Jennifer Nicholas

Mobile Apps for Bipolar Disorder: A Systematic Review of Features and Content Quality

Background With continued increases in smartphone ownership, researchers and clinicians are investigating the use of this technology to enhance the management of chronic illnesses such as bipolar disorder (BD). Smartphones can be used to deliver interventions and psychoeducation, supplement treatment, and enhance therapeutic reach in BD, as apps are cost-effective, accessible, anonymous, and convenient. While the evidence-based development of BD apps is in its infancy, there has been an explosion of publicly available apps. However, the opportunity for mHealth to assist in the self-management of BD is only feasible if apps are of appropriate quality. Objective Our aim was to identify the types of apps currently available for BD in the Google Play and iOS stores and to assess their features and the quality of their content. Methods A systematic review framework was applied to the search, screening, and assessment of apps. We searched the Australian Google Play and iOS stores for English-language apps developed for people with BD. The comprehensiveness and quality of information was assessed against core psychoeducation principles and current BD treatment guidelines. Management tools were evaluated with reference to the best-practice resources for the specific area. General app features, and privacy and security were also assessed. Results Of the 571 apps identified, 82 were included in the review. Of these, 32 apps provided information and the remaining 50 were management tools including screening and assessment (n=10), symptom monitoring (n=35), community support (n=4), and treatment (n=1). Not even a quarter of apps (18/82, 22%) addressed privacy and security by providing a privacy policy. Overall, apps providing information covered a third (4/11, 36%) of the core psychoeducation principles and even fewer (2/13, 15%) best-practice guidelines. Only a third (10/32, 31%) cited their information source. Neither comprehensiveness of psychoeducation information (r=-.11, P=.80) nor adherence to best-practice guidelines (r=-.02, P=.96) were significantly correlated with average user ratings. Symptom monitoring apps generally failed to monitor critical information such as medication (20/35, 57%) and sleep (18/35, 51%), and the majority of self-assessment apps did not use validated screening measures (6/10, 60%). Conclusions In general, the content of currently available apps for BD is not in line with practice guidelines or established self-management principles. Apps also fail to provide important information to help users assess their quality, with most lacking source citation and a privacy policy. Therefore, both consumers and clinicians should exercise caution with app selection. While mHealth offers great opportunities for the development of quality evidence-based mobile interventions, new frameworks for mobile mental health research are needed to ensure the timely availability of evidence-based apps to the public.

The Ins and Outs of an Online Bipolar Education Program: A Study of Program Attrition

Background The science of eHealth interventions is rapidly evolving. However, despite positive outcomes, evaluations of eHealth applications have thus far failed to explain the high attrition rates that are associated with some eHealth programs. Patient adherence remains an issue, and the science of attrition is still in its infancy. To our knowledge, there has been no in-depth qualitative study aimed at identifying the reasons for nonadherence to—and attrition from— online interventions. Objective This paper explores the predictors of attrition and participant-reported reasons for nonadherence to an online psycho-education program for people newly diagnosed with a bipolar disorder. Methods As part of an ongoing randomized controlled trial (RCT) evaluating an online psycho-education program for people newly diagnosed with a bipolar disorder, we undertook an in-depth qualitative study to identify participants’ reasons for nonadherence to, and attrition from, the online intervention as well as a quantitative study investigating predictors of attrition. Within the RCT, 370 participants were randomly allocated to 1 of 2 active interventions or an attention control condition. Descriptive analyses and chi-square tests were used to explore the completion rates of 358 participants, and standard regression analysis was used to identify predictors of attrition. The data from interviews with a subsample of 39 participants who did not complete the online program were analyzed using “thematic analysis” to identify patterns in reported reasons for attrition. Results Overall, 26.5% of the sample did not complete their assigned intervention. Standard multiple regression analysis revealed that young age (P= .004), male gender (P= .001), and clinical recruitment setting (P= .001) were significant predictors of attrition (F7,330= 8.08, P< .001). Thematic analysis of interview data from the noncompleter subsample revealed that difficulties associated with the acute phases of bipolar disorder, not wanting to think about one’s illness, and program factors such as the information being too general and not personally tailored were the major reasons for nonadherence. Conclusions The dropout rate was equivalent to other Internet interventions and to face-to-face therapy. Findings from our qualitative study provide participant-reported reasons for discontinuing the online intervention, which, in conjunction with the quantitative investigations about predictors, add to understanding about Internet interventions. However, further research is needed to determine whether there are systematic differences between those who complete and those who do not complete eHealth interventions. Ultimately, this may lead to the identification of population subgroups that most benefit from eHealth interventions and to informing the development of strategies to improve adherence. Trial Registration ACTRN12608000411347; http://www.anzctr.org.au/ACTRN12608000411347.aspx (Archived by WebCite at http://www.webcitation.org/5uX4uYwVN)

