Supporting patients and clinicians during the breast cancer care path with AI: The Arianna solution.

The onset of cancer disease is a traumatic experience for both patients and their families that suddenly change the patient's life and is accompanied by important physical, emotional, and psycho-social problems. The complexity of this scenario has been exacerbated by the COVID-19 pandemic which dramatically affected the continuity of the provision of optimal care to chronic patients. Telemedicine can support the management of oncology care paths by furnishing a suite of effective and efficient tools to monitor the therapies of cancer patients. In particular, this is a suitable setting for therapies that are administered at home. In this paper, we present an AI-based system, called Arianna, designed and implemented to support and monitor patients treated by the professionals belonging to the Breast Cancer Unit Network (BCU-Net) along the entire clinical path of breast cancer treatment. We describe in this work the three modules composing the Arianna system (the tools for patients and clinicians, and the symbolic AI-based module). The system has been validated in a qualitative way and we demonstrated how the Arianna solution reached a high level of acceptability by all types of end-users by making it suitable for a concrete integration into the daily practice of the BCU-Net.

Educational Intervention of Healthy Life Promotion for Children with a Migrant Background or at Socioeconomic Disadvantage in the North of Italy: Efficacy of Telematic Tools in Improving Nutritional and Physical Activity Knowledge.

The aim of the "Smuovi La Salute" ("Shake Your Health") project was to implement an integrated and comprehensive model to prevent and treat overweight and obesity in low socioeconomic status (SES) and minority groups living in three different districts in the north of Italy. An app and a cookbook promoting transcultural nutrition and a healthy lifestyle were developed, and no-cost physical activities were organized. Healthy lifestyle teaching was implemented in 30 primary school classrooms. Learning was assessed through pre- and post-intervention questionnaires. At the Obesity Pediatric Clinic, overweight and obese children of migrant background or low SES were trained on transcultural nutrition and invited to participate in the project. Primary school students increased their knowledge about healthy nutrition and the importance of physical activity (p-value < 0.001). At the Obesity Pediatric Clinic, after 6 months, pre-post-intervention variation in their consumption of vegetables and fruit was +14% (p < 0.0001) and no variation in physical activity habits occurred (p = 0.34). In this group, the BMI z-score was not significantly decreased (-0.17 ± 0.63, p= 0.15). This study demonstrates the feasibility and efficacy of telematic tools and targeted community approaches in improving students' knowledge with regard to healthy lifestyle, particularly in schools in suburbs with a high density of migrants and SES families. Comprehensive and integrated approaches provided to the obese patients remain mostly ineffective.

Engagement and Effectiveness of a Healthy-Coping Intervention via Chatbot for University Students During the COVID-19 Pandemic: Mixed Methods Proof-of-Concept Study.

BACKGROUND: University students are increasingly reporting common mental health problems, such as stress, anxiety, and depression, and they frequently face barriers to seeking psychological support because of stigma, cost, and availability of mental health services. This issue is even more critical in the challenging time of the COVID-19 pandemic. Digital mental health interventions, such as those delivered via chatbots on mobile devices, offer the potential to achieve scalability of healthy-coping interventions by lowering cost and supporting prevention. OBJECTIVE: The goal of this study was to conduct a proof-of-concept evaluation measuring the engagement and effectiveness of Atena, a psychoeducational chatbot supporting healthy coping with stress and anxiety, among a population of university students. METHODS: In a proof-of-concept study, 71 university students were recruited during the COVID-19 pandemic; 68% (48/71) were female, they were all in their first year of university, and their mean age was 20.6 years (SD 2.4). Enrolled students were asked to use the Atena psychoeducational chatbot for 4 weeks (eight sessions; two per week), which provided healthy-coping strategies based on cognitive behavioral therapy, positive psychology, and mindfulness techniques. The intervention program consisted of conversations combined with audiovisual clips delivered via the Atena chatbot. Participants were asked to complete web-based versions of the 7-item Generalized Anxiety Disorder scale (GAD-7), the 10-item Perceived Stress Scale (PSS-10), and the Five-Facet Mindfulness Questionnaire (FFMQ) at baseline and postintervention to assess effectiveness. They were also asked to complete the User Engagement Scale-Short Form at week 2 to assess engagement with the chatbot and to provide qualitative comments on their overall experience with Atena postintervention. RESULTS: Participants engaged with the Atena chatbot an average of 78 (SD 24.8) times over the study period. A total of 61 out of 71 (86%) participants completed the first 2 weeks of the intervention and provided data on engagement (10/71, 14% attrition). A total of 41 participants out of 71 (58%) completed the full intervention and the postintervention questionnaires (30/71, 42% attrition). Results from the completer analysis showed a significant decrease in anxiety symptoms for participants in more extreme GAD-7 score ranges (t39=0.94; P=.009) and a decrease in stress symptoms as measured by the PSS-10 (t39=2.00; P=.05) for all participants postintervention. Participants also improved significantly in the describing and nonjudging facets, based on their FFMQ subscale scores, and asked for some improvements in the user experience with the chatbot. CONCLUSIONS: This study shows the benefit of deploying a digital healthy-coping intervention via a chatbot to support university students experiencing higher levels of distress. While findings collected during the COVID-19 pandemic show promise, further research is required to confirm conclusions.

