A Novel Approach to Improve the Planning of Adaptive and Interactive Sessions for the treatment of Major Depression

[EN] Human Computer Interaction (HCI) is a research field which aims to improve the relationship between users and interactive computer systems. A main objective of this research area is to make the user experience more pleasant and efficient, minimizing the barrier between the users' cognition of what they want to accomplish and the computer's understanding of the user's tasks, by means of userfriendly, useful and usable designs. A bad HCI design is one of the main reasons behind user rejection of computer-based applications, which in turn produces loss of productivity and economy in industrial environments. In the eHealth domain, user rejection of computer-based systems is a major barrier to exploiting the maximum benefit from those applications developed to support the treatment of diseases, and in the worst cases a poor design in these systems may cause deterioration in the clinical condition of the patient. Thus, a high level of personalisation of the system according to users' needs is extremely important, making it easy to use and contributing to the system's efficacy, which in turn facilitates the empowerment of the target users. Ideally, the content offered through the interactive sessions in these applications should be continuously assessed and adapted to the changing condition of the patient. A good HCI design and development can improve the acceptance of these applications and contribute to promoting better adherence levels to the treatment, preventing the patient from further relapses. In this work, we present a mechanism to provide personalised and adaptive daily interactive sessions focused on the treatment of patients with Major Depression. These sessions are able to automatically adapt the content and length of the sessions to obtain personalised and varied sessions in order to encourage the continuous and long-term use of the system. The tailored adaptation of session content is supported by decision-making processes based on: (i) clinical requirements; (ii) the patient's historical data; and (iii) current responses from the patient. We have evaluated our system through two different methodologies: the first one performing a set of simulations producing different sessions from changing input conditions, in order to assess different levels of adaptability and variability of the session content offered by the system. The second evaluation process involved a set of patients who used the system for 14 to 28 days and answered a questionnaire to provide feedback about the perceived level of adaptability and variability produced by the system. The obtained results in both evaluations indicated good levels of adaptability and variability in the content of the sessions according to the input conditions.E. Fuster Garcia acknowledges the financial support from the "Torres Quevedo" program (Spanish Ministry of Economy and Competitiveness) co-funded by the European Social Fund (PTQ-12-05693), and the financial support from the Universitat Politecnica de Valencia under the Grant "Ayudas Para la Contratacion de Doctores para el Acceso al Sistema Espanol de Ciencia, Tecnologia e Innovacion" (PAID-10-14).Bresó Guardado, A.; Martínez Miranda, JC.; Fuster García, E.; García Gómez, JM. (2016). A Novel Approach to Improve the Planning of Adaptive and Interactive Sessions for the treatment of Major Depression. International Journal of Human-Computer Studies. 87:80-91. https://doi.org/10.1016/j.ijhcs.2015.11.003S80918

Gamified cognitive control training for remitted depressed individuals : user requirements analysis

Background: The high incidence and relapse rates of major depressive disorder demand novel treatment options. Standard treatments (psychotherapy, medication) usually do not target cognitive control impairments, although these seem to play a crucial role in achieving stable remission. The urgent need for treatment combined with poor availability of adequate psychological interventions has instigated a shift toward internet interventions. Numerous computerized programs have been developed that can be presented online and offline. However, their uptake and adherence are oftentimes low. Objective: The aim of this study was to perform a user requirements analysis for an internet-based training targeting cognitive control. This training focuses on ameliorating cognitive control impairments, as these are still present during remission and can be a risk factor for relapse. To facilitate uptake of and adherence to this intervention, a qualitative user requirements analysis was conducted to map mandatory and desirable requirements. Methods: We conducted a user requirements analysis through a focus group with 5 remitted depressed individuals and individual interviews with 6 mental health care professionals. All qualitative data were transcribed and examined using a thematic analytic approach. Results: Results showed mandatory requirements for the remitted sample in terms of training configuration, technological and personal factors, and desirable requirements regarding knowledge and enjoyment. Furthermore, knowledge and therapeutic benefits were key requirements for therapists. Conclusions: The identified requirements provide useful information to be integrated in interventions targeting cognitive control in depression

