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.Philip J. Batterham is supported by NHMRC fellowship 1035262. Helen Christensen is supported by NHMRC Fellowship 1056964

Detecting suicidality on Twitter

Twitter is increasingly investigated as a means of detecting mental health status, including depression and suicidality, in the population. However, validated and reliable methods are not yet fully established. This study aimed to examine whether the level of concern for a suicide-related post on Twitter could be determined based solely on the content of the post, as judged by human coders and then replicated by machine learning. From 18th February 2014 to 23rd April 2014, Twitter was monitored for a series of suicide-related phrases and terms using the public Application Program Interface (API). Matching tweets were stored in a data annotation tool developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO). During this time, 14,701 suicide-related tweets were collected: 14% were randomly (n = 2000) selected and divided into two equal sets (Set A and B) for coding by human researchers. Overall, 14% of suicide-related tweets were classified as ‘strongly concerning’, with the majority coded as ‘possibly concerning’ (56%) and the remainder (29%) considered ‘safe to ignore’. The overall agreement rate among the human coders was 76% (average κ = 0.55). Machine learning processes were subsequently applied to assess whether a ‘strongly concerning’ tweet could be identified automatically. The computer classifier correctly identified 80% of ‘strongly concerning’ tweets and showed increasing gains in accuracy; however, future improvements are necessary as a plateau was not reached as the amount of data increased. The current study demonstrated that it is possible to distinguish the level of concern among suicide-related tweets, using both human coders and an automatic machine classifier. Importantly, the machine classifier replicated the accuracy of the human coders. The findings confirmed that Twitter is used by individuals to express suicidality and that such posts evoked a level of concern that warranted further investigation. However, the predictive power for actual suicidal behaviour is not yet known and the findings do not directly identify targets for intervention.This project was supported in part by funding from the NSW Mental Health Commission and the NHMRC John Cade Fellowship 1056964. PJB and ALC are supported by the NHMRC Early Career Fellowships 1035262 and 1013199

A randomised controlled trial of a relationship-focussed mobile phone application for improving adolescents' mental health

Background: This study evaluated the acceptability and effectiveness of a relationship-focussed mobile phone application (WeClick) for improving depressive symptoms and other mental health outcomes in adolescents. Methods: A randomised controlled trial involving 193 youth (M age: 14.82, SD: 0.94, 86.5% female) from Australia was conducted. Youth were recruited via the Internet and randomly allocated to the intervention or a 4-week wait list control condition, stratified for age and gender. The primary outcome was change in depressive symptom scores measured using the Patient Health Questionnaire for Adolescents (PHQ-A) at baseline, 4-week post-test and 12-week follow-up. Secondary outcomes included anxiety, psychological distress, wellbeing, help-seeking intentions for mental health, social self-efficacy and social support. Participants in the intervention condition received access to the intervention for four weeks. Thematic analysis was utilised to identify and examine acceptability. Results: The change in PHQ-A scores from baseline to 4-week post-test did not differ significantly (d = 0.26, p = .138) between the intervention (Mchange = 2.9, SD = 5.3) and wait list control conditions (Mchange = 1.7, SD = 4.3). However, significant between-group improvements were observed in wellbeing (d = 0.37, p = .023), help-seeking intentions (d = 0.36, p = .016) and professional help-seeking intentions for mental health problems (d = 0.36, p = .008). Increases in help-seeking intentions were sustained at follow-up in the intervention condition. No differential effects were found for generalised anxiety, separation anxiety, social self-efficacy or for any social support outcomes. Over 90% of participants indicated the app was enjoyable, interesting and easy to use. The app provided ‘advice and direction’ (n = 42; 46.15%), an ‘opportunity for self-reflection’ (n = 33; 36.3%) and ‘normalised experiences’ (n = 21; 23.1%). Conclusions: The WeClick app was found to be effective for improving wellbeing and help-seeking intentions for mental health in adolescents. A larger, adequately powered trial is now required to establish differential effects on depressive symptoms. This trial was registered with the Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12618001982202. Keywords: Adolescence; depression; mental health; e-health; relationships.P.J.B. is supported by NHMRC Fellowship 1158707. A.L.C. is supported by NHMRC Fellowship 1122544. A.W-S. is supported by a NSW Health Early Career Fellowship. H.C. is supported by NHMRC Fellowship 1155614

Effectiveness of Self-guided Tailored Implementation Strategies in Integrating and Embedding Internet-Based Cognitive Behavioral Therapy in Routine Mental Health Care: Results of a Multicenter Stepped-Wedge Cluster Randomized Trial

