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ronment. We are currently exploring the possibility of using it in speech therapy situations. ©Santiago García García-Carbajal, María Pipa-Muniz, Jose Luis Múgica. Originally published in JMIR Serious Games (http//games.jmir.org), 27.02.2020.BACKGROUND The digital revolution has led to a boom in the number of available online health care resources. To navigate these resources successfully, digital literacy education is required. Learners who can evaluate the reliability and validity of online health care information are likely to be more effective at avoiding potentially dangerous misinformation. In addition to providing health care education, massive open online courses (MOOCs) are well positioned to play a role in providing digital literacy education in this context. OBJECTIVE This study focused on learners enrolled in a MOOC on cancer genomics. The aim of this study was to evaluate the efficacy of a series of digital literacy-related activities within this course. This was an iterative study, with changes made to digital literacy-related activities in 4 of the 8 runs of the course. METHODS This mixed methods study focused on learner engagement with the digital literacy-related activities, including the final course written assignment. Quantitath care MOOCs, the course studied here had a heterogeneous group of learners, including patients (and their families), the public, health care students, and practitioners. Carefully designing a range of digital literacy-related activities that would be beneficial to this heterogenous group of learners enabled learners to become more effective at evaluating and citing appropriate online resources within their written assignments. ©Louise M Blakemore, Sarah E M Meek, Leah K Marks. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 26.02.2020.BACKGROUND Lack of knowledge and poor attitude are barriers to colorectal cancer screening participation. Printed material, such as pamphlets and posters, have been the main approach in health education on disease prevention in Malaysia. Current information technology advancements have led to an increasing trend of the public reading from websites and mobile apps using their mobile phones. Thus, health information dissemination should also be diverted to websites and mobile apps. Increasing knowledge and awareness could increase screening participation and prevent late detection of diseases such as colorectal cancer. OBJECTIVE This study aimed to assess the effectiveness of the ColorApp mobile app in improving the knowledge and attitude on colorectal cancer among users aged 50 years and older, who are the population at risk for the disease in Kedah. METHODS A quasi-experimental study was conducted with 100 participants in Kedah, Malaysia. Participants from five randomly selected community empowerment programs=19.81, P less then .001). However, there was no significant difference in mean attitude scores between the intervention and control groups with regards to time (F1,95=0.36, P=.55). CONCLUSIONS The ColorApp mobile app may be an adjunct approach in educating the public on colorectal cancer. ©Nor Azwany Yaacob, Muhamad Fadhil Mohamad Marzuki, Najib Majdi Yaacob, Shahrul Bariyah Ahmad, Muhammad Radzi Abu Hassan. Originally published in JMIR Human Factors (http//humanfactors.jmir.org), 25.02.2020.BACKGROUND Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS We first discussed various NLP techniques and demonstrated how they are implemented in the presented frameasily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts. ©Burkhardt Funk, Shiri Sadeh-Sharvit, Ellen E Fitzsimmons-Craft, Mickey Todd Trockel, Grace E Monterubio, Neha J Goel, Katherine N Balantekin, Dawn M Eichen, Rachael E Flatt, Marie-Laure Firebaugh, Corinna Jacobi, Andrea K Graham, Mark Hoogendoorn, Denise E Wilfley, C Barr Taylor. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 19.02.2020.BACKGROUND Social media data are being increasingly used for population-level health research because it provides near real-time access to large volumes of consumer-generated data. Recently, a number of studies have explored the possibility of using social media data, such as from Twitter, for monitoring prescription medication abuse. However, there is a paucity of annotated data or guidelines for data characterization that discuss how information related to abuse-prone medications is presented on Twitter. OBJECTIVE This study discusses the creation of an annotated corpus suitable for training supervised classification algorithms for the automatic classification of medication abuse-related chatter. The annotation strategies used for improving interannotator agreement (IAA), a detailed annotation guideline, and machine learning experiments that illustrate the utility of the annotated corpus are also described. METHODS We employed an iterative annotation strategy, with interannotator discussions held and update, nonmedical use, nonstandard route of intake, and consumption above the prescribed doses. Among machine learning classifiers, support vector machines obtained the highest automatic classification accuracy of 73.00% (95% CI 71.4-74.5) over the test set (n=3271). CONCLUSIONS Our manual analysis and annotations of a large number of tweets have revealed types of information posted on Twitter about a set of abuse-prone prescription medications and their distributions. In the interests of reproducible and community-driven research, we have made our detailed annotation guidelines and the training data for the classification experiments publicly available, and the test data will be used in future shared tasks. ©Karen O'Connor, Abeed Sarker, Jeanmarie Perrone, Graciela Gonzalez Hernandez. