@article{Matey2023c,
title = {Dataset of inertial measurements of smartphones and smartwatches for human activity recognition},
author = {Miguel Matey-Sanz and Sven Casteleyn and Carlos Granell-Canut},
doi = {https://doi.org/10.1016/j.dib.2023.109809},
issn = {2352-3409},
year = {2023},
date = {2023-12-15},
journal = {Data in Brief},
volume = {51},
pages = {109809},
abstract = {This article describes a dataset for human activity recognition with inertial measurements, i.e., accelerometer and gyroscope, from a smartphone and a smartwatch placed in the left pocket and on the left wrist, respectively. Twenty-three heterogeneous subjects (μ = 44.3, σ = 14.3, 56% male) participated in the data collection, which consisted of performing five activities (seated, standing up, walking, turning, and sitting down) arranged in a specific sequence (corresponding with the TUG test). Subjects performed the sequence of activities multiple times while the devices collected inertial data at 100 Hz and were video-recorded by a researcher for data labelling purposes. The goal of this dataset is to provide smartphone- and smartwatch-based inertial data for human activity recognition collected from a heterogeneous (i.e., age-diverse, gender-balanced) set of subjects. Along with the dataset, the repository includes demographic information (age, gender), information about each sequence of activities (smartphone's orientation in the pocket, direction of turns), and a Python package with utility functions (data loading, visualization, etc). The dataset can be reused for different purposes in the field of human activity recognition, from cross-subject evaluation to comparison of recognition performance using data from smartphones and smartwatches.},
keywords = {activity recognition, dataset, machine learning, smartphone app, smartwatch, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{GomezCambronero2023a,
title = {A smartphone-based serious game for depressive symptoms: Protocol for a pilot randomized controlled trial},
author = {Águeda Gómez-Cambronero and Sven Casteleyn and Juana Bretón-López and Azucena García-Palacios and Adriana Mira},
doi = {https://doi.org/10.1016/j.invent.2023.100624},
issn = {2214-7829},
year = {2023},
date = {2023-04-28},
journal = {Internet Interventions},
volume = {32},
pages = {100624},
abstract = {Background
Depression is the most prevalent mental disorder, with detrimental effects on the patient's well-being, high disability, and a huge associated societal and economic cost. There are evidence-based treatments, but it is difficult to reach all people in need. Internet-based interventions, and more recently smartphone-based interventions, were explored to overcome barriers to access. Evidence shows them to be effective alternatives to traditional treatments. This paper presents the protocol of a pilot study whose primary aim is to investigate the efficacy of a smartphone-based serious game intervention for patients with mild to moderate depressive symptoms.

Methods
This randomized controlled pilot trial protocol foresees two arms design: 1/ smartphone- based serious game intervention (based on Cognitive Behavior Therapy with particular emphasis on Behavioral Activation and Physical Activity), 2/ waiting list control group. The study is expected to recruit 40 participants (18+), which will be randomly assigned to one of the experimental conditions. The duration of the intervention is two months. The primary outcome measure will be depressive symptomatology. Secondary outcomes will include other variables such as physical activity, resilience, anxiety, depression impairment, and positive and negative affect. Treatment expectation, satisfaction, usability, and game playability will also be measured. The data will be analyzed based on the intention-to-treat and per protocol analyses.

