User-Centered Mobile Applications for Stroke Survivors (MAPPS): A Mixed-Methods Study of Patient Preferences.

OBJECTIVE: Investigate stroke survivors' (SS) preferences for a hypothetical mHealth app for post-stroke care and to study the influence of demographic variables on these preferences. DESIGN: Mixed-methods, sequential, observational study. SETTING: Focus groups (phase 1) were conducted to identify SS perceptions and knowledge of mHealth applications (apps). Using grounded theory approach, recurring themes were identified. A multiple-choice questionnaire of 5 desired app features was generated using these themes and mailed to SS (national survey, phase 2). SS' demographics and perceived usefulness (yes/no) for each feature were recorded. In-person usability testing (phase 3) was conducted to identify areas of improvement in user interfaces of existing apps. Summative telephone interviews (phase 4) were conducted for final impressions supplementary to national survey. PARTICIPANTS: SS aged >18 years recruited from study hospital, national stroke association database, stroke support and advocacy groups. Non-English speakers and those unable to communicate were excluded. INTERVENTIONS: None. MAIN OUTCOME MEASURES: (1) Percentage of SS (phase 2) identifying proposed app features to be useful. (2) Influence of age, sex, race, education, and time since stroke on perceived usefulness. RESULTS: Ninety-six SS participated in focus groups. High cost, complexity, and lack of technical support were identified as barriers to adoption of mHealth apps. In the national survey (n=1194), ability to track fitness and diet (84%) and communication (70%) were the most and least useful features, respectively. Perceived usefulness was higher among younger SS (P<.001 to .006) and SS of color (African American and Hispanic) (ORs 1.73-4.41). Simple design and accommodation for neurologic deficits were main recommendations from usability testing. CONCLUSIONS: SS are willing to adopt mHealth apps that are free of cost and provide technical support. Apps for SS should perform multiple tasks and be of simple design. Greater interest for the app's features among SS of color may provide opportunities to address health inequities.

Seven-Year Experience From the National Institute of Neurological Disorders and Stroke-Supported Network for Excellence in Neuroscience Clinical Trials.

Importance: One major advantage of developing large, federally funded networks for clinical research in neurology is the ability to have a trial-ready network that can efficiently conduct scientifically rigorous projects to improve the health of people with neurologic disorders. Observations: National Institute of Neurological Disorders and Stroke Network for Excellence in Neuroscience Clinical Trials (NeuroNEXT) was established in 2011 and renewed in 2018 with the goal of being an efficient network to test between 5 and 7 promising new agents in phase II clinical trials. A clinical coordinating center, data coordinating center, and 25 sites were competitively chosen. Common infrastructure was developed to accelerate timelines for clinical trials, including central institutional review board (a first for the National Institute of Neurological Disorders and Stroke), master clinical trial agreements, the use of common data elements, and experienced research sites and coordination centers. During the first 7 years, the network exceeded the goal of conducting 5 to 7 studies, with 9 funded. High interest was evident by receipt of 148 initial applications for potential studies in various neurologic disorders. Across the first 8 studies (the ninth study was funded at end of initial funding period), the central institutional review board approved the initial protocol in a mean (SD) of 59 (21) days, and additional sites were added a mean (SD) of 22 (18) days after submission. The median time from central institutional review board approval to first site activation was 47.5 days (mean, 102.1; range, 1-282) and from first site activation to first participant consent was 27 days (mean, 37.5; range, 0-96). The median time for database readiness was 3.5 months (mean, 4.0; range, 0-8) from funding receipt. In the 4 completed studies, enrollment met or exceeded expectations with 96% overall data accuracy across all sites. Nine peer-reviewed manuscripts were published, and 22 oral presentations or posters and 9 invited presentations were given at regional, national, and international meetings. Conclusions and Relevance: NeuroNEXT initiated 8 studies, successfully enrolled participants at or ahead of schedule, collected high-quality data, published primary results in high-impact journals, and provided mentorship, expert statistical, and trial management support to several new investigators. Partnerships were successfully created between government, academia, industry, foundations, and patient advocacy groups. Clinical trial consortia can efficiently and successfully address a range of important neurologic research and therapeutic questions.

