Relationship Between Patient Engagement and Depressive Symptoms Among People Living With HIV in a Mobile Health Intervention: Secondary Analysis of a Randomized Controlled Trial

Yu Zeng, Yan Guo, Linghua Li, Y Alicia Hong, Yiran Li, Mengting Zhu, Chengbo Zeng, Hanxi Zhang, Weiping Cai, Cong Liu, Shaomin Wu, Peilian Chi, Aliza Monroe-Wise, Yuantao Hao, Rainbow Tin Hung Ho, Yu Zeng, Yan Guo, Linghua Li, Y Alicia Hong, Yiran Li, Mengting Zhu, Chengbo Zeng, Hanxi Zhang, Weiping Cai, Cong Liu, Shaomin Wu, Peilian Chi, Aliza Monroe-Wise, Yuantao Hao, Rainbow Tin Hung Ho

Abstract

Background: Associations between higher levels of patient engagement and better health outcomes have been found in face-to-face interventions; studies on such associations with mobile health (mHealth) interventions have been limited and the results are inconclusive.

Objective: The objective of this study is to investigate the relationship between patient engagement in an mHealth intervention and depressive symptoms using repeated measures of both patient engagement and patient outcomes at 4 time points.

Methods: Data were drawn from a randomized controlled trial (RCT) of an mHealth intervention aimed at reducing depressive symptoms among people living with HIV and elevated depressive symptoms. We examined the association between patient engagement and depressive symptoms in the intervention group (n=150) where participants received an adapted cognitive-behavioral stress management (CBSM) course and physical activity promotion on their WeChat social media app. Depressive symptoms were repeatedly measured using the Patient Health Questionnaire (PHQ-9) at baseline and 1 month, 2 months, and 3 months. Patient engagement was correspondingly measured by the completion rate, frequency of items completed, and time spent on the program at 1 month, 2 months, and 3 months. Latent growth curve models (LGCMs) were used to explore the relationship between patient engagement and depressive symptoms at multiple time points in the intervention.

Results: The mean PHQ-9 scores were 10.2 (SD 4.5), 7.7 (SD 4.8), 6.5 (SD 4.7), and 6.7 (SD 4.1) at baseline, 1 month, 2 months, and 3 months, respectively. The mean completion rates were 50.6% (SD 31.8%), 51.5% (SD 32.2%), and 50.8% (SD 33.7%) at 1, 2, and 3 months, respectively; the average frequencies of items completed were 18.0 (SD 14.6), 32.6 (SD 24.8), and 47.5 (SD 37.2) at 1, 2, and 3 months, respectively, and the mean times spent on the program were 32.7 (SD 66.7), 65.4 (SD 120.8), and 96.4 (SD 180.4) minutes at 1, 2, and 3 months, respectively. LGCMs showed good model fit and indicated that a higher completion rate (β at 3 months=-2.184, P=.048) and a greater frequency of items completed (β at 3 months=-0.018, P=.04) were associated with fewer depressive symptoms at 3 months. Although not significant, similar trends were found in the abovementioned relationships at 1 and 2 months. There was no significant relationship between time spent on the program and depressive symptoms.

Conclusions: This study revealed a positive association between patient engagement and health outcomes at 3 months of an mHealth intervention using LGCMs and repeated measures data. The results underscore the importance of improving patient engagement in mHealth interventions to improve patient-centered health outcomes.

Trial registration: Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://tinyurl.com/yxb64mef.

International registered report identifier (irrid): RR2-10.1186/s12889-018-5693-1.

Keywords: HIV; depressive symptoms; latent growth curve model; mHealth; patient engagement.

Conflict of interest statement

Conflicts of Interest: None declared.

©Yu Zeng, Yan Guo, Linghua Li, Y Alicia Hong, Yiran Li, Mengting Zhu, Chengbo Zeng, Hanxi Zhang, Weiping Cai, Cong Liu, Shaomin Wu, Peilian Chi, Aliza Monroe-Wise, Yuantao Hao, Rainbow Tin Hung Ho. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 29.10.2020.

Figures

Figure 1
Figure 1
Unconditional latent growth curve model for depressive symptoms (n=150). Model fit statistic: χ2=7.0, P=.07, degrees of freedom=3; CFI=0.975, TLI=0.949, SRMR=0.039, RMSEA=0.094. Observed variables were indicated by boxes and latent variables were indicated by ovals. Unidirectional arrows indicated the effect of one variable on another and bidirectional arrows indicated correlations. The nonsignificant path was indicated by dotted line. 0: baseline; 1: 1 month after baseline; 2: 2 months after baseline; 3: 3 months after baseline; *P<.05, **P<.001.
Figure 2
Figure 2
Conditional latent growth curve model for depressive symptoms with completion rate as the measure of patient engagement (n=150). Model fit statistic: χ2=13.0, P=.79, degrees of freedom=18; CFI=1.000; TLI=1.000; RMSEA<0.001; SRMR=0.030. Baseline characteristics included education, income, and duration of HIV infection. Observed variables were indicated by boxes and latent variables were indicated by ovals. Unidirectional arrows indicated the effect of one variable on another and bidirectional arrows indicated correlations. Nonsignificant paths were indicated by dotted lines. Rate: completion rate; 0: baseline; 1: 1 month after baseline; 2: 2 months after baseline; 3: 3 months after baseline; *P<.05, **P<.001.
Figure 3
Figure 3
Conditional latent growth curve model for depressive symptoms with frequency of items completed as the measure of patient engagement (n=150). Model fit statistic: χ2=14.0, P=.73, degrees of freedom=18; CFI=1.000; TLI=1.000; RMSEA<0.001; SRMR=0.028. Baseline characteristics included education, income, and duration of HIV infection. Observed variables were indicated by boxes and latent variables were indicated by ovals. Unidirectional arrows indicated the effect of one variable on another and bidirectional arrows indicated correlations. Nonsignificant paths were indicated by dotted lines. Frequency: frequency of items completed; 0: baseline; 1: 1 month after baseline; 2: 2 months after baseline; 3: 3 months after baseline; *P<.05, **P<.001.
Figure 4
Figure 4
Conditional latent growth curve model for depressive symptoms with the time spent on the program as the measure of patient engagement (n=150). Model fit statistic: χ2=19.6, P=.36, degrees of freedom=18; CFI=0.993; TLI=0.988; RMSEA=0.024; SRMR=0.025. Baseline characteristics included education, income, and duration of HIV infection. Observed variables were indicated by boxes and latent variables were indicated by ovals. Unidirectional arrows indicated the effect of one variable on another and bidirectional arrows indicated correlations. Nonsignificant paths were indicated by dotted lines. Time: time spent on the program; 0: baseline; 1: 1 month after baseline; 2: 2 months after baseline; 3: 3 months after baseline; *P<.05, **P<.001.

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