BackgroundEarly detection in primary care could improve pancreatic cancer survival, but diagnosis is often delayed due to the low prevalence of the disease, the nonspecific nature of early symptoms, and the broad range of conditions and volume of consultations managed by general practitioners (GPs). In Australia, improving pancreatic cancer outcomes, including via earlier diagnosis, is a priority being progressed under the National Pancreatic Cancer Roadmap developed by Cancer Australia. Computerized clinical decision support systems (CDSSs) have shown promise in aiding timely cancer diagnosis; however, barriers to adopting CDSS such as mistrust of the recommendations or not being embedded in the clinical workflow remain. Simulation techniques, which offer flexible and cost-effective ways to evaluate digital health interventions, can be used to test CDSS before real-world implementation. ObjectiveThis study aims to assess the acceptability and feasibility of identifying patients with symptoms associated with pancreatic cancer through a CDSS within a simulated environment. MethodsWe developed a CDSS that interacted with an electronic health record used in general practice to identify patients with symptoms, which may indicate pancreatic cancer (unintended weight loss or new-onset diabetes), in a simulation laboratory for digital interventions. We tested it by inviting GPs (n=11) to use the CDSS, with patient actors simulating specific clinical scenarios. We then interviewed GPs about the interaction to assess the acceptability and feasibility of the CDSS in their clinical practice. We used thematic analysis and 2 relevant frameworks to analyze the data. ResultsGPs found the CDSS easy to use, unobstructive, and effective as a prompt to consider investigations for people with risk factors for pancreatic cancer. However, they expressed concerns about possible overtesting, financial costs, and the potential for anxiety in patients with a very low probability of having cancer. ConclusionsWhile GPs found the tool useful and compatible with their workflow, concerns about overtesting, lack of evidence, and cost-effectiveness were identified as barriers. GPs favored a stepwise approach to investigations rather than immediate imaging. Despite the overall acceptability of the tool, additional evidence to underpin clinical recommendations is necessary before implementing a CDSS with these specific recommendations for pancreatic cancer in primary care.

Patients forget up to 80% of information conveyed during medical consultations. While clinicians may provide hand-written notes to patients during in-person appointments, such opportunities are limited in telehealth. Palliative care patients with complex information needs may benefit from consultation summaries. We developed a consultation summary application (CSA) to generate patient-facing summaries during video telehealth, in a palliative care context. Traditional research methods fall short in early identification and resolution of socio-technical factors, e.g., workflow compatibility, which impact the adoption of digital health innovations. Drawing on the Service Readiness Level Framework, we adopted a phased approach to generating evidence for the CSA. We conducted clinical simulations with seven clinician-simulated patient dyads involving the metastatic lung cancer scenario to examine and address usability and workflow integration issues prior to real-world implementation. Both clinicians and simulated patients perceived the CSA as a valuable tool to support palliative care patients with information recall and self-management. We recommend clinical simulation to de-risk real-world deployment, and optimise the digital health innovations.

Abstract Patients with a brain tumour receive evidence-based clinical care in Australia but a focus on supportive care, including social connection, is often deficient. Digital health platforms hold promise to support these patients and their carers. Existing platforms often lack end-user co-design, evidence-based development and rigorous evaluation. Recognising this unmet need, we co-designed Brain Tumours Online, a digital supportive care platform to streamline access to educational resources, symptom management tools, and peer support for patients, carers, and healthcare professionals. In this article, we present our evaluation approach for Brain Tumours Online to advance methodological thinking in the evaluation of multi-faceted, co-designed digital health platforms. In contrast to standardised procedures in clinical trials, digital health interventions such as supportive care platforms are more complex due to their interactive nature, no prescriptive protocols for usage and the dynamic content of web-based information. Thus, traditional evaluation approaches often fall short in evaluating such multi-faceted digital health supportive care platforms. To address these challenges, we developed a bespoke, logic-modelling based evaluation approach to assess the usability, engagement, impact, and economic value of our platform. Our pragmatic but rigourous evaluation approach required the adaptation of existing evaluation frameworks, subject-matter, and lived experience expert knowledge. Our implementation science and co-design approach are shared in different papers. Our study outcomes will also be shared in a separate paper. In the current paper, we share our approach to the evaluation of Brain Tumours Online and provide insights that may be of value for other researchers interested in the nuances of trialing multi-faceted digital health supportive care platforms.

