22,329 research outputs found
Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies
to collect data and extract relevant informationâs for patient management. Artificial intelligence (AI) techniques
allow processing of real-time observational information and continuously learning from data to build
understanding. We designed a system able to get clinical sense from digital footprints based on the smartphoneâs
native sensors and advanced machine learning and signal processing techniques in order to identify suicide risk.
Method/design: The Smartcrisis study is a cross-national comparative study. The study goal is to determine the
relationship between suicide risk and changes in sleep quality and disturbed appetite. Outpatients from the
Hospital FundaciĂłn JimĂ©nez DĂaz Psychiatry Department (Madrid, Spain) and the University Hospital of Nimes
(France) will be proposed to participate to the study. Two smartphone applications and a wearable armband will
be used to capture the data. In the intervention group, a smartphone application (MEmind) will allow for the
ecological momentary assessment (EMA) data capture related with sleep, appetite and suicide ideations.
Discussion: Some concerns regarding data security might be raised. Our system complies with the highest level of
security regarding patientsâ data. Several important ethical considerations related to EMA method must also be
considered. EMA methods entails a non-negligible time commitment on behalf of the participants. EMA rely on
daily, or sometimes more frequent, Smartphone notifications. Furthermore, recording participantsâ daily experiences
in a continuous manner is an integral part of EMA. This approach may be significantly more than asking a
participant to complete a retrospective questionnaire but also more accurate in terms of symptoms monitoring.
Overall, we believe that Smartcrises could participate to a paradigm shift from the traditional identification of risks
factors to personalized prevention strategies tailored to characteristics for each patientThis study was partly funded by FundaciĂłn JimĂ©nez DĂaz Hospital, Instituto
de Salud Carlos III (PI16/01852), DelegaciĂłn del Gobierno para el Plan
Nacional de Drogas (20151073), American Foundation for Suicide Prevention
(AFSP) (LSRG-1-005-16), the Madrid Regional Government (B2017/BMD-3740
AGES-CM 2CM; Y2018/TCS-4705 PRACTICO-CM) and Structural Funds of the
European Union. MINECO/FEDER (âADVENTUREâ, id. TEC2015â69868-C2â1-R)
and MCIU Explora Grant âaMBITIONâ (id. TEC2017â92552-EXP), the French Embassy
in Madrid, Spain, The foundation de lâavenir, and the Fondation de
France. The work of D. RamĂrez and A. ArtĂ©s-RodrĂguez has been partly supported
by Ministerio de EconomĂa of Spain under projects: OTOSIS
(TEC2013â41718-R), AID (TEC2014â62194-EXP) and the COMONSENS Network
(TEC2015â69648-REDC), by the Ministerio de EconomĂa of Spain jointly with
the European Commission (ERDF) under projects ADVENTURE (TEC2015â
69868-C2â1-R) and CAIMAN (TEC2017â86921-C2â2-R), and by the Comunidad
de Madrid under project CASI-CAM-CM (S2013/ICE-2845). The work of P.
Moreno-Muñoz has been supported by FPI grant BES-2016-07762
The Impacts of Privacy Rules on Users' Perception on Internet of Things (IoT) Applications: Focusing on Smart Home Security Service
Department of Management EngineeringAs communication and information technologies advance, the Internet of Things (IoT) has changed the way people live. In particular, as smart home security services have been widely commercialized, it is necessary to examine consumer perception. However, there is little research that explains the general perception of IoT and smart home services. This article will utilize communication privacy management theory and privacy calculus theory to investigate how options to protect privacy affect how users perceive benefits and costs and how those perceptions affect individuals??? intentions to use of smart home service. Scenario-based experiments were conducted, and perceived benefits and costs were treated as formative second-order constructs. The results of PLS analysis in the study showed that smart home options to protect privacy decreased perceived benefits and increased perceived costs. In addition, the perceived benefits and perceived costs significantly affected the intention to use smart home security services. This research contributes to the field of IoT and smart home research and gives practitioners notable guidelines.ope
When does personalization work on social media? a posteriori segmentation of consumers
The aim of this research is to find a segment of consumers of fashion products based on their
personal visions of personalization of shoppable ads on mobile social media. To meet this
objective, three operational objectives are defined. First, a theoretical model is evaluated based
on the stimulus-organism-response framework (SâOâR). This examines, with a PLS-SEM
approach, how the stimulation of personalization will affect consumersâ internal cognitive
state (perceived usefulness) and consequently generates a behavioral response (intention
to buy). Second, we look for fashion consumer segments based on their perception of
personalization through prediction-oriented segmentation (PLS-POS). Third, the segments are
explained based on three constructs that were considered important in fashion consumption
through mobile social networks: purchase intention, concern for privacy, and perception of
trend. The inclusion of personalization and the perception of usefulness of advertisements can
greatly help the intention to purchase clothing to be understood. The application of a posterior
segmentation helps to better understand the different types of users exposed to shoppable
ads on mobile social networks and their relationship with the purchase intention, concern for
privacy and trend. While the measures and scales were tested in a context of mobile clothing
trade, the methodology can be applied to other types of products or services
Big Data Ethics in Research
The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (Data Protection Directive - General Data Protection Regulation, "GDPR"). The Ethics Issues section details the specific aspects of Big Data. After a brief section of Big Data Research, I finalize my work with the presentation of Conclusions on research ethics in working with Big Data.