Discussion
The study aims to establish initial evidence for the efficacy of a smartphone-based serious game intervention, to serve as input for a larger-scale randomized control trial. The intervention exploits advanced smartphone capabilities, such as the use of a serious game as delivery mode, with the potential benefit of engagement and treatment adherence, and motion sensors to monitor and stimulate physical activity. As a secondary objective, the study aims to gather initial evidence on the user's expectations, satisfaction, usability and playability of the serious game as a treatment.},
keywords = {depression, serious games, smartphone app, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Gonzalez-Perez2023a,
title = {AwarNS: A framework for developing context-aware reactive mobile applications for health and mental health},
author = {Alberto González-Pérez and Miguel Matey-Sanz and Carlos Granell-Canut and Laura Díaz-Sanahuja and Juana Bretón-López and Sven Casteleyn},
doi = {10.1016/j.jbi.2023.104359},
issn = {1532-0464},
year = {2023},
date = {2023-04-20},
journal = {Journal of Biomedical Informatics},
volume = {141},
pages = {104359},
abstract = {In recent years, interest and investment in health and mental health smartphone apps have grown significantly. However, this growth has not been followed by an increase in quality and the incorporation of more advanced features in such applications. This can be explained by an expanding fragmentation of existing mobile platforms along with more restrictive privacy and battery consumption policies, with a consequent higher complexity of developing such smartphone applications. To help overcome these barriers, there is a need for robust, well-designed software development frameworks which are designed to be reliable, power-efficient and ethical with respect to data collection practices, and which support the sense-analyse-act paradigm typically employed in reactive mHealth applications. In this article, we present the AwarNS Framework, a context-aware modular software development framework for Android smartphones, which facilitates transparent, reliable, passive and active data sampling running in the background (sense), on-device and server-side data analysis (analyse), and context-aware just-in-time offline and online intervention capabilities (act). It is based on the principles of versatility, reliability, privacy, reusability, and testability. It offers built-in modules for capturing smartphone and associated wearable sensor data (e.g. IMU sensors, geolocation, Wi-Fi and Bluetooth scans, physical activity, battery level, heart rate), analysis modules for data transformation, selection and filtering, performing geofencing analysis and machine learning regression and classification, and act modules for persistence and various notification deliveries. We describe the framework’s design principles and architecture design, explain its capabilities and implementation, and demonstrate its use at the hand of real-life case studies implementing various mobile interventions for different mental disorders used in clinical practice.},
keywords = {context-aware computing, digital phenotyping, location-based services, mHealth, smartphone app, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Acedo2022a,
title = {Emotive facets of place meet urban analytics},
author = {Albert Acedo-Sánchez and Alberto González-Pérez and Carlos Granell-Canut and Sven Casteleyn},
doi = {https://doi.org/10.1111/tgis.12990},
issn = {1361-1682},
year = {2022},
date = {2022-11-30},
journal = {Transactions in GIS},
volume = {26},
number = {7},
pages = {2954–2974},
abstract = {The lack of a well-established and unified place theory across disciplines is decelerating its formalization, evolution, and especially its pragmatic implications and applicability. In this article, we identify research gaps in the emotive facets of place scholarship. We found that it: (1) rarely joins physical, social, and individual variables in the same model; (2) omits the immediately perceived and sensory dimensions; (3) disregards the analysis of how individual–place emotive relationships vary across time; and (4) overlooks the difficulties of reducing multifaceted emotive facets of place into geographic features. Next, we examine these research gaps through the lens of technology-based advancements in urban analytics. Finally, we discuss the need to combine social-oriented research and (spatial) data-driven disciplines to enrich and expand the research area of emotive facets of place and connected disciplines.},
keywords = {data analysis methods, sense of place, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{diazsanchez2022a,
title = {Client’s Experiences Using a Location-Based Technology ICT System during Gambling Treatments’ Crucial Components: A Qualitative Study},
author = {Laura Díaz-Sanahuja and Ignacio Miralles and Carlos Granell-Canut and Adriana Mira and Alberto González-Pérez and Sven Casteleyn and Azucena García-Palacios and Juana Bretón-López

},
doi = {https://doi.org/10.3390/ijerph19073769},
issn = {1660-4601},
year = {2022},
date = {2022-03-22},
journal = {International Journal of Environmental Research and Public Health},
