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Träfflista för sökning "WFRF:(Williams Steven C. R.) ;hsvcat:5"

Sökning: WFRF:(Williams Steven C. R.) > Samhällsvetenskap

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1.
  • Sumaila, U. Rashid, et al. (författare)
  • WTO must ban harmful fisheries subsidies
  • 2021
  • Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 374:6567, s. 544-544
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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  • Main, Chris J., et al. (författare)
  • Implementation Science and Employer Disability Practices : Embedding Implementation Factors in Research Designs
  • 2016
  • Ingår i: Journal of occupational rehabilitation. - : Springer-Verlag New York. - 1053-0487 .- 1573-3688. ; 26:4, s. 448-464
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: For work disability research to have an impact on employer policies and practices it is important for such research to acknowledge and incorporate relevant aspects of the workplace. The goal of this article is to summarize recent theoretical and methodological advances in the field of Implementation Science, relate these to research of employer disability management practices, and recommend future research priorities.Methods: The authors participated in a year-long collaboration culminating in an invited 3-day conference, “Improving Research of Employer Practices to Prevent Disability”, held October 14–16, 2015, in Hopkinton, MA, USA. The collaboration included a topical review of the literature, group conference calls to identify key areas and challenges, drafting of initial documents, review of industry publications, and a conference presentation that included feedback from peer researchers and a question/answer session with a special panel of knowledge experts with direct employer experience.Results: A 4-phase implementation model including both outer and inner contexts was adopted as the most appropriate conceptual framework, and aligned well with the set of process evaluation factors described in both the work disability prevention literature and the grey literature. Innovative interventions involving disability risk screening and psychologically-based interventions have been slow to gain traction among employers and insurers. Research recommendations to address this are : (1) to assess organizational culture and readiness for change in addition to individual factors; (2) to conduct process evaluations alongside controlled trials; (3) to analyze decision-making factors among stakeholders; and (4) to solicit input from employers and insurers during early phases of study design.Conclusions: Future research interventions involving workplace support and involvement to prevent disability may be more feasible for implementation if organizational decision-making factors are imbedded in research designs and interventions are developed to take account of these influences. 
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4.
  • Frick, Andreas, et al. (författare)
  • Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure
  • 2014
  • Ingår i: Behavioural Brain Research. - : Elsevier BV. - 0166-4328 .- 1872-7549. ; 75:9, s. 358S-358S
  • Tidskriftsartikel (refereegranskat)abstract
    • Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n = 14) from healthy controls (n = 12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD.
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