Evidence map›Paper›PMID 34430835›Full record

ArticleEClinicalMedicine2021

HIV self-testing with digital supports as the new paradigm: A systematic review of global evidence (2010-2021).

Madison McGuire, Anna de Waal, Angela Karellis, Ricky Janssen, Nora Engel, Rangarajan Sampath, Sergio Carmona, Alice Anne Zwerling, Marta Fernandez Suarez, Nitika Pant Pai

Abstract read
In one paragraph

Article in EClinicalMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 6 pooled it
–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

64 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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4 more citing papers are in PubMed but not listed here.

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

10 authors.

Madison McGuireDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Ave W, Montreal, QC H3A 1A2, Canada.
Anna de WaalDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Ave W, Montreal, QC H3A 1A2, Canada.
Angela KarellisThe Research Institute of the McGill University Health Centre, 1001 Decarie Blvd, 5252 blvd de Maisonneuve W., Montreal, QC H4A 3J1, Canada.
Ricky JanssenDepartment of Health, Ethics and Society, Maastricht University, Postbus 616 6200 MD, Maastricht, the Netherland.
Nora EngelDepartment of Health, Ethics and Society, Maastricht University, Postbus 616 6200 MD, Maastricht, the Netherland.
Rangarajan SampathFoundation for Innovative New Diagnostics, Chemin des Mines 9, Geneva 1202, Switzerland.
Sergio CarmonaFoundation for Innovative New Diagnostics, Chemin des Mines 9, Geneva 1202, Switzerland.
Alice Anne ZwerlingSchool of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON K1G 5Z, Canada.
Marta Fernandez SuarezFoundation for Innovative New Diagnostics, Chemin des Mines 9, Geneva 1202, Switzerland.
Nitika Pant PaiThe Research Institute of the McGill University Health Centre, 1001 Decarie Blvd, 5252 blvd de Maisonneuve W., Montreal, QC H4A 3J1, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHIV self-testing (HIVST) is recommended by the WHO as an innovative strategy to reach UNAIDS targets to end HIV by 2030. HIVST with digital supports is defined as the use of digital interventions (e.g., website-based, social media, mobile HIVST applications (apps), text messaging (SMS), digital vending machines (digital VMs)) to improve the efficiency and impact of HIVST. HIVST deployment and integration in health services is an emerging priority. We conducted a systematic review aiming to close the gap in evidence that summarizes the impact of digitally supported HIVST and to inform policy recommendations.

methodsWe searched PubMed and Embase for articles and abstracts on HIVST with digital supports published during the period February 1st, 2010 to June 15th, 2021, following Cochrane guidelines and PRISMA methodology. We assessed feasibility, acceptability, preference, and impact outcomes across all populations and study designs. Metrics reported were willingness to use HIVST, preferences for HIVST delivery, proportion of first-time testers, HIVST uptake, HIVST kit return rate, and linkage to care. Heterogeneity of the interventions and reported metrics precluded us from conducting a meta-analysis.

findings46 studies were narratively synthesized, of which 72% were observational and 28% were RCTs. Half of all studies (54%, 25/46) assessed web-based innovations (e.g., study websites, videos, chatbots), followed by social media (26%, 12/46), HIVST-specific apps (7%, 3/46), SMS (9%, 4/46), and digital VMs (4%, 2/46). Web-based innovations were found to be acceptable (77-97%), preferred over in-person and hybrid options by more first-time testers (47-48%), highly feasible (93-95%), and were overall effective in supporting linkage to care (53-100%). Social media and app-based innovations also had high acceptability (87-95%) and linkage to care proportions (80-100%). SMS innovations increased kit return rates (54-94%) and HIVST uptake among hard-to-reach groups. Finally, digital VMs were highly acceptable (54-93%), and HIVST uptake was six times greater when using digital VMs compared to distribution by community workers.

interpretationHIVST with digital supports was deemed feasible, acceptable, preferable, and was shown to increase uptake, engage first-time testers and hard-to-reach populations, and successfully link participants to treatment. Findings pave the way for greater use of HIVST interventions with digital supports globally.

Indexed as

DigitalHIVInterventionMhealthOnlineSelf-testing

Identifiers

PMID34430835
PMCPMC8367787

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.