Pediatric asthma incidence in Texas and associations with ambient ozone levels in an urban area an analysis using Medicaid claims data

Few recent estimates of childhood asthma incidence exist in the literature, although the importance of incidence surveillance for understanding asthma risk factors has been recognized. Asthma prevalence, morbidity and mortality reports have repeatedly shown that low-income children are disproportionately impacted by the disease. The aim of this study was to demonstrate the utility of Medicaid claims data for providing statewide estimates of asthma incidence. Medicaid Analytic Extract (MAX) data for Texas children ages 0-17 enrolled in Medicaid between 2004 and 2007 were used to estimate incidence overall and by age group, gender, race and county of residence. A 13+ month period of continuous enrollment was required in order to distinguish incident from prevalent cases identified in the claims data. Age-adjusted incidence of asthma was 4.26/100 person-years during 2005-2007, higher than reported in other populations. Incidence rates decreased with age, were higher for males than females, differed by race, and tended to be higher in rural than urban areas. With this study, we were able to demonstrate the utility of MAX data for estimating asthma incidence, and create a dataset of incident cases to use in further analysis. ^ In subsequent analyses, we investigated a possible association between ambient air pollutants and incident asthma among Medicaid-enrolled children in Harris County Texas between 2005 and 2007. This population is at high risk for asthma, and living in an area with historically poor air quality. We used a time-stratified case-crossover design and conditional logistic regression to calculate odds ratios, adjusted for weather variables and aeroallergens, to assess the effect of increases in ozone, NO2 and PM2.5 concentrations on risk of developing asthma. Our results show that a 10 ppb increase in ozone was significantly associated with asthma during the warm season (May-October), with the strongest effect seen when a 6-day cumulative lag period was used to compute the exposure metric (OR=1.05, 95% CI, 1.02–1.08). Similar results were seen for NO2 and PM 2.5 (OR=1.07, 95% CI, 1.03–1.11 and OR=1.12, 95% CI, 1.03–1.22, respectively). PM2.5 also had significant effects in the cold season (November-April), 5-day cumulative lag: OR=1.11, 95% CI, 1.00–1.22. When compared with children in the lowest quartile of O3 exposure, the risk for children in the highest quartile was 20% higher. This study indicates that these pollutants are associated with newly-diagnosed childhood asthma in this low-income urban population, particularly during the summer months. ^

Ozone and fine particulate matter association with CVD and COPD emergency room visits in Harris County, Texas: Spatiotemporal analysis

This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

Associations between teacher support and students' fruit and vegetable consumption in low-income elementary schools in central Texas

Background. Similar to parent support in the home environment, teacher support at school may positively influence children's fruit and vegetable (FV) consumption. This study assessed the relationship between teacher support for FV consumption and the FV intake of 4th and 5th grade students in low-income elementary schools in central Texas. Methods. A secondary analysis was performed on baseline data collected from 496 parent-child dyads during the Marathon Kids study carried out by the Michael & Susan Dell Center for Healthy Living at the University of Texas School of Public Health. A hierarchical linear regression analysis adjusting for key demographic variables, parent support, and home FV availability was conducted. In addition, separate linear regression models stratified by quartiles of home FV availability were conducted to assess the relationship between teacher support and FV intake by level of home FV availability. Results. Teacher support was not significantly related to students' FV intake (p = .44). However, the interaction of teacher support and home FV availability was positively associated with students' FV consumption (p < .05). For students in the lowest quartile of home FV availability, teacher support accounted for approximately 6% of the FV intake variance (p = .02). For higher levels of FV availability, teacher support and FV intake were not related. Conclusions. For lower income elementary school-aged children with low FV availability at home, greater teacher support may lead to modest increases in FV consumption.^

Risk factors for metabolic syndrome among overweight and obese Hispanic children attending a pediatric clinic in New Braunfels, Texas

