Wendy Miller
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Utilizing Innovative Methods to inform Patient-Centered Interventions in People with Epilepsy
All chronic diseases, including epilepsy, require self-management on the part of the patient. Self-management in epilepsy is particularly complex, and influences important outcomes such as social functioning and quality of life. Dr. Wendy Miller’s research focuses on finding new ways to improve the daily self-management and quality of life for people living with epilepsy. For example, Dr. Miller created the Life Changes in Epilepsy Scale that is being used locally, nationally, and internationally by healthcare providers to determine areas in the lives of their patients that need intervention. Also, through her collaboration with other researchers, the American Epilepsy Society updated its guidelines for discussing Sudden Unexpected Death in Epilepsy (SUDEP) with patients with epilepsy and/or their parents/caregivers. Prior to this achievement, accurate information about SUDEP, which is a leading cause of death for people with epilepsy, was not discussed with them.
More recently, Dr. Miller worked with other researchers to capture patient concerns using Big Data machine learning methods. This technology provided a plethora of data that was used to find quality of life issues that had not previously been addressed. Consequently, Dr. Miller created myAURA, a web-based intervention that uses machine learning and artificial intelligence to provide users with individualized, theory-based self-management enhancing content that does not require a human interventionist. This platform has been used during the COVID-19 pandemic to help patients self-manage their epilepsy and to also inform researchers about the ways in which the pandemic has affected self-management of chronic diseases.
Dr. Miller’s work to generate new knowledge and create better interventions for people with epilepsy is another great example of how IUPUI’s faculty members are TRANSLATING their RESEARCH INTO PRACTICE.
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Item Epilepsy Self-Management in Older Adults: A Qualitative Study(2012-03-19) Miller, Wendy Renee; Buelow, Janice; Bakas, Tamilyn; Habermann, Barbara; Unverzagt, FrederickEpilepsy is the most common chronic neurological condition in the United States, and it is incurable. Those who suffer from it must engage in both collaborative and independent management of their condition for the remainder of their lives. The treatment and care of those with epilepsy must therefore include not only medical interventions, which alone cannot cure the disorder or prevent the disability associated with it, but must also prepare persons for and facilitate their independent management—self-management—of the disorder. Self-management is a process that affects important outcomes including resource utilization, mortality, and quality of life. In the United States, those age 60 years and older have the highest incidence of new-onset epilepsy. Despite the high incidence of epilepsy in this population, coupled with the knowledge that self-management affects important outcomes, a thorough search of the literature suggests that self-management experiences of older adults diagnosed with epilepsy late in life have not been investigated. The purpose of the study was to examine, using a qualitative descriptive design, the self-management experiences of older adults diagnosed with epilepsy at or after age 60. Semi-structured interviews were used to generate data. A total of 20 older adults participated. Major findings indicate that older adults in the sample, and particularly the women, experienced a delay in receiving an epilepsy diagnosis. These older adults experienced multiple problems and life changes since diagnosis—some of which are unique to this population and many of which are amenable to intervention. These older adults devise and execute a variety of management strategies, within a system, that are classified as disease/treatment-focused and problem/life changes-focused. These strategies further are categorized as proactive or reactive, with proactive strategies being pre-planned and effective, and reactive strategies being unplanned and less effective. Knowledge generated from this study reveals the problems experienced by older adults with epilepsy, as well as their management needs. These findings will inform future studies, the aim of which will be to investigate more thoroughly these problems and needs and, ultimately, to inform interventions aimed at resolving this population’s problems and concerns while also improving outcomes.Item Goal Development in Parents of Children with Epilepsy and Learning Disorders(Office of the Vice Chancellor for Research, 2014-04-11) Keener, Lindsey; Miller, Wendy; Buelow, Janice