Perceptions and experiences of internet-based testing for sexually transmitted infections: Systematic Review and Synthesis of Qualitative Research.

BACKGROUND Internet-based testing for sexually transmitted infections (STIs) allows asymptomatic individuals to order a self-sampling kit online and receive their results electronically, reducing the need to attend a clinic unless for treatment. This approach has become increasingly common, however there is evidence that barriers exist to accessing it, particularly among some high-risk populations. We review the qualitative evidence on this topic, as qualitative research is well-placed to identify the complex influences which relate to accessing testing. OBJECTIVE To explore perceptions and experiences of internet-based testing for STIs among users and potential users. METHODS Searches were run through five electronic databases (CINAHL, EMBASE, MEDLINE, PsychINFO and Web of Science) to identify peer-reviewed studies published between 2005 and 2018. Search terms were drawn from four categories: STIs; testing or screening; digital health; and qualitative methods. Included studies were conducted in high-income countries and explored patient perceptions or experiences of internet-based testing, and data underwent thematic synthesis. RESULTS A total of 11 studies were included in the review, from 1735 identified in the initial search. The synthesis identified that internet-based testing is viewed widely as being acceptable, and is preferred over clinic testing by many individuals due to perceived convenience and anonymity. However, a number of studies identified concerns relating to test accuracy and lack of communication with practitioners, particularly when receiving results. There was a lack of consensus on preferred media for results delivery, although convenience and confidentiality were again strong influencing factors. The majority of included studies were limited by the fact that they researched hypothetical services. CONCLUSIONS Internet-based testing providers may benefit from emphasising its comparative convenience and privacy compared to face-to-face testing in order to improve uptake, as well as alleviating concerns about the self-sampling process. There is a clear need for further research exploring in-depth the perceptions and experiences of people who have accessed internet-based testing, and for research on internet-based testing explicitly gathering the views of populations which are at high-risk of STIs. CLINICALTRIA

Leveraging eQTLs to identify individual-level tissue of interest for a complex trait.

Genetic predisposition for complex traits often acts through multiple tissues at different time points during development. As a simple example, the genetic predisposition for obesity could be manifested either through inherited variants that control metabolism through regulation of genes expressed in the brain, or that control fat storage through dysregulation of genes expressed in adipose tissue, or both. Here we describe a statistical approach that leverages tissue-specific expression quantitative trait loci (eQTLs) corresponding to tissue-specific genes to prioritize a relevant tissue underlying the genetic predisposition of a given individual for a complex trait. Unlike existing approaches that prioritize relevant tissues for the trait in the population, our approach probabilistically quantifies the tissue-wise genetic contribution to the trait for a given individual. We hypothesize that for a subgroup of individuals the genetic contribution to the trait can be mediated primarily through a specific tissue. Through simulations using the UK Biobank, we show that our approach can predict the relevant tissue accurately and can cluster individuals according to their tissue-specific genetic architecture. We analyze body mass index (BMI) and waist to hip ratio adjusted for BMI (WHRadjBMI) in the UK Biobank to identify subgroups of individuals whose genetic predisposition act primarily through brain versus adipose tissue, and adipose versus muscle tissue, respectively. Notably, we find that these individuals have specific phenotypic features beyond BMI and WHRadjBMI that distinguish them from random individuals in the data, suggesting biological effects of tissue-specific genetic contribution for these traits