Evidence map›Paper›PMID 39972444›Full record

SynthesisBMC public health2025

Acceptability of self-sampling and self-testing for infections: a rapid systematic review on public users' views.

Aleksandra J Borek, Caity Roleston, Runa Lazzarino, Mineli Cooray, Gail Hayward, Nia Roberts, Edward Blandford, Tom Fowler, Sarah Tonkin-Crine

Abstract readSystematic Review
In one paragraph

Synthesis in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

9 authors.

Aleksandra J BorekNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK. aborek@gmail.com.
Caity RolestonNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Runa LazzarinoNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Mineli CoorayNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Gail HaywardNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Nia RobertsBodleian Health Care Libraries, University of Oxford, Oxford, UK.
Edward BlandfordUK Health Security Agency, London, UK.
Tom FowlerUK Health Security Agency, London, UK.
Sarah Tonkin-CrineNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-sampling and self-testing have been increasingly used for sexually transmitted infections (STIs) and quickly became widespread during the COVID-19 pandemic. User acceptability, preferences, and experiences are important factors affecting self-sampling/self-testing uptake. Understanding these factors is key to managing infections and planning responses to health emergencies. This review aimed to identify user views and experiences related to the acceptability, usability, motivations and preferences for self-sampling/self-testing for infections.

methodsWe conducted a rapid systematic review. We searched Medline, EMBASE, PsycINFO, CINAHL, and Web of Science, limiting records to those published in English between 2014 and 2023. We also searched manually for additional peer-reviewed and grey literature. We included reports of public users' views on self-sampling/self-testing for any symptomatic and asymptomatic infections (except human papillomavirus) with qualitative, mixed-methods or survey data relevant to the review aim. Data were extracted into tables and qualitative findings were coded in NVivo. We synthesised data narratively.

resultsWe identified 194 eligible reports, including 64 from Europe (which we prioritised for detailed synthesis) and 130 from outside of Europe. In Europe, the studied infections were respiratory (n = 42, including 37 for COVID-19), STIs/HIV/genital infections (n = 20), and hepatitis C (n = 2). Findings indicate that users found self-sampling/self-testing acceptable across infection/sampling types, populations, settings, and countries. Users wanted self-sampling/self-testing to help determine infection status and protect others. The main benefits were privacy and convenience, helping reduce the potential stigma of STIs/HIV/genital infections, and (for COVID-19) informing behaviour (e.g., socialising, self-isolating) and contributing to research. Easier to perform and less invasive sampling approaches were more acceptable. However, some participants reported challenges to self-sampling/self-testing, such as not understanding instructions, pain/discomfort in collecting samples, and lack of confidence in interpreting results.

conclusionsThis review synthesised evidence on the acceptability of SS/ST and factors affecting it across different infections, sampling approaches, settings, and populations. Evidence shows that most people with experience of self-sampling/self-testing found it acceptable and were willing to accept some discomfort in favour of several perceived benefits. This amenability to self-sampling/self-testing could be leveraged for diagnosing infections and preventing transmission. It can be used to support the viability of new models of clinical care and pandemic preparedness.

trial registrationThe review was pre-registered on PROSPERO (ref. CRD42024507656 ).

Indexed as

COVID-19Patient Acceptance of Health CareSelf-TestingSexually Transmitted DiseasesHumansDiagnosticsInfectionsInfectious diseasesPandemic preparednessPublic healthQualitative synthesisSelf-samplingSelf-testingSystematic reviewTesting at home

Identifiers

PMID39972444
PMCPMC11841015

What OpenQuestion holds

Textmetadata
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.