BACKGROUND: Internet-based cognitive behavioral therapy (iCBT) services for common mental health disorders have been found to be effective. There is a need for strategies that improve implementation in routine practice. One-size-fits-all strategies are likely to be ineffective. Tailored implementation is considered as a promising approach. The self-guided integrated theory-based Framework for intervention tailoring strategies toolkit (ItFits-toolkit) supports local implementers in developing tailored implementation strategies. Tailoring involves identifying local barriers; matching selected barriers to implementation strategies; developing an actionable work plan; and applying, monitoring, and adapting where necessary. OBJECTIVE: This study aimed to compare the effectiveness of the ItFits-toolkit with implementation-as-usual (IAU) in implementing iCBT services in 12 routine mental health care organizations in 9 countries in Europe and Australia. METHODS: A stepped-wedge cluster randomized trial design with repeated measures was applied. The trial period lasted 30 months. The primary outcome was the normalization of iCBT delivery by service providers (therapists, referrers, IT developers, and administrators), which was measured with the Normalization Measure Development as a proxy for implementation success. A 3-level linear mixed-effects modeling was applied to estimate the effects. iCBT service uptake (referral and treatment completion rates) and implementation effort (hours) were used as secondary outcomes. The perceived satisfaction (Client Satisfaction Questionnaire), usability (System Usability Scale), and impact of the ItFits-toolkit by implementers were used to assess the acceptability of the ItFits-toolkit. RESULTS: In total, 456 mental health service providers were included in this study. Compared with IAU, the ItFits-toolkit had a small positive statistically significant effect on normalization levels in service providers (mean 0.09, SD 0.04; P=.02; Cohen d=0.12). The uptake of iCBT by patients was similar to that of IAU. Implementers did not spend more time on implementation work when using the ItFits-toolkit and generally regarded the ItFits-toolkit as usable and were satisfied with it. CONCLUSIONS: The ItFits-toolkit performed better than the usual implementation activities in implementing iCBT services in routine practice. There is practical utility in the ItFits-toolkit for supporting implementers in developing and applying effective tailored implementation strategies. However, the effect on normalization levels among mental health service providers was small. These findings warrant modesty regarding the effectiveness of self-guided tailored implementation of iCBT services in routine practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT03652883; https://clinicaltrials.gov/ct2/show/NCT03652883. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-020-04686-4

Is e-health the answer to gaps in adolescent mental health service provision?

Purpose of review Depression and anxiety are prevalent among adolescents; however, many young people do not seek help from professional services. This is due, in part, to the inadequacies of existing healthcare systems. This article aims to review the current evidence for e-health interventions for depression and anxiety in youth, as a potential solution to the gaps in mental health service provision. Recent findings Five randomized controlled trials reporting on e-health interventions for youth depression or anxiety were identified. Of these, two trials focused exclusively on anxiety symptoms, and three trials examined both anxiety and depression. The majority of trials assessed online cognitive behavioral therapy and focused on prevention rather than treatment. In all but one trial, results demonstrated positive effects for the e-health interventions, relative to the control. Summary There is growing evidence for the effectiveness of online cognitive behaviour therapy interventions for reducing the level of anxiety and depressive symptoms in adolescents aged between 12 and 18 years, when delivered in school and clinical settings, with some level of supervision. However, there are a number of gaps in the literature. More research is needed to strengthen the evidence base for prevention and treatment programs that are delivered via the internet, particularly for depression

Pilot evaluation of the Sleep Ninja : a smartphone application for adolescent insomnia symptoms

Objectives The aim of this study was to test the feasibility, acceptability and preliminary effects of a recently developed smartphone application, Sleep Ninja, for adolescent sleep difficulties. Setting The study was conducted online with Australian individuals recruited through the community. Participants Participants were 50 young people aged 12-16 years with sleep difficulties. Design A single-Arm pre-post design was used to evaluate feasibility, acceptability and sleep and mental health variables at baseline and postintervention. Intervention Cognitive-behavioural therapy for insomnia informed the development of the Sleep Ninja. The core strategies covered by the app are psychoeducation, stimulus control, sleep hygiene and sleep-related cognitive therapy. It includes six training sessions (lessons), a sleep tracking function, recommended bedtimes based on sleep guidelines, reminders to start a wind-down routine each night, a series of sleep tips and general information about sleep. Users progress through each training session and conclude the 6-week programme with a black belt in sleep. Outcome measures Feasibility was evaluated based on consent rates, adherence and attrition, acceptability was assessed using questionnaires and a poststudy interview, and sleep, depression and anxiety variables were assessed at baseline and postintervention. Results Data indicated that the Sleep Ninja is a feasible intervention and is acceptable to young people. Findings showed that there were significant improvements on sleep variables including insomnia (within-group effect size d=-0.90), sleep quality (d=-0.46), depression (d=-0.36) and anxiety (d=-0.41). Conclusions The Sleep Ninja is a promising intervention that could assist adolescents who experience sleep difficulties. A follow-up randomised controlled trial is now warranted

