Browsing by Author "McDaniel, Anna M."
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Item Assessing the Potential Utility of a Virtual and Mixed/Augmented Reality System to Assist in Stroke RehabilitationLeventhal, Jeremy; McDaniel, Anna M.Stroke is the number one cause of disability in the United States. This thesis summarizes current techniques and technologies for stroke rehabilitation and in addition, describes a revolutionary new concept and rehabilitation system, Visually Directed Intention (VDI), created by Dr. Jill Bolte Taylor (Indiana University). The purpose of this research is to determine the feasibility and potential of her system through comparative research and expert opinion. Dr. Taylor‟s rehabilitation system harnesses several technologies such as mixed reality, biofeedback, and game-like environments. Key concepts such as visualization, intention, motivation and repetition are also pivotal to her ideology. Specifically the system uses biofeedback, viewed through a mixed reality headset to motivate a user to utilize nerves and muscles he/she may have lost through experiencing a stroke. In order to properly identify and analyze current methods used in stroke rehabilitation, several subject matter experts (SME) at the University of Chicago‟s Rehabilitation Institute of Chicago (RIC) were interviewed. The SME provided useful critique on current stroke rehabilitation techniques, technologies and Dr. Taylor‟s innovative concept. Through a general qualitative interview, examining the SMEs research and actually experimenting with some of their technologies, meaningful insight into expert opinions on stroke rehabilitation technologies was obtained. After several detailed interviews at the RIC, the experts agreed that VDI is noble concept and has great potential. Although they had some specific comments about how to properly utilize the technologies involved, overall they believe the system encompasses Assessing the Potential Utility for a Mixed Reality System (vii) several exciting and motivating features that will significantly improve the rehabilitation process.Item Automated Telephone Monitoring for Relapse Risk among Recent Quitters Enrolled in Quitline Services(Office of the Vice Chancellor for Research, 2011-04-08) McDaniel, Anna M.; Carlini, Beatriz H.; Stratton, Renée M.; Cerutti, Barbara; Monahan, Patrick O.; Stump, Timothy E.; Kauffman, Ross M.; Zbikowski, Susan M.This study is part of a randomized controlled trial to test the efficacy of interactive voice response (IVR) technology for enhancing existing quitline services (Free & Clear’s Quit for Life® program) to prevent smoking relapse and achieve abstinence. The IVR system screens for six indicators of risk for relapse including smoking lapse, physical withdrawal symptoms, depressive symptoms, perceived stress, decreased self-efficacy for quitting, and decreased motivation to quit. Participants can screen positive on any one or more risks, resulting in a rollover call to a telephone counselor. There are two intervention arms that differ in timing and frequency of IVR screening. In the Technology Enhanced Quitline arm (TEQ-10), 10 automated calls are placed at decreasing frequency for 8 weeks post-quit (twice a week for the first two weeks, then weekly). The High Intensity Technology-Enhanced Quitline arm (TEQ-20) includes 20 IVR calls (daily for the first 2 weeks, then weekly). This preliminary analysis includes IVR data collected on calls from 4/12/2010 to 10/31/2010. 2620 calls were made to 98 participants in the two intervention arms, TEQ-10 (n=44) and TEQ-20 (n=54). The two arms did not differ significantly on demographics or comorbid conditions. Three outcomes were analyzed: completed screening assessments, positive screen for relapse risk, and smoking lapse (i.e., smoking even a puff since the last call). 136 of the 736 (18.5%) completed assessments were positive for relapse risk: 66 for smoking lapse (49%), 42 craving (31%), 32 depressive symptoms (24%), 27 lack of confidence (20%), 8 stress (6%), and 8 lack of motivation (6%). Logistic regression models (adjusted for age and gender), with GEE estimation to account for withinperson correlation, showed that compared to the TEQ-10 study group, participants in the TEQ-20 study group were more likely to complete assessments (OR=1.7; 95% CI=1.2-2.4), less likely to screen positive for relapse risk (OR=.3; 95% CI=.2-.6), and less likely to have smoked (OR=.2; 95% CI=.09-.4). These results indicate that frequent IVR monitoring during the immediate postquit period may have a positive effect on relapse risk.Item Clinical Educators' Adoption of Socioculturally-Based Teaching Strategies(2009-06-24T12:47:13Z) Phillips, Janet Martha; Ironside, Pamela M.; McDaniel, Anna M.; Halstead, Judith A.; Merrill, Henry S.Nursing education is faced with addressing the challenge of educational reform as a result of the rapid