Effects of adjunctive peer support on perceptions of illness control and understanding in an online psychoeducation program for bipolar disorder: A randomised controlled trial

OBJECTIVESnTo examine the comparative effectiveness of an online psychoeducation program for people diagnosed with bipolar disorder within the previous 12 months, completed alone or with adjunctive peer support, on symptoms and perceived control over the illness.nnnMETHODnParticipants were randomly allocated to an eight-week online psychoeducation program (n=139), a psychoeducation program plus online peer support (n=134) or an attentional control condition (n=134).nnnRESULTSnIncreased perceptions of control, decreased perceptions of stigmatisation and significant improvements in levels of anxiety and depression, from pre- to post-intervention were found across all groups. There were no significant differences between groups on outcome measures, although a small clinical difference was found between the supported and unsupported conditions in depression symptoms and in functional impairment at the six-month follow-up. Adherence to the treatment program was significantly higher in the supported intervention than in the unsupported program. Gender and age were also significant predictors of adherence, with females and those over the age of 30 showing greater adherence.nnnLIMITATIONSnMood state at study entry was measured by self-report rather than by clinical interview.nnnCONCLUSIONSnThe pattern of outcomes suggests a primary influence of non-specific or common therapeutic factors across all three intervention groups. A personally tailored intervention may be more suitable for individuals recently diagnosed with bipolar disorder, and longer term coaching may increase program adherence and long-term improvement in symptoms and functioning.

A Systematic Assessment of Smartphone Tools for Suicide Prevention

Background Suicide is a leading cause of death globally, and there has been a rapid growth in the use of new technologies such as mobile health applications (apps) to help identify and support those at risk. However, it is not known whether these apps are evidence-based, or indeed contain potentially harmful content. This review examines the concordance of features in publicly available apps with current scientific evidence of effective suicide prevention strategies. Methods Apps referring to suicide or deliberate self-harm (DSH) were identified on the Android and iOS app stores. Systematic review methodology was employed to screen and review app content. App features were labelled using a coding scheme that reflected the broad range of evidence-based medical and population-based suicide prevention interventions. Best-practice for suicide prevention was based upon a World Health Organization report and supplemented by other reviews of the literature. Results One hundred and twenty-three apps referring to suicide were identified and downloaded for full review, 49 of which were found to contain at least one interactive suicide prevention feature. Most apps focused on obtaining support from friends and family (n = 27) and safety planning (n = 14). Of the different suicide prevention strategies contained within the apps, the strongest evidence in the literature was found for facilitating access to crisis support (n = 13). All reviewed apps contained at least one strategy that was broadly consistent with the evidence base or best-practice guidelines. Apps tended to focus on a single suicide prevention strategy (mean = 1.1), although safety plan apps provided the opportunity to provide a greater number of techniques (mean = 3.9). Potentially harmful content, such as listing lethal access to means or encouraging risky behaviour in a crisis, was also identified. Discussion Many suicide prevention apps are available, some of which provide elements of best practice, but none that provide comprehensive evidence-based support. Apps with potentially harmful content were also identified. Despite the number of apps available, and their varied purposes, there is a clear need to develop useful, pragmatic, and multifaceted mobile resources for this population. Clinicians should be wary in recommending apps, especially as potentially harmful content can be presented as helpful. Currently safety plan apps are the most comprehensive and evidence-informed, for example, “Safety Net” and “MoodTools—Depression Aid”.

The efficacy of smartphone‐based mental health interventions for depressive symptoms: a meta‐analysis of randomized controlled trials

The rapid advances and adoption of smartphone technology presents a novel opportunity for delivering mental health interventions on a population scale. Despite multi‐sector investment along with wide‐scale advertising and availability to the general population, the evidence supporting the use of smartphone apps in the treatment of depression has not been empirically evaluated. Thus, we conducted the first meta‐analysis of smartphone apps for depressive symptoms. An electronic database search in May 2017 identified 18 eligible randomized controlled trials of 22 smartphone apps, with outcome data from 3,414 participants. Depressive symptoms were reduced significantly more from smartphone apps than control conditions (g=0.38, 95% CI: 0.24‐0.52, p<0.001), with no evidence of publication bias. Smartphone interventions had a moderate positive effect in comparison to inactive controls (g=0.56, 95% CI: 0.38‐0.74), but only a small effect in comparison to active control conditions (g=0.22, 95% CI: 0.10‐0.33). Effects from smartphone‐only interventions were greater than from interventions which incorporated other human/computerized aspects along the smartphone component, although the difference was not statistically significant. The studies of cognitive training apps had a significantly smaller effect size on depression outcomes (p=0.004) than those of apps focusing on mental health. The use of mood monitoring softwares, or interventions based on cognitive behavioral therapy, or apps incorporating aspects of mindfulness training, did not affect significantly study effect sizes. Overall, these results indicate that smartphone devices are a promising self‐management tool for depression. Future research should aim to distil which aspects of these technologies produce beneficial effects, and for which populations.

Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials

BACKGROUNDnVarious psychological interventions are effective for reducing symptoms of anxiety when used alone, or as an adjunct to anti-anxiety medications. Recent studies have further indicated that smartphone-supported psychological interventions may also reduce anxiety, although the role of mobile devices in the treatment and management of anxiety disorders has yet to be established.nnnMETHODSnWe conducted a systematic review and meta-analysis of all randomized clinical trials (RCTs) reporting the effects of psychological interventions delivered via smartphone on symptoms of anxiety (sub-clinical or diagnosed anxiety disorders). A systematic search of major electronic databases conducted in November 2016 identified 9 eligible RCTs, with 1837 participants. Random-effects meta-analyses were used to calculate the standardized mean difference (as Hedges g) between smartphone interventions and control conditions.nnnRESULTSnSignificantly greater reductions in total anxiety scores were observed from smartphone interventions than control conditions (g=0.325, 95% C.I.=0.17-0.48, p<0.01), with no evidence of publication bias. Effect sizes from smartphone interventions were significantly greater when compared to waitlist/inactive controls (g=0.45, 95% C.I.=0.30-0.61, p<0.01) than active control conditions (g=0.19, 95% C.I.=0.07-0.31, p=0.003).nnnLIMITATIONSnThe extent to which smartphone interventions can match (or exceed) the efficacy of recognised treatments for anxiety has yet to established.nnnCONCLUSIONSnThis meta-analysis shows that psychological interventions delivered via smartphone devices can reduce anxiety. Future research should aim to develop pragmatic methods for implementing smartphone-based support for people with anxiety, while also comparing the efficacy of these interventions to standard face-to-face psychological care.

Mechanisms underpinning effective peer support: a qualitative analysis of interactions between expert peers and patients newly-diagnosed with bipolar disorder

BackgroundThe increasing burden on mental health services has led to the growing use of peer support in psychological interventions. Four theoretical mechanisms have been proposed to underpin effective peer support: advice grounded in experiential knowledge, social support, social comparison and the helper therapy principle. However, there has been a lack of studies examining whether these mechanisms are also evident in clinical populations in which interpersonal dysfunction is common, such as bipolar disorder.MethodThis qualitative study, conducted alongside a randomized controlled trial, examined whether the four mechanisms proposed to underpin effective peer support were expressed in the email exchange between 44 individuals newly-diagnosed with bipolar disorder and their Informed Supporters (n = 4), over the course of a supported online psychoeducation program for bipolar disorder. A total of 104 text segments were extracted and coded. The data were complemented by face-to-face interviews with three of the four Informed Supporters who participated in the study.ResultsQualitative analyses of the email interchange and interview transcripts revealed rich examples of all four mechanisms. The data illustrated how the involvement of Informed Supporters resulted in numerous benefits for the newly-diagnosed individuals, including the provision of practical strategies for illness management as well as emotional support throughout the intervention. The Informed Supporters encouraged the development of positive relationships with mental health services, and acted as role models for treatment adherence. The Informed Supporters themselves reported gaining a number of benefits from helping, including a greater sense of connectedness with the mental health system, as well as a broader knowledge of illness management strategies.ConclusionsExamples of the mechanisms underpinning effective peer support were found in the sample of emails from individuals with newly-diagnosed bipolar disorder and their Informed Supporters. Experiential knowledge, social support, social comparison and helper therapy were apparent, even within a clinical population for whom relationship difficulties are common. Trial registration number ACTRN12608000411347.