AIMS:Rural, regional, and remote hospitals in Australia face barriers to digital transformation, including limited infrastructure, digital literacy, and workforce capacity. This Commentary outlines a pragmatic strategy to build rural digital readiness through the safe implementation of ambient artificial intelligence (AI) scribes as a low-risk starting point for AI adoption. CONTEXT:AI scribes use generative AI to convert clinical conversations into documentation. They offer potential to reduce administrative burden and workforce strain while preparing rural health services for future AI use. Although the Victorian Department of Health has established minimum standards for AI scribe use, rural hospitals face unique challenges including lower AI literacy, workforce pressure, and limited research infrastructure. Insights from ongoing implementation research highlight the value of simulation methods to examine usability, workflow effects, and ethical considerations before deployment. APPROACH:Three key enablers support responsible implementation: (1) clinical simulation for research, (2) harmonisation of evaluation metrics, and (3) shared infrastructure for consent, training, and monitoring. CONCLUSION:Implementing AI scribes provides a practical pathway for rural hospitals to strengthen capability, reduce administrative burden, and build readiness for more advanced clinical AI, supporting safe and equitable adoption across rural Australia.

Background:It is widely accepted that the COVID-19 pandemic has accelerated the era of online health care delivery, including within community palliative care. This study was part of a larger project involving a collaboration between universities, health care services, government agencies, and software developers that sought to enhance an existing telehealth (video call) platform with additional features to improve both patient and health care professional (HCP) experience in a palliative care context. Objective:The aim of this study was to understand palliative care patients' and HCPs' experiences of telehealth delivery in a palliative care context in Victoria, Australia. For the purposes of this study, telehealth included consultations by both video and telephone calls. By better understanding users' experiences and perceptions of telehealth, we hoped to determine users' preferences for new telehealth enhancement features. Methods:A total of 6 health care professionals and 6 patients were recruited from a major tertiary hospital network's palliative care unit in Victoria, Australia. Participants were asked to generate 3-5 photographs depicting their telehealth experiences. These photographs were used as visual aids to prompt discussion during subsequent one-on-one interviews. Intertextual analysis was conducted to identify key themes. Results:A total of 3 overarching themes emerged: comfort (or lack thereof) afforded by telehealth, connection considerations in telehealth, and care quality impacts of telehealth. Patients (n=6) described telehealth as supporting their physical and psychological comfort and maintaining connection with HCPs, yet there were specific situations where it failed to meet their needs or impacted care quality and delayed treatment. HCPs (n=6) recognized the benefit of telehealth for patients but reported several limitations of telehealth, in particular due to lack of physical examination opportunities. Participants indicated that 2 types of connection were imperative for effective telehealth delivery: technical connection (eg, good internet connectivity or clear phone line) and interpersonal connection (ie, good rapport and therapeutic alliance between the HCPs and patients). Often technical connection issues impeded the development of interpersonal connection between the HCPs and patients in telehealth. Conclusions:The findings presented in this study combined with other co-design activities, which are outside the scope of this paper, indicated the potential value of a telehealth enhancement feature that generates patient-facing clinical consultation summaries. Our team has developed a video telehealth enhancement feature (or "add-on"), which will enable clinicians to distill key actionable advice and self-management guidance discussed during teleconsultations for a take-home summary document for patients. The add-on's prototype has also been subjected to an initial simulation study, which will be reported in a future publication.

