Evidence map›Paper›PMID 30235656›Full record

Trial reportMedicine2018

Modifying and evaluating efficacy of interactive computerized program using motion tracking technology to improve unilateral neglect in patients with chronic stroke.

Si Hyun Kang, Don-Kyu Kim, Kyung Mook Seo, Kwang Nam Choi

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 51% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Trial
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 at 1 institution in 1 country.

Si Hyun KangDepartment of Physical Medicine & Rehabilitation School of Computer Science & Engineering, Chung-Ang University, Seoul, Republic of Korea.
Don-Kyu Kim
Kyung Mook Seo
Kwang Nam Choi
Chung-Ang University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo modify and evaluate the efficacy of a computerized visual perception rehabilitation program using interactive motion tracking technology with unilateral neglect after chronic stroke.

methodsStudy design is single-blinded (analyst-blinded) controlled prospective clinical trial. Subjects are 16 patients with chronic stroke and unilateral neglect for over 6 months and 19 healthy volunteers. We modified our previous program to 9 tasks with built-in scoring system, and the subjects performed 3 sessions per week, 30 minutes per session for 4 weeks.

resultsScores for the Modified Barthel Index (MBI), Mini-Mental State Examination (MMSE), Motor-free Visual Perception Test (MVPT), Line bisection test, Star cancellation test, Forward Digit Test, and Backward Digit Test showed significant improvement at the end of the sessions in the patient group. By comparing the parameters of built-in scoring system of each task among the control group, the first session of training in the patient group, and the last session of training in the patient group, we categorized the parameters for optional measurement to determine the effect of training or to be a candidate for evaluative use.

conclusionsOur modified computerized visual perception rehabilitation program using improved unilateral neglect in patients post-stroke. Built-in scoring system in this program was helpful to assess availability of it more objectively.

Indexed as

MotionSoftwareVisual PerceptionAgedAlgorithmsChronic DiseaseFemaleHumansMaleMiddle AgedNeuropsychological TestsProspective StudiesSingle-Blind MethodStroke Rehabilitation

Identifiers

PMID30235656
PMCPMC6160019
OpenAlexW2895162662

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.