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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Run4Love, a mHealth (WeChat-based) intervention to improve mental health of people living with HIV: a randomized controlled trial protocol
|
|---|---|
| Published in |
BMC Public Health, June 2018
|
| DOI | 10.1186/s12889-018-5693-1 |
| Pubmed ID | |
| Authors |
Yan Guo, Y. Alicia Hong, Jiaying Qiao, Zhimeng Xu, Hanxi Zhang, Chengbo Zeng, Weiping Cai, Linghua Li, Cong Liu, Yiran Li, Mengting Zhu, Nathan Asher Harris, Cui Yang |
| Abstract |
People living with HIV (PLWH) suffer from high rates of mental illness; but targeted effective interventions are limited, especially in developing countries. High penetration of smartphone usage and widespread acceptance of social media applications provide an unprecedented opportunity for mobile-based health interventions (mHealth interventions) in resource-limited settings like China. The current report describes the design and sample characteristics of the Run4Love randomized controlled trial (RCT) aimed at improving mental health in PLWH in China. A total of 300 PLWH with elevated depressive symptoms were recruited and randomized into either the intervention or control group. Participants in the intervention group received an adapted cognitive-behavioral stress management (CBSM) course delivered by the enhanced WeChat platform (for 3 months) and were motivated to engage in physical activities. Progress of the participants was automatically tracked and monitored with timely feedback and rewards. The control group received a brochure on nutrition for PLWH in addition to standard care. The outcome assessments are conducted at baseline, 3, 6, and 9 months using tablets. The primary outcome is depressive symptoms measured by the scale of the Center for Epidemiology Studies Depression (CES-D). Secondary outcomes include quality of life, chronic stress measured with biomarker of hair cortisol, and other measures of stress and depression, self-efficacy, coping, HIV-related stigma, physical activity, and patient satisfaction. Mixed effects model with repeated measures (MMRM) will be used to analyze the intervention effects. The Run4Love study is among the first efforts to develop and evaluate a multicomponent and integrated mHealth intervention to improve the mental health and quality of life of PLWH. Once proven effective, Run4Love could be scaled up and potentially integrated into the routine case management of PLWH and adapted to other populations with chronic diseases. Chinese Clinical Trial Registry - ChiCTR-IPR-17012606 , registered on 07 September 2017. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 488 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 488 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 66 | 14% |
| Student > Bachelor | 53 | 11% |
| Student > Ph. D. Student | 52 | 11% |
| Researcher | 34 | 7% |
| Student > Doctoral Student | 28 | 6% |
| Other | 73 | 15% |
| Unknown | 182 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 70 | 14% |
| Medicine and Dentistry | 59 | 12% |
| Psychology | 58 | 12% |
| Social Sciences | 19 | 4% |
| Computer Science | 11 | 2% |
| Other | 67 | 14% |
| Unknown | 204 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 February 2020.
All research outputs
#4,013,910
of 23,092,602 outputs
Outputs from BMC Public Health
#4,424
of 15,059 outputs
Outputs of similar age
#77,453
of 329,072 outputs
Outputs of similar age from BMC Public Health
#151
of 321 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,059 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,072 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 321 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.