262 research outputs found

    Enhancing suicide risk assessment through the use of visual metaphor : a thesis presented in partial fulfillment of the requirements for the degree of Master of Health Science in Psychology at Massey University, Albany Campus, New Zealand

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    Competent assessment and management of the risk of harm is a core competency that mental health professionals are expected to possess. However, despite this expectation, adequate training programs have been lacking for decades and, even when risk assessment training is provided, it is often reported as being insufficient. The literature indicates that training delivery methods often include passive and didactic methods during supervision or seminar sessions. To help enhance the learning of suicide risk factors, some authors proposed a visual metaphor that visually and metaphorically depicts all suicide risk factors. The main purpose of this study was to examine the efficacy of the proposed visual metaphor. A pilot RCT was undertaken to test several hypotheses, all of which predicted that the visual metaphor would demonstrate superior effects when compared with the conventional textual teaching methods. A group of 22 psychology students were randomized into either a control group (who learnt suicide risk factors via the conventional textual teaching methods) or a treatment group (that learnt the risk factors using the visual metaphor in addition to the conventional textual teaching methods). Memory recall, knowledge transfer, cognitive load, and satisfaction were all tested at the end of the learning sessions. Independent samples t tests indicated that the visual metaphor was effective in improving memory recall and knowledge transfer and reducing the cognitive load. The differences between the two groups’ post-learning scores were significant in each of these outcome measures. The treatment group also expressed higher satisfaction levels in comparison to the control group. Overall the visual metaphor of suicide risk factors was found to be superior to the conventional teaching methods in teaching suicide risk factors to university psychology students. Limitations, implications of this study and directions for future research are discussed

    Walking-based activity and sedentary behavior in Saudi males with chronic obstructive pulmonary disease

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    © 2018, Saudi Arabian Armed Forces Hospital. All rights reserved. Objectives: To compare walking-based activity and sedentary behavior between males with chronic obstructive pulmonary disease (COPD) and healthy controls and to examine the association between dyspnea with time spent in walking-based activity and sedentary behavior in males with COPD. Methods: This cross-sectional study of 30 males with COPD (age 62.0±5.0 years; forced expiratory volume in one second [FEV1] 46±15% predicted) and 29 healthy controls (age 63.0±4.3 years; FEV1 91±5% predicted) was conducted at the outpatient pulmonary clinics at King Fahad Medical City, Riyadh, Kingdom of Saudi Arabia between February 2013 and March 2014. Walking-based activity and sedentary behavior were evaluated using an activity monitor. Results: Participants with COPD spent less time engaged in walking-based activity (22±8% versus 37±7% of waking hours; p<0.001) and more time engaged in sedentary behavior (78±8% versus 63±6% of waking hours; p<0.001) than healthy controls. In males with COPD, moderate to strong associations were found between the scores of the quality and emotional response components of the Dyspnea-12 (D-12) questionnaire and time spent engaged in walking-based activity and sedentary behavior (r: =0.46, all p<0.01). Conclusion: Males with COPD were less active and more sedentary than healthy controls. The D-12 components were associated with walking-based activity and sedentary behavior in males with COPD

    Blockchain Empowered Federated Learning Ecosystem for Securing Consumer IoT Features Analysis

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    Resource constraint Consumer Internet of Things (CIoT) is controlled through gateway devices (e.g., smartphones, computers, etc.) that are connected to Mobile Edge Computing (MEC) servers or cloud regulated by a third party. Recently Machine Learning (ML) has been widely used in automation, consumer behavior analysis, device quality upgradation, etc. Typical ML predicts by analyzing customers’ raw data in a centralized system which raises the security and privacy issues such as data leakage, privacy violation, single point of failure, etc. To overcome the problems, Federated Learning (FL) developed an initial solution to ensure services without sharing personal data. In FL, a centralized aggregator collaborates and makes an average for a global model used for the next round of training. However, the centralized aggregator raised the same issues, such as a single point of control leaking the updated model and interrupting the entire process. Additionally, research claims data can be retrieved from model parameters. Beyond that, since the Gateway (GW) device has full access to the raw data, it can also threaten the entire ecosystem. This research contributes a blockchain-controlled, edge intelligence federated learning framework for a distributed learning platform for CIoT. The federated learning platform allows collaborative learning with users’ shared data, and the blockchain network replaces the centralized aggregator and ensures secure participation of gateway devices in the ecosystem. Furthermore, blockchain is trustless, immutable, and anonymous, encouraging CIoT end users to participate. We evaluated the framework and federated learning outcomes using the well-known Stanford Cars dataset. Experimental results prove the effectiveness of the proposed framework

    Amygdala and subregion volume are associated with photoperiod and seasonal depressive symptoms : A cross sectional study in the UK Biobank cohort

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    ACKNOWLEDGEMENTS This research has been conducted using the UK Biobank Resource. This work was supported by the Aberdeen Biomedical Imaging Centre with financial support from the Roland Sutton Academic Trust (RSAT-0039/R/16) and Jazan University and Ministry of Health in Saudi Arabia.Peer reviewedPublisher PD

    Polymeric Nanovectors Incorporated with Ganciclovir and HSV-tk Encoding Plasmid for Gene-Directed Enzyme Prodrug Therapy

