Evidence map›Paper›PMID 42726816›Full record

ArticlePLOS digital health2026

The development of a technologic approach to improve access to individualized clinical documentation in caregivers' preferred language.

Jacqueline Toscano, King Yan Kwok, Meg Simione

Abstract read
In one paragraph

Article in PLOS digital health, 2026. 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

3 authors.

Jacqueline ToscanoDepartment of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-8215-2937
King Yan KwokDepartment of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, Massachusetts, United States of America.
Meg SimioneDepartment of Communicative Disorders, College of Health Sciences, University of Rhode Island, Kingston, Rhode Island, United States of America.ORCID https://orcid.org/0000-0003-2636-9714

Funding

Adapting a pediatric weight management program for implementation via telehealthK23HL161447 · NHLBI · UNIVERSITY OF RHODE ISLAND · PI Meg Simione · 2022 to 2026
$709k
NHLBI NIH HHS K23 HL161447
6 · The paper itself

Abstract

This pilot study aims to describe the process of developing a template that semi-automatically translates information from English to Spanish to improve caregivers' access to clinical documents in their preferred language. It used human-centered design and the Discover, Design/Build, and Test Framework to improve health literacy outcomes for patients who use a language other than English. The Discover Phase revealed current methods and barriers to clinicians providing patients access to written documentation in their primary language. During the Design/Build Phase, an interprofessional team of a speech-language pathologist and a certified translation specialist developed the template in the electronic health record. In the Test Phase, we evaluated the template's acceptability and feasibility and surveyed speech-language pathologists (SLPs) and patients' caregivers. Clinicians affirmed the importance of the template, but also had concerns regarding feasibility and usability. Caregivers found it helpful to receive their child's health information in their primary language. The results showed that sustainable access to written documentation in patients' preferred language is lacking, and this template is prepared to reduce language barriers in an overwhelmed healthcare system.

Identifiers

PMID42726816
PMCPMC13568490

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.