E-Health Interventions for Suicide Prevention

Many people at risk of suicide do not seek help before an attempt, and do not remain connected to health services following an attempt. E-health interventions are now being considered as a means to identify at-risk individuals, offer self-help through web interventions or to deliver proactive interventions in response to individuals’ posts on social media. In this article, we examine research studies which focus on these three aspects of suicide and the internet: the use of online screening for suicide, the effectiveness of e-health interventions aimed to manage suicidal thoughts, and newer studies which aim to proactively intervene when individuals at risk of suicide are identified by their social media postings. We conclude that online screening may have a role, although there is a need for additional robust controlled research to establish whether suicide screening can effectively reduce suicide-related outcomes, and in what settings online screening might be most effective. The effectiveness of Internet interventions may be increased if these interventions are designed to specifically target suicidal thoughts, rather than associated conditions such as depression. The evidence for the use of intervention practices using social media is possible, although validity, feasibility and implementation remains highly uncertain.


Introduction
E-health interventions for suicide prevention can be classed into three categories. First, the Internet can be used to help individuals self-screen: to identify whether they might be at risk for suicide or a mental health problem. Through screening and feedback, it may be possible to increase service use, by directing at-risk individuals who would not otherwise seek help to access appropriate evidence-based online programs or to access traditional mental health services [1]. Second, web applications, both guided and unguided, have been developed to provide psychological interventions to assist in reducing suicidal behaviour and lowering suicidal ideation. Guided interventions involve a therapist or a researcher assisting the user through the program either through email or over the telephone, whereas unguided are self-help, automated programs which can be initiated and used directly by the public. The third type of intervention is one where a person is considered to be at risk of suicide because of the nature of their social media use. Here, tweets, status updates, comments or posts indicative of suicide ideation are used to classify those at risk. Such content can be identified in real-time by other users or by computerised language processing and progress in this area has accelerated. The aims of the present paper are to review the evidence around these three styles of intervention. Three separate literature reviews were conducted. The first examined the evidence for whether online screening for suicide might be effective in reducing suicidal ideation and behaviours. The second reviewed web interventions, updating two recent reviews of web based suicide prevention [2,3] and distinguishing two approaches: web interventions that target suicidal behaviour and using depression therapies; and interventions that target suicidal behaviour using suicide-specific therapies. The final review examined the use of social media platforms for identifying those who may be at risk of suicide.

Methods
Comprehensive literature searches for all three reviews were conducted in March 2014 using the Medline, PsychInfo, and Cochrane Library databases. Conference abstracts, non-peer reviewed papers, non-English language papers, and PhD theses were excluded from all three reviews. All articles were screened for eligibility by two independent researchers. The specifics of each search are outlined below.

Identifying Screening Programs
Search terms indicative of internet technology (computer or computer-based or cyber or cyberspace or electronic or "electronic mail" or email or e-mail or internet or internet-based or net or online or virtual or web or web-based or web-based or "world wide web" or www or "social media" or "social network" or blog or forum), screening (screen* or assess*) and suicide (suicid*) were employed. The search resulted in 855 articles, of which 98 were excluded due to being in a non-English language or animal-based and a further 162 were excluded as duplicates. The remaining 595 abstracts were screened for relevance, with 78 papers identified as potentially meeting the criterion of reporting on the screening of individuals for suicidal ideation or behaviours using the internet. Full-text copies of these papers were then obtained for further scrutiny and reference checks conducted to identify papers that may have been missed in the search. After examining the full text of these articles, 47 did not meet the criteria of the screening review. Hierarchical reasons for exclusion were not being a peer-reviewed paper (11 papers), not using online data collection (20 papers), not including a measure of the respondent's suicidality (eight papers), not reporting on suicidality outcomes (seven papers), or being a review paper (one paper). One additional relevant paper was identified in reference checking, resulting in 32 papers from 30 studies that reported on online assessment of suicidal ideation or behaviours.

