Monthly Archives: October 2018

Spousal Support for Patients With Rheumatoid Arthritis: Getting the Wrong Kind Is a Pain.






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Spousal Support for Patients With Rheumatoid Arthritis: Getting the Wrong Kind Is a Pain.
Front Psychol. 2018;9:1760
Authors: Pow J, Stephenson E, Hagedoorn M, DeLongis A
Abstract
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Mindfulness-based stress reduction for menopausal symptoms after risk-reducing salpingo-oophorectomy (PURSUE study): a randomized controlled trial.






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Mindfulness-based stress reduction for menopausal symptoms after risk-reducing salpingo-oophorectomy (PURSUE study): a randomized controlled trial.
BJOG. 2018 Sep 17;:
Authors: van Driel CMG, de Bock… Continue reading

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Does Twitter language reliably predict heart disease? A commentary on Eichstaedt et al. (2015a).






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Does Twitter language reliably predict heart disease? A commentary on Eichstaedt et al. (2015a).

PeerJ. 2018;6:e5656

Authors: Brown NJL, Coyne JC

Abstract
We comment on Eichstaedt et al.’s (2015a) claim to have shown that language patterns among Twitter users, aggregated at the level of US counties, predicted county-level mortality rates from atherosclerotic heart disease (AHD), with “negative” language being associated with higher rates of death from AHD and “positive” language associated with lower rates. First, we examine some of Eichstaedt et al.’s apparent assumptions about the nature of AHD, as well as some issues related to the secondary analysis of online data and to considering counties as communities. Next, using the data files supplied by Eichstaedt et al., we reproduce their regression- and correlation-based models, substituting mortality from an alternative cause of death-namely, suicide-as the outcome variable, and observe that the purported associations between “negative” and “positive” language and mortality are reversed when suicide is used as the outcome variable. We identify numerous other conceptual and methodological limitations that call into question the robustness and generalizability of Eichstaedt et al.’s claims, even when these are based on the results of their ridge regression/machine learning model. We conclude that there is no good evidence that analyzing Twitter data in bulk in this way can add anything useful to our ability to understand geographical variation in AHD mortality rates.

PMID: 30258732 [PubMed]

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A Close Examination of the Relationship Between Self-Compassion and Depressive Symptoms.






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A Close Examination of the Relationship Between Self-Compassion and Depressive Symptoms.

Mindfulness (N Y). 2018;9(5):1470-1478

Authors: López A, Sanderman R, Schroevers MJ

Abstract
Self-compassion has shown to be beneficial for individuals’ wellbeing; in particular, it has been associated with lower levels of depressive symptoms. The purpose of this study was to further explore the association between self-compassion, as measured by the Self-Compassion Scale (SCS), and depressive symptoms, in a large representative sample of community adults (n = 734, Mean age = 55.7, SD = 15.2). We examined the association of depressive symptoms with the SCS total score, the SCS six subscales (i.e., self-kindness, common humanity, mindfulness, self-judgment, isolation, and over-identification), and the SCS positive and negative items (referred to as self-compassion and self-coldness, respectively). In addition, we explored the predictive ability of self-compassion, self-coldness, and the SCS six subscales on depressive symptoms both cross-sectionally and over a 1-year period of time. Finally, we sought to test the moderating role of self-compassion on the association between self-coldness and depressive symptoms. Results showed that the SCS negative items and subscales were more strongly related to depressive symptoms than the SCS positive items and subscales. Accordingly, self-coldness was a stronger predictor of depressive symptoms, cross-sectionally and over a 1-year timeframe, when compared with self-compassion. Particularly, the feeling of being isolated was shown to be strongly associated with depressive symptoms. We did not find substantial evidence for a moderating role of self-compassion on the association between self-coldness and depressive symptoms. Future research needs to determine the added value of assessing self-coldness and whether or not it is an essential part of self-compassion.

PMID: 30294388 [PubMed]

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