e-Mental Health Program Usage Patterns in Randomized Controlled Trials and in the General Public to Inform External Validity Considerations: Sample Groupings Using Cluster Analyses.

BACKGROUND: Randomized controlled trials (RCTs) with vigorous study designs are vital for determining the efficacy of treatments. Despite the high internal validity attributed to RCTs, external validity concerns limit the generalizability of results to the general population. Bias can be introduced, for example, when study participants who self-select into a trial are more motivated to comply with study conditions than are other individuals. These external validity considerations extend to e-mental health (eMH) research, especially when eMH tools are designed for public access and provide minimal or no supervision. OBJECTIVE: Clustering techniques were employed to identify engagement profiles of RCT participants and community users of a self-guided eMH program. This exploratory approach inspected actual, not theorized, RCT participant and community user engagement patterns. Both samples had access to the eMH program over the same time period and received identical usage recommendations on the eMH program website. The aim of this study is to help gauge expectations of similarities and differences in usage behaviors of an eMH tool across evaluation and naturalistic contexts. METHODS: Australian adults signed up to myCompass, a self-guided online treatment program created to reduce mild to moderate symptoms of negative emotions. They did so either by being part of an RCT onboarding (160/231, 69.6% female) or by accessing the program freely on the internet (5563/8391, 66.30% female) between October 2011 and October 2012. During registration, RCT participants and community users provided basic demographic information. Usage metrics (number of logins, trackings, and learning activities) were recorded by the system. RESULTS: Samples at sign-up differed significantly in age (P=.003), with community users being on average 3 years older (mean 41.78, SD 13.64) than RCT participants (mean 38.79, SD 10.73). Furthermore, frequency of program use was higher for RCT participants on all usage metrics compared to community users through the first 49 days after registration (all P values <.001). Two-step cluster analyses revealed 3 user groups in the RCT sample (Nonstarters, 10-Timers, and 30+-Timers) and 2 user groups in the community samples (2-Timers and 20-Timers). Groups seemed comparable in patterns of use but differed in magnitude, with RCT participant usage groups showing more frequent engagement than community usage groups. Only the high-usage group among RCT participants approached myCompass usage recommendations. CONCLUSIONS: Findings suggested that external validity concerns of RCT designs may arise with regards to the predicted magnitude of eMH program use rather than overall usage styles. Following up RCT nonstarters may help provide unique insights into why individuals choose not to engage with an eMH program despite generally being willing to participate in an eMH evaluation study. Overestimating frequency of engagement with eMH tools may have theoretical implications and potentially impact economic considerations for plans to disseminate these tools to the general public.

A Narrative Review of Methods for Applying User Experience in the Design and Assessment of Mental Health Smartphone Interventions.

OBJECTIVES: User experience (UX) plays a key role in uptake and usage of mental health smartphone interventions, yet remains underinvestigated. This review aimed to characterize and compare UX evaluation approaches that have been applied in this specific context, and to identify implications for research and practice. METHODS: A narrative review was conducted of UX-themed studies published in PubMed, PsycINFO, and Scopus up to February 2019. Eligible studies reported on data reflecting users' interactions with a smartphone intervention for any mental health condition. Studies were categorized into "situated" versus "construct-based" methods according to whether or not an established UX construct was used to acquire and analyze data. RESULTS: Situated approaches used bespoke UX metrics, including quantitative measures of usage and performance, as well as grounded interview data. Construct-based approaches such as assessments of usability and acceptability were based on conceptual frameworks, with methodologically stronger versions featuring construct definitions, validated measurement tools, and an ability to compare data across studies. Constructs and measures were sometimes combined to form bespoke construct-based approaches. CONCLUSIONS: Both situated and construct-based UX data may provide benefits during design and implementation of a mental health smartphone intervention by helping to clarify the needs of users and the impact of new features. Notable however was the omission of UX methods, such as split testing. Future research should consider these unaddressed methods, aim to improve the rigor of UX assessment, integrate their use alongside clinical outcomes, and explore UX assessment of more complex, adaptive interventions.

Digital health at fifteen: more human (more needed).

There is growing appreciation that the success of digital health - whether digital tools, digital interventions or technology-based change strategies - is linked to the extent to which human factors are considered throughout design, development and implementation. A shift in focus to individuals as users and consumers of digital health highlights the capacity of the field to respond to secular developments, such as the adoption of person-centred care and consumer health technologies. We argue that this project is not only incomplete, but is fundamentally 'uncompletable' in the face of a highly dynamic landscape of both technological and human challenges. These challenges include the effects of consumerist, technology-supported care on care delivery, the rapid growth of digital users in low-income and middle-income countries and the impacts of machine learning. Digital health research will create most value by retaining a clear focus on the role of human factors in maximising health benefit, by helping health systems to anticipate and understand the person-centred effects of technology changes and by advocating strongly for the autonomy, rights and safety of consumers.

Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research and Clinical Applications.

In this viewpoint we describe the architecture of, and design rationale for, a new software platform designed to support the conduct of digital phenotyping research studies. These studies seek to collect passive and active sensor signals from participants' smartphones for the purposes of modelling and predicting health outcomes, with a specific focus on mental health. We also highlight features of the current research landscape that recommend the coordinated development of such platforms, including the significant technical and resource costs of development, and we identify specific considerations relevant to the design of platforms for digital phenotyping. In addition, we describe trade-offs relating to data quality and completeness versus the experience for patients and public users who consent to their devices being used to collect data. We summarize distinctive features of the resulting platform, InSTIL (Intelligent Sensing to Inform and Learn), which includes universal (ie, cross-platform) support for both iOS and Android devices and privacy-preserving mechanisms which, by default, collect only anonymized participant data. We conclude with a discussion of recommendations for future work arising from learning during the development of the platform. The development of the InSTIL platform is a key step towards our research vision of a population-scale, international, digital phenotyping bank. With suitable adoption, the platform will aggregate signals from large numbers of participants and large numbers of research studies to support modelling and machine learning analyses focused on the prediction of mental illness onset and disease trajectories.

Using Cluster Analysis to Explore Engagement and e-Attainment as Emergent Behavior in Electronic Mental Health.

BACKGROUND: In most e-mental health (eMH) research to date, adherence is defined according to a trial protocol. However, adherence to a study protocol may not completely capture a key aspect of why participants engage with eMH tools, namely, to achieve personal mental health goals. As a consequence, trial attrition reported as non-adherence or dropout may reflect e-attainment, the discontinuation of eMH engagement after personal goals have been met. Clarifying engagement patterns, such as e-attainment, and how these align with mental health trajectories, may help optimize eMH design and implementation science. OBJECTIVE: This study aimed to use clustering techniques to identify real-world engagement profiles in a community of eMH users and examine if such engagement profiles are associated with different mental health outcomes. The novelty of this approach was our attempt to identify actual user engagement behaviors, as opposed to employing engagement benchmarks derived from a trial protocol. The potential of this approach is to link naturalistic behaviors to beneficial mental health outcomes, which would be especially informative when designing eMH programs for the general public. METHODS: Between May 2013 and June 2018, Australian adults (N=43,631) signed up to myCompass, a self-guided eMH program designed to help alleviate mild to moderate symptoms of depression, anxiety, and stress. Recorded usage data included number of logins, frequency of mood tracking, number of started and completed learning activities, and number of tracking reminders set. A subset of users (n=168) completed optional self-assessment mental health questionnaires (Patient Health Questionnaire-9 item, PHQ-9; Generalized Anxiety Disorder Questionnaire-7 item, GAD-7) at registration and at 28 and 56 days after sign-up. Another subset of users (n=861) completed the PHQ-9 and GAD-7 at registration and at 28 days. RESULTS: Two-step cluster analyses revealed 3 distinct usage patterns across both subsamples: moderates, trackers, and super users, signifying differences both in the frequency of use as well as differences in preferences for program functionalities. For both subsamples, repeated measures analysis of variances showed significant decreases over time in PHQ-9 and GAD-7 scores. Time-by-cluster interactions, however, did not yield statistical significance in both subsamples, indicating that clusters did not predict symptom reduction over time. Interestingly, users who completed the self-assessment questionnaires twice had slightly but significantly lower depression and anxiety levels at sign-up compared with users who completed the questionnaires a third time at 56 days. CONCLUSIONS: Findings suggested that although users engaged with myCompass in different but measurable ways, those different usage patterns evoked equivalent mental health benefits. Furthermore, the randomized controlled trial paradigm may unintentionally limit the scope of eMH engagement research by mislabeling early mental health goal achievers as dropouts. More detailed and naturalistic approaches to study engagement with eMH technologies may improve program design and, ultimately, program effectiveness.

The Emerging Imperative for a Consensus Approach Toward the Rating and Clinical Recommendation of Mental Health Apps.

