Mental Health Experiences Among Undergraduate Nursing Students in a New Zealand Tertiary Institution: A Time for Change.

Nursing students in undergraduate programmes exhibit comparable, sometimes higher, levels of poor mental health and substance use compared to the general population; however, this area remains under-researched in New Zealand. The study involved 172 nursing students enrolled in the Bachelor of Nursing programme at one tertiary institution in Auckland, New Zealand. Employing a mixed-methodology approach, a 29-question survey comprising both open and closed questions was administered to explore the students' experiences with mental health and substance use, as well as their access to support services.

Can an inertial measurement unit, combined with machine learning, accurately measure ground reaction forces in cricket fast bowling?

This study examined whether an inertial measurement unit (IMU) could measure ground reaction force (GRF) during a cricket fast bowling delivery. Eighteen male fast bowlers had IMUs attached to their upper back and bowling wrist. Each participant bowled 36 deliveries, split into three different intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%.

Assessing Autistic Traits in Toddlers Using a Data-Driven Approach with DSM-5 Mapping.

Autistic spectrum disorder (ASD) is a neurodevelopmental condition that characterises a range of people, from individuals who are not able to speak to others who have good verbal communications. The disorder affects the way people see, think, and behave, including their communications and social interactions. Identifying autistic traits, preferably in the early stages, is fundamental for clinicians in expediting referrals, and hence enabling patients to access to required healthcare services.

"Crying on the Bus": First Time Fathers' Experiences of Distress on Their Return to Work.

There is increasing research interest in the experiences of new fathers taking paternity leave, but less insight into men's experiences of returning to work after the birth of their first baby. For many men in the UK context, this could take place immediately after the birth or after one or two weeks of paternity leave. This paper utilizes data from a UK-based study whilst also drawing on international literature and policy contexts.

Artificial intelligence: An eye cast towards the mental health nursing horizon.

There has been an international surge towards online, digital, and telehealth mental health services, further amplified during COVID-19. Implementation and integration of technological innovations, including artificial intelligence (AI), have increased with the intention to improve clinical, governance, and administrative decision-making. Mental health nurses (MHN) should consider the ramifications of these changes and reflect on their engagement with AI.

Ngā whakāro hauora Māori o te karu: Māori thoughts and considerations surrounding eye health.

Clinical Relevance: Research highlighting Indigenous patient perspectives is essential in the pursuit of understanding and addressing longstanding health inequities.

Background: Evidence indicates that disparities in ocular health outcomes between Māori and non-Māori are pervasive in the New Zealand health system. Evidence shows the cause of these inequities is often multifactorial; due to factors such as colonisation, ongoing marginalisation, racism, socioeconomic status, poverty and culturally unsafe practice between health professionals and Māori patients.

Examining Cognitive Factors for Alzheimer's Disease Progression Using Computational Intelligence.

Prognosis of Alzheimer's disease (AD) progression has been recognized as a challenging problem due to the massive numbers of cognitive, and pathological features recorded for patients and controls. While there have been many studies investigated the diagnosis of dementia using pathological characteristics, predicting the advancement of the disease using cognitive elements has not been heavily studied particularly using technologies like artificial intelligence and machine learning. This research aims at evaluating items of the Alzheimer's Disease Assessment Scale-Cognitive 13 (ADAS-Cog-13) test to determine key cognitive items that influence the progression of AD.

Autism screening: an unsupervised machine learning approach.

Early screening of autism spectrum disorders (ASD) is a key area of research in healthcare. Currently artificial intelligence (AI)-driven approaches are used to improve the process of autism diagnosis using computer-aided diagnosis (CAD) systems. One of the issues related to autism diagnosis and screening data is the reliance of the predictions primarily on scores provided by medical screening methods which can be biased depending on how the scores are calculated.

The relationship between bowling intensity and ground reaction force in cricket pace bowlers.

This study examined the relationship between perceived bowling intensity, ball release speed and ground reaction force (measured by peak force, impulse and loading rate) in male pace bowlers. Twenty participants each bowled 36 deliveries, split evenly across three perceived intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. Peak force and loading rate were significantly different across the three perceived intensity zones in the horizontal and vertical directions (Cohen's range = 0.

Time to review reflective practice?

Background: Reflective practice is an integral part of modern healthcare. If done well, it can significantly improve the individual skills of health care practitioners. However, we hypothesize that extrapolating individual reflective practice into broader organization applications undermines its fundamental nature and inhibits objective benchmarking within the health sector.

Quantifying cricket fast bowling volume, speed and perceived intensity zone using an Apple Watch and machine learning.

This study examined whether an inertial measurement unit (IMU) and machine learning models could accurately measure bowling volume (BV), ball release speed (BRS), and perceived intensity zone (PIZ). Forty-four male pace bowlers wore a high measurement range, research-grade IMU (SABELSense) and a consumer-grade IMU (Apple Watch) on both wrists. Each participant bowled 36 deliveries, split into two different PIZs (Zone 1 = 70-85% of maximum bowling effort, Zone 2 = 100% of maximum bowling effort).