Comparative randomized trial of an online cognitive-behavioral therapy program and an online support group for depression and anxiety

This study examined the effects of an online cognitive behavior therapy (CBT) program (MoodGYM) compared with an online support group (MoodGarden) in decreasing symptoms of depression and anxiety, and improving dysfunctional thoughts, online social support, and CBT literacy in young adults. Thirty-nine university students (aged 18-25) with elevated scores on the Kessler Psychological Distress Scale were allocated to either the MoodGYM, MoodGarden or control condition. Relative to the control condition, participation in the MoodGYM group significantly improved anxiety symptoms and CBT literacy. Similarly, participation in the MoodGarden group significantly improved anxiety symptoms and online social support relative to the control condition. Although it appears that these online resources are beneficial, further research is needed to determine their long-term efficacy. Furthermore, qualitative participant evaluations indicated that improvements may need to be made to MoodGYM to ensure that young adults remain engaged with the program.7 page(s

A Linguistic Analysis of Suicide-Related Twitter Posts

Background: Suicide is a leading cause of death worldwide. Identifying those at risk and delivering timely interventions is challenging. Social media site Twitter is used to express suicidality. Automated linguistic analysis of suicide-related posts may help to differentiate those who require support or intervention from those who do not. Aims: This study aims to characterize the linguistic profiles of suicide-related Twitter posts. Method: Using a dataset of suicide-related Twitter posts previously coded for suicide risk by experts, Linguistic Inquiry and Word Count (LIWC) and regression analyses were conducted to determine differences in linguistic profiles. Results: When compared with matched non-suicide- related Twitter posts, strongly concerning suicide-related posts were characterized by a higher word count, increased use of first-person pronouns, and more references to death. When compared with safe-to-ignore suicide-related posts, strongly concerning suicide-related posts were characterized by increased use of first-person pronouns, greater anger, and increased focus on the present. Other differences were found. Limitations: The predictive validity of the identified features needs further testing before these results can be used for interventional purposes. Conclusion: This study demonstrates that strongly concerning suicide-related Twitter posts have unique linguistic profiles. The examination of Twitter data for the presence of such features may help to validate online risk assessments and determine those in need of further support or intervention.BOD is supported by an OPTYMISE Centre for Research Excellence Postdoctoral Fellowship and a Society for Mental Health Research 2015 Early Career Research Award. MEL is supported by a Centre for Research Excellence in Suicide Prevention (CRESP) Postdoctoral Fellowship and a Society for Mental Health Research 2015 Early Career Research Awar

Attitudes towards suicide attempts broadcast on social media: an exploratory study of Chinese microblogs

Introduction. Broadcasting a suicide attempt on social media has become a public health concern in many countries, particularly in China. In these cases, social media users are likely to be the first to witness the suicide attempt, and their attitudes may determine their likelihood of joining rescue efforts. This paper examines Chinese social media (Weibo) users' attitudes towards suicide attempts broadcast on Weibo

The rate of reply and nature of responses to suicide-related posts on Twitter

The social media platform Twitter has been used by individuals to communicate suicidal thoughts and intentions. Currently, the nature and rate of reply to this type of Twitter content is unknown. This brief report aimed to understand how Twitter users respond to suicide-related content as compared to non-suicide related content. Using a dataset of suicide and non-suicide related posts, replies, retweets and likes were analysed and compared. The content of the first replies to suicide-related posts were also reviewed. When compared to non-suicide related posts, those that were suicide-related received a significantly greater number of replies, with fewer retweets and likes. The rate of reply to the suicide-related posts was also significantly faster than that of the non-suicide related posts, with the average reply occurring within 1 h. Thematic analysis revealed that 62% of the first replies to suicidal posts were of a potentially helpful nature (e.g. discouraging suicide, caring, or clarifying), while 23% were dismissive or encouraging of the suicide. These findings indicate that Twitter users respond differently to suicidal content. Further research is needed to determine the effects of the replies on suicidal intentions or ideations, and whether this platform can be used to intervene, increase help-seeking, or provide anti-stigma campaigns