High Blood Pressure Before and During Early Pregnancy Is Associated With an Increased Risk of Gestational Diabetes Mellitus

OBJECTIVE—While women with prior gestational diabetes mellitus (GDM) are more likely to display features of the metabolic syndrome, including hypertension, in the years after delivery, it is unclear whether these components are also present before pregnancy. We examined the relationship between blood pressure (BP) measured before and during early pregnancy (<20 weeks) and the risk of GDM in a nested case-control study

Author Correction: A consensus-based transparency checklist.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

The Glasgow Norms:Ratings of 5,500 words on nine scales

The Glasgow Norms are a set of normative ratings for 5,553 English words on nine psycholinguistic dimensions: arousal, valence, dominance, concreteness, imageability, familiarity, age of acquisition, semantic size, and gender association. The Glasgow Norms are unique in several respects. First, the corpus itself is relatively large, while simultaneously providing norms across a substantial number of lexical dimensions. Second, for any given subset of words, the same participants provided ratings across all nine dimensions (33 participants/word, on average). Third, two novel dimensions—semantic size and gender association—are included. Finally, the corpus contains a set of 379 ambiguous words that are presented either alone (e.g., toast) or with information that selects an alternative sense (e.g., toast (bread), toast (speech)). The relationships between the dimensions of the Glasgow Norms were initially investigated by assessing their correlations. In addition, a principal component analysis revealed four main factors, accounting for 82% of the variance (Visualization, Emotion, Salience, and Exposure). The validity of the Glasgow Norms was established via comparisons of our ratings to 18 different sets of current psycholinguistic norms. The dimension of size was tested with megastudy data, confirming findings from past studies that have explicitly examined this variable. Alternative senses of ambiguous words (i.e., disambiguated forms), when discordant on a given dimension, seemingly led to appropriately distinct ratings. Informal comparisons between the ratings of ambiguous words and of their alternative senses showed different patterns that likely depended on several factors (the number of senses, their relative strengths, and the rating scales themselves). Overall, the Glasgow Norms provide a valuable resource—in particular, for researchers investigating the role of word recognition in language comprehension

A qualitative investigation of the impact of peer to peer online support for women living with Polycystic Ovary Syndrome

Background: Polycystic Ovary Syndrome is a common, chronic condition which affects women living with the condition both physically and psychologically. Social support may be beneficial to sufferers in coping with chronic conditions and the Internet is becoming a common place for accessing social support and information. The aim of this study was to consider the experiences of women living with Polycystic Ovary Syndrome who access and participate in an online support group discussion forum dedicated to issues surrounding this condition. Methods: Fifty participants responded to a series of open-ended questions via an online survey. Results: Thematic analysis revealed a number of empowering and disempowering experiences associated with online support group participation. The empowering processes reported by members of the group included: Connecting with others who understand; Access to information and advice; Interaction with healthcare professionals; Treatment-related decision making; Improved adjustment and management. In terms disempowering processes, only two were described by group participants: Reading about the negative experiences of others and Feeling like an outsider. Conclusions: For women living with Polycystic Ovary Syndrome, participation within an online support group may help to empower them in a range of important ways however, there may be some disempowering consequences

Discrete Emotion Effects on Lexical Decision Response Times

Our knowledge about affective processes, especially concerning effects on cognitive demands like word processing, is increasing steadily. Several studies consistently document valence and arousal effects, and although there is some debate on possible interactions and different notions of valence, broad agreement on a two dimensional model of affective space has been achieved. Alternative models like the discrete emotion theory have received little interest in word recognition research so far. Using backward elimination and multiple regression analyses, we show that five discrete emotions (i.e., happiness, disgust, fear, anger and sadness) explain as much variance as two published dimensional models assuming continuous or categorical valence, with the variables happiness, disgust and fear significantly contributing to this account. Moreover, these effects even persist in an experiment with discrete emotion conditions when the stimuli are controlled for emotional valence and arousal levels. We interpret this result as evidence for discrete emotion effects in visual word recognition that cannot be explained by the two dimensional affective space account

A consensus-based transparency checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository

Checking and bootstrapping lexical norms by means of word similarity indexes

In psychology, lexical norms related to the se- mantic properties of words, such as concreteness and va- lence, are important research resources. Collecting such norms by asking judges to rate the words is very time consuming, which strongly limits the number of words that compose them. In the present article, we present a technique for estimating lexical norms based on the latent semantic analysis of a corpus. The analyses conducted emphasize the technique’s effectiveness for several semantic dimensions. In addition to the extension of norms, this technique can be used to check human ratings to identify words for which the rating is very different from the corpus-based estimate