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Behavioral Response to HIV/AIDS Prevention Messages Among Students in Selected Universities of Amhara Region, Northwest Ethiopia: An Extended Parallel Process Model

Authors Afenigus AD, Mulugeta H, Tsehay B, Gedfew M, Ayenew T, Getnet A

Received 5 November 2020

Accepted for publication 30 December 2020

Published 2 February 2021 Volume 2021:13 Pages 115—124

DOI https://doi.org/10.2147/HIV.S288297

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Bassel Sawaya


Abebe Dilie Afenigus,1 Henok Mulugeta,1 Binalfew Tsehay,2 Mihretie Gedfew,1 Temesgen Ayenew,1 Asmamaw Getnet1

1Department of Nursing, College of Health Sciences, Debre Markos University, Debre Markos, Gojjam, Ethiopia; 2Department of Biomedical Sciences, School of Medicine, Debre Markos University, Debre Markos, Ethiopia

Correspondence: Abebe Dilie Afenigus
Department of Nursing, College of Health Sciences, Debre Markos University, PO Box 269, Debre Markos, Gojjam, Ethiopia
Email abexdmu@gmail.com

Background: HIV/AIDS is a global pandemic. Sub-Saharan Africa accounts for two-thirds of the newly HIV-infected cases in the world. Similarly, the prevalence of HIV infections among Ethiopian university students has also increased as HIV prevention was not sufficiently prioritized. In order to decrease the surge of the HIV pandemic, prevention messages that encourage individuals to reduce sexual and risk behaviors still remain a key intervention strategy. Besides this, the behavioral response to HIV prevention messages among Ethiopian universities is not well studied.
Objective: To assess students’ behavioral response to HIV/AIDS prevention messages in selected universities of the Amhara region using an extended parallel process model (EPPM), in 2019.
Methods: A facility-based cross-sectional study was employed among 423 eligible students from January to February, 2019 using a stratified sampling technique. The dependent variable is response to HIV/AIDS prevention messages (danger control and fear control) which is addressed by EPPM. The model explains the components of threat (perceived susceptibility and perceived severity) and efficacy (response efficacy and self-efficacy). Subtracting wings of threat component score from efficacy wings score gives the critical value. If the critical value had positive scores, it showed responses of danger control; if the critical value was negative, it showed response of fear control. A logistic regression model was fitted to assess the association between the dependent and independent variables.
Results: The response rate of this study was 94.6%. Among 400 respondents, 263 (65.8%; 95%CI: 61– 70) of them were in the danger control response whereas 137 (34.2%; 95%CI: 30– 39) were in fear control response. Moreover, 200 (50%) of the participants had adequate knowledge and 180 (45%) had a favorable attitude towards HIV/AIDS prevention messages. Danger control response for HIV prevention messages was higher among first-year students (AOR=5.5; 95%CI: 1.5– 19) and third-year students (AOR=3.9; 95%CI: 2– 14) compared with fifth-year students. Similarly, those students who reside on the campus were 60% times less likely to develop danger control when compared with students who live with their family (AOR=0.4; 95%CI: 0.2– 0.9). Besides this, students who had adequate knowledge (AOR=2.6; 95%CI: 1.5– 4.5) and students who receive fear-inducer messages (AOR=4.5; 95%CI: 3– 25] were more likely to develop danger control responses.
Conclusion and Recommendation: Nearly two-thirds of the participants were in the danger control response. Year of study, with whom students currently live, type of message they received, and the knowledge level of respondents were the factors associated with students’ response to HIV/AIDS prevention messages. Therefore, the messages must aim at enhancing threat component perception with appropriate efficacy messages to control danger and promote behavioral change.

Keywords: behavioral response, HIV prevention messages, extended parallel process model

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