The National Institute for Health and Care Excellence defines self-harm as any act of self-injury or poisoning, irrespective of the motivation behind the act [1]. It is a growing concern that can have great physical, psychological [2], and societal [3] costs. Notably, self-harm has been identified as a significant and persistent predictor of suicide [4]. In recent years, the lifetime prevalence of self-harm in the general English population has seen a sharp increase from 2.4% in 2000 to 6.4% in 2014; this was most common in young adult females who reported an increase in prevalence from 6.5% to 19.7% [5]. Furthermore, given that individuals are often reluctant to disclose their self-harm behaviors due to the shame and stigma associated with it [6], rates of self-harm may be even higher than what these figures suggest [7].

Tørmoen et al [8] surveyed 11,440 young people aged 14-17 years in Norway and found that only 34% of those who had self-harmed had ever sought professional help, indicating that help-seeking is low among those who self-harm [9,10]. Concerns over being perceived as “attention-seeking” or “crazy” and difficulty talking about their self-harm behaviors have been identified as some of the barriers to seek support by adolescents [11]. Furthermore, a lack of effective interventions for self-harm creates barriers to receive support when an individual seeks professional help. The National Institute for Health and Care Excellence guidelines advise against the use of pharmacological treatments for self-harm, instead recommending psychological interventions tailored to self-harm that may involve problem solving, cognitive behavioral or psychodynamic elements [12]. Despite this, to date, there is limited high-quality evidence suggesting that psychological or pharmacological interventions for self-harm are effective [13,14]. Moreover, increased pressure on services and the resulting difficulties with the availability and accessibility of these interventions can further prevent individuals from receiving support [15].

The use of mobile health (mHealth) may help overcome the barriers to treatment accessibility and availability. mHealth is a branch of eHealth, defined by the Global Observatory for eHealth as “medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices” [16]. Given the ubiquity of mobile phone ownership [17,18], providing mental health support in this way has the potential to reach many individuals who may not be receiving help for self-harm. mHealth offers multiple possibilities, including self-help smartphone apps, SMS text messaging with a support service, physical symptom tracking through wearable technologies, and receiving virtual therapy [19]. Clough and Casey [20] found that mHealth users felt that receiving virtual mHealth therapy was more beneficial compared with face-to-face therapy, particularly highlighting the freedom they felt to be completely open and honest with their therapist. mHealth tools also have merit as standalone interventions, with some studies reporting reductions in symptoms of mental health difficulties, including anxiety [21], schizophrenia [22], depression [23], and borderline personality disorder [24].

Studies investigating the efficacy of mHealth interventions for managing self-harm have also been reviewed but they are limited. Witt et al [25] identified only one study that included outcome measures of an mHealth intervention for self-harm, whereas Melia et al [26] identified 2. These reviews focused on randomized controlled trials (RCTs) and pre- and poststudies. Arshad et al [27] focused more closely on self-harm and identified 22 studies; however, this was still limited by their decision to exclude qualitative studies and those where self-harm was not the primary outcome. A broader scoping review will help to identify more mHealth tools available for managing self-harm and broaden our knowledge of them.

This scoping review aims to (1) identify mHealth interventions for self-harm within the literature, (2) understand the types and features of interventions that have been developed and evaluated, (3) highlight research findings around mHealth interventions for self-harm, and (4) determine what outcomes are typically used to assess the efficacy of interventions.

A detailed methodology can be found in the review protocol [28]. The following databases were searched in April 2020: Embase, PubMed, PsycINFO, PsycEXTRA, Web of Science, and the Cochrane Library. The reference lists of all papers identified in the searches were also screened. Multimedia Appendix 1 describes the full and detailed search strategy.

After duplicates were removed, the titles and abstracts were initially screened according to the aims of this review and were progressed for a full screening if they met the following inclusion criteria: (1) the study described an mHealth intervention (eg, SMS text messaging, phone calls, or websites accessible through a mobile device) designed to have a direct (ie, if the intervention was designed for self-harm or for people who self-harm) or indirect (if self-harm was measured as an outcome) treatment effect and (2) the paper was in English.

The full texts of the papers that met these criteria were then screened. Before screening the title and abstract, a pilot screening was performed by all 3 reviewers (BC, JT, and IG) on 20 papers selected at random. An interrated reliability check of at least 75% agreement was required to progress the papers to full screening. Initially, 80% agreement was achieved, and the remaining papers were briefly discussed until 100% agreement was achieved. Each paper was screened by at least two reviewers, with a third reviewer resolving any inconsistencies. During the title and abstract screening, there was 98% agreement between the 2 reviewers on each paper, with the others being discussed and resolved again. The full texts of the progressed papers were screened for eligibility.

