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BackgroundAlthough the incidence of breast cancer is lower in African-American women than in White women, African-American women have a decreased survival rate. The difference in survival rate may stem from poor endocrine therapy adherence, which increases breast cancer recurrence. Therefore, accessible and culturally sensitive interventions to increase endocrine therapy adherence are necessary. ObjectiveThe purpose of this concurrent convergent mixed methods study was to provide further data to guide the development of the proposed culturally sensitive mHealth app, STORY+ for African-American women with breast cancer. MethodsWe recruited 20 African-American women diagnosed with estrogen-positive breast cancer and currently prescribed endocrine therapy. We used a concurrent convergent data collection method to (1) assess the use of smartphones and computers related to health care and (2) identify foundational aspects to support endocrine therapy adherence for incorporation in a mobile health app. ResultsOverwhelmingly, the participants preferred using smartphones to using computers for health care. Communicating with health care providers and pharmacies was the most frequent health care use of smartphones, followed by exercise tracking, and accessing the patient portal. We identified 4 aspects of adherence to endocrine therapy and smartphone use for incorporation in app development. The factors that emerged from the integrated qualitative and quantitative data were (1) willingness to use, (2) side effects, (3) social connection, and (4) beliefs about endocrine therapy. ConclusionsFurther research is needed to develop a culturally sensitive app for African-American women with breast cancer to improve adherence to endocrine therapy. Our work strongly suggests that this population would use the app to connect with other African-American breast cancer survivors and manage endocrine therapy.

BackgroundMobile health (mHealth) apps are dramatically changing how patients and providers manage and monitor chronic health conditions, especially in the area of self-monitoring. African Americans have higher mortality rates from heart failure than other racial groups in the United States. Therefore, self-management of heart failure may improve health outcomes for African American patients. ObjectiveThe aim of the present study was to determine the feasibility of using an mHealth app, and explore the outcomes of quality of life, including self-care maintenance, management, and confidence, among African American patients managing their condition after discharge with a diagnosis of heart failure. MethodsPrior to development of the app, we conducted qualitative interviews with 7 African American patients diagnosed with heart failure, 3 African American patients diagnosed with cardiovascular disease, and 6 health care providers (cardiologists, nurse practitioners, and a geriatrician) who worked with heart failure patients. In addition, we asked 6 hospital chaplains to provide positive spiritual messages for the patients, since spirituality is an important coping method for many African Americans. These formative data were then used for creating a prototype of the app, named Healthy Heart. Specifically, the Healthy Heart app incorporated the following evidence-based features to promote self-management: one-way messages, journaling (ie, weight and symptoms), graphical display of data, and customized feedback (ie, clinical decision support) based on daily or weekly weight. The educational messages about heart failure self-management were derived from the teaching materials provided to the patients diagnosed with heart failure, and included information on diet, sleep, stress, and medication adherence. The information was condensed and simplified to be appropriate for text messages and to meet health literacy standards. Other messages were derived from interviews conducted during the formative stage of app development, including interviews with African American chaplains. Usability testing was conducted over a series of meetings between nurses, social workers, and computer engineers. A pilot one-group pretest-posttest design was employed with participants using the mHealth app for 4 weeks. Descriptive statistics were computed for each of the demographic variables, overall and subscales for Health Related Quality of Life Scale 14 (HQOL14) and subscales for the Self-Care of Heart Failure Index (SCHFI) Version 6 using frequencies for categorical measures and means with standard deviations for continuous measures. Baseline and postintervention comparisons were computed using the Fisher exact test for overall health and paired t tests for HQOL14 and SCHFI questionnaire subscales. ResultsA total of 12 African American participants (7 men, 5 women; aged 51-69 years) diagnosed with heart failure were recruited for the study. There was no significant increase in quality of life (P=.15), but clinically relevant changes in self-care maintenance, management, and confidence were observed. ConclusionsAn mHealth app to assist with the self-management of heart failure is feasible in patients with low literacy, low health literacy, and limited smartphone experience. Based on the clinically relevant changes observed in this feasibility study of the Healthy Heart app, further research should explore effectiveness in this vulnerable population.

