-assisted matching paradigms offer precise, quantitative assessment of upper limb proprioception, but their psychometric properties require evaluation. Methods: The search was conducted using PubMed, Web of Science, EMBASE, and MEDLINE to identify studies on technology-assisted matching paradigms for assessing upper limb proprioception in post-stroke patients. Studies were selected based on the inclusion and exclusion criteria, and relevant data were extracted. Results: A total of 13 articles were included. Upper limb robots for active mirror-matching tasks were the most used technology among our included studies (9 out of 13 studies). Seven studies showed a moderate level of concurrent validity, and four studies showed a moderate level of convergent validity. Seven studies compared stroke patients to healthy individuals, with most showing good responsiveness. Five studies revealed moderate to high test-retest and inter-rater reliability. Conclusion: Technology-assisted matching paradigms demonstrate moderate validity and moderate to high reliability when applied in clinical settings for assessing upper limb proprioception in post-stroke patients.

Indexed as

assessmentproprioceptionpsychometricsrehabilitation engineeringsensory disordersstroke

Identifiers

PMID40642214
PMCPMC12243609

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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.