The relationship between attitudes, beliefs and physical activity in older adults with knee pain: secondary analysis of a randomised controlled trial

Objective To investigate how attitudes and beliefs about exercise relate to physical activity behavior in older adults with knee pain attributable to osteoarthritis (OA). Methods We conducted secondary data analyses of a randomized controlled trial of exercise interventions (ISRCTN: 93634563). Participants were adults ≥45 years old with knee pain attributable to OA (n = 514). Crude and adjusted cross‐sectional and longitudinal associations between baseline Self‐Efficacy for Exercise (SEE), Positive Outcome Expectations for Exercise (POEE), Negative Outcome Expectations for Exercise scores, and physical activity level, at baseline, 3 months, and 6 months (measured by self‐report using the Physical Activity Scale for the Elderly [PASE]), and important increases in physical activity level (from baseline to 6‐month followup) were investigated using multiple linear and logistic regression. Results Cross‐sectional associations were found between SEE and PASE scores (β = 4.14 [95% confidence interval (95% CI) 0.26, 8.03]) and POEE and PASE scores (β = 16.71 [95% CI 1.87, 31.55]), adjusted for sociodemographic and clinical covariates. Longitudinal associations were found between baseline SEE and PASE scores at 3 months (β = 4.95 [95% CI 1.02, 8.87]) and 6 months β = 3.71 (0.26, 7.16), and baseline POEE and PASE at 3 months (β = 34.55 [95% CI 20.13, 48.97]) and 6 months (β = 25.74 [95% CI 11.99, 39.49]), adjusted for baseline PASE score and intervention arm. However, no significant associations with important increases in physical activity level were found. Conclusion Greater exercise self‐efficacy and more positive exercise outcome expectations were associated with higher current and future physical activity levels. These may be targets for interventions aimed at increasing physical activity

Shiny app to predict agricultural tire dimensions

The main objective of this project, carried out in an industrial context, was to apply a multivariate analysis to variables related to the specifications required for the production of an agricultural tire and the dimensional test results. With the exploratory data analysis, it was possible to identify strong correlations between predictor variables and with the response variables of each test. In this project, the principal component analysis (PCA) serves to eliminate the effects of multicollinearity. The use of regression analysis was intended to predict the behavior of the agricultural tire considering the selected variables of each test. In the case of Test 1, when applying the Stepwise methods to select the variables, the model with the lowest value of Akaike Information Criterion (AIC) was achieved with the technique “Both”. However, the lowest value of AIC for Test 2 was achieved with “Backward”. Regarding the validation of assumptions, both Test 1 and Test 2 were validated. Therefore, all the quantitative variables are important, both in Test 1 and Test 2, because they are a linear combination that determines the principal components. In order to make it easier to compute predictions for future agricultural tires, an application that was developed in Shiny allows the company to know the behavior of the tire before it was produced. Using the application, it is possible to reduce the industrialization time, materials and resources, thus increasing efficiency and profits.This work has been supported by FCT – Fundação para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Patient-Centered Care: An Examination of Provider–Patient Communication Over Time

Objective: To examine the quality of provider communication over time considering the increasing emphasis on patient-centered care (PCC). Patient-centered care has been shown to have a positive impact on health outcomes, care experiences, quality-of-life, as well as decreased costs. Given this emphasis, we expect that provider–patient communication has improved over time. Data Source: We collected primary data by self-report surveys between summer 2017 and fall 2018. Study Design: We use a quantitative retrospective cohort study of a national sample of 353 patients who had an ostomy surgery. Data Extraction Method: We measure provider communication from open-ended self-reports from patients of the number of stated inadequacies in their care. Principal Findings: Results show that the time since patients had their surgery is related to higher quality provider communication. That is, patients who had their surgery further back in time reported higher quality provider communication compared with patients who had their surgery performed more recently. Conclusion: Results suggest that the quality of provider communication has not improved even with an emphasis on PCC.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research was funded by a “Graduate College Foundation Fellowship from the Department of Sociology and the Graduate College at the University of Oklahoma” to Leslie Miller. The funding does not impact the study in any way. Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

Detecting and correcting partial errors: Evidence for efficient control without conscious access

Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed

Reproductive health and lifestyle factors associated with health-related quality of life among perinatally HIV-infected adolescents in Uganda

Background With increased survival of perinatally HIV - infected adolescents due to antiretroviral therapy (ART), the focus of HIV care has shifted to health-related quality of life (HRQoL) as a measure of disease progression, effects of ART co-morbidity and prognosis. We assessed factors associated with better HRQoL in perinatally HIV -infected adolescents in Uganda by determining the associations between sexual and reproductive health (SRH) or lifestyle experiences on HRQoL. Methods In a cross-sectional study, data on SRH, lifestyle experiences, socio demographic factors, communication with parents on sexuality and satisfaction of SRH services in ART clinics were collected from 614 HIV perinatally infected adolescents aged 10–19 using an interviewer-administered survey questionnaire. HRQoL data were collected using the Medical Outcomes Study HIV Health Survey instrument (MOS-HIV). Factors associated with better HRQoL were analysed using multiple logistic regression. Results The mean age was 16.2 ± 2.1 years, 362 (58.8 %) were females and 210 (34.2 %) were sexually active. Adolescents on ART were twice likely to present with better physical health (AOR = 2.07, 95 % CI: 1.24–3.46) and four times more likely to present with better mental health (AOR = 3.9, 95 % CI: 2.22–6.92) than those who were not on ART. There were no statistically significant associations between SRH (ever had sex, ever been pregnant, condom use, contraceptive use) or life style factors and physical health or mental health. Those with secondary or tertiary education were more likely to present with a better mental health (AOR = 5.3, 95 % CI: 1.86–15.41) compared those who had attained primary or no education. Participants who desired to have a child in future more likely (AOR 1.7, 95 % CI: 1.05–3.00) to present with a better mental health. Lack of communication with guardians on sexuality (AOR = 0.6, 95 % CI: 0.40–0.89), or dissatisfaction with SRH services (AOR 0.34, 95 % CI: 0.18–0.62) were associated with poorer mental health. Conclusion Among perinatally HIV-infected adolescents in Uganda, being on ART was associated with better physical and mental health while lack of communication with guardians on sexuality or dissatisfaction with SRH services was associated with poor mental health. Adolescents with pregnancy intentions were more likely to have a better mental health

Statistical Power of Model Selection Strategies for Genome-Wide Association Studies

Genome-wide association studies (GWAS) aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the Comprehensive R Archive Network (CRAN) or http://bioinformatics.med.yale.edu/group/

Relationship Between Attitudes and Beliefs and Physical Activity in Older Adults With Knee Pain: Secondary Analysis of a Randomized Controlled Trial: Attitudes About Physical Activity in Older Adults With Knee Pain

OBJECTIVE:To investigate how attitudes and beliefs about exercise relate to physical activity behavior in older adults with knee pain attributable to osteoarthritis (OA).METHODS:We conducted secondary data analyses of a randomized controlled trial of exercise interventions (ISRCTN: 93634563). Participants were adults ≥45 years old with knee pain attributable to OA (n = 514). Crude and adjusted cross-sectional and longitudinal associations between baseline Self-Efficacy for Exercise (SEE), Positive Outcome Expectations for Exercise (POEE), Negative Outcome Expectations for Exercise scores, and physical activity level, at baseline, 3 months, and 6 months (measured by self-report using the Physical Activity Scale for the Elderly [PASE]), and important increases in physical activity level (from baseline to 6-month followup) were investigated using multiple linear and logistic regression.RESULTS:Cross-sectional associations were found between SEE and PASE scores (β = 4.14 [95% confidence interval (95% CI) 0.26, 8.03]) and POEE and PASE scores (β = 16.71 [95% CI 1.87, 31.55]), adjusted for sociodemographic and clinical covariates. Longitudinal associations were found between baseline SEE and PASE scores at 3 months (β = 4.95 [95% CI 1.02, 8.87]) and 6 months β = 3.71 (0.26, 7.16), and baseline POEE and PASE at 3 months (β = 34.55 [95% CI 20.13, 48.97]) and 6 months (β = 25.74 [95% CI 11.99, 39.49]), adjusted for baseline PASE score and intervention arm. However, no significant associations with important increases in physical activity level were found.CONCLUSION:Greater exercise self-efficacy and more positive exercise outcome expectations were associated with higher current and future physical activity levels. These may be targets for interventions aimed at increasing physical activity