volume = {19},
number = {7},
pages = {3769},
abstract = {Cognitive Behavioral Therapy is the treatment of choice for Gambling Disorder (GD), with stimulus control (SC) and exposure with response prevention (ERP) being its two core components. Despite their efficacy, SC and ERP are not easy to deliver, so it is important to explore new ways to enhance patient compliance regarding SC and ERP. The aim of this study is to describe and assess the opinion of two patients diagnosed with problem gambling and GD that used the Symptoms app, a location-based ICT system, during SC and ERP. A consensual qualitative research study was conducted. We used a semi-structured interview, developed ad-hoc based on the Expectation and Satisfaction Scale and System Usability Scale. A total of 20 categories were identified within six domains: usefulness, improvements, recommendation to other people, safety, usability, and opinion regarding the use of the app after completing the intervention. The patients considered the app to be useful during the SC and ERP components and emphasized that feeling observed and supported at any given time helped them avoid lapses. This work can offer a starting point that opens up new research paths regarding psychological interventions for gambling disorder, such as assessing whether location-based ICT tools enhance commitment rates.},
keywords = {gambling, geolocation, mental health, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Gonzalez-Perez2022a,
title = {Using Mobile Devices as Scientific Measurements Instruments: Reliable Android Task Scheduling},
author = {Alberto González-Pérez and Miguel Matey-Sanz and Carlos Granell-Canut and Sven Casteleyn},
doi = {https://doi.org/10.1016/j.pmcj.2022.101550},
isbn = {1574-1192},
year = {2022},
date = {2022-02-01},
journal = {Pervasive and Mobile Computing},
volume = {81},
number = {101550},
abstract = {In various usage scenarios, smartphones are used as measuring instruments to systematically and unobtrusively collect data measurements (e.g., sensor data, user activity, phone usage data). Unfortunately, in the race towards extending battery life and improving privacy, mobile phone manufacturers are gradually restricting developers in (frequently) scheduling background (sensing) tasks and impede the exact scheduling of their execution time (i.e., Android’s “best effort” approach). This evolution hampers successful deployment of smartphones in sensing applications in scientific contexts, with unreliable and incomplete sampling rates frequently reported in literature. In this article, we discuss the ins and outs of Android’s background tasks scheduling mechanism, and formulate guidelines for developers to successfully implement reliable task scheduling. Implementing these guidelines, we present a software library, agnostic from the underlying Android scheduling mechanisms and restrictions, that allows Android developers to reliably schedule tasks with a maximum sampling rate of one minute. Our evaluation demonstrates the use and versatility of our task scheduler, and experimentally confirms its reliability and acceptable energy usage.},
keywords = {Mobile apps, mobile computing, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Osma2021,
title = {Implementation, efficacy and cost effectiveness of the unified protocol in a blended format for the transdiagnostic treatment of emotional disorders: a study protocol for a multicentre, randomised, superiority controlled trial in the Spanish National Health System },
author = {Jorge Osma and Laura Martínez-García and Óscar Perís-Baquero and María Vicenta Navarro-Haro and Alberto González-Pérez and Carlos Suso-Ribera},
doi = {10.1136/bmjopen-2021-054286},
issn = {2044-6055},
year = {2021},
date = {2021-12-31},
journal = {BMJ Open},
volume = {11},
number = {e054286},
abstract = {Introduction: Emotional disorders (EDs) have become the most prevalent psychological disorders in the general population, which has boosted the economic burden associated with their management. Approximately half of the individuals do not receive adequate treatment. Consequently, finding solutions to deliver cost-effective treatments for EDs has become a key goal of today’s clinical psychology. Blended treatments, a combination of face-to-face and online interventions, have emerged as a potential solution to the previous. The Unified Protocol for the Transdiagnostic Treatment of EDs (UP) might serve this purpose, as it can be applied to a variety of disorders simultaneously and its manualised format makes it suitable for blended interventions.

Methods and analysis: The study is a multicentre, randomised, superiority, clinical trial. Participants will be 310 individuals with a diagnosis of an ED. They will be randomised to a treatment as usual (individual cognitive behavioural therapy) or a UP condition in a blended format (face-to-face individual UP +online, app-based UP). Primary outcomes will be ED diagnostic criteria and depression and anxiety symptoms. Cost efficiency of the intervention, app usability, as well as opinion and confidence in the treatment will also be evaluated. Assessment points will include baseline and 3 months, 6 months and 12 months after UP treatment.

