87 resultados para Linear factor model
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Purposes: The first objective was to propose a new model representing the balance level of adults with intellectual and developmental disabilities (IDD) using Principal Components Analysis (PCA); and the second objective was to use the results from the PCA recorded by regression method to construct and validate summative scales of the standardized values of the index, which may be useful to facilitate a balance assessment in adults with IDD. Methods: A total of 801 individuals with IDD (509 males) mean 33.1±8.5 years old, were recruited from Special Olympic Games in Spain 2009 to 2012. The participants performed the following tests: the timed-stand test, the single leg stance test with open and closed eyes, the Functional Reach Test, the Expanded Timed-Get-up-and-Go Test. Data was analyzed using principal components analysis (PCA) with Oblimin rotation and Kaiser normalization. We examined the construct validity of our proposed two-factor model underlying balance for adults with IDD. The scores from PCA were recorded by regression method and were standardized. Results: The Component Plot and Rotated Space indicated that a two-factor solution (Dynamic and Static Balance components) was optimal. The PCA with direct Oblimin rotation revealed a satisfactory percentage of total variance explained by the two factors: 51.6 and 21.4%, respectively. The median score standardized for component dynamic and static of the balance index for adults with IDD is shown how references values. Conclusions: Our study may lead to improvements in the understanding and assessment of balance in adults with IDD. First, it confirms that a two-factor model may underlie the balance construct, and second, it provides an index that may be useful for identifying the balance level for adults with IDD.
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This study reported on the validation of the psychometric properties, the factorability, validity, and sensitivity of the Dysexecutive Questionnaire (DEX) in 3 clinical and nonclinical samples. A mixed sample of 997 participants—community (n = 663), psychiatric (depressed [n = 92] and anxious [n = 122]), and neurologically impaired (n = 120)—completed self-report questionnaires assessing executive dysfunction, depression, anxiety, stress, general self-efficacy, and satisfaction with life. Before analyses the data were randomly split into 2 subsets (A and B). Exploratory factor analysis performed on Subset A produced a 3-factor model (Factor 1: Inhibition, Factor 2: Volition, and Factor 3: Social Regulation) in which 15 of the original 20 items provided a revised factor structure that was superior to all other structures. A series of confirmatory factor analyses performed on Subset B confirmed that this revised factor structure was valid and reliable. The revised structure, labeled the DEX-R, was found to be a reliable and valid tool for assessing behavioral symptoms of dysexecutive functioning in mixed community, psychiatric, and neurological samples.
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Abstract Background The purpose of this study was the development of a valid and reliable “Mechanical and Inflammatory Low Back Pain Index” (MIL) for assessment of non-specific low back pain (NSLBP). This 7-item tool assists practitioners in determining whether symptoms are predominantly mechanical or inflammatory. Methods Participants (n = 170, 96 females, age = 38 ± 14 years-old) with NSLP were referred to two Spanish physiotherapy clinics and completed the MIL and the following measures: the Roland Morris Questionnaire (RMQ), SF-12 and “Backache Index” (BAI) physical assessment test. For test-retest reliability, 37 consecutive patients were assessed at baseline and three days later during a non-treatment period. Face and content validity, practical characteristics, factor analysis, internal consistency, discriminant validity and convergent validity were assessed from the full sample. Results A total of 27 potential items that had been identified for inclusion were subsequently reduced to 11 by an expert panel. Four items were then removed due to cross-loading under confirmatory factor analysis where a two-factor model yielded a good fit to the data (χ2 = 14.80, df = 13, p = 0.37, CFI = 0.98, and RMSEA = 0.029). The internal consistency was moderate (α = 0.68 for MLBP; 0.72 for ILBP), test-retest reliability high (ICC = 0.91; 95%CI = 0.88-0.93) and discriminant validity good for either MLBP (AUC = 0.74) and ILBP (AUC = 0.92). Convergent validity was demonstrated through similar but weak correlations between the ILBP and both the RMQ and BAI (r = 0.34, p < 0.001) and the MLBP and BAI (r = 0.38, p < 0.001). Conclusions The MIL is a valid and reliable clinical tool for patients with NSLBP that discriminates between mechanical and inflammatory LBP. Keywords: Low back pain; Psychometrics properties; Pain measurement; Screening tool; Inflammatory; Mechanical
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Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.