Use of eHealth Platforms and Apps to Support Monitoring and Management of Home-Quarantined Patients With COVID-19 in the Province of Trento, Italy: App Development and Implementation.

BACKGROUND: Italy was the first country to largely experience the COVID-19 epidemic among other Western countries during the so-called first wave of the COVID-19 pandemic. Proper management of an increasing number of home-quarantined individuals created a significant challenge for health care authorities and professionals. This was especially true when considering the importance of remote surveillance to detect signs of disease progression and consequently regulate access to hospitals and intensive care units on a priority basis. OBJECTIVE: In this paper, we report on an initiative promoted to cope with the first wave of the COVID-19 epidemic in the Spring/Summer of 2020, in the Autonomous Province of Trento, Italy. A purposefully built app named TreCovid19 was designed to provide dedicated health care staff with a ready-to-use tool for remotely monitoring patients with progressive symptoms of COVID-19, who were home-quarantined during the first wave of the epidemic, and to focus on those patients who, based on their self-reported clinical data, required a quick response from health care professionals. METHODS: TreCovid19 was rapidly developed to facilitate the monitoring of a selected number of home-quarantined patients with COVID-19 during the very first epidemic wave. The app was built on top of an existing eHealth platform, already in use by the local health authority to provide home care, with the following functionalities: (1) to securely collect and link demographic and clinical information related to the patients and (2) to provide a two-way communication between a multidisciplinary health care team and home-quarantined patients. The system supported patients to self-assess their condition and update the multidisciplinary team on their health status. The system was used between March and June 2020 in the province of Trento. RESULTS: A dedicated multidisciplinary group of health care professionals adopted the platform over a period of approximately 3 months (from March-end to June 2020) to monitor a total of 170 patients with confirmed COVID-19 during home quarantine. All patients used the system until the end of the initiative. The TreCovid19 system has provided useful insights of possible viability and impact of a technological-organizational asset to manage a potentially critical workload for the health care staff involved in the periodic monitoring of a relevant number of quarantined patients, notwithstanding its limitations given the rapid implementation of the whole initiative. CONCLUSIONS: The technological and organizational model adopted in response to the COVID-19 pandemic was developed and finalized in a relatively short period during the initial few weeks of the epidemic. The system successfully supported the health care staff involved in the periodic monitoring of an increasing number of home-quarantined patients and provided valuable data in terms of disease surveillance.

Automated vs. Human Health Coaching: Exploring Participant and Practitioner Experiences.

Health coaching can be an effective intervention to support self-management of chronic conditions like diabetes, but there are not enough coaching practitioners to reach the growing population in need of support. Conversational technology, like chatbots, presents an opportunity to extend health coaching support to broader and more diverse populations. However, some have suggested that the human element is essential to health coaching and cannot be replicated with technology. In this research, we examine automated health coaching using a theory-grounded, wizard-of-oz chatbot, in comparison with text-based virtual coaching from human practitioners who start with the same protocol as the chatbot but have the freedom to embellish and adjust as needed. We found that even a scripted chatbot can create a coach-like experience for participants. While human coaches displayed advantages expressing empathy and using probing questions to tailor their support, they also encountered tremendous barriers and frustrations adapting to text-based virtual coaching. The chatbot coach had advantages in being persistent, as well as more consistently giving choices and options to foster client autonomy. We discuss implications for the design of virtual health coaching interventions.