Childhood obesity is a persistent problem in the U.S., especially among Hispanics. Health complications like hypertension, type II diabetes, and metabolic syndrome (Met-S) are being seen at younger ages, and current screening procedures may be inadequate. This study sought to describe the risk factors for Met-S present in a sample of 106 overweight and obese Hispanic children, aged 5-14 years, participating in Nutrition and Exercise Start Today (NEST), a randomized weight management intervention trial at a rural health clinic in New Braunfels, Texas; and to determine associations between these factors and other clinical and socio-demographic characteristics linked to obesity. Baseline data was analyzed for the prevalence of large waist circumference (WC), elevated blood pressure (BP), high fasting serum glucose and serum triglycerides (TG), and low serum HDL cholesterol, in relationship with selected sample characteristics. Main findings included high baseline prevalence rates of large WC (77%), reduced HDL (57%), and elevated BP (30%). WC was significantly associated with BMI percentile and the serum liver function test alanine aminotransferase (ALT) by Fisher's exact test (p<0.001 and p=0.032, respectively), while there were significant relationships between HDL and both female gender and ALT. BMI percentile and ALT were associated with all sets of Met-S diagnostic criteria examined. BMI percentile also had a strong association (p=0.005) with total number of Met-S risk factors, while ALT had a weaker association (p=0.093). WC is a low-cost, simple measure whose use may improve clinic surveillance for childhood obesity and complications like Met-S. WC, BP, HDL and ALT may be used as part of targeted screening for obesity complications like Met-S, particularly in situations where resources are limited.^

Association between length of stay in the U.S. and diabetes risk factors among Chinese Americans in Houston, Texas in 2004-2005

Studies have suggested that acculturation is related to diabetes prevalence and risk factors among immigrant groups in the United States (U.S.), however scant data are available to investigate this relationship among Asian Americans and Asian American subgroups. The objective of this cross-sectional study was to examine the association between length of stay in the U.S. and type 2 diabetes prevalence and its risk factors among Chinese Americans in Houston, Texas. Data were obtained from the 2004-2005 Asian-American Health Needs Assessment in Houston, Texas (N=409 Chinese Americans) for secondary analysis in this study. Diabetes prevalence and risk factors (overweight/obesity and access to medical care) were based on self-report. Descriptive statistics summarized demographic characteristics, diabetes prevalence, and reasons for not seeing a doctor. Logistic regression, using an incremental modeling approach, was used to measure the association between length of stay and diabetes prevalence and related risk factors, while adjusting for the potential confounding factors of age, gender, education level, and income level. Although the prevalence of type 2 diabetes was highest among those living in the U.S. for more than 20 years, there was no significant association between length of stay in the U.S. and diabetes prevalence among these Chinese Americans after adjustment for confounding factors. No association was found between length of stay in the U.S. and overweight/obese status among this population either, after adjusting for confounding factors, too. On the other hand, a longer length of stay was significantly associated with increased health insurance coverage in both unadjusted and adjusted models. The findings of this study suggest that length of stay in the U.S. alone may not be an indicator for diabetes risk among Chinese Americans. Future research should consider alternative models to measure acculturation (e.g., models that reflect acculturation as a multi-dimensional, not uni-dimensional process), which may more accurately depict its effect on diabetes prevalence and related risk factors.^

Harris County Medical Society, Woman's Auxiliary Year Book 1926-1927

Partnering with the Texas Medical Association Alliance "to improve the health of all Texans," the Harris County Medical Society (HCMS) Alliance was organized in 1919 as the HCMS Woman’s Auxiliary. Current membership consists of the spouses of physicians, as well as physicians, in Harris County. http://hcmsa.org/ accessed 11/20/2012 This booklet lists the members of the Auxiliary, officers, programs for September, 1926 – May, 1927, and the organization’s constitution and by-laws. Booklet is 7 1/8 x 4 ½ inches and contains 18 pages.

