Patients with hereditary breast and ovarian cancer (HBOC) are not only concerned about their own health but also about that of their children, grandchildren, and other relatives. Therefore, they have specific needs for information and support. During genetic counseling guidance is provided to HBOC patients and other individuals who may be at risk for familial cancer. The purpose of the study was to identify the needs of HBOC patients during the genetic counseling process that could be addressed by digital solutions. Nine semi-structured qualitative interviews were conducted. Overall, the patients appreciated the personal contact with human geneticists as an especially positive factor in the genetic counseling process. However, patients noted the following needs (1) support in the time following genetic counseling, (2) support before genetic counseling by collecting own and familial medical information, (3) Need for contact options to support services, (4) Need for patient-friendly medical information, (5) Wish for administration-related components in a support app. The results will inform the development of a patient-centered mobile support app.

BACKGROUND: It is difficult for families to navigate and access services for their children with autism. Barriers to service access are compounded among families from low-resourced backgrounds.
OBJECTIVE: The purpose of our study was to explore the development of an app to facilitate access to services among families of children with autism from low-resourced backgrounds. Our specific aims were to explore feedback from an advisory board about the app and to explore feedback from navigators about the app.
METHODS: Via a multistage codevelopment process, we elicited feedback from 5 key parties: the research team, a community organization, the app development team, the advisory board, and family navigators. Collectively, 36 individuals provided feedback about the development of the app via individual interviews, focus groups, observations, and surveys. The key features of the app included a dashboard showing the service needs of the family and related resources, a messaging feature between the family, the navigator, and the supervisor, and a fidelity checklist and evaluation feature.
RESULTS: The advisory board provided feedback about the app to increase its user-friendliness, include the ability to develop an action plan, improve the identification of needed services, and add information about service providers. Navigators suggested that the app should connect navigators to one another, have a clearer purpose for the notes section, and reflect an easier log-in process. Navigators also wanted training to role-play using the app. After participating in a role play using the app, navigators reported significantly more satisfaction with the app and greater usefulness (P<.001).
CONCLUSIONS: Our work sheds light on the importance of eliciting feedback from end users, especially users who are often overlooked by the research community and app developers. Further, it is important to elicit feedback in multiple ways to improve the app.

Contamination of fresh produce with Listeria monocytogenes can occur throughout the supply chain, including at retail, where Listeria spp., including L. monocytogenes, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of Listeria transmission to fresh produce. Therefore, we developed an agent-based model that can simulate Listeria transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of Listeria introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., Listeria prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial Listeria concentration from incoming produce, (ii) transfer coefficient from produce to employee\'s hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (p < 0.0018) associated with the mean Listeria prevalence across all agents, suggesting that the accuracy of these parameters are important for prediction of overall Listeria prevalence at retail. Cluster analysis grouped agents with similar contamination patterns into six unique clusters; this information can be used to optimize the sampling plans for retail environments. Scenario analysis suggested that (i) more stringent supplier control as well as (ii) practices reducing Listeria transmission via consumer\'s hands may have the largest impact on reducing finished product contamination. Overall, we show that an agent-based model can serve as a foundational tool to help with decision-making on Listeria control strategies at retail.

UNASSIGNED: The individualized PREdiction of DIsease Control using digital sensor Technology (iPREDICT) program was developed for asthma management using digital technology. Devices were integrated into daily lives of patients to establish a predictive model of asthma control by measuring changes from baseline health status with minimal device burden.
UNASSIGNED: To establish baseline disease characteristics of the study participants, detect changes from baseline associated with asthma events, and evaluate algorithms capable of identifying triggers and predicting asthma control changes from baseline data. Patient experience and compliance with the devices were also explored.
UNASSIGNED: This was a multicenter, observational, 24-week, proof-of-concept study conducted in the United States.
UNASSIGNED: Patients (⩾12 years) with severe, uncontrolled asthma engaged with a spirometer, vital sign monitor, sleep monitor, connected inhaler devices, and two mobile applications with embedded patient-reported outcome (PRO) questionnaires. Prospective data were linked to data from electronic health records and transmitted to a secure platform to develop predictive algorithms. The primary endpoint was an asthma event: symptom worsening logged by patients (PRO); peak expiratory flow (PEF) < 65% or forced expiratory volume in 1 s < 80%; increased short-acting β2-agonist (SABA) use (>8 puffs/24 h or >4 puffs/day/48 h). For each endpoint, predictive models were constructed at population, subgroup, and individual levels.
UNASSIGNED: Overall, 108 patients were selected: 66 (61.1%) completed and 42 (38.9%) were excluded for failure to respond/missing data. Predictive accuracy depended on endpoint selection. Population-level models achieved low accuracy in predicting endpoints such as PEF < 65%. Subgroups related to specific allergies, asthma triggers, asthma types, and exacerbation treatments demonstrated high accuracy, with the most accurate, predictive endpoint being >4 SABA puffs/day/48 h. Individual models, constructed for patients with high endpoint overlap, exhibited significant predictive accuracy, especially for PEF < 65% and >4 SABA puffs/day/48 h.
UNASSIGNED: This multidimensional dataset enabled population-, subgroup-, and individual-level analyses, providing proof-of-concept evidence for development of predictive models of fluctuating asthma control.