M.Epilepsy is the most common, chronic neurological condition in children, impacting 2.4 children per 1,000. Caregivers of children with epilepsy and learning disorders are affected by many confounding factors including complex drug regimens, navigating a complex healthcare system, the uncertainty of their child’s future and the challenge of creating an effective educational program in conjunction with their child’s school. Parents of children with epilepsy and learning disorders participated in the Creating Avenues for Parent Partnerships (CAPP) program. The original study was an experimental design in which parents were randomly placed in an intervention group or a wait list control group. Each group consisted of 25 parents, with a total of 50 parents participating in the pilot test of CAPP. One of the instruments that the parents completed throughout the duration of this interventional program was the Goal Attainment Scale (GAS). In the GAS, parents described their goals related to their child’s condition and care. Using a qualitative and systematic coding system the parent’s goals were categorized based on content and outcomes related to their child. The goals created by parents in this population subset fell into eight distinct categories. The categories discerned during analysis were future oriented, internal/perspective adjustment, interpersonal, maintaining normalcy, education/coordination with schools, interaction with health care professionals, physical fitness, and acknowledgement/fostering independence.. Based on analysis of the goals that parents created within the GAS, parents of children with epilepsy are particularly concerned with the security of their child’s future (both residentially and vocationally), educational advancement in partnership with schools, and improving health status through interaction with health care professionals. For the nurse interacting with patients and their caregiver in this specialized population it is critical to understand the goals that caregivers create in relation to the problems that they perceive as the most significant in their lives. Then the nurse will be able to enable caregivers to meet their goals and improve the health outcomes and overall quality of life in children with epilepsy and learning disorders.Item Oncology Nurses’ Experiences with Prognosis Related Communication(Office of the Vice Chancellor for Research, 2013-04-05) McLennon, Susan M.; Lasiter, Sue; Miller, Wendy; Amlin, Kathryn; Chamness, Amy R.; Helft, Paul R.Background: Oncology nurses have opportunities to engage in prognosis related communication with advanced cancer patients but often encounter barriers that impede patient prognosis understanding. Deficits in prognosis understanding have been associated with delays in transitions to end of life care, overly aggressive and potentially non-beneficial cancer treatments, and poor quality of life. Purpose: The purpose of this study was to describe nurses' experiences with prognosis related communication with advanced cancer patients. Methods: A framework of realism was used in this qualitative, descriptive design. A thematic analysis of audio-recorded interviews with oncology nurses (n=27) recruited from a Midwestern urban academic health center and 3 affiliated institutions was performed. Interviews were transcribed verbatim and accuracy checked. Data were coded by 3 experienced researchers. After coding, themes were identified, and a thematic map was developed. Methods to ensure trustworthiness of the findings were used. Results: Six themes were identified: Being in the middle, assessing the situation, barriers to prognosis communication, nurse actions, benefits of prognosis understanding, and negative outcomes. Nurses managed barriers through facilitation, collaboration, or independent actions to assist patients and/or families with prognosis understanding. Conclusions: Shortcomings in prognosis related communication with advanced cancer patients may contribute to negative outcomes for patients and nurses. Interventions to advance nurses’ abilities to facilitate and engage in prognosis communications are needed. Inter-professional communication skills education may also be beneficial.Item Discussing Sudden Unexpected Death in Epilepsy (SUDEP) with Patients: Practices of Health-Care Providers(Elsevier, 2014-03) Miller, Wendy R.; Young, Neicole; Friedman, Daniel; Buelow, Janice M.; Devinsky, Orin; IU School of NursingItem Finding the Patient’s Voice Using Big Data: Analysis of Users’ Health-Related Concerns in the ChaCha Question-and-Answer Service (2009–2012)(JMIR, 2016) Priest, Chad; Knopf, Amelia; Groves, Doyle; Carpenter, Janet S.; Furrey, Christopher; Krishnan, Anand; Miller, Wendy R.; Otte, Julie L.; Palakal, Mathew; Wiehe, Sarah E.; Wilson, Jeffrey S.; IU School of