Digital Commons Network^™

Caring For Post Icu Patients: Knowledge And Attitude Among Nurses Working In General Wards, At Tertiary Hospitals, Dar Es Salaam, Tanzania, Nazahed Mkiramweni, Kahabi Isangula, Masunga Iseselo, Dickson Mkoka, Emmanuel Mlay

School of Nursing & Midwifery, East Africa

Introduction: Caring for patients from the Intensive Care Unit (post-ICU) in general wards iscritical in determining patient outcomes. As primary caregivers, nurses provide hour-to-hour care and are essential in monitoring and addressing any signs of deterioration during this crucial transition period. Adequate knowledge and a positive attitudeare vital for ensuring the timely identification and management of complications. This study aimed to assess the knowledge and attitudes of nurses caring for post-ICU patients in general wards.

Methods: A hospital-based descriptive cross-sectional study wasconducted from May to August 2021 at Muhimbili National Hospital (MHN), Muhimbili Orthopedic Institute (MOI), and Jakaya …

Vercation: Precise Vulnerable Open-Source Software Version Identification Based On Static Analysis And Llm, Yiran Cheng, Ting Zhang, Lwin Khin Shar, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun

Research Collection School Of Computing and Information Systems

Open-source software (OSS) has experienced a surge in popularity, attributed to its collaborative development model and cost-effective nature. However, the adoption of specific software versions in development projects may introduce security risks when these versions bring along vulnerabilities. Current methods of identifying vulnerable versions typically analyze and extract the code features involved in vulnerability patches using static analysis with pre-defined rules. They then use code clone detection to identify the vulnerable versions. These methods are hindered by imprecision due to (1) the exclusion of vulnerability- irrelevant code in the analysis and (2) the inadequacy of code clone detection. This paper …

Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao

Research Collection School Of Computing and Information Systems

Garbage Collection (GC) in the Java Virtual Machine (JVM) serves as an automatic memory management mechanism, efficiently reclaiming unused memory space in different production scenarios. To optimize JVM performance, developers typically fine-tune the garbage collector by identifying an optimal set of GC configurations for specific scenarios. Despite the sophisticated design of garbage collectors, they still have the potential for bugs in different settings, and these bugs can result in more severe consequences. Hence, comprehensive testing of these garbage collectors is imperative before their release. Code coverage criteria are typically employed to assess the comprehensiveness of a test suite. However, traditional …

Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Function calling is a fundamental capability of today's large language models, but sequential function calling posed efficiency problems. Recent studies have proposed to request function calls with parallelism support in order to alleviate this issue. However, they either delegate the concurrent function calls to users for execution which are conversely executed sequentially, or overlook the relations among various function calls, rending limited efficiency. This paper introduces LLMOrch, an advanced framework for automated, parallel function calling in large language models. The key principle behind LLMOrch is to identify an available processor to execute a function call while preventing any single processor …

Less Is More: Docstring Compression In Code Generation, Guang Yang, Yu Zhou, Wei Cheng, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, Xin Zhou, Ke Liu, David Lo, Taolue Chen

Research Collection School Of Computing and Information Systems

The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocString to executable code. DocStrings, which capture user requirements for the code and are typically used as the prompt for LLMs, often contain redundant information. Recent advancements in prompt compression have shown promising results in Natural Language Processing (NLP), but their applicability to code generation remains uncertain. Our empirical study shows that the state-ofthe-art prompt compression methods achieve only about 10% reduction, as further reductions …

Fcghunter: Towards Evaluating Robustness Of Graph-Based Android Malware Detection, Shiwen Song, Xiaofei Xie, Ruitao Feng, Qi Guo, Sen Chen

Research Collection School Of Computing and Information Systems

Graph-based detection methods leveraging Function Call Graph (FCG) have shown promise for Android malware detection (AMD) due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent approaches evaluate the robustness of FCG-based detectors using adversarial attacks, their effectiveness is constrained by the vast perturbation space, particularly across diverse models and features. To address these challenges, we introduce FCGHunter, a novel robustness testing framework for FCG-based AMD systems. Specifically, FCGHunter employs innovative techniques to enhance exploration and exploitation within this huge search space. Initially, it identifies critical …

Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He

Research Collection School Of Computing and Information Systems

With the revolution of generative AI, video-related tasks have been widely studied. However, current state-of-the-art video models still lag behind image models in visual quality and user control over generated content. In this paper, we introduce TokenWarping, a novel framework for temporally coherent video translation. Existing diffusion-based video editing approaches rely solely on key and value patches in self-attention to ensure temporal consistency, often sacrificing the preservation of local and structural regions. Critically, these methods overlook the significance of the query patches in achieving accurate feature aggregation and temporal coherence. In contrast, TokenWarping leverages complementary token priors by constructing temporal …

Prisrv+: Privacy And Usability-Enhanced Wireless Service Discovery With Fast And Expressive Matchmaking Encryption, Yang Yang, Guomin Yang, Yingjiu Li, Pengfei Wu, Rui Shi, Minming Huang, Jian Weng, Hwee Hwa Pang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The evolution of decentralized identity (DID) and self-sovereign identity (SSI) frameworks, as endorsed by W3C Verifiable Credentials (VC) and eIDAS 2.0, underscores the need for secure, efficient, and privacy-preserving credential management. However, existing credential systems often depend on centralized issuers, lack efficient aggregation mechanisms, or fail to ensure unlinkability across authentication sessions. To address these challenges, we propose DISC (Decentralized Identity System with Self-Sovereign Credential Aggregation), a novel credential system that enables multi-authority credential issuance, user-controlled credential aggregation, and unlinkable authentication. DISC allows users to aggregate credentials from multiple issuers while maintaining constant-size authentication tokens and supporting batch verification for …

Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang

Research Collection School Of Computing and Information Systems

Node classification is a fundamental problem in information retrieval with many real-world applications, such as community detection in social networks, grouping articles published online and product categorization in e-commerce. Zero-shot node classification in text-attributed graphs (TAGs) presents a significant challenge, particularly due to the absence of labeled data. In this paper, we propose a novel Zero-shot Prompt Tuning (ZPT) framework to address this problem by leveraging a Universal Bimodal Conditional Generator (UBCG). Our approach begins with pre-training a graph-language model to capture both the graph structure and the associated textual descriptions of each node. Following this, a conditional generative model …

Fortifying The Seams Between C/C++ And Rust: Characterizing Bugs In Interop Tools, Xuemeng Cai, Jiakun Liu, Cunyang Liu, Lingfeng Bao, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Rust has become increasingly popular in recent years due to its safety and high performance. Despite these advantages, Rust projects rarely start from scratch in practice, and many Rust-based systems instead use hybrid programming, where Rust interoperates with existing C/C++ code. To reduce the manual effort involved in this interoperation (interop) process, several interop tools have been proposed to facilitate hybrid programming between Rust and C/C++. However, the challenges and limitations of these tools remain largely unexplored, leaving developers unclear about the future directions and users unclear about the appropriate usage scenarios. To fill the gap, we mined 320 bugs …

Grounding Is All You Need? Dual Temporal Grounding For Video Dialog, You Qin, Wei Ji, Xinze Lan, Hao Fei, Xun Yang, Dan Guo, Roger Zimmermann, Lizi Liao

Research Collection School Of Computing and Information Systems

In the realm of video dialog response generation, capturing both the essence of video content and the temporal nuances of conversation history is crucial. While some approaches rely on large-scale pretrained visual-language models, often neglecting temporal dynamics, others emphasize spatial-temporal relationships within videos but demand intricate object trajectory pre-extractions and overlook dialog temporal dynamics. This paper introduces the Dual Temporal Grounding-enhanced Video Dialog model (DTGVD), designed to bridge the gap between these two approaches. DTGVD uniquely integrates the strengths of both by emphasizing dual temporal relationships. It achieves this by predicting dialog turn-specific temporal regions, selectively filtering video content, and …

Learnable Game-Theoretic Policy Optimization For Data-Centric Self-Explanation Rationalization, Yunxiao Zhao, Zhiqiang Wang, Xingtong Yu, Xiaoli Li, Jiye Liang, Ru Li