BACKGROUND: Digital tools are progressively reshaping the daily work of health care professionals (HCPs) in hospitals. While this transformation holds substantial promise, it leads to frustrating experiences, raising concerns about negative impacts on clinicians\' well-being.
OBJECTIVE: The goal of this study was to comprehensively explore the lived experiences of HCPs navigating digital tools throughout their daily routines.
METHODS: Qualitative in-depth interviews with 52 HCPs representing 24 medical specialties across 14 hospitals in Switzerland were performed.
RESULTS: Inductive thematic analysis revealed 4 main themes: digital tool use, workflow and processes, HCPs\' experience of care delivery, and digital transformation and management of change. Within these themes, 6 intriguing paradoxes emerged, and we hypothesized that these paradoxes might partly explain the persistence of the challenges facing hospital digitalization: the promise of efficiency and the reality of inefficiency, the shift from face to face to interface, juggling frustration and dedication, the illusion of information access and trust, the complexity and intersection of workflows and care paths, and the opportunities and challenges of shadow IT.
CONCLUSIONS: Our study highlights the central importance of acknowledging and considering the experiences of HCPs to support the transformation of health care technology and to avoid or mitigate any potential negative experiences that might arise from digitalization. The viewpoints of HCPs add relevant insights into long-standing informatics problems in health care and may suggest new strategies to follow when tackling future challenges.

UNASSIGNED: Malnutrition is prevalent among cancer patients, smartphone-based self-administered nutritional assessment tools offer a promising solution for effective nutritional screening. This study aims to retrospectively analyze the relationships between nutritional status evaluated by the digital tool (R+ Dietitian) and clinicopathologic factors of cancer patients.
UNASSIGNED: Cancer patients who met the inclusion criteria were divided into two subgroups based on age, Nutritional Risk Screening-2002, Patient-Generated Subjective Global Assessment Short Form, body mass index, and hospital stays for comparison. Correlation and regression analysis were used to comprehensively assess the relationship between nutritional status and clinicopathologic factors.
UNASSIGNED: A total of 535 hospitalized cancer patients (58.32 ± 11.24 years old) were recruited. Patients identified with nutritional risk assessed by R+ Dietitian were significantly older, had lower body weight, lower body mass index, greater weight loss, and longer hospital stays (all of above, P < 0.01). Multiple logistic regression analysis indicated that serum prealbumin concentration (odds ratio: 0.992, 95% confidence interval: 0.987-0.997, P = 0.001), weight loss (odds ratio: 7.309, 95% confidence interval: 4.026-13.270, P < 0.001), and body mass index < 18.5 (odds ratio: 5.882, 95% confidence interval: 2.695-12.821, P < 0.001) predicted nutritional risk indicated by Nutritional Risk Screening-2002 score ≥3. Hemoglobin concentration (odds ratio: 0.983, 95% confidence interval: 0.970-0.996, P = 0.011), weight (odds ratio: 1.111, 95% confidence interval: 1.056-1.169, P < 0.001), weight loss (odds ratio: 7.502, 95% confidence interval: 4.394-12.810, P < 0.001), body mass index (odds ratio: 0.661, 95% confidence interval: 0.564-0.775, P < 0.001), and energy intake (odds ratio: 0.996, 95% confidence interval: 0.995-0.997, P < 0.001) predicted nutritional risk indicated by Patient-Generated Subjective Global Assessment Short Form score ≥4. Multiple linear regression analysis revealed that Patient-Generated Subjective Global Assessment Short Form scores ≥3 (b = 2.032, P = 0.008) were significantly associated with longer hospital stays.
UNASSIGNED: The nutritional risks assessed by R+ Dietitian accurately reflected the characteristics of malnutrition in cancer patients and predicted hospital stay and cost, indicating the applicability of R+ Dietitian to improving the efficiency of nutritional management for cancer patients.

