RECOVER Winter Research Projects

The 2025 Winter Research Program will run for four (4) weeks between 30 June - 25 July 2025.

Application period: 24 March - 13 April 2025

General information on the program, including how to apply, is available from the UQ Student Employability Centre’s program website.

Mobile health for chronic musculoskeletal pain: Perspectives from Culturally and Linguistically Diverse Communities

Hours of engagement & delivery mode	For the Winter program, students will be engaged for 4 weeks only. Hours of engagement must be between 20 – 36 hrs per week and must fall within the official program dates (30 June – 25 July 2025). The project will be offered through a hybrid arrangement (on-site AND remotely).
Description:	Chronic musculoskeletal pain significantly impacts quality of life and mental well-being. This issue disproportionately affects people identifying as culturally and linguistically diverse (CALD) who often experience more pain than the wider population. Despite this, they lack access to culturally appropriate and accessible pain management options. Exercise and physical activity are first-line and effective treatments for chronic musculoskeletal pain. However, engagement among CALD people with chronic musculoskeletal pain is low (17%) due to limited access to health professionals who understand their cultural needs and can provide culturally appropriate exercise prescriptions and support. Mobile health (mHealth) solutions, such as mobile apps and text messaging, can be a feasible solution, given high ownership (>90%) of a smartphone among CALD individuals. They have proven to effectively decrease pain, improve function and confidence by supporting sustained exercise. However, current mHealth interventions for chronic musculoskeletal pain lack cultural sensitivity, as they are not designed with or by CALD individuals, limiting their effectiveness in real-world clinical settings that serve CALD individuals. This project aims to bridge this gap. It aims to explore the perspectives, interests, and preferences of CALD individuals with chronic musculoskeletal pain on using mHealth to optimise their participation of exercise and physical activity. The findings from this research will inform the design, content, and functionality of a culturally sensitive, accessible and effective mHealth intervention that will optimise exercise and physical activity participation, ultimately reducing chronic musculoskeletal pain among CALD individuals.
Expected learning outcomes and deliverables:	By participating in this project, students will develop a diverse set of skills essential for personal and professional growth, including: Critical Analysis and Interpretation: Students will gain skills to analyse qualitative data, building strong critical analysis skills. Collaboration and Teamwork: The project offers a supportive environment to enhance teamwork and collaborative abilities, valuable in both academic and professional settings. Report Writing and Oral Presentation: Students may be required to produce detailed reports or deliver presentations (e.g., at team meetings), thereby improving their written and verbal communication skills. Networking: Participation will facilitate networking opportunities with peers, PhD students, mentors, and other academics. Publication Opportunities: Students may have the chance to contribute to publications from this project, adding valuable credentials to their academic and professional portfolios.
Suitable for:	We are seeking a highly motivated candidate with excellent organizational skills, a proactive attitude, and a strong interest in learning and contributing to a collaborative research project. Candidates should also have a background in health (e.g. physiotherapy, exercise physiology)
Primary Supervisor:	Dr Yanfei Xie yanfei.xie@uq.edu.au
Further info:	If you would like further information, please contact me via email at yanfei.xie@uq.edu.au, at any point in your application process.

Exploring the influence of social determinants of health on digital health use in a community-based adult population

Hours of engagement & delivery mode

Hours of engagement will be 36 hrs per week between 30 June – 25 July 2025.

The project will be offered through a hybrid arrangement.

Description:

Aim: To investigate the relationship between social determinants of health, digital health use, and willingness to use digital health technologies, among adults who have attended a community-based health clinic. Specifically, the study aims to explore how demographic variables (such as age, gender, socioeconomic status, education level, First Nations status, language spoken at home) influence the types of digital technology used to track physical activity and nutrition (if any), connect with the community, engage with services (e.g. telehealth) and their willingness to use technology for future health care interactions.

Study design: This study will employ a cross-sectional design to analyse existing data from a community-based adult population. The retrospective cross-sectional approach allows for the examination of the relationships between variables, at a specific point in time.

Population (type & location): The study population includes adults who have attended a community-based allied health clinic and includes individuals with variability in age, gender, race/ethnicity, education, employment status and access to health care services. Participants are adults who have engaged in the community-based health clinic who have completed an intake survey related to digital health use and provided consent for their data to be used for research purposes.

Data (type & collection methods): The data set includes variables related to both social determinants of health and digital health use. The key variables of interest include:

Demographics (Social Determinants of Health): Age, gender, race/ethnicity, education level, employment status, language spoken at home, healthcare utilisation.
Digital Health Use: Types of technology used to track physical activity and nutrition (e.g., wearable devices, mobile apps), Use of technology to connect with community (Y/N), Telehealth use (Y/N), Willingness to use telehealth for future healthcare interactions (Not at all to very willing).

Analysis: Descriptive statistics will be used to summarise the demographic characteristics of the study population and the extent of digital health use. The primary analysis will involve exploring associations between the demographic and digital health variables. Multivariable logistic regression models will be developed to assess the influence of multiple social determinants of health on digital health use and willingness to engage in telehealth in the future.

Expected learning outcomes and deliverables:

Scholars will gain skills in data collection, processing and analysis and have an opportunity to be involved in generating a publication from the project. Students may be asked to produce an oral presentation at the end of their project.

Suitable for:

This project is open to applications from students with a background in health. Students should have an interest in data anlysis.

Primary Supervisor:

Dr Megan Ross, Mr Denny Giguere, A/Prof Sjaan Gomersall, Dr Joshua Simmich, Professor Trevor Russell

Technology enabled rehabilitation at the RECOVER Injury Research Centre

Hours of engagement & delivery mode

Hours of engagement is 36 hrs per week from 30 June – 25 July 2025.

The project will be offered through a hybrid arrangement.

Description:

The Technology Enabled Rehabilitation stream of Research within the RECOVER Injury Research Centre seek to use cutting edge technology to facilitate the provision of high quality rehabilitation services, regardless of where the patient is physically located. Utilising technologies such as virtual reality, telerehabilitation, artificial intelligence, simulators and sensors, research focusses on how to use cutting edge technology for clinical service provision.

This winter research position will assist project leads on a number of projects within the centre and be exposed to projects across the full range of technologies. Duties may include assisting with the writing of ethics applications, assisting with data collection and analysis and assisting with the writing of manuscripts.

Expected learning outcomes and deliverables:

Scholars may gain skills in data collection and analysis, be involved in specific writing tasks such as ethics applications and have an opportunity to be involved in the writing of publications from projects. Students may also be asked to produce an oral presentation at the end of their project.

Suitable for:

This project is open to applications from students with a background in rehabilitation such as physiotherapy.

Primary Supervisor:

Professor Trevor Russell

t.russell@uq.edu.au