changes in the complexity of health care delivery systems, increased technology and biomedical knowledge, a shortage in nursing faculty, and increased enrollment in schools of nursing. Although national nursing organizations have called for reform and innovation in nursing education little is known about the factors that are related to educators’ adoption of such changes. The purpose of this descriptive, exploratory, correlational, survey study was to explore the adoption of socioculturally-based teaching strategies (SCBTS) by examining the following variables in relation to their adoption using Everett Rogers’ diffusion of innovations model: (a) clinical nurse educators’ perceived characteristics of SCBTS, (b) clinical nurse educators’ perceived organizational support for innovation, and (c) selected demographic characteristics. Minimal research has been conducted regarding the factors related to clinical nurse educators’ adoption of SCBTS, which may better prepare nurse graduates for today’s health care system. Findings from this study suggest that adoption is not straightforward, but the perceived characteristics of teaching strategies play an important role in the clinical nurse educator’s decision to adopt or not adopt SCBTS. Rogers’ model was partially supported based on the findings that clinical nurse educators were more likely to adopt a teaching strategy if it was perceived to be advantageous, compatible, and not too complex. On the other hand, clinical nurse educators were more likely not to adopt teaching strategies that they must “try out” or that must be observable by others, which was not supportive of Rogers’ model. Adopters of SCBTS were more experienced clinical educators who felt supported by their academic organizations in terms of innovation; however organizational support for innovations was not associated with adoption of the teaching strategies. Holding a certificate in a nursing specialty, the type of program in which the educator taught, and the age of the educator were not associated with the adoption of SCBTS. Future research using Rogers’ model or other appropriate models is called for to further explore the adoption of SCBTS by clinical nurse educators.Item The effect of shared dynamic understanding on willingness to contribute information: design and analysis of a mega-collaborative interface(2016-05-06) Newlon, Christine Mae; Bolchini, Davide P.; Faiola, Anthony; McDaniel, Anna M.; MacDorman, Karl F.Collaborative helping via social networking conversation threads can pose serious challenges in emergency situations. Interfaces that support complex group interaction and sense-making can help. This research applies human-computer interaction (HCI), computer-supported cooperative work (CSCW), and collaboration engineering in developing an interactive design, the Mega-Collaboration Tool (MCT). The goal is to reduce the cognitive load of a group’s growing mental model, thus increasing the general public’s ability to organize spontaneous collaborative helping. The specific aims of this research include understanding the dynamics of mental model negotiation and determining whether MCT can assist the group’s sense-making ability without increasing net cognitive load. The proposed HCI theory is that interfaces supporting collaborative cognition motivate contribution and reduce information bias, thus increasing the information shared. These research questions are addressed: 1. Does MCT support better collaborative cognition? 2. Does increasing the size of the shared data repository increase the amount of information shared? 3. Does this happen because group members experience 1) a greater sense of strategic commitment to the knowledge structure, 2) increased intrinsic motivation to contribute, and 3) reduced resistance to sharing information? These questions were affirmed to varying degrees, giving insight into the collaborative process. Greater content did not motive group members directly; instead, half of their motivation came from awareness of their contribution’s relevance. Greater content and organization improved this awareness, and also encouraged sharing through increased enthusiasm and reduced bias. Increased commitment was a result of this process, rather than a cause. Also, MCT increased collaborative cognition but was significantly hampered by Internet performance. This challenge indicates MCT’s system components should be redesigned to allow asynchronous interaction. These results should contribute to the development of MCT, other collaboration engineering applications, and HCI and information science theory.Item Gender and managerial competence: a comparison of male and female first-line nurse managers in Indonesia(Frontiers Media, 2021) Gunawan, Joko; Aungsuroch, Yupin; Fisher, Mary L.; McDaniel, Anna M.; School of NursingObjective: First-line nurse managers are more likely to work according to gender