Use Of Apps Research Articles

Couple-Focused Smartphone Intervention to Reduce Problem Drinking: Pilot Randomized Control Trial.

Alcohol use disorder is among the most pervasive substance use disorders in the United States, with a lifetime prevalence of 30%. Recommended treatment options include evidence-based behavioral interventions; smartphone-based interventions confer a number of benefits such as portability, continuous access, and stigma avoidance; and research suggests that interventions involving couples may outperform those for patients only. In this context, a behavioral intervention delivered to couples through smartphones may serve as an effective adjunct to alcohol use disorder treatment. This pilot study aimed to (1) evaluate the feasibility of comparing a patient-only (Addiction version of the Comprehensive Health Enhancement Support System; A-CHESS) versus a couple-focused (Partner version of the Comprehensive Health Enhancement Support System; Partner-CHESS) eHealth app for alcohol misuse delivered by smartphone, (2) assess perceptions about and use of the 2 apps, and (3) examine initial indications of differences in primary clinical outcomes between patient groups using the 2 apps. Broadly, these aims serve to assess the feasibility of the study protocol for a larger randomized controlled trial. A total of 33 romantic couples were randomized to 6 months of A-CHESS app use (active treatment control) or Partner-CHESS app use (experimental). Couples comprised a patient with current alcohol use disorder (25/33, 76% male) and a romantic partner (26/33, 79% female). Patients and partners in both arms completed outcome measure surveys at 0, 2, 4, and 6 months. Primary outcomes were patients' percentage of days with heavy drinking and percentage of days with any drinking, measured by timeline follow back. Secondary outcomes included app use and perceptions, and multiple psychosocial variables. At 6 months, 78% (14/18) of Partner-CHESS patients and 73% (11/15) of A-CHESS patients were still using the intervention. The apps were rated helpful on a 5-point scale (1=not at all helpful, 5=extremely helpful) by 89% (29/33) of both Partner-CHESS patients (mean 3.7, SD 1) and partners (mean 3.6, SD 0.9) and by 87% (13/15) of A-CHESS patients (mean 3.1, SD 0.9). At 6 months, Partner-CHESS patients had a nonsignificantly lower percentage of days with heavy drinking compared with A-CHESS patients (β=-17.4, 95% CI -36.1 to 1.4; P=.07; Hedges g=-0.53), while the percentage of drinking days was relatively equal between patient groups (β=-2.1, 95% CI -24.8 to 20.7; P=.85; Hedges g=-0.12). Initial results support the feasibility of evaluating patient-only and couple-focused, smartphone-based interventions for alcohol misuse. Results suggest that both interventions are perceived as helpful and indicate maintained engagement of most participants for 6 months. A future, fully powered trial is warranted to evaluate the relative effectiveness of both interventions. ClinicalTrials.gov NCT04059549; https://clinicaltrials.gov/ct2/show/NCT04059549.

Covid-19 Policy Responses, Digital Health Apps and Data Sharing: Attitudes of Swiss Medical Students

Background: In this paper we present findings from a survey with 256 medical students in Switzerland about their perception of Covid-19 public health measures, their attitude towards digital health apps to respond to the pandemic, and whether the Covid-19 crisis changed their willingness to share their health data in the future for public health research purposes. Results: Results show that most respondents indicated to be somewhat negatively affected by the pandemic, but deemed the public health policy responses to the pandemic in Switzerland as just right or even as slightly too unrestrictive. Most respondents evaluate the use of apps to respond to the pandemic as positive, and 61.7% indicated that they used the contact tracing app and 97.6% the immunity certificate app. The latter was evaluated more positively than the former. They indicated that a better communication about its benefits or the possibility to share health data for research (e.g. by listing Covid-19 symptoms and vaccination status) would improve the contact tracing app. Nearly all respondents indicated that they would share their health data or samples for research purposes in the future. The types of data they would be willing to share are mostly questionnaires about their health status, blood samples and other biological samples, with social media being the least willing to share. Our findings highlight that most respondents believe that their attitude towards sharing data for public health research did not change during or with the Covid-19 pandemic. Conclusions: Recent developments in digital health app use were fuelled by the Covid-19 pandemic and the public – as a central actor – defined social trends with regard to digital health app uptake and willingness to share health data. With this survey we aimed to fill the gap of empirically examining how Swiss medical students – a young, technology- and medicine-inclined subpopulation, perceived the Covid-19 pandemic response, how they evaluate the related use of apps to respond to the pandemic as well as their willingness to share data for health research. The results may shed light on how the Covid-19-related use of technology and health data is changing the health landscape in Switzerland.