Preterm infants have increased morbidity and mortality due to immature physiology and neonatal complications. Necrotizing enterocolitis (NEC) is a devastating gastrointestinal complication that affects morbidity and mortality in preterm infants. The authors present an adaptation of Neuman's systems model called the NEC systems model to explore intrinsic and extrinsic factors leading to NEC in preterm infants. The literature was searched for theoretical models to guide exploration of neonatal disease influenced by the environment. Neuman's Systems Model provides a holistic approach to care of the system, offering a foundation to develop frameworks to examine preterm infants in their environment with associated stressors. [ABSTRACT FROM AUTHOR]

To maintain their quality of life and avoid hospitalization and early mortality, patients with heart failure must recognize and respond to symptoms of exacerbation. A promising method for engaging patients in their self‐care is through mobile health applications (mHealth apps). However, for mHealth to have its greatest chance for improving patient outcomes, the app content must be readable, provide useful functions and be based in evidence. The study aimed to determine: (1) readability, (2) types of functions, and (3) linkage to authoritative sources of evidence for self‐care focused mHealth apps targeting heart failure patients that are available in the Apple and Google Play Stores. We systematically searched for mHealth apps targeting patients with heart failure in the Apple and Google Play Stores and applied selection criteria. Readability of randomly selected informational paragraphs were determined using Flesch–Kincaid grade level test tool in Microsoft Word. Ten mHealth apps met our criteria. Only one had a reading grade level at or below the recommended 6th grade reading level (average 9.35). The most common functions were tracking, clinical data feedback, and non‐data‐based reminders and alerts. Only three had statements that clearly linked the mHealth app content to trustworthy, evidence‐based sources. Only two had interoperability with the electronic health record and only one had a communication feature with clinicians. Future mHealth designs that are tailored to patients' literacy level and have advanced functions may hold greater potential for improving patient outcomes. [ABSTRACT FROM AUTHOR]

Research using mHealth apps has the potential to positively impact health care management and outcomes. However, choosing an appropriate mHealth app may be challenging for the health researcher. The author team used existing evaluation tools, checklists, and guidelines to assess selected mHealth apps to identify strengths, challenges, and potential gaps within existing evaluation tools. They identified specific evaluation tool components, questions, and items most effective in examining app content, usability, and features, including literacy demand and cultural appropriateness; technical information; practical aspects of app functionality; and evolving capabilities of mobile medical apps. Challenges included the subjective nature of the results, time required to complete the evaluation, lack of emphasis on evidence‐based content, and inadequate tool flexibility. Health researchers considering the integration of mobile apps into research will benefit from evaluation tools that assess both evidence‐based content and the ability of the mobile app to securely integrate with other digital technologies involved in patient care. Next steps will include the involvement of health care providers and professionals, including nurses a wide range of expertise, to develop an mHealth evaluation tool that focuses on identifying quality, evidence‐based mobile apps into patient outcomes research. [ABSTRACT FROM AUTHOR]

Objective: Our objective was to validate a novel irritant gas syndrome agent (IGSA) triage algorithm for use in an emergency department (ED). We assessed efficiency, accuracy, and precision of our IGSA triage algorithm based on signs/symptoms of actual patients., Design: After characterizing the signs/symptoms of an actual IGSA exposure event, we developed and validated the IGSA triage algorithm using a simulated computer exercise to compare the IGSA triage algorithm to the preferred hospital triage algorithm, the Emergency Severity Index (ESI)., Setting: This study was a simulated computer exercise using surveys developed in Research Electronic Data Capture software. Nurse volunteers simulated triaging 298 patients., Participants: Patient data included 146 patients treated during the disaster as well as 152 unexposed patients. Twenty-six nurse volunteers were assigned to triage the patients using one of the algorithms in the simulated computer exercise., Main Outcome Measure(s): The precision of the IGSA triage algorithm was 0.82 (confidence interval [CI] 0.78-0.85) and ESI 0.73 (CI 0.69-0.77). Weighted κ for ESI and IGSA accuracy for exposed patients was 0.32 (95% CI 0.26-0.37) and 0.81 (95% CI 0.77-0.85), respectively., Results: The IGSA triage algorithm was more accurate and precise than the ESI algorithm for triaging patients exposed to an irritant gas., Conclusions: This study validates the IGSA triage algorithm as the basis for the development of a prototype software application to quickly identify victims of a chemical disaster and triage patients efficiently and accurately with the potential to dramatically improve the processing of patients in EDs.