Importance:A large proportion of college students report experiencing psychological distress. Smartphone app-based interventions may alleviate distress, but their effectiveness across severity levels is unclear. Artificial intelligence (AI)-enhanced response-adaptive randomized clinical trials may offer an efficient method to evaluate competing interventions. Objective:To compare the effectiveness of 3 brief, 2-week self-guided smartphone application-based interventions (physical activity, mindfulness, sleep hygiene) or an active control (ecological momentary assessment [EMA]) for reducing psychological distress among college students with mild, moderate, or severe distress. Design, Setting, and Participants:This population-based AI-enhanced response-adaptive randomized clinical trial included 1282 participants with distress scores of 20 or more on the 10-item Kessler Psychological Distress Scale in 12 minitrials from November 9, 2021, with final follow-up on February 17, 2023. Participants' distress was categorized as mild, moderate, or severe based on their normalized 21-item Depression Anxiety Stress Scale (DASS-21) scores at screening. Interventions:After a 2-week onboarding period of daily EMA, participants were assigned by a contextual multi-armed bandit algorithm to 1 of 4 two-week self-guided app interventions: physical activity, mindfulness, sleep hygiene, or a control that continued EMA. Main Outcomes and Measures:The primary outcome was change in psychological distress (DASS-21 total score) from week 2 (before intervention) to week 4 (after intervention). The primary end point was after the intervention (4 weeks). Secondary outcomes included DASS-21 subscale scores, self-reported physical activity, mindfulness, sleep quality, and app engagement, usability, and satisfaction. Analysis was performed on an intention-to-treat basis. Results:A total of 1282 individuals (mean [SD] age, 23.5 [5.2] years; 950 women [74.1%]) participated: physical activity (n = 305), mindfulness (n = 453), sleep hygiene (n = 431), or a control that continued EMA (n = 93). Among 349 participants with severe distress, physical activity (n = 79) and mindfulness (n = 180) were significantly more effective than the EMA control (n = 29) in reducing DASS-21 total scores (physical activity vs control: standardized mean difference [SMD], 0.62 [95% CI, 0.23-1.02]; mindfulness vs control: SMD, 0.53 [95% CI, 0.19-0.87]) and sleep hygiene (n = 61) (physical activity vs sleep hygiene: SMD, 0.50 [95% CI, 0.16-0.84]; mindfulness vs sleep hygiene: SMD, 0.41 [95% CI, 0.13-0.69]). Among 494 participants with mild distress, physical activity (n = 161) and sleep hygiene (n = 224) were significantly more effective than control (n = 37) in reducing DASS-21 total scores (physical activity vs control: SMD, 0.58 [95% CI, 0.30-0.86]; sleep hygiene vs control: SMD, 0.47 [95% CI, 0.20-0.73]). No significant group differences were observed among participants with moderate distress (n = 439). Conclusions and Relevance:In this AI-enhanced response-adaptive randomized clinical trial among college students, physical activity and mindfulness were most effective for severe distress, while physical activity and sleep hygiene were most effective for mild distress. These findings can guide personalized mental health interventions for college students. This trial improved efficiency by minimizing control group allocation but had reduced power to detect significant group differences. Trial Registration:http://anzctr.org.au Identifier: ACTRN12621001223820.

Typing behaviour derived from smartphone keystroke metadata is an emerging digital phenotype that may assist in diagnosing and monitoring depressive symptoms. While psychomotor agitation and slowing have been hypothesised as depressive symptoms that may influence typing behaviour, no studies have directly tested this assumption. Here, we tested whether specific depressive symptoms were associated with various keystroke features of typing behaviour in adolescents. Adolescents from an Australian cohort study (n = 895) completed a typing task on their smartphones. Common features of keystroke timing (i.e., median, dwell, interval, latency, down-down time, and up-up time) and frequency (i.e., total keystrokes, backspaces, spaces, backspace ratio, and spaces ratio) were extracted. Depressive symptoms were assessed using the Patient Health Questionnaire-Adolescent version (PHQ-A). Multiple linear regression models were used to test associations between symptom items and keystroke features. Non-linear effects and moderating effects of sex were also explored. Psychomotor symptoms (i.e., PHQ-A item 8) were not associated with keystroke timing or frequency. However, higher appetite symptoms (i.e., PHQ-A item 5) were associated with faster down-down time and a greater number of total key presses. Symptoms of anhedonia (i.e., PHA item 1) showed non-linear associations with keystroke features. The results do not support a relationship between psychomotor symptoms and typing behaviour in adolescents. However, appetite-related symptoms were associated with faster and more frequent typing. Further research into the relationship between typing behaviour and mental health in young people is warranted. Clinical Trial Registry: ACTRN12619000855123.

