Readiness for Use of HIV Preexposure Prophylaxis Among Men Who Have Sex With Men in Malawi: Qualitative Focus Group and Interview Study
Bibliographic record
Abstract
BACKGROUND: Men who have sex with men (MSM) are a key group for HIV interventions in Malawi considering their high HIV prevalence (17.5% compared to 8.4% among men in the general population). The use of oral preexposure prophylaxis (PrEP) presents a new opportunity for MSM to be protected. We present the findings from a qualitative assessment designed to assess awareness of and willingness and barriers to using PrEP among MSM in Malawi. OBJECTIVE: The 3 main objectives of this assessment were to determine: (1) awareness of PrEP, (2) factors that influence willingness to use PrEP, and (3) potential barriers to PrEP use and adherence among MSM in order to guide the design and implementation of a PrEP program in Malawi. METHODS: Ahead of the introduction of PrEP in Malawi, a qualitative study using in-depth interviews (IDIs) and focus group discussions (FGDs) was conducted in October 2018 in Blantyre, Lilongwe, and rural districts of Mzimba North and Mangochi. With support of members of the population, study participants were purposively recruited from 4 MSM-friendly drop-in centers where MSM receive a range of health services to ensure representativeness across sites and age. Participants were asked what they had heard about PrEP, their willingness to use PrEP, their barriers to PrEP use, and their preferences for service delivery. The data were analyzed using a thematic content analysis framework that was predetermined in line with objectives. RESULTS: A total of 109 MSM were interviewed-13 through IDIs and 96 through FGDs. Most participants were aware of PrEP as a new HIV intervention but had limited knowledge related to its use. However, the majority were willing to use it and were looking forward to having access to it. IDI participants indicated that they will be more willing to take PrEP if the dosing frequency were appropriate and MSM were involved in information giving and distribution of the drug. FGD participants emphasized that places of distribution and characteristics of the service provider are the key factors that will affect use. Knowing the benefits of PrEP emerged as a key theme in both the IDIs and FGDs. Participants highlighted barriers that would hinder them from taking PrEP such as side effects which were cited in IDIs and FGDs. Key factors from FGDs include cost, fear of being outed, drug stockouts, fear of being known as MSMs by wives, and lack of relevant information. FGDs cited stigma from health care workers, forgetfulness, and community associated factors. CONCLUSIONS: Despite having inadequate knowledge about PrEP, study participants were largely willing to use PrEP if available. Programs should include an effective information, education, and communication component around their preferences and provide PrEP in MSM-friendly sites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".