Research Collection School Of Computing and Information Systems

Rationalization, a data-centric framework, aims to build self-explanatory models to explain the prediction outcome by generating a subset of human-intelligible pieces of the input data. It involves a cooperative game model where a generator generates the most human-intelligible parts of the input (i.e., rationales), followed by a predictor that makes predictions based on these generated rationales. Conventional rationalization methods typically impose constraints via regularization terms to calibrate or penalize undesired generation. However, these methods are suffering from a problem called mode collapse, in which the predictor produces correct predictions yet the generator consistently outputs rationales with collapsed patterns. Moreover, existing …

Mm-Attackg: A Multimodal Approach To Attack Graph Construction With Large Language Models, Yongheng Zhang, Xinyun Zhao, Yunshan Ma, Haokai Ma, Yingxiao Guan, Guozheng Yang, Yuliang Lu, Xiang Wang

Research Collection School Of Computing and Information Systems

Cyber Threat Intelligence (CTI) parsing aims to extract key threat information from massive data, transform it into actionable intelligence, enhance threat detection and defense efficiency, including attack graph construction, intelligence fusion, and indicator extraction. Among these research topics, Attack Graph Construction (AGC) is essential for visualizing and understanding the potential attack paths of threat events from CTI reports. Existing approaches primarily construct the attack graphs purely from the textual data to reveal the logical threat relationships between entities within the attack behavioral sequence. However, they typically overlook the specific threat information inherent in visual modalities, which preserves key threat details …

Obstructive Sleep Apnea Prediction: A Comprehensive Review And Comparative Study, Thi Khanh Chi Huynh, Amonae Dabbs-Brown, Anna Jurek-Loughrey, James Mulhall, Tuan Dung Pham, Ngoc Phu Doan, Viet Hung Tran, Zichi Zhang, Xuan Hoang Nguyen, Yimeng An, Peixin Li, Phi Hung Nguyen, Thi Linh Hoang, Xinming Shi, Hans Vandierendonck, Sebastien Bailly, Jean-Louis Pépin, Thai Son Mai

Research Collection School Of Computing and Information Systems

Obstructive Sleep Apnea (OSA) is a highly prevalent sleep disorder linked to considerable public health burdens and comorbidities. However, its heterogeneous presentation and the limited accessibility of traditional diagnostic tools such as polysomnography (PSG) lead to widespread underdiagnosis. As a result, artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL) models, have attracted attention as an alternative pathway to detection. This paper first provides a comprehensive review of AI-driven OSA diagnosis, covering different diagnosis problems, input-data types, data biases, pre-processing techniques, and model performance. We then leverage the largest clinical dataset used in OSA prediction to date, …

Imagined Nations: Ireland, Palestine, And The Politics Of Anti-Colonial Memory, Grace P. Wingerter

Armstrong Undergraduate Journal of History

This paper covers the life and career of notable IRA operative Brendan “the Dark” Hughes and how his thoughts on the “Armed Struggle” or “Cause” changed over time. Brendan Hughes was forced to frequently deal with violent and heavy handed discrimination from Protestants, which led to him joining the Paramilitary movements as a result of frustration and misplaced youthful vigor. Brendan played a major role in the Troubles through his planning of prolific violent attacks such as the Four Square Laundry attack, Bloody Friday, and the H Block blanket protest and subsequent hunger strike in the Maze Prison. Brendan’s disconnect …

Impact Of The Lace Index Scoring Tool On Sepsis Readmissions, Tabitha M. Keaty Sheppard

Electronic Theses and Dissertations

Sepsis is a life-threatening medical emergency that negatively affects patients and healthcare organizations worldwide. Consequently, sepsis survivors are presented with even greater health risks following acute hospitalizations, and the financial implications on healthcare organizations increase with each patient readmission. This quality improvement project studied the impact of the LACE Index Scoring Tool on sepsis readmissions within a single healthcare organization in the southern region of the United States. Per quality metric data, sepsis readmissions have remained a prevalent issue at the project site. The purpose of this doctoral project was to reduce 30-day sepsis readmissions following the implementation of the …

Longevity, Resilience, And Thriving Of Women In Ministry: A Case Study Of Women In Ministry From A United Pentecostal Holiness Church, Eunice Cheryl Feltus Little

