Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-25T06:24:06.071Z Has data issue: false hasContentIssue false

Digital mental health in China: a systematic review

Published online by Cambridge University Press:  28 September 2021

Xiaolong Zhang
Affiliation:
Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
Shôn Lewis
Affiliation:
Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
Joseph Firth
Affiliation:
Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK NICM Health Research Institute, Western Sydney University, Westmead, Australia
Xu Chen
Affiliation:
The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
Sandra Bucci*
Affiliation:
Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK
*
Author for correspondence: Sandra Bucci, E-mail: sandra.bucci@manchester.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Mental health problems are highly prevalent in China; however, China's mental health services lack resources to deliver high-quality care to people in need. Digital mental health is a promising solution to this short-fall in view of the population's digital literacy. In this review, we aim to: (i) investigate the effectiveness, acceptability, usability, and safety of digital health technologies (DHTs) for people with mental health problems in China; (ii) critically appraise the literature; and (iii) make recommendations for future research directions. The databases MEDLINE, PsycINFO, EMBASE, Web of Science, CNKI, WANFANG, and VIP were systemically searched for English and Chinese language articles evaluating DHTs for people with mental health problems in mainland China. Eligible studies were systematically reviewed. The heterogeneity of studies included precluded a meta-analysis. In total, 39 articles were retrieved, reporting on 32 DHTs for various mental health problems. Compared with the digital mental health field in the West, the Chinese studies targeted schizophrenia and substance use disorder more often and investigated social anxiety mediated by shame and culturally specific variants, DHTs were rarely developed in a co-production approach, and methodology quality was less rigorous. To our knowledge, this is the first systematic review focused on digital mental health in the Chinese context including studies published in both English and the Chinese language. DHTs were acceptable and usable among Chinese people with mental health problems in general, similar to findings from the West. Due to heterogeneity across studies and a paucity of robust control trial research, conclusions about the efficacy of DHTs are lacking.

Type
Review Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Introduction

Mental health problems are a major cause of global disease burden (Vigo, Thornicroft, & Atun, Reference Vigo, Thornicroft and Atun2016), and constitute the largest single source of world economic burden, greater than many physical health diseases (Mental Health Foundation, 2015). Mental health problems are prevalent in China; the 12-month prevalence rate of any mental health problem is 9.3%, and lifetime prevalence is 16.6% (Huang et al., Reference Huang, Wang, Wang, Liu, Yu, Yan and Wu2019). Despite the tremendous demands on mental healthcare, there is a vast shortage of resources to deliver high-quality care to help-seeking individuals across China. The scarcity of mental health professionals in China is significant, with an estimated shortage of 40 000 psychiatrists relative to the population need (Wu, Zhao, & Ye, Reference Wu, Zhao and Ye2016). Since the Chinese healthcare system is designed to be delivered in tertiary hospitals (Yip & Hsiao, Reference Yip and Hsiao2014), well-trained mental health professionals are concentrated in psychiatric hospitals in urban areas (Liu et al., Reference Liu, Chen, Xie, Yan, Jin and Wu2013), leaving a significant short-fall in accessing mental healthcare for rural/remote communities (Xiang, Ng, Yu, & Wang, Reference Xiang, Ng, Yu and Wang2018). A national programme aimed at integrating hospital and community-based mental health services for people with severe mental health problems (i.e. the 686 programme) has more than 6 million current enrollees with severe mental illness, and more than 70% of the enrollees have received basic medication treatment (Lu, Reference Lu2019; Ma, Reference Ma2012). However, further mental health service reform is indispensable to close the treatment gap and promote mental health in China (Liang, Mays, & Hwang, Reference Liang, Mays and Hwang2018b; Que, Lu, & Shi, Reference Que, Lu and Shi2019).

With the Chinese economy booming and the fast-paced development of digital health technologies (DHTs), digital mental health is a promising solution to this short-fall. China's use of digital technologies has grown exponentially in the past decade, with ownership rates of smartphone in China is now 96% (Chou, Chung, & Lam, Reference Chou, Chung and Lam2019), which comparable to Western countries. In a recent review (Yin et al., Reference Yin, Wardenaar, Wang, Wang, Chen, Zhang and Schoevers2020), 172 mental health smartphone apps have been developed in Chinese and can be downloaded from app stores. Since coronavirus disease 2019 (COVID-19), online mental health services have also significantly increased in China (Liu et al., Reference Liu, Yang, Zhang, Xiang, Liu, Hu and Zhang2020), as has been seen in many other countries worldwide (Torous, Myrick, Rauseo-Ricupero, & Firth, Reference Torous, Myrick, Rauseo-Ricupero and Firth2020). Although four systematic reviews on digital mental health in low- and middle-income countries (LMICs; Carter, Araya, Anjur, Deng, & Naslund, Reference Carter, Araya, Anjur, Deng and Naslund2021; Fu, Burger, Arjadi, & Bockting, Reference Fu, Burger, Arjadi and Bockting2020; Naslund et al. Reference Naslund, Aschbrenner, Araya, Marsch, Unützer, Patel and Bartels2017) or resource-limited settings (Kaonga & Morgan, Reference Kaonga and Morgan2019) have been conducted, findings have been interpreted in the general context of LMICs. However, these reviews excluded a number of studies published in Chinese/Chinese-based journals, and to date, there have been no systematic reviews examining digital mental health in a specific Chinese context. Therefore, in order to understand how digital mental health can help solve the mental health crisis for the most populated country and the second largest economy in the world, and to inform the development of DHTs in other LMICs, a systematic review of DHTs in the Chinese context is timely. The aims of the current systematic review are to: (i) investigate the effectiveness, acceptability, usability, and safety of digital mental health interventions for people with mental health problems in the Chinese context; (ii) critically appraise the literature; and (iii) make recommendations for future research directions for developing digital mental health in China.

Method

Search strategy

This study was conducted and reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines (Moher, Liberati, Tetzlaff, Altman, & Group, Reference Moher, Liberati, Tetzlaff, Altman and Group2009). A protocol of the review was registered with PROSPERO (CRD42020192185). Four English language databases (MEDLINE, PsycINFO, EMBASE via Ovid, and Web of Science), and three Chinese language databases (China National Knowledge of Infrastructure, WANFANG Data, and VIP Information) were systemically searched. Terms were used to search title, abstract, keywords, and subject headings. A detailed search strategy in both English and Chinese is provided in online Supplementary Table S1. Results were limited to English and Chinese language peer-reviewed journal publications. A hand search of reference lists of eligible papers was conducted to identify additional relevant studies. Two reviewers (XZ and XC) independently screened 100% of the papers returned from the search in both English and Chinese at each of the title, abstract, and full-text paper levels, and assessed study eligibility with queries resolved through discussion with the research team. Primary searches were completed in February 2020 and updated in June 2021.

Eligibility criteria

Eligible studies were peer-reviewed, quantitative, and qualitative studies aimed at evaluating effectiveness, acceptability, usability, or safety of digital mental health interventions. Study designs included randomised controlled trials (RCTs), non-randomised controlled trials (non-RCTs), case report/case-series studies, survey studies, interview, and focus group studies. We included studies conducted in mainland China with participants who met DSM or ICD criteria where diagnosis was operationalised as those who met clinical threshold assessed by a validated clinical tool or confirmed by a treating clinician, with no restriction on age. Studies conducted in Hong Kong or Taiwan were not included, in view of the different healthcare contexts. Studies focused on DHTs targeting mental health problems, including short message service (SMS), mobile apps, computer programmes, software, interactive websites, social media, wearable and ambient sensors, virtual reality, or artificial intelligence. Programmes that focused solely on information provision (e.g. internet-based psychoeducation with no additional interactive function), or purely provided electronic communication (e.g. contact via telephone, videoconference, text, or email with professional without any therapeutic content) were excluded. Studies where a mental health problem was not the primary focus of the paper, such as physical health problems, health behaviours (e.g. smoking cessation), neurodegenerative disorders (e.g. dementia), and internet addiction, were excluded.

Data extraction and analytic plan

The study selection process is summarised in Fig. 1. Cohen's kappa was used to assess interrater reliability, and strong interrater agreements were found for both the title and abstract level (κ = 0.89) and the full text level (κ = 0.94) screening. The following information was extracted from selected papers: (a) general information (author, article title, type of publication, country of origin); (b) study characteristics (study aim/objectives, study design, study inclusion and exclusion criteria, recruitment procedures used); (c) participant characteristics (age, gender, ethnicity, diagnostic information, number of participants in each characteristic category for intervention and control groups); (d) study setting (country, type of service); (e) intervention (intervention name, length, frequency, intervention development, summary of intervention, theoretical basis); and (f) outcome data/results (unit of assessment/analysis statistical techniques used). Quantitative and qualitative data were integrated using a narrative synthesis approach. Due to the heterogeneity regarding study designs and outcomes, a meta-analysis was not conducted.

