IU Indianapolis ScholarWorks :: Browsing by Author "Dickinson, Stephanie L."

Browsing by Author "Dickinson, Stephanie L."

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A comparison between perceived rurality and established geographic rural status among Indiana residents
(Wolters Kluwer, 2023) Bhattacharyya, Oindrila; Rawl, Susan M.; Dickinson, Stephanie L.; Haggstrom, David A.; Economics, School of Liberal Arts
The study assessed the association and concordance of the traditional geography-based Rural-Urban Commuting Area (RUCA) codes to individuals' self-reported rural status per a survey scale. The study included residents from rural and urban Indiana, seen at least once in a statewide health system in the past 12 months. Surveyed self-reported rural status of individuals obtained was measured using 6 items with a 7-point Likert scale. Cronbach's alpha was used to measure the internal consistency between the 6 survey response items, along with exploratory factor analysis to evaluate their construct validity. Perceived rurality was compared with RUCA categorization, which was mapped to residential zip codes. Association and concordance between the 2 measures were calculated using Spearman's rank correlation coefficient and Gwet's Agreement Coefficient (Gwet's AC), respectively. Primary self-reported data were obtained through a cross-sectional, statewide, mail-based survey, administered from January 2018 through February 2018, among a random sample of 7979 individuals aged 18 to 75, stratified by rural status and race. All 970 patients who completed the survey answered questions regarding their perceived rurality. Cronbach's alpha value of 0.907 was obtained indicating high internal consistency among the 6 self-perceived rurality items. Association of RUCA categorization and self-reported geographic status was moderate, ranging from 0.28 to 0.41. Gwet's AC ranged from -0.11 to 0.26, indicating poor to fair agreement between the 2 measures based on the benchmark scale of reliability. Geography-based and self-report methods are complementary in assessing rurality. Individuals living in areas of relatively high population density may still self-identify as rural, or individuals with long commutes may self-identify as urban.
Comparison of health information exchange data with self-report in measuring cancer screening
(BMC, 2023-07-25) Bhattacharyya, Oindrila; Rawl, Susan M.; Dickinson, Stephanie L.; Haggstrom, David A.; Economics, School of Liberal Arts
Background: Efficient measurement of the receipt of cancer screening has been attempted with electronic health records (EHRs), but EHRs are commonly implemented within a single health care setting. However, health information exchange (HIE) includes EHR data from multiple health care systems and settings, thereby providing a more population-based measurement approach. In this study, we set out to understand the value of statewide HIE data in comparison to survey self-report (SR) to measure population-based cancer screening. Methods: A statewide survey was conducted among residents in Indiana who had been seen at an ambulatory or inpatient clinical setting in the past year. Measured cancer screening tests included colonoscopy and fecal immunochemical test (FIT) for colorectal cancer, human papilloma virus (HPV) and Pap tests for cervical cancer, and mammogram for breast cancer. For each screening test, the self-reported response for receipt of the screening (yes/no) and 'time since last screening' were compared with the corresponding information from patient HIE to evaluate the concordance between the two measures. Results: Gwet's AC for HIE and self-report of screening receipt ranged from 0.24-0.73, indicating a fair to substantial concordance. For the time since receipt of last screening test, the Gwet's AC ranged from 0.21-0.90, indicating fair to almost perfect concordance. In comparison with SR data, HIE data provided relatively more additional information about laboratory-based tests: FIT (19% HIE alone vs. 4% SR alone) and HPV tests (27% HIE alone vs. 12% SR alone) and less additional information about procedures: colonoscopy (8% HIE alone vs. 23% SR alone), Pap test (13% HIE alone vs. 19% SR alone), or mammography (9% HIE alone vs. 10% SR alone). Conclusion: Studies that use a single data source should consider the type of cancer screening test to choose the optimal data collection method. HIE and self-report both provided unique information in measuring cancer screening, and the most robust measurement approach involves collecting screening information from both HIE and patient self-report.