Exploring female fitness app users' motivations and perceptions: A qualitative study.

Women make up nearly 60% of fitness App users and play an important role in the operation and development of these Apps. Despite the widespread adoption of fitness Apps in recent years due to their many physical and mental benefits, the use of Apps tends to be short-term, and user engagement is relatively low. Little is known about the factors that motivate female users to consistently use fitness Apps. This study aimed to study attributes of fitness Apps that are most likely to influence female users during their use of Apps. The means-ends chain theory and the soft-laddering interview technique were used to analyze the attributes that influenced females' perceptions of fitness apps, focusing on the features most likely to provide them with benefits and value. The results of the study indicated that instructiveness, interaction, personalization, ease of use, and convenience were the most important attributes valued by female fitness App users; peer support, entertainment, and exercise adherence were the most important consequences; and health, self-fulfillment, enjoyment of life and sense of achievement were the most important values. The findings provide researchers and management of fitness Apps and women's sports with valuable insights from the means-ends chain theory, as well as suggestions for applying App design and promotion.

Effects of using a mobile application on pelvic floor training in women with stress urinary incontinence: A randomized controlled clinical study.

Urinary incontinence (UI) is defined as any involuntary loss of urine that causes negative impacts on women's lives. Pelvic floor muscle training (PFMT) is considered to be "level A" of scientific evidence in the treatment of UI. Despite its efficacy, it is known that the effect of PFMT may depend on continuous adherence. Therefore, healthcare professionals are looking for alternatives to improve adherence in their patients. Healthcare has been innovating through mobile device apps. Thus, the objective of this study was to verify the effects of PFMT with the use of a mobile device app in incontinent women. This was a controlled, randomized clinical trial that occurred remotely. A total of 104 women with stress UI and/or mixed incontinence, over 18 years old, literate, with preserved cognitive capacity, with internet access and a mobile device with the Android system, participated in this study. They were randomly divided into two groups: The App group and the Booklet group, which underwent a PFMT protocol guided by a mobile app and a booklet, respectively. Both groups received daily reminders to perform the exercises. Before and after 12 weeks of intervention, it was evaluated using the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) and the King's Health Questionnaire (KHQ). Both groups showed improvements in the final ICIQ-SF score. However, superior results were shown for the Booklet group (App: pre: 11.5 [±3.8], post: 9.8 [±4.5]; Booklet: pre: 12.6 [±4.5], post: 7.4 [±4.3]; p = 0.03). It was concluded that PFMT, with the use of a mobile app, is capable of reducing UI and the impact of UI, but it is not superior to training with the use of booklet instructions.

The impact of a lifestyle behaviour change program on healthcare costs: Quasi-experimental real-world evidence from an open-access mobile health app in the Netherlands

ObjectiveRecognizing the substantial role of modifiable risk factors such as physical inactivity, unhealthy diets, and substance use in driving global healthcare expenses, this study aims to assess the impact of a lifestyle behaviour change mobile health (mHealth) app on healthcare costs within a real-world setting. MethodsEmploying a difference-in-difference approach, this research compared healthcare costs between users of an mHealth app (treatment group) and a propensity score-matched control group of non-users. The study included data from 15,506 participants in the Netherlands, covering healthcare cost records collected from 2015 to 2019. ResultsThe implementation of the mHealth app was linked to a steady reduction in healthcare costs, achieving a 4.9 % decrease (β=−0.05,95%CI:−0.10to0.00) during the first year following the program's implementation, and a further 5.3 % decrease (β=−0.05,95%CI:−0.10to−0.00) in the second year. This healthcare costs reduction is associated with lower expenses for general practitioner services as well as diminished specialist visits. Additionally, increased app use led to further cost reductions, with frequency of use proving more important than intensity. ConclusionsThis study demonstrates that a behaviour change mHealth app is linked to significant reductions in healthcare costs, with more frequent and intense use leading to greater savings. Given their relatively low cost and ability to reach diverse population groups, such apps not only enhance individual health outcomes but can also serve as effective policy tools for large-scale health promotion, supporting broader societal health improvements.

