Sunmoo Yoon

A Practical Approach for Content Mining of Tweets

Use of data generated through social media for health studies is gradually increasing. Twitter is a short-text message system developed 6 years ago, now with more than 100 million users generating over 300 million Tweets every day. Twitter may be used to gain real-world insights to promote healthy behaviors. The purposes of this paper are to describe a practical approach to analyzing Tweet contents and to illustrate an application of the approach to the topic of physical activity. The approach includes five steps: (1) selecting keywords to gather an initial set of Tweets to analyze; (2) importing data; (3) preparing data; (4) analyzing data (topic, sentiment, and ecologic context); and (5) interpreting data. The steps are implemented using tools that are publically available and free of charge and designed for use by researchers with limited programming skills. Content mining of Tweets can contribute to addressing challenges in health behavior research.

Using social network analysis to examine collaborative relationships among PhD and DNP students and faculty in a research-intensive university school of nursing.

The nursing profession has seen a dramatic rise in the number of schools offering both DNP and PhD nursing programs. Information is limited on the impact of this parallel approach in doctoral education on the quality and scope of scholarly interactions or institutional culture.The authors studied collaboration characteristics across the DNP and PhD programs of a research-intensive university school of nursing, before and after programmatic enhancements. An IRB-approved online survey was delivered to faculty and students of both programs at baseline and one year after curricular changes. Response rates were 70% and 74%, respectively. The responses were analyzed by using social network analysis and descriptive statistics to characterize the number and strength of connections between and within student groups, and between students and faculty. At baseline, the flow of communication was centralized primarily through faculty. At Time 2, density of links between students increased and network centralization decreased, suggesting more distributed communication. This nonlinear quantitative approach may be a useful addition to the evaluation strategies for doctoral education initiatives.

Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research.

Introduction: To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research data warehouse (RDW) by linking electronic clinical data (ECD) from New York Presbyterian Hospital’s clinical data warehouse with ECD from ambulatory care, long-term care, and home health settings and the WICER community health survey (CHS). The purposes of the research were to identify areas of overlap between the WICER CHS and two other surveys that include health behavior data (the Behavioral Risk Factor Surveillance System (BRFSS) Survey and the New York City Community Health Survey (NYC CHS)) and to identify gaps in the current WICER RDW that have the potential to affect patient-centered CER. Methods: We compared items across the three surveys at the item and conceptual levels. We also compared WICER RDW (ECD and WICER CHS), BRFSS, and NYC CHS to the County Health Ranking framework. Results: We found that 22 percent of WICER items were exact matches with BRFSS and that there were no exact matches between WICER CHS and NYC CHS items not also contained in BRFSS. Conclusions: The results suggest that BRFSS and, to a lesser extent, NYC CHS have the potential to serve as population comparisons for WICER CHS for some health behavior-related data and thus may be particularly useful for considering the generalizability of CER study findings. Except for one measure related to health behavior (motor vehicle crash deaths), the WICER RDW’s comprehensive coverage supports the mortality, morbidity, and clinical care measures specified in the County Health Ranking framework but is deficient in terms of some socioeconomic factors and descriptions of the physical environment as captured in BRFSS. Linkage of these data in the WICER RDW through geocoding can potentially facilitate patient-centered CER that integrates important socioeconomic and physical environment influences on health outcomes. The research methods and findings may be relevant to others interested in either integrating health behavior data into RDWs to support patient-centered CER or conducting population-level comparisons.

Digital divide and information needs for improving family support among the poor and underserved

Despite of its emotional benefits, communication with family members who live abroad can present a large financial burden for low-income foreign-born individuals. The aims of this study were (1) to explore the current technologies available for low-cost communication with family living abroad and (2) to assess the level of awareness and use of low-cost technologies for family communication as well as related information needs among low-income foreign-born individuals. This mixed-methods study included an environmental scan, survey, and focus groups with low-income foreign-born individuals living in East Harlem in New York City. Low-income individuals who have family members living abroad face financial stress with complicated technology choices for communication with family living abroad and they have many information needs. They would welcome interactive and convenient educational tools that (1) build skills for utilization of various technologies and (2) provide decision support to simplify choosing among the vast array of available communication options.

Usability testing of a computerized communication tool in a diverse urban pediatric population.

