Social media interventions for mental health: A scoping review

Background: Social media in healthcare has been widely used over the past few years with increasing popularity worldwide. Social media platforms can potentially act as a possible mental health service provider by improving communication, awareness and education. Objective: The aim of this scoping review is to describe the use of social media interventions for mental health and to provide an understanding of the current state of knowledge. Methods: The search platforms utilized for the scoping review were PubMed and IEEE. The inclusion criteria were as follows: research-based articles, primary means for mental health service is social media, and articles that specify mental disorders (depression, anxiety, etc). Results: After applying the inclusion and exclusion criteria on 190 articles, 30 were included for the purpose of this review. Twelve studies originated from the USA while six studies were from the UK. While fourteen papers were on general mental health disorders, twelve papers focused on depression. The results generally showed that social media interventions for mental health had advantages over the conventional treatments. A lack of studies from developing countries, and fewer studies including the elderly population and the assumption of digital literacy are among the identified gaps. Conclusion: Social media has the potential to act as a service provider for users with mental health issues. However, the effectiveness of this method has not been accurately measured and more research is required for evaluating the effectiveness of using social media for treatment over conventional methods.

population. By 2018, various social media platforms reported having 3.196 billion users 1 from around the globe. With this increase in number, there has also been a rise in the number of people utilizing social media for various purposes, especially health-related ones. The ability of social media interventions for physical and lifestyle management, diabetes management, asthma and obesity control are well known and widely used 2 . Most recently the ability of social media to act as a mental health service provider has been explored 2 . This association is important as mental disorders are one of the prominent causes of disability according to WHO and around 450 million people worldwide suffered from various mental health problems as of 2018 3 .
According to a report by Care Quality Commission in 2017, young people are not receiving timely care for their mental health issues and as a result have to wait for weeks and months to get access to a psychiatric consultant, which is very risky 4 . One possible solution for this problem is to utilize social media as a mental health service provider.
With mental health being a highly stigmatized topic, patients need a lot of support and encouragement from people to acknowledge the presence of it and talk about it openly, all of which can be provided by various platforms of social media 5 . The anonymity of social media can make mentally ill patients more comfortable as well 5 .
Social media offers accessibility to information from around the world and better communication and rapid response, which is crucial for mental illnesses 5 . Incorporating machine learning can help in the early detection and prediction of mental illness from the activities of a user in their social media account.
The purpose of this scoping review is to describe the existing literature that deals with social media interventions for mental health. We anticipate this work will help researchers, psychologists and policy makers to understand the role and use of social media interventions for mental health.

Identification and selection of study
The searches were carried out in two prominent electronic databases: Pubmed and IEEE.
Article selection was not subject to any constraints based on publication date. Medical subject heading (MeSH) was used to search in Pubmed. Searches comprised of the following keywords and related terms in different combinations: 'mental illness', 'mental health', 'mental health informatics', 'social network', social media', 'mental health interventions', and 'mental health services'.
The preliminary search from the two databases generated 190 citations according to the keywords used. 45 duplicates of those articles were removed. 76 articles were further removed by checking the titles and their relevance to our topic. The abstracts were checked and reviewed for the remaining 69 articles. After reading the abstracts, 38 papers were removed on the basis of not meeting the inclusion criteria. 31 articles were retrieved for a thorough full-text review among which 2 papers were removed. However, 1 article was added at this point as a result of examining the references. The finalized set of papers were thirty (see Figure 1).

Inclusion criteria and exclusion criteria
The inclusion criteria included the following: (i) research-based articles; (ii) primary means for mental health service is social media; (iii) articles that specify mental disorders (depression, anxiety, etc); (iv) people falling in any age group; (v) all social media platforms and (vi) the language of article should be English. Any commentary articles or reports were excluded. Also papers that investigated about mental illness that was caused as a result of another disease such as cancer, were excluded. In addition, the reference lists of the selected papers were searched.

Data Extraction
From the studies selected after reviewing the abstracts, the following information was extracted and recorded in an Excel spreadsheet: objective of the study, types of participants, different methods used, study design, intervention design, research location, and main outcomes of the study.

Results
Sample population range There were two types of studies based on the sample population type: studies with human subjects as sample and studies with data extracted online as the sample population. While the range of the sample size for human subjects varied from 20 adolescents to 526 adults, the sample size for posts differed from 132 tweets to 620,000 posts from various social media platforms. Studies with posts or tweets as the sample population collected the data from either one single source or made use of multiple sources.

Characteristics of studies
A summary of the selected articles is presented in Table 1. Of the thirty studies, ten studies discussed interventions that used social media, five were observational studies, fourteen studies employed machine learning methods and one randomized control trial.
The intervention based studies included three qualitative analyses studies that respectively examined the comments under YouTube videos related to schizoaffective disorders 8 , the posts from various social media platforms to understand what users expected in this exchange 28 , and the tweets to see why users use social media for mental health services 9 . Intervention based studies also included three thematic analyses 14,16,26 with various purposes such as assessing the power of Twitter for mental health and studying experiences of youth using social media for the same purpose. One longitudinal text analysis study 32 was conducted to explore timelines of users that committed suicide to identify patterns and another text outlined a framework that proposed an e-psychology platform 13 . In addition, there was a conceptual model 21 and an empirical model 27 to promote the social media platform for mental health services.
One randomized control trial 11 was carried out to develop and test a tool that helped prevent depression. Two surveys 10,19 were carried out to see the interest of psychiatric patients in using technology for treatment and how social media can help manage them.
Another study conducted a survey to study exclusively about the 'Historically black colleges and universities' (HBCU) population. One cross sectional study 6 to investigate the popularity of mobile apps for mental health and an online questionnaire 33 to study the effectiveness of social media interventions were included in the thirty articles.
Two studies 23,38 used Natural Language Processing (NLP) to extract and transform information in a post or comment to predict possible post-traumatic stress disorder (PTSD), depression, bipolar disorder, and seasonal affective disorder (SAD) and two studies 18,31 described about tools with machine learning that helped in the collection and exploration of big data.
Ten articles out of the thirty examined accounts or collected posts from different social media platforms rather than focusing on one of them 15,16,19,20,21,24,28,29,32,33 .
One study investigated comments under videos in YouTube 8

