Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data

Background: Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk. Objectives: Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak. Methods: A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data. Results: Eight key themes emerged from the analysis of data: emotion and feeling, health related information, general commentary and resources, media and health organisations, politics, country of origin, food, and humour and/or sarcasm. Discussion: A major novel finding was that due to the name 'swine flu', Twitter users had the belief that pigs and pork could host and/or transmit the virus. Our paper also considered the methodological implications for the wider field of library and information science as well as specific implications for health information and library workers. Conclusions: Novel insights were derived on how users communicate about disease outbreaks on social media platforms. Our study also provides an innovative methodological contribution because it was found that by utilising an indepth method it was possible to extract greater insight into user communication

Long-term Memory of Sensory Experiences from the First Pregnancy, its Peri-partum and Post-partum in Women with Autism Spectrum Disorders without Intellectual Disabilities: A Retrospective Study

Purpose: To explore the recalled experience of pregnancy and motherhood in women diagnosed with Autism Spectrum Disorders (ASD) without intellectual disabilities, focusing on sensory perceptions and mood. Methods: We retrospectively evaluated, through an ad-hoc structured interview, the sensory sensitivity during the pre-partum, the peri-partum, and the post-partum of thirty-three mothers with ASD and thirty-two neurotypical mothers. Participants also underwent a psychometric assessment about autistic traits, general sensory sensitivity, and post-partum depressive symptomatology. Results: Mothers with ASD recalled a higher sensitivity than the comparison group across the three time-points; however, during the peri-partum their recalled hypersensitivity decreases, and in the post-partum it returned as high as before childbirth. The difference in the length of recall between groups did not statistically influence our results. Higher levels of autistic traits correlated with higher depressive post-partum symptomatology. Conclusions: Mothers with ASD seem to recall their experience of pregnancy, childbirth, and post-partum period differently from neurotypical mothers, particularly in terms of hypersensitivity. The correlation with depressive symptoms and the potential role of oxytocin and of long-term memory (encoding and recollection) are discussed. Further exploring these aspects might give fundamental hints to provide tailored support to mothers with ASD during pregnancy and motherhood

Perspectives on Large Language Models for Relevance Judgment

When asked, current large language models (LLMs) like ChatGPT claim that they can assist us with relevance judgments. Many researchers think this would not lead to credible IR research. In this perspective paper, we discuss possible ways for LLMs to assist human experts along with concerns and issues that arise. We devise a human-machine collaboration spectrum that allows categorizing different relevance judgment strategies, based on how much the human relies on the machine. For the extreme point of "fully automated assessment", we further include a pilot experiment on whether LLM-based relevance judgments correlate with judgments from trained human assessors. We conclude the paper by providing two opposing perspectives - for and against the use of LLMs for automatic relevance judgments - and a compromise perspective, informed by our analyses of the literature, our preliminary experimental evidence, and our experience as IR researchers. We hope to start a constructive discussion within the community to avoid a stale-mate during review, where work is dammed if is uses LLMs for evaluation and dammed if it doesn't

Breast MRI in Community Practice: Equipment and Imaging Techniques at Facilities in the Breast Cancer Surveillance Consortium

MRI is increasingly used for detection of breast carcinoma. Little is known about breast MRI techniques among community practice facilities. This study evaluated equipment and acquisition techniques used by community facilities across the U.S., including compliance with minimum standards by the American College of Radiology Imaging Network (ACRIN) 6667 Trial and the European Society of Breast Imaging (EUSOBI)

Patterns of Breast Magnetic Resonance Imaging Use in Community Practice

Breast magnetic resonance imaging (MRI) is increasingly used for breast cancer screening, diagnostic evaluation, and surveillance However, we lack data on national patterns of breast MRI use in community practice

Appropriate referral and selection of patients with chronic pain for spinal cord stimulation: European consensus recommendations and e-health tool

Background: Spinal cord stimulation (SCS) is an established treatment for chronic neuropathic, neuropathic-like and ischaemic pain. However, the heterogeneity of patients in daily clinical practice makes it often challenging to determine which patients are eligible for this treatment, resulting in undesirable practice variations. This study aimed to establish patient-specific recommendations for referral and selection of SCS in chronic pain. Methods: A multidisciplinary European panel used the RAND/UCLA Appropriateness Method (RUAM) to assess the appropriateness of (referral for) SCS for 386 clinical scenarios in four pain areas: chronic low back pain and/or leg pain, complex regional pain syndrome, neuropathic pain syndromes and ischaemic pain syndromes. In addition, the panel identified a set of psychosocial factors that are relevant to the decision for SCS treatment. Results: Appropriateness of SCS was strongly determined by the neuropathic or neuropathic-like pain component, location and spread of pain, anatomic abnormalities and previous response to therapies targeting pain processing (e.g. nerve block). Psychosocial factors considered relevant for SCS selection were as follows: lack of engagement, dysfunctional coping, unrealistic expectations, inadequate daily activity level, problematic social support, secondary gain, psychological distress and unwillingness to reduce high-dose opioids. An educational e-health tool was developed that combines clinical and psychosocial factors into an advice on referral/selection for SCS. Conclusions: The RUAM was useful to establish a consensus on patient-specific criteria for referral/selection for SCS in chronic pain. The e-health tool may help physicians learn to apply an integrated approach of clinical and psychosocial factors. Significance: Determining the eligibility of SCS in patients with chronic pain requires careful consideration of a variety of clinical and psychosocial factors. Using a systematic approach to combine evidence from clinical studies and expert opinion, a multidisciplinary European expert panel developed detailed recommendations to support appropriate referral and selection for SCS in chronic pain. These recommendations are available as an educational e-health tool (https://www.scstool.org/)

Breast MRI BI-RADS Assessments and Abnormal Interpretation Rates by Clinical Indication in US Community Practices

As breast MRI use grows, benchmark performance parameters are needed for auditing and quality assurance purposes. We describe the variation in breast MRI abnormal interpretation rates (AIRs) by clinical indication among a large sample of U.S. community practices

Data-driven clustering of combined Functional Motor Disorders based on the Italian registry

Functional Motor Disorders (FMDs) represent nosological entities with no clear phenotypic characterization, especially in patients with multiple (combined FMDs) motor manifestations. A data-driven approach using cluster analysis of clinical data has been proposed as an analytic method to obtain non-hierarchical unbiased classifications. The study aimed to identify clinical subtypes of combined FMDs using a data-driven approach to overcome possible limits related to "a priori" classifications and clinical overlapping

Purificação e caracterização de endopeptidases acídicas de sementes Canavalia ensiformis

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