765 research outputs found

    HPV Awareness, Knowledge and Attitudes among Older African-American Women

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    Objective: To assess correlates of human papillomavirus (HPV) awareness, knowledge, and attitudes among older, church-going African-American women.ᅠMethods: Participants (N = 759), aged 40-80, answered survey questions about HPV awareness, knowledge, and attitudes toward vaccination of adolescent daughters. Associations between participant characteristics and HPV items were assessed using chi-square tests and logistic regression analyses.ᅠResults: Younger age, higher education, a family history of cancer, and less spirituality were each associated with HPV awareness individually, and when considered jointly in a single model (p values <.038). Higher education was related to HPV knowledge (p = .006).ᅠConclusions: African-American women of older age, less education, no family history of cancer, and/or higher spirituality might benefit from targeted church-based HPV educational campaigns

    A Continuous-Time Dynamic Factor Model for Intensive Longitudinal Data Arising from Mobile Health Studies

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    Intensive longitudinal data (ILD) collected in mobile health (mHealth) studies contain rich information on multiple outcomes measured frequently over time that have the potential to capture short-term and long-term dynamics. Motivated by an mHealth study of smoking cessation in which participants self-report the intensity of many emotions multiple times per day, we propose a dynamic factor model that summarizes the ILD as a low-dimensional, interpretable latent process. This model consists of two submodels: (i) a measurement submodel -- a factor model -- that summarizes the multivariate longitudinal outcome as lower-dimensional latent variables and (ii) a structural submodel -- an Ornstein-Uhlenbeck (OU) stochastic process -- that captures the temporal dynamics of the multivariate latent process in continuous time. We derive a closed-form likelihood for the marginal distribution of the outcome and the computationally-simpler sparse precision matrix for the OU process. We propose a block coordinate descent algorithm for estimation. Finally, we apply our method to the mHealth data to summarize the dynamics of 18 different emotions as two latent processes. These latent processes are interpreted by behavioral scientists as the psychological constructs of positive and negative affect and are key in understanding vulnerability to lapsing back to tobacco use among smokers attempting to quit.Comment: Main text is 19 pages with 4 figures and 1 table. Supporting material is 25 page

    The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.

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    MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland-Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes

    Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies

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    ObjectiveInsufficient engagement is a critical barrier impacting the utility of digital interventions and mobile health assessments. As a result, engagement itself is increasingly becoming a target of studies and interventions. The purpose of this study is to investigate the dynamics of engagement in mobile health data collection by exploring whether, how, and why response to digital self-report prompts change over time in smoking cessation studies.MethodData from two ecological momentary assessment (EMA) studies of smoking cessation among diverse smokers attempting to quit (N = 573) with a total of 65,974 digital self-report prompts. We operationalize engagement with self-reporting in term of prompts delivered and prompt response to capture both broad and more granular engagement in self-reporting, respectively. The data were analyzed to describe trends in prompt delivered and prompt response over time. Time-varying effect modeling (TVEM) was employed to investigate the time-varying effects of response to previous prompt and the average response rate on the likelihood of current prompt response.ResultsAlthough prompt response rates were relatively stable over days in both studies, the proportion of participants with prompts delivered declined steadily over time in one of the studies, indicating that over time, fewer participants charged the device and kept it turned on (necessary to receive at least one prompt per day). Among those who did receive prompts, response rates were relatively stable. In both studies, there is a significant, positive and stable relationship between response to previous prompt and the likelihood of response to current prompt throughout all days of the study. The relationship between the average response rate prior to current prompt and the likelihood of responding to the current prompt was also positive, and increasing with time.ConclusionOur study highlights the importance of integrating various indicators to measure engagement in digital self-reporting. Both average response rate and response to previous prompt were highly predictive of response to the next prompt across days in the study. Dynamic patterns of engagement in digital self-reporting can inform the design of new strategies to promote and optimize engagement in digital interventions and mobile health studies

    Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data

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    Advances in digital technology have greatly increased the ease of collecting intensive longitudinal data (ILD) such as ecological momentary assessments (EMAs) in studies of behavior changes. Such data are typically multilevel (e.g., with repeated measures nested within individuals), and are inevitably characterized by some degrees of missingness. Previous studies have validated the utility of multiple imputation as a way to handle missing observations in ILD when the imputation model is properly specified to reflect time dependencies. In this study, we illustrate the importance of proper accommodation of multilevel ILD structures in performing multiple imputations, and compare the performance of a multilevel multiple imputation (multilevel MI) approach relative to other approaches that do not account for such structures in a Monte Carlo simulation study. Empirical EMA data from a tobacco cessation study are used to demonstrate the utility of the multilevel MI approach, and the implications of separating participant- and study-initiated EMAs in evaluating individuals’ affective dynamics and urge