Electronic Theses and Dissertations

Abstract

The problem of ministry attrition caused by burnout is well documented. Research attributes the impact of burnout on the resilience, longevity, and thriving of ministry workers to role-related stress and adversity. High attrition rates throughout religious organizations and a lag in longevity and resilience contribute to a shortage of ministry workers. Some ministry workers leave the vocation because of stress and burnout, yet others persevere. Despite the possible adverse effects, many men and women find a sense of well-being and joy in ministry work. This qualitative distributive case study focused on those who stayed in ministry and the strategies …

Leader Rounding For Outcomes To Improve Employee Retention, Laura R. Escobar

Electronic Theses and Dissertations

Intention to leave a nursing staff position, if not addressed, may lead to an increased rate of nursing turnover. High turnover rates can negatively affect staffing patterns, increase organizational costs, and disrupt the continuity of patient care. A quantitative quasi-experimental pre-/posttest design was used to evaluate the impact of the High Reliability Organization Leader Rounding for Outcomes tool to reduce the intent-to-leave scores, as measured by the Turnover Intention Scale (TIS-6), compared to current practice over 12 weeks. Implementation of the tool provided a structured leader rounding process designed to strengthen communication, recognize staff contributions, and proactively identify workplace concerns. …

Patient Wait Time And Throughput Interventions In The Cardiology Outpatient Setting, Chioma Ohiri Tawose

Electronic Theses and Dissertations

Healthcare collaboration and patient care require effective communication. Poor communication impacts wait time. Inadequate communication in the outpatient cardiology clinic can lead to disruptive patient throughput, or workflow, and extend patient length of visit. The purpose of this project was to implement a means of communication for clinicians and healthcare assistants to improve patient flow and cut down idleness, ultimately reducing patient wait time. The project established the incorporation of a built-in electronic health record communication notification system, the Event Button, for asynchronous communication between staff. A quantitative quality improvement design was used to conduct this project. Inferential and descriptive …

Examining The Effects Of Viewing Nature And Animal Smartphone Wallpapers On Affect, Behaviour, And Cognition: A Randomised Cross-Over Trial, Nadyanna M. Majeed, Nicole R. Y. Chen, Adalia Y. H. Goh, Meilan Hu, Kenneth J. J. Koh, Yuolmae H. G. Ang, Andree Hartanto

Research Collection School of Social Sciences

This study aims to investigate the effects of different smartphone lock screen wallpapers on weekly perceived well-being, procrastination, and productivity in young adults. Through a pre-registered within-subject experiment, 60 participants were exposed to three smartphone wallpaper conditions: nature, animal, and neutral (control). Each participant experienced each condition over three weeks, with the order of conditions counterbalanced. Using Frequentist and Bayesian analyses, we did not find any differences between conditions across the pre-registered confirmatory outcomes (i.e., life satisfaction, positive affect, negative affect, stress, productivity, and procrastination). Exploratory outcomes related to lock screen engagement, however, revealed some meaningful effects. Animal-themed smartphone wallpapers …

Flips In Two-Dimensional Hypertriangulations, Herbert Edelsbrunner, Alexey Garber, Mohadese Ghafari, Teresa Heiss, Morteza Saghafian

School of Mathematical & Statistical Sciences Faculty Publications

We study flips in hypertriangulations of planar points sets. Here a level-k hypertriangulation of n points in the plane is a subdivision induced by the projection of a k-hypersimplex, which is the convex hull of the barycenters of the (k−1)-dimensional faces of the standard (n−1)-simplex. In particular, we introduce four types of flips and prove that the level-2 hypertriangulations are connected by these flips.

Constrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

In this work, we extend the classical framework of quantization for Borel probability measures defined on normed spaces ℝ𝑘 by introducing and analyzing the notions of the nth constrained quantization error, constrained quantization dimension, and constrained quantization coefficient. These concepts generalize the well-established nth quantization error, quantization dimension, and quantization coefficient, which are traditionally considered in the unconstrained setting and thereby broaden the scope of quantization theory. A key distinction between the unconstrained and constrained frameworks lies in the structural properties of optimal quantizers. In the unconstrained setting, if the support of P contains at least n elements, then the …

Analysis Of Pediatric Cervical Spine Injury Evaluation Workflow In The Emergency Department, Annie J Truelove, Megan E Gregory, Fahd A Ahmad, Sean P Pajak, Nicole C Hammer, Daniel Corwin, Leah Tzimenatos, Scott O King, Matthew Szadkowski, Martin J Herman, Julie C Leonard

2020-Current year OA Pubs

OBJECTIVES: The decision to image children for cervical spine injuries (CSI), an uncommon injury with high associated morbidity and mortality, is complex. X-rays and computed tomography are often used to screen for CSI; however, radiation exposure increases lifetime cancer risk. We recently developed a CSI prediction rule to inform pediatric imaging decisions. To guide implementation, we conducted a workflow analysis of CSI screening in children after blunt trauma.

METHODS: We interviewed emergency departments (ED) and trauma clinicians at 21 hospitals following the applied cognitive task analysis task diagram, knowledge audit, and simulation interview approaches. Interviews were coded using a combined …

Prediabetes Associates With Musculoskeletal Alterations Independent Of Total Body Adiposity, Alan Fappi, Clifton J Holmes, Chao Cao, Vasavi Shabrish, Aman P Aher, Karen Shen, Paul K Commean, Dwight A Towler, Dominic N Reeds, Gretchen A Meyer, Bettina Mittendorfer

2020-Current year OA Pubs

BACKGROUND: Excess adiposity is a major risk factor for insulin resistance, prediabetes, and Type 2 diabetes and increases the risk for sarcopenia and osteosarcopenia later in life. It has been proposed that altered metabolic function and musculoskeletal status in people with obesity are directly linked, presumably because they share common pathophysiological mechanisms. However, the effect of metabolic dysfunction, independent of adiposity, on musculoskeletal status is unknown.

METHODS: We performed a comprehensive assessment of musculoskeletal status in people with overweight/obesity and prediabetes (n = 12; 72% women; age: 67 ± 6 years; weight: 81 ± 11 kg; mean ± SD) and …

In-Silico Trial Of Same-Day Simulation-Free Spatially Fractionated Adaptive Radiotherapy (Sf2-Art), Dennis N Stanley, Alyssa R Birchmeier, Carlos E Cardenas, Richard A Popple, Natalie Viscariello, Joel A Pogue, Courtney B Stanley, Mehran Yusuf, Michael Soike, Samuel R Marcrom, Joseph Harms

2020-Current year OA Pubs

PURPOSE: Here we present an in-silico trial of the feasibility and deliverability of a same-day, simulation-free workflow for spatially fractionated adaptive radiotherapy (SF

METHODS AND MATERIALS: Ten patients (five thoracic and five extremity), previously treated with spatially fractionated radiotherapy (SFRT), were selected for this in silico trial. A two-phase regimen was simulated: Phase 1 delivered 12 Gy SBRT to a uniform, predefined high-dose lattice and 4 Gy to the gross tumor volume (GTV); Phase 2 consisted of 4 additional fractions of 4 Gy to the GTV. The planning workflow was performed entirely in silico, without the need for CT simulation. …

Accelerated Diffusion Basis Spectrum Imaging With Tensor Computations, Kainen L Utt, Jacob S Blum, Donsub Rim, Sheng-Kwei Song

2020-Current year OA Pubs

This paper introduces an advanced framework for accelerated processing of diffusion-weighted imaging (DWI) data that utilizes an entire-image modeling approach to optimize the estimation of diffusion parameters from DWIs by mapping input diffusion data to predicted signals and estimating parameter values via a stochastic gradient descent optimizer (Adam). To validate this approach, we applied this framework to diffusion basis spectrum imaging (DBSI) and analyzed in vivo human brain and ex vivo mouse brain DWIs. Results demonstrate significant improvements to computational speed and signal-to-noise ratio (SNR) in estimated parameter maps compared to standard DBSI. Our approach is applicable to any diffusion …

Mitigating Malware Prevalence In Networks With Arbitrary Topologies: A Flip-It Cyber Game Approach Integrated With Epidemic Modeling, Mousa Tayseer Jafar, Lu Xing Yang, Gang Li, Robin Doss, Kon Mouzakis, Rajesh Vasa, Helge Janicke, Ahmed Ibrahim, Ahmed Mohsin, Iqbal H. Sarker, Kristen Moore, Seyit Camtepe, Diksha Goel

