304 research outputs found

    Differences between immigrant and non-immigrant groups in the use of primary medical care; a systematic review

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    Background. Studies on differences between immigrant and non-immigrant groups in health care utilization vary with respect to the extent and direction of differences in use. Therefore, our study aimed to provide a systematic overview of the existing research on differences in primary care utilization between immigrant groups and the majority population. Methods. For this review PubMed, PsycInfo, Cinahl, Sociofile, Web of Science and Current Contents were consulted. Study selection and quality assessment was performed using a predefined protocol by 2 reviewers independently of each other. Only original, quantitative, peer-reviewed papers were taken into account. To account for this hierarchical structure, logistic multilevel analyses were performed to examine the extent to which differences are found across countries and immigrant groups. Differences in primary care use were related to study characteristics, strength of the primary care system and methodological quality. Results. A total of 37 studies from 7 countries met all inclusion criteria. Remarkably, studies performed within the US more often reported a significant lower use among immigrant groups as compared to the majority population than the other countries. As studies scored higher on methodological quality, the likelihood of reporting significant differences increased. Adjustment for health status and use of culture-/language-adjusted procedures during the data

    Heterogeneity in Health Insurance Coverage Among US Latino Adults

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    We sought to determine the differences in observed and unobserved factors affecting rates of health insurance coverage between US Latino adults and US Latino adults of Mexican ancestry. Our hypothesis was that Latinos of Mexican ancestry have worse health insurance coverage than their non-Mexican Latino counterparts. The National Health Interview Survey (NHIS) database from 1999–2007 consists of 33,847 Latinos. We compared Latinos of Mexican ancestry to non-Mexican Latinos in the initial descriptive analysis of health insurance coverage. Disparities in health insurance coverage across Latino categories were later analyzed in a multivariable logistic regression framework, which adjusts for confounding variables. The Blinder-Oaxaca technique was applied to parse out differences in health insurance coverage into observed and unobserved components. US Latinos of Mexican ancestry consistently had lower rates of health insurance coverage than did US non-Mexican Latinos. Approximately 65% of these disparities can be attributed to differences in observed characteristics of the Mexican ancestry population in the US (e.g., age, sex, income, employment status, education, citizenship, language and health condition). The remaining disparities may be attributed to unobserved heterogeneity that may include unobserved employment-related information (e.g., type of employment and firm size) and behavioral and idiosyncratic factors (e.g., risk aversion and cultural differences). This study confirmed that Latinos of Mexican ancestry were less likely to have health insurance than were non-Mexican Latinos. Moreover, while differences in observed socioeconomic and demographic factors accounted for most of these disparities, the share of unobserved heterogeneity accounted for 35% of these differences

    Rasch analysis of the Psychiatric Out-Patient Experiences Questionnaire (POPEQ)

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    <p>Abstract</p> <p>Background</p> <p>The Psychiatric Out-Patient Experiences Questionnaire (POPEQ) is an 11-item core measure of psychiatric out-patients experiences of the perceived outcome of the treatment, the quality of interaction with the clinician, and the quality of information provision. The POPEQ was found to have evidence for reliability and validity following the application of classical test theory but has not previously been assessed by Rasch analysis.</p> <p>Methods</p> <p>Two national postal surveys of psychiatric outpatients took place in Norway in 2004 and 2007. The performance of the POPEQ, including item functioning and differential item functioning, was assessed by Rasch analysis. Principal component analysis of item residuals was used to assess the presence of subdimensions.</p> <p>Results</p> <p>6,677 (43.3%) and 11,085 (35.2%) psychiatric out patients responded to the questionnaire in 2004 and 2007, respectively. All items in the scale were retained after the Rasch analysis. The resulting scale had reasonably good fit to the Rasch model. The items performed the same for the two survey years and there was no differential item functioning relating to patient characteristics. Principal component analysis of the residuals confirmed that the measure to a high degree is unidimensional. However, the data also reflects three potential subscales, each relating to one of the three included aspects of health care.</p> <p>Conclusions</p> <p>The POPEQ had excellent psychometric properties and Rasch analysis further supported the construct validity of the scale by also identifying the three subdimensions originally included as components in the instrument development. The 11-item instrument is recommended in future research on psychiatric out-patient experiences. Future development may lead to the construction of more precise measures of the three subdomains that the POPEQ is based on.</p

