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Cancer Research Group

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Normative [REPACK]

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Normative [REPACK]

Its objectives are to:Provide an integrated approach to the evaluation of normative work in the UN;Provide hands-on methodological guidance, concise practical examples and tools for conducting evaluations of normative work; andHighlight relevant lessons and best-fit practices of the evaluation of normative work inside and outside the UN system.The handbook is intended primarily for evaluation professionals in the UN. It may also be useful to UN staff responsible for designing, managing and monitoring programmes and projects that integrate the norms, standards and codes of practice; and to the UN's partners in its normative work, particularly to governments and civil society organizations (CSOs). The handbook might also be applied when evaluating the internal performance of UN organizations with respect to standards for gender equality, human rights, ethics, conduct of humanitarian assistance and environmental sustainability.Available in English, French & Spanish

Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.

Using an ethical lens, this review evaluates two methods of working within patient care and public health: the weight-normative approach (emphasis on weight and weight loss when defining health and well-being) and the weight-inclusive approach (emphasis on viewing health and well-being as multifaceted while directing efforts toward improving health access and reducing weight stigma). Data reveal that the weight-normative approach is not effective for most people because of high


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