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The past few decades have seen an exponential increase in using mobile phones to support medical care (mobile health [mHealth]) among people living with psychosis worldwide, yet little is known about WeChat use and WeChat-based mHealth among people living with schizophrenia (PLS) in China.
This study aims to assess WeChat use, endorsement of WeChat-based mHealth programs, and health related to WeChat use among PLS.
We recruited a random sample of 400 PLS from 12 communities in Changsha City of Hunan Province, China. WeChat use was assessed using the adapted WeChat Use Intensity Questionnaire (WUIQ). We also compared psychiatric symptoms, functioning, disability, recovery, quality of life, and general well-being between WeChat users and nonusers using one-to-one propensity-score matching.
The WeChat use rate was 40.8% in this sample (163/400); 30.7% (50/163) had more than 50 WeChat friends and nearly half (81/163, 49.7%) spent more than half an hour on WeChat, a pattern similar to college students and the elderly. PLS also showed higher emotional connectedness to WeChat use than college students. About 80.4% (131/163) of PLS were willing to participate in a WeChat-based mHealth program, including psychoeducation (91/163, 55.8%), professional support (82/163, 50.3%), and peer support (67/163, 41.1%). Compared with nonusers, WeChat users were younger, better educated, and more likely to be employed. WeChat use was associated with improved health outcomes, including lower psychiatric symptoms, lower depression, higher functioning, better recovery, and higher quality of life.
WeChat-based mHealth programs hold promise as an empowering tool to provide cost-effective interventions, to foster global recovery, and to improve both physical and mental well-being among PLS. WeChat and WeChat-based mHealth programs have the potential to offer a new path to recovery and well-being for PLS in China.
People living with schizophrenia (PLS) are individuals with a diagnosis of schizophrenia, which is a disturbance of thought, perception, and a blunting of affect, which can be characterized by 3 major symptoms: psychosis, cognitive dysfunction, and negative symptoms [
A burgeoning literature has consistently demonstrated strong evidence for the feasibility, effectiveness, and efficacy of mHealth [
Given these benefits, mHealth presents new opportunities to promote recovery and well-being among PLS. Recovery is a multifaceted concept that involves the development of new meaning and purpose in one’s life as one grew beyond the catastrophic effects of mental illness [
In China, the most prevalent mobile app is WeChat (literally: micro message) owned by Chinese tech giant Tencent [
The wide recognition of the extensive benefits of mHealth for PLS worldwide, and the lack of research on WeChat use and WeChat-based mHealth among PLS in China represent a significant knowledge gap relevant to mental health services research in China. As the growth in demand for mental health care exceeds the resources available to China’s mental health system, it is critical to develop more innovative and cost-effective methods of health care delivery. WeChat and WeChat-based mHealth hold great promise for improving mental health care delivery through extending the reach of services and supplementing existing models of care [
This study was conducted to fill this research gap by examining WeChat use, endorsement of WeChat-based mHealth programs, and health outcomes of WeChat users in an urban community sample of PLS in China. Specifically, we first examined participants’ WeChat use rate and patterns and compared these with 2 college samples and 1 elderly sample. We then examined participants’ endorsement of WeChat-based mHealth programs by assessing their interest in joining various potential WeChat-based programs. Finally, we examined how WeChat use is related to clinical outcomes, personal recovery, and well-being for this population
This was a cross-sectional study conducted in 12 community health centers from May 2019 to September 2019. All participants were recruited from China’s largest demonstration project in mental health services—the “686 Program”. The “686 Program” is aimed at integrating hospital and community services for serious mental illness, with a series of services provided including a monthly free medicine distribution to registered patients [
The study was approved by the Institutional Review Board of the Xiangya School of Public Health of Central South University. During the monthly free medicine distribution day, a research team of 3-5 psychiatrists went to each health center, where registered people with mental illness receive medication refills. A poster with detailed information about the study was posted in each health center to promote study participation. Individuals who expressed interest in participating in the study completed a clinical assessment about their current symptoms and functioning by 3 psychiatrists and a brief survey by the research team. All participants had the study explained to them and provided written informed consent before participating. Their responses were then checked by a quality control member of the team to ensure there were no inconsistencies or missing items. All participants were reimbursed with RMB 10 (US $1.4) in return for their time for participating.