Fig. 1. PRISMA flow chart of study selection.

Quality assessment

Due to the diversity of study designs included, the Mixed Methods Appraisal Tool (MMAT; Hong et al., 2018) was used to assess the quality of studies. The MMAT permits the appraisal of the methodological quality of studies across five categories, including qualitative research, RCTs, non-RCTs, quantitative descriptive studies, and mixed-methods studies. The quality assessment was independently carried out by two reviewers (XZ and XC; κ = 0.97). Discrepancies were due to some studies not explicitly describing their methodology; therefore, further discussion was required before consensus was reached. Criteria from the MMAT are shown in online Supplementary Table S2.

Results

The database search returned 8279 results. Duplicate results were removed (n = 2280 articles) using reference manager software before titles and abstracts were screened for inclusion (n = 5999 articles). A further 5891 papers were excluded by title and abstract screening. Full-text papers were assessed for the remaining 108 articles; 70 were excluded (reasons are shown in Fig. 1). One further article was identified following a hand search of reference lists of eligible studies. Finally, 39 articles were retrieved in total. The process of study selection is demonstrated in Fig. 1.

Characteristics of included studies

A summary of the characteristics of selected studies is shown in Table 1. A more detailed description of each study is provided in online Supplementary Table S3. Included studies were published from 2010 to 2021. Eleven papers were published in Chinese; 28 papers were published in English. There were 27 RCTs, four non-RCTs, five case-series studies, and three qualitative studies.

Table 1. Characteristics of included studies (organised by type of digital health technologies)

RCT, randomised controlled trail; IG, intervention group; CG, control group; MCCB, MATRICS Consensus Cognitive Battery; WCST, Wisconsin Card Sort Test; UPSA, UCSD Performance-based Skills Assessment; NOSIE, Nurse's Observation Scale for Inpatient Evaluation; PANSS, Positive and Negative Syndrome Scale; CCRT, Computerised cognitive remediation therapy; BARS, Brief Adherence Rating Scale; DAI, Drug Attitude Inventory; CGI, Clinical Global Impression; WHODAS, WHO Disability Assessment Schedule; LSAS, Liebowitz Social Anxiety Scale; STAI, State-Trait Anxiety Inventory; SUD, substance use disorder; DDT, delay discounting task; IGT, Iowa gambling task; BART, balloon analogue risk task; CCAT, Computerised Cognitive Addiction Therapy; EMA, Ecological Momentary Assessment; LET, life experience timeline; PDS, Posttraumatic Diagnostic Scale; SCL-D, Symptom Checklist -Depression; SFI, Social Functioning Impairment; CSS, Crisis Support Scale; CSE, Coping Self-Efficacy; PCC, Post-traumatic Cognitive Changes; RPM, Raven's Progressive Matrices; CAST, Childhood Autism Spectrum Test; PEP-3, Psychoeducational Profile Third Edition; ABAS-II, Adaptive Behaviour Assessment System – Second Edition; CESD-R, Centre for Epidemiologic Studies Depression Scale – Revised; ITT, intention to treat; SSQ, Simulator Sickness Questionnaire; VQ, Volitional Questionnaire; CES-D, Centre for Epidemiologic Studies Depression Scale; PSP, Personal and Social Performance Scale; SIAS, Social Interaction Anxiety Scale; SPS, Social Phobia Scale; BDI, Beck Depression Inventory; IPROS, Inpatient Psychiatric Rehabilitation Outcome Scale; ASD, autism spectrum disorder; non-RCT, non-randomised controlled trial; ADOS, Autism Diagnostic Observation Schedule; BPRS, Brief Psychiatric Rating Scale; CGI-S, Clinical Global Impression-Severity; ACCT, A battery of computerised cognitive test; PHQ, Patient Health Questionnaire; VAS, Visual Analogue Scale; WHOQOL-BREF, WHO Quality of Life-Brief; SWLS, Satisfaction With Life Scale; TKSS, Taijin Kyofusho Scale; WSAP, Word Sentence Association Paradigm; LSAS, Liebowitz Social Anxiety Scale; STAI, State Trait Anxiety; PDS, Posttraumatic Diagnostic Scale; DTQ, Disclosure of Trauma Questionnaire; SAQ, Social Acknowledgement Questionnaire; CBM-A, cognitive bias modification-attention; CBM-I, cognitive bias modification-interpretation; AIM, attention and interpretation modification; ASI, addiction severity index; MAQ, Medication Adherence Questionnaire; SQLS, Schizophrenia Quality of Life Scale; PSAS, Pre-sleep Arousal Scale; ISI, insomnia severity index; HADS, Hospital Anxiety and Depression Scale; HAMA, Hamilton Anxiety Scale; FCV-19S, Fear of COVID-19 Scale; TAU, treatment as usual; ADHD, attention deficit hyperactivity disorder.

aThe criteria for each of the MMAT items (Hong et al. Reference Hong, Fàbregues, Bartlett, Boardman, Cargo, Dagenais and Pluye2018) are shown in online Supplementary Table S2.

b Taijin Kyofusho is a culturally bound form of social anxiety, mostly seen in Eastern cultures, where people worry that their behaviours, expressions, or physical characteristics will offend or make others feel uncomfortable (Kleinknecht et al., Reference Kleinknecht, Dinnel, Kleinknecht, Hiruma and Harada1997).

Characteristics of participants

Selected studies investigated a variety of mental health problems, including schizophrenia (n = 12), depression (n = 7), anxiety (n = 6), substance use disorder (SUD; n = 5), autism spectrum disorder (ASD; n = 3), trauma (n = 3), attention deficit hyperactivity disorder (ADHD; n = 1), insomnia (n = 1), and suicide prevention (n = 1). The total number of people with mental health problems recruited from mainland China was 3112. The mean age of participants with mental health problems ranged from 4.7 to 47.4 years. The total number of female and rural participants was 1676 (54%) and 395 (13%), respectively.

Overview of the measurement of outcomes

Where studies examined efficacy or effectiveness of DHTs, outcomes included psychiatric symptomatology, cognitive outcomes, functional outcomes, shame, and medication adherence (see Table 1 and online Supplementary Table S3). Where studies evaluated acceptability and usability, survey and interview data, and programme use (e.g. time spent on website) were reported.

Characteristics of DHTs

A summary of intervention characteristics is demonstrated in Table 1 (see online Supplementary Table S3 for a more detailed summary of studies). In total, 32 DHTs were identified from included studies; of these, six DHTs were adapted from existed tools developed in Western countries (Hu et al., Reference Hu, Yang, Lu, Zhao, Zhu and Yi2021; Kishimoto et al., Reference Kishimoto, Krieger, Berger, Qian, Chen and Yang2016; Patel et al., Reference Patel, Sobowale, Fan, Liu, Kuwabara, Lei and Van Voorhees2017; Sit et al., Reference Sit, Hall, Wang, Zhang, Ju and Gan2020; Wang, Wang, & Maercker, Reference Wang, Wang and Maercker2013b; Yeung et al., Reference Yeung, Wang, Feng, Zhang, Cooper, Hong and Fava2018). Only one of the selected studies involved patient and public involvement methods in the DHT development process (Schulte et al., Reference Schulte, Liang, Wu, Lan, Tsay, Du and Hser2016). The length and duration of DHTs varied widely, ranging from one session to an 8-month intervention window.

Acceptability, usability, and safety of DHTs in the Chinese context

Internet-based programmes

Five studies reported acceptability and usability data on internet-based programmes for depression, anxiety, and trauma. In general, most participants deemed the programmes to be helpful and useful. One study reported 100% of participants reported that the programme was useful, while 64% participants felt the programme was too long (Yeung et al., Reference Yeung, Wang, Feng, Zhang, Cooper, Hong and Fava2018). Older participants (Chen et al., Reference Chen, Rodriguez, Qian, Kishimoto, Lin and Berger2020), participants with more severe symptoms (Chen et al., Reference Chen, Rodriguez, Qian, Kishimoto, Lin and Berger2020; Wang, Wang, & Maercker, Reference Wang, Wang and Maercker2013a), and participants with higher functioning levels (Wang, Wang, & Maercker, Reference Wang, Wang and Maercker2016) showed higher rates of engagement with the programme. One qualitative study (Patel et al., Reference Patel, Sobowale, Fan, Liu, Kuwabara, Lei and Van Voorhees2017) indicated that substantial cultural adaptation was needed for a programme originally developed in the USA. One study (Yeung et al., Reference Yeung, Wang, Feng, Zhang, Cooper, Hong and Fava2018) examined safety of an internet-based programme and no severe adverse events were observed. Overall, participants considered internet-based programmes acceptable and helpful, although some negative feedback was expressed (e.g. the content of the programme was too long).

