Evidence map›Paper›PMID 29196281›Full record

ArticleJournal of medical Internet research2017

The Use of Avatar Counseling for HIV/AIDS Health Education: The Examination of Self-Identity in Avatar Preferences.

Shantrel Canidate, Mark Hart

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
23.4field-weighted citation impact, top 1% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Ocular manifestations of people living with HIV in Tunisia.Southern African journal of HIV medicine · 2021
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

2 authors at 1 institution in 1 country.

Shantrel CanidateSocial and Behavioral Sciences Program, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States.ORCID 0000-0001-6963-5408
Mark HartSocial and Behavioral Sciences Program, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States.ORCID 0000-0001-5253-5873
University of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe number of adults using the Internet to obtain health information is on the rise. An estimated 66% of the adults reportedly use the Internet to obtain health information related to a specific disease (ie, human immunodeficiency virus and acquired immunodeficiency syndrome, HIV/AIDS). Previous research has demonstrated that health information seekers use the Internet to seek answers to stigma-laden questions from health avatars.

objectiveThe objective of this study was to identify patterns in the choice of avatar among health information seekers (patients or public health workers) using the Internet to obtain HIV/AIDS information and to describe the demographic characteristics (age, gender, and ethnicity) of health information seekers to determine whether they preferred an avatar that was similar to their own gender and ethnicity.

methodsThe Rural South Public Health Training Center (RSPHTC) partnered with the New York State Department of Health to create the HIV/AIDS Avatar project. The avatar project was created to serve as an educational resource for public health workers by providing relevant and accurate information about HIV/AIDS. First, the user was instructed to choose one of the 8 avatars that voiced responses to 100 common questions and answers about HIV/AIDS. Next, the website gave users the option to complete a brief 3-question demographic survey. Finally, the demographic characteristics of each user were compared with the chosen avatar to determine whether they preferred an avatar that was similar to their own gender and ethnicity.

resultsThe avatar project website was loaded with 800 videos that included the answers to the top 100 questions about HIV/AIDS voiced by 8 avatars. A total of 1119 Web-based health information seekers completed the demographic survey upon accessing the website. Of these, 55.14% (617/1119) users were female. A total of 49.96% (559/1119) users were aged between 30 and 49 years. The ethnicity of the user and the avatar was found to have the strongest connection. All the users choose the female avatar matching their own ethnicity, followed by the male avatar. Additionally, the white female avatar was chosen the most by all users regardless of the age group or gender.

conclusionsWeb-based health information seekers using the Internet to access medical research information may feel more comfortable receiving the answers to HIV stigma-laden questions from avatars, rather than receiving information directly from a health care provider. Additionally, providers seeking to utilize avatars to deliver interventions in health care settings may benefit from offering individuals choices in how they receive health information. Having the ability to choose whom you seek information from may lead to an increase in knowledge and awareness and could motivate HIV-positive individuals to seek care.

Indexed as

Acquired Immunodeficiency SyndromeHealth EducationHIV InfectionsSelf ConceptAdultDirective CounselingEthnicityFemaleHumansInternetMaleMiddle AgedMotivationNew YorkPublic HealthRural Populationavatarsdistance educationlearningtechnology

Identifiers

PMID29196281
PMCPMC5732328
OpenAlexW2775604912

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.