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a, Geranda EC Slager, Wiebren Zijlstra, Martin Stevens. Originally published in JMIR Rehabilitation and Assistive Technology (http//rehab.jmir.org), 27.04.2020.BACKGROUND Quality of life (QoL) is considered a key treatment outcome in bipolar disorder (BD) across research, clinical, and self-management contexts. Web-based assessment of patient-reported outcomes offer numerous pragmatic benefits but require validation to ensure measurement equivalency. A web-based version of the Quality of Life in Bipolar Disorder (QoL.BD) questionnaire was developed (QoL Tool). OBJECTIVE This study aimed to evaluate the psychometric properties of a web-based QoL self-report questionnaire for BD (QoL Tool). Key aims were to (1) characterize the QoL of the sample using the QoL Tool, (2) evaluate the internal consistency of the web-based measure, and (3) determine whether the factor structure of the original version of the QoL.BD instrument was replicated in the web-based instrument. METHODS Community-based participatory research methods were used to inform the development of a web-based adaptation of the QoL.BD instrument. Individuals with BD who registered for an account with the QoL ven Barnes, Colin Depp, CREST.BD, Erin Michalak. Originally published in JMIR Mental Health (http//mental.jmir.org), 27.04.2020.BACKGROUND The Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT) is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses the collective intelligence of users (ie, preferences and feedback) and demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors. OBJECTIVE The objective of this study was to describe and evaluate the use of PERSPeCT in African American people who smoke compared with white people who smoke. METHODS Using a quasi-experimental design, we compared African American people who smoke with a historical cohort of white people who smoke, who both received up to 30 emailed tailored messages over 65 days. People who smoke rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two grID) RR2-10.2196/jmir.6465. ©Jamie M Faro, Catherine S Nagawa, Jeroan A Allison, Stephenie C Lemon, Kathleen M Mazor, Thomas K Houston, Rajani S Sadasivam. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 27.04.2020.BACKGROUND Massive open online courses (MOOCs) have the potential to make a broader educational impact because many learners undertake these courses. Despite their reach, there is a lack of knowledge about which methods are used for evaluating these courses. OBJECTIVE The aim of this review was to identify current MOOC evaluation methods to inform future study designs. METHODS We systematically searched the following databases for studies published from January 2008 to October 2018 (1) Scopus, (2) Education Resources Information Center, (3) IEEE (Institute of Electrical and Electronic Engineers) Xplore, (4) PubMed, (5) Web of Science, (6) British Education Index, and (7) Google Scholar search engine. Two reviewers independently screened the abstracts and titles of the studies. Published studies in the English language that evaluated MOOCs were included. RK 24466 chemical structure The study design of the evaluations, the underlying motivation for the evaluation studies, data collection, and data analysis methods were quantitatively and iptive and inferential statistics, which were the top 2 preferred methods. In all, 26 studies with a cross-sectional design had a low-quality assessment, whereas RCTs and quasi-experimental studies received a high-quality assessment. CONCLUSIONS The MOOC evaluation data collection and data analysis methods should be determined carefully on the basis of the aim of the evaluation. The MOOC evaluations are subject to bias, which could be reduced using pre-MOOC measures for comparison or by controlling for confounding variables. Future MOOC evaluations should consider using more diverse data sources and data analysis methods. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.2196/12087. ©Abrar Alturkistani, Ching Lam, Kimberley Foley, Terese Stenfors, Elizabeth R Blum, Michelle Helena Van Velthoven, Edward Meinert. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 27.04.2020.BACKGROUND Generative participatory design (PD) may help in developing electronic health (eHealth) interventions. PD is characterized by the involvement of all stakeholders in creative activities. This is different from the traditional user-centered design, where users are less involved. When looking at PD from a research through design perspective, it is important to summarize the reasons for choosing a certain form of generative PD to further develop its methodology. However, the scientific literature is currently unclear about which forms of PD are used to develop eHealth and which arguments are used to substantiate the decision to use a certain form of generative PD. OBJECTIVE This study aimed to explore the reporting and substantiation of generative PD methodologies in empirical eHealth studies published in scientific journals to further develop PD methodology in the field of eHealth. METHODS A systematic literature review following the Cochrane guidelines was conducted in several databases (EMBASE, MEDLand the type of outcome measures adopted point to the involvement of PD principles. CONCLUSIONS Studies that have used a PD research methodology to develop eHealth primarily substantiate the choice of tools made and much less the use of stakeholders and outcome measures. ©Pieter Vandekerckhove, Marleen de Mul, Wichor M Bramer, Antoinette A de Bont. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 27.04.2020.BACKGROUND Objective measures of physical function in older adults are widely used to predict health outcomes such as disability, institutionalization, and mortality. App-based clinical tests allow users to assess their own physical function and have objective tracking of changes over time by use of their smartphones. Such tests can potentially guide interventions remotely and provide more detailed prognostic information about the participant's physical performance for the users, therapists, and other health care personnel. We developed 3 smartphone apps with instrumented versions of the Timed Up and Go (Self-TUG), tandem stance (Self-Tandem), and Five Times Sit-to-Stand (Self-STS) tests. OBJECTIVE This study aimed to test the usability of 3 smartphone app-based self-tests of physical function using an iterative design. METHODS The apps were tested in 3 iterations the first (n=189) and second (n=134) in a lab setting and the third (n=20) in a separate home-based study. Participants were healthy adults between 60 and 80 years of age.