PeerJ
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Fibromyalgia is a syndrome characterized by the presence of widespread chronic pain. People with fibromyalgia report lower levels of Positive Affect and higher levels of Negative Affect than non-fibromyalgia peers. The Positive and Negative Affect Schedule (PANAS)-a widely used questionnaire to assess two core domains of affect; namely 'Positive Affect' and 'Negative Affect' -has a controversial factor structure varying across studies. The internal structure of a measurement instrument has an impact on the meaning and validity of its score. Therefore, the aim of the present study was to assess the structural construct validity of the PANAS in adult women with fibromyalgia. ⋯ The present study demonstrates that both Positive Affect and Negative Affect are core dimensions of affect in adult women with fibromyalgia. A structure with two correlated factors of the PANAS emerged from our sample of women with fibromyalgia from Andalusia (Southern Spain). In this model, the amount of variance shared by Positive Affect and Negative Affect was small. Therefore, our findings support to use and interpret the Positive Affect and Negative Affect subscales of the PANAS as separate factors that are associated but distinctive as well.
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Early detection of social anxiety and loneliness might be useful to prevent substantial impairment in personal relationships. Understanding the way people use smartphones can be beneficial for implementing an early detection of social anxiety and loneliness. This paper examines different types of smartphone usage and their relationships with people with different individual levels of social anxiety or loneliness. ⋯ This paper finds that there exists certain correlation among smartphone usage and social anxiety and loneliness. The result may be useful to improve social interaction for those who lack social interaction in daily lives and may be insightful for recognizing individual levels of social anxiety and loneliness through smartphone usage behaviors.
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Background. Physician wellness is a vital element of a well-functioning health care system. Not only is physician wellness empirically associated with quality and patient outcomes, but its ramifications span individual, interpersonal, organizational, and societal levels. ⋯ Our findings indicate that the factors that enhance professional fulfillment and those that precipitate burnout are distinct: motivation and quality of work performed were supported by domains intrinsic to the work itself, whereas external dysfunctional work aspects resulted in frustration. Thus, it can be anticipated that optimization of physician wellness would require tailored approaches in each of these dimensions with sustained funding and support for wellness initiatives. Physicians identified the availability of resources to enable them to thrive and provide excellent patient care as their most important wellness-enhancing factor.
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We apply a novel mistake index to assess trends in the proportion of corrections published between 1993 and 2014 in Nature, Science and PNAS. The index revealed a progressive increase in the proportion of corrections published in these three high-quality journals. The index appears to be independent of the journal impact factor or the number of items published, as suggested by a comparative analyses among 16 top scientific journals of different impact factors and disciplines. ⋯ According to the three categories established, 34.7% of the corrections were considered mild, 47.7% moderate and 17.6% severe, also differing among journals. Errors occurring during the printing process were responsible for 5% of corrections in Nature, 3% in Science and 18% in PNAS. The measurement of the temporal trends in the quality of scientific manuscripts can assist editors and reviewers in identifying the most common mistakes, increasing the rigor of peer-review and improving the quality of published scientific manuscripts.
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Problems in using p-curve analysis and text-mining to detect rate of p-hacking and evidential value.
Background. The p-curve is a plot of the distribution of p-values reported in a set of scientific studies. Comparisons between ranges of p-values have been used to evaluate fields of research in terms of the extent to which studies have genuine evidential value, and the extent to which they suffer from bias in the selection of variables and analyses for publication, p-hacking. ⋯ Furthermore, while studies with evidential value will usually generate a right-skewed p-curve, we cannot treat a right-skewed p-curve as an indicator of the extent of evidential value, unless we have a model specific to the type of p-values entered into the analysis. We conclude that it is not feasible to use the p-curve to estimate the extent of p-hacking and evidential value unless there is considerable control over the type of data entered into the analysis. In particular, p-hacking with ghost variables is likely to be missed.