WeChat use was assessed with the WeChat Use Intensity Questionnaire (WUIQ), as adapted by 2 studies (Wen et al [
Psychiatric symptoms were measured with the 18-item Brief Psychiatric Rating Scale (BPRS-18) to assess a set of common symptom characteristics in patients with psychiatric disorders [
Participant functioning was assessed using the Global Assessment of Functioning (GAF) scale to measure a person’s psychological, social, and occupational functioning on a hypothetical continuum of mental health illness ranging from 1 to 100 [
The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) [
Depression was assessed with the Patient Health Questionnaire-9 (PHQ-9) [
Anxiety was assessed with the Generalized Anxiety Disorder Scale-7 (GAD-7) [
Recovery was assessed with the Recovery Assessment Scale (RAS). The RAS is the most widely used scale for measuring a personal perspective on recovery globally, and originally included 5 factors. In this study, we used an 8-item short form of RAS (RAS-8) composed of 2 factors: (1) personal confidence and hope, and (2) no domination by symptoms [
Quality of life and general well-being were measured using the first 2 general questions from the World Health Organization Quality of Life Brief Scale (WHOQOL-BREF) [
Scales and indices were tested for reliability, and exploratory and summary statistics were computed for all variables. Data were examined for the presence of missing and influential values, as well as for outliers, skew, and kurtosis. Continuous variables were described using mean and standard deviation, and categorical variables were described using frequency and percentage. WeChat use patterns in this study were compared with those of other populations in other studies using the same or similar scale [
WeChat use rate was 40.8% in this sample (163/400). As shown in
We also compared the WUIQ score of the current PLS sample with 3 other available samples—2 college student samples and 1 elderly sample [
Summary statistics for WeChat intensity score and comparison with other studies.
Variables | People living with schizophrenia (N=163) (this study) | Undergraduates and graduates (N=339) [ |
College students (N=508) [ |
Old persons aged ≥50 (N=35) [ |
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Continuous, mean (SD) | 1.52 (0.99) | 2.34 (1.71) | 2.44 (1.31) | —b | ||||
≤50, n (%) | 113 (69.33) | 125 (36.87) | — | 23 (65.71) | |||||
>50, n (%) | 50 (30.67) | 214 (63.13) | — | 12 (34.29) | |||||
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Continuous, mean (SD) | 2.08 (1.38) | 2.00 (1.47) | 2.77 (1.51) | — | ||||
≤30 minutes, n (%) | 82 (50.31) | 165 (48.67) | — | 8 (22.86) | |||||
>30 minutes, n (%) | 81 (49.69) | 174 (51.33) | — | 27 (77.14) | |||||
WeChat is part of my everyday activityd, mean (SD) | 3.61 (0.94) | 3.61 (1.03) | 3.48 (0.99) | — | |||||
I am proud to tell people I am on WeChatd, mean (SD) | 3.28 (1.18) | 2.77 (1.16) | 2.74 (0.86) | — | |||||
I feel out of touch when I haven’t logged onto WeChat for a dayd, mean (SD) | 3.06 (1.17) | 2.27 (1.13) | 2.76 (1.11) | — | |||||
I feel I am part of the WeChat communityd, mean (SD) | 3.31 (1.01) | 3.10 (1.08) | 3.04 (1.00) | — | |||||
I would be sorry if WeChat shut downd, mean (SD) | 3.28 (1.04) | 2.93 (1.25) | 3.09 (1.08) | — | |||||
Total mean score for all 7 items, mean (SD) | 2.83 (0.77) | 2.72 (1.26) | 2.98 (0.78) | — |
aOptional answers include: 1=50 or less; 2=51-100; 3=101-150; 4=151-200; 5=more than 200; in the table we reclassified the answers into 2 classes with 50 as cutoff.
bNot available.
cOptional answers include: 1=less than 30 minutes; 2=30-60 minutes; 3=1-2 hours; 4=2-3 hours; 5=more than 3 hours; in the table we reclassified the answers into 2 classes with 30 minutes as cutoff.
dOptional answers include: 1=strongly disagree; 2=disagree; 3=neutral; 4=agree; 5=strongly agree.
Endorsement of WeChat-based mHealth programs (N=163).
Variables | n (%) |
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No | 32 (19.6) |
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Yes | 131 (80.4) |
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No | 72 (44.2) |
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Yes | 91 (55.8) |
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No | 96 (58.9) |
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Yes | 67 (41.1) |
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No | 81 (49.7) |
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Yes | 82 (50.3) |
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0 | 32 (19.6) |
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1 | 60 (36.8) |
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2 | 33 (20.2) |
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3 | 38 (23.3) |
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Sociodemographic comparison between WeChat users and nonusers.
