METHODS: Through the review of the literature, this paper discusses seven questions, (i) What is SLE? (ii) What are the types of SLEs? (iii) How is SLE classified? (iv) What is HF SLE? (v) What types of SLEs are available in audiology and their level of fidelity? (vi) What are the components needed for developing HF SLE? (vii) What are the possible types of HF SLEs that are suitable for audiology training? Publications were identified by structured searches from three major databases PubMed, Web of Knowledge and PsychInfo and from the reference lists of relevant articles. The authors discussed and mapped the levels of fidelity of SLE audiology training modules from the literature and the learning domains involved in the clinical audiology courses.
RESULTS: The discussion paper has highlighted that most of the existing SLE audiology training modules consist of either low- or medium-fidelity types of simulators. Those components needed to achieve a HF SLE for audiology training are also highlighted.
CONCLUSION: Overall, this review recommends that the combined approach of different levels and types of SLE could be used to obtain a HF SLE training module in audiology training.
METHODS AND FINDINGS: A randomised clinical trial involving 146 Sudanese TB patients will be conducted at the Abu Anga hospital in Khartoum. The participants will be randomly assigned to the intervention and control groups. A 2-hour session will be offered to the intervention group in a one-day TB educational intervention course. The same educational materials will also be provided to the control group after the randomised controlled trial (RCT). Data will be collected at baseline, one month, and four months after the intervention. The primary outcome of interest is TB treatment adherence, while secondary outcomes include quality of life score, tuberculosis knowledge, and health belief domains. Generalised estimating equations (GEE) in SPSS software version 25.0 will be utilised to evaluate the changes over time.
CONCLUSIONS: This trial will provide information that could be used in improving TB control strategies to achieve better results in the adherence of healthcare services to the norms of the National Program and patient adherence to the disease treatment and cure.
TRIAL REGISTRATION: This study is registered at TCTR: (TCTR20210607006).
METHODS: A validated, bilingual, self-administered questionnaire comprising fifteen questions across the domains of Knowledge, Attitude and Practice was used and responses were assessed with 3 responses; one correct, one incorrect and one reflecting uncertainty. 507 patients from five orthodontic centres participated in this study. Data was analysed using SPSS. Continuous data was summarised as mean and standard deviation or median and inter-quartile range, as appropriate. Categorical data was summarised as frequency and percentage, then univariable analysis was carried out with Pearson's chi-square test or Fisher's exact test, as appropriate.
RESULTS: The mean age of respondents was 22.5 years (SD ± 2.8). A majority of respondents were female (64.1%) and from the lowest income bracket or B40 group (71%). Overall, for the knowledge domain, a majority of the respondents got all questions correct. 69.4% of patients were aware that incomplete treatment could lead to worsening of their malocclusion. 80.9% of respondents were aware of the need for a retainer upon completion of their orthodontic treatment. For the attitude section, 64.7% felt that they had to wait a very long time to see the orthodontist. In the Practice domain, the majority only got two of the five questions correct. Only 39.8% of respondents made an effort to alter dietary habits all of the time. In general, females and those with tertiary education fared better for all three domains.
CONCLUSIONS: The orthodontic patients in the Federal Territories of Kuala Lumpur and Putrajaya possess good knowledge about their treatment however their attitude and orthodontic related practices need to be improved.
METHODS: 52 prostate cancer patients who had completed radiotherapy were selected and randomly divided into 2 groups with 40 and 12 separately. Then both VMAT and IMRT plans were manually designed for all patients. The total plans in the group with 40 cases as training datasets were added to the knowledge-based planning (KBP) models for learning and finally obtained VMAT and IMRT training models. Another 12 cases were selected as the validation group to be used to generated auto IMRT plans by KBP VMAT and IMRT models. At last, the radiotherapy plans from three groups were obtained: the automated IMRT plan (V-IMRT) predicted by the VMAT model, the automated IMRT plan (I-IMRT) predicted by the IMRT model and the manual IMRT plan (M-IMRT) designed before. The dosimetric parameters of planning target volume (PTV) and organ at risks (OARs) as well as the time parameters (monitor unit, MU) were statistically analyzed.
RESULTS: The dose limit of all plans in the training datasets met the clinical requirements. Compared with the training plans added to VMAT model, the dosimetry parameters have no statistical differences in PTV (P > 0.05); the dose of X% volume (Dx%) with D25% and D35% in rectal and the maximum dose (Dmax) in the right femoral head were lower (P = 0.04, P = 0.01, P = 0.00) while D50% in rectal was higher ( 0.05), but the Dmax in left femoral heard and D15% in the right femoral head were lower and have significant differences (P 0.05).
CONCLUSION: Compared with the manual plan, the IMRT plans generated by the KBP models had a significant advantage in dose control of both OARs and PTV. Compared to the I-IMRT plans, the V-IMRT plans was not only without significant disadvantages, but it also achieved slightly better control of the low-dose region, which meet the clinical requirements and can used in the clinical treatment. This study demonstrates that it is feasible to transfer the KBP VMAT model in the prediction of IMRT plans.
METHODS: This study builds upon previous work that developed a causal loop diagram of AMR using input from two workshops conducted in 2019 in Sweden with experts within the European food system context. A secondary analysis of the workshop transcripts was conducted to identify semi-quantitative data to parameterize drivers in a model of AMR.
MAIN FINDINGS: Participants spoke about AMR by combining their personal experiences with professional expertise within their fields. The analysis of participants' statements provided semi-quantitative data that can help inform a future of AMR emergence and transmission based on a causal loop diagram of AMR in a Swedish One Health system context.
CONCLUSION: Using transcripts of a workshop including participants with diverse expertise across the system that drives AMR, we gained invaluable insight into the past, current, and potential future states of the major drivers of AMR, particularly where quantitative data are lacking.