NursingBackground: The development of effective health care and public health interventions requires a comprehensive understanding of the perceptions, concerns, and stated needs of health care consumers and the public at large. Big datasets from social media and question-and-answer services provide insight into the public’s health concerns and priorities without the financial, temporal, and spatial encumbrances of more traditional community-engagement methods and may prove a useful starting point for public-engagement health research (infodemiology). Objective: The objective of our study was to describe user characteristics and health-related queries of the ChaCha question-and-answer platform, and discuss how these data may be used to better understand the perceptions, concerns, and stated needs of health care consumers and the public at large. Methods: We conducted a retrospective automated textual analysis of anonymous user-generated queries submitted to ChaCha between January 2009 and November 2012. A total of 2.004 billion queries were read, of which 3.50% (70,083,796/2,004,243,249) were missing 1 or more data fields, leaving 1.934 billion complete lines of data for these analyses. Results: Males and females submitted roughly equal numbers of health queries, but content differed by sex. Questions from females predominantly focused on pregnancy, menstruation, and vaginal health. Questions from males predominantly focused on body image, drug use, and sexuality. Adolescents aged 12–19 years submitted more queries than any other age group. Their queries were largely centered on sexual and reproductive health, and pregnancy in particular. Conclusions: The private nature of the ChaCha service provided a perfect environment for maximum frankness among users, especially among adolescents posing sensitive health questions. Adolescents’ sexual health queries reveal knowledge gaps with serious, lifelong consequences. The nature of questions to the service provides opportunities for rapid understanding of health concerns and may lead to development of more effective tailored interventions. [J Med Internet Res 2016;18(3):e44]Item Psychometric Testing of the Life Changes in Epilepsy Scale(Springer, 2017) Miller, Wendy Renee; Weaver, Michael; Bakoyannis, Giorgos; Bakas, Tamilyn; Buelow, Janice; Sabau, Dragos; School of NursingPurpose: Three aims were addressed: (a) Evaluate properties of the items comprising the Life Changes in Epilepsy Scale-Pilot (LCES-P), (b) use item analysis to optimize the scale, (c) evaluate construct and criterion-related validity of the optimized LCES. Methods: The LCES-P was administered to 174 adults with epilepsy. Item analysis and exploratory factor analysis were performed. Internal consistency reliability, construct validity, and criterion-related validity were evaluated. Results: 17 items were retained in the optimized LCES. Internal consistency reliability was supported. Path analysis was used to evaluate construct validity. Criterion-related validity was supported by correlations with the Medical Outcomes SF-36 Survey (SF-36) General Health subscale and a criterion variable. Conclusions: The optimized version of the LCES can serve as a valuable outcome measure in clinical and research environments.Item Word Adjacency Graph Modeling: Separating Signal From Noise in Big Data(Sage, 2017-01) Miller, Wendy R.; Groves, Doyle; Knopf, Amelia; Otte, Julie L.; Silverman, Ross D.; School of NursingThere is a need to develop methods to analyze Big Data to inform patient-centered interventions for better health outcomes. The purpose of this study was to develop and test a method to explore Big Data to describe salient health concerns of people with epilepsy. Specifically, we used Word Adjacency Graph modeling to explore a data set containing 1.9 billion anonymous text queries submitted to the ChaCha question and answer service to (a) detect clusters of epilepsy-related topics, and (b) visualize the range of epilepsy-related topics and their mutual proximity to uncover the breadth and depth of particular topics and groups of users. Applied to a large, complex data set, this method successfully identified clusters of epilepsy-related topics while allowing for separation of potentially non-relevant topics. The method can be used to identify patient-driven research questions from large social media data sets and results can inform the development of patient-centered interventions.Item Menopause and Big Data: Word Adjacency Graph Modeling of Menopause-Related ChaCha® Data(Wolters Kluwer, 2017-07) Carpenter, Janet S.; Groves, Doyle; Chen, Chen X.; Otte, Julie L.; Miller, Wendy; School of NursingOBJECTIVE: To detect and visualize salient queries about menopause using Big Data from ChaCha. METHODS: We used Word Adjacency Graph (WAG) modeling to detect clusters and