With over 10,000 mental health- and psychiatry-related smartphone apps available today and expanding, there is a need for reliable and valid evaluation of these digital tools. However, the updating and nonstatic nature of smartphone apps, expanding privacy concerns, varying degrees of usability, and evolving interoperability standards, among other factors, present serious challenges for app evaluation. In this article, we provide a narrative review of various schemes toward app evaluations, including commercial app store metrics, government initiatives, patient-centric approaches, point-based scoring, academic platforms, and expert review systems. We demonstrate that these different approaches toward app evaluation each offer unique benefits but often do not agree to each other and produce varied conclusions as to which apps are useful or not. Although there are no simple solutions, we briefly introduce a new initiative that aims to unify the current controversies in app elevation called CHART (Collaborative Health App Rating Teams), which will be further discussed in a second article in this series.

Issues for eHealth in Psychiatry: Results of an Expert Survey.

BACKGROUND: Technology has changed the landscape in which psychiatry operates. Effective, evidence-based treatments for mental health care are now available at the fingertips of anyone with Internet access. However, technological solutions for mental health are not necessarily sought by consumers nor recommended by clinicians. OBJECTIVE: The objectives of this study are to identify and discuss the barriers to introducing eHealth technology-supported interventions within mental health. METHODS: An interactive polling tool was used to ask "In this brave new world, what are the key issues that need to be addressed to improve mental health (using technology)?" Respondents were the multidisciplinary attendees of the "Humans and Machines: A Quest for Better Mental Health" conference, held in Sydney, Australia, in 2016. Responses were categorized into 10 key issues using team-based qualitative analysis. RESULTS: A total of 155 responses to the question were received from 66 audience members. Responses were categorized into 10 issues and ordered by importance: access to care, integration and collaboration, education and awareness, mental health stigma, data privacy, trust, understanding and assessment of mental health, government and policy, optimal design, and engagement. In this paper, each of the 10 issues are outlined, and potential solutions are discussed. Many of the issues were interrelated, having implications for other key areas identified. CONCLUSIONS: As many of the issues identified directly related to barriers to care, priority should be given to addressing these issues that are common across mental health delivery. Despite new challenges raised by technology, technology-supported mental health interventions represent a tremendous opportunity to address in a timely way these major concerns and improve the receipt of effective, evidence-based therapy by those in need.

Financial Incentives and Inequalities in Smoking Cessation Interventions in Primary Care: Before-and-After Study.

INTRODUCTION: The Quality and Outcomes Framework (QOF) is a financial incentive scheme that rewards UK general practices for providing evidence-based care, including smoking cessation advice mainly as a secondary prevention intervention. We examined the effects on smoking outcomes and inequalities of a local version of QOF (QOF+), which ran from 2008 to 2011 and extended financial incentives to the provision of cessation advice as a primary prevention intervention. METHODS: Before-and-after study using data from 28 general practices in Hammersmith & Fulham, London, United Kingdom. We used logistic regression to examine changes in smoking outcomes associated with QOF+ within and between sociodemographic groups. RESULTS: Recording of smoking status increased from 55.5% to 64.3% for men (P < .001) and from 67.9% to 75.8% for women (P < .001). All groups benefitted from the increase, but younger patients remained less likely to be asked about smoking than older patients. White patients were less likely to be asked than those from other ethnic groups. Smoking cessation advice increased from 32.7% to 54.0% for men (P < .001) and from 35.4% to 54.1% for women (P < .01) and there was little variation between groups for this outcome. Recorded smoking prevalence reduced from 25.0% to 20.8% for men (P < .001) and from 16.1% to 12.5% for women (P < .001). White patients and those from more deprived areas remained more likely to be smokers than other groups. CONCLUSION: The introduction of QOF+ was associated with general improvements in recording of smoking outcomes, but inequalities in ascertainment and smoking prevalence with respect to age, ethnicity, and deprivation persisted.

The evolution of mobile apps for asthma: an updated systematic assessment of content and tools.