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    In the area of gene-directed enzyme prodrug therapy (GDEPT), using herpes simplex virus thymidine kinase (HSV-tk) paired with prodrug ganciclovir (GCV) for cancer treatment has been extensively studied. It is a process involved with two steps whereby the gene (HSV-tk) is first delivered to malignant cells. Afterward, non-toxic GCV is administered to that site and activated to cytotoxic ganciclovir triphosphate by HSV-tk enzyme expressed exogenously. In this study, we presented a one-step approach that both gene and prodrug were delivered at the same time by incorporating them with polymeric micellar nanovectors. GCV was employed as an initiator in the ring-opening polymerization of ε-caprolactone (ε-CL) to synthesize hydrophobic GCV-poly(caprolactone) (GCV-PCL), which was furthered grafted with hydrophilic chitosan to obtain amphiphilic polymer (GCV-PCL-chitosan) for the fabrication of self-assembled micellar nanoparticles. The synthesized amphiphilic polymer was characterized using Fourier transform infrared spectroscopy and proton nuclear magnetic resonance. Micellar prodrug nanoparticles were analyzed by dynamic light scattering, zeta potential, critical micelle concentration, and transmission electron microscopy. Polymeric prodrug micelles with optimal features incorporated with HSV-tk encoding plasmids were cultivated with HT29 colorectal cancer cells and anticancer effectiveness was determined. Our results showed that prodrug GCV and HSV-tk cDNA encoded plasmid incorporated in GCV-PCL-chitosan polymeric nanocarriers could be delivered in a one-step manner to HT-29 cells and triggered high cytotoxicity

    Oxaliplatin use in pressurized intraperitoneal aerosol chemotherapy (PIPAC) is safe and effective: A multicenter study.

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    Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is a new drug delivery method used in patients with peritoneal cancer (PC) of primary or secondary origin. Intraperitoneal use of oxaliplatin raises concerns about toxicity, especially abdominal pain. The objective of this study was to assess the tolerance of PIPAC with oxaliplatin (PIPAC-Ox) in a large cohort of patients and to identify the risk factors for high grade toxicity, discontinuation of treatment and impaired survival. This retrospective cohort study included all consecutive patients treated with PIPAC-Ox (92 mg/m <sup>2</sup> ) in five centers specialized in the treatment of PC. The procedure was repeated every 6 weeks. Outcomes of interest were Common Terminology Criteria for Adverse Events (CTCAE), symptoms and survival (Kaplan-Meier). Univariate risk factors were included in a multinominal regression model to control for bias. Overall, 251 PIPAC-Ox treatments were performed in 101 patients (45 female) having unresectable PC of various origins: 66 colorectal, 15 gastric, 5 ovarian, 3 mesothelioma, 2 pseudomyxoma, 10 other malignancies (biliary, pancreatic, endocrine) respectively. The median PCI was 19 (IQR: 10-28). Postoperative abdominal pain was present in 23 patients. Out of the 9 patients with grade 3 abdominal pain, only 3 needed a change of PIPAC drug. CTCAE 4.0 toxicity grade 4 or higher was encountered in 16(15.9%) patients. The patients had a mean of 2.5 procedures/patient (SD = 1.5). 50 subjects presented with symptom improvement. Oxaliplatin-based PIPAC appears to be a safe treatment that offers good symptom control and promising survival for patients with advanced peritoneal disease

    Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

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    OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis costs but improve patient management and outcomes. METHODS: In this study, we developed machine learning models using selective key pathological categories to identify clinical test attributes that will aid in accurate early diagnosis of CKD. Such an approach will save time and costs for diagnostic screening. We have also evaluated the performance of several classifiers with k-fold cross-validation on optimized datasets derived using these selected clinical test attributes. RESULTS: Our results suggest that the optimized datasets with important attributes perform well in diagnosis of CKD using our proposed machine learning models. Furthermore, we evaluated clinical test attributes based on urine and blood tests along with clinical parameters that have low costs of acquisition. The predictive models with the optimized and pathologically categorized attributes set yielded high levels of CKD diagnosis accuracy with random forest (RF) classifier being the best performing. CONCLUSIONS: Our machine learning approach has yielded effective predictive analytics for CKD screening which can be developed as a resource to facilitate improved CKD screening for enhanced and timely treatment plans

    Pressurised intraperitoneal aerosol chemotherapy: rationale, evidence, and potential indications.

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    Pressurised intraperitoneal aerosol chemotherapy (PIPAC) was introduced as a new treatment for patients with peritoneal metastases in November, 2011. Reports of its feasibility, tolerance, and efficacy have encouraged centres worldwide to adopt PIPAC as a novel drug delivery technique. In this Review, we detail the technique and rationale of PIPAC and critically assess its evidence and potential indications. A systematic search was done to identify all relevant literature on PIPAC published between Jan 1, 2011, and Jan 31, 2019. A total of 106 articles or reports on PIPAC were identified, and 45 clinical studies on 1810 PIPAC procedures in 838 patients were included for analysis. Repeated PIPAC delivery was feasible in 64% of patients with few intraoperative and postoperative surgical complications (3% for each in prospective studies). Adverse events (Common Terminology Criteria for Adverse Events greater than grade 2) occurred after 12-15% of procedures, and commonly included bowel obstruction, bleeding, and abdominal pain. Repeated PIPAC did not have a negative effect on quality of life. Using PIPAC, an objective clinical response of 62-88% was reported for patients with ovarian cancer (median survival of 11-14 months), 50-91% for gastric cancer (median survival of 8-15 months), 71-86% for colorectal cancer (median survival of 16 months), and 67-75% (median survival of 27 months) for peritoneal mesothelioma. From our findings, PIPAC has been shown to be feasible and safe. Data on objective response and quality of life were encouraging. Therefore, PIPAC can be considered as a treatment option for refractory, isolated peritoneal metastasis of various origins. However, its use in further indications needs to be validated by prospective studies
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