PerKApp: A general purpose persuasion architecture for healthy lifestyles.

Automatically monitoring and supporting healthy lifestyle is a recent research trend, fostered by the availability of low-cost monitoring devices, and it can significantly contribute to the prevention of chronic diseases deriving from incorrect diet and lack of physical activity. In this paper, we present a general purpose architecture for persuasion scenarios and behavioral change. The architecture is designed to be easily portable across languages and domains and has been implemented and evaluated in a specific system for Workplace Health Promotion (WHP) called PerKApp. PerKApp provides a fully fledged platform supporting the remote monitoring of workers lifestyle by providing real-time feedback through persuasive context-based messages when necessary.

Design of a Mobile App for Nutrition Education (TreC-LifeStyle) and Formative Evaluation With Families of Overweight Children.

BACKGROUND: Nutrition and diet apps represent today a popular area of mobile health (mHealth), offering the possibility of delivering behavior change (BC) interventions for healthy eating and weight management in a scalable and cost-effective way. However, if commercial apps for pediatric weight management fail to retain users because of a lack of theoretical background and evidence-based content, mHealth apps that are more evidence-based are found less engaging and popular among consumers. Approaching the apps development process from a multidisciplinary and user-centered design (UCD) perspective is likely to help overcome these limitations, raising the chances for an easier adoption and integration of nutrition education apps within primary care interventions. OBJECTIVE: The aim of this study was to describe the design and development of the TreC-LifeStyle nutrition education app and the results of a formative evaluation with families. METHODS: The design of the nutrition education intervention was based on a multidisciplinary UCD approach, involving a team of BC experts, working with 2 nutritionists and 3 pediatricians from a primary care center. The app content was derived from evidence-based knowledge founded on the Food Pyramid and Mediterranean Diet guidelines used by pediatricians in primary care. A formative evaluation of the TreC-LifeStyle app involved 6 families of overweight children (aged 7-12 years) self-reporting daily food intake of children for 6 weeks and providing feedback on the user experience with the mHealth intervention. Analysis of the app's usage patterns during the intervention and of participants' feedback informed the refinement of the app design and a tuning of the nutrition education strategies to improve user engagement and compliance with the intervention. RESULTS: Design sessions with the contribution of pediatricians and nutritionists helped define the nutrition education app and intervention, providing an effective human and virtual coaching approach to raise parents' awareness about children's eating behavior and lifestyle. The 6 families participating in the pilot study found the app usable and showed high compliance with the intervention over the 6 weeks, but analysis of their interaction and feedback showed the need for improving some of the app features related to the BC techniques "monitoring of the behavior" and "information provision." CONCLUSIONS: The UCD and formative evaluation of TreC-LifeStyle show that nutrition education apps are feasible and acceptable solutions to support health promotion interventions in primary care.

A system for automatic detection of momentary stress in naturalistic settings.

Prolonged exposure to stressful environments can lead to serious health problems. Therefore, measuring stress in daily life situations through non-invasive procedures has become a significant research challenge. In this paper, we describe a system for the automatic detection of momentary stress from behavioral and physiological measures collected through wearable sensors. The system's architecture consists of two key components: a) a mobile acquisition module; b) an analysis and decision module. The mobile acquisition module is a smartphone application coupled with a newly developed sensor platform (Personal Biomonitoring System, PBS). The PBS acquires behavioral (motion activity, posture) and physiological (hearth rate) variables, performs low-level, real-time signal preprocessing, and wirelessly communicates with the smartphone application, which in turn connects to a remote server for further signal processing and storage. The decision module is realized on a knowledge basis, using neural network and fuzzy logic algorithms able to combine as input the physiological and behavioral features extracted by the PBS and to classify the level of stress, after previous knowledge acquired during a training phase. The training is based on labeling of physiological and behavioral data through self-reports of stress collected via the smartphone application. After training, the smartphone application can be configured to poll the stress analysis report at fixed time steps or at the request of the user. Preliminary testing of the system is ongoing.