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Crucial tactics within scholarly creating coaching with regard to doctor regarding nursing practice pupils: A new Q-methodology research.
Intraoperative pelvic drains are often placed during low anterior resection (LAR) to evacuate postoperative fluid collections and identify/control potential anastomotic leaks. Our aim was to assess the validity of this practice.

Patients from the US Rectal Cancer Consortium (2007-2017) who underwent curative-intent LAR for a primary rectal cancer were included. Patients were categorized as receiving a closed suction drain intraoperatively or not. Primary outcomes were superficial surgical site infection (SSI), deep SSI, intraabdominal abscess, anastomotic leak, and need for secondary drain placement. Three subgroup analyses were conducted in patients who received neoadjuvant chemoradiation, had a diverting loop ileostomy (DLI), and had low anastomoses < 6 cm from the anal verge.

Of 996 patients 67% (n = 551) received a drain. Drain patients were more likely to be male (64 vs 54%), have a smoking history (25 vs 19%), have received neoadjuvant chemoradiation (73 vs 61%), have low tumors (56 vs 36%), an are associated with an increase in anastomotic leak rate and no reduction in the need for secondary drain placement or reoperation. Routine drainage appears to be unnecessary.Successful navigation requires memorising and recognising the locations of objects across different perspectives. Although these abilities rely on hippocampal functioning, which is susceptible to degeneration in older adults, little is known about the effects of ageing on encoding and response strategies that are used to recognise spatial configurations. To investigate this, we asked young and older participants to encode the locations of objects in a virtual room shown as a picture on a computer screen. Participants were then shown a second picture of the same room taken from the same (0°) or a different perspective (45° or 135°) and had to judge whether the objects occupied the same or different locations. Overall, older adults had greater difficulty with the task than younger adults although the introduction of a perspective shift between encoding and testing impaired performance in both age groups. Diffusion modelling revealed that older adults adopted a more conservative response strategy, while the analysis of gaze patterns showed an age-related shift in visual-encoding strategies with older adults attending to more information when memorising the positions of objects in space. Overall, results suggest that ageing is associated with declines in spatial processing abilities, with older individuals shifting towards a more conservative decision style and relying more on encoding target object positions using room-based cues compared to younger adults, who focus more on encoding the spatial relationships among object clusters.Although many studies of reaction time (RT) focus on a single measure of central tendency such as the mean RT, a more detailed picture of the underlying processes can be gained by looking at full distributions of RTs. Unfortunately, for practical reasons it is sometimes difficult to obtain enough trials per participant in a condition of interest to construct such a distribution with existing methods. The purpose of this article is to propose a method of forming group RT distributions that can be used to compare the full distributions of RTs even in an infrequent condition with only a few trials per participant. In brief, the percentile ranks of each participant's infrequent-condition RTs are scored relative to a larger pool including that participant's RTs in other conditions, and a histogram of the infrequent-condition's percentile ranks is then formed by pooling across participants. The resulting histogram of infrequent-condition RT ranks shows where the RTs in that condition tend to fall relative to the other conditions, and this histogram can reveal systematic patterns in the infrequent-condition's RT distribution. To illustrate the method, I present histograms of the ranks of infrequent error RTs (~ 5% of trials), ranked relative to correct responses, in real data sets from Simon and lexical decision tasks.Despite advances in automatic speech recognition (ASR), human input is still essential for producing research-grade segmentations of speech data. Conventional approaches to manual segmentation are very labor-intensive. We introduce POnSS, a browser-based system that is specialized for the task of segmenting the onsets and offsets of words, which combines aspects of ASR with limited human input. ThiametG In developing POnSS, we identified several sub-tasks of segmentation, and implemented each of these as separate interfaces for the annotators to interact with to streamline their task as much as possible. We evaluated segmentations made with POnSS against a baseline of segmentations of the same data made conventionally in Praat. We observed that POnSS achieved comparable reliability to segmentation using Praat, but required 23% less annotator time investment. Because of its greater efficiency without sacrificing reliability, POnSS represents a distinct methodological advance for the segmentation of speech data.Creativity research requires assessing the quality of ideas and products. In practice, conducting creativity research often involves asking several human raters to judge participants' responses to creativity tasks, such as judging the novelty of ideas from the alternate uses task (AUT). Although such subjective scoring methods have proved useful, they have two inherent limitations-labor cost (raters typically code thousands of responses) and subjectivity (raters vary on their perceptions and preferences)-raising classic psychometric threats to reliability and validity. We sought to address the limitations of subjective scoring by capitalizing on recent developments in automated scoring of verbal creativity via semantic distance, a computational method that uses natural language processing to quantify the semantic relatedness of texts. In five studies, we compare the top performing semantic models (e.g., GloVe, continuous bag of words) previously shown to have the highest correspondence to human relatedness judgements. We assessed these semantic models in relation to human creativity ratings from a canonical verbal creativity task (AUT; Studies 1-3) and novelty/creativity ratings from two word association tasks (Studies 4-5). We find that a latent semantic distance factor-comprised of the common variance from five semantic models-reliably and strongly predicts human creativity and novelty ratings across a range of creativity tasks. We also replicate an established experimental effect in the creativity literature (i.e., the serial order effect) and show that semantic distance correlates with other creativity measures, demonstrating convergent validity. We provide an open platform to efficiently compute semantic distance, including tutorials and documentation ( https//osf.io/gz4fc/ ).
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