Evidence map›Paper›PMID 42370010›Full record

ArticleDigital health

Development and preliminary validation of a WeChat-based auditory-speech rehabilitation system for Mandarin-speaking cochlear implant users.

Xuyuan Peng, Ran Cao, Pengjun Wang, Zheng Han, Yini Li, Jingjing Wang, Shujian Huang, Wen Lu, Yuli Hu, Jing Wang and 7 more

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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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

17 authors.

Xuyuan PengDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ran CaoDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Pengjun WangDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zheng HanDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yini LiDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jingjing WangDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shujian HuangDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wen LuDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuli HuDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jing WangDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhengnong ChenDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wendi ShiHangzhou Ren-Ai Hearing Rehabilitation Research Center, Hui'er Artificial Intelligence Hearing Research Center, Hangzhou, China.ORCID https://orcid.org/0009-0001-4169-5510
Lihui TaoShanghai Miaoyanhui Technology Co., Ltd, Shanghai, China.
Jun ZhanShanghai Miaoyanhui Technology Co., Ltd, Shanghai, China.
Kun NiDepartment of Otolaryngology-Head & Neck Surgery, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Dongzhen YuDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Haibo ShiDepartment of Otolaryngology Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cochlear implant (CI) users require long-term auditory-speech rehabilitation to achieve optimal outcomes, yet access to continuous and structured rehabilitation remains limited. Mobile health technologies offer a potential approach to improve the accessibility and continuity of rehabilitation services. Objective: This study aims to develop a WeChat-based auditory-speech rehabilitation system for Mandarin-speaking CI users and to conduct a preliminary validation of its usability and measurement consistency. Methods: Guided by a goal-oriented digital design framework, a WeChat-based system was developed to assess six domains of auditory and speech rehabilitation. A total of 20 Mandarin-speaking CI users were recruited from Shanghai Sixth People's Hospital. Usability and app quality were assessed using the System Usability Scale (SUS) and User Version of the Mobile App Rating Scale (uMARS), respectively. Measurement consistency was evaluated using the intraclass correlation coefficient (ICC), weighted Cohen's kappa (κ), and Bland-Altman analyses. Results: 20 Mandarin-speaking CI users completed the study. Usability assessment demonstrated favorable ratings (SUS = 71.50, SD = 13.58; uMARS = 4.19, SD = 0.50). The system-generated Categories of Auditory Performance classification showed excellent agreement with the rater (weighted κ = 0.97, 95% CI: 0.93-1.00). Articulation intelligibility scores demonstrated high consistency with rater assessments (system vs. rater 1: ICC = 0.97; system vs. rater 2: ICC = 0.94), with minimal bias observed in Bland-Altman analysis. Conclusion: This WeChat Mini Program provides preliminary support for the feasibility of a digital auditory-speech rehabilitation approach for Mandarin-speaking CI users. Further studies are needed to validate its broader applicability and effectiveness in out-of-hospital rehabilitation.

Indexed as

auditory-speech rehabilitationcochlear implantdigital healthhome-based rehabilitationusability

Identifiers

PMID42370010
PMCPMC13305792

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.