Evidence map›Paper›PMID 29728344›Full record

ArticleJMIR public health and surveillance2018

Trends in HIV Terminology: Text Mining and Data Visualization Assessment of International AIDS Conference Abstracts Over 25 Years.

Nicole Dancy-Scott, Gale A Dutcher, Alla Keselman, Colette Hochstein, Christina Copty, Diane Ben-Senia, Sampada Rajan, Maria Guadalupe Asencio, Jason Jongwon Choi

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Tracking Knowledge Evolution Based on the Terminology Dynamics in 4P-Medicine.International journal of environmental research and public health · 2020
    Article
  4. Article
  5. 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

9 authors.

Nicole Dancy-Scott *Division of Specialized Information Services, National Library of Medicine, Bethesda, MD, United States.ORCID http://orcid.org/0000-0001-6949-991X
Gale A Dutcher *Division of Specialized Information Services, National Library of Medicine, Bethesda, MD, United States.ORCID http://orcid.org/0000-0002-3829-9357
Alla Keselman *Division of Specialized Information Services, National Library of Medicine, Bethesda, MD, United States.ORCID http://orcid.org/0000-0002-3267-761X
Colette Hochstein *Division of Specialized Information Services, National Library of Medicine, Bethesda, MD, United States.ORCID http://orcid.org/0000-0001-7041-3167
Christina Copty *ICF, Fairfax, VA, United States.ORCID http://orcid.org/0000-0002-7078-7422
Diane Ben-Senia *ICF, Fairfax, VA, United States.ORCID http://orcid.org/0000-0002-0644-6826
Sampada Rajan *ICF, Fairfax, VA, United States.ORCID http://orcid.org/0000-0003-2705-7632
Maria Guadalupe Asencio *ICF, Fairfax, VA, United States.ORCID http://orcid.org/0000-0002-3744-0144
Jason Jongwon Choi *ICF, Fairfax, VA, United States.ORCID http://orcid.org/0000-0003-3385-3598

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
6 · The paper itself

Abstract

backgroundThe language encompassing health conditions can also influence behaviors that affect health outcomes. Few published quantitative studies have been conducted that evaluate HIV-related terminology changes over time. To expand this research, this study included an analysis of a dataset of abstracts presented at the International AIDS Conference (IAC) from 1989 to 2014. These abstracts reflect the global response to HIV over 25 years. Two powerful methodologies were used to evaluate the dataset: text mining to convert the unstructured information into structured data for analysis and data visualization to represent the data visually to assess trends.

objectiveThe purpose of this project was to evaluate the evolving use of HIV-related language in abstracts presented at the IAC from 1989 to 2014.

methodsOver 80,000 abstracts were obtained from the International AIDS Society and imported into a Microsoft SQL Server database for data processing and text mining analyses. A text mining module within the KNIME Analytics Platform, an open source software, was then used to mine the partially processed data to create a terminology corpus of key HIV terms. Subject matter experts grouped the terms into categories. Tableau, a data visualization software, was used to visualize the frequency metrics associated with the terms as line graphs and word clouds. The visualized dashboards were reviewed to discern changes in terminology use across IAC years.

resultsThe major findings identify trends in HIV-related terminology over 25 years. The term "AIDS epidemic" was dominantly used from 1989 to 1991 and then declined in use. In contrast, use of the term "HIV epidemic" increased through 2014. Beginning in the mid-1990s, the term "treatment experienced" appeared with increasing frequency in the abstracts. Use of terms identifying individuals as "carriers or victims" of HIV rarely appeared after 2008. Use of the terms "HIV positive" and "HIV infected" peaked in the early-1990s and then declined in use. The terms "men who have sex with men" and "MSM" were rarely used until 1994; subsequently, use of these terms increased through 2014. The term "sex worker" steadily increased in frequency throughout conference years, whereas the term "prostitute" decreased over time.

conclusionsThe results of this study highlight changes in HIV terminology use over 25 years, including the addition, disappearance, and changing use of terms that reflect advances in HIV research and medical practice and destigmatization of the disease. Coupled with findings from related quantitative research, HIV-related terminology recommendations based on results of this study are included. Adoption of these recommendations will further efforts to use less stigmatizing language and facilitate effective communication between health professionals and people affected by HIV.

Indexed as

acquired immunodeficiency syndromedata mininghistoryHIV infectionsterminology

Identifiers

PMID29728344
PMCPMC5960041

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.