BACKGROUND: Interest in mobile apps that support long-term conditions such as asthma is matched by recognition of the importance of the quality and safety of apps intended for patient use. We assessed how changes over a 2-year period affected the clinical suitability of apps providing self-management information and tools for people with asthma by updating a review first performed in 2011. METHODS: Systematic content assessment of all apps for iOS and Android examining the comprehensiveness of asthma information, consistency with the evidence base for asthma self-management and adherence to best practice principles for trustworthy content, comparing the quality of apps available in 2011 to those released since. RESULTS: Between 2011 and 2013, numbers of asthma apps more than doubled from 93 to 191, despite withdrawal of 25% (n = 23/93) of existing apps. Newer apps were no more likely than those available in 2011 to include comprehensive information, such as the use of action plans, or offer guidance consistent with evidence; 13% (n = 19/147) of all apps, and 39% (n = 9/23) of those intended to manage acute asthma, recommended self-care procedures unsupported by evidence. Despite increases in the numbers of apps targeting specific skills, such as acute asthma management (n = 12 to 23) and inhaler technique (from n = 2 to 12), the proportion consistent with guidelines (17%, n = 4/23) and inhaler instructions (25%, n = 3/12), respectively, was low, and most apps provided only either basic information about asthma (50%, n = 75/147) or simple diary functions (24%, n = 36/147). CONCLUSIONS: In addition to persisting questions about clinical quality and safety, dynamic aspects of app turnover and feature evolution affect the suitability of asthma apps for use in routine care. The findings underline the need for coordinated quality assurance processes that can adapt to changing clinical and information governance-related risks, ensure compliance with the evidence base and reflect local variations in clinical practice. It is unclear if substantial clinical benefits can be realized from a landscape dominated by low quality generic information apps and tools that do not adhere to accepted medical practice.

Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment.

BACKGROUND: Poor information privacy practices have been identified in health apps. Medical app accreditation programs offer a mechanism for assuring the quality of apps; however, little is known about their ability to control information privacy risks. We aimed to assess the extent to which already-certified apps complied with data protection principles mandated by the largest national accreditation program. METHODS: Cross-sectional, systematic, 6-month assessment of 79 apps certified as clinically safe and trustworthy by the UK NHS Health Apps Library. Protocol-based testing was used to characterize personal information collection, local-device storage and information transmission. Observed information handling practices were compared against privacy policy commitments. RESULTS: The study revealed that 89% (n = 70/79) of apps transmitted information to online services. No app encrypted personal information stored locally. Furthermore, 66% (23/35) of apps sending identifying information over the Internet did not use encryption and 20% (7/35) did not have a privacy policy. Overall, 67% (53/79) of apps had some form of privacy policy. No app collected or transmitted information that a policy explicitly stated it would not; however, 78% (38/49) of information-transmitting apps with a policy did not describe the nature of personal information included in transmissions. Four apps sent both identifying and health information without encryption. Although the study was not designed to examine data handling after transmission to online services, security problems appeared to place users at risk of data theft in two cases. CONCLUSIONS: Systematic gaps in compliance with data protection principles in accredited health apps question whether certification programs relying substantially on developer disclosures can provide a trusted resource for patients and clinicians. Accreditation programs should, as a minimum, provide consistent and reliable warnings about possible threats and, ideally, require publishers to rectify vulnerabilities before apps are released.

Smartphone apps for calculating insulin dose: a systematic assessment.

BACKGROUND: Medical apps are widely available, increasingly used by patients and clinicians, and are being actively promoted for use in routine care. However, there is little systematic evidence exploring possible risks associated with apps intended for patient use. Because self-medication errors are a recognized source of avoidable harm, apps that affect medication use, such as dose calculators, deserve particular scrutiny. We explored the accuracy and clinical suitability of apps for calculating medication doses, focusing on insulin calculators for patients with diabetes as a representative use for a prevalent long-term condition. METHODS: We performed a systematic assessment of all English-language rapid/short-acting insulin dose calculators available for iOS and Android. RESULTS: Searches identified 46 calculators that performed simple mathematical operations using planned carbohydrate intake and measured blood glucose. While 59% (n = 27/46) of apps included a clinical disclaimer, only 30% (n = 14/46) documented the calculation formula. 91% (n = 42/46) lacked numeric input validation, 59% (n = 27/46) allowed calculation when one or more values were missing, 48% (n = 22/46) used ambiguous terminology, 9% (n = 4/46) did not use adequate numeric precision and 4% (n = 2/46) did not store parameters faithfully. 67% (n = 31/46) of apps carried a risk of inappropriate output dose recommendation that either violated basic clinical assumptions (48%, n = 22/46) or did not match a stated formula (14%, n = 3/21) or correctly update in response to changing user inputs (37%, n = 17/46). Only one app, for iOS, was issue-free according to our criteria. No significant differences were observed in issue prevalence by payment model or platform. CONCLUSIONS: The majority of insulin dose calculator apps provide no protection against, and may actively contribute to, incorrect or inappropriate dose recommendations that put current users at risk of both catastrophic overdose and more subtle harms resulting from suboptimal glucose control. Healthcare professionals should exercise substantial caution in recommending unregulated dose calculators to patients and address app safety as part of self-management education. The prevalence of errors attributable to incorrect interpretation of medical principles underlines the importance of clinical input during app design. Systemic issues affecting the safety and suitability of higher-risk apps may require coordinated surveillance and action at national and international levels involving regulators, health agencies and app stores.

Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods.

BACKGROUND: Self-administered survey questionnaires are an important data collection tool in clinical practice, public health research and epidemiology. They are ideal for achieving a wide geographic coverage of the target population, dealing with sensitive topics and are less resource-intensive than other data collection methods. These survey questionnaires can be delivered electronically, which can maximise the scalability and speed of data collection while reducing cost. In recent years, the use of apps running on consumer smart devices (i.e., smartphones and tablets) for this purpose has received considerable attention. However, variation in the mode of delivering a survey questionnaire could affect the quality of the responses collected. OBJECTIVES: To assess the impact that smartphone and tablet apps as a delivery mode have on the quality of survey questionnaire responses compared to any other alternative delivery mode: paper, laptop computer, tablet computer (manufactured before 2007), short message service (SMS) and plastic objects. SEARCH METHODS: We searched MEDLINE, EMBASE, PsycINFO, IEEEXplore, Web of Science, CABI: CAB Abstracts, Current Contents Connect, ACM Digital, ERIC, Sociological Abstracts, Health Management Information Consortium, the Campbell Library and CENTRAL. We also searched registers of current and ongoing clinical trials such as ClinicalTrials.gov and the World Health Organization (WHO) International Clinical Trials Registry Platform. We also searched the grey literature in OpenGrey, Mobile Active and ProQuest Dissertation & Theses. Lastly, we searched Google Scholar and the reference lists of included studies and relevant systematic reviews. We performed all searches up to 12 and 13 April 2015. SELECTION CRITERIA: We included parallel randomised controlled trials (RCTs), crossover trials and paired repeated measures studies that compared the electronic delivery of self-administered survey questionnaires via a smartphone or tablet app with any other delivery mode. We included data obtained from participants completing health-related self-administered survey questionnaire, both validated and non-validated. We also included data offered by both healthy volunteers and by those with any clinical diagnosis. We included studies that reported any of the following outcomes: data equivalence; data accuracy; data completeness; response rates; differences in the time taken to complete a survey questionnaire; differences in respondent's adherence to the original sampling protocol; and acceptability to respondents of the delivery mode. We included studies that were published in 2007 or after, as devices that became available during this time are compatible with the mobile operating system (OS) framework that focuses on apps. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from the included studies using a standardised form created for this systematic review in REDCap. They then compared their forms to reach consensus. Through an initial systematic mapping on the included studies, we identified two settings in which survey completion took place: controlled and uncontrolled. These settings differed in terms of (i) the location where surveys were completed, (ii) the frequency and intensity of sampling protocols, and (iii) the level of control over potential confounders (e.g., type of technology, level of help offered to respondents). We conducted a narrative synthesis of the evidence because a meta-analysis was not appropriate due to high levels of clinical and methodological diversity. We reported our findings for each outcome according to the setting in which the studies were conducted. MAIN RESULTS: We included 14 studies (15 records) with a total of 2275 participants; although we included only 2272 participants in the final analyses as there were missing data for three participants from one included study.Regarding data equivalence, in both controlled and uncontrolled settings, the included studies found no significant differences in the mean overall scores between apps and other delivery modes, and that all correlation coefficients exceeded the recommended thresholds for data equivalence. Concerning the time taken to complete a survey questionnaire in a controlled setting, one study found that an app was faster than paper, whereas the other study did not find a significant difference between the two delivery modes. In an uncontrolled setting, one study found that an app was faster than SMS. Data completeness and adherence to sampling protocols were only reported in uncontrolled settings. Regarding the former, an app was found to result in more complete records than paper, and in significantly more data entries than an SMS-based survey questionnaire. Regarding adherence to the sampling protocol, apps may be better than paper but no different from SMS. We identified multiple definitions of acceptability to respondents, with inconclusive results: preference; ease of use; willingness to use a delivery mode; satisfaction; effectiveness of the system informativeness; perceived time taken to complete the survey questionnaire; perceived benefit of a delivery mode; perceived usefulness of a delivery mode; perceived ability to complete a survey questionnaire; maximum length of time that participants would be willing to use a delivery mode; and reactivity to the delivery mode and its successful integration into respondents' daily routine. Finally, regardless of the study setting, none of the included studies reported data accuracy or response rates. AUTHORS' CONCLUSIONS: Our results, based on a narrative synthesis of the evidence, suggest that apps might not affect data equivalence as long as the intended clinical application of the survey questionnaire, its intended frequency of administration and the setting in which it was validated remain unchanged. There were no data on data accuracy or response rates, and findings on the time taken to complete a self-administered survey questionnaire were contradictory. Furthermore, although apps might improve data completeness, there is not enough evidence to assess their impact on adherence to sampling protocols. None of the included studies assessed how elements of user interaction design, survey questionnaire design and intervention design might influence mode effects. Those conducting research in public health and epidemiology should not assume that mode effects relevant to other delivery modes apply to apps running on consumer smart devices. Those conducting methodological research might wish to explore the issues highlighted by this systematic review.