Sexual harassment or disinhibition? Residential care staff responses to older adults' unwanted behaviours.

Background: The ethical complexity of residential care is especially apparent for staff responding to residents' inappropriate sexual expression, particularly when directed towards care workers as these residents are typically frail, often cognitively impaired, and require ongoing care.

Objectives: To explore staff accounts of how they made meaning of and responded to residents' unwanted sexual behaviours directed towards staff. This exploration includes whether staff appeared to accept harassment as a workplace hazard to be managed, or an unacceptable workplace violation, or something else.

Forecasting Covid-19: SARMA-ARCH approach.

Forecasting the number of Covid-19 cases is a crucial tool in public health policy. In this paper, we construct seasonal autoregressive moving average and autoregressive conditional heteroscedasticity models to forecast the spread of the infection in the UAE. While most of the existing literature is dedicated to forecasting the total number of infections, we endeavor to forecast the number of infections which is a significantly more challenging task due to the greater volatility.

A meta ethnography of the cultural constructs of menopause in indigenous women and the context of Aotearoa/New Zealand.

The researchers aim in this synthesis is to interpret the cultural constructions of menopause in Indigenous women and apply these interpretations to the context of Māori women in Aotearoa/New Zealand. There is a lack of research about Indigenous women's interpretations of health, and how culture mediates understandings and experiences of menopause. There is even less research regarding Māori women's understandings and experiences of menopause, as the discourse is dominated by Western ideology.

The experience and meaning of recovery-oriented practice for nurses working in acute mental health services.

Since the 1990s, New Zealand mental health policy has shifted from a focus on the management of symptoms and risk to the recovery of psychological, social, cultural, and physical well-being. Despite a vision for recovery-oriented services being integrated within national and regional policies, there is growing concern that barriers to recovery-oriented service provision continue to exist. Such barriers include the attitudes, skills, and knowledge of front-line staff, as well as system issues.

Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two basic units in the proposed image cryptosystem, the permutation unit and the diffusion unit, are designed through SNP systems with multiple channels and polarizations (SNP-MCP systems), and SNP systems with astrocyte-like control (SNP-ALC systems), respectively. Different from the serial computing of the traditional image permutation/diffusion unit, SNP-MCP-based permutation/SNP-ALC-based diffusion unit can realize parallel computing through the parallel use of rules inside the neurons.

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was attached to the thoracic back of 44 fast bowlers. Each participant bowled 36 deliveries at two different PIZ zones (Zone 1 = 24 deliveries at 70% to 85% of maximum perceived bowling effort; Zone 2 = 12 deliveries at 100% of maximum perceived bowling effort) in a random order.

Dementia medical screening using mobile applications: A systematic review with a new mapping model.

Early detection is the key to successfully tackling dementia, a neurocognitive condition common among the elderly. Therefore, screening using technological platforms such as mobile applications (apps) may provide an important opportunity to speed up the diagnosis process and improve accessibility. Due to the lack of research into dementia diagnosis and screening tools based on mobile apps, this systematic review aims to identify the available mobile-based dementia and mild cognitive impairment (MCI) apps using specific inclusion and exclusion criteria.

The correlation of everyday cognition test scores and the progression of Alzheimer's disease: a data analytics study.

The process of diagnosing dementia conditions, especially Alzheimer's disease, and the cognitive tests that are involved in this process, are important areas of study. Everyday Cognition (ECog) is one test that can be used as part of Alzheimer's disease diagnosis to measure cognitive decline in different areas. In this study, we investigate two versions of the ECog test: the study partner reported version (ECogSP), and the patient reported version (ECogPT).

Xbee-Based WSN Architecture for Monitoring of Banana Ripening Process Using Knowledge-Level Artificial Intelligent Technique.

Real-time monitoring of fruit ripeness in storage and during logistics allows traders to minimize the chances of financial losses and maximize the quality of the fruit during storage through accurate prediction of the present condition of fruits. In Pakistan, banana production faces different difficulties from production, post-harvest management, and trade marketing due to atmosphere and mismanagement in storage containers. In recent research development, Wireless Sensor Networks (WSNs) are progressively under investigation in the field of fruit ripening due to their remote monitoring capability.

Exploring feature selection and classification methods for predicting heart disease.

Machine learning has been used successfully to improve the accuracy of computer-aided diagnosis systems. This paper experimentally assesses the performance of models derived by machine learning techniques by using relevant features chosen by various feature-selection methods. Four commonly used heart disease datasets have been evaluated using principal component analysis, Chi squared testing, ReliefF and symmetrical uncertainty to create distinctive feature sets.

A clustering approach for autistic trait classification.

Machine learning (ML) techniques can be utilized by physicians, clinicians, as well as other users, to discover Autism Spectrum Disorder (ASD) symptoms based on historical cases and controls to enhance autism screening efficiency and accuracy. The aim of this study is to improve the performance of detecting ASD traits by reducing data dimensionality and eliminating redundancy in the autism dataset. To achieve this, a new semi-supervised ML framework approach called Clustering-based Autistic Trait Classification (CATC) is proposed that uses a clustering technique and that validates classifiers using classification techniques.