Identifying Web Programs
In addition to the databases stated above, the Centre for Research Excellence of Suicide Prevention (CRESP) Suicide Prevention Database (http://cresp.edu.au/databases/sprct) was also used for this review. Search terms indicative of suicide, self-harm and mobile or online applications were employed: "Self harm OR self-harm OR deliberate self-harm OR deliberate self poisoning OR self cutting OR self-inflicted wounds OR deliberate self cutting OR suicid* OR suicide gesture OR suicidal behavio* OR suicidal ideation OR suicide attempt OR self-mutilation OR auto-mutilation OR auto mutilation OR self-injury OR self-injurious behavio* OR self destructive behavio* OR self-poisoning and overdose OR drug overdose" in Title, Abstract, Keywords and "trials OR randomised controlled trials OR randomized controlled trials OR meta-analysis" in Title, Abstract, Keywords and "internet OR mobile OR web OR email OR e-mail OR online" in Title, Abstract, Keywords.
The search yielded a total of 198 abstracts which was reduced to 109 after the removal of duplicates. Of these, nine papers met inclusion criteria. Inclusion and exclusion criteria were applied in order to identify any internet or mobile-based interventions that included a measure of suicidal behaviour. The trials did not need to explicitly target those experiencing suicidal behaviours, but they were required to measure participants' level of suicidality prior to program commencement and following program completion. Studies examining non-suicidal self-injury were not included. Due to the low numbers of trials, studies without control or comparison groups were included in addition to trials including control groups. The control group could consist of a wait-list, treatment-as-usual, or another treatment. There was no restriction on participant age.
Studies were excluded if they did not include an intervention, if suicidality was not measured as a primary or secondary outcome, and if the intervention was not internet or mobile based. One paper was excluded as the research design and sample was identical to another paper written by the same authors. Further, the study led by Merry [4] employed the Kazdin Hopelessness Scale in place of a suicidal behaviour measure. Considering this scale is widely used as a proxy for suicidal ideation, the study was included.
Two of the studies in the review are not discussed further. These are: Marasinghe, et al. [5]; and Wagner, et al. [6]. The first was eliminated because it did not involve a web component. The second because it was difficult to discern the type of therapy, and the extent to which the intervention was delivered online (it was not clear whether both groups received a paper and pencil manual).  [7] classification of social media, the current review focused explicitly on blogs/microblogs (e.g., Twitter), and social networking sites (e.g., Facebook, Myspace, Bebo). Content communities (e.g., YouTube), virtual worlds (e.g., Second life), MMORGs (e.g., World of Warcraft) and collaborative projects (e.g., Pinterest) were excluded. Articles that related to online discussion forums, online support groups or internet message boards were also excluded. The search yielded 1934 following number of articles. Of these, only 13 papers met inclusion criteria. Papers published prior to 2000 (the onset of social media) were excluded alongside those that focused on non-suicidal self-injury, murder-suicides or mental illnesses such as depression, which may increase the risk of suicide. A search for similar articles was conducted on all relevant papers; however, this returned zero results. Citation lists for each included article was also screened for other related papers which yielded an additional three papers. The article titled "Mining Twitter for Suicide Prevention" [8] is not discussed further as the publication source could not be identified. A total of 15 papers were included.

Online Screening for Suicide Ideation
Of the 32 papers that met inclusion criteria, only six (19%) had direct relevance to online screening programs. The details of these papers are provided in Table 1. Of the remaining papers not detailed in the table, 23 (72%) focused on assessing risk factors or prevalence of suicidal ideation or behaviours using cross-sectional web surveys, while one paper reported on the cost-effectiveness of an online suicide prevention trial, one paper reported on the psychometric properties of an online behavioural health measure and another reported on a cross-sectional survey assessing reasons why people seek help for suicide online. All of the six papers on screening were based on studies from the United States. Five of the papers focused on young people, including four on university students and/or staff. Sample sizes ranged from 374-13155 (M: 2916, Median: 1010) and 45% of all participants were female. Most studies used the PHQ-9 [9] to assess suicidal ideation, usually in association with a lifetime suicide attempt item. The remainder used binary prevalence measures (i.e., presence/absence of suicidal ideation, suicide plan, or suicide attempt).
Three of the papers [10][11][12] reported on the use of an online screening program developed by the American Foundation for Suicide Prevention in the university setting. Overall, these studies reported that online screening was effective for identifying students with history of suicidal ideation or behaviours. The direct referral of at-risk students to in-person services, such as campus counsellors, was also found to be effective, although only a minority (ranging approximately 10%-20%) of at-risk students agreed to service referral and fewer received services. Another study [13] examined web-based screening among adolescents presenting at the emergency department of a children's hospital, finding that 65% of adolescents agreed to screening, resulting in a 70% increase in identification of psychiatric problems and a 47% increase in assessments by a social worker or psychiatrist. Lawrence, et al. [14] tested the feasibility of using the PHQ-9 within a web-based screener administered in outpatient clinics to screen for depression and suicidality among people with HIV. In this program, 14% reported some level of suicidal ideation and 3% were deemed high-risk and referred to services. Critically though, none of the identified studies included a control (non-screened) group for comparison, so they were unable to assess whether screening and referral alone was sufficient to increase help seeking or to improve mental health outcomes. One additional study examined the acceptability and risk of online screening for suicidal ideation and behaviours, also among university students [15]. This study concluded that such screening was generally acceptable, with few individuals (<3%) reporting negative experiences as a result of the screening. Individuals with previous suicidality had greater discomfort with the survey but such individuals also found it more thought-provoking than those without previous suicidality [15].

