Information System for Symptom Diagnosis and Improvement of Attention Deficit Hyperactivity Disorder: Protocol for a Nonrandomized Controlled Pilot Study.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders during childhood; however, the diagnosis procedure remains challenging, as it is nonstandardized, multiparametric, and highly dependent on subjective evaluation of the perceived behavior. OBJECTIVE: To address the challenges of existing procedures for ADHD diagnosis, the ADHD360 project aims to develop a platform for (1) early detection of ADHD by assessing the user's likelihood of having ADHD characteristics and (2) providing complementary training for ADHD management. METHODS: A 2-phase nonrandomized controlled pilot study was designed to evaluate the ADHD360 platform, including ADHD and non-ADHD participants aged 7 to 16 years. At the first stage, an initial neuropsychological evaluation along with an interaction with the serious game developed ("Pizza on Time") for approximately 30-45 minutes is performed. Subsequently, a 2-week behavior monitoring of the participants through the mADHD360 app is planned after a telephone conversation between the participants' parents and the psychologist, where the existence of any behaviors characteristic of ADHD that affect daily functioning is assessed. Once behavior monitoring is complete, the research team invites the participants to the second stage, where they play the game for a mean duration of 10 weeks (2 times per week). Once the serious game is finished, a second round of behavior monitoring is performed following the same procedures as the initial one. During the study, gameplay data were collected and preprocessed. The protocol of the pilot trials was initially designed for in-person participation, but after the COVID-19 outbreak, it was adjusted for remote participation. State-of-the-art machine learning (ML) algorithms were used to analyze labeled gameplay data aiming to detect discriminative gameplay patterns among the 2 groups (ADHD and non-ADHD) and estimate a player's likelihood of having ADHD characteristics. A schema including a train-test splitting with a 75:25 split ratio, k-fold cross-validation with k=3, an ML pipeline, and data evaluation were designed. RESULTS: A total of 43 participants were recruited for this study, where 18 were diagnosed with ADHD and the remaining 25 were controls. Initial neuropsychological assessment confirmed that the participants in the ADHD group showed a deviation from the participants without ADHD characteristics. A preliminary analysis of collected data consisting of 30 gameplay sessions showed that the trained ML models achieve high performance (ie, accuracy up to 0.85) in correctly predicting the users' labels (ADHD or non-ADHD) from their gameplay session on the ADHD360 platform. CONCLUSIONS: ADHD360 is characterized by its notable capacity to discriminate player gameplay behavior as either ADHD or non-ADHD. Therefore, the ADHD360 platform could be a valuable complementary tool for early ADHD detection. TRIAL REGISTRATION: ClinicalTrials.gov NCT04362982; https://clinicaltrials.gov/ct2/show/NCT04362982. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/40189.

Eliminating the gap between the use of assistive technologies and the inclusion of people with intellectual disabilities in leisure activities.

Information and Communication Technology (ICT) tools and Assistive Technologies (AT) can support people with Down Syndrome (PDS) and Intellectual Disabilities (PID) in increasing their self-confidence and independence, enhancing skills, and competences, participating in leisure activities. For families of PDS/PID, professionals, non-formal caregivers and volunteers, the challenge is to appreciate the benefits of ICT Tools in promoting inclusion. The aim of this study is to present the interdisciplinary and multidimensional scope of the DS Leisure project aiming at promoting the inclusion of PDS/PID through innovative ICT tools and their participation in inclusive leisure activities. Particularly, 24 individuals were asked to assess the global satisfaction and performance of PDS/PID, as well as the exploitation of ICT tools. Findings suggested that PDS/PID specific social, decision-making, and communication skills were significantly improved after their participation in the Experiential Activity and the e-Training platform was positively rated and considered a constructive learning experience.

Design and evaluation of mobile scenario based learning in the self-management of chronic pain.