Ethics and dissemination: The study has received approvals by the Ethics Research Committee of Navarra, Castellón, Euskadi, Castilla y León, Extremadura, Lleida and Aragón. The study is currently under an approval process by the Ethics Research Committees of all the remaining collaborating centres. Outcomes will be disseminated through publication in peer-reviewed journals and presentations at international conference meetings.},
keywords = {mental health, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Miralles-Tena2020b,
title = {Smartphone apps for the treatment of mental disorders: a systematic review},
author = {Ignacio Miralles-Tena and Carlos Granell-Canut and Laura Díaz-Sanahuja and William Van Woensel and Juana Bretón-López and Adriana Mira and Diana Castilla and Sven Casteleyn},
doi = {10.2196/14897},
issn = {2291-5222},
year = {2020},
date = {2020-03-04},
journal = {JMIR mHealth and uHealth},
volume = {8},
number = {3},
pages = {e14897},
abstract = {Background: Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective.
Objective: This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]).
Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features.
Results: We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6%) and anxiety disorders (18/158, 11.4%). Of the total, 72.7% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods.
Conclusions: There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders.},
note = {IF},
keywords = {Health applications, mental health, Mobile apps, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Miralles-Tena2020,
title = {Enhancing in vivo exposure in the treatment of panic disorder and agoraphobia using location-based technologies: A case report},
author = {Ignacio Miralles-Tena and Carlos Granell-Canut and Azucena García-Palacios and Diana Castilla and Alberto González-Pérez and Sven Casteleyn and Juana Bretón-López.},
isbn = {1534-6501},
year = {2020},
date = {2020-03-01},
journal = {Clinical case studies},
volume = {19},
number = {2},
pages = {145-159},
abstract = {Panic disorder (PD) is quite prevalent and often appears along with agoraphobia (PD/A). The treatment of choice is cognitive behavioral therapy (CBT). Transdiagnostic intervention, an emotion-focused, cognitive behavioral intervention that has led to the Unified Protocol (UP), emphasizes the common underlying mechanisms that contribute to the development and maintenance of emotional disorders such as PD/A. A core feature of this treatment approach is in vivo exposure (IVE) to feared situations, which aims to prevent avoidance behaviors and encourages the patient to confront feared situations gradually. It is a difficult component for patients, especially when implementing the exposure on their own. Different feedback formats can be used to increase adequate IVE and reduce overt or subtle avoidance. The use of smartphones is a very useful option to initiate and sustain exposure behavior. The purpose of this study is to describe the use of location-based technologies (LBTs) during the IVE component of the UP treatment of a 47-year-old patient with PD/A. The acceptability and usability of the system were assessed. The Symptoms platform was employed during the exposure module, using LBT with a smartphone app. The patient reported positive expectations, high satisfaction scores, and an overall satisfactory experience. Enhancing key therapeutic components during treatment through the development of media-based tools is a very promising future research aim, and the possibility of using advanced smartphone features should be explored.},
keywords = {Health applications, LBS, mental health, symptoms},
pubstate = {published},
tppubtype = {article}
}

@article{Miralles-Tena2019,
title = {Considerations for designing context-aware mobile apps for mental health interventions},
author = {Ignacio Miralles-Tena and Carlos Granell-Canut},
doi = {10.3390/ijerph16071197},
year = {2019},
date = {2019-03-15},
journal = {International journal of environmental research and public health},
volume = {6},
number = {7},
pages = {1197},
abstract = {This work identifies major areas of knowledge and proposes a set of relevant dimensions by area that must be taken into account in the design and delivery of context-aware mobile applications for mental health interventions. We argue that much of the related research has focused only on a few dimensions, paying little or no attention to others and, most importantly, to potential relationships between them. Our belief is that the improvement of the effectiveness of mobile interventions to support mental health necessarily implies that developers and therapists comprehensively consider the interaction between the proposed dimensions. Taking as a starting point the three areas of knowledge (Technology, Context, and Mental Health), we re-examine each area to identify relevant dimensions, discuss the relationships between them and finally draw a series of
considerations. The resulting considerations can help therapists and developers to devise, design, and generate custom mobile applications in a way that increases the motivation and engagement of patients and, therefore, the effectiveness of psychological treatments.},
note = {IF},
keywords = {context-aware computing, FPU_Miralles, Health applications, Mobile apps, RyC-Granell, symptoms},
pubstate = {published},
tppubtype = {article}
}