Web Applications for Suicide Prevention
Outlined in Table 2, six studies examined suicide outcomes arising from the use of a web intervention which targeted depression. Of these, two studies used adolescent samples. A pre-post study (n = 83) of general practice adolescent patients with suicidal ideation (but not frequent ideation or actual intent) found reductions in self-harm thoughts and depressive symptoms at 6 weeks and 12 weeks using the "PROJECT CATCH-IT" web program (CBT, IPT and parent workbook) [16]. A non-inferiority RCT (n = 94) of psychiatric outpatients with depression compared a computerised self-help program "SPARX" (CBT) with TAU (face to face therapy) and found that SPARX was non-inferior on levels of hopelessness (a proxy measure of suicide ideation) [4]. Four studies targeted adults. Two Australian studies examined changes in suicide ideation using a pre-post design. In the first, 299 general practice patients with suicidal ideation undertook an internet intervention for depression (CBT, homework and clinician contact) and the researchers found a reduction in suicidal ideation [17]. A pre-post study (n = 359) of depressed or suicidal general practice patients, evaluated the "Sadness Program" (internet based CBT, homework, supplementary resources) and found reduction in suicidal ideation [18]. A third study (n = 105) of depressed patients with suicidal thoughts employed a RCT methodology. The researchers compared "Deprexis" (online CBT for depression) with wait list controls and found decreased scores on depression, dysfunctional attitudes and improved quality of life, but no difference on either suicidal thoughts and behaviour [19]. A second RCT (four arms) (n = 155) of depressed callers to Lifeline compared web-based CBT, web-based CBT plus telephone call, telephone call back line and TAU found no differences in the rate at which suicidal thoughts dissipated between the four conditions [20].
Taken together these findings from both the adult and the adolescent studies show that suicide ideation drops over time in response to internet interventions (the Deprexis results is the only anomaly). The two RCT trials [19,20] also demonstrate that depression websites have specific effects on depression symptoms above those of the control conditions. However, the studies were not able to establish that suicide ideation falls as a function of the depression CBT provided by the interventions. In other words, suicide ideation seems to drop in both depression and control conditions. These findings do not rule out the possibility that websites which target specific characteristics of suicidal thoughts and behaviour such as rumination disruption or mindfulness may be more effective than either depression interventions or the "passage of time". There is only one RCT that has been published which focuses on a specific intervention for suicidal thoughts. This study, compared an online self-help program (6 modules of CBT with DBT, PST, MBCT as well as weekly assignments and automated motivational emails) with a waitlist control group and found reductions in suicidal thoughts and levels of hopelessness in favour of the self-help program [21] and improved cost effectiveness [22]. Table 3 outlines the relevant papers and associated findings. Of the 15 articles identified, six were classified as case studies examining either one individual's social media use (n = 5), or, the social media use of a single organisation (n = 1). In the single organisation case study, Boyce [23] described the social media use of a suicide prevention agency ("Samaritans") in the United States (U.S.). This case study provided brief recommendations for the future but did not include any data in regards to the reach, impact or effectiveness of such social media use. The remaining five individual case studies focused on young males aged between 13-29 years living in either China or the U.S., or location undisclosed. In 2011, Ruder and colleagues [24] presented commentary on a case involving a suicide note posted on Facebook by a 28 year old male who died by suicide. No data or social network analysis was conducted. Lehavot, Ben-Zeev and Neville [25] outlined the ethical considerations involved with a therapist using Facebook as a monitoring tool for postings of suicidal imagery in a male patient. No data or social network analysis was conducted. Ahuja, et al. [26] briefly discussed the suicidal postings of a male in his late twenties with a history of mental illness and the potential for offline social network intervention. No data or social network analysis was conducted. Using sentiment analysis software, Fu, Cheng, Wong and Yip [27] examined the reactions and patterns of information diffusion to a self-harm post made by a male using the Chinese social networking site "Sina Weibo". Li, Chau, and Wong [28] examined the relationship between blog posting intensity and language use to explore the suicidal processes of a 13 year old male. The specific blog site was not identified.