Developing a smartphone web app to help DWI offenders and their families

IntroductionDriving while intoxicated (DWI) results in significant morbidity and mortality. Ignition interlock devices (IID) decrease the risk of drinking and driving while installed, but DWI rates increase after the IID is removed. Efforts are needed to maintain change after the IID is removed; engaging concerned family members (CFMs) is an untested strategy. Smartphones may provide a promising platform to support DWI offenders with IIDs and their CFMs; the purpose of the present study was to develop such a smartphone-web app. MethodsFormative work occurred in two sequential phases. Phase 1 included key informant interviews with DWI offenders and CFMs, development of one app module, and usability testing. Phase 2 included focus groups with DWI offenders and CFMs, development of three more app modules, and usability testing. The Bangor System Usability Scale was used to rate app usability and navigability. ResultsResults of key informants and focus groups indicated that offenders and CFMs lacked information and were frustrated by the IID, experienced financial burden from the DWI and IID, viewed supportive communication and positive shared activities as important, and were positive about the app. Four modules were developed, Life with Interlock, Supporting Changes in Drinking, Doing Things Together, and Effective Communication. Usability testing indicated that the B-SMART modules were easy to use and informative. ConclusionsCareful formative work resulted in an app responsive to the concerns of DWI offenders with IIDs and their CFMs. Controlled research is needed to evaluate the efficacy of the app.

Assessment of Acceptability, Usage, and Impact on Caregivers of Children With Autism's Stress and Mindfulness: Multiple-Method Feasibility Study of the 5Minutes4Myself App's Mindfulness Module.

Caregiver wellness programs need to be easily accessible to address caregivers' constraints to participation. We aimed to assess the feasibility of 5Minutes4Myself app's mindfulness module (usability, usage, and impact on caregivers' levels of mindfulness and perceived stress). Before and after participation in the 5Minutes4Myself program, 15 participants were asked to complete the Perceived Stress Scale (PSS) and Five Facet Mindfulness Questionnaire (FFMQ). Data on the usage of app-delivered meditations were collected electronically via the app, and app usability was rated on the Modified System Usability Scale. Analyses assessed participants' frequency of use of app-delivered meditations, app usability, and changes in participants' stress and mindfulness post intervention. Overall, participants completed 10.9 minutes of mindfulness meditations per week and rated the app 76.7, indicating above-average usability. Related samples t tests (2-tailed) found that group PSS (t10=1.20, P=.26) and FFMQ (t10=-1.57, P=.15) pre- or postintervention mean scores were not significantly different. However, a visualization of pre- and post-PSS and mindfulness scores suggested there was a group of responders who had decreased stress with increased mindfulness. This was confirmed via an individual change analysis. The effect size of the FFMQ scores (d=0.47) suggests there may be treatment effects with a larger sample. A hierarchical multiple regression analysis examined the degree mindfulness impacted perceived stress; 20% of the variance in participants' perceived stress could be attributed to increases in self-rated mindfulness (P=.04) when controlling for preintervention stress levels. Caregivers found the app highly usable and on average used low-dose levels of mindfulness meditations (10 min/wk). For responders, increased mindfulness was related to stress reduction to population-based levels.

Identifying barriers of financial app usage and their impact on negative emotions, customer ratings and recommendation intention: a text-mining based approach

PurposeLimited studies in the mobile payment segment have attempted at understanding the factors that resist customers from using financial apps or mobile payment services (MPSs). This study aims at identifying the barriers from online customer reviews and examine how these barriers affect customers’ negative emotions (anger, fear, sadness), customer ratings and recommendation intentions.Design/methodology/approachThis study, divided into three phases, has adopted a text-mining based mixed-method approach on 14,043 reviews present in Google PlayStore or App Store pages about financial apps used in India.FindingsPhase 1 identified barriers like, “bad user experience”, “UPI failure”, “trust issues”, “transaction delays” from the reviews. Phase 2 found that “bad user experience” and “UPI failure” trigger both “anger” and “sadness”. “Transaction delays” and “money lost in transaction” stimulate “fear”. From the IRT stance, in Phase 3 this study has found that barriers like, “transaction error”, “UPI failure” (usage), “bad user experience” (image) and “trust issues” (tradition) have a significant negative impact on both customer ratings and recommendation intention.Originality/valueThe current study contributes to the existing literature on MPSs by identifying barriers from user generated content. Additionally, this study has also examined the impact of the barriers on customers’ negative emotions and recommendation intention.

Family-based mobile application needs in childhood obesity management in South Korea: a qualitative study.