A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents

[EN] Interaction is defined as the realization of a reciprocal action between two or more people or things. Particularly in computer science, the term interaction refers to the discipline that studies the exchange of information between people and computers, and is generally known by the term Human-Computer Interaction (HCI). Good design decisions and an adequate development of the software is required for efficient HCI to facilitate the acceptability of computer-based applications by the users. In clinical settings it is essential to eliminate any barrier and facilitate the interaction between patients and the system. A smooth communication between the user and the computer-based application is fundamental to maximise the advantages and functionalities offered by the system. The design of these applications must consider the personal and current needs of the user by applying a User-Centered Design methodology. The main purpose of this research work is to contribute in the improvement of HCI-based applications addressed to the clinical context, particularly to enhance computer-based interactive sessions to support people suffering from a mental disorder such as Major Depression (MD). Thanks to the advances in Artificial Intelligence techniques, it is now possible to partially automate complex tasks such as the continuous provision of Cognitive-Behavioural Therapies (CBTs) to patients. These CBTs require good levels of adaptability and variability during the interaction with the patient that facilitates the acceptability in the user, an optimal usability and good level of engagement for a successful mid/long term use of the application and treatment adherence. The modelling of complex deliberative and affective processes in artificial systems can be applied to support the prevention and treatment of mental health related issues, enhancing the continuous and remote assistance of patients, saving some economical and clinical resources and reducing the waiting lists in the health services. In this regard, the efforts of this Thesis have been concentrated on the research of two main lines: (1) the generation and planning of adequate contents in an interactive system to support the prevention and treatment of MD based on characteristics of the user; and (2) the modelling of relevant affective processes able to communicate the contents in an emotional effective way taking into account the importance of the affective conditions associated with the MD in the users. Rule Based Systems and the appraisal theory of emotions have been the roots used to develop the main two modules of the computational Framework presented: the Contents Management and the Emotional Modules. Finally, the obtained Framework was integrated into two interactive systems to evaluate the achievement of the research objectives. The first system has been developed in the context of the Help4Mood European research project and its main aim was to support the remote treatment of patients with MD. The second scenario was a system developed to prevent MD and suicidal thoughts in the University community, which was developed in the context of the local PrevenDep research project. These evaluations have indicated that the proposed Framework has reached good levels of usability and acceptability in the target users thanks to the personalizations and adaptation capabilities of the contents and in the way how these contents are communicated to the user. The research work and the obtained results in this Thesis has contributed to the state of the art in HCI-based systems used as support in therapeutic interventions for the prevention and treatment of MD. This was obtained by the combination of a personalized content management to the patient, and the management of the affective processes associated to these pathologies. The developed work also identifies some research lines that need to be addressed in future works to get better HCI systems used for therapeutic purposes.[ES] Interactuar se define como la realización de una acción recíproca entre dos o más personas o cosas. Particularmente en informática, el término interacción se refiere a la disciplina que estudia el intercambio de información entre las personas y computadoras, y suele conocerse por el término anglosajón Human-Computer Interaction (HCI). Un buen diseño y un adecuado desarrollo del software es necesario para lograr una HCI eficiente que facilite la aceptabilidad del sistema por el usuario. En entornos clínicos es fundamental eliminar cualquier tipo de barrera y facilitar la interacción entre los pacientes y el computador. Es de vital importancia que haya una buena comunicación entre usuario y computador, por este motivo el sistema debe de estar diseñado pensando en las necesidades actuales, cambiantes y personales del usuario, basándose en la metodología de diseño centrado en el usuario. El propósito principal de esta investigación es la identificación de mejoras en HCI aplicada en entornos clínicos, en concreto para dar soporte a personas con trastornos mentales como la Depresión Mayor (DM) y que precisan de terapias psicológicas adecuadas y continuas. Gracias a técnicas de Inteligencia Artificial, es posible automatizar eficientemente ciertas acciones asociadas a los procesos de las terapias cognitivo-conductuales (CBTs, del inglés Cognitive-Behavioural Therapies). Los sistemas de ayuda a la CBT, requieren de una adaptabilidad y variabilidad en la interacción para favorecer la usabilidad del sistema y asegurar la continuidad de la motivación del paciente. Una buena gestión de esta automatización influiría en la aceptabilidad de los pacientes y podría mejorar su adherencia a los tratamientos y por consiguiente mejorar su estado de salud. Adicionalmente, la unión de procesos deliberativos dinámicos pueden liberar recursos clínicos, mejorando el control de los pacientes, y reduciendo los tiempos de espera y los costes económicos. En este sentido, los esfuerzos de esta Tesis se han centrado