visualize the range of menopause-related topics and their mutual proximity. The subset of relevant queries was fully modeled. We split each query into token words (ie, meaningful words and phrases) and removed stopwords (ie, not meaningful functional words). The remaining words were considered in sequence to build summary tables of words and two and three-word phrases. Phrases occurring at least 10 times were used to build a network graph model that was iteratively refined by observing and removing clusters of unrelated content. RESULTS: We identified two menopause-related subsets of queries by searching for questions containing menopause and menopause-related terms (eg, climacteric, hot flashes, night sweats, hormone replacement). The first contained 263,363 queries from individuals aged 13 and older and the second contained 5,892 queries from women aged 40 to 62 years. In the first set, we identified 12 topic clusters: 6 relevant to menopause and 6 less relevant. In the second set, we identified 15 topic clusters: 11 relevant to menopause and 4 less relevant. Queries about hormones were pervasive within both WAG models. Many of the queries reflected low literacy levels and/or feelings of embarrassment. CONCLUSIONS: We modeled menopause-related queries posed by ChaCha users between 2009 and 2012. ChaCha data may be used on its own or in combination with other Big Data sources to identify patient-driven educational needs and create patient-centered interventions.Item Chronic Disease Self-Management: A Hybrid Concept Analysis(Elsevier, 2015-03) Miller, Wendy R.; Lasiter, Sue; Bartlett Ellis, Rebecca J.; Buelow, Janice M.; School of NursingBACKGROUND: Chronic diseases require chronic disease self-management (CDSM). Existing CDSM interventions, while improving outcomes, often do not lead to long-lasting effects. To render existing and new CDSM interventions more effective, an exploration of the concept of CDSM from both the literature and patient perspectives is needed. The purpose of this study was to describe the current conceptualization of CDSM in the literature, identify potential inadequacies in this conceptualization based on a comparison of literature- and patient-based CDSM descriptions, and to offer a more comprehensive definition of CDSM. METHODS: A hybrid concept analysis was completed. DISCUSSION: In the literature, CDSM is defined as behaviors influenced by individual characteristics. Patients in the fieldwork phase discussed aspects of CDSM not well represented in the literature. CONCLUSIONS: CDSM is a complex process involving behaviors at multiple levels of a person's environment. Pilot work to develop and test CDSM interventions based on both individual and external characteristics is needed.Item Big Data and Dysmenorrhea: What Questions Do Women and Men Ask About Menstrual Pain?(Mary Ann Liebert, 2018-10) Chen, Chen X.; Groves, Doyle; Miller, Wendy R.; Carpenter, Janet S.; School of NursingBACKGROUND: Menstrual pain is highly prevalent among women of reproductive age. As the general public increasingly obtains health information online, Big Data from online platforms provide novel sources to understand the public's perspectives and information needs about menstrual pain. The study's purpose was to describe salient queries about dysmenorrhea using Big Data from a question and answer platform. MATERIALS AND METHODS: We performed text-mining of 1.9 billion queries from ChaCha, a United States-based question and answer platform. Dysmenorrhea-related queries were identified by using keyword searching. Each relevant query was split into token words (i.e., meaningful words or phrases) and stop words (i.e., not meaningful functional words). Word Adjacency Graph (WAG) modeling was used to detect clusters of queries and visualize the range of dysmenorrhea-related topics. We constructed two WAG models respectively from queries by women of reproductive age and bymen. Salient themes were identified through inspecting clusters of WAG models. RESULTS: We identified two subsets of queries: Subset 1 contained 507,327 queries from women aged 13-50 years. Subset 2 contained 113,888 queries from men aged 13 or above. WAG modeling revealed topic clusters for each subset. Between female and male subsets, topic clusters overlapped on dysmenorrhea symptoms and management. Among female queries, there were distinctive topics on approaching menstrual pain at school and menstrual pain-related conditions; while among male queries, there was a distinctive cluster of queries on menstrual pain from male's perspectives. CONCLUSIONS: Big Data mining of the ChaCha® question and answer service revealed a series of information needs among women and men on menstrual pain. Findings may be useful in structuring the content and informing the delivery platform for educational interventions.