Characteristic | All respondents (N=400) | WeChat users |
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No (N=237) | Yes (N=163) |
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Age, mean (SD) | 46.87 (10.99) | 50.42 (0.67) | 41.70 (0.77) | <.001b |
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.611 |
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Male, n (%) | 200 (50.00) | 121 (51.05) | 79 (48.47) |
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Female, n (%) | 200 (50.00) | 116 (48.95) | 84 (51.53) |
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.403 |
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Single, n (%) | 150 (37.50) | 83 (35.02) | 67 (41.10) |
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Married/cohabited, n (%) | 172 (43.00) | 104 (43.88) | 68 (41.72) |
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Elsec, n (%) | 78 (19.50) | 50 (21.10) | 28 (17.18) |
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<.001b |
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Primary and below, n (%) | 75 (18.75) | 66 (27.85) | 9 (5.52) |
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Middle and high, n (%) | 271 (67.75) | 158 (66.67) | 113 (69.33) |
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College and above, n (%) | 54 (13.50) | 13 (5.49) | 41 (25.15) |
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.001b |
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Unemployed, n (%) | 358 (89.50) | 222 (93.67) | 136 (83.44) |
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Employed, n (%) | 42 (10.50) | 15 (6.33) | 27 (16.56) |
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aDescriptive statistics were compared with chi-square tests for categorical variables (gender, marriage, education, and employment) and unpaired
bSignificance at
cElse include divorced, separated, and widowed.
In order to know if health outcomes of WeChat users are further affected by the number of WeChat friends and the time PLS spent on WeChat, we conducted similar comparisons of health outcomes by number of friends (with 50 as cutoff) and time spent on WeChat (with 30 minutes as cutoff) using propensity score matching. Our results showed the greater than 50 WeChat friend group had significantly better functioning than the less than or equal to 50 WeChat friend group (difference=4.61,
Health outcome comparison between the WeChat use group and nonuse group.a
Characteristic | All respondents (N=400), mean (SD) | WeChat use group (A), (N=163), mean (SD) | Non-use full group (B) (N=237), mean (SD) | (C) = A–B, |
Non-use matched group (D) (N=163), mean (SD) | (E) = A–D, |
BPRS-18b | 32.90 (11.43) | 30.47 (10.41) | 34.53 (11.81) | <.001c | 34.40 (10.72) | .030c |
WHODAS 2.0d | 26.02 (10.22) | 23.49 (9.03) | 27.74 (10.63) | <.001c | 27.10 (9.31) | .080e |
GAFf | 61.83 (13.58) | 66.13 (13.09) | 58.97 (13.18) | <.001c | 59.26 (11.61) | <.001c |
PHQ-9g | 9.01 (7.54) | 8.58 (7.48) | 9.30 (7.58) | .352 | 9.19 (6.52) | .024c |
GAD-7h | 6.67 (6.43) | 6.08 (6.17) | 7.08 (6.58) | .133 | 6.20 (5.67) | .101 |
RAS-8i | 20.29 (9.31) | 23.92 (9.07) | 17.80 (8.65) | <.001c | 17.30 (8.17) | <.001c |
QOL-1j | 3.05 (0.90) | 3.28 (0.89) | 2.89 (0.88) | <.001c | 2.96 (0.82) | .002c |
QOL-2j,e | 3.02 (0.95) | 3.16 (0.96) | 2.92 (0.94) | .014c | 3.00 (0.87) | .065e |
aContinuous variables were compared using independent 2-sample unpaired
bBPRS-18: the 18-item Brief Psychiatric Rating Scale
cSignificant at
dWHODAS 2.0: the 12-item World Health Organization Disability Assessment Schedule 2.0
eTrend effect at
fGAF: Global Assessment of Functioning
gPHQ-9: Patient Health Questionnaire-9
hGAD-7: Generalized Anxiety Disorder Scale-7
iRAS: Recovery Assessment Scale
jQOL: quality of life
This study provides a first examination of WeChat use patterns, endorsement of WeChat-based mHealth programs, and health outcomes related to WeChat use among an urban community sample of PLS in China. We also compared use patterns and intensity of use with comparable data available for other groups, such as for college students or an elderly sample. Our findings show a promising WeChat use rate of 40.8% (163/400) among this sample, whose WeChat friend number is similar to that of an elderly sample. Although PLS spent comparable time on WeChat to the college student samples, they showed a higher level of emotional connectedness to WeChat use than college students. About 80.4% (131/163) of PLS were willing to participate in any kind of WeChat-based mHealth programs, with psychoeducation being the most commonly endorsed program (91/163, 55.8%). Compared with nonusers, WeChat users were younger, better educated, and more likely to be employed. WeChat use was also associated with improved health outcomes, including lower psychiatric symptoms, lower depression, higher functioning, better recovery, and higher quality of life. This suggests that WeChat users among PLS may represent a higher functioning group that are particularly amenable to mHealth programs using WeChat.
