Tuwhera Research Repository

The Tuwhera Research Repository provides sustainable open access and archiving to a broad range of AUT produced research - theses, research outputs and datasets.

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Recent Submissions

Access status: Open Access ,
Amharic Adaptation of the OHIP-14 and WHO Oral Health Tools
(New Zealand Dental Association, 2026-07-05) Ketema, Betelehem; Lansdown, Karen; Al Naasan, Zeina; Han, Heuiwon; Trafford, Julie
Objective: To translate, culturally adapt, and preliminarily validate the English versions of the OHIP-14 and WHO Oral Health Assessment tools into Amharic for Ethiopian refugees in Aotearoa New Zealand. Methods: Following the five-stage cross-cultural adaptation framework proposed by Beaton et al. (2000), forward and backward translation, expert committee review, and pilot testing were conducted. Content validity was assessed by a bilingual panel using Likert-scale ratings and qualitative feedback. Face validity was evaluated through semi-structured interviews with five Amharic-speaking adults of Ethiopian refugee background. Quantitative data were analysed descriptively; qualitative feedback was thematically analysed. Cronbach’s alpha assessed internal consistency. Results: The adapted tools showed strong semantic and cultural equivalence. Key changes included gender-neutral pronouns (~~~ ), culturally resonant expressions (e.g., “~~~,~~~ ?” for “self-conscious”), and inclusion of traditional hygiene practices (mefakia, sintir, charcoal). Expert panel ratings confirmed clarity (M = 4.9), cultural appropriateness (M = 5.0), and semantic accuracy (M = 4.8). All OHIP-14 items scored ≥ 4 by participants, with mean clarity = 4.96 and cultural relevance = 5.0. Internal consistency was excellent (Cronbach’s α = 0.90). Participants found the modified tools respectful, understandable, and reflective of their experiences. Qualitative data from post-completion semi-structured interviews further confirmed the clarity, cultural alignment, and emotional safety of the adapted tool. Conclusion: The Amharic OHIP-14 and WHO Oral Health Assessment tools demonstrated strong face and content validity. These findings support the value of culturally and linguistically adapted tools for equitable oral health assessment in refugee populations and provide a foundation for future large-scale validation.
Access status: Open Access ,
Nothing About Us Without Us: Research Methods Enabling Participation for Aged Care Residents Who Have Dementia
(SAGE Publications, 2021-12-07) Shannon, Kay; Montayre, Jed; Neville, Stephen
The voices of people living with dementia are rarely included in primary data collection due to cognitive challenges and the concerns of researchers and others about limitations associated with informed consent. This article presents a successfully implemented, step-by-step process enabling effective participation of aged care residents with dementia using a case study approach. Three methodological and critical steps in data collection were identified that led to the successful participation of residents with dementia in research. The process corresponds with, yet is uniquely different from the common elements in the qualitative research process. These are active participation during data collection, researcher familiarization with participants, and their set interval and time-lapse considerations (timeline). The process of involvement of people with dementia in research should proceed at a pace that is guided by the participants. It is important to consider participant interview pace, pattern, and the conversation time points when interruptions occur, to restart the whole interview process. Researchers need to facilitate active engagement by building and maintaining authentic relationships with the participants.
Access status: Open Access ,
Sentiment Analysis on USA vs. New Zealand on Health and Safety Mandates During Early Stages of COVID-19 Pandemic
(IOS Press, 2021-10-27) Dales, Joshua; Mirza, Farhaan; Adel, Amr
The Coronavirus pandemic has surprised the world and social media was extremely used to express frustrations and development of the cases found. Social media tools, such as Twitter, show a comparable impact with the number of tweets related to COVID-19 indicating remarkable development in a limited ability to focus time. The purpose of this paper is to investigate the impact of Coronavirus on the United States of America (USA) and New Zealand (NZ), and how that is reflected in a sentiment analysis through the examination of American and New Zealand tweets. We have gathered tweets from a March 2020 - August 2020 and used sentiment extraction on the tweets. The major finding of this sentiment extraction is the fact that the overall average sentiment over the 5-month period stayed in a negative range in the USA and NZ. This paper aims to analyze these trends, identify patterns, and determine whether these trends were caused by the COVID-19 pandemic or outside sources. One trend that was analyzed was the spike of COVID-19 results in relation to the number of protests occurring in the USA.
Access status: Open Access ,
The Role of Applied Mechanics in Bridging the Gaps in Prior Learning for Aspirants of Engineering Education
(MDPI, 2021-10-11) Singamneni, Sarat
Building a technology-driven world appears to be the main motivational force behind students choosing to undertake engineering studies. The first year of engineering education plays a significant role in demonstrating sufficient mathematical and scientific rigor to satisfy these motivational factors. The common applied mechanics courses play a central role in achieving this. At the same time, a vast majority of students suffer from a lack of the necessary mathematical skills and analytical orientation for various reasons. Due to different educational philosophies and teaching pedagogies, a lack of proper integration between mathematics and applied mechanics is common. Several efforts were made to build better curriculum, teaching, and learning systems, resulting in widely varied solutions, but most of them require drastically different implementation approaches. With sufficient rigor in teaching and assessment, the first-year applied mechanics (common) courses designed for engineering students can solve students’ mathematical and motivational lapses and help bridge the gaps between pre-university and university education endeavours. This paper presents evidence supporting this argument. In particular, datasets collected from the direct experiences delivering the first-year static and dynamics courses to many students over the past decade and a half are analysed to establish the proposition.
Access status: Open Access ,
Real‐time and Offline Evaluation of Myoelectric Pattern Recognition for the Decoding of Hand Movements
(MDPI AG, 2021-08-23) Abbaspour, Sara; Naber, Autumn; Ortiz‐Catalan, Max; Gholamhosseini, Hamid; Lindén, Maria
Pattern recognition algorithms have been widely used to map surface electromyographic signals to target movements as a source for prosthetic control. However, most investigations have been conducted offline by performing the analysis on pre‐recorded datasets. While real‐time data analysis (i.e., classification when new data becomes available, with limits on latency under 200–300 milliseconds) plays an important role in the control of prosthetics, less knowledge has been gained with respect to real‐time performance. Recent literature has underscored the differences between offline classification accuracy, the most common performance metric, and the usability of upper limb prostheses. Therefore, a comparative offline and real‐time performance analysis between common algorithms had yet to be performed. In this study, we investigated the offline and real‐time performance of nine different classification algorithms, decoding ten individual hand and wrist movements. Surface myoelectric signals were recorded from fifteen able‐bodied subjects while performing the ten movements. The offline decoding demonstrated that linear discriminant analysis (LDA) and maximum likelihood estimation (MLE) significantly (p < 0.05) outperformed other clas-sifiers, with an average classification accuracy of above 97%. On the other hand, the real‐time investigation revealed that, in addition to the LDA and MLE, multilayer perceptron also outperformed the other algorithms and achieved a classification accuracy and completion rate of above 68% and 69%, respectively.