    Engaging Black Churches to Address Cancer Health Disparities: Project CHURCH

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    African Americans in the United States suffer disproportionately from cancer, having the highest mortality rate of any racial/ethnic group across all cancers for the past several decades. In addition, significant disparities exist in several cancer risk behaviors, including obesity, intake of fruits and vegetables, leisure time physical activity and cancer screening. Addressing these disparities require successful development of relationships with minority communities to partner in the research process, in order to understand areas of critical need and develop interventions that are compatible with this community. In this manuscript we describe Project CHURCH (Creating a Higher Understanding of Cancer Research and Community Health), a collaborative partnership between The University of Texas MD Anderson Cancer Center and Houston-area African American churches. Project CHURCH was developed to understand disparities in cancer prevention risk factors and engage African Americans as partners in the research process. Using community-based participatory research principles, we describe the development and infrastructure of the research partnership, as well as how the church community has been engaged in the development and implementation of a large African American cohort study (N = 2,338). Finally, the characteristics of the cohort are presented along with cohort success in addressing community need while having significant contribution to the scientific literature. Project CHURCH serves as a valuable resource for cancer prevention in the African American community

    Combined treatment for at-risk drinking and smoking cessation among Puerto Ricans: A randomized clinical trial

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    Tobacco and alcohol use are linked behaviors that individually and synergistically increase the risk for negative health consequences. This study was a two-group, randomized clinical trial evaluating the efficacy of a behavioral intervention, “Motivation And Problem Solving Plus” (MAPS+), designed to concurrently address smoking cessation and the reduction of at-risk drinking. Targeted interventions may promote coaction, the likelihood that changing one behavior (smoking) increases the probability of changing another behavior (alcohol use). Puerto Ricans (N=202) who were smokers and at-risk drinkers were randomized to standard MAPS treatment focused exclusively on smoking cessation (S-MAPS), or MAPS+, focused on cessation and at-risk drinking reduction. Drinking outcomes included: number of at-risk drinking behaviors, heavy drinking, binge drinking, and drinking and driving. MAPS+ did not have a significant main effect on reducing at-risk drinking relative to S-MAPS. Among individuals who quit smoking, MAPS+ reduced the number of drinking behaviors, the likelihood of meeting criteria for heavy drinking relative to S-MAPS, and appeared promising for reducing binge drinking. MAPS+ did not improve drinking outcomes among individuals who were unsuccessful at quitting smoking. MAPS+ showed promise in reducing at-risk drinking among Puerto Rican smokers who successfully quit smoking, consistent with treatment enhanced coaction. Integrating an alcohol intervention into cessation treatment did not reduce engagement in treatment, or hinder cessation outcomes, and positively impacted at-risk drinking among individuals who quit smoking. Findings of coaction between smoking and drinking speak to the promise of multiple health behavior change interventions for substance use treatment and chronic disease prevention

    Design of a randomized controlled trial for multiple cancer risk behaviors among Spanish-speaking Mexican-origin smokers

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    Background: Smoking, poor diet, and physical inactivity account for as much as 60% of cancer risk. Latinos experience profound disparities in health behaviors, as well as the cancers associated with them. Currently, there is a dearth of controlled trials addressing these health behaviors among Latinos. Further, to the best of our knowledge, no studies address all three behaviors simultaneously, are culturally sensitive, and are guided by formative work with the target population. Latinos represent 14% of the U. S. population and are the fastest growing minority group in the country. Efforts to intervene on these important lifestyle factors among Latinos may accelerate the elimination of cancer-related health disparities

    Search for squarks and gluinos with the ATLAS detector in final states with jets and missing transverse momentum using √s=8 TeV proton-proton collision data

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    A search for squarks and gluinos in final states containing high-p T jets, missing transverse momentum and no electrons or muons is presented. The data were recorded in 2012 by the ATLAS experiment in s√=8 TeV proton-proton collisions at the Large Hadron Collider, with a total integrated luminosity of 20.3 fb−1. Results are interpreted in a variety of simplified and specific supersymmetry-breaking models assuming that R-parity is conserved and that the lightest neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1330 GeV for a simplified model incorporating only a gluino and the lightest neutralino. For a simplified model involving the strong production of first- and second-generation squarks, squark masses below 850 GeV (440 GeV) are excluded for a massless lightest neutralino, assuming mass degenerate (single light-flavour) squarks. In mSUGRA/CMSSM models with tan β = 30, A 0 = −2m 0 and μ > 0, squarks and gluinos of equal mass are excluded for masses below 1700 GeV. Additional limits are set for non-universal Higgs mass models with gaugino mediation and for simplified models involving the pair production of gluinos, each decaying to a top squark and a top quark, with the top squark decaying to a charm quark and a neutralino. These limits extend the region of supersymmetric parameter space excluded by previous searches with the ATLAS detector
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