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The implicit structure of positive character traits was examined in two studies of 190 and 100 undergraduates. Participants judged the pairwise covariation or semantic similarity of 42 positive characteristics using a sorting or a rating task. Characteristics were drawn from a new classification of strengths and virtues, the Five-Factor Model, and a taxonomy of values. Participants showed consistent patterns of perceived association among the characteristics across the study conditions. Multidimensional scaling yielded three consistent dimensions underlying these judgments (“warmth vs. self-control,” “vivacity vs. decency,” and “wisdom vs. power”). Cluster analyses yielded six consistent groupings—“self-control,” “love,” “wisdom,” “drive,” “vivacity,” and “collaboration”—that corresponded only moderately to the virtue classification. All three taxonomies were systematically related to this implicit structure, but none captured it satisfactorily on its own. Revisions to positive psychology’s classification of strengths are proposed.
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Background Foot dorsiflexion plays an essential role in both controlling balance and human gait. Electromyography (EMG) and sonomyography (SMG) can provide information on several aspects of muscle function. The aim was to establish the relationship between the EMG and SMG variables during isotonic contractions of foot dorsiflexors. Methods Twenty-seven healthy young adults performed the foot dorsiflexion test on a device designed ad hoc. EMG variables were maximum peak and area under the curve. Muscular architecture variables were muscle thickness and pennation angle. Descriptive statistical analysis, inferential analysis and a multivariate linear regression model were carried out. The confidence level was established with a statistically significant p-value of less than 0.05. Results The correlation between EMG variables and SMG variables was r = 0.462 (p < 0.05). The linear regression model to the dependent variable “peak normalized tibialis anterior (TA)” from the independent variables “pennation angle and thickness”, was significant (p = 0.002) with an explained variance of R2 = 0.693 and SEE = 0.16. Conclusions There is a significant relationship and degree of contribution between EMG and SMG variables during isotonic contractions of the TA muscle. Our results suggest that EMG and SMG can be feasible tools for monitoring and assessment of foot dorsiflexors. TA muscle parameterization and assessment is relevant in order to know that increased strength accelerates the recovery of lower limb injuries.
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Objectives Mental health workers are constantly exposed to their clients’ stories of distress and trauma. While listening to these stories can be emotionally draining, professionals in this field still derive pleasure from their work. This study examined the role of personality and workplace belongingness in predicting compassion satisfaction, secondary traumatic stress, and burnout in mental health professionals. Methods Mental health staff (N = 156) working in a counselling service completed a questionnaire that included measures relating to professional quality of life, the Five-Factor Model of personality, workplace belongingness, as well as questions relating to the participants’ demographic profile, work roles and trauma history. Results The results indicated that, high levels of emotional stability (low neuroticism), extraversion, agreeableness, conscientiousness, and being connected at work, are essential factors that promote the professional quality of life of mental health workers. Specifically, workplace belongingness was the strongest predictor of compassion satisfaction and low levels of burnout, while neuroticism was the strongest predictor of secondary traumatic stress. Conclusions Important implications from this study include: (1) encouraging mental health staff to increase self-awareness of their dispositional characteristics and how their personalities affect their wellbeing at work, and; (2) encouraging management to facilitate practices where mental health workers feel connected, respected, and supported in their organisation.
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Background Understanding the relationship between extreme weather events and childhood hand, foot and mouth disease (HFMD) is important in the context of climate change. This study aimed to quantify the relationship between extreme precipitation and childhood HFMD in Hefei, China, and further, to explore whether the association varied across urban and rural areas. Methods Daily data on HFMD counts among children aged 0–14 years from 2010 January 1st to 2012 December 31st were retrieved from Hefei Center for Disease Control and Prevention. Daily data on mean temperature, relative humidity and precipitation during the same period were supplied by Hefei Bureau of Meteorology. We used a Poisson linear regression model combined with a distributed lag non-linear model to assess the association between extreme precipitation (≥ 90th precipitation) and childhood HFMD, controlling for mean temperature, humidity, day of week, and long-term trend. Results There was a statistically significant association between extreme precipitation and childhood HFMD. The effect of extreme precipitation on childhood HFMD was the greatest at six days lag, with a 5.12% (95% confident interval: 2.7–7.57%) increase of childhood HFMD for an extreme precipitation event versus no precipitation. Notably, urban children and children aged 0–4 years were particularly vulnerable to the effects of extreme precipitation. Conclusions Our findings indicate that extreme precipitation may increase the incidence of childhood HFMD in Hefei, highlighting the importance of protecting children from forthcoming extreme precipitation, particularly for those who are young and from urban areas.
