Validation of the Yoruba Version of the Pain Self-Efficacy Questionnaire in patients with chronic low back pain

STUDY DESIGN: Cultural adaptation and psychometric analysis. OBJECTIVE: This study determined the test-retest reliability, acceptability, internal consistency, divergent validity of the Yoruba pain self-efficacy questionnaire (PSEQ-Y). It also examined the ceiling and floor effects and the small detectable change (SDC) of the PSEQ-Y among patients with chronic low back pain (LBP). SUMMARY OF BACKGROUND DATA: There are various indigenous language translations of the PSEQ and none adapted to African language. However, translations of the PSEQ into Nigerian languages are not readily available. METHODS: The validity testing phase of the study involved 131 patients with LBP, while 83 patients with LBP took part in the reliability phase. Following the Beaton recommendation for cultural adaptation of instruments, the PSEQ was adapted into the Yoruba language. The psychometric properties of the PSEQ-Y determined comprised: internal consistency, divergent validity, test-retest reliability, and SDC. RESULTS: The mean age of the participants was 52.96 ± 17.3 years. The PSEQ-Y did not correlate with the Yoruba version of Visual Analogue Scale (VAS-Y) scores (r = -0.05; P = 0.59). The values for the internal consistency and the test-retest reliability of the PSEQ-Y were 0.79 and 0.86, with the 95% confidence interval of the test-retest reliability ranging between 0.82 and 0.90. The standard error of measurement (SEM) and the SDC of the PSEQ-Y were 1.2 and 3.3, respectively. The PSEQ-Y had no floor or ceiling effect, as none of the respondents scored either the minimal or maximal scores. CONCLUSION: This is the first study in Nigeria to culturally adapt PSEQ. The PSEQ-Y showed adequate psychometric properties similar to existing versions. Therefore, the tool can be used to assess pain self-efficacy in clinical and research settings and help to improve the health outcomes of patients chronic LBP.Level of Evidence: 3

Translation, cross-cultural adaptation and psychometric evaluation of Yoruba version of the short-form 12 health survey

Background. Short Form 12 (SF-12) health survey has found its utility in clinical and research settings because of its short length that spares time. Though several translations into other languages do exist there is none available in Yoruba language. Hence, this study’s objective was to culturally adapt and determine the reliability and validity of the Yoruba translated version of the SF-12. Methods. Forward and backward translations of SF-12 into Yoruba version of SF-12 (Y-SF-12) were done using the International Quality of Life Assessment Project Guidelines. Healthy participants were assessed using both English and Yoruba versions of SF-12 for the validation phase, and two weeks later were reassessed with the Y-SF-12 for the reliability phase. Results. Participants were 225 males and 171 females. The mean scores for each scale range from 73.4 to 86.1, with no gender difference. All scale and domain scores evidenced a negative skew and ranges from -1.79 to -0.62. Concurrent validity (0.879 – 0.938) and convergent validity (0.786 – 0.907) appeared to be good as reflected by their correlation values. The internal consistency of Y-SF-12 was good as Cronbach’s Alpha ranged between 0.899 and 0.968, while the Intraclass Correlation Coefficient (ICC) ranged between 0.775 and 0.949. Conclusion. This is the first study to assess the psychometric properties of the Y-SF-12. It appears to be valid and may be an appropriate tool for assessing health-related quality of life among Yoruba population. The tool may help to improve the health outcomes of individuals, and redress health inequalities in low and middle-income countries

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Central Source In Super-nova Remnant G127.1+0.5

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62859/1/276480a0.pd

The Racial/Ethnic Distribution of Heat Risk–Related Land Cover in Relation to Residential Segregation

Objective: We examined the distribution of heat risk–related land cover (HRRLC) characteristics across racial/ethnic groups and degrees of residential segregation. Methods: Block group–level tree canopy and impervious surface estimates were derived from the 2001 National Land Cover Dataset for densely populated urban areas of the United States and Puerto Rico, and linked to demographic characteristics from the 2000 Census. Racial/ethnic groups in a given block group were considered to live in HRRLC if at least half their population experienced the absence of tree canopy and at least half of the ground was covered by impervious surface (roofs, driveways, sidewalks, roads). Residential segregation was characterized for metropolitan areas in the United States and Puerto Rico using the multigroup dissimilarity index. Results: After adjustment for ecoregion and precipitation, holding segregation level constant, non-Hispanic blacks were 52% more likely (95% CI: 37%, 69%), non-Hispanic Asians 32% more likely (95% CI: 18%, 47%), and Hispanics 21% more likely (95% CI: 8%, 35%) to live in HRRLC conditions compared with non-Hispanic whites. Within each racial/ethnic group, HRRLC conditions increased with increasing degrees of metropolitan area-level segregation. Further adjustment for home ownership and poverty did not substantially alter these results, but adjustment for population density and metropolitan area population attenuated the segregation effects, suggesting a mediating or confounding role. Conclusions: Land cover was associated with segregation within each racial/ethnic group, which may be explained partly by the concentration of racial/ethnic minorities into densely populated neighborhoods within larger, more segregated cities. In anticipation of greater frequency and duration of extreme heat events, climate change adaptation strategies, such as planting trees in urban areas, should explicitly incorporate an environmental justice framework that addresses racial/ethnic disparities in HRRLC

Spatial distribution of surface temperature and land cover: A study concerning Sardinia, Italy

Land surface temperature (LST) is a key climate variable that has been studied mainly at the urban scale and in the context of urban heat islands. By analyzing the connection between LST and land covers, this study shows the potential of LST to analyze the relation between urbanization and heating phenomena at the regional level. Land cover data, drawn from Copernicus, and LST, retrieved from Landsat 8 satellite images, are analyzed through a methodology that couples GIS and regression analysis. By looking at the Italian island of Sardinia as a case study, this research shows that urbanization and the spatial dynamics of heating phenomena are closely connected, and that intensively farmed areas behave quite similarly to urban areas, whereas forests are the most effective land covers in mitigating LST, followed by areas covered with Mediterranean shrubs. This leads to key policy recommendations that decision makers could implement to mitigate LST at the regional scale and that can, in principle, be exported to regions with similar climate and land covers. The significance of this study can be summed up in a novel approach to analyze the relationship between LST and land covers that uses freely available spatial data and therefore can easily be replicated in other regional contexts to derive appropriate policy recommendations