There is a need to ensure that healthcare organisations enable their workforces to use digital methods in service delivery. This study aimed to evaluate the current level of digital understanding and ability in nursing, midwifery, and allied health workforces and identify some of the training requirements to improve digital literacy in these health professionals. Representatives from eight healthcare organizations in Victoria, Australia participated in focus groups. Three digital frameworks informed the focus group topic guide that sought to examine the barriers and enablers to adopting digital healthcare along with training requirements to improve digital literacy. Twenty-three participants self-rated digital knowledge and skills using Likert scales and attended the focus groups. Mid-range scores were given for digital ability in nursing, midwifery, and allied health professionals. Focus group participants expressed concern over the gap between their organizations’ adoption of digital methods relative to their digital ability, and there were concerns about cyber security. Participants also saw a need for the inclusion of consumers in digital design. Given the widening gap between digital innovation and health workforce digital capability, there is a need to accelerate digital literacy by rapidly deploying education and training and policies and procedures for digital service delivery.

Although many young people demonstrate resilience and strength, research and clinical evidence highlight an upward trend in mental health concerns among those aged 12 to 25 years. Youth-specific digital mental health interventions (DMHIs) aim to address this trend by providing timely access to mental health support for young people (12–25 years). However, there is a considerable gap in understanding young people user experiences with digital interventions. This review, co-designed with Australia’s leading mental health organization Beyond Blue, utilizes a systematic methodology to synthesize evidence on user experience in youth-oriented digital mental health interventions that are fully or partially guided. Five relevant online databases were searched for articles published from 2018 to 2023, yielding 22,482 articles for screening and 22 studies were included in the present analysis. User experience outcomes relating to satisfaction and engagement were assessed for each included intervention, with experience indicators relating to usefulness, usability, value, credibility, and desirability being examined. Elements associated with positive/negative outcomes were extracted. Elements shown to positively influence user experience included peer engagement, modern app-based delivery, asynchronous support, and personalized content. In contrast, users disliked static content, homework/log-keeping, the requirement for multiple devices, and social media integration. Asynchronous interventions showed high satisfaction but faced engagement issues, with combined asynchronous/synchronous interventions reporting better completion rates. DMHIs offer a promising platform for youth mental health support and has the potential to dramatically increase the reach of interventions through the adoption of technological and user experience best practices. While young people respond positively to many aspects of intervention modernization, such as interactive, app-based design, other concepts, such as social media integration, they need to be adopted by the field more cautiously to ensure trust and engagement.Trial Registration CRD42023405812

Background: Mental illness has become a prevalent issue impacting adolescents worldwide. Many barriers, including stigma and poor health literacy, prevent this population group from accessing reliable mental health care services. Synchronous text–therapy counseling is an underused therapeutic approach in combating adolescent mental illness. Phone-based text therapy is uniquely placed to offer personalized counseling to adolescents through a familiar and engaging treatment modality. Objective: This rapid review aims to understand the clinical effectiveness, usability, and accessibility of phone-based text therapy for youth mental health. Methods: Cochrane CENTRAL, Embase, PubMed, and PsycINFO were used to search for suitable literature. Five groups of keywords were used: those related to (1) “therapy,” (2) “text,” (3) “phone,” (4) “youth,” and (5) “mental health.” Eligibility criteria were formed through the PICO (Population, Intervention, Control, and Outcome) framework. Studies were included if a synchronous phone-based text therapy intervention was used in an adolescent population, with an age range of 12-24 years. Only literature available in full-text, English, and a peer-reviewed journal was considered. Furthermore, a date limit of 5 years was set to reflect the recent development of digital interventions for mental health. Pertinent information from each study was tabulated, and a narrative synthesis was used to assess, describe, and organize the included studies comprehensively and concisely. Results: Of the 771 studies dual screened, 7 studies were included in this rapid review. Most of the exclusions occurred due to the use of the wrong intervention, such as asynchronous messaging. The selected studies had a low risk of bias and were suitable for the review. All interventional trials demonstrated reductions in mental health symptoms, primarily depression and anxiety. Most studies displayed high usability among participants, while data were unclear regarding accessibility. Conclusions: This review reveals the high potential of phone-based text therapy as an intervention for adolescents experiencing mental illness. We hope that this review promotes further refinement of text-based phone therapies and encourages future research on this subject matter.

