Mediators of Intervention Effects on Depressive Symptoms Among People Living With HIV: Secondary Analysis of a Mobile Health Randomized Controlled Trial Using Latent Growth Curve Modeling

Mengting Zhu, Weiping Cai, Linghua Li, Yan Guo, Aliza Monroe-Wise, Yiran Li, Chengbo Zeng, Jiaying Qiao, Zhimeng Xu, Hanxi Zhang, Yu Zeng, Cong Liu, Mengting Zhu, Weiping Cai, Linghua Li, Yan Guo, Aliza Monroe-Wise, Yiran Li, Chengbo Zeng, Jiaying Qiao, Zhimeng Xu, Hanxi Zhang, Yu Zeng, Cong Liu

Abstract

Background: Although several studies have investigated the effects of mobile health (mHealth) interventions on depression among people living with HIV, few studies have explored mediators of mHealth-based interventions to improve mental health in people living with HIV. Identifying influential mediators may enhance and refine effective components of mHealth interventions to improve mental health of people living with HIV.

Objective: This study aimed to examine mediating factors of the effects of a mHealth intervention, Run4Love, designed to reduce depression among people living with HIV using 4 time-point measurement data.

Methods: This study used data from a randomized controlled trial of a mHealth intervention among people living with HIV with elevated depressive symptoms in Guangzhou, China. A total of 300 patients were assigned to receive either the mHealth intervention (n=150) or a waitlist control group (n=150) through computer-generated block randomization. Depressive symptoms, coping, and HIV-related stigma were measured at baseline, 3-, 6-, and 9-month follow-ups. The latent growth curve model was used to examine the effects of the intervention on depressive symptoms via potential mediators. Mediating effects were estimated using bias-corrected 95% bootstrapped CIs (BCIs) with resampling of 5000.

Results: Enhanced positive coping and reduced HIV-related stigma served as effective treatment mediators in the mHealth intervention. Specially, there was a significant indirect effect of the mHealth intervention on the slope of depressive symptoms via the slope of positive coping (beta=-2.86; 95% BCI -4.78 to -0.94). The indirect effect of the mHealth intervention on the slope of depressive symptoms via the slope of HIV-related stigma was also statistically significant (beta=-1.71; 95% BCI -3.03 to -0.40). These findings indicated that enhancement of positive coping and reduction of HIV-related stigma were important mediating factors of the mHealth intervention in reducing depression among people living with HIV.

Conclusions: This study revealed the underlying mediators of a mHealth intervention to reduce depression among people living with HIV using latent growth curve model and 4 time-point longitudinal measurement data. The study results underscored the importance of improving positive coping skills and mitigating HIV-related stigma in mHealth interventions to reduce depression among people living with HIV.

Keywords: HIV; depression; longitudinal studies; mobile health; randomized controlled trial.

Conflict of interest statement

Conflicts of Interest: None declared.

©Mengting Zhu, Weiping Cai, Linghua Li, Yan Guo, Aliza Monroe-Wise, Yiran Li, Chengbo Zeng, Jiaying Qiao, Zhimeng Xu, Hanxi Zhang, Yu Zeng, Cong Liu. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 15.11.2019.

Figures

Figure 1
Figure 1
Measurements of depressive symptoms, coping, and HIV-related stigma over time. Error bars indicate 95% confidence intervals.
Figure 2
Figure 2
Conditional latent growth curve modeling examining the effects of the mobile health intervention on the outcome and potential mediators. Continuous lines with arrows indicate statistically significant paths. Dotted lines indicate nonsignificant paths. The first and second factor loadings of the latent slope of all models were set to 1, the third and fourth factor loadings of the latent slope of all models were freely estimated. Group: intervention or control group; DS: depressive symptoms; HS: HIV-related stigma; PC: positive coping; NC: negative coping.
Figure 3
Figure 3
Latent growth curve modeling examining mediating effects between the mobile health intervention and changes in depressive symptoms. Continuous lines with arrows indicate statistically significant paths. Dotted lines indicate nonsignificant paths. The first and second factor loadings of the latent slope of the model were set to 1, the third and fourth factor loadings of the latent slope of the model were freely estimated. Group: intervention or control group; PC: positive coping; HS: HIV-related stigma; DS: depressive symptoms.

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