Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status

Gwang Suk Kim; Mi So Shim; Jeongmin Yi

doi:10.1080/09540121.2021.1954587

Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status

Gwang Suk Kim, Mi So Shim, Jeongmin Yi

Nursing

Research output: Contribution to journal › Article › peer-review

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Abstract

Disclosure of human immunodeficiency virus (HIV) infection status improves treatment adherence and HIV prevention. Social networks influence such disclosure by people living with HIV/AIDS (PLWH). This study aimed to investigate the disclosure status of Korean PLWH and determine the social network characteristics associated with disclosure. A cross-sectional study design was used, and 148 Korean PLWH answered self-report questionnaires that included items on the characteristics of social networks and disclosure. Logistic regression and decision tree analysis were performed. In total, 81 participants (54.7%) reported disclosing HIV status to the most important supporter. Five factors were found to influence disclosure: age, self-help group participation, living arrangement, social network relationship, and tie strength; three groups had higher percentages of nondisclosure. The findings suggest that healthcare practitioners should provide adequate counseling by considering the characteristics of social networks and disclosure status of PLWH. Researchers should identify high-risk populations using decision tree analysis.

Original language	English
Pages (from-to)	118-126
Number of pages	9
Journal	AIDS Care - Psychological and Socio-Medical Aspects of AIDS/HIV
Volume	34
Issue number	1
DOIs	https://doi.org/10.1080/09540121.2021.1954587
Publication status	Published - 2022

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea [grant numbers NRF-2015R1D1A1A01057423, 2020R1A2C101081712] and a research program from the Yonsei University College of Nursing [grant number 6-2017-0125]. We thank all the PLWH who participated in our study and the nurses and physicians who cooperated with the research. This study was performed in line with the principles of the Declaration of Helsinki. The authors express our gratitude to Dr. Chang Gi Park, who gave professional advice on research methodology. The previous study from which data were used had obtained approval from the institutional review board of the institution to which the researcher belonged (IRB No: 2015-0040), and additional approval was obtained for the secondary analysis (IRB No: Y-2017-0088). Informed consent was obtained from all participants included in the study.

Publisher Copyright:
© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

All Science Journal Classification (ASJC) codes

Health(social science)
Social Psychology
Public Health, Environmental and Occupational Health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/09540121.2021.1954587

Cite this

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title = "Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status",

abstract = "Disclosure of human immunodeficiency virus (HIV) infection status improves treatment adherence and HIV prevention. Social networks influence such disclosure by people living with HIV/AIDS (PLWH). This study aimed to investigate the disclosure status of Korean PLWH and determine the social network characteristics associated with disclosure. A cross-sectional study design was used, and 148 Korean PLWH answered self-report questionnaires that included items on the characteristics of social networks and disclosure. Logistic regression and decision tree analysis were performed. In total, 81 participants (54.7%) reported disclosing HIV status to the most important supporter. Five factors were found to influence disclosure: age, self-help group participation, living arrangement, social network relationship, and tie strength; three groups had higher percentages of nondisclosure. The findings suggest that healthcare practitioners should provide adequate counseling by considering the characteristics of social networks and disclosure status of PLWH. Researchers should identify high-risk populations using decision tree analysis.",

author = "Kim, {Gwang Suk} and Shim, {Mi So} and Jeongmin Yi",

note = "Funding Information: This work was supported by the National Research Foundation of Korea [grant numbers NRF-2015R1D1A1A01057423, 2020R1A2C101081712] and a research program from the Yonsei University College of Nursing [grant number 6-2017-0125]. We thank all the PLWH who participated in our study and the nurses and physicians who cooperated with the research. This study was performed in line with the principles of the Declaration of Helsinki. The authors express our gratitude to Dr. Chang Gi Park, who gave professional advice on research methodology. The previous study from which data were used had obtained approval from the institutional review board of the institution to which the researcher belonged (IRB No: 2015-0040), and additional approval was obtained for the secondary analysis (IRB No: Y-2017-0088). Informed consent was obtained from all participants included in the study. Publisher Copyright: {\textcopyright} 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.",

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Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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