It is essential to investigate the users' needs in developing user-centered, family-based applications (apps) for managing childhood obesity. This study conducted focus group interviews with ten parents, ten children, and four app developers to investigate the need to develop a family-based mobile app for childhood obesity. The interview period was from July 17 to August 30, 2023. The data were analyzed using thematic analysis. The results highlighted 31 key themes critical to family-based app development, including the need for comprehensive content promoting healthy lifestyle habits, tailored expert support, and motivational factors for app engagement, which were categorized as intrinsic, extrinsic, and social motivations and technological features. Participants also highlighted potential challenges, such as app usability issues and the need for a user-friendly interface. The pivotal role of parents in guiding and supporting their children's health behaviors was emphasized, particularly in creating a supportive environment that encourages sustained engagement with the app. These findings provide a comprehensive understanding of the needs and preferences of parents, children, and app developers in managing childhood obesity. Emphasis on integrating healthy lifestyle content, providing expert support, and incorporating motivational strategies is crucial for the app's success. Additionally, addressing potential difficulties and recognizing the pivotal role of parents are essential considerations. These insights will inform the design and development of a user-centered mobile app that supports families in managing childhood obesity.

Usability and engagement of web application on parental behaviors for child obesity intervention

Background: Childhood obesity is a growing global health issue, with increasing prevalence in Asian countries, including Malaysia. Web applications such as JEJAK BMI offer an alternative intervention to address this concern by targeting parental behaviors that could influence their children’s weight. The usability and engagement of the app used are important elements that could influence the intervention outcome. Objective: To assess the engagement and usability of JEJAK BMI apps that could affect parental use of apps in child obesity interventions. Methods: To evaluate the app’s usability, three criteria were evaluated which were ease of use, visual appeal and functionality, post-intervention questionnaires were completed by the parents. Results: The study found that most parents considered the app practical, easy to use, visually engaging and functional. However, the impact on children's BMI over the short term was inconclusive. Conclusion: The JEJAK BMI web application demonstrated strong usability and positive effects on parental behaviors. Nonetheless, significant changes in children's BMI may require longer-term interventions and additional strategies.

Acceptability and Scalability of a Meditation App Among Adolescents With Type 1 Diabetes Mellitus.

Background Adolescents with type 1 diabetes mellitus (T1DM) experience stress from general life stressors and diabetes-specific stressors. This stress manifests in a range of ways, such as mood swings, heightened frustration, strained familial relationships, and difficulties in T1DM self-management, which then leads to worse health outcomes. There is small to moderate evidence that frequent use of mental health applications (MHapps) improves mental and physical health outcomes. Meditation apps may help reduce some of the stress associated with living with T1DM. This study explores the acceptability and scalability of a self-guided, smartphone-based meditation app, the Healthy Minds Program (HMP) app, among adolescents with T1DM using the Unified Theory of Acceptance and Use of Technology. Methods Eight adolescents ages 15-19 were recruited from a pediatric clinic in a Midwestern state and introduced to the HMP app. After using the HMP app for one week, they were invited to participate in three successive focus group meetings. During the meetings, they shared their perspectives on the content, navigation, and acceptability of the HMP app and strategies to introduce and scale app utilization among adolescents with T1DM. Researchers conducted conventional content analysis using a hybrid coding approach. Data was managed and analyzed using NVivo 10 (Lumivero, Denver, Colorado, USA). Findings Participants believed that the HMP app has the potential to enhance their stress management, mood, and coping abilities when dealing with the challenges of T1DM management. They found the app enjoyable and easy to use but expressed concerns about time constraints as a potential barrier. To address this, they shared recommendations for facilitating app uptake and usage. Conclusions This study's results provide an in-depth understanding of how positively this subset of adolescents with T1DM viewed the HMP app. The participants also offered valuable suggestions that can promote the adoption and sustained use of MHapps by adolescents living with T1DM.

Initial Evaluation of Acceptability, Engagement, and Effectiveness of the MO App to Provide Tailored and Comprehensive Support for Smoking Cessation: Development and Usability Study.