CONTENTS:
Abstract
1. Introduction
- 1.1 Definitions
- 1.2 Big Data dimensions
2. Technology
- 2.1 Applications
- - 2.1.1 In research
3. Philosophical aspects
4. Legal aspects
- 4.1 GDPR
- - Stages of processing of personal data
- - Principles of data processing
- - Privacy policy and transparency
- - Purposes of data processing
- - Design and implicit confidentiality
- - The (legal) paradox of Big Data
5. Ethical issues
- Ethics in research
- Awareness
- Consent
- Control
- Transparency
- Trust
- Ownership
- Surveillance and security
- Digital identity
- Tailored reality
- De-identification
- Digital inequality
- Privacy
6. Big Data research
Conclusions
Bibliography
DOI: 10.13140/RG.2.2.11054.4640
Emotions in context: examining pervasive affective sensing systems, applications, and analyses
Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; âsensingâ, âanalysisâ, and âapplicationâ. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing
DOES PRIVACY THREAT MATTER IN MOBILE HEALTH SERVICE? FROM HEALTH BELIEF MODEL PERSPECTIVE
A lot of mobile health (mHealth) service apps have been launched in the market with advances in technology. When people decide to use these mHealth service apps, they have to provide their personal data or personal health data more or less to the service providers. However, the health data is more sensitive data than general personal data. In addition, the behaviour of using mHealth service apps includes technology use behaviour and health promotion behaviour. Therefore, we employed HBM to be the theory foundation to find out what factors will impact on the intention to upload personal health data via a mHealth service app. Online questionnaires were distributed and 133 valid questionnaires were returned. The results showed the perceived benefits is the only factor to influence an individual intention to upload personal health data. The specific information privacy concerns has no significant effect on the behaviour intention. That means people value the benefits that the mhealth service app can bring more than the threat of privacy they perceived. The construct, disposition to value privacy (DTVP), have strong effects on perceived vulnerability, perceived severity, and specific information privacy concerns. Future studies will be recommended
The Surprising Lack of Effect of Privacy Concerns on Intention to Use Online Social Networks
The number of users of Online Social Networks (OSNs) has increased dramatically. To join OSNs, users need to disclosetheir information to others. If people have higher levels of privacy concerns, they may hesitate to expose their information.Therefore, privacy concerns should be an important factor affecting the use of OSNs. Based on prior studies, we investigatehow individualsâ perceived benefits (usefulness, playfulness) and perceived costs (privacy concern) directly influence theirintention to continue using OSNs, and how the benefits are mediated by cost factors in cognitive cost-benefit calculations.We suggest five hypotheses and examine them empirically with 391 survey responses. The results only support the directeffect of perceived benefits on OSNs. Results do not show any direct effect or mediation effect of privacy concerns on theintention to use OSNs. This paper contributes to future social network studies by providing a conceptual framework as wellas empirical results
Your privacy for a discount? Exploring the willingness to share personal data for personalized offers
publishedVersio
Sustaining Patient Engagement: The Role of Health Emotion and Personality Traits in Patient Portal Continuous Use Decision
Healthcare providers increasingly rely on technology, such as patient portals, for asynchronous communication with their patients. Even though clinicians have increasingly adopted patient portals to enhance healthcare quality and reduce cost, few patients continue to use this technology. In this paper, we investigate the effect that individualsâ health emotion and personality traits as measured using the five-factor model (FFM) have on patientsâ intention to continually use patient portals through the lens of emotional dissonance theory. We collected survey data from 187 patients at a major medical center in the Midwestern United States. After we analyzed the data using structural equation modeling, we found that the final model explained 40 percent of the variance in intention to continue to use. Our results suggest that whether individuals continue to use technology depends on their reactions to technology in which health emotions and personality traits play a crucial part. Additionally, health emotion modifies the effect that personality traits have on patientsâ intention to continue to use a patient portal. Our study provides healthcare organizations with an integrated view of patient portal use behavior and shows that individual personality traits and health emotion may increase sustainable patient enrollment and engagement
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