Bullied status and physical activity in Texas youths

Data from the 2009–2011 School Physical Activity and Nutrition (SPAN) project were analyzed to examine the association between bullied status at school during the past six months and engaging in five or more days of physical activity during the past seven days in a population of 8th and 11th grade Texas youths after stratifying by gender. As a secondary aim, this study also examined the association between weight status and the prevalence of bullied status at school. The final sample size for this study, after excluding missing data, consisted of 6,246 8th and 11th grade youths (girls, n= 3,237; boys, n=3,009) representing a total of 518,838 youths from 8th and 11th grade. Results from the multiple logistic regression adjusting for weight status, grade, and ethnicity, indicate that girls with a bullied status of at least two or three times per month had significantly lower odds of engaging in five or more days of physical activity during the past seven days than girls who were never bullied at school (ORadj=0.62; 95% CI, 0.40, 0.96). Conversely, girls who reported a bullied status of at least once per week were significantly more likely to engage in five or more days of physical activity during the past seven days compared to girls who were never bullied at school (ORadj=3.44; 95% CI, 1.56, 7.63). No significant associations between bullied status and engaging in five or more days of physical activity during the past seven days were found for boys. Bullied status differed significantly across weight status for 8th grade girls (χ2(6)=63.7, p<.05) and 11th grade boys (χ2(6) =94.93, p<.05), with overweight and obese youths reporting a higher prevalence of being bullied once or twice, at least two or three times per month, and at least once per week than their normal weight peers. Our finding that girls with bullied status of at least once per week were more likely to engage in five or more days of physical activity than girls who were never bullied warrants future qualitative research to identify potential explanations for such results. Future research on relational and weight-based bullying is also needed and may help explain the inconsistent findings between bullied status and engaging in physical activity in girls.^

Correlation of tuberculosis and human immunodeficiency virus in Harris County, Texas from 2009 through 2010 using Geographic Information Systems

A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^

MEDICINE MAN IN TEXAS

The author George (Georgia?) Plunkett Red was the wife of Samuel Clark Red (1861-1940). Dr. Red was the son of Texas pioneer physician Dr. George Clark Red. Dr. Samuel Clark Red was “the county physician of Harris County, one of the organizers of the Harris County Medical Society, a fellow of the American College of Surgeons, and president of the Texas Medical Association.” Not much is known about the author, but given her husband’s position and family history, it can be surmised that she was interested in history and had access to some of the children of other pioneer medical families. There is a brief bibliography for each of the chapters. Part Two of the book consists of biographies of physicians from Texas Counties. Merle Weir, "RED, SAMUEL CLARK," Handbook of Texas Online (http://www.tshaonline.org/handbook/online/articles/fre09), accessed December 10, 2012. Published by the Texas State Historical Association.

The History of Pathology in Texas

The History of Pathology in Texas is the study of the changes of disease in Texas from the frontier days to the 1990s. Marilyn Miller Baker wrote the book for the Texas Society of Pathologists. The book was published in 1996 with a forward by Vernie A. Stembridge, MD, the Ashbel Smith Professor and Chairman Emeritus of Pathology at the University of Texas Southwestern Medical Center at Dallas. The book covers the story of pathology from the "performance of crude autopsies" on the frontier through the emergence of bacteriology and immunology and beyond.

A History of Organized Medicine in Harris County, Texas

The item was written by the Historical Committee of the Harris County Medical Society and signed on October 28, 1948. A brief history of medicine in Texas is given before the focus shifts to the Harris County and Houston area. Information on the early years is taken from various sources such as Pat Ireland Nixon’s The Medical Story of Early Texas and the writings of George Plunkett (Mrs. S. C.) Red. Significant information comes from the Minutes of the Harris County Medical Society.

Sugar sweetened beverage consumption and behavioral correlates in a pilot study of high school students in Austin, Texas

Habitual consumption of sugar-sweetened beverages (SSB) has been reliably linked to obesity in adolescents. A wide variety of beverages sweetened with sugar are available to this population. The objective of this secondary data analysis was to assess the consumption of SSB by category and to identify behaviors that occur concurrently with the consumption of soda, sport drinks and fruit-flavored drinks in high school students. The analysis used self-reported survey data from 97 adolescents ages 14 to 18. SSB categories considered in the consumption analysis included regular soda, sports drinks, fruit-flavored drinks (FFD), iced tea, coffee drinks and energy drinks. The mean weekly sweetened beverage load in this population, calculated from the frequency and amount of consumption, was 145 ounces when all categories were considered. When SSB categories were considered independently, sports drinks (45 oz.) had the highest contribution to the mean sweetened beverage load followed by FFD (41 oz.), iced tea (27 oz.), soda (26 oz.) coffee drinks (15 oz.) and energy drinks (2 oz.). Sweetened beverage load was higher in boys (151 oz.) than girls (138 oz.) and was highest in Hispanics (159 oz.) followed by whites (152 oz.), blacks (137 oz.) and others (104 oz.). Behaviors that occurred on a usual basis during SSB consumption included watching TV, eating a family meal, eating salty and fried foods, being on the computer and hanging out with friends. Activities concurrent with sports drink consumption included physical activity behaviors whereas soda and FFD did not. Sports drink and FFD consumption commonly co-occurred with fruit consumption. Multiple SSB categories contribute to the total SSB consumption and the common dietary and activity behaviors are distinct between categories. Several of the concurrent behaviors point to the importance of home beverage availability, and to the influence that parents and peers have on SSB consumption. Identifying and assessing intervention strategies targeted to specific beverage categories could be an important step in behavioral intervention research aimed at reducing added sugar consumption, and ultimately, promote a healthy weight in adolescents. ^

Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

Understanding and Characterizing Shared Decision-Making and Behavioral Intent in Medical Uncertainty

Applying Theoretical Constructs to Address Medical Uncertainty Situations involving medical reasoning usually include some level of medical uncertainty. Despite the identification of shared decision-making (SDM) as an effective technique, it has been observed that the likelihood of physicians and patients engaging in shared decision making is lower in those situations where it is most needed; specifically in circumstances of medical uncertainty. Having identified shared decision making as an effective, yet often a neglected approach to resolving a lack of information exchange in situations involving medical uncertainty, the next step is to determine the way(s) in which SDM can be integrated and the supplemental processes that may facilitate its integration. SDM involves unique types of communication and relationships between patients and physicians. Therefore, it is necessary to further understand and incorporate human behavioral elements - in particular, behavioral intent - in order to successfully identify and realize the potential benefits of SDM. This paper discusses the background and potential interaction between the theories of shared decision-making, medical uncertainty, and behavioral intent. Identifying Shared Decision-Making Elements in Medical Encounters Dealing with Uncertainty A recent summary of the state of medical knowledge in the U.S. reported that nearly half (47%) of all treatments were of unknown effectiveness, and an additional 7% involved an uncertain tradeoff between benefits and harms. Shared decision-making (SDM) was identified as an effective technique for managing uncertainty when two or more parties were involved. In order to understand which of the elements of SDM are used most frequently and effectively, it is necessary to identify these key elements, and understand how these elements related to each other and the SDM process. The elements identified through the course of the present research were selected from basic principles of the SDM model and the “Data, Information, Knowledge, Wisdom” (DIKW) Hierarchy. The goal of this ethnographic research was to identify which common elements of shared decision-making patients are most often observed applying in the medical encounter. The results of the present study facilitated the understanding of which elements patients were more likely to exhibit during a primary care medical encounter, as well as determining variables of interest leading to more successful shared decision-making practices between patients and their physicians. Understanding Behavioral Intent to Participate in Shared Decision-Making in Medically Uncertain Situations Objective: This article describes the process undertaken to identify and validate behavioral and normative beliefs and behavioral intent of men between the ages of 45-70 with regard to participating in shared decision-making in medically uncertain situations. This article also discusses the preliminary results of the aforementioned processes and explores potential future uses of this information which may facilitate greater understanding, efficiency and effectiveness of doctor-patient consultations.Design: Qualitative Study using deductive content analysisSetting: Individual semi-structure patient interviews were conducted until data saturation was reached. Researchers read the transcripts and developed a list of codes.Subjects: 25 subjects drawn from the Philadelphia community.Measurements: Qualitative indicators were developed to measure respondents’ experiences and beliefs related to behavioral intent to participate in shared decision-making during medical uncertainty. Subjects were also asked to complete the Krantz Health Opinion Survey as a method of triangulation.Results: Several factors were repeatedly described by respondents as being essential to participate in shared decision-making in medical uncertainty. These factors included past experience with medical uncertainty, an individual’s personality, and the relationship between the patient and his physician.Conclusions: The findings of this study led to the development of a category framework that helped understand an individual’s needs and motivational factors in their intent to participate in shared decision-making. The three main categories include 1) an individual’s representation of medically uncertainty, 2) how the individual copes with medical uncertainty, and 3) the individual’s behavioral intent to seek information and participate in shared decision-making during times of medically uncertain situations.