beliefs and stereotypes, which may affect their managerial competence. This study is aimed at comparing managerial competence of male and female first-line nurse managers in public hospitals in Indonesia. Methods: This study employed a descriptive comparative approach with a cross-sectional survey with a total of 256 participants selected from 18 public hospitals. To measure managerial competence, the managerial competence scale for Indonesian first-line nurse managers was used. Data were analyzed using descriptive analyses using mean, standard deviation, and Independent t-test. Results: Managerial competence of male and female first-line nurse managers was not significantly different (P = 0.555). Female nurse managers descriptively reported/received higher ranking in facilitating spiritual nursing care, managing self, staffing and professional development, utilizing informatics, and applying quality care improvement. Male nurse managers reported higher in leadership and financial management. Conclusions: Female and male first-line nurse managers should be treated equally for leadership and managerial development.Item Hypothesis Generation Using Network Structures on Community Health Center Cancer-Screening Performance(Elsevier, 2015-10) Carney, Timothy Jay; Morgan, Geoffrey P.; Jones, Josette; McDaniel, Anna M.; Weaver, Michael; Weiner, Bryan; Haggstrom, David A.; BioHealth Informatics, School of Informatics and ComputingRESEARCH OBJECTIVES: Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. METHODS: To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. RESULTS: This virtual experiment revealed that patterns of overall network symmetry, agent cohesion, and connectedness varied by community health center performance level. Visual assessment of both the agent-to-agent knowledge sharing network and agent-to-resource knowledge use network diagrams demonstrated that community health centers labeled as high performers typically showed higher levels of collaboration and cohesiveness among agent classes, faster knowledge-absorption rates, and fewer agents that were unconnected to key knowledge resources. Conclusions and research implications: Using the point-in-time survey data outlining community health center cancer-screening practices, our computational model successfully distinguished between high and low performers. Results indicated that high-performance environments displayed distinctive network characteristics in patterns of interaction among agents, as well as in the access and utilization of key knowledge resources. Our study demonstrated how non-network-specific data obtained from a point-in-time survey can be employed to forecast community health center performance over time, thereby enhancing the sustainability of long-term strategic-improvement efforts. Our results revealed a strategic profile for community health center cancer-screening improvement via simulation over a projected 10-year period. The use of computational modeling allows additional inferential knowledge to be drawn from existing data when examining organizational performance in increasingly complex environments.Item Interactive Communication Technology and Processing of Behavioral Health Change Messages(2005-06) McCracken-Stratton, Renee Marie; McDaniel, Anna M.Consumer processing of interactive communication technology (ICT) messages is an understudied area. It is incumbent upon the Informatics community to partner with various health content and population domain experts to design healthcare information products that increase reach, improve awareness, and meet consumer needs. This research is a secondary analysis of a larger study to develop and pilot test an interactive, multimedia computer program as an adjunct to usual clinical care in an effort to reduce smoking in low-income rural Indiana communities. The objective of this research was to measure the degree of consumer processing of health behavioral change messages delivered by ICT. The sample size for this research was 30 subjects. Degree of consumer message processing was high (mean processing score=80.5, SD=6.837). Instruments to assess the number of actionable cessation responses (ACRs) and cognitive changes were completed at the 3-month follow-up. A relationship was observed between degree of message processing and making a quit attempt (rbis=.384, p=.044). Knowledge scores improved over baseline measures (t=3.123, p=.004). These results suggest that ICT is feasible for promoting the processing of cessation messages and increasing consideration of ACRs in low-income rural Indiana populations.Item Knowledge Management For Quality Improvement of Service Methods - A Case Study of a Laboratory InstrumentNierste, Michael K.; McDaniel, Anna M.A systematic method can extrapolate tacit knowledge (hidden or subjective knowledge) so that it can become objective and discernable. This process focused on