Effects of ACT Out! Social Issue Theater on Social-Emotional Competence and Bullying in Youth and Adolescents: Cluster Randomized Controlled Trial
(JMIR Publications, 2021-01-06) Agley, Jon; Jun, Mikyoung; Eldridge, Lori; Agley, Daniel L.; Xiao, Yunyu; Sussman, Steve; Golzarri-Arroyo, Lilian; Dickinson, Stephanie L.; Jayawardene, Wasantha; Gassman, Ruth; School of Social Work
Background: Schools increasingly prioritize social-emotional competence and bullying and cyberbullying prevention, so the development of novel, low-cost, and high-yield programs addressing these topics is important. Further, rigorous assessment of interventions prior to widespread dissemination is crucial. Objective: This study assesses the effectiveness and implementation fidelity of the ACT Out! Social Issue Theater program, a 1-hour psychodramatic intervention by professional actors; it also measures students' receptiveness to the intervention. Methods: This study is a 2-arm cluster randomized control trial with 1:1 allocation that randomized either to the ACT Out! intervention or control (treatment as usual) at the classroom level (n=76 classrooms in 12 schools across 5 counties in Indiana, comprised of 1571 students at pretest in fourth, seventh, and tenth grades). The primary outcomes were self-reported social-emotional competence, bullying perpetration, and bullying victimization; the secondary outcomes were receptiveness to the intervention, implementation fidelity (independent observer observation), and prespecified subanalyses of social-emotional competence for seventh- and tenth-grade students. All outcomes were collected at baseline and 2-week posttest, with planned 3-months posttest data collection prevented due to the COVID-19 pandemic. Results: Intervention fidelity was uniformly excellent (>96% adherence), and students were highly receptive to the program. However, trial results did not support the hypothesis that the intervention would increase participants' social-emotional competence. The intervention's impact on bullying was complicated to interpret and included some evidence of small interaction effects (reduced cyberbullying victimization and increased physical bullying perpetration). Additionally, pooled within-group reductions were also observed and discussed but were not appropriate for causal attribution. Conclusions: This study found no superiority for a 1-hour ACT Out! intervention compared to treatment as usual for social-emotional competence or offline bullying, but some evidence of a small effect for cyberbullying. On the basis of these results and the within-group effects, as a next step, we encourage research into whether the ACT Out! intervention may engender a bystander effect not amenable to randomization by classroom. Therefore, we recommend a larger trial of the ACT Out! intervention that focuses specifically on cyberbullying, measures bystander behavior, is randomized by school, and is controlled for extant bullying prevention efforts at each school.
Financial hardship is associated with lower uptake of colorectal, breast, and cervical cancer screenings
(Springer, 2021-10) Kasting, Monica L.; Haggstrom, David A.; Lee, Joy L.; Dickinson, Stephanie L.; Shields, Cleveland G.; Rawl, Susan M.; School of Nursing
PURPOSE: Cancer screening uptake differs between groups in ways that cannot be explained by socioeconomic status alone. This study examined associations between material, psychosocial, and behavioral aspects of financial hardship and cancer screening behaviors. METHODS: Surveys were mailed to 7,979 people ages 18-75 who were seen in the statewide health system in Indiana. Participants reported SES, feelings about finances, and whether they had to forgo medical care due to cost. This was compared to uptake of mammogram, colonoscopy/sigmoidoscopy, and Pap testing in best-fit multivariable logistic regression analyses controlling for demographic and healthcare characteristics. RESULTS: A total of 970 surveys were returned; the majority of respondents were female (54%), non-Hispanic White (75%), and over 50 years old (76%). 15% reported forgoing medical care due to cost; this barrier was higher among Black than White participants (24% vs. 13%; p = 0.001). In a best fit regression model for colonoscopy/sigmoidoscopy, those who reported they had to forgo medical care due to cost had lower odds of screening (aOR 0.41; 95% CI 0.22-0.74). Forgoing medical care due to cost was not significantly associated with Pap testing in bivariate analyses. For mammogram, forgoing medical care due to cost was significant in bivariate analyses (OR 0.44; 95% CI 0.22-0.88), but was not significant in the multivariable model. CONCLUSION: Associations between financial hardship and cancer screening suggest the need to reduce barriers to cancer screening even among patients who have access to healthcare. Future research should explore barriers related to both healthcare and personal costs.
From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research
(Oxford University Press, 2022) Chusyd, Daniella E.; Austad, Steven N.; Brown, Andrew W.; Chen, Xiwei; Dickinson, Stephanie L.; Ejima, Keisuke; Fluharty, David; Golzarri-Arroyo, Lilian; Holden, Richard; Jamshidi-Naeini, Yasaman; Landsittel, Doug; Lartey, Stella; Mannix, Edward; Vorland, Colby J.; Allison, David B.; Anatomy, Cell Biology and Physiology, School of Medicine
This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: (a) errors in randomization, (b) errors related to testing within-group instead of between-group differences, (c) failing to account for clustering, (d) failing to consider interference effects, (e) standardizing metrics of effect size, (f) maximum life-span testing, (g) testing for effects beyond the mean, (h) tests for power and sample size, (i) compression of morbidity versus survival curve squaring, and (j) other hot topics, including modeling high-dimensional data and complex relationships and assessing model assumptions and biases. We hope that bringing increased awareness of these topics to the scientific community will emphasize the importance of employing sound statistical practices in all aspects of aging and senescence research.