The reviewers extracted predefined data regarding the study details (eg, year and country), participants (eg, number, age, and ethnicity), type of mHealth intervention, study design, measures, and outcomes. Both before and after data extraction, consistency was checked between reviewers using a random sample of papers. Data extraction was an iterative process in which categories were added or amended in accordance with the aims of the review.

The search results are summarized in Figure 1. A total of 295 papers were identified. After duplicates were removed, 78% (229/295) of titles and abstracts were left to be screened. About 35% (79/229) of titles and abstracts progressed to a full-text screening, resulting in 54% (43/79) of papers being excluded. Of these, 51% (22/43) did not present an mHealth intervention for self-harm, 21% (9/43) were systematic reviews that did not identify any papers not already identified by our search, and 19% (8/43) were protocols for studies for which a full text had since become available. Of the remaining 4 papers, 2 (5%) were replies or comments on other studies, 1 (2%) was a content analysis of apps that were commercially available with no references to an evidence base, and 1 (2%) was a description of an app that had already been identified. A total of 36 papers met the inclusion criteria and are summarized in Table 1.

The 36 papers related to 35 separate studies, 2 of which were published from the same study with one paper detailing the quantitative findings [36] and the other the qualitative findings [37]. They were therefore not removed as duplicates; however, as the study details were the same, the study characteristics were merged to not present the same information twice.

A total of 12 papers reported protocols. The corresponding authors were contacted to request any update or preliminary findings; a preprint paper was received from one, so the protocol was replaced with this and the data were extracted. The remaining 11 protocols had no further data at the time of this review (April-June 2020).

The most common study design was the RCT (20/35, 57%), with most papers published between 2014 and 2020 (33/35, 94%). Studies were most commonly conducted in Europe (14/35, 40%) and North America (7/35, 20%). Most studies measured self-harm using various self-report questionnaires (18/35, 51%) and looked at both suicidal and nonsuicidal self-harm (19/35, 54%).

The study outcomes are summarized in Table 4. Most studies had multiple outcomes related to self-harm (21/35, 60%), suicide attempts (19/35, 54%), suicidal ideation (16/35, 46%), intervention experience (16/35, 46%), and engagement with the intervention (13/35, 37%). Other mental health issues such as depression (16/35, 46%) and anxiety (9/35, 26%) were also considered. Outcomes related to self-harm mostly focused on episode frequency (14/21, 67%), whereas others focused on repeated presentations to hospital (5/21, 24%) or self-harm thoughts or urges (4/21, 19%).

This scoping review identified 36 papers relating to 34 separate mHealth tools for managing self-harm. Papers were primarily RCTs and protocols published in Europe or North America within the last 6 years. This recent increase in papers reflects the growing interest in developing evidence-based mHealth interventions to improve access to psychological therapies. The large number of protocols suggests that this trend will continue as more findings are published in the coming years. Participants were mostly White adult females recruited from clinical populations, with only one nonbinary participant across all the studies, and many did not report the ethnicity of their participants. This is concerning given the high prevalence of self-harm found in both ethnic [68] and gender minorities [69]. It is possible that other nonbinary or gender-diverse individuals participated in these studies, but they were not truly represented in the way that the researchers assessed or reported participant demographics.

Depression and anxiety were the 2 most highly studied comorbidities, which is consistent with research suggesting strong correlations between these disorders and self-harm [70]. The interventions most commonly studied were not blended with any face-to-face support and were mostly text or call-based services or apps used on mobile phones or smartphones. Considering the ubiquity of both mobile phones [17,71] and smartphones [71], this is a positive finding and suggests that there are indeed mHealth interventions that could be more widely accessed. Interestingly, no interventions designed for use on other devices, such as wearable technologies, have been identified. This is despite research suggesting that they are acceptable for treating mental health issues among those who do not typically engage with mental health services [72]. However, this is still a relatively new area, and wearable devices designed to treat or help manage mental health difficulties are predicted to increase over the next few years [73].

Several studies did not specify any underpinning therapeutic models informing the content of their intervention, which raises concerns given the unhelpful and even dangerous advice that has been found in other freely available mental health apps [74]. Similarly, less than a third of the interventions were developed with individuals who have lived experience of self-harm, despite evidence suggesting that this could lead to more effective interventions being developed. Given the expertise of those with lived experience of self-harm, their input is essential [75,76].