Chronic pain is a lifelong issue, being one of the main causes of disability, affecting a great number of people worldwide, many of which often avoid seeking medical advice from pain experts and/or demonstrate poor adherence to their therapeutic plan. One of the most important steps in achieving a manageable course of disease, is the ability of self-management. We aimed at applying a method of systematic patient education and self-management through the use of Virtual Patients (VPs), a well-established method for educating medical doctors and students but never before targeting patients. Two VPs scenarios were designed, tested and evaluated by patients with rheumatic disorders, achieving a SUS score of 88/100 "Best Imaginable", alongside with positive reviews from the participants. The positive feedback from the patients supports the potential of VP educational paradigm to educate these patients and equip them with disease coping skills and strategies.

A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial.

BACKGROUND: Smoking cessation is the most common preventative for an array of diseases, including lung cancer and chronic obstructive pulmonary disease. Although there are many efforts advocating for smoking cessation, smoking is still highly prevalent. For instance, in the USA in 2015, 50% of all smokers attempted to quit smoking, and only 5-7% of them succeeded - with slight deviation depending on external assistance. Previous studies show that computer-tailored messages which support smoking abstinence are effective. The combination of health recommender systems and behavioral-change theories is becoming increasingly popular in computer-tailoring. The objective of this study is to evaluate patients's smoking cessation rates by means of two randomized controlled trials using computer-tailored motivational messages. A group of 100 patients will be recruited in medical centers in Taiwan (50 patients in the intervention group, and 50 patients in the control group), and a group of 1000 patients will be recruited on-line (500 patients in the intervention group, and 500 patients in the control group). The collected data will be made available to the public in an open-source data portal. METHODS: Our study will gather data from two sources. The first source is a clinical pilot in which a group of patients from two Taiwanese medical centers will be randomly assigned to either an intervention or a control group. The intervention group will be provided with a mobile app that sends motivational messages selected by a recommender system that takes the user profile (including gender, age, motivations, and social context) and similar users' opinions. For 6 months, the patients' smoking activity will be followed up, and confirmed as "smoke-free" by using a test that measures expired carbon monoxide and urinary cotinine levels. The second source will be a public pilot in which Internet users wanting to quit smoking will be able to download the same mobile app as used in the clinical pilot. They will be randomly assigned to a control group that receives basic motivational messages or to an intervention group, that receives personalized messages by the recommender system. For 6 months, patients in the public pilot will be assessed periodically with self-reported questionnaires. DISCUSSION: This study will be the first to use the I-Change behavioral-change model in combination with a health recommender system and will, therefore, provide relevant insights into computer-tailoring for smoking cessation. If our hypothesis is validated, clinical practice for smoking cessation would benefit from the use of our mobile solution. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03108651 . Registered on 11 April 2017.

Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol.

BACKGROUND: Smoking is one of the most avoidable health risk factors, and yet the quitting success rates are low. The usage of tailored health messages to support quitting has been proved to increase quitting success rates. Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items-for instance, motivational messages aimed at smoking cessation-for each user based on his or her profile. The goals of this study are to analyze the perceived quality of an mHealth recommender system aimed at smoking cessation, and to assess the level of engagement with the messages delivered to users via this medium. METHODS: Patients participating in a smoking cessation program will be provided with a mobile app to receive tailored motivational health messages selected by a health recommender system, based on their profile retrieved from an electronic health record as the initial knowledge source. Patients' feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. This paper details the implementation and evaluation protocol that will be followed. DISCUSSION: This study will explore whether a health recommender system algorithm integrated with an electronic health record can predict which tailored motivational health messages patients would prefer and consider to be of a good quality, encouraging them to engage with the system. The outcomes of this study will help future researchers design better tailored motivational message-sending recommender systems for smoking cessation to increase patient engagement, reduce attrition, and, as a result, increase the rates of smoking cessation. TRIAL REGISTRATION: The trial was registered at clinicaltrials.org under the ClinicalTrials.gov identifier NCT03206619 on July 2nd 2017. Retrospectively registered.

Multimodal e-Health Services for Smoking Cessation and Public Health: The SmokeFreeBrain Project Approach.