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Background The number of citations received by an article is considered as an objective marker judging the importance and the quality of the research work. The present study aims to study the determinants of citations for research articles published by Sri Lankan authors. Methods Papers were selectively retrieved from the SciVerse Scopus® (Elsevier Properties S.A, USA) database for 10 years from 1st January 1997 to 31st December 2006, of which 50% were selected for inclusion by simple random sampling. The primary outcome measure was citation rate (defined as the number of citations during the 2 subsequent years after publication). Citation data was collected using the SciVerse Scopus® Citation Analyzer and self citations were excluded. A linear regression analysis was performed with ‘number of citations’ as the continuous dependent variable and other independent variables. Result The number of publications has steadily increased during the period of study. Over three quarter of papers were published in international journals. More than half of publications were research studies (55.3%), and most of the research studies were descriptive cross-sectional studies (27.1%). The mean number of citations within 2 years of publication was 1.7 and 52.1% of papers were not cited within the first two years of publication. The mean number of citations for collaborative studies (2.74) was significantly higher than that of non-collaborative studies (0.66). The mean number of citations did not significantly change depending on whether the publication had a positive result (2.08) or not (2.92) and was also not influenced by the presence (2.30) or absence (1.99) of the main study conclusion in the title of the article. In the linear regression model, the journal rank, number of authors, conducting the study abroad, being a research study or systematic review/meta-analysis and having regional and/or international collaboration all significantly increased the number of citations. Conclusion The journal rank, number of authors, conducting the study abroad, being a research study or systematic review/meta-analysis and having regional and/or international collaboration all significantly increased the number of citations. However, the presence of a positive result in the study did not influence the citation rate.
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Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.
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With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.
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Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.
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Purpose The aim of this study was to determine alterations to the corneal subbasal nerve plexus (SNP) over four years using in vivo corneal confocal microscopy (IVCM) in participants with type 1 diabetes and to identify significant risk factors associated with these alterations. Methods A cohort of 108 individuals with type 1 diabetes and no evidence of peripheral neuropathy at enrollment underwent laser-scanning IVCM, ocular screening, and health and metabolic assessment at baseline and the examinations continued for four subsequent annual visits. At each annual visit, eight central corneal images of the SNP were selected and analyzed to quantify corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL). Linear mixed model approaches were fitted to examine the relationship between risk factors and corneal nerve parameters. Results A total of 96 participants completed the final visit and 91 participants completed all visits. No significant relationships were found between corneal nerve parameters and time, sex, duration of diabetes, smoking, alcohol consumption, blood pressure or BMI. However, CNFD was negatively associated with HbA1c (β=-0.76, P<0.01) and age (β=-0.13, P<0.01) and positively related to high density lipids (HDL) (β=2.01, P=0.03). Higher HbA1c (β=-1.58, P=0.04) and age (β=-0.23, P<0.01) also negatively impacted CNBD. CNFL was only affected by higher age (β=-0.06, P<0.01). Conclusions Glycemic control, HDL and age have significant effects on SNP structure. These findings highlight the importance of diabetic management to prevent corneal nerve damage as well as the capability of IVCM for monitoring subclinical alterations in the corneal SNP in diabetes.
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Introduction: Extreme heat events (both heat waves and extremely hot days) are increasing in frequency and duration globally and cause more deaths in Australia than any other extreme weather event. Numerous studies have demonstrated a link between extreme heat events and an increased risk of morbidity and death. In this study, the researchers sought to identify if extreme heat events in the Tasmanian population were associated with any changes in emergency department admissions to the Royal Hobart Hospital (RHH) for the period 2003-2010. Methods: Non-identifiable RHH emergency department data and climate data from the Australian Bureau of Meteorology were obtained for the period 2003-2010. Statistical analyses were conducted using the computer statistical computer software ‘R’ with a distributed lag non-linear model (DLNM) package used to fit a quassi-Poisson generalised linear regression model. Results: This study showed that RR of admission to RHH during 2003-2010 was significant over temperatures of 24 C with a lag effect lasting 12 days and main effect noted one day after the extreme heat event. Discussion: This study demonstrated that extreme heat events have a significant impact on public hospital admissions. Two limitations were identified: admissions data rather than presentations data were used and further analysis could be done to compare types of admissions and presentations between heat and non-heat events. Conclusion: With the impacts of climate change already being felt in Australia, public health organisations in Tasmania and the rest of Australia need to implement adaptation strategies to enhance resilience to protect the public from the adverse health effects of heat events and climate change.