Study outcomes
All the studies involved arrived at the conclusion that social media has the potential to be used as a mental health service provider. Eight studies particularly illustrated how social networks can act as a mental health consultant and improve the wellbeing of people suffering from mental illnesses 5,18,21,22,24,29,30,31 . One study reported that 16% of the people they interviewed believed that the usage of apps related to mental health can bring positive results and help people understand more about their mental issues 4 . Four studies identified important themes that proved the use of social media to be convenient as they provide immediate response and continuous interaction and care 7,14,27,30 . The presence of peer support was an important factor for people approaching social media over traditional consultation methods. In a study where YouTube comments were examined, people with schizoaffective disorders posted comments under videos so that they could identify themselves with others and have support from fellow schizoaffective users 6 . Subjects of five studies confirmed they were more comfortable and less conscious using social media as their service providers for mental health 36,19,22,37,38 .
Fourteen papers used machine learning algorithms to analyze the data extracted online.
The results of the studies that used classification models to predict depression, yielded above 70% accuracy scores in all three cases 25,26,37 . One study categorized depression into four levels and through their model, classified a user with depression into any of the four categories 25 . The studies that employed Natural Language Processing techniques were able to extract information from the posts or comments to predict possible mental illnesses 18,23,38 . Another study that made use of a multilevel predictive model to detect depression with respect to another variable concluded that a multilevel predictor had more performance capability than a model that predicted depression single-handedly 34 .
Three studies that analyzed posts related to suicide found commonly that there is always an increase in the occurrence of posts or tweets nearing the time of suicide 28,31,35 and it is viable to detect and track suicide behaviors through social media.
Other studies focused their work on two particular populations:-Sexual and gender minorities (SGM) and Historically black colleges and universities (HBCU). The study that took 'sexual and gender minorities' (SGM) as their population described that SGM exhibited more negative feelings through Twitter compared to others 12 . The study that tested the use of an app specially designed for students in 'Historically black colleges and universities' (HBCU) called 'Soul Glow' reported that the app provided a platform for students with mental health issues to share their stories and interact openly 24 .

Patient reported experiences
One of the most prominent advantages of social media is its reach and accessibility.
McClellan, C. 28  Along with the advantages certain disadvantages or challenges were also emphasized.
Privacy is the most notorious among them. People are taking a very high risk of losing their confidentiality while discussing their mental illnesses online and public 6,4,25 .
Reliability of information available online is another risk. Patients should take care of the facts and figures they get online and make sure they are accurate and reliable. Also it is not necessary that a particular way of treatment can be applied or effective on everyone. However, more methods should be employed and studies be conducted to increase the prediction accuracy level. The social media enabled internet based apps for mental health services should be constructed in a way that deals with the user carefully and gently and should be very user friendly considering the fact that the users are mental health patients. The data the social media leaves behind can be an important source to the doctors or consultants to assess the emotional cycle and quality of life of their patients.
The success of using social media is subjective and depends solely on the users. The effectiveness or success rate has not been studied enough and can be considered as a future study area. Also, the potential of possible negative health impacts while using social media or apps needs to be taken into account. The continuous usage of social media can also leave a negative impact on patients, especially with mental health issues. Also usability and user experience of the apps that use social media as a primary tool for mental health service is a key factor. Too many technicalities should be avoided and make sure the users do not get frustrated, as they are dealing with people with mental illness.
For this purpose, digital literacy is vital, which will further help in providing better mental health services through technologies.
In the selected studies, little consideration was given to the elderly population. A good majority of the studies concentrated on the mental health of the youth, teenagers or adolescents. The elderly population is also vulnerable to mental health issues and future studies should include them as well.

Limitations
Scoping reviews are conducted to map the currently available knowledge in any area, thus spotting issues worthy of more research. This can help in exploring the research area initially during the development phase. However, a scoping review does not assess the quality of the studies included. There could have been limitations regarding the keywords used for searching. The language was a limitation for sure. Only English language was considered for this review when good quality papers might exist in several other languages as well. The lack of papers that assessed the effectiveness and efficiency of social media interventions for mental health is a limitation

Conclusions
With the increase in mental health illness worldwide and the stigma attached to it, social media can be valuable in the treatment and monitoring of mental illnesses. As social media is accessible and people are faceless in it, they can choose to openly talk about their illnesses online without the fear of being judged. Platforms such as Twitter, Facebook, and YouTube provide access to a large number of health data. Social media also provide good interaction, rapid response, and peer to peer support, which is lacking in the conventional health system. However, more research is necessary to fill the gaps identified in the current literature. Researchers and psychological specialists should take advantage of social media interventions and explore how they can be used to promote mental health and achieve positive results in the long run. Also, different platforms of social media can enhance their features keeping in mind that they are being used for health related purposes.

Declarations
The author declare that they have no competing interests.

Author details
Hamad Bin Khalifa University, Qatar   Figure 1 Scoping review flow diagram