Relationship Between Patient Engagement and Depressive Symptoms Among People Living With HIV in a Mobile Health Intervention: Secondary Analysis of a Randomized Controlled Trial
Authors: Zeng Yu , Guo Yan , Li Linghua , Hong Y Alicia , Li Yiran , Zhu Mengting , Zeng Chengbo , Zhang Hanxi , Cai Weiping , Liu Cong , Wu Shaomin , Chi Peilian , Monroe-Wise Aliza , Hao Yuantao , Ho Rainbow Tin Hung 
Published: September 2020

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