discovering causes of failures by extricating data from medical equipment service software cases closed by telephone by field service personnel. Their responses to observed failures were compared to troubleshooting guides in use by telephone support personnel to find new processes that would increase effectiveness of telephone support staff. We asked “What are indicators of device failure reported in technical support calls?” and then “What factors contribute to user reported device failures identified by callers to technical support?” A series of interviews with veteran personnel were used to validate responses from the “phone closed” cases along with ideas pulled from a review of documentation. Analysis of one hundred seventy three cases yielded over five hundred recommendations to make the telephone support personnel’s responses more accurate, consistent and reliable.Item Natural Language Processing and Extracting Information From Medical Reports(2006-06-29T19:24:21Z) Pfeiffer II, Richard D.; McDaniel, Anna M.The purpose of this study is to examine the current use of natural language processing for extracting meaningful data from free text in medical reports. The use of natural language processing has been used to process information from various genres. To evaluate the use of natural language processing, a synthesized review of primary research papers specific to natural language processing and extracting data from medical reports. A three phased approach is used to describe the process of gathering the final metrics for validating the use of natural language processing. The main purpose of any NLP is to extract or understand human language and to process it into meaning for a specified area of interest or end-user. There are three types of approaches: symbolic, statistical, and connectionist. There are identified problems with natural language processing and the different approaches. Problems noted about natural language processing in the research are: acquisition, coverage, robustness, and extensibility. Metrics were gathered from primary research papers to evaluate the success of the natural language processors. Recall average of the four papers was 85%. Precision average of five papers was 87.7%. Accuracy average was 97%. Sensitivity average was 84%, while specificity was 97.4%. Based on the results of the primary research there was no definitive way to validate one NLP approach as an industry standard The research reviewed it is clear that there has been at least limited success with information extraction from free text with use of natural language processing. It is important to understand the continuum of data, information, and knowledge in the previous and future research of natural language processing. In the industry of health informatics this is a technology necessary for improving healthcare and research.Item An Organizational Informatics Analysis of Colorectal, Breast, and Cervical Cancer Screening Clinical Decision Support and Information Systems within Community Health Centers(2013-03-06) Carney, Timothy Jay; Jones, Josette F.; Haggstrom, David A.; McDaniel, Anna M.; Weaver, Michael; Palakal, Mathew J.A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services Research, and (4) Organizational Change/Theory. The study design builds upon the constructs of a conceptual framework developed by Jane Zapka, namely, (1) organizational and/or practice settings, (2) provider characteristics, and (3) patient population characteristics. These constructs have been operationalized as measures in a 2005 HRSA/NCI Health Disparities Cancer Collaborative inventory of 44 community health centers. The first, statistical models will use: sequential, multivariable regression models to test for the organizational determinants that may account for the presence and intensity-of-use of clinical decision support (CDS) and information systems (IS) within community health centers for use in colorectal, breast, and cervical cancer screening. A subsequent test will assess the impact of CDS/IS on provider reported cancer screening improvement rates. The second, computational models will use a multi-agent model of network evolution called CONSTRUCT® to identify the agents, tasks, knowledge, groups, and beliefs associated with cancer screening practices and CDS/IS use to inform both CDS/IS implementation and cancer screening intervention strategies. This virtual experiment will facilitate hypothesis-generation through computer simulation exercises. The outcome of this research will be to identify barriers and facilitators to improving community health center facility-level cancer screening performance using CDS/IS as an agent of change. Stakeholders for this work include both national and local community health center IT leadership, as well as clinical managers deploying IT strategies to improve cancer screening among vulnerable patient populations.