Smartphone apps

Five studies evaluated the acceptability and feasibility of two smartphone app-based interventions: one study on a smartphone app for perinatal depression and the other four studies about an app for SUD. One RCT (Sun et al., Reference Sun, Li, Wang, Chen, Bazzano and Cao2021) reported poor intervention completion rates for an app-based mindfulness training on perinatal depression; 52.3% of participants in the intervention group completed at least 4 weeks of the intervention and only 8% completed the full 8-week intervention programme. For smartphone apps for SUD, participants from one RCT study (Liang, Han, Du, Zhao, & Hser, Reference Liang, Han, Du, Zhao and Hser2018a) reported that the content was easy to understand in only 55% of cases, although 72% said that the app was easy to use. One focus group study (Schulte et al., Reference Schulte, Liang, Wu, Lan, Tsay, Du and Hser2016) reported that receiving support via the app helped people avoid feeling ashamed of sharing personal information with others compared to attending services in-person. However, another study indicated limited acceptance; 46% of participants preferred in-person services instead of using the app (Han et al., Reference Han, Zhang, Hser, Liang, Li, Wang and Zhao2018). In summary, the feasibility of app-based interventions for perinatal depression was limited, and contradictory results were found for smartphone app-based programmes for SUD; some participants felt the app was acceptable, while others preferred in-person services.

Text messaging

Two studies investigated the acceptability and usability of a text messaging intervention for people who experienced a suicide attempt and people with chronic schizophrenia. In the post-treatment interview, 80% (12/15) of people who experienced a suicide attempt reported that receiving text messages was acceptable and they were willing to receive the messages for a longer period (Chen, Mishara, & Liu, Reference Chen, Mishara and Liu2010). Another small qualitative study (Wang et al., Reference Wang, Xiao, Xu, Li, Nie, Yuan and Gong2017) found that five out of the eight people with chronic schizophrenia and all of the family members who participated in the interview reported that the text messaging intervention was acceptable. However, not all of the participants and their family members mastered using a mobile phone, mainly due to low literacy level, older age, and cognitive impairment. In summary, these results showed that text messaging interventions are generally acceptable.

Effects of DHTs on symptoms, neurocognitive, and functional outcomes in the Chinese context

Computerised programmes

Ten studies examined computerised programmes in people with a diagnosis of schizophrenia and depression. Eight studies tested the effects of computerised cognitive remediation therapy (CCRT) improving neurocognitive outcomes for people with schizophrenia. Seven RCT studies (Byrne et al., Reference Byrne, Peng, McCabe, Mellor, Zhang, Zhang and Xu2013; Hu et al., Reference Hu, Yang, Lu, Zhao, Zhu and Yi2021; Liao, Ding, Wu, Zhou, & Pan, Reference Liao, Ding, Wu, Zhou and Pan2016; Tan et al., Reference Tan, Zhu, Fan, Tan, Yang, Wang and Wykes2019; Zhang, Xu, Chen, & Chen, Reference Zhang, Xu, Chen and Chen2016b; Zhu et al., Reference Zhu, Sun, Tang, Jiang, Zhang and Shi2018a; Zhu et al., Reference Zhu, Fan, Fan, Zhao, Tan, Yang and Tan2020b) found computerised programmes improved neurocognitive functioning in schizophrenia patients compared with a control group. Of these, two studies (Byrne et al., Reference Byrne, Peng, McCabe, Mellor, Zhang, Zhang and Xu2013; Tan et al., Reference Tan, Zhu, Fan, Tan, Yang, Wang and Wykes2019) found improved negative symptom and psychotic symptom scores of the Positive and Negative Syndrome Scale (PANSS) compared with a control group, and two studies (Zhang et al., Reference Zhang, Xu, Chen and Chen2016b; Zhu et al., Reference Zhu, Fan, Fan, Zhao, Tan, Yang and Tan2020b) found that the CCRT programme significantly improved functional outcomes compared to controls. Conversely, Byrne, Pan, McCabe, Mellor, and Xu (Reference Byrne, Pan, McCabe, Mellor and Xu2015) conducted a non-RCT and found no significant difference in symptoms and neurocognitive outcomes between the intervention group compared with treatment as usual (TAU) plus antipsychotic, but a significant improve in functional outcomes was observed. However, of the eight studies, five were conducted with inpatients and two studies recruited male participants only, which limits the generalisability of study results.

Overall, the efficacy of CCRT programme on improving neurocognitive functioning in schizophrenia patients was demonstrated by all seven RCT studies. These are better effects than trials conducted in Western countries (Kambeitz-Ilankovic et al., Reference Kambeitz-Ilankovic, Betz, Dominke, Haas, Subramaniam, Fisher and Kambeitz2019), but the efficacy on enhancing psychotic symptoms and functional outcomes remains uncertain. Moreover, computerised programme may help improve neurocognitive functions (Zhu et al., Reference Zhu, Sun and Wang2020a) and depressive symptoms (Sit et al., Reference Sit, Hall, Wang, Zhang, Ju and Gan2020) in people with depression; however, the representativeness of findings is limited to people with mild to the moderate levels of depression.

Internet-based programmes

Ten studies investigated the effectiveness of internet-based programmes for people with anxiety, depression, trauma, and ADHD. Two RCTs (Lin et al., Reference Lin, Wang, Kishimoto, Rodriguez, Qian, Yang and Tian2020; Wang et al., Reference Wang, Zhao, Mu, Rodriguez, Qian and Berger2020) and two non-RCTs (Chen et al., Reference Chen, Rodriguez, Qian, Kishimoto, Lin and Berger2020; Kishimoto et al., Reference Kishimoto, Krieger, Berger, Qian, Chen and Yang2016) tested internet-based cognitive behavioural therapy (ICBT) for social anxiety. All four studies showed ICBT reduced the severity of social anxiety, with up to 42% of participants in one study (compared to 20% of participants in the control group; Lin et al., Reference Lin, Wang, Kishimoto, Rodriguez, Qian, Yang and Tian2020) showing significant improvements in social anxiety symptoms post-treatment. Lin et al. (Reference Lin, Wang, Kishimoto, Rodriguez, Qian, Yang and Tian2020) also evaluated the effects of internet-based programmes on cultural specific condition, Taijin Kyofusho (TKS), which is a culture-related subtype of social anxiety recognised by both the DSM-5 and the ICD-10. TKS is commonly seen in Eastern cultures manifesting as individuals fear of embarrassing or offending others by behaviours, expressions, or physical characteristics (Kleinknecht, Dinnel, Kleinknecht, Hiruma, & Harada, Reference Kleinknecht, Dinnel, Kleinknecht, Hiruma and Harada1997). Results showed a 44% improvement rate for participants in the intervention group using the TKS Scale. Another RCT study (Wang et al., Reference Wang, Zhao, Mu, Rodriguez, Qian and Berger2020) explored the effects on reducing shame, a potential mediator of social anxiety. Both guided and unguided internet-based programmes reduced shame proneness compared to the control group. One large-scale non-RCT (Chen et al., Reference Chen, Rodriguez, Qian, Kishimoto, Lin and Berger2020, n = 255) showed a significant reduction of social anxiety symptoms in the intervention group. However, long-term effects of the interventions were unknown, and drop-out rates of the studies were high, ranging from 41.82% to 59.56%.

Two RCT studies tested the effectiveness of an iCBT programme (the Chinese version MoodGYM) in clinical samples with depression (Ren et al., Reference Ren, Li, Zhao, Yu, Li, Lai and Jiang2016; Yeung et al., Reference Yeung, Wang, Feng, Zhang, Cooper, Hong and Fava2018). Significant reductions in depression were reported in both studies post-treatment. However, neither of the studies examined the long-term effects of the programme on depressive symptoms. The results differ from a large-scale pragmatic RCT of MoodGYM conducted in the UK that found no significant improvement of depression compared with controls (Gilbody et al., Reference Gilbody, Littlewood, Hewitt, Brierley, Tharmanathan, Araya and White2015).

For post-traumatic stress disorder (PTSD), one RCT study (Wang et al., Reference Wang, Wang and Maercker2013b) evaluated the efficacy in both an urban and rural group. The urban group completed the programme online. The rural group completed the programme at a local counselling centre (due to the lack of access to a computer at home). There was a significant reduction in traumatic symptoms and improved functioning for urban-dwelling participants. For rural participants, there was significant improvement in traumatic symptoms compared to the waitlist control group, but no effect on functioning. For both the urban and rural groups, the effect was sustained at 3-months. However, the drop-out rate in the urban sample was relatively high, with 54% drop-out at post-treatment and 64% at 3-month follow-up in the intervention group.

One RCT study (Li, Liao, Zhou, Wang, and Qian, Reference Li, Liao, Zhou, Wang and Qian2017) tested the efficacy of an online cognitive training programme on improving core clinical symptoms and executive function compared with working memory training in children with ADHD. After 12-weeks of training, both groups showed a significant decrease in clinical symptoms and increased executive function performance, with no between group differences.