Digital inclusion is considered a pivotal social determinant of health, particularly for older adults who may face significant barriers to digital access due to physical, sensory, and social limitations. Avatar for Global Access to Technology for Healthy Aging (AGATHA) is a virtual healthy aging coach developed by the World Health Organization to address these challenges. Designed as a comprehensive virtual coach, AGATHA comprises a gamified platform that covers multiple health-related topics and modules aimed at fostering user engagement and promoting healthy aging.
The aim of this study was to explore the perception and user experience of Malaysian older adults in their interactions with the AGATHA app and its avatar. The focus of this study was to examine the engagement, usability, and educational impact of the app on health literacy and digital skills.
We performed a qualitative study among adults 60 years and older from suburban and rural communities across six states in Malaysia. Participants were purposefully recruited to ensure representation across various socioeconomic and cultural backgrounds. Each participant attended a 1-hour training session to familiarize themselves with the interface and functionalities of AGATHA. Subsequently, all participants were required to engage with the AGATHA app two to three times per week for up to 2 weeks. Upon completion of this trial phase, an in-depth interview session was conducted to gather detailed feedback on their experiences.
Overall, the participants found AGATHA to be highly accessible and engaging. The content was reported to have a comprehensive structure and was delivered in an easily understandable and informative manner. Moreover, the participants found the app to be beneficial in enhancing their understanding pertaining to health-related issues in aging. Some key feedback gathered highlighted the need for increased interactive features that would allow for interaction with peers, better personalization of content tailored to the individual\'s health condition, and improvement in the user-experience design to accommodate older users\' specific needs. Furthermore, enhancements in decision-support features within the app were suggested to better assist users in making health decisions.
The prototype digital health coaching program AGATHA was well received as a user-friendly tool suitable for beginners, and was also perceived to be useful to enhance older adults\' digital literacy and confidence. The findings of this study offer important insights for designing other digital health tools and interventions targeting older adults, highlighting the importance of a user-centered design and personalization to improve the adoption of digital health solutions among older adults. This study also serves as a useful starting point for further development and refinement of digital health programs aimed at fostering an inclusive, supportive digital environment for older adults.

BACKGROUND: The efficacy of diagnostic and monitoring tools in ophthalmology is significantly influenced by patient engagement levels. This presents a notable challenge, especially in the context of developing tools designed for telemedicine applications. Ensuring consistent patient engagement is therefore crucial for the accurate and reliable utilization of these technologies. This study assesses patient perceptions and experiences after using a purpose-built web application, called PocDoc.
METHODS: A cross-sectional questionnaire-based survey was conducted among 440 patients recruited from general and specialist eye clinics between March 2022 and October 2023, both before and after using the PocDoc app.
RESULTS: Pre-test findings revealed that 86.8% of patients thought that a remote eye monitoring application would have use, while 70.9% anticipated frequent usage. Only 16.4% found it overly complex, and 55.2% perceived it as easy to use. Additionally, 34.5% foresaw the need for technical support, while 72.5% believed they would quickly grasp its use. In the post-test questionnaire, 63.3% of patients still expressed intent for frequent PocDoc usage. The perception of complexity decreased to 20.4%, with 79.3% finding it easy to use. The belief in the need for technical support decreased to 36.5%, while 89.9% felt confident in mastering the application quickly. Moreover, 77.3% found the application\'s functions well-integrated, and 64.6% were very confident using PocDoc.
CONCLUSIONS: Results suggest patient receptivity to web-based applications, confirming their viability for specific patient groups. Overall, our study contributes to the growing body of evidence indicating that greater exposure to digital health tools can significantly influence patient acceptance and perceived ease of use, an insight that has important implications for the implementation and design of these technologies in clinical settings.

OBJECTIVE: In order to share their knowledge, sterilization unit managers publish the results of their work in journals or at scientific conferences. The aim of Enthalpies is to list all such work in a single database. The work presented describes the construction of this database and the assessment of its feasibility for the washing step.
METHODS: The first step was to carry out a literature review. Only articles published over 10years (2013-2023) in connection with the ten-year washing stage were included. Then, each publication was categorized, coded, graded and summarized by a pharmacist-internal pair. All this data was collated in an Excel® spreadsheet, and from the data categorization a tree structure was created, enabling the interface between the user and the platform hosting Enthalpies to be understood.
RESULTS: Eighty-one publications were identified. These were categorized into 6 themes and 27 sub-themes. A reading grid was drawn up for each publication. Genially®, an online platform, was chosen to host our database.
CONCLUSIONS: Enthalpies was not designed to issue recommendations for best practice. However, by collating published scientific data, this tool can be used to assist decision-making. It represents an innovative solution for providing a literature review in the field of hospital sterilization.

Most of the recent studies indicated the prevalence of Post-Traumatic Stress Symptoms (PTSS) are increasing after the COVID pandemic around the world. Bo et al. reported PTSS prevalence of 96.2% among the COVID-19-infected people. The sociocultural and individual vulnerability and protective factors may influence onset and maintenance of the symptoms. However, there is significant lack in understanding the risk factors and preventive factors that influence the maintenance of Post-Traumatic Stress symptoms that defines Post-Traumatic Stress Disorder (PTSD). The digital technology gives us the unique opportunity to assess this risk, to monitor and track this evolution longitudinally. In this research project we aimed to design and develop a smartphone application for longitudinal data collection enabling to (1) predict and follow the evolution of PTSS toward PTSD, (2) assess the relative efficacy of several methods to prevent the evolution of PTSS right after exposure to trauma (1-24 h), (3) educate people about psychological effects that can occur during and after trauma, normalize acute distress and refer to professional help if a disorder is constituted. We hope that this research project will help to understand how to maximize the self help support during the acute phase (golden hours) after trauma to prevent the transition from PTSS to PTSD. A video abstract can be found on https://www.youtube.com/watch?v=RZJehj3J8go&feature=emb_title.