    Decrypting magnetic fabrics (AMS, AARM, AIRM) through the analysis of mineral shape fabrics and distribution anisotropy

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    The fieldwork was supported by the DIPS project (grant no. 240467) and the MIMES project (grant no. 244155) funded by the Norwegian Research Council awarded to O.G. O.P.'s position was funded from Y-TEC.Anisotropy of magnetic susceptibility (AMS) and anisotropy of magnetic remanence (AARM and AIRM) are efficient and versatile techniques to indirectly determine rock fabrics. Yet, deciphering the source of a magnetic fabric remains a crucial and challenging step, notably in the presence of ferrimagnetic phases. Here we use X-ray micro-computed tomography to directly compare mineral shape-preferred orientation and spatial distribution fabrics to AMS, AARM and AIRM fabrics from five hypabyssal trachyandesite samples. Magnetite grains in the trachyandesite are euhedral with a mean aspect ratio of 1.44 (0.24 s.d., long/short axis), and > 50% of the magnetite grains occur in clusters, and they are therefore prone to interact magnetically. Amphibole grains are prolate with magnetite in breakdown rims. We identified three components of the petrofabric that influence the AMS of the analyzed samples: the magnetite and the amphibole shape fabrics and the magnetite spatial distribution. Depending on their relative strength, orientation and shape, these three components interfere either constructively or destructively to produce the AMS fabric. If the three components are coaxial, the result is a relatively strongly anisotropic AMS fabric (P’ = 1.079). If shape fabrics and/or magnetite distribution are non-coaxial, the resulting AMS is weakly anisotropic (P’ = 1.012). This study thus reports quantitative petrofabric data that show the effect of magnetite distribution anisotropy on magnetic fabrics in igneous rocks, which has so far only been predicted by experimental and theoretical models. Our results have first-order implications for the interpretation of petrofabrics using magnetic methods.Publisher PDFPeer reviewe

    Are health care professionals able to judge cancer patients' health care preferences correctly? A cross-sectional study

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    Background: Health care for cancer patients is primarily shaped by health care professionals. This raises the question to what extent health care professionals are aware of patients' preferences, needs and values. The aim of this study was to explore to what extent there is concordance between patients' preferences in cancer care and patients' preferences as estimated by health care professionals. We also examined whether there were gender differences between health care professionals with regard to the degree in which they can estimate patients' preferences correctly. Methods: To obtain unbiased insight into the specific preferences of cancer patients, we developed the 'Cancer patients' health care preferences' questionnaire'. With this questionnaire we assessed a large sample of cancer patients (n = 386). Next, we asked health care professionals (medical oncologists, nurses and policymakers, n = 60) to fill out this questionnaire and to indicate preferences they thought cancer patients would have. Mean scores between groups were compared using Mann-Whitney tests. Effect sizes (ESs) were calculated for statistically significant differences. Results: We found significant differences (ESs 0.31 to 0.90) between patients and professionals for eight out of twenty-one scales and two out of eight single items. Patients valued care aspects related to expertise and attitude of health care providers and accessibility of services as more important than the professionals thought they would do. Health care professionals overestimated the value that patients set on particularly organisational and environmental aspects. We found significant gender-related differences between the professionals (ESs 0.69 to 1.39) for eight out of twenty-one scales and two out of eight single items. When there were significant differences between male and female healthcare professionals in their estimation of patients health care preferences, female health care professionals invariably had higher scores. Generally, female health care professionals did not estimate patients' preferences and needs better than their male colleagues. Conclusions: Health care professionals are reasonably well able to make a correct estimation of patients preferences, but they should be aware of their own bias and use additional resources to gain a better understanding of patients' specific preferences for each patient is different and ultimately the care needs and preferences will also be unique to the person
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