In summary, internet-based programmes may have short-term effects on (social) anxiety, depression, trauma, and ADHD, although long-term effects remain uncertain. Improved functional outcomes were evident in studies that included people who had experienced PTSD. High drop-out rates were commonly seen across studies, partially due to the self-help nature of the internet-based programmes.

Smartphone apps

Seven studies examined the effect of using a smartphone app for SUD, social anxiety, and ASD. For SUDs, one RCT study (Liang et al., Reference Liang, Han, Du, Zhao and Hser2018a) assessed a smartphone app on supporting recovery and found the intervention group had a significantly lower number of days using drugs in the past week compared to the control group post-treatment. One RCT study (Xu et al., Reference Xu, Chen, Chen, Chen, Fu, Song and Jiang2021) tested the efficacy of a smartphone app to support community-based rehabilitation for people with SUDs. Urine drug screens showed a significantly lower percentage of drug positive rates in the intervention group compared with the control group (3.3% v. 7.5%). Another small-scale RCT study (n = 40; Zhu et al., Reference Zhu, Jiang, Su, Zhong, Li, Li and Zhao2018b) targeting cognitive impairments found the intervention group reported significant improvements in cognitive functions and risk decision-making compared to controls. However, due to the relative small sample size of the three studies and the latter study only including male participants, the generalisability of findings is limited.

Two studies tested smartphone app-based cognitive bias modification programme in people with social anxiety. One RCT study (Sun et al., Reference Sun, Yang, Zhang, Xiao, Li and Cui2019) showed that the level of social anxiety significantly reduced in the intervention group compared to that in the control group post-treatment and sustained at 1-month follow-up. Another RCT study (Yang et al., Reference Yang, Cui, Li, Xiao, Zhang and Oei2017) compared three different forms of cognitive bias modification programmes (i.e. attention bias modification, interpretation bias modification, and attention and interpretation bias modification) and found that only the interpretation bias modification group showed a significant reduction in cognitive bias outcomes compared to the control group. However, the generalisability of the results was limited, as both studies recruited university students.

Two case-series studies investigated smartphone app-based interventions on children with ASD. One study (An et al., Reference An, Feng, Dai, Bo, Wang, Li and Wei2017) evaluated a speech-generating augmentative and alternative communication smartphone app for minimally verbal children with ASD. The training has five phases with each session increasing the degree of difficulty of the task. All participants (n = 10) successfully completed at least one phase of the training, and at least 50% accuracy in at least two of the five phases were achieved by seven children, suggesting that the app was feasible for ASD children for speech training. Another study in just three children (Zhang et al., Reference Zhang, Xia, Li, Shen, Liu, Zhao and Chen2019) examined the effects of an app-based intervention on improving facial expression recognition and emotion understanding abilities in children with ASD. The app consisted of seven training domains regarding social communication skills.

Overall, preliminary results of smartphone apps in SUD, social anxiety, and ASD showed feasibility, but clear conclusions regarding efficacy were limited by small samples and a lack of representativeness of study samples.

Text messaging

One RCT study (Xu et al., Reference Xu, Xiao, He, Caine, Gloyd, Simoni and Gong2019) (n = 278) tested a text messaging intervention to increase medication adherence in schizophrenia patients in a resource-limited rural area. Participants in the intervention group and their lay health supporters (i.e. family members or community volunteers) received two text messages daily during a 6-month period. Post-treatment, the intervention group demonstrated significant improvements in medication adherence and a substantial reduction in the risk of relapse and re-hospitalisation compared to the control group. However, the control group received no digital intervention; therefore, treatment effects may be due to non-specific factors. An extended implementation phase was carried out to further explore the effectiveness of the text messaging programme (Cai et al., Reference Cai, Gong, He, Hughes, Simoni, Xiao and Xu2020). In the extended phase, both the intervention group and the control group received the same text messaging intervention. After the 6-month extended intervention, there were further improvements in medication adherence. However, the contribution of the lay health supporters was not examined, which may have resulted in an overestimation of the effects of the text messages.

Social media

Two studies examined the effectiveness of a social media-based intervention utilising WeChat, one of the most widely used social media tools in mainland China. One study explored medication adherence in people who had received a diagnosis of schizophrenia, and the other explored insomnia during the COVID-19 pandemic.Zhu et al. (Reference Zhu, Li, Liu, Chang, Wang and Liu2020c) found a significant increase in medication adherence and quality of life for schizophrenia patients who received the WeChat-based 6-month medication adherence programme compared to controls (who received a telephone check in). However, medication adherence was measured by self-report assessment, which may affect the reliability of reporting due to social desirability and recall bias.

Using a case-series design, Zhang et al. (Reference Zhang, Yang, Liu, Xu, Zheng and Zhang2021) evaluated the efficacy of a self-guided WeChat-based CBT programme for people who experienced insomnia during the COVID-19 pandemic. After the 1-week intervention, completers (i.e. login time = 7) showed significantly less pro-sleep arousal problems and reported lower insomnia severity scores compared to non-completers (i.e. login time ⩽6). However, due to the lack of control group, the efficacy of the programmes remains uncertain.

Virtual reality (VR)

Three studies investigated interventions using VR; one in people with a diagnosis of major depressive disorder or bipolar disorder depressive episodes, one in people with a diagnosis of generalised anxiety disorder specifically related to fear of COVID-19 infection, and one in people with a diagnosis of ASD.

One RCT study (Lyu et al., Reference Lyu, Zhang, Zhong, Jia, Lai, Shen and Miao2020) evaluated the effectiveness of a VR attention training programme on neurocognitive function compared to CCRT and TAU in people with depressive episode or bipolar disorder. After the 4-week intervention, participants receiving the VR attention training programme showed significantly higher performance on information processing speed and attention/alertness compared with participants received CCRT or no treatment.

One case-series study (Zhang et al., Reference Zhang, Paudel, Shi, Liang, Liu, Zeng and Zhang2020) investigated the effects of VR exposure therapy reducing anxiety due to COVID-19 infection in three participants. Anxiety symptoms decreased significantly at post-treatment; phobic symptoms (i.e. fear of COVID-19 infection) decreased over time but the reduction was statistically non-significant.

One non-RCT (Zhang, Che, Guo, and Lei, Reference Zhang, Che, Guo and Lei2016a) demonstrated children with ASD significantly increased their ability to pay attention to others and level of language using, and scored higher on social skills compared with the control group post-treatment after receiving a 4-week VR attention bias modification programme. However, the long-term effects were unclear as there was no follow-up period.

In summary, studies primarily tested the efficacy of VR-based interventions in improving neurocognitive function in depression, social skills in ASD, and anxiety. Although feasibility and preliminary efficacy were demonstrated, more rigorous and longitudinal studies with larger sample sizes are needed to evaluate the efficacy of VR interventions.

Methodological quality

Results of the MMAT quality ratings are shown in Table 1. The methodology of many studies was poorly described and varied in quality across studies. High drop-out rates (i.e. above 20%) were seen in a quarter of the studies, ranging from 27% to 60%, which resulted in incomplete outcome data in these studies. Nearly one-third of included RCTs did not adequately report randomisation procedures, and less than half of RCTs had outcome assessors who were blind to the intervention provided. Most non-randomised controlled studies and case-series studies were poorly representative of the target population.

Discussion

We systematically and critically appraised current evidence evaluating the efficacy, acceptability, usability, and safety of DHTs across a broad range of mental health problems in China. We identified 39 studies published from 2009 to 2021 which examined 32 DHTs across a range of mental health problems. Of note, most studies were published in the past 5 years, indicating that digital mental health is receiving significant attention and is a fast-growing area of research in China. A quarter of the studies (11/39) were published in Chinese, which demonstrates that a significant number of studies would have been missed if a comprehensive search in Chinese language databases was not conducted; this is indeed a strength of the current study. Compared with papers published in English, Chinese language studies were predominantly RCTs (9/11) and mainly assessed cognitive training interventions (e.g. CCRT).