Most studies testing interventions reported overall promising findings, suggesting that mHealth can be a viable tool for people struggling with self-harm. The study outcomes largely promoted a reduction in self-harm frequency over and above others, such as a reduction in self-harm urges or severity. Although reduced frequency is a common measure of self-harm recovery within research, it has been argued that it is not advisable to rely solely on this; a reduction in self-harm episodes may mean that each episode has become more severe or has been replaced with a different type of self-destructive behavior [77]. Overall, there needs to be a more consistent framework to assess outcomes from self-harm research, with further research looking into the maintenance of positive outcomes. Similarly, there was considerable variation in the tools used to measure self-harm across the studies. This makes comparisons between studies difficult; therefore, greater consistency may also be beneficial.

Another commonly observed finding was the clinicians’ favorable attitudes toward the intervention. This reflects overall positive attitudes and an eagerness to incorporate technology into practice found in research on clinicians’ attitudes toward technology in mental health care [78]. This is important considering that there is research highlighting that clinicians’ attitudes are pivotal in intervention implementation [79].

A barrier to the implementation of blended interventions that required clinician involvement was the lack of engagement that people who self-harm have with mental health services. This is consistent with the body of literature that corroborates the lack of professional help-seeking among people who self-harm [8-11] and further emphasizes the need for mHealth interventions for self-harm that individuals can access easily and discretely. Despite many studies having positive outcomes, it seems that not many of the interventions studied are readily available to the general public or even to those attending mental health services. Moreover, few papers made this information apparent, so information on availability was sought from internet and app store searches and by contacting the authors of the papers.

This review identified several limitations in the current literature on mHealth tools for managing self-harm. Notably, research thus far has been limited to White adult females from western societies, yet self-harm has been identified as a significant issue among minority groups [68,69], highlighting the need to diversify research by recruiting understudied groups such as males and minority populations who may also benefit from mHealth interventions. It is also important for future studies to report the ethnicity of participants. Similarly, participants have mostly been from clinical samples; however, given that people who self-harm do not often seek professional help, it is possible that findings from clinical samples may not necessarily be generalizable to wider populations who self-harm. Therefore, it is important to assess the efficacy of interventions in community samples. It is also essential for more intervention developers to collaborate with people who have lived experience of self-harm, given the limited instances thus far highlighted in this review.

Another notable point is that the measurements of self-harm recovery were typically restricted to a reduction in the frequency of episodes and, although this may be a useful assessment, it may also be worth considering measuring other elements as well, such as the severity of self-harming episodes or any other substitute self-destructive behaviors.

Another consideration to take forward from this review is the reliance on RCTs to evaluate digital interventions. Although RCTs have long been considered the gold standard method, the pace at which digital interventions develop and evolve means that the data can be outdated before the trial has been completed [80-82]. Following this, it may be prudent for future research to also consider different study designs, such as pre- and posttests that can keep up with the rapid development of digital interventions. Furthermore, RCTs can indicate whether an intervention is effective but may be limited in their ability to explore the reason [83]. Therefore, it may also be beneficial for future research to apply the NIMH’s experimental therapeutics approach or use qualitative studies that can contribute further to the understanding of how and why certain interventions are effective as well as whether they are safe and do no harm. Similarly, the application of the experimental therapeutic approach may contribute further to the understanding of how and why certain interventions are effective [84]. Future work should also focus on the implementation and dissemination of effective interventions, following the lack of availability of interventions within the papers in this review.

As the purpose of this review was to collate the data available on mHealth tools for managing self-harm, there was no scope to conduct a quality assessment of the included studies. This means that we cannot verify that the research included here is of sufficient quality to draw concrete inferences from. This review may also have been limited by the decision to not include any papers for which there was no English version available. Nonetheless, this review offers insight into the current evidence base for mHealth interventions for self-harm.

This review has synthesized the current evidence for mHealth tools for managing self-harm. Overall, there are useful interventions that have been developed to promote recovery from self-harm. However, certain limitations pose challenges in drawing firm conclusions from the included studies. Suggestions for how future research can improve upon this have been made, in the hope of developing a robust evidence base so that clinicians and users are better equipped to make informed decisions about which mHealth tools to use. This will hopefully help to overcome some of the barriers that people who self-harm face in accessing support.