CoachAI: A Conversational Agent Assisted Health Coaching Platform

Poor lifestyle represents a health risk factor and is the leading cause of morbidity and chronic conditions. The impact of poor lifestyle can be significantly altered by individual behavior change. Although the current shift in healthcare towards a long lasting modifiable behavior, however, with increasing caregiver workload and individuals' continuous needs of care, there is a need to ease caregiver's work while ensuring continuous interaction with users. This paper describes the design and validation of CoachAI, a conversational agent assisted health coaching system to support health intervention delivery to individuals and groups. CoachAI instantiates a text based healthcare chatbot system that bridges the remote human coach and the users. This research provides three main contributions to the preventive healthcare and healthy lifestyle promotion: (1) it presents the conversational agent to aid the caregiver; (2) it aims to decrease caregiver's workload and enhance care given to users, by handling (automating) repetitive caregiver tasks; and (3) it presents a domain independent mobile health conversational agent for health intervention delivery. We will discuss our approach and analyze the results of a one month validation study on physical activity, healthy diet and stress management

A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly

This paper presents a dialogue act taxonomy designed for the development of a conversational agent for elderly. The main goal of this conversational agent is to improve life quality of the user by means of coaching sessions in different topics. In contrast to other approaches such as task-oriented dialogue systems and chit-chat implementations, the agent should display a pro-active attitude, driving the conversation to reach a number of diverse coaching goals. Therefore, the main characteristic of the introduced dialogue act taxonomy is its capacity for supporting a communication based on the GROW model for coaching. In addition, the taxonomy has a hierarchical structure between the tags and it is multimodal. We use the taxonomy to annotate a Spanish dialogue corpus collected from a group of elder people. We also present a preliminary examination of the annotated corpus and discuss on the multiple possibilities it presents for further research.The research presented in this paper is conducted as part of the project EMPATHIC that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769872. The authors would also like to thank the support by the Basque Government through the project IT-1244-19

Analysis of the interaction between elderly people and a simulated virtual coach

The EMPATHIC project develops and validates new interaction paradigms for personalized virtual coaches (VC) to promote healthy and independent aging. To this end, the work presented in this paper is aimed to analyze the interaction between the EMPATHIC-VC and the users. One of the goals of the project is to ensure an end-user driven design, involving senior users from the beginning and during each phase of the project. Thus, the paper focuses on some sessions where the seniors carried out interactions with a Wizard of Oz driven, simulated system. A coaching strategy based on the GROW model was used throughout these sessions so as to guide interactions and engage the elderly with the goals of the project. In this interaction framework, both the human and the system behavior were analyzed. The way the wizard implements the GROW coaching strategy is a key aspect of the system behavior during the interaction. The language used by the virtual agent as well as his or her physical aspect are also important cues that were analyzed. Regarding the user behavior, the vocal communication provides information about the speaker's emotional status, that is closely related to human behavior and which can be extracted from the speech and language analysis. In the same way, the analysis of the facial expression, gazes and gestures can provide information on the non verbal human communication even when the user is not talking. In addition, in order to engage senior users, their preferences and likes had to be considered. To this end, the effect of the VC on the users was gathered by means of direct questionnaires. These analyses have shown a positive and calm behavior of users when interacting with the simulated virtual coach as well as some difficulties of the system to develop the proposed coaching strategy.The research presented in this paper is conducted as part of the project EMPATHIC that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no 769872