Medical Mobile Applications for Stroke Survivors and Caregivers.

BACKGROUND: Recent studies estimate nearly half of the US population can access mobile medical applications (apps) on their smartphones. The are no systematic data available on apps focused on stroke survivors/caregivers. OBJECTIVE: To identify apps (a) designed for stroke survivors/caregivers, (b) dealing with a modifiable stroke risk factor (SRF), or (c) were developed for other purposes but could potentially be used by stroke survivors/caregivers. METHODS: A systematic review of the medical apps in the US Apple iTunes store was conducted between August 2013 and January 2016 using 18 predefined inclusion/exclusion criteria. SRFs considered were: diabetes, hypertension, smoking, obesity, atrial fibrillation, and dyslipidemia. RESULTS: Out of 30,132 medical apps available, 843 (2.7%) eligible apps were identified. Of these apps, (n = 74, 8.7%) apps were specifically designed for stroke survivors/caregivers use and provided the following services: language/speech therapy (n = 28, 37%), communication with aphasic patients (n = 19, 25%), stroke risk calculation (n = 11, 14%), assistance in spotting an acute stroke (n = 8, 10%), detection of atrial fibrillation (n = 3, 4%), direction to nearby emergency room (n = 3, 4%), physical rehabilitation (n = 3, 4%), direction to the nearest certified stroke center (n = 1, < 2%), and visual attention therapy (n = 1, <2%). 769 apps identified that were developed for purposes other than stroke. Of these, the majority (n = 526, 68%) addressed SRFs. CONCLUSIONS: Over 70 medical apps exist to specifically support stroke survivors/caregivers and primarily targeted language and communication difficulties. Apps encompassing most stroke survivor/caregiver needs could be developed and tested to ensure the issues faced by these populations are being adequately addressed.

Ischemic Stroke Predictors in Patients Presenting with Dizziness, Imbalance, and Vertigo.

OBJECTS: To identify predictors of acute ischemic stroke (AIS) among patients presenting to the Emergency Department (ED) with dizziness, imbalance, or vertigo (DIV) based on demographic and clinical characteristics. METHODS: We identified patients admitted to the hospital after presenting to the ED with DIV from the Statewide Planning and Research Cooperative System database of New York from 2010 to 2014. Demographic and clinical characteristics were systematically collected. Multivariable logistic regression was used to determine predictors of a discharge diagnosis of AIS. RESULTS: Among 77,993 patients with DIV, 3857 (4.9%) had a discharge diagnosis of AIS. Admission presentation of imbalance, African-American race, history of hypertension, diabetes mellitus, hypercholesterolemia, tobacco use, atrial fibrillation, and prior AIS due to extracranial artery atherosclerosis were each positively associated with an AIS diagnosis independently. Factors negatively associated with an AIS discharge diagnosis included: admission presentation of vertigo, female sex, age > 81, history of anemia, coronary artery disease, asthma, depressive disorders, and anxiety disorders. CONCLUSIONS: Multiple potential positive and negative predictive AIS risk factors were identified. Combining with currently available centrally-caused dizziness prediction tools, these newly identified factors could provide more accurate AIS risk stratifying method for DIV patients.

Impact of mental health training on village health workers regarding clinical depression in rural India.

Village health worker (VHW) programs are known to be effective means of promoting health of communities. Comprehensive rural health project in India recently trained VHWs to identify, refer, and help people with mental health issues. This study evaluated knowledge, attitude, and behavior of VHWs regarding depression. Cluster sampling was used including all 36 VHWs trained in mental health. Among these, 24 were available and willing to participate in the study. Five FGDs were conducted among 24 VHWs, and the results were analyzed qualitatively. Four out of five groups were able to diagnose the presented case correctly as depression. VHWs were able to identify many symptoms and to suggest management options for depression. They showed supportive and empathetic attitudes towards depressed patients. VHWs are likely to be useful at identifying and assisting people with depression in the communities with lack of adequate resources provided they receive ongoing training and supervision.