Evidence map›Paper›PMID 41996173›Full record

ArticleJournal of medical Internet research2026

Facility-Level Associations Between Use of a Digital Health Platform for Voluntary Counseling and Testing and HIV Testing Outcomes in the Urban Primary Health Care Centers of Guangzhou, China: Cross-Sectional Study.

Ye Chen, Yu-Fei Wang, Yu-Zhou Gu, Xiao-Ru Fan, Yong-Heng Lu, Ju-Shuang Li, Jun Wang, Zhi-Ye Lin, Chun-Li Zhang, Meng-Die Li and 7 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 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
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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

17 authors.

Ye Chen *Department of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0007-5040-9612
Yu-Fei Wang *Department of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0006-8374-9173
Yu-Zhou Gu *Guangzhou Center for Disease Control and Prevention (Guangzhou Health Supervision Institute), Guangzhou, China.ORCID https://orcid.org/0000-0002-9187-9190
Xiao-Ru FanLiwan District Center for Disease Control and Prevention, Guangzhou, China.ORCID https://orcid.org/0009-0001-3098-9652
Yong-Heng LuGuangzhou Lingnan Community Support Center, Guangzhou, China.ORCID https://orcid.org/0009-0008-1977-7449
Ju-Shuang LiDepartment of Epidemiology and Health Statistics, School of Public Health, Hengyang Medical School, Hengyang, China.ORCID https://orcid.org/0000-0002-5906-0265
Jun WangHospital of Stomatology, Sun Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0001-5163-8683
Zhi-Ye LinAkeso Biopharma Co, Ltd, Zhongshan, China.ORCID https://orcid.org/0009-0000-0197-3937
Chun-Li ZhangDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-5852-8639
Meng-Die LiDepartment of Medical Record Management, the Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China.ORCID https://orcid.org/0009-0002-0435-0940
Ning-Jun RenDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0000-0003-3339-0511
Zhi-Zhong LuoDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0009-3157-2857
Rui-Fei ZuoDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0001-2904-3413
Fu-Chuan XiongDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0002-4879-3137
Yu-Tong KangDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0009-9596-7057
Xiu-Rong LinDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0005-8592-2825
Chun HaoDepartment of Medical Statistics, School of Public Health, Sun-Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-9881-6504

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWellTest, a digital health platform designed to facilitate HIV voluntary counseling and testing (VCT) services, has been widely implemented in Guangzhou, China. However, the extent of its use by primary health care centers (PHCs) and the facility-level associations between WellTest use and HIV testing outcomes remain unclear.

objectiveThis study aimed to assess the use of WellTest at the facility level across PHCs in urban Guangzhou, China, and to explore the associations between WellTest use and HIV testing outcomes.

methodsWe obtained data on VCT services visits from the National HIV/AIDS Prevention and Control Information System and the WellTest platform between January 1 and December 31, 2022. Two facility-level HIV testing outcomes, the HIV testing volume and HIV positivity rate, were calculated for each PHC. A structured questionnaire collected data on the PHCs' characteristics. Multilevel negative binomial regression and zero-inflated gamma models were used to examine associations between WellTest use and 2 HIV testing outcomes at the facility level.

resultsA total of 81 PHCs across 5 urban districts in Guangzhou were included. WellTest was used for 7997 active consultations and 7969 HIV tests that resulted in 157 newly diagnosed HIV cases, for an overall positivity rate of 2.0%, during 2022. The median share of clients booking via WellTest was 71% (IQR 34%-98%), and 81% (66/81) of PHCs offered online slots on all service days without mandates. PHCs that actively confirmed appointments had significantly lower HIV testing volumes compared with those that took no actions after clients scheduled appointments (incidence rate ratio 0.75, 95% CI 0.58-0.97; P=.03) but exhibited higher HIV positivity rates (β=.39, 95% CI 0.02-0.76; P=.04). Additionally, PHCs where ≥50% of clients used WellTest to schedule appointments showed higher HIV positivity rates than those with lower uptake (β=1.11; 95% CI 0.82-1.40; P<.001).

conclusionsWellTest showed substantial use among VCT clients and providers in urban Guangzhou PHCs, with greater use of digital appointments and counselor follow-up linked to increased HIV positivity rates. Strategies to optimize institutional adoption may help address stigma-related barriers, strengthen engagement in HIV testing, and support HIV case finding in primary health care settings.

Indexed as

CounselingHIV InfectionsHIV TestingPrimary Health CareAdultChinaCross-Sectional StudiesDigital HealthFemaleHumansMaleMiddle AgedUrban Populationdigital healthfactor analysishealth serviceHIV testingvoluntary counseling and testing

Identifiers

PMID41996173
PMCPMC13135155

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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.