Despite the growing availability of smoking cessation apps, low engagement and cessation rates have remained a significant challenge. To address this issue, we used a user-centered design to iteratively develop a mobile app (MO) to provide comprehensive, tailored, and evidence-based content to support smokers in their quitting journey. This study examined the acceptability, use, and preliminary efficacy of the MO app for smoking cessation. Specifically, we sought to understand smokers' preferred features, engagement, and satisfaction with MO; identify concerns in using the app and ways to improve the app; and evaluate its smoking cessation outcomes. Through 3 cohorts, we recruited 10, 12, and 85 adult smokers who attempted to quit smoking to pilot-test the MO app between December 2019 and July 2022. Participants were instructed to complete a baseline survey, interact with the app for 6 weeks, and fill in a postsurvey at week 6. Participants in cohort 3 completed an additional postsurvey at week 12. Participants' app use was tracked and analyzed. The primary outcome measures were participants' 7-day point prevalence abstinence at 6 and 12 weeks. Participants reported high levels of satisfaction with the MO app across all 3 cohorts, rating it between 4.40 and 4.76 on a scale of 5 for acceptability. Users engaged with app activities for an average of 89 to 159 times over 35 days. The most liked features of the app included "quit plan," "tracking," "reminders and notifications," "MOtalks," and "motivational quotes." The 7-day point prevalence abstinence rate of the modified intention to treat population in cohort 3 was 58% at 6 weeks and 52% at 12 weeks. Those who interacted more frequently with app features and engaged with more diverse activities were more likely to maintain abstinence at weeks 6 and 12. For each additional time logged into the app, the odds of staying abstinent at week 12 increased by 5% (odds ratio [OR] 1.05, 95% CI 1.01-1.08). Participants who earned >5000 points during app use also had higher odds of quitting at both 6 weeks (OR 3.12, 95% CI 1.25-7.75) and 12 weeks (OR 4.65, 95% CI 1.83-11.76), compared with those who earned <5000 points. Our study demonstrated that MO is a feasible mobile phone app with high acceptability and usability and can effectively deliver smoking cessation support to individuals who want to quit. Implications for developing and evaluating mobile phone apps for smoking cessation are discussed.

Young Adults Journey with Digital Fitness Tools-A Qualitative Study on Use of Fitness Tracking Device

Background Physical activity trackers possess the potential to encourage increased physical activity. However, users often exhibit poor long-term adherence to these devices, which may stem from a lack of understanding of the factors influencing their use, as well as changes in health behavior. This study aims to provide new insights into the types of health-related apps and devices that young people discover, select, and utilize, along with the underlying reasons for their choices. Methods Young adults aged between 18-25 years reporting the use and nonuse of health apps and wearables were recruited and participated in focus group discussions about app choice, features, their perceptions towards the physical activity trackers, and reasons for continued use and for not using one. A total of Nine FGDS were conducted among users, nonusers, and former users of physical activity tracker usage. Data was recorded, transcribed, and analyzed for themes in an iterative approach. Results The physical activity tracker users group stated that they had a sense of achievement, validation, and other motivational feedback, which helped with adherence. All three groups (user, non-user, and former user) had similar concerns about cost, reliability, accuracy, and dependency. Former users also reported that the idea of accomplishing the goals would create anxiety and, in turn, harm the body. Former users and nonusers expressed their concerns regarding lack of time and loss of motivation to track their physical activity. Nonusers had issues with the functionality of the device (ease of use, battery, notifications, apps hang) and were also aware of all the health benefits of using wearables. Conclusion Physical activity users group, former users group, and nonusers group shared concerns about accuracy, cost, and battery.

1.B. Round table: Artificial Intelligence in Mobile Health Apps: Ethical, Legal, and Regulatory Challenges