Application of a Rule-Based Approach in Real-Time Crash Risk Prediction Model Development Using Loop Detector Data

Objectives: There is a growing trend in development and application of real-time crash risk prediction models within dynamic safety management systems. These real-time crash risk prediction models are constructed by associating crash data with the real-time traffic surveillance data (e.g. collected by loop detectors). The main objective of this paper is to develop a real-time risk model that will potentially be utilized within traffic management systems. This model aims to predict the likelihood of crash occurrence on motorways. Methods: In this study, the potential prediction variables are confined to traffic related characteristics. Given that the dependent variable (i.e. traffic safety condition) is dichotomous (i.e. “no-crash” or “crash”), a rule-based approach is considered for model development. The performance of rule-based classifiers is further compared with the more conventional techniques like binary logistic regression and decision trees. The crash and traffic data used in this study were collected between June 2009 and December 2011 on a part of the E313 motorway in Belgium between Geel-East and Antwerp-East exits, on the direction towards Antwerp. Results: The results of analysis show that several traffic flow characteristics such as traffic volume, average speed and standard deviation of speed at the upstream loop detector station, and the difference in average speed on upstream and downstream loop detector stations significantly contribute to the crash occurrence prediction. The final chosen classifier is able to predict 70% of crash occasions accurately while it correctly predicts 90% of no-crash instances, indicating a 10% false alarm rate. Conclusions: The findings of this study can be used to predict the likelihood of crash occurrence on motorways within dynamic safety management systems.This research was carried out within the framework of the Policy Research Centre on Traffic Safety with the support of the Flemish government and was partly supported by a grant from the Research Foundation Flanders (FWO). The content of this article is the sole responsibility of the authors.rule-based classifiers; real-time crash risk prediction; dynamic safety management systems; traffic surveillance data

The genomic features that affect the lengths of 5’ untranslated regions in multicellular eukaryotes

<p>Abstract</p> <p>Background</p> <p>The lengths of 5’UTRs of multicellular eukaryotes have been suggested to be subject to stochastic changes, with upstream start codons (uAUGs) as the major constraint to suppress 5’UTR elongation. However, this stochastic model cannot fully explain the variations in 5’UTR length. We hypothesize that the selection pressure on a combination of genomic features is also important for 5’UTR evolution. The ignorance of these features may have limited the explanatory power of the stochastic model. Furthermore, different selective constraints between vertebrates and invertebrates may lead to differences in the determinants of 5’UTR length, which have not been systematically analyzed.</p> <p>Methods</p> <p>Here we use a multiple linear regression model to delineate the correlation between 5’UTR length and the combination of a series of genomic features (G+C content, observed-to-expected (OE) ratios of uAUGs, upstream stop codons (uSTOPs), methylation-related CG/UG dinucleotides, and mRNA-destabilizing UU/UA dinucleotides) in six vertebrates (human, mouse, rat, chicken, African clawed frog, and zebrafish) and four invertebrates (fruit fly, mosquito, sea squirt, and nematode). The relative contributions of each feature to the variation of 5’UTR length were also evaluated.</p> <p>Results</p> <p>We found that 14%~33% of the 5’UTR length variations can be explained by a linear combination of the analyzed genomic features. The most important genomic features are the OE ratios of uSTOPs and G+C content. The surprisingly large weightings of uSTOPs highlight the importance of selection on upstream open reading frames (which include both uAUGs and uSTOPs), rather than on uAUGs <it>per se</it>. Furthermore, G+C content is the most important determinants for most invertebrates, but for vertebrates its effect is second to uSTOPs. We also found that shorter 5’UTRs are affected more by the stochastic process, whereas longer 5’UTRs are affected more by selection pressure on genomic features.</p> <p>Conclusions</p> <p>Our results suggest that upstream open reading frames may be the real target of selection, rather than uAUGs. We also show that the selective constraints on genomic features of 5’UTRs differ between vertebrates and invertebrates, and between longer and shorter 5’UTRs. A more comprehensive model that takes these findings into consideration is needed to better explain 5’UTR length evolution.</p