Background: Developed in Norway, Sisom is an interactive, rigorously tested, computerized, communication tool designed to help children with cancer express their perceived symptoms/problems. Children travel virtually from island to island rating their symptoms/problems. While Sisom has been found to significantly improve communication in patient consultations in Norway, usability testing is warranted with US children prior to further use in research studies. Objective: The objective of this study was to determine the usability of Sisom in a sample of English- and Spanish-speaking children in an urban US community. Methods: A mixed-methods usability study was conducted with a purposive sample of healthy children and children with cancer. Semistructured interviews were used to assess healthy children’s symptom recognition. Children with cancer completed 8 usability tasks captured with Morae 3.3 software. Data were downloaded, transcribed, and analyzed descriptively. Results: Four healthy children and 8 children with cancer participated. Of the 44 symptoms assessed, healthy children recognized 15 (34%) pictorial symptoms immediately or indicated 13 (30%) pictures were good representations of the symptom. Six children with cancer completed all tasks. All children navigated successfully from one island to the next, ranking their symptom/problem severity, clicking the magnifying glass for help, or asking the researcher for assistance. All children were satisfied with the aesthetics and expressed an interest in using Sisom to communicate their symptoms/problems. Conclusions: A few minor suggestions for improvement and adjustment may optimize the use of Sisom for US children. Implications for Practice: Sisom may help clinicians overcome challenges assessing children’s complex symptoms/problems in a child-friendly manner.

Linguistic Validation of an Interactive Communication Tool to Help French-Speaking Children Express Their Cancer Symptoms:

Sisom is an interactive tool designed to help children communicate their cancer symptoms. Important design issues relevant to other cancer populations remain unexplored. This single-site, descriptive, qualitative study was conducted to linguistically validate Sisom with a group of French-speaking children with cancer, their parents, and health care professionals. The linguistic validation process included 6 steps: (1) forward translation, (2) backward translation, (3) patient testing, (4) production of a Sisom French version, (5) patient testing this version, and (6) production of the final Sisom French prototype. Five health care professionals and 10 children and their parents participated in the study. Health care professionals oversaw the translation process providing clinically meaningful suggestions. Two rounds of patient testing, which included parental participation, resulted in the following themes: (1) comprehension, (2) suggestions for improving the translations, (3) usability, (4) parental engagement, and (5) overall impression. Overall, Sisom was well received by participants who were forthcoming with input and suggestions for improving the French translations. Our proposed methodology may be replicated for the linguistic validation of other e-health tools.

Refining a self-assessment of informatics competency scale using Mokken scaling analysis

Abstract Healthcare environments are increasingly implementing health information technology (HIT) and those from various professions must be competent to use HIT in meaningful ways. In addition, HIT has been shown to enable interprofessional approaches to health care. The purpose of this article is to describe the refinement of the Self-Assessment of Nursing Informatics Competencies Scale (SANICS) using analytic techniques based upon item response theory (IRT) and discuss its relevance to interprofessional education and practice. In a sample of 604 nursing students, the 93-item version of SANICS was examined using non-parametric IRT. The iterative modeling procedure included 31 steps comprising: (1) assessing scalability, (2) assessing monotonicity, (3) assessing invariant item ordering, and (4) expert input. SANICS was reduced to an 18-item hierarchical scale with excellent reliability. Fundamental skills for team functioning and shared decision making among team members (e.g. “using monitoring systems appropriately,” “describing general systems to support clinical care”) had the highest level of difficulty, and “demonstrating basic technology skills” had the lowest difficulty level. Most items reflect informatics competencies relevant to all health professionals. Further, the approaches can be applied to construct a new hierarchical scale or refine an existing scale related to informatics attitudes or competencies for various health professions.

Comparison of Different Algorithms for Sentiment Analysis: Psychological Stress Notes

To visualize and compare three text analysis algorithms of sentiment (AFINN, Bing, Syuzhet), applied to 1549 ecologically assessed self-report stress notes obtained by smartphone, in order to gain insights about stress measurement and management.

A Data Mining Approach for Examining Predictors of Physical Activity Among Urban Older Adults.

The current study applied innovative data mining techniques to a community survey dataset to develop prediction models for two aspects of physical activity (i.e., active transport and screen time) in a sample of urban, primarily Hispanic, older adults (N=2,514). Main predictors for active transport (accuracy=69.29%, precision=0.67, recall=0.69) were immigrant status, high level of anxiety, having a place for physical activity, and willingness to make time for physical activity. The main predictors for screen time (accuracy=63.13%, precision=0.60, recall=0.63) were willingness to make time for exercise, having a place for exercise, age, and availability of family support to access health information on the Internet. Data mining methods were useful to identify intervention targets and inform design of customized interventions.