Evidence map›Paper›PMID 32130147›Full record

Observational studyJMIR mHealth and uHealth2020

Protecting Men Who Have Sex With Men From HIV Infection With an mHealth App for Partner Notification: Observational Study.

Xiangyu Yan, Zuhong Lu, Bo Zhang, Yongjie Li, Wenjun Tang, Lingling Zhang, Zhongwei Jia

Registry-linked trialOpen access · goldAbstract readObservational Study
In one paragraph

Observational study in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04349748 (The Effect of Providing mHealth Intervention of Partner Notification to Protect MSM From HIV and Sexually Transmitted Diseases Infection), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 26% 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.

NCT04349748 naunknown statusnot on this map

The Effect of Providing mHealth Intervention of Partner Notification to Protect MSM From HIV and Sexually Transmitted Diseases Infection: a Pragmatic Stepped Wedge Cluster Randomized Controlled Trial

TypeinterventionalSponsorNational Institute on Drug Dependence, ChinaRan2020 to 2023Enrolled6,172ConditionsHIV/AIDS, Sexually Transmitted Diseases, PreventionArmsHealth education, and regular HIV and STDs testing prompting service, Health status inquiry through app (partner notification)
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 19 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Xiangyu YanSchool of Public Health, Peking University, Beijing, China.ORCID 0000-0002-1496-0358
Zuhong LuBiomedical Engineering, Southeast University, Jiangsu Province, China.ORCID 0000-0003-3332-2615
Bo ZhangSchool of Public Health, Peking University, Beijing, China.ORCID 0000-0003-2244-5388
Yongjie LiSchool of Public Health, Peking University, Beijing, China.ORCID 0000-0003-4811-3947
Wenjun TangSchool of Public Health, Peking University, Beijing, China.ORCID 0000-0002-2656-5873
Lingling ZhangCollege of Nursing and Health Sciences, University of Massachusetts Boston, Boston, MA, United States.ORCID 0000-0002-9988-6512
Zhongwei JiaNational Institute on Drug Dependence, Peking University, Beijing, China.ORCID 0000-0002-5362-7339
Peking University · CNSoutheast University · CNUniversity of Massachusetts Boston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional partner notification methods have been implemented for HIV-infected patients, as well as HIV treatment, in order to identify people at risk of HIV infection, especially men who have sex with men (MSM), since they are more likely to have casual sex partners. These traditional methods have some limitations.

objectiveOur study focused on developing an mHealth app to improve partner notification in practice for MSM; the study then focused on evaluating the effects of the app.

methodsWe developed an mHealth app with different modules using Java and HTML5 and tested it in an MSM community to prevent HIV transmission. The HIV incidence stratified by different follow-up periods were calculated. Poisson regression and social networks were used to estimate the risk ratios and to identify the connection among MSM, respectively.

resultsIn addition to the partner notification module, which is the kernel of the app, we developed a test result self-query module to enable MSM to get their approved test results in a timely manner, a prompt and warning module to alert users to protect themselves from high-risk conditions, and a health education module to teach users more skills regarding HIV/AIDS prevention. Over a 1-year duration, a total of 3186 MSM used the app, of which 678 had at least two HIV test results since becoming app users; they were included in the final analysis. Among 678 users, a total of 6473 self-queries and 623 partner notifications were recorded, which identified 180 social networks of MSM app users. Those who used the partner notification function were more likely to have self-queries (P<.001). The 678 MSM app users covered 296.47 person-years and contributed to 20 HIV seroconversions; the cumulative HIV infection incidence was estimated as 6.75 per 100 person-years (95% CI 4.38-10.01). We found that the longer the app was used, the lower the HIV incidence (>5 months vs ≤5 months: 2.22 per 100 person-years vs 6.99 per 100 person-years; risk ratio 0.32, 95% CI 0.12- 0.87).

conclusionsThe app developed in this study is consistent with the World Health Organization's sensitivity and confidentiality recommendations; it has the potential to reduce the risk of HIV infection among MSM.

Indexed as

Contact TracingHIV InfectionsMobile ApplicationsTelemedicineAdultHomosexuality, MaleHumansMaleSexual and Gender MinoritiesYoung Adultmen who have sex with menmobile phone apppartner notificationsexual network

Identifiers

PMID32130147
PMCPMC7057823
OpenAlexW3008640862

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.