Comparison with the broader digital mental health filed

The Chinese studies targeted more often on schizophrenia (12 out of 39 included studies) and SUD (5/39) compared with the field in the Western countries (Miralles et al., Reference Miralles, Granell, Díaz-Sanahuja, Van Woensel, Bretón-López, Mira and Casteleyn2020) and LMICs (Carter et al., Reference Carter, Araya, Anjur, Deng and Naslund2021; Fu et al., Reference Fu, Burger, Arjadi and Bockting2020) where depression was the most studied mental health problem. The different emphasis may reflect how the Chinese mental healthcare system is primarily focused on psychosis and the effort of the government initiated project to manage severe mental health problems (i.e. the ‘686’ programme; Liu et al., Reference Liu, Ma, He, Xie, Xu, Tang and Yu2011) and the extreme limited access to treatment for people with SUD (Liang et al., Reference Liang, Han, Du, Zhao and Hser2018a). Another explanation may be the researcher deemed digital intervention as an adjunct treatment to medication, as most of the studies focused on neurocognitive training and social skills training, which are domains where medication is less effective (Choi, Wykes, & Kurtz, Reference Choi, Wykes and Kurtz2013; Erhart, Marder, & Carpenter, Reference Erhart, Marder and Carpenter2006; Kirkpatrick, Fenton, Carpenter, & Marder, Reference Kirkpatrick, Fenton, Carpenter and Marder2006). However, some types of digital mental health tools that have been studied in schizophrenia in high-income countries, such as smartphone app-based treatment, symptom monitoring, and self-management tools (Firth & Torous, Reference Firth and Torous2015; Rus-Calafell & Schneider, Reference Rus-Calafell and Schneider2020), have not been developed and tested in China. Unlike the West, cultural-specific conditions have been studied, such as TKS, as well as the target of shame in social anxiety disorders. Although studies included in this review covered a range of prevalent mental health problems in China, there are notable gaps in the development of DHTs for some mental health problems (e.g. bipolar disorder). Moreover, studies disproportionately focused on adult population, while child and adolescent mental health problems received less attention.

Computerised programmes, internet-based programmes, and smartphone apps were the most studied DHTs in this review. This might be attributed to higher access and usage of such technologies compared with other DHTs (e.g. VR). For example, the prevalence of smartphones in China is high, and a significant expansion of the smartphone app market has been witnessed in recent years (Chou et al., Reference Chou, Chung and Lam2019; Yin et al., Reference Yin, Wardenaar, Wang, Wang, Chen, Zhang and Schoevers2020). However, rural settings have fewer internet and smartphone users compared with those living in an urban setting (China Internet Network Information Centre, 2021). Therefore, text messaging interventions might be more feasible in rural or remote settings at this stage (Xu et al., Reference Xu, Xiao, He, Caine, Gloyd, Simoni and Gong2019). Additionally, as fewer studies have been conducted in rural areas, the feasibility and effectiveness of DHTs in such settings are poorly understood. Furthermore, similar to Western countries, the efficacy of the majority of apps available on commercial app stores has not been tested using rigorous clinical trial methodology (Torous et al., Reference Torous, Andersson, Bertagnoli, Christensen, Cuijpers, Firth and Arean2019; Yin et al., Reference Yin, Wardenaar, Wang, Wang, Chen, Zhang and Schoevers2020). Moreover, some commonly used DHTs have not been tested in China so far, such as wearables.

The second difference is the lack of using co-production approach on DHT development, with co-production was only reported in one included study (Schulte et al., Reference Schulte, Liang, Wu, Lan, Tsay, Du and Hser2016). Systematic co-production involving both mental health professionals and people with mental health problems is considered critical to optimise acceptability (Bucci, Schwannauer, & Berry, Reference Bucci, Schwannauer and Berry2019). Acceptability and usability were evaluated only in internet-based programmes, smartphone apps, and text messaging interventions. In general, DHTs were acceptable and usable among Chinese people with mental health problems, although contradictory results were reported, especially for smartphone apps for SUDs, indicating that refinement in design and development is necessary to promote acceptability and usability. Co-production has been increasingly implemented in Western countries; however, in China, this approach is primarily utilised in policy making and governance (Li, Hu, Liu, & Fang, Reference Li, Hu, Liu and Fang2019; Miao, Schwarz, & Schwarz, Reference Miao, Schwarz and Schwarz2021) and is relatively new to healthcare research. Future studies should involve co-production in the development and testing process of DHTs to increase engagement and meet service users’ needs (Bucci et al., Reference Bucci, Schwannauer and Berry2019).

Finally, the methodological quality of the Chinese studies was less rigorous, which may increase the risk of a type 1 statistical error and might be the reason why most of the efficacy studies were positive. For example, all of the included CCRT studies in schizophrenia showed positive effects on improving neurocognitive and functional outcomes, when previous systematic reviews indicated only small to moderate effects and many trials reported negative results (Kambeitz-Ilankovic et al., Reference Kambeitz-Ilankovic, Betz, Dominke, Haas, Subramaniam, Fisher and Kambeitz2019; Vita et al., Reference Vita, Barlati, Ceraso, Nibbio, Ariu, Deste and Wykes2021). The current review indicated DHTs may play a role in improving symptom, neurocognitive, and functional outcomes in mental health problems in the Chinese population. However, due to the diversity of the studies, no definitive conclusions can be drawn about the effectiveness of identified DHTs. More rigorously designed RCT studies with sufficiently powered samples and long-term follow up are needed to further investigate the effectiveness of DHTs for mental health problems in China and their sustained effects.

Strengths and limitations

To our knowledge, this is the first review that conducted a comprehensive search in Chinese language databases and included studies published in the Chinese language in the field of digital mental health. Therefore, the cross-cultural generalisability of our findings is robust. Another strength is the inclusion of both quantitative and qualitative design studies. There are also some limitations of the current review. First, differences in outcome assessment, intervention, and comparator conditions precluded meta-analysis. Second, almost all of the included studies reported positive findings, which may suggest publication bias of the review. Finally, there was considerable variation in methodological quality. Nearly half of the RCTs did not report adequate randomisation procedures. Most studies had small sample sizes and were underpowered to detect significant differences, should differences be present. Thus, it is not yet possible to make definitive conclusions about the effectiveness of identified DHTs for mental health problems in China based on the current state of evidence.

Future research

Future research using larger and more rigorously designed RCTs to evaluate the effectiveness of DHTs is needed, ideally examining a broader range of mental health problems. More large-scale studies with long-term follow-up periods are needed to understand the sustained effects of DHTs. As one of the major advantages of DHTs is its potential to benefit people living in rural/remote settings, more studies in rural areas are needed. Considering most mental health problems develop during adolescence (Kessler et al., Reference Kessler, Angermeyer, Anthony, Graaf, Demyttenaere, Gasquet and Üstün2007), more attention is needed in this group to understand how young people may benefit from DHTs. Finally, in order to ensure DHTs meet the needs of the end-user, and to maximise the likelihood of engagement, the process of designing DHTs should adopt a systematic co-production approach that involve all stakeholders.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721003731

Financial support

This research received no specific grant from any funding agency, commercial, or not-for-profit sectors.

Conflict of interest

SL is Mental Health Lead of Health Innovation Manchester, Director of Affigo CiC (not for profit) and Strategic Advisor of Kooth PLC. JF is supported by a University of Manchester Presidential Fellowship (P123958) and a UK Research and Innovation Future Leaders Fellowship (MR/T021780/1) and has consulted for ParachuteBH on a separate project. SB is Director of Affigo CiC (not-for-profit) and is supported by an NIHR Research Professorship. XZ and XC declare no conflicts of interest.