A Hybrid Physical-Digital Simulation Laboratory to Expedite Context-Aware Design and Usability Testing in Digital Health.

Fit within existing physical and digitalised workflows is a critical aspect of digital health software usability. Early, iterative exploration of contextual usability issues is complicated by barriers of access to healthcare settings. The Validitron SimLab is a new facility for digital health prototyping that augments immersive, realistic physical environments with a digital sandbox allowing new and existing software to be easily set up and tested in the physical space.

Adapting an Environmental Scan for 'Insights Reporting': Learnings from an Online Brain Cancer Peer Support Platform.

When developing a digital health solution, product owners, healthcare professionals, researchers, IT teams, and consumers require timely, accurate contextual information to inform solution development. Insights Reporting can rapidly draw together information from literature, end users and existing technology to inform the development process. This was the case when creating an online brain cancer peer support platform where solution development was conducted in parallel with contextual information synthesis. This paper discusses the novel adaptation of an environmental scan methodology using codesign and multiple layers of qualitative rigor, to create Insights Reporting. This seven-step process can be completed in two months and results in salient points of knowledge that can rapidly inform the design of a solution, creating a shared understanding of a digital health phenomenon. Project members noted that Insights Reporting surfaces previously inaccessible knowledge, catalyzes decision-making and allows all stakeholders to influence the report agenda, affirming principles of digital health equity.

Designing an Interprofessional Online Course to Foster Learning Health Systems.

The Learning Health Systems (LHS) framework demonstrates the potential for iterative interrogation of health data in real time and implementation of insights into practice. Yet, the lack of appropriately skilled workforce results in an inability to leverage existing data to design innovative solutions. We developed a tailored professional development program to foster a skilled workforce. The short course is wholly online, for interdisciplinary professionals working in the digital health arena. To transform healthcare systems, the workforce needs an understanding of LHS principles, data driven approaches, and the need for diversly skilled learning communities that can tackle these complex problems together.

Efficacy of BrighterSide, a Self-Guided App for Suicidal Ideation: Randomized Controlled Trial.

Background: Self-guided digital interventions can reduce the severity of suicidal ideation, although there remain relatively few rigorously evaluated smartphone apps targeting suicidality. Objective: This trial evaluated whether the BrighterSide smartphone app intervention was superior to a waitlist control group at reducing the severity of suicidal ideation. Methods: A total of 550 adults aged 18 to 65 years with recent suicidal ideation were recruited from the Australian community. In this randomized controlled trial, participants were randomly assigned to receive either the BrighterSide app or to a waitlist control group that received treatment as usual. The app was self-guided, and participants could use the app at their own pace for the duration of the study period. Self-report measures were collected at baseline, 6 weeks, and 12 weeks. The primary outcome was severity and frequency of suicidal ideation, and secondary outcomes included psychological distress and functioning and recovery. Additional data were collected on app engagement and participant feedback. Results: Suicidal ideation reduced over time for all participants, but there was no significant interaction between group and time. Similar improvements were observed for self-harm, functioning and recovery, days out of role, and coping. Psychological distress was significantly lower in the intervention group at the 6-week follow-up, but this was not maintained at 12 weeks. Conclusions: The BrighterSide app did not lead to a significant improvement in suicidal ideation relative to a waitlist control group. Possible reasons for this null finding are discussed.

Smartphone and tablet self management apps for asthma.