Social Media for Suicide Prevention
Four of the overall papers, including one brief correspondence, were non-systematic literature reviews discussing the use of social media for suicide prevention. Two of these reviews, published by Luxton and colleagues [29,30] described the social media platforms currently being used, or those with potential, for suicide prevention. The most recent review by Luxton, June and Fairall [29] found a total of 580 Twitter groups and 385 blog profiles on blogger.com designated to suicide prevention, one social networking site designed for social media prevention in the US (lifeline-gallery.org), and discussed the application of internal functions that could act as alert systems for potential suicide behavior. Luxton, et al. [29] also discussed the presence of suicide notes on social media, but did not refer to any data or particular studies. The third review [31] outlined the potential benefits and complications of social networking sites as a therapeutic intervention for self-injury but did not include any data or references to a specific platform. The brief correspondence [32] presented policy initiatives and internal functions of social media that could be adopted for suicide prevention.
Only five papers specifically examined the utilisation of social media for the tracking of suicide risk. These studies focused on either Twitter (n = 1), Myspace (n = 2), Facebook (n = 1) or other blog site (n = 1, Naver blog, Korea). The studies focusing on Myspace included self-reported adolescent samples with ages ranging between 13-24 years. Age range of participants in the other papers could not be determined. To our knowledge, the first study published in this area was an exploration of public Myspace blogs of New Zealand youth using automated sentiment analysis [33]. Cash and colleagues [34] further explored the content of suicidal statements made on the public Myspace profiles of adolescents aged between 13-24 years old. Using Twitter, Jashinsky, et al. [35] identified a significant association between suicide risk factors within Twitter and geographic specific suicide rates in the US. Using automated sentiment analysis software, Won, Myung, Song, Lee, et al. [36] examined whether two blog sentiments (suicide-related and dysphoria-related) along with traditional social, economic and meteorological variables significantly predicted suicide rates in Korea over a three year period (2008-2010). The final study [37] was a thematic content analysis of the portrayal of suicide and self-harm within a Facebook group in April 2009. Computerised sentiment analysis was not used. RCT; four arms: (1) Web-based CBT intervention; (2) Web-based CBT intervention + telephone call back; (3) proactive call back telephone line; (4) TAU.         Non-systematic literature review NA A discussion of the internet uses associated with self-injury.
No reference to particular social media platforms.
Luxton, et al. [29] Non-systematic literature review NA Social media has the potential to be used for suicide prevention within a public health framework although more research is needed on the degree and extent of the influence of social media for such purposes.
Cheng, et al. [32] Brief Correspondence NA Suggested that social networking sites could help prevent suicides by deleting pro-suicide groups re and automatically delivering private messages to those at risk.

Research
Huang, et al. [33] Computerised sentiment analysis with manual

Discussion
To date, there exists no controlled study testing whether online suicide screening can effectively increase levels of help seeking or reduce suicidal ideation or behaviours. Online screening for suicidal thoughts and behaviours appears to be acceptable among young people [15], supporting previous findings from a randomised controlled trial that screening for suicide risk using paper surveys does not increase the risk of suicidal thoughts or behaviours [38,39]. Although there is some evidence that screening is a feasible way to increase identification of suicidality and increase service referrals, research of online screening programs has not rigorously evaluated whether screening programs are effective compared to not screening. Furthermore, most of the programs reported in the literature have been conducted in selective populations, specifically, among university students in the United States. There is some evidence from paper-and-pencil assessments that suicide screening programs can be effective in specific settings with the availability of appropriate referral sources, with most of this research also conducted among young people (e.g., [40,41]). However, there is a need for additional robust controlled research to establish whether suicide screening can effectively reduce suicide-related outcomes, and in what settings screening might be effective [42][43][44]. None of the identified studies had a control condition, so they were unable to robustly assess whether online screening directly increased help seeking or led to improved mental health outcomes. This evidence gap appears to be especially conspicuous for online screening.
With respect to online suicide prevention programs, there is some evidence to suggest that suicide interventions via the web may be effective, but only if they specifically target suicidal content, rather than the associated symptoms of depression through CBT. There is no evidence CBT web-based programs do harm, so excluding those with suicide ideation from participation does not seem warranted for online programs in general. Further research targeting specific suicidal content on the web is warranted.
Although limited, there is evidence to suggest that social media platforms can be used to identify individuals or geographical areas at risk of suicide. The few studies conducted in this area have demonstrated that it is possible to use computerised sentiment analysis and data mining to identify users at risk of suicide; however, these studies have been conducted in publically available networks. Little is known about private online social networks such as those within Facebook. Furthermore, the prevalence and response rate of suicide notes posted on social media is yet to be clearly understood. The repost networks within social media may be a potential preventative method that could be activated quickly for effective intervention in emergency situations; although, current methodologies cannot fully disentangle whether suicidal postings always receive a response and if so, the nature of such responses. It is unknown if sharing thoughts and feelings this way is beneficial to an individual or whether they are placed at further risk. While evidence suggests that social media may be a viable tool for real-time monitoring of suicide risk on a large scale, future studies are needed to further validate this method, in addition to determining the underlying mechanisms for providing support via these channels.

Conclusions
This review highlights that there is currently limited evidence for the effectiveness of e-health interventions for suicide prevention. Whilst feasible, the reliability and preventative capacity of online screening for suicidality is yet to be clearly determined. Research in this area is incomplete. Furthermore, online therapeutic interventions do not appear to be effective unless content is targeted to suicidal thoughts and behavior; however, addressing risk factors, such as depression, through online CBT does not appear to cause harm. Lastly, social media shows significant potential for identifying those at risk of suicide in addition to mapping suicide contagion, although further validation research in this area is also needed.