While it is widely acknowledged that co-design will enhance project outcomes, including for digital health innovation, the definition and application of co-design remain heterogenous. Efforts to systematise co-design as a meaningful and rigorous methodology, have been made over the past decades using co-design frameworks. However, we find that co-design frameworks present challenges when operational contexts are complex, and research problems nebulous, as is often the case in digital health research and development initiatives. Here, we present our experience of co-designing a self-guided supportive care digital health platform for Australians affected by brain tumours, called ‘Brain Tumours Online’. The Brain Tumours Online platform seeks to mitigate unmet supportive care needs of patients and their carers through a three-pronged approach: a repository of evidence-based information, an online peer support community, and a directory of validated digital therapeutic tools. Our co-design approach for this platform was influenced by three key contextual considerations: a) disparate operating models and competing priorities of partner organisations; b) patient population-specific needs; and c) the need to practice epistemic flexibility and adaptation to evolving project needs. Instead of following a standardised co-design framework, we adopted methodological pluralism, with a bespoke multi-modal co-design approach. This approach allowed us to combine strengths of various stakeholders and mitigate organisational barriers of working across sectors, characteristic of digital health initiatives in healthcare. Layperson summary In the realm of digital health innovation, co-design is recognized as crucial for achieving successful outcomes. Co-design refers to a participatory method whereby stakeholders, such as patients and carers, collaborate with design professionals to design solutions for problems. In the past, applying co-design methods has proved to be challenging, as there exist many different interpretations and contexts. In this paper, we reflect on the complexities we experienced when co-designing a supportive care digital health platform for Australians affected by brain tumours. Challenges encountered during this study included differing organizational priorities among partners, specific needs of patients, and the necessity for adaptable methods that respond to evolving project demands. To address these challenges, we used a variety of methods instead of adhering to a single systematized co-design framework. Our experience highlights how incorporating adaptability and engaging with different stakeholders in flexible ways can lead to better outcomes for digital health projects. By sharing what we have learned, we hope to encourage more flexible and collaborative approaches in digital health innovation, which can make treatments and tools more effective and useful for everyone involved.

QuestionWhich brief digital intervention most effectively reduces mild, moderate, and severe levels of psychological distress among college students?FindingsThis artificial intelligence-enhanced response-adaptive randomized clinical trial involving 1282 distressed college students found that smartphone-based physical activity and mindfulness were most effective for severe distress and that physical activity and sleep hygiene were most effective for mild distress; no significant differences were observed for moderate distress. The trial's novel methods improved efficiency by reducing control group allocation.MeaningThese findings support using brief smartphone-based physical activity for mild and severe distress, mindfulness for severe distress, and sleep hygiene for mild distress. ImportanceA large proportion of college students report experiencing psychological distress. Smartphone app-based interventions may alleviate distress, but their effectiveness across severity levels is unclear. Artificial intelligence (AI)-enhanced response-adaptive randomized clinical trials may offer an efficient method to evaluate competing interventions.ObjectiveTo compare the effectiveness of 3 brief, 2-week self-guided smartphone application-based interventions (physical activity, mindfulness, sleep hygiene) or an active control (ecological momentary assessment [EMA]) for reducing psychological distress among college students with mild, moderate, or severe distress.Design, Setting, and ParticipantsThis population-based AI-enhanced response-adaptive randomized clinical trial included 1282 participants with distress scores of 20 or more on the 10-item Kessler Psychological Distress Scale in 12 minitrials from November 9, 2021, with final follow-up on February 17, 2023. Participants' distress was categorized as mild, moderate, or severe based on their normalized 21-item Depression Anxiety Stress Scale (DASS-21) scores at screening.InterventionsAfter a 2-week onboarding period of daily EMA, participants were assigned by a contextual multi-armed bandit algorithm to 1 of 4 two-week self-guided app interventions: physical activity, mindfulness, sleep hygiene, or a control that continued EMA.Main Outcomes and MeasuresThe primary outcome was change in psychological distress (DASS-21 total score) from week 2 (before intervention) to week 4 (after intervention). The primary end point was after the intervention (4 weeks). Secondary outcomes included DASS-21 subscale scores, self-reported physical activity, mindfulness, sleep quality, and app engagement, usability, and satisfaction. Analysis was performed on an intention-to-treat basis.ResultsA total of 1282 individuals (mean [SD] age, 23.5 [5.2] years; 950 women [74.1%]) participated: physical activity (n = 305), mindfulness (n = 453), sleep hygiene (n = 431), or a control that continued EMA (n = 93). Among 349 participants with severe distress, physical activity (n = 79) and mindfulness (n = 180) were significantly more effective than the EMA control (n = 29) in reducing DASS-21 total scores (physical activity vs control: standardized mean difference [SMD], 0.62 [95% CI, 0.23-1.02]; mindfulness vs control: SMD, 0.53 [95% CI, 0.19-0.87]) and sleep hygiene (n = 61) (physical activity vs sleep hygiene: SMD, 0.50 [95% CI, 0.16-0.84]; mindfulness vs sleep hygiene: SMD, 0.41 [95% CI, 0.13-0.69]). Among 494 participants with mild distress, physical activity (n = 161) and sleep hygiene (n = 224) were significantly more effective than control (n = 37) in reducing DASS-21 total scores (physical activity vs control: SMD, 0.58 [95% CI, 0.30-0.86]; sleep hygiene vs control: SMD, 0.47 [95% CI, 0.20-0.73]). No significant group differences were observed among participants with moderate distress (n = 439).Conclusions and RelevanceIn this AI-enhanced response-adaptive randomized clinical trial among college students, physical activity and mindfulness were most effective for severe distress, while physical activity and sleep hygiene were most effective for mild distress. These findings can guide personalized mental health interventions for college students. This trial improved efficiency by minimizing control group allocation but had reduced power to detect significant group differences.Trial Registrationhttp://anzctr.org.au Identifier: ACTRN12621001223820 This randomized clinical trial compares the effectiveness of 3 brief smartphone app-based interventions (physical activity, mindfulness, and sleep hygiene) or an active control (ecological momentary assessment) for reducing mild, moderate, and severe psychological distress among college students.

