Introduction: Multidisciplinary therapy assistants (TAs) are increasingly seen as a model suited to the provision of allied health services in rural and remote areas. Supervision is a key aspect of therapy assistant practice. The rural context presents many challenges in supervising TAs including: a multidisciplinary TA role, outreach service delivery models, inexperienced allied health professionals (AHPs) and a high turnover of AHPs. At present there are no accepted standards for supervising TAs in this context. This study aimed to improve the supervision of TAs by AHPs in a rural setting. Improving supervision formed one aspect of the Therapy Assistant Project (TAP).
Methods: Minimum standards for supervision were developed, a process for recording TA supervision introduced, and training in supervision skills was delivered to AHPs. A mixed method study design was used to determine the impact of introducing minimum standards and supervisor training on supervision practices.
Results: Minimum supervision standards included: program and administrative discussion, observation, and demonstration of therapy sessions. Methods recommended for supervising allowed regular supervision of TAs in small, distant rural towns. Developing minimum standards for supervision, a process for recording supervision, and training in supervisory skills resulted in increased supervision between AHPs and TAs. AHP and TA participants expressed satisfaction with minimum supervision standards. The frequency and amount of supervision increased although videoconferencing for supervising TAs in distant towns was not widely used for supervision.
Conclusion: This study provides a new resource for supervision practices for rural TAs. The minimum standards for supervision would be a suitable resource to assist health services seeking to improve supervision of TAs or commencing a TA program. Further exploration of the use of videoconferencing for supervising TAs in distant rural towns is suggested. Training in supervision skills for AHPs should include introductory and complex supervision methods. This study represents one step in defining standards for rural and remote TA practice.
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Comput Methods Programs Biomed
January 2025
Shanghai Maritime University, Shanghai 201306, China. Electronic address:
Background And Objective: Inferring large-scale brain networks from functional magnetic resonance imaging (fMRI) provides more detailed and richer connectivity information, which is critical for gaining insight into brain structure and function and for predicting clinical phenotypes. However, as the number of network nodes increases, most existing methods suffer from the following limitations: (1) Traditional shallow models often struggle to estimate large-scale brain networks. (2) Existing deep graph structure learning models rely on downstream tasks and labels.
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January 2025
University of Ghana, P.O. Box 134, Legon-Accra, Ghana.
Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the accurate results and overcome the current issue. In other words, because of those issues, conventional approaches cannot perform well and accomplish results with high efficiency.
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January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
View Article and Find Full Text PDFDiabetologia
January 2025
Department of Public Health, University of Helsinki, Helsinki, Finland.
Aims/hypothesis: Eating disorders are over-represented in type 1 diabetes and are associated with an increased risk of complications, but it is unclear whether type 1 diabetes affects the treatment of eating disorders. We assessed incidence and treatment of eating disorders in a nationwide sample of individuals with type 1 diabetes and diabetes-free control individuals.
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Sci Rep
January 2025
Department of Critical Care Medicine, Tongde Hospital of Zhejiang Province, #234 Gucui Road, Hangzhou, 310012, Zhejiang, People's Republic of China.
The intestinal barrier function is a critical defense mechanism in the human body, serving as both the primary target and initiating organ in cases of sepsis. Preserving the integrity of this barrier is essential for preventing complications and diseases, including sepsis and mortality. Despite this importance, the impact of resveratrol on intestinal barrier function remains unclear.
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