In this study, WeChat use rate was 40.8% (163/400) among PLS, a rate within the range of 27%-71% for social media use reported among PLS in various studies across the world [
The finding that 80.4% (131/163) of PLS were willing to participate in any kind of WeChat-based mHealth programs is consistent with past literature showing high endorsement of mHealth intervention among PLS and other persons with other psychoses [
Consistent with most of previous studies, our study finds that WeChat users are generally of younger age, have higher education, and being employed than nonusers. That younger people are more likely to use WeChat in China is constituent with worldwide data that younger people are more likely to get online and use social media, such as Instagram, Snapchat, and Facebook [
We found generally better health outcomes in WeChat users than nonusers, including lower psychiatric symptoms, lower depression, higher functioning, better recovery, and higher quality of life. While higher number of WeChat friends was associated with higher functioning and better recovery, daily time spent on WeChat use showed no significant relationship to any of the health outcomes in this study. It seems like WeChat use alone, regardless of WeChat use intensity, was associated with better health outcomes. This finding aligns with the growing literature showing that social media use is associated with improved clinical and psychosocial outcomes among PLS and other persons with other psychoses, with reports of fewer symptoms, better functioning, better recovery, and better quality of life [
This study has several limitations. First, our sample was drawn from 12 urban communities and may not be generalizable to other locales such as rural communities, where mobile phone and WeChat access may be lower. As a result, the findings in this study may not capture the whole picture of social media use among PLS in China. Future research may benefit from conducting a nationally representative sample of WeChat users who are PLS. Second, when comparing WeChat use intensity, we used 2 college student samples and 1 elderly sample as comparison groups, instead of the general population or similar PLS samples. This was due to the lack of similar WeChat use intensity data on these populations. We expect more studies on WeChat use among various populations, including PLS using the WUIS in the future to allow for more cross-comparisons. Third, the cross-sectional study design did not make it possible to establish causality between WeChat use and health outcomes. Future research should examine WeChat use longitudinally and examine the relationship between use and well-being. Fourth, WeChat, like any other social media, may carry the potential risk of violating personal privacy and confidentiality, which should be taken into consideration when designing WeChat-based mHealth research and interventions. All participants in research or interventions should be made aware of the potential privacy issues pertaining to their WeChat data and provide informed consent prior to participation.
This initial study provides new data on the relationship between social media use using WeChat, mHealth program interest, and characteristics of WeChat users (PLS) in China. Our findings show a promising WeChat use rate and wide acceptability of WeChat-based mHealth programs among this population. This finding has implications for enhancing the current community-based treatment of PLS in China to augment existing treatment programs with WeChat-based mHealth interventions. Such interventions hold promise for reaching a larger population with schizophrenia, especially in regions of the world where traditional resources are scarce [
the 18-item Brief Psychiatric Rating Scale
Chinese Classification of Mental Disorders-3
Generalized Anxiety Disorder Scale-7
Global Assessment of Functioning
International Classification of Diseases-10
Patient Health Questionnaire-9
people living with schizophrenia
Recovery Assessment Scale
the 12-item World Health Organization Disability Assessment Schedule 2.0
World Health Organization Quality of Life Brief Scale
WeChat Use Intensity Questionnaire
This work was funded by a grant from the National Natural Science Foundation of China (Grant Number 71804197) and the China Scholarship Council (CSC) in support of the first author. The authors thank all PLS and their families for their participation in the study. We are also grateful to Changsha Psychiatric Hospital as well as the 12 community health centers for their collaboration and support.
All authors have made substantial contributions to the study conception and design, data collection and analysis, and to the development and editing of the manuscript. The principal investigator (YY) led the initial study design, while S Xiao and JT substantially revised and updated the research question and study design prior to initiating the project. YY, YL, TL, S Xi, and XX contributed to the research conduction and data collection; YY and YL contributed to data analyses; TL, S Xi, XX, S Xiao, and JT contributed to data interpretation; YY drafted the article while TL, S Xi, XX, S Xiao, and JT critically appraised it and revised it. All authors approved the final version of manuscript for submission and publication.
None declared.