Research outputs 2022 to 2026

Cyber threats have evolved in complexity, aiming at a wide range of sectors using advanced methods and tools. This evolving threat landscape challenges existing cybersecurity frameworks, many of which lack the adaptability to counteract the complex tactics of sophisticated adversaries. Developing robust cyber defense strategies requires simulating dynamic interactions between attackers and defenders across high, moderate, and low-impact scenarios. The Flip-It cyber game serves as an intelligent framework for simulating these interactions, enabling the analysis of adaptive strategies in cybersecurity. This paper aims to address the problem of mitigating malware prevalence with full consideration of attack/defense capabilities in arbitrary network …

Novel Buxus Papillosa-Assisted Green Synthesis Of Copper And Nickel Oxide Nanoparticles With Enhanced Catalytic Degradation Of Alizarin Red S Dye, Afrah Zahid, Warda Hassan, Syed Awais Ali, Zahoor Ullah, Mohammad Younas, Syed Nasir Shah, Ali Fatehizadeh, Mashallah Rezakazemi

Research outputs 2022 to 2026

In this work, the biogenic synthesis route using the leaf extract of Buxus papillosa was employed for the green synthesis of copper oxide (CuO) and nickel oxide (NiO) nanoparticles (NPs), which were then applied for the catalytic degradation of Alizarin Red S dye (ARS) as a model organic pollutant. Scanning electron microscopy (SEM) analysis confirmed spherical and rod-like morphologies for CuO and NiO NPs, respectively, while Energy dispersive spectroscopy (EDS) verified their elemental composition. The average crystallite sizes of CuO and NiO NPs were 6.21 and 5.94 nm, respectively, as determined by X-ray diffraction (XRD), and their optical band gaps …

Feasibility And Implementation Of Interval-Gap4: A Global Randomised Controlled Trial Of Intense Hybrid-Supervised/Self-Managed Versus Self-Directed Exercise For Metastatic Prostate Cancer, Stacey A. Kenfield, Nicolas H. Hart, Kerry S. Courneya, Rosemary Greenwood, June M. Chan, Jennette Sison, Li Zhang, Sarah Rudman, Leah Ung, Moritz Schumann, Erin L. Van Blarigan, Sam Mckeown, Charles J. Ryan, James Catto, Daniel A. Galvão, Robert U. Newton, Fred Saad

Research outputs 2022 to 2026

Background and objective: Physical activity is associated with a lower risk of mortality in men with prostate cancer (PC); yet, randomised controlled trials with survival endpoints are nonexistent. INTense ExeRcise for surviVAL-Global Action Plan 4 (INTERVAL-GAP4) was a global phase 3 trial designed to test whether structured, hybrid-supervised/self-managed exercise improves survival in men with metastatic PC. The trial was stopped early due to poor accrual. This paper reports feasibility and implementation outcomes. Methods: Men with metastatic PC were randomised (1:1) to a supervised/self-managed moderate- to high-intensity resistance and aerobic programme (three sessions per week for 2 yr) or to self-directed …

Back-On-Track: Protocol For Randomised Controlled Feasibility Trial Of Behavioural Activation In Farmers With Mood Problems, Alison Kennedy, Richard Gray, Martin Jones, Anna Greene, Lauren Mitchell, Meera Senthuren, Suzy Malseed, Feby Savira, Kelly Barnes, Kate Gunn, Susan Brumby

Research outputs 2022 to 2026

The mental health of people living in farming communities has been identified as an important public health issue. Cumulative exposure to a range of situational factors contributes to heightened risk of poor mental health and suicide. Access to evidence-based psychological treatments is limited by the availability of skilled mental health professionals. The aim of this trial—co-designed by members of the farming community—is to establish the feasibility of conducting randomised controlled, trial-testing, peer-worker-delivered Behavioural Activation in the farming community. We will undertake a single-blind, parallel group, randomised controlled feasibility trial in rural Australia. People living in farming communities aged over 15 …