en la investigación de dos líneas diferentes: (1) la selección y planificación adecuada de los contenidos presentados durante la interacción a través de una planificación dinámica y personalizada, y (2) la adecuación de la comunicación de los contenidos hacia el paciente tomando en cuenta la importancia de los procesos afectivos asociados a estas patologías. Los Sistemas Basados en Reglas (SBR) han sido la herramienta utilizada para dar soporte a los dos módulos principales que componen el Framework presentado en esta Tesis: el módulo de gestión de los contenidos y el módulo emocional. Concluida la fase de diseño, desarrollo y testeo, el Framework fue adaptado e integrado en sistemas reales, para validar la viabilidad y la adecuación del marco de trabajo de esta Tesis. En primer lugar, el sistema se aplicó durante tres años en el tratamiento de la DM en varios centros clínicos europeos en el contexto del Proyecto Europeo de investigación Help4Mood. Finalmente, el sistema fue evaluado en la tarea de prevención de la DM y del suicidio en el Proyecto Local de investigación PrevenDep, de un año de duración. El feedback de estas evaluaciones demostraron que el HCI del Framework tiene unos niveles altos de usabilidad y aceptación, gracias a la personalización, variabilidad y adaptación de los contenidos y de la comunicación de los mismos. Los experimentos computacionales llevados a cabo en esta Tesis han permitido avanzar el estado del arte de sistemas computacionales emocionales aplicados en entornos terapéuticos para la prevención y tratamiento de la DM. Principalmente, gracias a la combinación de una gestión personalizada de los contenidos hacia el paciente tomando en cuenta la importancia de los procesos afectivos asociados a estas patologías. Este trabajo abre nuevas líneas de investigación, como la aplicación de este sistema en otras patologías de salud mental en las qu[CA] Interactuar es defineix com la realització d'una acció recíproca entre dos o més persones o coses. Particularment en informàtica, el terme interacció es refereix a la disciplina que estudia l'intercanvi d'informació entre les persones i computadores, i es sol conèixer pel terme anglosaxó Human-Computer Interaction (HCI). Un bon disseny i un adequat desenvolupament del software és necessari per aconseguir una HCI eficient que faciliti l'acceptabilitat del sistema per l'usuari. En entorns clínics és fonamental eliminar qualsevol tipus de barrera i facilitar la interacció entre els pacients i el computador. És de vital importància que hi hagi una bona comunicació entre l'usuari (o pacient) i el computador, per aquest motiu el sistema ha d'estar dissenyat pensant en les necessitats actuals, cambiants i personals de l'usuari, basant-se en la metodologia de disseny centrat en l'usuari. El propòsit principal d'aquesta investigació és la identificació de millores en HCI aplicada en entorns clínics, en concret per donar suport a persones amb trastorns mentals com la Depressió Major (DM) i que precisen de teràpies psicològiques adequades i contínues. Gràcies a tècniques d'Intel·ligència Artificial, és possible automatitzar eficientment certes accions asociades al processos de les teràpies cognitiu-conductuals. Els sistemes computacionals de ajuda a la CBT, requereixen d'una adaptabilitat i variabilitat en la interacció per afavorir la usabilitat del sistema i assegurar la continuïtat de la motiviació del pacient. Una bona gestió d'aquesta automatització influiria en l'acceptabilitat dels pacients i podria millorar la seva adherència als tractaments i per tant millorar el seu estat de salut. Addicionalment, la unió de processos deliberatius dinàmics poden alliberar recursos clínics, millorant el control dels pacients, i reduint els temps d'espera i els costos econòmics. En aquest sentit, els esforços d'aquesta Tesi s'han centrat en la investigació de dues línies diferents: (1) la selecció i planificació adequada dels continguts presentats durant la interacció a través d'una planificació dinàmica i personalitzada, i (2) l'adequació de la comunicació dels continguts cap al pacient tenint en compte la importància dels processos afectius associats a aquestes patologies. Els Sistemes Basats en Regles (SBR) han estat la eina utilitzada per donar suport als dos mòduls principals que componen el Framework presentat en aquesta Tesi: el mòdul de gestió dels continguts oferits a l'usuari; i el mòdul emocional. Conclosa la fase de disseny, desenvolupament i testeig, el Framework va ser adaptat als dominis corresponents i integrat en sistemes madurs per ser avaluat en dos escenaris reals, per validar la viabilitat i l'adequació del Framework d'aquesta tesi. Primerament, el sistema es va aplicar durant tres anys en el tractament de la DM major en diversos centres clínics europeus en el context del Projecte Europeu d'investigació Help4Mood. Finalment, el sistema va ser avaluat en la tasca de prevenció de la DM i del suïcidi al Projecte Local d'investigació PrevenDep, d'un any de durada. El feedback de les avaluacions han demostrat que el HCI del Framework obté uns nivells alts d'usabilitat i acceptació, gràcies a la personalització, variabilitat i adaptació dels continguts i de la comunicació. Els experiments computacionals duts a terme en aquesta Tesi han permès avançar l'estat de l'art de sistemes computacionals emocionals aplicats en entorns terapèutics per a la prevenció i tractament de la DM. Principalment, gracies a la combinació d'una gestió personalitzada dels continguts cap al pacient tenint en compte la importància dels processos afectius associats a aquestes patologies. Aquest treball obre noves línies d'investigació, com l'aplicació d'aquest sistema en altres patologies de salut mental en què sigui recomanable l'aplicació de sessions terapèutiques.Bresó Guardado, A. (2016). A Computational Framework for Planning Therapeutical Sessions aimed to Support the Prevention and Treatment of Mental Health Disorders using Emotional Virtual Agents [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64082TESI

