Contact

Email

k.scurrah@unimelb.edu.au

Credentials

Position
Honorary Principal Fellow
Melbourne School of Population and Global Health - Centres and Institutes
Education
PhD
The University of Western Australia
PhD
The University of Western Australia
Bachelors Degree (Honours)
University of Newcastle
ORCID

0000-0001-5226-7370

A/Prof Katrina Scurrah

Honorary Principal Fellow
Melbourne School of Population and Global Health
123 Scholarly works
7 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Examining the effectiveness of the Better Access initiative using data from real-world practice settings
    DOI: 10.1177/00048674251405142
  • 2026

    Journal article

    Examining Better Access use by Australian adults using data from two longitudinal studies (Ten to Men and the Australian Longitudinal Study on Women’s Health)
    DOI: 10.1177/00048674251409017
  • 2026

    Journal article

    Who uses Better Access treatment services? A re-analysis of data from the usual care arms of two randomised controlled trials
    DOI: 10.1177/00048674251406028
  • 2026

    Journal article

    Peripheral autonomic dysregulation in response to standing: a new form associated with cardiovascular disease, mobility reduction, and cognitive alterations.
    DOI: 10.1093/eurheartj/ehaf1120
  • 2025

    Journal article

    Exploring the Influence of Masculine Norms on Suicidal Ideation and Help-Seeking Behavior Findings from a Longitudinal Cohort Study of Australian Men
    DOI: 10.1027/0227-5910/a000976
  • 2020

    Research Contracts

    Statistical Consulting for AstonRx May 2020
  • 2018

    Research Grant

    Quantifying the Role of Epigenetic Factors in Neurocognitive Outcomes: A Twin Study
Katrina Scurrah

RECENT SCHOLARLY WORKS

RECENT PROJECTS

  • 2009

    Research Grant

    New Methods for Analysing Twin Data
  • 2010

    Research Grant

    Genes of the Renin-Angiotensin System and Their Association With Blood Pressure and Cardiovascular Disease

  • Research Grant

    Developing and Applying Biologically Plausible Statistical Models for Normal and Non-Normal Family Data