Evidence map›Paper›PMID 38703258›Full record

ArticleJournal of immigrant and minority health2024

Relationship between Illness Perception and the need for Professional Medical Interpretation for International Patients in Japan.

Akira Oonishi, Ai Ikeda, Francois Niyonsaba, Naoko Ono

Abstract read
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In one paragraph

Article in Journal of immigrant and minority health, 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.

Akira OonishiDepartment of Medical Interpreting, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Ai IkedaDepartment of Medical Interpreting, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Francois NiyonsabaDepartment of Medical Interpreting, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Naoko OnoDepartment of Medical Interpreting, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. na-ono@juntendo.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to conduct a cross-sectional questionnaire survey of foreign patients to analyze the impact of patients' illness perceptions on their need for professional medical interpreters. From February 2022 to May 2023, an online questionnaire was distributed to 4,962 individuals aged 18 years or older who were non-native speakers of Japanese. These individuals were enrolled in organizations such as international exchange associations and Japanese language support classes and had utilized medical institutions in Japan due to their own illness or injury or that of their children. Among the 312 valid responses, international patients with a high score for illness perception were more likely to want to utilize professional medical interpreters than those with a low score for illness perception (odds ratio, 1.968; 95% confidence interval, 1.044-3.709; P = 0.036). Our findings suggest that hospitals should be better prepared to meet the potential language needs of international patients with a higher illness perception.

Indexed as

Communication BarriersAdolescentAdultAgedCross-Sectional StudiesEmigrants and ImmigrantsFemaleHumansJapanLanguageMaleMiddle AgedPerceptionSurveys and QuestionnairesTranslatingYoung AdultIllness perceptionLanguage barrierMedical interpreterMedication adherence

Identifiers

What OpenQuestion holds

Textmetadata
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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.