Usability and acceptability assessment of an empathic virtual agent to prevent major depression

In Human-Computer Interaction, the adaptation of the content and the way of how this content is communicated to the users in interactive sessions is a critical issue to promote the acceptability and usability of any computational system. We present a user-adapted interactive platform to identify and provide an early intervention for symptoms of depression and suicide. In particular, we describe the work performed to assess users' system acceptability and usability. An empathic Virtual Agent is the main interface with the user, and it has been designed to generate the appropriate dialogues and emotions during the interactions according to the detected user's specific needs. This personalization is based on a dynamic user model nurtured with clinical, demographical and behavioural information. The evaluation was performed with 60 participants from the university community. The obtained results were promising, allowing the execution of a further clinical trial. The system's usability score was 75.7%, and the score of the user-adapted content and the emotional responses of the Virtual Agent was 70.9%.The work presented in this manuscript has been partially funded by the Conselleria de Sanidad of Generalitat Valenciana, in the research project entitled 'Sistema computacional de ayuda a la prevencion de episodios de depresion y suicidio - PREVENDEP'. We thank the company Faceshift (www.faceshift.com) for providing their software to perform facial motion capture in order to develop the talking head that represent our empathic virtual agent.Bresó Guardado, A.; Martinez-Miranda, J.; Botella Arbona, C.; Baños Rivera, RM.; García Gómez, JM. (2016). Usability and acceptability assessment of an empathic virtual agent to prevent major depression. Expert Systems. 33(4):297-312. doi:10.1111/exsy.12151S29731233

Adaptive School-based Implementation of CBT (ASIC): clustered-SMART for building an optimized adaptive implementation intervention to improve uptake of mental health interventions in schools

Abstract Background Depressive and anxiety disorders affect 20–30% of school-age youth, most of whom do not receive adequate services, contributing to poor developmental and academic outcomes. Evidence-based practices (EBPs) such as cognitive behavioral therapy (CBT) can improve outcomes, but numerous barriers limit access among affected youth. Many youth try to access mental health services in schools, but school professionals (SPs: counselors, psychologists, social workers) are rarely trained adequately in CBT methods. Further, SPs face organizational barriers to providing CBT, such as lack of administrative support. Three promising implementation strategies to address barriers to school-based CBT delivery include (1) Replicating Effective Programs (REP), which deploys customized CBT packaging, didactic training in CBT, and technical assistance; (2) coaching, which extends training via live supervision to improve SP competence in CBT delivery; and (3) facilitation, which employs an organizational expert who mentors SPs in strategic thinking to promote self-efficacy in garnering administrative support. REP is a relatively low-intensity/low-cost strategy, whereas coaching and facilitation require additional resources. However, not all schools will require all three strategies. The primary aim of this study is to compare the effectiveness of a school-level adaptive implementation intervention involving REP, coaching, and facilitation versus REP alone on the frequency of CBT delivered to students by SPs and student mental health outcomes. Secondary and exploratory aims examine cost-effectiveness, moderators, and mechanisms of implementation strategies. Methods Using a clustered, sequential multiple-assignment, randomized trial (SMART) design, ≥ 200 SPs from 100 schools across Michigan will be randomized initially to receive REP vs. REP+coaching. After 8 weeks, schools that do not meet a pre-specified implementation benchmark are re-randomized to continue with the initial strategy or to augment with facilitation. Discussion EBPs need to be implemented successfully and efficiently in settings where individuals are most likely to seek care in order to gain large-scale impact on public health. Adaptive implementation interventions hold the promise of providing cost-effective implementation support. This is the first study to test an adaptive implementation of CBT for school-age youth, at a statewide level, delivered by school staff, taking an EBP to large populations with limited mental health care access. Trial registration NCT03541317 —Registered on 29 May 2018 on ClinicalTrials.gov PRShttps://deepblue.lib.umich.edu/bitstream/2027.42/145606/1/13012_2018_Article_808.pd