Abstract Globally, governments and public health authorities are integrating Artificial Intelligence (AI) techniques in mobile apps to improve public health. For example, during the COVID-19 outbreak, AI-driven chatbots were deployed to provide immediate health information and advice. AI-based mobile apps are also used to support mental health or for preventive healthcare, such as personalized dietary recommendations. Moreover, the use of generative AI for public health purposes is rapidly increasing. In 2024, the WHO launched S.A.R.A.H - a generative AI chatbot designed to provide information on major health topics such as healthy lifestyles and mental health. By integrating AI, public institutions could potentially achieve better health outcomes, improve efficiency, and enhance access to healthcare. However, the rapid adoption of AI public health apps also raises significant ethical, legal, and regulatory challenges. The large amounts of sensitive personal data collected and processed by such apps may create issues for privacy, data protection, and cybersecurity. At the same time, the tendency of AI to exhibit biases may deepen existing health inequities. The new EU ‘digital’ legal framework does not directly address these challenges. This workshop aims to convene leading experts working on AI in health to address these issues. We bring together scholars from different disciplines (health law, health policy, bioethics, biosciences). The workshop objectives are twofold: (1) to critically assess the current landscape of AI in public health apps from a legal, ethical, and regulatory point of view, and (2) to lay the groundwork for policy recommendations on how to ensure the deployment of AI apps for public health in compliance with ethical principles and fundamental rights. First, the panel explores the differences in the data protection regulation of AI public health apps in the EU and the US (speaker: James Hazel). Second, it discusses how these apps are regulated under the new EU Artificial Intelligence Act (speaker: Hannah van Kolfschooten). Third, it investigates the consequences of the European Health Data Space regulation on how health data can be processed through public health apps (speaker: Mahsa Shabani). Finally, as the cross-border use of apps complicates regulatory efforts, it discusses the need for international cooperation in establishing and enforcing guidelines (speaker: Vasiliki Rahimzadeh). The workshop will be conducted as a round table discussion with 4 short presentations of 5 minutes each. Speakers first present a key challenge posed by AI in mobile health apps, and then suggest a potential regulatory solution. This will be followed by a dialogue between panelists and the audience to share best practices on how to regulate AI in mobile public health apps from a legal, ethical, and regulatory perspective. The input will be used to develop a submission for the Call for papers of BMC Bioinformatics. Key messages • As public institutions are increasingly integrating AI technologies into their mobile public health solutions, it is crucial to evaluate the ethical, legal, and regulatory implications. • In light of current gaps in the EU legal framework, we convene scholars from different disciplines and legal systems to design guidelines on the ethical use of AI mobile apps for public health. Speakers/Panelists James Hazel University of Amsterdam, Amsterdam, Netherlands Mahsa Shabani University of Amsterdam, Ghent University, Amsterdam, Netherlands Hannah van Kolfschooten University of Amsterdam, Amsterdam, Netherlands Vasiliki Rahimzadeh Baylor College of Medicine, Houston, USA Pramiti Parwani University of Amsterdam, Amsterdam, Netherlands

What to expect when generating data through the use of a mobile health application

Abstract Background Digitalization has significantly expanded the possibilities for collecting health data. Besides options such as online surveys, data can be collected through the use of digital applications (apps). Once users have given their consent, contact information from the app registration can be accessed to invite the relevant target group for further surveys. To generate a sufficient amount of data, a high level of willingness to participate and long-term involvement are required. This study aims to illustrate the willingness to share data and what can be expected from it by means of the Neo-MILK app, which supports mothers during lactation. Methods The willingness to share data and the data resulting from the use of the app is shown by the frequency of consent to the different data use options and the users’ participation. Results While over 68% of the n = 1079 registered app users consented to the use of their app data, 47% agreed to be contacted again for scientific purposes. Data from n = 421 active users were available for analysis. From n = 220 mothers, milk pumping data was available. In 36% of cases, little (&amp;lt;10) or no information on pumping was provided. Of the users who agreed to be contacted again for scientific purposes, n = 300 were invited to participate in another survey and 23% (n = 69) participated. Conclusions In this example, the general willingness to share data and participate in further studies shows great potential for data collection. However, the data collection methods differ primarily in the motivation to participate. When collecting data through app usage, ensuring that the design of the app meets the needs of the user is essential to optimize the user experience and thereby generating complete data. If the use of contact information has been agreed to, incentives may be considered to increase the willingness to participate. Required ethics approvals and data protection regulations should also be ensured for app-based data collection. Key messages • Generating data via app usage as well as the collection of data through the use of users’ contact information shows great potential for health research. • App-based data collection should be considered when planning future health research projects.