Foodbot: A goal-oriented just-in-time healthy eating interventions chatbot

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

MOTIBOT: IL COACH VIRTUALE PER INTERVENTI DI COPING SANO PER ADULTI CON DIABETE MELLITO

Il diabete mellito (DM) è una malattia metabolica autogestita, in cui se l'individuo non è motivato o non è in grado di gestire regolarmente il proprio DM, i risultati medici e psicosociali saranno scarsi. Il DM è più di una condizione di salute fisica: ha impatti comportamentali, fisiologici, psicologici e sociali, e richiede alti livelli di motivazione per seguire le raccomandazioni cliniche e adottare comportamenti sani. A questo scopo, le linee guida dell'American Association of Diabetes Educators (AADE) hanno introdotto il costrutto di coping sano per identificare le strategie di coping per ridurre i sintomi di depressione, ansia, stress e disagio emotivo legato al diabete, migliorando anche il benessere degli adulti con DM. In questo contesto, i Virtual Coaches (VCs) sono diventati un importante risorsa nel supporto e nella gestione delle barriere comuni nel contesto dell'aderenza ai comportamenti sani tra gli adulti con DM. Tuttavia, pochi sono i VC specificamente sviluppati a fornire supporto psicosociale agli adulti con DM. L'obiettivo principale della presente tesi è stato, infatti, lo sviluppo di un VC per fornire supporto psicosociale agli adulti con DM di tipo 1 (T1DM) o DM di tipo 2 (T2DM). Più specificamente, questo VC mirava a motivare gli adulti con DM a ridurre sintomi di depressione, ansia, stress, il disagio emotivo legato al diabete, e a migliorare il loro benessere, incoraggiandoli ad acquisire e coltivare strategie di coping psicosociale sano. Queste abilità di coping facevano riferimento alle linee guida dell'AADE e quindi alla pratica della meditazione; in questo studio è stata, infatti, applicata la Mindfulness-Based Cognitive Therapy. La presente tesi è articolata secondo tre studi. Lo studio 1 mirava a fornire prove meta-analitiche sull'efficacia degli interventi eHealth nel sostenere il benessere psicosociale e medico degli adulti con T1DM o T2DM. Lo studio 2 mirava a testare il prototipo del VC simulato, cioè Wizard of Oz (WOZ), attraverso la piattaforma di messaggistica WhatsApp per 6 settimane, con due sessioni a settimana. In particolare, questo studio ha indagato l'accettabilità preliminare e la User Experience (UX) del protocollo di intervento, che sarà incorporato nel futuro VC. Infatti, il metodo di progettazione è stato duplice. Da un lato, è stato applicato il metodo WOZ, in cui gli studenti di psicologia credevano di interagire con un VC; invece, stavano comunicando con un essere umano. Dall'altro lato, è stato utilizzato il modello Obesity-Related Behavioural Intervention Trials (ORBIT), in particolare le sue prime fasi, poiché favorisce un approccio iterativo. Lo studio 3, seguendo le fasi successive del modello ORBIT, mirava a valutare l'efficacia preliminare del VC, chiamato Motibot - abbreviazione di Motivational bot - sviluppato attraverso una combinazione di Natural Language Processing (NLU) e regole pre-strutturate. Un totale di 13 adulti italiani con DM (Mage = 30.08, SD = 10.61) hanno interagito con Motibot attraverso l'applicazione di messaggistica Telegram per 12 sessioni, in cui il paziente poteva pianificare l'appuntamento secondo le sue esigenze: ha interagito con Motibot una o due sessioni a settimana. Motibot è stato percepito come motivante, incoraggiante e capace di innescare un'auto-riflessione sulle proprie emozioni: gli utenti e i pazienti hanno riferito di aver avuto un'esperienza molto positiva con Motibot. Motibot può essere uno strumento utile per fornire supporto psicosociale agli adulti con DM; potrebbe essere prescritto dal diabetologo come misura preventiva per il benessere del paziente e/o quando il paziente presenta sintomi psicosociali lievi e moderati. L'approccio di design centrato sull'utente e il concetto di bidirezionalità tra fattori psicosociali e medici sono punti chiave nello sviluppo di un trattamento digitale personalizzato.Diabetes Mellitus (DM) is a self-managed, metabolic disease, in which if the individual is unwilling, unmotivated, or unable to regularly self-manage their DM, the medical and psychosocial outcomes will be poor. Indeed, DM is more than a physical health condition: it has behavioural, physiological, psychological, and social impacts, and demands high levels of motivation in order to follow the clinical recommendations and adopt healthy behaviours. To this end, the American Association of Diabetes Educators (AADE) guidelines introduced the healthy coping construct to identify healthy coping strategies for reducing symptoms of depression, anxiety, stress, and diabetes-related emotional distress while also improving the well-being of adults with DM. Virtual Coaches (VCs) have recently become more prevalent in the support and management of common barriers in the context of adherence to healthy behaviours among adults with DM, in particular those regarding medical and physical behaviours. However, few VCs were found to be specifically aimed at providing psychosocial support to adults with DM. The main aim of the present thesis was, indeed, the development and implementation of a VC for the provision of psychosocial support to adults with Type 1 (T1DM) or Type 2 DM (T2DM). More specifically, this VC aimed at motivating adults with DM to reduce depression, anxiety, perceived stress symptoms, diabetes-related emotional distress, and improve their well-being, by encouraging them to acquire and cultivate psychosocial healthy coping strategies. These coping skills referred to the AADE guidelines and thus to practicing meditation; in this study, the Mindfulness-Based Cognitive Therapy has been applied. The present thesis is articulated according to three studies. Study 1 aimed at providing meta-analytical evidence on the efficacy of eHealth interventions in supporting the psychosocial and medical well-being of adults with T1DM or T2DM. Study 2 aimed at testing the prototype of the simulated VC, namely Wizard of Oz (WOZ), via the WhatsApp messaging platform for 6-week, with two sessions per week. In particular, this study investigated the preliminary acceptability and the User Experience (UX) of the intervention protocol, which will be incorporated into the future VC. Indeed, the design method was two-fold. On the one hand, the WOZ method was applied, in which psychology students believed that they were interacting with a VC, instead they were communicating with a human being. On the other hand, the Obesity-Related Behavioural Intervention Trials (ORBIT) model was used, particularly its early phases, since it favours an iterative approach. Study 3, following the next phases of the ORBIT model, aimed at assessing the preliminary efficacy of the VC, called Motibot—the abbreviation for Motivational bot—developed through a combination of Natural Language Processing (NLU) and hand-crafted rules. A total of 13 Italian adults with DM (Mage = 30.08, SD = 10.61) interacted with Motibot through the Telegram messaging application for 12 sessions, in which the patient planned the appointment according to his/her needs: he/she interacted with Motibot one or two sessions per week. Therefore, Motibot was perceived as motivating, encouraging and able to trigger self-reflection on one’s own emotions: users and patients reported having a very positive experience with Motibot. Motibot, thus, can be a useful tool to provide psychosocial support to adults with DM; as such, it might be prescribed by the diabetologist as a preventive measure for the patient’s well-being and/or when the patient presents mild and moderate psychosocial symptoms. The user-centred design approach and the concept of bidirectionality between psychosocial and medical factors are key points in the development of a personalised treatment within the digital intervention