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 26.02.2020.BACKGROUND Previous data have validated the benefit of digital health interventions (DHIs) on weight loss in patients following acute coronary syndrome entering cardiac rehabilitation (CR). OBJECTIVE The primary purpose of this study was to test the hypothesis that increased DHI use, as measured by individual log-ins, is associated with improved weight loss. Secondary analyses evaluated the association between log-ins and activity within the platform and exercise, dietary, and medication adherence. METHODS We obtained DHI data including active days, total log-ins, tasks completed, educational modules reviewed, medication adherence, and nonmonetary incentive points earned in patients undergoing standard CR following acute coronary syndrome. Linear regression followed by multivariable models were used to evaluate associations between DHI log-ins and weight loss or dietary adherence. RESULTS Participants (n=61) were 79% male (48/61) with mean age of 61.0 (SD 9.7) years. We found a significant positive association of total log-ins during CR with weight loss (r2=.10, P=.03). Educational modules viewed (r2=.11, P=.009) and tasks completed (r2=.10, P=.01) were positively significantly associated with weight loss, yet total log-ins were not significantly associated with differences in dietary adherence (r2=.05, P=.12) or improvements in minutes of exercise per week (r2=.03, P=.36). CONCLUSIONS These data extend our previous findings and demonstrate increased DHI log-ins portend improved weight loss in patients undergoing CR after acute coronary syndrome. DHI adherence can potentially be monitored and used as a tool to selectively encourage patients to adhere to secondary prevention lifestyle modifications. TRIAL REGISTRATION ClinicalTrials.gov (NCT01883050); https//clinicaltrials.gov/ct2/show/NCT01883050. ©R Jay Widmer, Conor Senecal, Thomas G Allison, Francisco Lopez-Jimenez, Lilach O Lerman, Amir Lerman. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 26.02.2020.BACKGROUND With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The development of cloud health care provides a more convenient and effective solution for health. click here Studying the evolution of knowledge and research hotspots in the field of cloud health care is increasingly important for medical informatics. Scholars in the medical informatics community need to understand the extent of the evolution of and possible trends in cloud health care research to inform their future research. OBJECTIVE Drawing on the cloud health care literature, this study aimed to describe the development and evolution of research themes in cloud health care through a knowledge map and common word analysis. METHODS A total of 2878 articles about cloud health care was retrieved from the Web of Science database. We used cybermetrics to analyze and visualize the kee three possible trends in the future development of the cloud health care field. ©Dongxiao Gu, Xuejie Yang, Shuyuan Deng, Changyong Liang, Xiaoyu Wang, Jiao Wu, Jingjing Guo. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 25.02.2020.BACKGROUND HIV remains a significant health issue in the United States and disproportionately affects African Americans. African American women living with HIV (AAWH) experience a particularly high number of barriers when attempting to manage their HIV care, including antiretroviral therapy (ART) adherence. To enable the development and assessment of effective interventions that address these barriers to support ART adherence, there is a critical need to understand more fully the use of objective measures of ART adherence among AAWH, including electronic medication dispensers for real-time surveillance. OBJECTIVE This study aimed to evaluate the use of the Wisepill medication event-monitoring system (MEMS) and compare the objective and subjective measures of ART adherence. METHODS We conducted a 30-day exploratory pilot study of the MEMS among a convenience sample of community-dwelling AAWH (N=14) in rural Florida. AAWH were trained on the use of the MEMS to determine the feasibility of collecting, capturing, 19.02.2020.Globally, the burden of noncommunicable diseases such as type 2 diabetes is crippling health care systems. Type 2 diabetes, a disease linked with obesity, affects 1 in every 30 people today and is expected to affect 1 in 10 people by 2030. Current provisions are struggling to manage the trajectory of type 2 diabetes prevalence. Offline, face-to-face education for patients with type 2 diabetes has shown to lack long-term impact or the capacity for widespread democratized adoption. Digitally delivered interventions have been developed for patients with type 2 diabetes, and the evidence shows that some interventions provide the capacity to support hyperpersonalization and real-time continuous support to patients, which can result in significant engagement and health outcomes. However, digital health app engagement is notoriously difficult to achieve. This paper reviews the digital behavior change architecture of the Low Carb Program and the application of health behavioral theory underpinning its development and use in scaling novel methods of engaging the population with type 2 diabetes and supporting long-term behavior change.