2.F. Scientific session: Challenges in healthcare architectures

Abstract The Workshop titled “Challenges in healthcare architectures” - proposed and developed by the three EUPHA Section: Urban Public Health (URB), Public Mental Health (MEN) and Environmental Health (ENV) - is aimed to foster the dialogue between designers (architects and urban planners), Public Health experts (operators, professionals and epidemiologists), general/sanitary Directors of healthcare facilities and medical staff, to establish a multidisciplinary approach for understanding together how to create and manage the healthcare facilities of the future. According to the main Conference topic “Sailing the waves of European public health: exploring a sea of innovation”, the workshop mainly addresses both the “Health care services and systems” and the “Health workforce, practice and training” EPH24 conference topics. The Workshops purpose is to explore the concept for the hospital of the future, that should be resilient to changes and capable of protecting different users’ health and tackle the transforming social, economic, environmental and epidemiological needs of the context in which they are located. As in many other spheres and economic activities, the pandemic accelerated the processes of innovation and digitization that had somehow already been activated. The healthcare issue, the use of smart devices for a dialogue between the healthcare professionals and the pervasive use of apps to monitor certain health parameters, are just some of the megatrends that were being observed and which have now necessarily entered into everyday life. In the same way, the hospital, which in the face of this gradual process of dematerialization and relocation of ‘softer’ clinical-diagnostic activities, reaffirms itself as a center of the highest specialty for the treatment and care of acute patients, for high-level clinical and experimental re-search, for diagnostics and more complex operations. At the same time, and finally, the hospital is inserted in a territorial healthcare facilities network, that should be planned, designed, and managed. The workshop program includes inputs which they argue current experiences, emerging practices and scientific outcomes related to the hospital design, planning and management sphere, coming from four different European countries. From designing to managing practices, in “Hospital Design and planning in the line of Foresight of Health Needs” and in “Sustainability in the Next Generation Hospital”. From digitalization in national resilience experiences, in “Digital Health Spaces in the City of Lisbon. The Role of Digitalization in linking Boundaryless Hospitals and Smart Health Cities” to novel approaches for specific disease, in “Building bridges: mobile mental health care units in four European countries”. Key messages • Explore the “hospital of the future” concept, resilient to changes, capable of protecting users’ health, and to tackle the transforming social, economic, environmental and epidemiological needs. • Establish a multidisciplinary and territorial approach, for understanding together how to create and manage the healthcare network of the future.

EvalDepApps: How to evaluate depression management based on evidence and end users

Abstract The use of apps is increasing in the field of mental health due to their ease of use and accessibility, although there is not enough evidence on their effectiveness and safety. EvalDepApps aims to develop an evaluation tool for depression management apps. A systematic review with meta-analysis (SRMA) was performed to evaluate the efficacy and safety of apps for depression, and to identify the evaluation criteria used. PRISMA methodology was followed. The MEDLINE, PsycINFO, and Embase databases were consulted. The risk of bias was assessed with the RoB2 scale. An online 2 rounds Delphi was carried out to prioritize the most relevant criteria identified. 44 people (26 professionals, 18 patients) were invited. They were asked to rate the importance of each criterion on a Likert scale (1 - 6). Those that obtained a high consensus were selected; those with a medium were submitted to the 2nd round. Empathization (6) and co-design (6) sessions were held with patients (23) and professionals (33) in Catalonia, the Canary Islands and Andalusia to identify what relevant aspects the tool should have. Twenty-nine studies were included in the SRMA (67% unclear bias), finding a significant effect of mHealth interventions in reducing depressive symptoms compared to non-active control (Hedges g = −0.62, 95% CI: −0.87 to − 0.37, I2 = 87%). In Round 1 of the Delphi (59% participation) 24 criteria obtained a high consensus, 20 a medium and 7 a low. In Round 2 (52% participation), 4 criteria reached high consensus. The empathy sessions showed that the actions most requested by patients were reduce anxiety, and information about their condition; for professionals, suicide prevention. Regarding co-design, it was proposed that the tool provide ranking of the apps, recommendation systems and a very visual format. The RSMA and Delphi guarantee that the tool will be based on scientific evidence and expert judgment, while empathization and co-design that it will fit with the needs of end users. Key messages • It is relevant to evaluate the quality of health apps, especially those addressed to vulnerable populations such as people with depression. • It is crucial that the development of evaluation tools for digital health interventions will be developed based on evidence-based but also includes end users.

Usability Insights from the BUMPER Cancer Prevention App Pilot Study: A Mixed-Methods Approach

