Evidence map›Paper›PMID 33914824›Full record

ArticlePloS one2021

HIV Pre-exposure Prophylaxis (PrEP): Knowledge, attitudes and counseling practices among physicians in Germany - A cross-sectional survey.

Mary Katherine Sammons, Matthew Gaskins, Frank Kutscha, Alexander Nast, Ricardo Niklas Werner

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 47% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
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  3. Article
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

5 authors at 1 institution in 1 country.

Mary Katherine SammonsDivision of Evidence Based Medicine (dEBM), Department of Dermatology, Venereology and Allergology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0002-3338-3891
Matthew GaskinsDivision of Evidence Based Medicine (dEBM), Department of Dermatology, Venereology and Allergology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0001-6436-2703
Frank KutschaDivision of Evidence Based Medicine (dEBM), Department of Dermatology, Venereology and Allergology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Alexander NastDivision of Evidence Based Medicine (dEBM), Department of Dermatology, Venereology and Allergology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Ricardo Niklas WernerDivision of Evidence Based Medicine (dEBM), Department of Dermatology, Venereology and Allergology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.ORCID 0000-0003-3209-1392
Humboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGerman statutory health insurance began covering the costs associated with HIV PrEP in September 2019; however, to bill for PrEP services, physicians in Germany must either be certified as HIV-specialists according to a nationwide quality assurance agreement, or, if they are non-HIV-specialists, have completed substantial further training in HIV/PrEP care. Given the insufficient implementation of PrEP, the aim of our study was to explore the potential to increase the number of non-HIV-specialists providing PrEP-related services.

methodsWe conducted an anonymous survey among a random sample of internists, general practitioners, dermatologists and urologists throughout Germany using a self-developed questionnaire. We calculated a knowledge score and an attitudes score from individual items in these two domains. Both scores ranged from 0-20, with high values representing good knowledge or positive attitudes. We also asked participants about the proportion of PrEP advice they provided proactively to men who have sex with men (MSM) and trans-persons who met the criteria to be offered PrEP.

results154 physicians completed the questionnaire. Self-assessed knowledge among HIV-specialists was greater than among non-HIV-specialists [Median knowledge score: 20.0 (IQR = 0.0) vs. 4.0 (IQR = 11.0), p<0.001]. Likewise, attitudes towards PrEP were more positive among HIV-specialists than non-HIV-specialists [Median attitudes score: 18.0 (IQR = 3.0) vs. 13.0 (IQR = 5.25), p<0.001]. The proportion of proactive advice on PrEP provided to at-risk MSM and trans-persons by HIV-specialists [Median: 30.0% (IQR = 63.5%)] was higher than that provided by non-HIV-specialists [Median: 0.0% (IQR = 11.3%), p<0.001]. However, the results of our multiple regression suggest the only independent predictor of proactive PrEP advice was the knowledge score, and not whether physicians were HIV-specialists or non-HIV-specialists.

conclusionsThese findings point to opportunities to improve PrEP implementation in individuals at risk of acquiring HIV. Targeted training, particularly for non-HIV-specialists, and the provision of patient-centered information material could help improve care, especially in rural areas.

Indexed as

AdultAgedAged, 80 and overClinical CompetenceCounselingCross-Sectional StudiesFemaleGermanyHealth Knowledge, Attitudes, PracticeHIV InfectionsHomosexuality, MaleHumansMaleMiddle AgedPhysiciansPre-Exposure Prophylaxis

Identifiers

PMID33914824
PMCPMC8084214
OpenAlexW3158988584

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.