867 research outputs found

    Seabird Bycatch in Pelagic Longline Fisheries Is Grossly Underestimated when Using Only Haul Data

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    Hundreds of thousands of seabirds are killed each year as bycatch in longline fisheries. Seabirds are predominantly caught during line setting but bycatch is generally recorded during line hauling, many hours after birds are caught. Bird loss during this interval may lead to inaccurate bycatch information. In this 15 year study, seabird bycatch was recorded during both line setting and line hauling from four fishing regions: Indian Ocean, Southern Ocean, Coral Sea and central Pacific Ocean. Over 43,000 albatrosses, petrels and skuas representing over 25 species were counted during line setting of which almost 6,000 seabirds attempted to take the bait. Bait-taking interactions were placed into one of four categories. (i) The majority (57%) of bait-taking attempts were “unsuccessful” involving seabirds that did not take the bait nor get caught or hooked. (ii) One-third of attempts were “successful” with seabirds removing the bait while not getting caught. (iii) One-hundred and seventy-six seabirds (3% of attempts) were observed being “caught” during line setting, with three albatross species – Laysan (Phoebastria immutabilis), black-footed (P. nigripes) and black-browed (Thalassarche melanophrys)– dominating this category. However, of these, only 85 (48%) seabird carcasses were retrieved during line hauling. Most caught seabirds were hooked through the bill. (iv) The remainder of seabird-bait interactions (7%) was not clearly observed, but likely involved more “caught” seabirds. Bait taking attempts and percentage outcome (e.g. successful, caught) varied between seabird species and was not always related to species abundance around fishing vessels. Using only haul data to calculate seabird bycatch grossly underestimates actual bycatch levels, with the level of seabird bycatch from pelagic longline fishing possibly double what was previously thought

    Predicting performance using background characteristics of international medical graduates in an inner-city university-affiliated Internal Medicine residency training program

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    <p>Abstract</p> <p>Background</p> <p>IMGs constitute about a third of the United States (US) internal medicine graduates. US residency training programs face challenges in selection of IMGs with varied background features. However data on this topic is limited. We analyzed whether any pre-selection characteristics of IMG residents in our internal medicine program are associated with selected outcomes, namely competency based evaluation, examination performance and success in acquiring fellowship positions after graduation.</p> <p>Methods</p> <p>We conducted a retrospective study of 51 IMGs at our ACGME accredited teaching institution between 2004 and 2007. Background resident features namely age, gender, self-reported ethnicity, time between medical school graduation to residency (pre-hire time), USMLE step I & II clinical skills scores, pre-GME clinical experience, US externship and interest in pursuing fellowship after graduation expressed in their personal statements were noted. Data on competency-based evaluations, in-service exam scores, research presentation and publications, fellowship pursuance were collected. There were no fellowships offered in our hospital in this study period. Background features were compared between resident groups according to following outcomes: (a) annual aggregate graduate PGY-level specific competency-based evaluation (CBE) score above versus below the median score within our program (scoring scale of 1 – 10), (b) US graduate PGY-level specific resident in-training exam (ITE) score higher versus lower than the median score, and (c) those who succeeded to secure a fellowship within the study period. Using appropriate statistical tests & adjusted regression analysis, odds ratio with 95% confidence intervals were calculated.</p> <p>Results</p> <p>94% of the study sample were IMGs; median age was 35 years (Inter-Quartile range 25th – 75th percentile (IQR): 33–37 years); 43% women and 59% were Asian physicians. The median pre-hire time was 5 years (IQR: 4–7 years) and USMLE step I & step II clinical skills scores were 85 (IQR: 80–88) & 82 (IQR: 79–87) respectively. The median aggregate CBE scores during training were: PG1 5.8 (IQR: 5.6–6.3); PG2 6.3 (IQR 6–6.8) & PG3 6.7 (IQR: 6.7 – 7.1). 25% of our residents scored consistently above US national median ITE scores in all 3 years of training and 16% pursued a fellowship.</p> <p>Younger residents had higher aggregate annual CBE score than the program median (p < 0.05). Higher USMLE scores were associated with higher than US median ITE scores, reflecting exam-taking skills. Success in acquiring a fellowship was associated with consistent fellowship interest (p < 0.05) and research publications or presentations (p <0.05). None of the other characteristics including visa status were associated with the outcomes.</p> <p>Conclusion</p> <p>Background IMG features namely, age and USMLE scores predict performance evaluation and in-training examination scores during residency training. In addition enhanced research activities during residency training could facilitate fellowship goals among interested IMGs.</p

    What we observe is biased by what other people tell us: beliefs about the reliability of gaze behavior modulate attentional orienting to gaze cues

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    For effective social interactions with other people, information about the physical environment must be integrated with information about the interaction partner. In order to achieve this, processing of social information is guided by two components: a bottom-up mechanism reflexively triggered by stimulus-related information in the social scene and a top-down mechanism activated by task-related context information. In the present study, we investigated whether these components interact during attentional orienting to gaze direction. In particular, we examined whether the spatial specificity of gaze cueing is modulated by expectations about the reliability of gaze behavior. Expectations were either induced by instruction or could be derived from experience with displayed gaze behavior. Spatially specific cueing effects were observed with highly predictive gaze cues, but also when participants merely believed that actually non-predictive cues were highly predictive. Conversely, cueing effects for the whole gazed-at hemifield were observed with non-predictive gaze cues, and spatially specific cueing effects were attenuated when actually predictive gaze cues were believed to be non-predictive. This pattern indicates that (i) information about cue predictivity gained from sampling gaze behavior across social episodes can be incorporated in the attentional orienting to social cues, and that (ii) beliefs about gaze behavior modulate attentional orienting to gaze direction even when they contradict information available from social episodes

    How Can Psychological Science Inform Research About Genetic Counseling for Clinical Genomic Sequencing?

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    Next generation genomic sequencing technologies (including whole genome or whole exome sequencing) are being increasingly applied to clinical care. Yet, the breadth and complexity of sequencing information raise questions about how best to communicate and return sequencing information to patients and families in ways that facilitate comprehension and optimal health decisions. Obtaining answers to such questions will require multidisciplinary research. In this paper, we focus on how psychological science research can address questions related to clinical genomic sequencing by explaining emotional, cognitive, and behavioral processes in response to different types of genomic sequencing information (e.g., diagnostic results and incidental findings). We highlight examples of psychological science that can be applied to genetic counseling research to inform the following questions: (1) What factors influence patients’ and providers’ informational needs for developing an accurate understanding of what genomic sequencing results do and do not mean?; (2) How and by whom should genomic sequencing results be communicated to patients and their family members?; and (3) How do patients and their families respond to uncertainties related to genomic information?Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147034/1/jgc40193.pd
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