Abstract Introduction As the second leading cause of death in the EU, cancer is expected to see a 55% rise in new cases globally over the next two decades. The European Code Against Cancer (ECAC) and the EU’s Beating Cancer Plan (EBCP) provide resources for understanding and preventing cancer. The BUMPER project aims to develop a cancer prevention App to make the ECAC more accessible to the public. Objectives Understand the factors influencing the use of a cancer prevention app among users with different digital health literacy levels and to evaluate the app’s usability. Methods Mixed-methods approach was used to gather user feedback. FGDs explored user perspectives on app usage, while a cross-sectional survey assessed usability through task completion on an initial app wireframe. The pilot was conducted across seven EU countries in late 2023. Results 77 participants participated in the pilots and FGDs across seven EU countries. The average task completion time was approximately 79 seconds. Participants rated their confidence to complete the tasks at 3.96 and difficulty at 2.28 on a scale of 1 to 5. The average task pass rate was 92.11%. Qualitative findings highlighted the need for evidence-based content, user-friendly design, language accessibility, offline functionality, and data security. Participants also stressed the importance of clear instructions, regular updates, and robust tracking features. Despite some challenges, the app was generally well-received, with users appreciating its educational potential and tracking capabilities. Conclusions The BUMPER project’s pilot study demonstrated the cancer prevention App being developed as a potential tool for cancer education and awareness. Despite navigational and language challenges, the app was favorably received by a diverse user base, underscoring the need for ongoing improvements in user guidance, comprehension, and functionality to enhance accessibility. Key messages • BUMPER project’s cancer prevention app shows promise in pilot study, enhancing cancer education and awareness. • Despite challenges, the app was well-received, highlighting the need for ongoing improvements to enhance accessibility.

Prediction of mental health risk in adolescents via a smartphone app: a feasibility pilot study

Abstract Background The prevalence of mental health problems in adolescents is a global public health concern. Machine learning (ML) can analyse multidimensional data collected by phone sensors (passive tracking) and symptom self-reporting (active tracking) to model and predict mental health states. However, research in adolescents is lacking. This study investigated the feasibility of using ML to predict mental health in a non-clinical population of adolescents from active and passive data collected through the Mindcraft mobile app. Methods We recruited 103 secondary students (aged 14-18) who first completed the Strengths and Difficulties Questionnaire (SDQ) and then used the Mindcraft app for two weeks. The app integrates sensor data (location, steps, noise, light, battery, app usage) and self-reports. We extracted 85 sensor-based features and 19 from questionnaires to develop a gradient-boosted ensemble ML model. This model identifies students with abnormal SDQ scores and was evaluated using leave-one-out cross-validation. Results All students completed the active questionnaires; 67 also provided passive sensor data. 31 had abnormal SDQ scores. Using passive data, the ML model reached a balanced accuracy of 0.64 and an AUC score of 0.57. Incorporating both data types improved accuracy to 0.67 and AUC to 0.70. Feature importance scores showed step count and questionnaire on racing thoughts and hopefulness as most significant. Conclusions Our findings affirm the potential of integrating passive and active data collection to monitor mental health in real-world settings. Our ML model demonstrated moderate accuracy in predicting adolescents’ mental health risk measured with a behavioural screening questionnaire. This study will guide the development of a ML-driven, personalised mobile intervention for early symptom detection and mental health self-management, which might constitute an innovative and scalable tool for mental health prevention and intervention in adolescents. Key messages • This study shows the feasibility of using active and passive data to predict mental health risk in adolescents. • This study informs the development of a personalised machine learning-driven mobile intervention.

Developing explicit and implicit L2 knowledge with Duolingo’s input-based features: Case studies of L2 Spanish learning

In this single-case study with a quasi-experimental design, we set out to examine the role of two input-based features of the language learning app Duolingo on learners’ development of implicit and explicit second language (L2) knowledge. We investigated the effect of Duolingo’s Stories feature and Podcast feature on two Spanish-L2 learners’ performance on a battery of implicit and explicit L2 knowledge tests. Once a week, over a four-week period using these input-based features, both participants repeatedly performed oral narrative tasks, timed and untimed grammaticality judgment tasks, and metalinguistic knowledge tests. The participant assigned to the Podcast condition showed meager gains in productive implicit knowledge (measured by oral narrative tasks) but decreased in receptive explicit knowledge (measured by untimed grammaticality judgment tasks). The participant assigned to the Stories condition showed a large increase in receptive implicit knowledge of Spanish (measured by timed grammaticality judgment tasks). Neither participant showed meaningful gains in the measure of productive explicit knowledge (measured by metalinguistic knowledge tasks). Although there was a slight increase in receptive explicit knowledge for the participant using Stories, the data from both participants discount the idea that app-based mobile-assisted language learning (MALL) prioritizes receptive explicit L2 knowledge, at least when considering these novel input-based features of Duolingo. These findings add nuance to previous research showing that the primary outcome of MALL app use is receptive explicit L2 knowledge.