Background:Early cancer detection is crucial, but recognizing the significance of associated symptoms such as unintended weight loss in primary care remains challenging. Clinical decision support systems (CDSSs) can aid cancer detection but face implementation barriers and low uptake in real-world settings. To address these issues, simulation environments offer a controlled setting to study CDSS usage and improve their design for better adoption in clinical practice. Objective:This study aimed to evaluate a CDSS integrated within general practice electronic health records aimed at identifying patients at risk of undiagnosed cancer. Methods:The evaluation of a CDSS to identify patients with unintended weight loss was conducted in a simulated primary care environment where general practitioners (GPs) interacted with the CDSS in simulated clinical consultations. There were four possible clinical scenarios based on patient gender and risk of cancer. Data collection included interviews with GPs, cancer survivors (lived-experience community advocates), and patient actors, as well as video analysis of GP-CDSS interactions. Two theoretical frameworks were employed for thematic interpretation of the data. Results:We recruited 10 GPs and 6 community advocates, conducting 20 simulated consultations with 2 patient actors (2 consultations per GP: 1 high-risk consultation and 1 low-risk consultation). All participants found the CDSS acceptable and unobtrusive. GPs utilized CDSS recommendations in three distinct ways: as a communication aid when discussing follow-up with the patient, as a reminder for differential diagnoses and recommended investigations, and as an aid to diagnostic decision-making without sharing with patients. The CDSS's impact on patient-doctor communication varied, facilitating and hindering interactions depending on the GP's communication style. Conclusions:We developed and evaluated a CDSS for identifying cancer risk in patients with unintended weight loss in a simulated environment, revealing its potential to aid clinical decision-making and communication while highlighting implementation challenges and the need for context-sensitive application.

Background Psychological prevention programmes delivered in schools may reduce symptoms of depression. However, high-quality, large-scale trials are lacking.Objective The aim was to examine whether a digital cognitive–behavioural programme (‘SPARX’), delivered at scale in schools, would reduce depressive symptoms 12 months later.Methods A cluster randomised controlled trial with parallel arms (intervention; control) was conducted in Australian schools, between August 2019 and December 2022. Cluster randomisation occurred at the school level (1:1 allocation). Investigators were blind to group allocation, and outcomes were assessed at baseline, 6 weeks, 6 months (primary outcome only) and 12 months post baseline. The intervention was delivered via smartphone app. Schools were instructed to provide in-class time for intervention completion. The primary outcome was the difference in depressive symptom change from baseline to 12 months between the intervention and control group. Secondary outcomes were change in anxiety, psychological distress and insomnia.Findings 134 schools participated in this study, and baseline data were collected from n=6388 students (n=3266 intervention; n=3122 control). Intent-to-treat analyses showed no difference in depression change between groups from baseline to 12 months, (mean change difference= −0.05, z= −0.32, 95% CI: −0.36 to 0.23, p=0.75). There were no differences on secondary outcomes. Many schools did not provide in-class time for intervention completion, and engagement was low (22% completion rate).Conclusions Scaled delivery of a digital cognitive–behavioural programme did not reduce symptoms of depression, relative to a control group.Clinical implications Given the variability in the engagement with and delivery of the digital universal cognitive–behavioural programme, caution is required prior to scaled delivery of SPARX in school contexts.Trial registration number ACTRN12619000855123.