BACKGROUND: Asthma is one of the most common long-term conditions worldwide, which places considerable pressure on patients, communities and health systems. The major international clinical guidelines now recommend the inclusion of self management programmes in the routine management of patients with asthma. These programmes have been associated with improved outcomes in patients with asthma. However, the implementation of self management programmes in clinical practice, and their uptake by patients, is still poor. Recent developments in mobile technology, such as smartphone and tablet computer apps, could help develop a platform for the delivery of self management interventions that are highly customisable, low-cost and easily accessible. OBJECTIVES: To assess the effectiveness, cost-effectiveness and feasibility of using smartphone and tablet apps to facilitate the self management of individuals with asthma. SEARCH METHODS: We searched the Cochrane Airways Group Register (CAGR), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, CINAHL, Global Health Library, Compendex/Inspec/Referex, IEEEXplore, ACM Digital Library, CiteSeer(x) and CAB abstracts via Web of Knowledge. We also searched registers of current and ongoing trials and the grey literature. We checked the reference lists of all primary studies and review articles for additional references. We searched for studies published from 2000 onwards. The latest search was run in June 2013. SELECTION CRITERIA: We included parallel randomised controlled trials (RCTs) that compared self management interventions for patients with clinician-diagnosed asthma delivered via smartphone apps to self management interventions delivered via traditional methods (e.g. paper-based asthma diaries). DATA COLLECTION AND ANALYSIS: We used standard methods expected by the Cochrane Collaboration. Our primary outcomes were symptom scores; frequency of healthcare visits due to asthma exacerbations or complications and health-related quality of life. MAIN RESULTS: We included two RCTs with a total of 408 participants. We found no cluster RCTs, controlled before and after studies or interrupted time series studies that met the inclusion criteria for this systematic review. Both RCTs evaluated the effect of a mobile phone-based asthma self management intervention on asthma control by comparing it to traditional, paper-based asthma self management. One study allowed participants to keep daily entries of their asthma symptoms, asthma medication usage, peak flow readings and peak flow variability on their mobile phone, from which their level of asthma control was calculated remotely and displayed together with the corresponding asthma self management recommendations. In the other study, participants recorded the same readings twice daily, and they received immediate self management feedback in the form of a three-colour traffic light display on their phones. Participants falling into the amber zone of their action plan twice, or into the red zone once, received a phone call from an asthma nurse who enquired about the reasons for their uncontrolled asthma.We did not conduct a meta-analysis of the data extracted due to the considerable degree of heterogeneity between these studies. Instead we adopted a narrative synthesis approach. Overall, the results were inconclusive and we judged the evidence to have a GRADE rating of low quality because further evidence is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. In addition, there was not enough information in one of the included studies to assess the risk of bias for the majority of the domains. Although the other included study was methodologically rigorous, it was not possible to blind participants or personnel in the study. Moreover, there are concerns in both studies in relation to attrition bias and other sources of bias.One study showed that the use of a smartphone app for the delivery of an asthma self management programme had no statistically significant effect on asthma symptom scores (mean difference (MD) 0.01, 95% confidence interval (CI) -0.23 to 0.25), asthma-related quality of life (MD of mean scores 0.02, 95% CI -0.35 to 0.39), unscheduled visits to the emergency department (OR 7.20, 95% CI 0.37 to 140.76) or frequency of hospital admissions (odds ratio (OR) 3.07, 95% CI 0.32 to 29.83). The other included study found that the use of a smartphone app resulted in higher asthma-related quality of life scores at six-month follow-up (MD 5.50, 95% CI 1.48 to 9.52 for the physical component score of the SF-12 questionnaire; MD 6.00, 95% CI 2.51 to 9.49 for the mental component score of the SF-12 questionnaire), improved lung function (PEFR) at four (MD 27.80, 95% CI 4.51 to 51.09), five (MD 31.40, 95% CI 8.51 to 54.29) and six months (MD 39.20, 95% CI 16.58 to 61.82), and reduced visits to the emergency department due to asthma-related complications (OR 0.20, 95% CI 0.04 to 0.99). Both studies failed to find any statistical differences in terms of adherence to the intervention and occurrence of other asthma-related complications. AUTHORS' CONCLUSIONS: The current evidence base is not sufficient to advise clinical practitioners, policy-makers and the general public with regards to the use of smartphone and tablet computer apps for the delivery of asthma self management programmes. In order to understand the efficacy of apps as standalone interventions, future research should attempt to minimise the differential clinical management of patients between control and intervention groups. Those studies evaluating apps as part of complex, multicomponent interventions, should attempt to tease out the relative contribution of each intervention component. Consideration of the theoretical constructs used to inform the development of the intervention would help to achieve this goal. Finally, researchers should also take into account: the role of ancillary components in moderating the observed effects, the seasonal nature of asthma and long-term adherence to self management practices.

Uptake of the NHS Health Check programme in an urban setting.