Smoking is the largest avoidable cause of preventable morbidity worldwide. It causes most of the cases of lung cancer and chronic obstructive pulmonary disease (COPD) and contributes to the development of other lung diseases. SmokeFreeBrain aims to address the effectiveness of a multi-level variety of interventions aiming at smoking cessation in high risk target groups within High Middle Income Countries (HMIC) such as unemployed young adults, COPD and asthma patients, and within the general population in Low-Middle Income Countries (LMIC). The project addresses existing approaches aimed to prevent lung diseases caused by tobacco while developing new treatments and evaluating: (i) Public Service Announcement (PSA) against smoking, (ii) the use of electronic cigarettes, (iii) neurofeedback protocols against smoking addiction, (iv) a specifically developed intervention protocol based on behavioral therapy, social media/mobile apps and short text messages (sms) and (v) pharmacologic interventions. Emphasis in this paper, however, is placed on the e-heath, m-health, open (big) data, mobile game and neuroscientific challenges and developments upon facilitating the aforementioned interventions.

Medical Content Searching, Retrieving, and Sharing Over the Internet: Lessons Learned From the mEducator Through a Scenario-Based Evaluation.

BACKGROUND: The mEducator Best Practice Network (BPN) implemented and extended standards and reference models in e-learning to develop innovative frameworks as well as solutions that enable specialized state-of-the-art medical educational content to be discovered, retrieved, shared, and re-purposed across European Institutions, targeting medical students, doctors, educators and health care professionals. Scenario-based evaluation for usability testing, complemented with data from online questionnaires and field notes of users' performance, was designed and utilized for the evaluation of these solutions. OBJECTIVE: The objective of this work is twofold: (1) to describe one instantiation of the mEducator BPN solutions (mEducator3.0 - "MEdical Education LINnked Arena" MELINA+) with a focus on the metadata schema used, as well as on other aspects of the system that pertain to usability and acceptance, and (2) to present evaluation results on the suitability of the proposed metadata schema for searching, retrieving, and sharing of medical content and with respect to the overall usability and acceptance of the system from the target users. METHODS: A comprehensive evaluation methodology framework was developed and applied to four case studies, which were conducted in four different countries (ie, Greece, Cyprus, Bulgaria and Romania), with a total of 126 participants. In these case studies, scenarios referring to creating, sharing, and retrieving medical educational content using mEducator3.0 were used. The data were collected through two online questionnaires, consisting of 36 closed-ended questions and two open-ended questions that referred to mEducator 3.0 and through the use of field notes during scenario-based evaluations. RESULTS: The main findings of the study showed that even though the informational needs of the mEducator target groups were addressed to a satisfactory extent and the metadata schema supported content creation, sharing, and retrieval from an end-user perspective, users faced difficulties in achieving a shared understanding of the meaning of some metadata fields and in correctly managing the intellectual property rights of repurposed content. CONCLUSIONS: The results of this evaluation impact researchers, medical professionals, and designers interested in using similar systems for educational content sharing in medical and other domains. Recommendations on how to improve the search, retrieval, identification, and obtaining of medical resources are provided, by addressing issues of content description metadata, content description procedures, and intellectual property rights for re-purposed content.

Internet addiction in Greek medical students: an online survey.

OBJECTIVE: The authors investigated the prevalence of Internet addiction (IA) in undergraduate medical students to identify possible associations with sociodemographics and Internet habits. METHODS: All students at the Aristotle University of Thessaloniki School of Medicine, Greece, were invited to complete the online Internet Addiction Test (IAT) along with sociodemographics and preferences on Internet activities. RESULTS: The authors received 585 responses after three reminders (23.5 % response rate). Mild IA was found in 24.5 %, moderate in 5.4 %, and severe in 0.2 %. In multivariable analysis, the odds to develop IA were increased with visits in Internet cafes (Odds Ratio [OR] 3.49, 95 % Confidence Interval [CI]: 1.45, 8.46), the use of Facebook (OR 2.43, 95 % CI: 1.35, 4.38), Twitter (OR 2.45, 95 % CI: 1.37, 4.39), and online games (OR 1.95, 95 % CI: 1.29, 2.94). Using e-mails seemed to be protective against IA (OR 0.59, 95 % CI: 0.37, 0.94). CONCLUSION: This is the first IA prevalence study in a European medical school. Early-detection systems and other ways to help students with pathological behaviors should be developed.