Quantifying app store dynamics: longitudinal tracking of mental health apps

Background For many mental health conditions, mobile health apps offer the ability to deliver information, support, and intervention outside the clinical setting. However, there are difficulties with the use of a commercial app store to distribute health care resources, including turnover of apps, irrelevance of apps, and discordance with evidence-based practice. Objective The primary aim of this study was to quantify the longevity and rate of turnover of mental health apps within the official Android and iOS app stores. The secondary aim was to quantify the proportion of apps that were clinically relevant and assess whether the longevity of these apps differed from clinically nonrelevant apps. The tertiary aim was to establish the proportion of clinically relevant apps that included claims of clinical effectiveness. We performed additional subgroup analyses using additional data from the app stores, including search result ranking, user ratings, and number of downloads. Methods We searched iTunes (iOS) and the Google Play (Android) app stores each day over a 9-month period for apps related to depression, bipolar disorder, and suicide. We performed additional app-specific searches if an app no longer appeared within the main search Results On the Android platform, 50% of the search results changed after 130 days (depression), 195 days (bipolar disorder), and 115 days (suicide). Search results were more stable on the iOS platform, with 50% of the search results remaining at the end of the study period. Approximately 75% of Android and 90% of iOS apps were still available to download at the end of the study. We identified only 35.3% (347/982) of apps as being clinically relevant for depression, of which 9 (2.6%) claimed clinical effectiveness. Only 3 included a full citation to a published study. Conclusions The mental health app environment is volatile, with a clinically relevant app for depression becoming unavailable to download every 2.9 days. This poses challenges for consumers and clinicians seeking relevant and long-term apps, as well as for researchers seeking to evaluate the evidence base for publicly available apps.

The use of technology in suicide prevention

Suicide is one of the leading causes of death globally, and is notably a significant cause of death amongst young people. A suicide outcome is a complex combination of personal, social, and health factors, and therefore suicide prevention is a challenge, requiring a systems approach incorporating public health strategies, screening at-risk individuals, targeted interventions, and follow-up for suicide survivors and those bereaved by suicide. Engineering practice has been implicated in the hindrance of the adoption of suicide prevention strategies, such as installing safety barriers at the Golden Gate Bridge, however technological developments offer new opportunities in suicide prevention, and the potential to reduce the number of deaths by suicide. We present an overview of current technological developments which are facilitating research in the field of suicide prevention, including multiple modes of screening such as network analysis of mobile-phone collected connectivity data, automatic detection of suicidality from social media content, and crisis detection from acoustic variability in speech patterns. The current field of mhealth apps for suicide prevention is assessed, and an innovative app for an Indigenous population is presented. From this overview, future challenges - technical and ethical - are discussed.

The Reviews Are in: A Qualitative Content Analysis of Consumer Perspectives on Apps for Bipolar Disorder

Background The delivery of mobile health (mHealth) services is acceptable to mental health consumers. However, despite the benefits of accessibility, cost-effectiveness, anonymity, and ability to tailor content to individual needs, consumer engagement remains a hurdle for uptake and continued use. This may be unsurprising as few studies have examined app content from the consumer perspective or assessed consumer preferences for the content of apps for mental health management. An opportunity to examine consumer perspectives exists in using naturally generated data that is publically available in the Google Play and Apple app stores. Whereas commercial developers routinely use this data, to date there has been no in-depth evaluation within scientific research. Objective The aim of our study was to explore what consumers consider useful content for mental health management apps, identify unmet needs, and understand user expectations of mental health apps within the context of apps for bipolar disorder. Methods Publically available English language consumer reviews of 48 apps for bipolar disorder were used as data, providing a total of 2173 reviews. Review text was coded and analyzed using a team approach to qualitative content analysis. Results were presented in 2 forms: (1) a quantitative summary of the 9 major and minor themes and (2) a qualitative synthesis of key thematic findings. Results The majority of reviews were for symptom monitoring apps (87.94%, 1911/2173). The qualitative content analysis revealed 5 main themes: (1) laudatory talk, comments regarding the app’s benefits including helpfulness and successful design features (74.00% of reviews, 1608/2173); (2) unfavorable feedback, negative reviews largely concerning unmet needs, privacy and technical issues, and potential dangers of app use (25.54%, 555/2173); (3) conceptions of community, referring to both communities of users with mental ill-health accessed via the app and a community created among app users and developers (24.25%, 527/2173); (4) wishlist features, app features requested by users (17.53%, 381/2173); and (5) apps and therapy, app use within clinical care (10.58%, 230/2173). Four minor themes were also identified: (1) app cost, (2) privacy and data security, (3) comparisons with traditional monitoring, and (4) evidence-based mHealth. Conclusions Although mostly positive, the proportion of reviews containing wishlist requests indicates consumer needs are not adequately addressed by currently available disorder management apps. Consumers value content that is helpful, supportive, and easy to use, and they are integrating apps into their health management and clinical care without necessarily considering the evidence-base or clinical effectiveness of the tool. User expectations regarding developer responsiveness to their needs has implications for community-based participatory research and integrated knowledge translation. However, this expectation is incompatible with current mHealth funding structures.