School of Clinical Sciences
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The School of Clinical Sciences plays an important role in specialist teaching and research conducted by its academic staff and postgraduate students. This places AUT students at the forefront of much of the ground-breaking research undertaken in New Zealand, especially in the fields of Midwifery, Nursing, Occupational Therapy, Oral Health, Paramedicine, Physiotherapy, Podiatry.
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- ItemHow to Peer Review Quantitative Studies, Qualitative Studies, and Literature Reviews: Considerations from the ‘Other’ Side(Springer Science and Business Media LLC, 2024-08-07) Rodda, SN; Bijker, R; Merkouris, SS; Landon, J; Hawker, CO; Dowling, NAPurpose of review: The main research approaches in the field of addiction include qualitative studies, quantitative studies, and literature reviews. Researchers tend to have specific expertise in one, or perhaps two of these approaches, but are frequently asked to peer review studies using approaches and methods in which they are less well versed. This review aims to provide guidance to peer reviewers by summarizing key issues to attend to when reviewing studies of each approach. Recent findings: A diverse range of research approaches are utilised in the study of addiction including quantitative, qualitative, and literature reviews. In this paper, we outline reporting standards for each research approach, and summarize how data are collected, analyzed, reported, and interpreted, as a guide for peer-reviewers to assess the robustness of studies. Summary: Providing a good peer review requires that careful attention is paid to the specific requirements of the methods used. General principles of clarity around an evidence-based rationale, data collection and analysis, and careful interpretation remain fundamental, regardless of the method used. Reviews should be balanced and fair and based on the research and associated reporting requirements for the method used.
- ItemTrauma-Informed Care Beliefs Scale-Comprehensive for Child Welfare Carers Using Rasch Analysis.(Elsevier BV, 2024-08-16) Beehag, Nathan; Dryer, Rachel; McGrath, Andrew; Krägeloh, Chris; Medvedev, OlegBACKGROUND: The literature on trauma-informed care practices (TIC) indicates that this framework is beneficial for young people, carers, and staff. However, a significant gap in the literature and practice is the absence of psychometrically sound scales to measure carer adherence to TIC principles. Emerging evidence suggests that TIC practices shift carer attitudes and beliefs, which mediate positive outcomes for both carers and young people. OBJECTIVE: To develop a theoretically comprehensive and psychometrically sound measure of carer TIC beliefs using Rasch methodology. PARTICIPANTS AND SETTING: Active carers (N = 719, M = 43 years, SD = 10.7 years) from online support groups in Australia, Canada, the United States of America, the United Kingdom, and the Republic of Ireland completed the questionnaire online. METHODS: Based on previous research (e.g., limitations of the Trauma-Informed Belief Scale-Brief [TIBS-B]; Beehag, Dryer, et al., 2023a) and a scoping review of the TIC literature (Beehag, 2023), 61 candidate items were created that covered the three main characteristics of carer-related TIC theory (i.e., beliefs on TIC strategies to manage trauma symptoms, beliefs on the impact of adverse childhood experiences (ACE), and beliefs on the importance of self-care/reflection). The resulting data was subjected to Rasch analyses. RESULTS: Following analyses and minor modifications, a 35-item version of the questionnaire was confirmed, which fitted the Rasch model and demonstrated unidimensionality, reasonable targeting, and sound internal consistency reliability (Person Separation Index = 0.81). CONCLUSIONS: The TIBS-C is a psychometrically sound measure of child welfare carer TIC beliefs. Future studies are needed to provide further evidence of its validity (e.g., predictive validity), reliability (e.g., test-retest reliability) and clinical utility.
- ItemBreaking the Dental Fear Cycle(The New Zealand Dental Association, 2024-07-01) Morse, Zac
- ItemValidation of the Filling Factor Index to Study the Filling Process of the sEMG Signal in the Quadriceps(Elsevier BV, 2023-08-15) Rodriguez-Falces, J; Malanda, A; Mariscal, C; Niazi, IK; Navallas, JIntroduction: The EMG filling factor is an index to quantify the degree to which an EMG signal has been filled. Here, we tested the validity of such index to analyse the EMG filling process as contraction force was slowly increased. Methods: Surface EMG signals were recorded from the quadriceps muscles of healthy subjects as force was gradually increased from 0 to 40% MVC. The sEMG filling process was analyzed by measuring the EMG filling factor (calculated from the non-central moments of the rectified sEMG). Results: (1) As force was gradually increased, one or two prominent abrupt jumps in sEMG amplitude appeared between 0 and 10% of MVC force in all the vastus lateralis and medialis. (2) The jumps in amplitude were originated when a few large-amplitude MUPs, clearly standing out from previous activity, appeared in the sEMG signal. (3) Every time an abrupt jump in sEMG amplitude occurred, a new stage of sEMG filling was initiated. (4) The sEMG was almost completely filled at 2–12% MVC. (5) The filling factor decreased significantly upon the occurrence of an sEMG amplitude jump, and increased as additional MUPs were added to the sEMG signal. (6) The filling factor curve was highly repeatable across repetitions. Conclusions: It has been validated that the filling factor is a useful, reliable tool to analyse the sEMG filling process. As force was gradually increased in the vastus muscles, the sEMG filling process occurred in one or two stages due to the presence of abrupt jumps in sEMG amplitude.
- ItemA Comparative Analysis of Global Optimization Algorithms for Surface Electromyographic Signal Onset Detection(Elsevier BV, 2023-09-01) Alam, S; Zhao, X; Niazi, IK; Ayub, MS; Khan, MASurface Electromyography (sEMG) is a technique for measuring muscle activity by recording electrical signals from the surface of the body. It is widely used in fields such as medical diagnosis, human–computer interaction, and sports injury rehabilitation. The detection of the onset and offset of muscle activation is a longstanding challenge in sEMG analysis. This study pioneers the implementation, configuration, and evaluation of Particle Swarm Optimization (PSO) against other optimization algorithms for sEMG signal detection, including Genetic algorithms (GA), Simulated Annealing (SA), Ant Colony Optimization (ACO), and Tabu Search (TS). The results show that the PSO algorithm achieves the highest median accuracy and F1-Score and is the fastest among the selected algorithms but has lower stability compared to Genetic algorithms and Ant colony optimization. The design and value of the cost function had a significant impact on the results, with optimal results obtained when the cost value was between 0.1203 and 0.1384. The use of these algorithms improved detection efficiency and reduced the need for manual parameter adjustment. To the best of our knowledge, no published studies have utilized Simulated Annealing, Ant colony optimization, and Tabu search meta-heuristic algorithms to detect sEMG signal onsets.