Locomotor analysis identifies early compensatory changes during disease progression and subgroup classification in a mouse model of amyotrophic lateral sclerosis
(Medknow Publications, 2017-10) Haulcomb, Melissa M.; Meadows, Rena M.; Miller, Whitney M.; McMillan, Kathryn P.; Hilsmeyer, MeKenzie J.; Wang, Xuefu; Beaulieu, Wesley T.; Dickinson, Stephanie L.; Brown, Todd J.; Sanders, Virginia M.; Jones, Kathryn J.; Anatomy and Cell Biology, School of Medicine
Amyotrophic lateral sclerosis is a motoneuron degenerative disease that is challenging to diagnose and presents with considerable variability in survival. Early identification and enhanced understanding of symptomatic patterns could aid in diagnosis and provide an avenue for monitoring disease progression. Use of the mSOD1G93A mouse model provides control of the confounding environmental factors and genetic heterogeneity seen in amyotrophic lateral sclerosis patients, while investigating underlying disease-induced changes. In the present study, we performed a longitudinal behavioral assessment paradigm and identified an early hindlimb symptom, resembling the common gait abnormality foot drop, along with an accompanying forelimb compensatory mechanism in the mSOD1G93A mouse. Following these initial changes, mSOD1 mice displayed a temporary hindlimb compensatory mechanism resembling an exaggerated steppage gait. As the disease progressed, these compensatory mechanisms were not sufficient to sustain fundamental locomotor parameters and more severe deficits appeared. We next applied these initial findings to investigate the inherent variability in B6SJL mSOD1G93A survival. We identified four behavioral variables that, when combined in a cluster analysis, identified two subpopulations with different disease progression rates: a fast progression group and a slow progression group. This behavioral assessment paradigm, with its analytical approaches, provides a method for monitoring disease progression and detecting mSOD1 subgroups with different disease severities. This affords researchers an opportunity to search for genetic modifiers or other factors that likely enhance or slow disease progression. Such factors are possible therapeutic targets with the potential to slow disease progression and provide insight into the underlying pathology and disease mechanisms.
Metabolic Biomarkers for the Early Detection of Cancer Cachexia
(Frontiers Media, 2021-09-21) O’Connell, Thomas M.; Golzarri-Arroyo, Lilian; Pin, Fabrizio; Barreto, Rafael; Dickinson, Stephanie L.; Couch, Marion E.; Bonetto, Andrea; Otolaryngology -- Head and Neck Surgery, School of Medicine
Background: Cancer cachexia is a severe metabolic disorder characterized by progressive weight loss along with a dramatic loss in skeletal muscle and adipose tissue. Like cancer, cachexia progresses in stages starting with pre-cachexia to cachexia and finally to refractory cachexia. In the refractory stage, patients are no longer responsive to therapy and management of weight loss is no longer possible. It is therefore critical to detect cachexia as early as possible. In this study we applied a metabolomics approach to search for early biomarkers of cachexia. Methods: Multi-platform metabolomics analyses were applied to the murine Colon-26 (C26) model of cachexia. Tumor bearing mice (n = 5) were sacrificed every other day over the 14-day time course and control mice (n = 5) were sacrificed every fourth day starting at day 2. Linear regression modeling of the data yielded metabolic trajectories that were compared with the trajectories of body weight and skeletal muscle loss to look for early biomarkers of cachexia. Results: Weight loss in the tumor-bearing mice became significant at day 9 as did the loss of tibialis muscle. The loss of muscle in the gastrocnemius and quadriceps was significant at day 7. Reductions in amino acids were among the earliest metabolic biomarkers of cachexia. The earliest change was in methionine at day 4. Significant alterations in acylcarnitines and lipoproteins were also detected several days prior to weight loss. Conclusion: The results of this study demonstrate that metabolic alterations appear well in advance of observable weight loss. The earliest and most significant alterations were found in amino acids and lipoproteins. Validation of these results in other models of cachexia and in clinical studies will pave the way for a clinical diagnostic panel for the early detection of cachexia. Such a panel would provide a tremendous advance in cachectic patient management and in the design of clinical trials for new therapeutic interventions.
Rural and Urban Differences in the Adoption of New Health Information and Medical Technologies
(Wiley, 2019-03) Haggstrom, David A.; Lee, Joy L.; Dickinson, Stephanie L.; Kianersi, Sina; Roberts, Jamie L.; Teal, Evgenia; Baker, Layla B.; Rawl, Susan M.; Medicine, School of Medicine
Background This statewide survey sought to understand the adoption level of new health information and medical technologies, and whether these patterns differed between urban and rural populations. Methods A random sample of 7,979 people aged 18‐75 years, stratified by rural status and race, who lived in 1 of 34 Indiana counties with high cancer mortality rates and were seen at least once in the past year in a statewide health system were surveyed. Results Completed surveys were returned by 970 participants. Rural patients were less likely than urban to use electronic health record messaging systems (28.3% vs 34.5%, P = .045) or any communication technology (43.0% vs 50.8%, P = .017). Rural patients were less likely to look for personal health information for someone else's medical record (11.0% vs 16.3%, P = .022), look‐up test results (29.5% vs 38.3%, P = .005), or use any form of electronic medical record (EMR) access (57.5% vs 67.1%, P = .003). Rural differences in any use of communication technology or EMRs were no longer significant in adjusted models, while education and income were significantly associated. There was a trend in the higher use of low‐dose computed tomography (CT) scan among rural patients (19.1% vs 14.4%, P = .057). No significant difference was present between rural and urban patients in the use of the human papilloma virus test (27.1% vs 26.6%, P = .880). Conclusions Differences in health information technology use between rural and urban populations may be moderated by social determinants. Lower adoption of new health information technologies (HITs) than medical technologies among rural, compared to urban, individuals may be due to lower levels of evidence supporting HITs.

Browsing by Author "Dickinson, Stephanie L."

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