References

An, S., Feng, X., Dai, Y., Bo, H., Wang, X., Li, M., … Wei, L. (2017). Development and evaluation of a speech-generating AAC mobile app for minimally verbal children with autism spectrum disorder in Mainland China. Molecular Autism, 8(52), 1–12. https://doi.org/10.1186/s13229-017-0165-5.CrossRefGoogle ScholarPubMed
Bucci, S., Schwannauer, M., & Berry, N. (2019). The digital revolution and its impact on mental health care. Psychology and Psychotherapy: Theory, Research and Practice, 92(2), 277297. https://doi.org/10.1111/papt.12222.CrossRefGoogle ScholarPubMed
Byrne, L. K., Pan, L., McCabe, M., Mellor, D., & Xu, Y. (2015). Assessment of a six-week computer-based remediation program for social cognition in chronic schizophrenia. Shanghai Archives of Psychiatry, 27(5), 296306. https://doi.org/10.11919/j.issn.1002-0829.215095.Google ScholarPubMed
Byrne, L. K., Peng, D., McCabe, M., Mellor, D., Zhang, J., Zhang, T., … Xu, Y. (2013). Does practice make perfect? Results from a Chinese feasibility study of cognitive remediation in schizophrenia. Neuropsychological Rehabilitation, 23(4), 580596. https://doi.org/10.1080/09602011.2013.799075.CrossRefGoogle Scholar
Cai, Y., Gong, W., He, H., Hughes, J. P., Simoni, J., Xiao, S., … Xu, D. (Roman). (2020). Mobile texting and lay health supporters to improve schizophrenia care in a resource-poor community in rural China (LEAN trial): Randomized controlled trial extended implementation. Journal of Medical Internet Research, 22(12), e22631. https://doi.org/10.2196/22631.CrossRefGoogle Scholar
Carter, H., Araya, R., Anjur, K., Deng, D., & Naslund, J. A. (2021). The emergence of digital mental health in low-income and middle-income countries: A review of recent advances and implications for the treatment and prevention of mental disorders. Journal of Psychiatric Research, 133, 223246. https://doi.org/10.1016/j.jpsychires.2020.12.016.CrossRefGoogle ScholarPubMed
Chen, H., Mishara, B. L., & Liu, X. X. (2010). A pilot study of Mobile telephone message interventions with suicide attempters in China. Crisis, 31(2), 109112. https://doi.org/10.1027/0227-5910/a000017.CrossRefGoogle ScholarPubMed
Chen, H., Rodriguez, M. A., Qian, M., Kishimoto, T., Lin, M., & Berger, T. (2020). Predictors of treatment outcomes and adherence in internet-based cognitive behavioral therapy for social anxiety in China. Behavioural and Cognitive Psychotherapy, 48(3), 291303. https://doi.org/10.1017/S1352465819000730.CrossRefGoogle ScholarPubMed
China Internet Network Information Centre. (2021). The 47th China Statistical Report on Internet Development. Retrieved from https://www.cnnic.com.cn/IDR/ReportDownloads/202104/P020210420557302172744.pdf.Google Scholar
Choi, K.-H., Wykes, T., & Kurtz, M. M. (2013). Adjunctive pharmacotherapy for cognitive deficits in schizophrenia: Meta-analytical investigation of efficacy. The British Journal of Psychiatry, 203(3), 172178. https://doi.org/10.1192/bjp.bp.111.107359.CrossRefGoogle Scholar
Chou, W., Chung, R., & Lam, T. (2019). Chinese consumers at the forefront of digital technologies. Retrieved from Deloitte website https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/technology-media-telecommunications/deloitte-cn-2018-mobile-consumer-survey-en-190121.pdf.Google Scholar
Erhart, S. M., Marder, S. R., & Carpenter, W. T. (2006). Treatment of schizophrenia negative symptoms: Future prospects. Schizophrenia Bulletin, 32(2), 234237. https://doi.org/10.1093/schbul/sbj055.CrossRefGoogle ScholarPubMed
Firth, J., & Torous, J. (2015). Smartphone apps for schizophrenia: A systematic review. JMIR mHealth and uHealth, 3(4), e102. https://doi.org/10.2196/mhealth.4930.CrossRefGoogle ScholarPubMed
Fu, Z., Burger, H., Arjadi, R., & Bockting, C. L. H. (2020). Effectiveness of digital psychological interventions for mental health problems in low-income and middle-income countries: A systematic review and meta-analysis. The Lancet Psychiatry, 7(10), 851864. https://doi.org/10.1016/S2215-0366(20)30256-X.CrossRefGoogle ScholarPubMed
Gilbody, S., Littlewood, E., Hewitt, C., Brierley, G., Tharmanathan, P., Araya, R., … White, D. (2015). Computerised cognitive behaviour therapy (cCBT) as treatment for depression in primary care (REEACT trial): Large scale pragmatic randomised controlled trial. British Medical Journal, 351, h5627. https://doi.org/10.1136/bmj.h5627.CrossRefGoogle ScholarPubMed
Han, H., Zhang, J. Y., Hser, Y.-I., Liang, D., Li, X., Wang, S. S., … Zhao, M. (2018). Feasibility of a mobile phone app to support recovery from addiction in China: Secondary analysis of a pilot study. JMIR mHealth and uHealth, 6(2), e46. https://doi.org/10.2196/mhealth.8388.CrossRefGoogle ScholarPubMed
Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., … Pluye, P. (2018a). The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Education for Information, 34(4), 285291. https://doi.org/10.3233/EFI-180221.CrossRefGoogle Scholar
Hu, G., Yang, C., Lu, Q., Zhao, J., Zhu, M., & Yi, Z. (2021). Ji Suan Ji Hua Ren Zhi Jiao Zheng Zhi Liao Dui Jing Shen Fen Lie Zheng Huan Zhe Ren Zhi Gong Neng De Ying Xiang [Effects of computerized cognitive correction therapy on cognitive function of schizophrenia]. Journal of Shanghai Jiao Tong University (Medical Science), 41(5), 622627. https://doi.org/10.3969/j.issn.1674-8115.2021.05.010.Google Scholar
Huang, Y., Wang, Y., Wang, H., Liu, Z., Yu, X., Yan, J., … Wu, Y. (2019). Prevalence of mental disorders in China: A cross-sectional epidemiological study. The Lancet Psychiatry, 6(3), 211224. https://doi.org/10.1016/S2215-0366(18)30511-X.CrossRefGoogle ScholarPubMed
Kambeitz-Ilankovic, L., Betz, L. T., Dominke, C., Haas, S. S., Subramaniam, K., Fisher, M., … Kambeitz, J. (2019). Multi-outcome meta-analysis (MOMA) of cognitive remediation in schizophrenia: Revisiting the relevance of human coaching and elucidating interplay between multiple outcomes. Neuroscience & Biobehavioral Reviews, 107, 828845. https://doi.org/10.1016/j.neubiorev.2019.09.031.CrossRefGoogle ScholarPubMed
Kaonga, N. N., & Morgan, J. (2019). Common themes and emerging trends for the use of technology to support mental health and psychosocial well-being in limited resource settings: A review of the literature. Psychiatry Research, 281, 112594. https://doi.org/10.1016/j.psychres.2019.112594.CrossRefGoogle ScholarPubMed
Kessler, R. C., Angermeyer, M., Anthony, J. C., Graaf, R. D., Demyttenaere, K., Gasquet, I., … Üstün, T. B. (2007). Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization's World Mental Health Survey Initiative. World Psychiatry, 6(3), 168176.Google ScholarPubMed
Kirkpatrick, B., Fenton, W. S., Carpenter, W. T. Jr., & Marder, S. R. (2006). The NIMH-MATRICS consensus statement on negative symptoms. Schizophrenia Bulletin, 32(2), 214219. https://doi.org/10.1093/schbul/sbj053.CrossRefGoogle ScholarPubMed
Kishimoto, T., Krieger, T., Berger, T., Qian, M., Chen, H., & Yang, Y. (2016). Internet-based cognitive behavioral therapy for social anxiety with and without guidance compared to a wait list in China: A propensity score study. Psychotherapy and Psychosomatics, 85(5), 317319. https://doi.org/10.1159/000446584.CrossRefGoogle ScholarPubMed
Kleinknecht, R. A., Dinnel, D. L., Kleinknecht, E. E., Hiruma, N., & Harada, N. (1997). Cultural factors in social anxiety: A comparison of social phobia symptoms and Taijin Kyofusho. Journal of Anxiety Disorders, 11(2), 157177. https://doi.org/10.1016/S0887-6185(97)00004-2.CrossRefGoogle ScholarPubMed
Li, B., Hu, B., Liu, T., & Fang, L. (2019). Can co-production be state-led? Policy pilots in four Chinese cities. Environment and Urbanization, 31(1), 249266. https://doi.org/10.1177/0956247818797276.CrossRefGoogle Scholar
Li, Y., Liao, W., Zhou, X., Wang, Y., & Qian, Q. (2017). Zhu Yi Que Xian Duo Dong Zhanɡ Ai Huan Er Duo Wei Ji Suan Ji Hua Zhi Xing Gong Neng Xun Lian De Tan Suo Xing Sui Ji Dui Zhao Yan Jiu [Multi-dimensional executive function by computer training in children with attention deficit hyperactivity disorder: A pilot randomized controlled trial]. Chinese Journal of Psychiatry, 50(6), 445451. https://doi.org/10.3760/cma.j.issn.1006-7884.2017.06.010.Google Scholar