BACKGROUND: The NHS Health Check programme aims to improve prevention, early diagnosis and management of cardiovascular disease (CVD) in England. High and equitable uptake is essential for the programme to effectively reduce the CVD burden. OBJECTIVES: Assessing the impact of a local financial incentive scheme on uptake and statin prescribing in the first 2 years of the programme. METHODS: Cross-sectional study using data from electronic medical records of general practices in Hammersmith and Fulham, London on all patients aged 40-74 years. We assessed uptake of complete Health Check, exclusion of patients from the programme (exception reporting) and statin prescriptions in patients confirmed with high CVD risk. RESULTS: The Health Check uptake was 32.7% in Year 1 and 20.0% in Year 2. Older patients had higher uptake of Health Check than younger (65- to 74-year-old patients: Year 1 adjusted odds ratio (AOR) 2.05 (1.67-2.52) & Year 2 AOR 2.79 (2.49-3.12) compared with 40- to 54-year-old patients). The percentage of confirmed high risk patients prescribed a statin was 17.7% before and 52.9% after the programme. There was a marked variation in Health Check uptake, exception reporting and statin prescribing between practices. CONCLUSIONS: Uptake of the Health Check was low in the first year in patients with estimated high risk despite financial incentives to general practices; although this matched the national required rate in second year. Further evaluations for cost and clinical effectiveness of the programme are needed to clarify whether this spending is appropriate, and to assess the impact of financial incentives on programme performance.

The impact of COVID-19 and bushfires on the mental health of Australian adolescents: a cross-sectional study.

BACKGROUND: When COVID-19 spread to Australia in January 2020, many communities were already in a state of emergency from the Black Summer bushfires. Studies of adolescent mental health have typically focused on the effects of COVID-19 in isolation. Few studies have examined the impact of COVID-19 and other co-occurring disasters, such as the Black Summer bushfires in Australia, on adolescent mental health. METHODS: We conducted a cross-sectional survey to examine the impact of COVID-19 and the Black Summer bushfires on the mental health of Australian adolescents. Participants (N = 5866; mean age 13.61 years) answered self-report questionnaires about COVID-19 diagnosis/quarantine (being diagnosed with and/or quarantined because of COVID-19) and personal exposure to bushfire harm (being physically injured, evacuated from home and/or having possessions destroyed). Validated standardised scales were used to assess depression, psychological distress, anxiety, insomnia, and suicidal ideation. Trauma related to COVID-19 and the bushfires was also assessed. The survey was completed in two large school-based cohorts between October 2020 and November 2021. RESULTS: Exposure to COVID-19 diagnosis/quarantine was associated with increased probability of elevated trauma. Exposure to personal harm by the bushfires was associated with increased probability of elevated insomnia, suicidal ideation, and trauma. There were no interactive effects between disasters on adolescent mental health. Effects between personal risk factors and disasters were generally additive or sub-additive. CONCLUSIONS: Adolescent mental health responses to community-level disasters are multi-faceted. Complex psychosocial factors associated with mental ill health may be relevant irrespective of disaster. Future research is needed to investigate synergistic effects of disasters on young mental health.

Implementing a Digital Depression Prevention Program in Australian Secondary Schools: Cross-Sectional Qualitative Study.

BACKGROUND: Depression is common during adolescence and is associated with adverse educational, employment, and health outcomes in later life. Digital programs are increasingly being implemented in schools to improve and protect adolescent mental health. Although digital depression prevention programs can be effective, there is limited knowledge about how contextual factors influence real-world delivery at scale in schools. OBJECTIVE: The purpose of this study was to examine the contextual factors that influence the implementation of the Future Proofing Program (FPP) from the perspectives of school staff. The FPP is a 2-arm hybrid type 1 effectiveness-implementation trial evaluating whether depression can be prevented at scale in schools, using an evidence-based smartphone app delivered universally to year 8 students (13-14 years of age). METHODS: Qualitative interviews were conducted with 23 staff from 20 schools in New South Wales, Australia, who assisted with the implementation of the FPP. The interviews were guided by our theory-driven logic model. Reflexive thematic analysis, using both deductive and inductive coding, was used to analyze responses. RESULTS: Staff perceived the FPP as a novel ("innovative approach") and appropriate way to address an unmet need within schools ("right place at the right time"). Active leadership and counselor involvement were critical for planning and engaging; teamwork, communication, and staff capacity were critical for execution ("ways of working within schools"). Low student engagement and staffing availability were identified as barriers for future adoption and implementation by schools ("reflecting on past experiences"). CONCLUSIONS: Four superordinate themes pertaining to the program, implementation processes, and implementation barriers were identified from qualitative responses by school staff. On the basis of our findings, we proposed a select set of recommendations for future implementation of digital prevention programs delivered at scale in schools. These recommendations were designed to facilitate an organizational change and help staff to implement digital mental health programs within their schools. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2020-042133.