A psychosocial network approach studying biomedical HIV prevention uptake between 2017 and 2019

Abstract

Biomedical HIV-prevention strategies (BmPS) among men who have sex with men (MSM), such as pre-exposure prophylaxis (PrEP) and viral load sorting (VLS), are essential but relatively new and their uptake gradual. Using an extension of the causal attitude network approach, we investigated which beliefs are related to uptake of PrEP and VLS at each time-point. We included 632 HIV-negative MSM from the Amsterdam Cohort Studies from four data-waves between 2017 and 2019. We estimated weighted, undirected networks for each time-point, where we included pairwise interactions of PrEP and VLS uptake and related beliefs. PrEP use increased from 10 to 31% (p < 0.001), while VLS was reported by 7-10% at each time-point. Uptake of both BmPS was directly related to the perceived positive impact of the strategy on one's quality of sex life and perceived supportive social norms. Overall network structure differed between time points, specifically in regard to PrEP. At earlier time points, perceptions of efficacy and affordability played an important role for PrEP uptake, while more recently social and health-related concerns became increasingly important.The network structure differed across data-waves, suggesting specific time changes in uptake motives. These findings may be used in communication to increase prevention uptake.

Figure 1

Example of a simple undirected weighted network with 3 nodes (represented by circles) and 2 edges (represented by lines). The magnitude of the connection is indicated by edge width. A blue line represents a positive and a red line represents a negative association.

Figure 2

Flowchart of the included ACS study participants per time point. ACS Amsterdam Cohort Study on HIV, PrEP pre-exposure prophylaxis, VLS viral load sorting, HIV Human Immunodeficiency Virus, MSM men who have sex with men.

Figure 3

Estimated networks of PrEP use, VLS and related factors at each time point. Nodes represent the measured factors and edges represent the bidirectional relations. Positive relations are displayed with blue edges and negative associations with red edges. Stronger relations are displayed with thicker edges and greater color intensity. Edge weights below. 15 are omitted to increase clarity. For the relations between continuous nodes, edges can be interpreted as partial correlations. For relations with the binary nodes (PrEP, VLS and sp), a positive relation indicates that increasing the node results in a higher probability of outcome 1 of the factor (PrEP = 1: used PrEP in past 6 months, VLS = 1: reported VLS in past 6 months; sp = 1: reported a steady partner in the past 6 months). The colored groups indicated clusters of higher interconnectedness (i.e., communities). PrEP pre-exposure prophylaxis, VLS viral load sorting, HIV Human Immunodeficiency Virus.

Figure 4

Centrality plot of the estimated networks of PrEP use, VLS and related factors at each time point. Strength indicates the influence of a node on the network as it is based on the sum of the absolute edge values that are connected to a node. A high score indicates that changing the specific node is more likely to have a profound effect on the network as a whole due to its relation with many other nodes. VLS viral load sorting, PrEP pre-exposure prophylaxis, HIV Human Immunodeficiency Virus.

Figure 5

Significant differences in edge weights between time points (T1 vs. T4; T1 vs. T2; T2 vs. T3; T3 vs. T4) obtained from the network comparison test (NCT). The magnitude of the edge differences is indicated by edge width. A blue edge indicates that the relation (based on edge weights) is significantly weaker, absent or more negative at the later time point compared to the earlier time point. A red edge indicates that the relation is significantly weaker, absent or more negative at the earlier time point. Edge weights below. 15 are omitted to increase clarity. Note that the NCT compares networks of either continuous or binary variables, and not from mixed networks using mgm. The results of the NCT (i.e. significant differences between edges) are therefore based on the networks estimated for continuous variables (with EBICglasso). The NCT graph displays those edges that differ significantly according to the results of the NCT with the displayed difference in strength based on the edge weight in the mgm network. VLS viral load sorting, PrEP pre-exposure prophylaxis, HIV Human Immunodeficiency Virus.