Liang, D., Han, H., Du, J., Zhao, M., & Hser, Y.-I. (2018a). A pilot study of a smartphone application supporting recovery from drug addiction. Journal of Substance Abuse Treatment, 88, 5158. https://doi.org/10.1016/j.jsat.2018.02.006.CrossRefGoogle Scholar
Liang, D., Mays, V. M., & Hwang, W.-C. (2018b). Integrated mental health services in China: Challenges and planning for the future. Health Policy and Planning, 33(1), 107122. https://doi.org/10.1093/heapol/czx137.CrossRefGoogle Scholar
Liao, L., Ding, Y., Wu, X., Zhou, Y., & Pan, G. (2016). Ji Suan Ji Hua Ren Zhi Jiao Zheng Xun Lian Dui Jing Shen Fen Lie Zheng De Sui Ji Dui Zhao Shi Yan [A randomized controlled trial of the computerized cognitive remediation therapy to adult schizophrenia]. Chinese Journal of Clinical Psychology, 24(05), 954957. https://doi.org/10.16128/j.cnki.1005-3611.2016.05.042.Google Scholar
Lin, L.-Y., Wang, K., Kishimoto, T., Rodriguez, M., Qian, M., Yang, Y., … Tian, C. (2020). An internet-based intervention for individuals with social anxiety and different levels of Taijin Kyofusho in China. Journal of Cross-Cultural Psychology, 51(5), 387402. https://doi.org/10.1177/0022022120920720.CrossRefGoogle Scholar
Liu, C., Chen, L., Xie, B., Yan, J., Jin, T., & Wu, Z. (2013). Number and characteristics of medical professionals working in Chinese mental health facilities. Shanghai Archives of Psychiatry, 25(5), 277285. https://doi.org/10.3969/j.issn.1002-0829.2013.05.003.Google ScholarPubMed
Liu, J., Ma, H., He, Y.-L., Xie, B., Xu, Y.-F., Tang, H.-Y., … Yu, X. (2011). Mental health system in China: History, recent service reform and future challenges. World Psychiatry, 10(3), 210216. https://doi.org/10.1002/j.2051-5545.2011.tb00059.x.CrossRefGoogle ScholarPubMed
Liu, S., Yang, L., Zhang, C., Xiang, Y.-T., Liu, Z., Hu, S., & Zhang, B. (2020). Online mental health services in China during the COVID-19 outbreak. The Lancet Psychiatry, 7(4), e17e18. https://doi.org/10.1016/S2215-0366(20)30077-8.CrossRefGoogle ScholarPubMed
Lu, L. (2019). Zhong Guo Jing Shen Wei Sheng Xue Ke Fa Zhan De Hui Gu Yu Zhan Wang [Retrospect and prospect of the development of mental health discipline in China]. Journal of Peking University (Health Sciences), 51(3), 379383. https://doi.org/10.19723/j.issn.1671-167X.2019.03.001.Google Scholar
Lyu, S., Zhang, L., Zhong, S., Jia, Y., Lai, S., Shen, S., … Miao, H. (2020). Ji Yu Xu Ni Xian Shi Zhu Yi Li Xun Lian Dui Yi Yu Fa Zuo Huan Zhe Ren Zhi Gong Neng Gan Yu De Yan Jiu [Effect of virtual reality attention training on cognitive function in patients with depressive episodes]. Chinese Journal of Psychiatry, 53(05), 384391. https://doi.org/10.3760/cma.j.cn113661-20191009-00348.Google Scholar
Ma, H. (2012). Integration of hospital and community services – The ‘686 Project’ – Is a crucial component in the reform of China's mental health services. Shanghai Archives of Psychiatry, 24(3), 172174. https://doi.org/10.3969/j.issn.1002-0829.2012.03.007.Google ScholarPubMed
Mental Health Foundation. (2015). Fundamental Facts about Mental Health 2015. Retrieved from https://www.mentalhealth.org.uk/publications/fundamental-facts-about-mental-health-2015.Google Scholar
Miao, Q., Schwarz, S., & Schwarz, G. (2021). Responding to COVID-19: Community volunteerism and coproduction in China. World Development, 137, 105128. https://doi.org/10.1016/j.worlddev.2020.105128.CrossRefGoogle ScholarPubMed
Miralles, I., Granell, C., Díaz-Sanahuja, L., Van Woensel, W., Bretón-López, J., Mira, A., … Casteleyn, S. (2020). Smartphone apps for the treatment of mental disorders: Systematic review. JMIR mHealth and uHealth, 8(4), e14897. https://doi.org/10.2196/14897.CrossRefGoogle ScholarPubMed
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, T. P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097.CrossRefGoogle ScholarPubMed
Naslund, J. A., Aschbrenner, K. A., Araya, R., Marsch, L. A., Unützer, J., Patel, V., & Bartels, S. J. (2017). Digital technology for treating and preventing mental disorders in low-income and middle-income countries: A narrative review of the literature. The Lancet Psychiatry, 4(6), 486500. https://doi.org/10.1016/S2215-0366(17)30096-2.CrossRefGoogle ScholarPubMed
Patel, U., Sobowale, K., Fan, J., Liu, N., Kuwabara, S., Lei, Z., … Van Voorhees, B. (2017). Cultural considerations for the adaptation of an Internet-based intervention for depression prevention in Mainland China. International Journal of Adolescent Medicine and Health, 29(5), 1–7. https://doi.org/10.1515/ijamh-2015-0099.Google Scholar
Que, J., Lu, L., & Shi, L. (2019). Development and challenges of mental health in China. General Psychiatry, 32(1), e100053. https://doi.org/10.1136/gpsych-2019-100053.CrossRefGoogle ScholarPubMed
Ren, Z., Li, X., Zhao, L., Yu, X., Li, Z., Lai, L., … Jiang, G. (2016). Yi Yu Zheng Wang Lao Hua Zi Zhu Gan Yu De Xiao Guo Ji Zuo Yong Ji Zhi Yi Han Hua MoodGYM Wei Li [Effectiveness and mechanism of internet-based self-help intervention for depression: The Chinese version of MoodGYM]. Acta Psychologica Sinica, 48(7), 818832.CrossRefGoogle Scholar
Rus-Calafell, M., & Schneider, S. (2020). Are we there yet?! – A literature review of recent digital technology advances for the treatment of early psychosis. mHealth, 6, 33. https://doi.org/10.21037/mhealth.2019.09.14.CrossRefGoogle ScholarPubMed
Schulte, M., Liang, D., Wu, F., Lan, Y.-C., Tsay, W., Du, J., … Hser, Y.-I. (2016). A smartphone application supporting recovery from heroin addiction: Perspectives of patients and providers in China, Taiwan, and the USA. Journal of Neuroimmune Pharmacology, 11(3), 511522.CrossRefGoogle ScholarPubMed
Sit, H. F., Hall, B. J., Wang, Y., Zhang, Y., Ju, Q., & Gan, Y. (2020). The effect of positive mental imagery training on Chinese university students with depression: A pilot study. Current Psychology. https://doi.org/10.1007/s12144-020-00867-1.CrossRefGoogle Scholar
Sun, X., Yang, R., Zhang, Q., Xiao, J., Li, C., & Cui, L. (2019). Cognitive bias modification for interpretation training via smartphones for social anxiety in Chinese undergraduates. Journal of Experimental Psychopathology, 10(3), 204380871987527. https://doi.org/10.1177/2043808719875274.CrossRefGoogle Scholar
Sun, Y., Li, Y., Wang, J., Chen, Q., Bazzano, A. N., & Cao, F. (2021). Effectiveness of smartphone-based mindfulness training on maternal perinatal depression: Randomized controlled trial. Journal of Medical Internet Research, 23(1), e23410. https://doi.org/10.2196/23410.CrossRefGoogle ScholarPubMed
Tan, S., Zhu, X., Fan, H., Tan, Y., Yang, F., Wang, Z., … Wykes, T. (2019). Who will benefit from computerized cognitive remediation therapy? Evidence from a multisite randomized controlled study in schizophrenia. Psychological Medicine, 50(10), 16331643. https://doi.org/10.1017/S0033291719001594.CrossRefGoogle Scholar
Torous, J., Andersson, G., Bertagnoli, A., Christensen, H., Cuijpers, P., Firth, J., … Arean, P. A. (2019). Towards a consensus around standards for smartphone apps and digital mental health. World Psychiatry, 18(1), 9798. https://doi.org/10.1002/wps.20592.CrossRefGoogle ScholarPubMed
Torous, J., Myrick, K. J., Rauseo-Ricupero, N., & Firth, J. (2020). Digital mental health and COVID-19: Using technology today to accelerate the curve on access and quality tomorrow. JMIR Mental Health, 7(3), e18848. https://doi.org/10.2196/18848.CrossRefGoogle ScholarPubMed
Vigo, D., Thornicroft, G., & Atun, R. (2016). Estimating the true global burden of mental illness. The Lancet Psychiatry, 3(2), 171178. https://doi.org/10.1016/S2215-0366(15)00505-2.CrossRefGoogle ScholarPubMed
Vita, A., Barlati, S., Ceraso, A., Nibbio, G., Ariu, C., Deste, G., & Wykes, T. (2021). Effectiveness, core elements, and moderators of response of cognitive remediation for schizophrenia: A systematic review and meta-analysis of randomized clinical trials. JAMA Psychiatry, 78(8), 848858. https://doi.org/10.1001/jamapsychiatry.2021.0620.CrossRefGoogle ScholarPubMed
