Abstract

Deciding to test for HIV is necessary for receiving HIV treatment and care among those who are HIV-positive. This article presents a systematic review of quantitative studies on relationships between psychological (cognitive and affective) variables and HIV testing. Sixty two studies were included (fifty six cross sectional). Most measured lifetime testing. HIV knowledge, risk perception and stigma were the most commonly measured psychological variables. Meta-analysis was carried out on the relationships between HIV knowledge and testing, and HIV risk perception and testing. Both relationships were positive and significant, representing small effects (HIV knowledge, d = 0.22, 95 % CI 0.14–0.31, p < 0.001; HIV risk perception, OR 1.47, 95 % CI 1.26–1.67, p < 0.001). Other variables with a majority of studies showing a relationship with HIV testing included: perceived testing benefits, testing fear, perceived behavioural control/self-efficacy, knowledge of testing sites, prejudiced attitudes towards people living with HIV, and knowing someone with HIV. Research and practice implications are outlined.

Highlights

  • HIV testing is a prerequisite for receiving HIV treatment and care among those who are HIV-positive

  • This review aimed to synthesise and analyse data from studies investigating the relationship between psychological variables and HIV testing

  • Many HIV-testing related variables included in studies are featured in health behaviour models [102,103,104]

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Summary

Introduction

HIV testing is a prerequisite for receiving HIV treatment and care among those who are HIV-positive. Diagnosis and access to treatment is associated with a reduced likelihood of onward transmission [1], better response to antiretroviral treatment (ART), and reduced mortality and morbidity [2]. Many people living with HIV are unaware of their status. The World Health Organisation (WHO) estimates that less than half of those infected with HIV have been diagnosed [3]. The growing availability of ART reinforces the need to scale up testing interventions. To develop interventions that are effective in increasing uptake, it is crucial to study the factors that may influence the decision to test [4]

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