Background: News of the impact of COVID-19 around the world delivered a brief opportunity for Australian health services to plan new ways of delivering care to large numbers of people while maintaining staff safety through greater physical separation. The rapid pivot to telemedicine and virtual care provided immediate and longer term benefits; however, such rapid-cycle development also created risks. Objective: The aim of this study was to understand the sociotechnical aspects of the rapid-cycle development of seven different COVID-19 virtual care tools, and to identify enablers, barriers, and risks at three health services in Victoria, Australia. Methods: A qualitative, embedded, multiple case study design was adopted. Researchers from three health services collaborated with university researchers who were independent from those health services to gather and analyze structured interview data from key people involved in either clinical or technical aspects of designing and deploying seven different virtual care tools. Results: The overall objectives of each health service reflected the international requirements for managing large numbers of patients safely but remotely and for protecting staff. However, the governance, digital maturity, and specific use cases at each institution shaped the methodology and specific outcomes required. Dependence on key individuals and their domain knowledge within an existing governance framework generally enabled rapid deployment, but sometimes posed barriers. Existing relationships with technical service developers enabled strong solutions, which in some cases were highly scalable. Conventional project methodologies such as steering committees, scope, budget control, tight functional specification, consumer engagement and codesign, universal accessibility, and postimplementation evaluation were ignored almost universally in this environment. Conclusions: These three health services took a variety of approaches to the rapid-cycle development of virtual care tools to meet their urgent needs for triaging and remote monitoring during the first year of the COVID-19 pandemic. Their experiences provided insights into many social and technical barriers and enablers to the development of virtual care tools. If these are addressed proactively, they will improve clinical governance and technical management of future virtual care. Some changes can be made within individual health services, while others entail health system policy reforms. Enhancing the environment for virtual care tool design and implementation now will yield returns not only during future health emergencies but also in many more routine care settings.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The use of artificial intelligence (AI) in health care has been steadily increasing for over 2 decades. Integrating AI into neonatal intensive care units (NICUs) has promise as it has the potential to reshape neonatal care and improve outcomes. However, challenges such as data quality, clinical interpretation, and ethical considerations may hinder AI’s practical implementation in NICUs. Objective: This study aims (1) to analyze the current AI research landscape for predicting clinical outcomes and length of stay in the NICU and (2) to explore the benefits and challenges of using AI in the NICU for these predictions. Methods: A systematic review was conducted across 6 databases—PubMed, Embase, CINAHL, Cochrane Library, Informit, and La Trobe Library—to identify English-language peer-reviewed articles published between January 2017 and March 2023 that focused on the use of AI for predicting length of stay and clinical outcomes for NICU patients. Eligibility criteria excluded studies outside the NICU context or lacking predictive focus. Both prospective and retrospective designs were included. A thematic analysis of AI applications in NICUs from the articles identified was conducted. Results: A total of 24 studies were included in the review, comprising 15 retrospective and 9 prospective designs. These studies primarily originated from the United States (13 studies), with others from Austria, Taiwan, and other countries. The studies evaluated AI applications in NICU settings to predict comorbidities (18/24), mortality (4/24), and length of stay (2/24). Sixteen studies were in the exploration stage, lacking cohesive AI strategies, while 8 demonstrated systematic exploration but no fully integrated solutions. The synthesis of results identified key applications of AI in NICU care, including data-driven insights and predictive models, advancements in medical imaging, improved risk stratification, and personalized neonatal care. AI showed promise in enhancing diagnostic accuracy and care planning, but significant challenges persist, such as data quality, model generalization, and ethical concerns. No studies reported a fully integrated AI ecosystem, highlighting the need for further research to bridge gaps and realize AI’s transformative potential in neonatal care. Conclusions: This review highlights the potential of AI in improving NICU care, particularly through predictive models, medical imaging, and personalized interventions. However, the evidence is limited by significant methodological variability, small sample sizes, risk of bias, and a lack of external validation in included studies. Many studies remain in exploratory phases without cohesive AI strategies or integration into clinical practice, limiting the practical applicability of findings. These results underscore the importance of addressing challenges such as data quality, model generalization, and ethical considerations to fully realize AI’s potential in neonatal care. Future research should focus on robust validation, comprehensive implementation strategies, and ethical frameworks to ensure AI's effective and responsible integration into NICU settings. Trial Registration:

This Rapid Evidence Assessment (REA) aimed to investigate the impact of electronic medical record (EMR) implementation on the process and outcomes of nursing handover by synthesising the existing scientific literature. Clinical nursing handover involves transferring patient information, responsibility and accountability to ensure continuity of care and patient safety. Poor or absent clinical handover can negatively impact quality of care, patient safety and patient outcomes. EMRs are patient information systems that facilitate the real‐time sharing of patient data. It has been proposed that EMRs may assist in addressing communication issues often associated with poor nursing handover, yet the implementation and impact of EMR implementations remain varied. A database search was conducted in PubMed, CINAHL and Cochrane. Articles for inclusion were studies in which the impact of an EMR implementation was evaluated, where participants were nurses performing handover from shift to shift in a hospital setting. Eleven studies from 4 different countries were included. The study findings revealed 4 broad themes that serve to answer the research question: use of the EMR during handover; nurse perceptions and satisfaction with the EMR; barriers to use; and enablers to use. EMR‐mediated handover was described in 7 studies. EMR‐structured handover was described in 7 studies. EMR‐generated printouts were described in 4 studies. While the EMR was routinely used to validate and check certain pieces of information during handover, nurses considered their personalised paper‐based forms to be the preferred handover tool. The main findings were that nurses generally expressed dissatisfaction with using the EMR to facilitate handover, with three studies reported dissatisfaction with EMR‐based handover. 50% of nurses found printouts cumbersome, and 69% reported irrelevant information. Barriers to EMR use included 6 studies that identified design‐related barriers. 4 studies emphasised the importance of cognitive support and situational awareness. 4 studies highlighted the lack of nursing engagement and codesign. 5 studies discussed variations in nurse digital literacy. Enablers to EMR use included two studies highlighting the importance of nurse engagement and codesign in successful EMR‐facilitated handover. Three studies showed nurses deliberately adopting EMR‐based handover tools, contrasting with previous examples of forced adaptation. No single tool was able to provide nurses with the whole patient story, the required situational awareness, nor the cognitive support required to convey and receive information during handover. An effective EMR‐mediated solution that improves the efficacy and quality of nursing handover has not yet been realised. Future efforts to design EMR‐mediated solutions to better support nurses must fully appreciate the complexities of nursing handover, the mental workload associated with the task and the definitive qualities of tools to provide this support. This REA has demonstrated the need for clinical nurses to be more directly involved in the iterative development and evaluation of these tools in order to specifically enhance processes and outcomes of nursing handover.