ents’ engagement in the diabetes education courses. Middle-aged patients (35-59 years old) and elderly patients (≥60 years old) completed more diabetes education courses (middle-aged group, β=2.22, P=.01; elderly group, β=2.42, P=.02) than young patients (18-34 years old). CONCLUSIONS LCCP app-based diabetes education is effective for glycemic control and SMBG behavior improvement in patients with type 2 diabetes receiving insulin therapy. Young patients’ engagement in the education courses was relatively low. We need to conduct in-depth interviews with users to further improve the curriculum. ©Yiyu Zhang, Chaoyuan Liu, Shuoming Luo, Jin Huang, Xia Li, Zhiguang Zhou. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 06.03.2020.BACKGROUND Previous research suggests that artificial agents may be a promising source of social support for humans. However, the bulk of this research has been conducted in the context of social support interventions that specifically address stressful situations or health improvements. Little research has examined social support received from artificial agents in everyday contexts. OBJECTIVE Considering that social support manifests in not only crises but also everyday situations and that everyday social support forms the basis of support received during more stressful events, we aimed to investigate the types of everyday social support that can be received from artificial agents. METHODS In Study 1, we examined publicly available user reviews (N=1854) of Replika, a popular companion chatbot. In Study 2, a sample (n=66) of Replika users provided detailed open-ended responses regarding their experiences of using Replika. We conducted thematic analysis on both datasets to gain insight into the kind of everydaro, Alexia Loggarakis. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 06.03.2020.BACKGROUND Approximately 50% of patients are nonadherent to prescribed medications. Patient perception regarding medication effectiveness has been linked to improved adherence. However, how patients perceive effectiveness is poorly understood. OBJECTIVE The aim of this study was to elucidate factors associated with perceived treatment satisfaction and effectiveness among patients with chronic health conditions. METHODS We conducted a descriptive study using a cross-sectional survey design. We administered a Web-based survey to participants with migraine, multiple sclerosis (MS), or rheumatoid arthritis (RA). Patients were recruited from established online communities of Health Union. Descriptive statistics, correlations, and comparison tests were used to examine outcomes. RESULTS Data were collected from 1820 patients 567 with migraine, 717 with MS, and 536 with RA. The majority of participants were female (1644/1820, 90.33%), >40 years old (1462/1820, 80.33%), and diagnosed >5 years ago (1189/1820, 65.33%). icelli Leonard, Courtney Robertson, Amrita Bhowmick, Leslie Beth Herbert. Originally published in the Interactive Journal of Medical Research (http//www.i-jmr.org/), 06.03.2020.BACKGROUND Surveys suggest that a large proportion of people use the internet to search for information on medical symptoms they experience and that around one-third of the people in the United States self-diagnose using online information. However, surveys are known to be biased, and the true rates at which people search for information on their medical symptoms before receiving a formal medical diagnosis are unknown. OBJECTIVE This study aimed to estimate the rate at which people search for information on their medical symptoms before receiving a formal medical diagnosis by a health professional. METHODS We collected queries made on a general-purpose internet search engine by people in the United States who self-identified their diagnosis from 1 of 20 medical conditions. We focused on conditions that have evident symptoms and are neither screened systematically nor a part of usual medical care. CrEL Thus, they are generally diagnosed after the investigation of specific symptoms. We evaluated how many of these pes finding has important implications for systems that attempt to screen for medical conditions. ©Irit Hochberg, Raviv Allon, Elad Yom-Tov. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 06.03.2020.BACKGROUND Wearable activity trackers and social media have been identified as having the potential to increase physical activity among adolescents, yet little is known about the perceived ease of use and perceived usefulness of the technology by adolescents. OBJECTIVE The aim of this study was to use the technology acceptance model to explore adolescents’ acceptance of wearable activity trackers used in combination with social media within a physical activity intervention. METHODS The Raising Awareness of Physical Activity study was a 12-week physical activity intervention that combined a wearable activity tracker (Fitbit Flex) with supporting digital materials that were delivered using social media (Facebook). A total of 124 adolescents aged 13 to 14 years randomized to the intervention group (9 schools) participated in focus groups immediately post intervention. Focus groups explored adolescents’ perspectives of the intervention and were analyzed using pen profiles using a coding framework based on the tec and the social media platform, the effort required to use these technologies, as well as the issues concerning risks and compatibility, may have influenced overall engagement and technology acceptance. As wearable activity trackers and social media platforms can change rapidly, future research is needed to examine the factors that may influence the acceptance of specific forms of technology by using the technology acceptance model. TRIAL REGISTRATION Australian and New Zealand Clinical Trials Registry ACTRN12616000899448; https//www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370716. ©Mark D Drehlich, Michael Naraine, Katie Rowe, Samuel K Lai, Jo Salmon, Helen Brown, Harriet Koorts, Susie Macfarlane, Nicola D Ridgers. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 06.03.2020.