Wang, H., Xiao, S., Xu, D., Li, Q., Nie, J., Yuan, Y., … Gong, W. (2017). A qualitative study on experiences of using SMS services among schizophrenia patients and their families in rural communities. Journal of Nursing Science, 32(8), 8992. https://doi.org/10.3870/j.issn.1001-4152.2017.08.089.Google Scholar
Wang, H., Zhao, Q., Mu, W., Rodriguez, M., Qian, M., & Berger, T. (2020). The effect of shame on patients with social anxiety disorder in internet-based cognitive behavioral therapy: Randomized controlled trial. JMIR Mental Health, 7(7), e15797. https://doi.org/10.2196/15797.CrossRefGoogle ScholarPubMed
Wang, Z., Wang, J., & Maercker, A. (2013a). Chuang Shang Jing Li Zhe De Wang Luo Zi Zhu Gan Yu Cheng Xu De Shi Yong Yan Jiu [An internet-based self-help intervention program application for traumatized persons]. Chinese Mental Health Journal, 27(08), 583590. https://doi.org/10.3969/j.issn.1000-6729.2013.08.006.Google Scholar
Wang, Z., Wang, J., & Maercker, A. (2013b). Chinese my trauma recovery, a web-based intervention for traumatized persons in two parallel samples: Randomized controlled trial. Journal of Medical Internet Research, 15(9), e213. https://doi.org/10.2196/jmir.2690.CrossRefGoogle Scholar
Wang, Z., Wang, J., & Maercker, A. (2016). Program use and outcome change in a web-based trauma intervention: Individual and social factors. Journal of Medical Internet Research, 18(9), e243. https://doi.org/10.2196/jmir.5839.CrossRefGoogle Scholar
Wu, Q., Zhao, L., & Ye, X.-C. (2016). Shortage of healthcare professionals in China. British Medical Journal, 354(i4860). https://doi.org/10.1136/bmj.i4860.CrossRefGoogle ScholarPubMed
Xiang, Y.-T., Ng, C. H., Yu, X., & Wang, G. (2018). Rethinking progress and challenges of mental health care in China. World Psychiatry, 17(2), 231232. https://doi.org/10.1002/wps.20500.CrossRefGoogle ScholarPubMed
Xu, D. (Roman), Xiao, S., He, H., Caine, E. D., Gloyd, S., Simoni, J., … Gong, W. (2019). Lay health supporters aided by mobile text messaging to improve adherence, symptoms, and functioning among people with schizophrenia in a resource-poor community in rural China (LEAN): A randomized controlled trial. PLoS Medicine, 16(4), e1002785. https://doi.org/10.1371/journal.pmed.1002785.CrossRefGoogle Scholar
Xu, X., Chen, S., Chen, J., Chen, Z., Fu, L., Song, D., … Jiang, H. (2021). Feasibility and preliminary efficacy of a community-based addiction rehabilitation electronic system in substance use disorder: Pilot randomized controlled trial. JMIR mHealth and uHealth, 9(4), e21087. https://doi.org/10.2196/21087.CrossRefGoogle ScholarPubMed
Yang, R., Cui, L., Li, F., Xiao, J., Zhang, Q., & Oei, T. P. S. (2017). Effects of cognitive bias modification training via smartphones. Frontiers in Psychology, 8, 1370. https://doi.org/10.3389/fpsyg.2017.01370.CrossRefGoogle ScholarPubMed
Yeung, A., Wang, F., Feng, F., Zhang, J., Cooper, A., Hong, L., … Fava, M. (2018). Outcomes of an online computerized cognitive behavioral treatment program for treating Chinese patients with depression: A pilot study. Asian Journal of Psychiatry, 38, 102107. https://doi.org/10.1016/j.ajp.2017.11.007.CrossRefGoogle ScholarPubMed
Yin, H., Wardenaar, K. J., Wang, Y., Wang, N., Chen, W., Zhang, Y., … Schoevers, R. A. (2020). Mobile mental health apps in China: Systematic app store search. Journal of Medical Internet Research, 22(7), e14915. https://doi.org/10.2196/14915.CrossRefGoogle ScholarPubMed
Yip, W., & Hsiao, W. (2014). Harnessing the privatisation of China's fragmented health-care delivery. The Lancet, 384(9945), 805818. https://doi.org/10.1016/S0140-6736(14)61120-X.CrossRefGoogle ScholarPubMed
Zhang, C., Yang, L., Liu, S., Xu, Y., Zheng, H., & Zhang, B. (2021). One-week self-guided internet cognitive behavioral treatments for insomnia in adults with situational insomnia during the COVID-19 outbreak. Frontiers in Neuroscience, 14, 1–9. https://doi.org/10.3389/fnins.2020.622749.CrossRefGoogle ScholarPubMed
Zhang, F., Che, W., Guo, C., & Lei, X. (2016a). Xu Ni Xian Shi Ji Shu Zai Gao Gong Neng Gu Du Zheng Er Tonɡ Tong Ban Jiao Wang Xun Lian Zhong De Ying Yong: Zhu Yi Li Pian Xiang Jiao Zheng [The application of virtual reality technology in the training of peer interaction in children with high functioning autism: Attentional bias modification]. Chinese Journal of Behavioral Medicine and Brain Science, 25(08), 754757. https://doi.org/10.3760/cma.j.issn.1674-6554.2016.08.018.Google Scholar
Zhang, L., Xu, C., Chen, H., & Chen, M. (2016b). Ji Suan Ji Hua Ren Zhi Xun Lian Dui Man Xing Zhu Yuan Jing Shen Fen Lie Zheng Huan Zhe Ren Zhi Gong Neng De Ying Xiang [Effects of computerized cognitive rehabilitation training on cognitive function in chronic schizophrenia inpatients]. Journal of Neuroscience and Mental Health, 16(6), 698–701. https://doi.org/10.3969/j.issn.1009-6574.2016.06.020.Google Scholar
Zhang, S., Xia, X., Li, S., Shen, L., Liu, J., Zhao, L., & Chen, C. (2019). Using technology-based learning tool to train facial expression recognition and emotion understanding skills of Chinese pre-schoolers with autism spectrum disorder. International Journal of Developmental Disabilities, 65(5), 378386. https://doi.org/10.1080/20473869.2019.1656384.CrossRefGoogle ScholarPubMed
Zhang, W., Paudel, D., Shi, R., Liang, J., Liu, J., Zeng, X., … Zhang, B. (2020). Virtual reality exposure therapy (VRET) for anxiety due to fear of COVID-19 infection: A case series. Neuropsychiatric Disease and Treatment, 16, 26692675. https://doi.org/10.2147/NDT.S276203.CrossRefGoogle ScholarPubMed
Zhu, C., Sun, J., Tang, J., Jiang, C., Zhang, Z., & Shi, J. (2018a). Ji Suan Ji Fu Chu Ren Zhi Jiao Zheng Zhi Liao Dui Kang Fu Qi Jing Shen Fen Lie Zheng Huan Zhe Ren Zhi Gong Neng Zi Zun Shui Ping Ji She Hui Gong Neng De Ying Xiang [Effect of computer-assisted cognitive remediation therapy on the improvement of cognitive function level of selfesteem and social performance in schizophrenia patients during recovery period]. Chinese General Practice, 21(16), 20032008. https://doi.org/10.3969/j.issn.1007-9572.2018.16.020.Google Scholar
Zhu, C, Sun, J, & Wang, Y. (2020a). Ji Suan Ji Fu Chu Ren Zhi Jiao Zheng Zhi Liao Lian He Kang Yi Yu Yao Dui Huan Jie Qi Yi Yu Zheng Huan Zhe Ren Zhi Gong Neng De Liao Xiao [Effect of computer-assisted cognitive remediation therapy on cognition in recovering patients with major depressive disorder]. Chin J Health Manage, 14(2), 142147. https://doi.org/10.3760/cma.j.cn115624-20190514-00216.Google Scholar
Zhu, X., Fan, H., Fan, F., Zhao, Y., Tan, Y., Yang, F., … Tan, S. (2020b). Improving social functioning in community-dwelling patients with schizophrenia: A randomized controlled computer cognitive remediation therapy trial with six months follow-up. Psychiatry Research, 287, 112913. https://doi.org/10.1016/j.psychres.2020.112913.CrossRefGoogle Scholar
Zhu, X., Li, M., Liu, P., Chang, R., Wang, Q., & Liu, J. (2020c). A mobile health application-based strategy for enhancing adherence to antipsychotic medication in schizophrenia. Archives of Psychiatric Nursing, 34(6), 472480. https://doi.org/10.1016/j.apnu.2020.08.001.CrossRefGoogle Scholar
Zhu, Y., Jiang, H., Su, H., Zhong, N., Li, R., Li, X., … Zhao, M. (2018b). A newly designed mobile-based computerized cognitive addiction therapy app for the improvement of cognition impairments and risk decision making in methamphetamine use disorder: Randomized controlled trial. JMIR mHealth and uHealth, 6(6), e10292. https://doi.org/10.2196/10292.CrossRefGoogle Scholar
Figure 0

Fig. 1. PRISMA flow chart of study selection.

Figure 1

Table 1. Characteristics of included studies (organised by type of digital health technologies)

Supplementary material: File

Zhang et al. supplementary material

Zhang et al. supplementary material 1

Download Zhang et al. supplementary material(File)
File 14.6 KB
Supplementary material: File

Zhang et al. supplementary material

Zhang et al. supplementary material 2

Download Zhang et al. supplementary material(File)
File 13.3 KB