BACKGROUND:Access to healthcare significantly influences health outcomes, and rural, regional and remote populations face greater challenges in accessing healthcare than urban populations. Digital health tools, such as remote patient monitoring (RPM), have significant potential to address these healthcare challenges, yet there is little research on the facilitators and barriers of RPM in these regions. AIM:This study aims to identify and understand the facilitators and barriers healthcare staff face implementing RPM in rural and regional Australia, with focus on challenges that arose after the onset of the COVID-19 pandemic. METHODS:Semi-structured focus groups were conducted with healthcare professionals from publicly funded health services in western rural and regional Victoria, Australia. An open-ended interview guide based on the Consolidated Framework for Implementation Research (CFIR) was used to identify key themes and strategies for effective RPM implementation. The analysis considered barriers and facilitators at micro, meso, and macro levels. RESULTS:Several barriers to RPM implementation were identified across different levels: (1) Micro-Level Factors, such as perceived low digital literacy and language barriers among individuals; (2) Meso-Level Factors, including disparities in IT infrastructure and device availability, limited training opportunities, and the need for enhanced governance within healthcare settings; and (3) Macro-Level Factors, encompassing evolving funding models and the reliability of service providers. Despite these challenges, participants acknowledged potential benefits such as improved technological interoperability, enhanced community engagement, and a data-driven approach to quality improvement. Importantly, a flexible, tailored RPM approach to accommodate specific rural and regional needs was deemed valuable. CONCLUSION:Effective RPM deployment in rural and regional areas is viewed by health professionals as crucial for bridging healthcare divides. However, if strategies developed for urban settings are not recalibrated to address rural challenges, the risk of RPM failure may escalate. Future initiatives must prioritize region-specific strategies and policy reforms aimed at ensuring equitable digital infrastructure and financial resource allocation to enhance healthcare access in rural and regional settings. This approach may ensure that RPM solutions are both adaptable and effective, tailored to the unique needs of each community.

BackgroundWith increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence–driven adaptive trial—Vibe Up. ObjectiveWe evaluated the effectiveness of recruitment via Facebook and Instagram compared to traditional methods for a treatment trial and compared different recruitment methods’ retention rates. With recruitment coinciding with COVID-19 lockdowns across Australia, we also compared the cost-effectiveness of social media recruitment during and after lockdowns. MethodsRecruitment was completed for 2 pilot trials and 6 minitrials from June 2021 to May 2022. To recruit participants, paid social media advertising on Facebook and Instagram was used, alongside mailing lists of university networks and student organizations or services, media releases, announcements during classes and events, study posters or flyers on university campuses, and health professional networks. Recruitment data, including engagement metrics collected by Meta (Facebook and Instagram), advertising costs, and Qualtrics data on recruitment methods and survey completion rates, were analyzed using RStudio with R (version 3.6.3; R Foundation for Statistical Computing). ResultsIn total, 1314 eligible participants (aged 22.79, SD 4.71 years; 1079, 82.1% female) were recruited to 2 pilot trials and 6 minitrials. The vast majority were recruited via Facebook and Instagram advertising (n=1203; 92%). Pairwise comparisons revealed that the lead institution’s website was more effective in recruiting eligible participants than Facebook (z=3.47; P=.003) and Instagram (z=4.23; P<.001). No differences were found between recruitment methods in retaining participants at baseline, at midpoint, and at study completion. Wilcoxon tests found significant differences between lockdown (pilot 1 and pilot 2) and postlockdown (minitrials 1-6) on costs incurred per link click (lockdown: median Aus $0.35 [US $0.22], IQR Aus $0.27-$0.47 [US $0.17-$0.29]; postlockdown: median Aus $1.00 [US $0.62], IQR Aus $0.70-$1.47 [US $0.44-$0.92]; W=9087; P<.001) and the amount spent per hour to reach the target sample size (lockdown: median Aus $4.75 [US $2.95], IQR Aus $1.94-6.34 [US $1.22-$3.97]; postlockdown: median Aus $13.29 [US $8.26], IQR Aus $4.70-25.31 [US $2.95-$15.87]; W=16044; P<.001). ConclusionsSocial media advertising via Facebook and Instagram was the most successful strategy for recruiting distressed tertiary students into this artificial intelligence–driven adaptive trial, providing evidence for the use of this recruitment method for this type of trial in digital mental health research. No recruitment method stood out in terms of participant retention. Perhaps a reflection of the added distress experienced by young people, social media recruitment during the COVID-19 lockdown period was more cost-effective. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12621001092886; https://tinyurl.com/39f2pdmd; Australian New Zealand Clinical Trials Registry ACTRN12621001223820; https://tinyurl.com/bdhkvucv

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.

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.

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.

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. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12621000712808; https://trialsearch.who.int/Trial2.aspx?TrialID=ACTRN12621000712808

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