On 20 September 2021, The Sax Institute hosted its latest Sax Forum – a workshop aimed at early-to-mid-career researchers interested in using cohort data for mental health research.
This Forum featured six panellists, all of whom work closely with big data sets such as the 45 and Up Study, the Australian Longitudinal Study on Women’s Health and the PATH Through Life Project. Panelists included:
- Scientia Professor Kaarin Anstey, UNSW Sydney
- Piumee Bandara, Sax Institute
- Professor Julie Byles, University of Newcastle
- Professor Cate D’Este, Sax Institute
- Honorary Associate Professor Annette Erlangsen, Australian National University
- Professor Andrew Page, Western Sydney University
There is increasing interest in mental health research, and longitudinal studies offer researchers a valuable opportunity to track changes in mental health over long periods of time. But working with such longitudinal data sets can be daunting for those in the early stages of their research careers.
During the Forum’s lively discussion, panelists shared techniques and lessons learned from their own experience using cohort data for mental health research. This included: navigating complex protocols and permissions; using emerging technologies for collecting mental health data; and creating high-impact research to inform policy and practice. The panel discussion also suggested a number of tips for researchers interested in using longitudinal data. These included:
- Have a clear understanding of your research question and a detailed statistical data analysis plan.
- Allow the necessary time for data preparation so you can understand your data. People often underestimate this preparation stage. As a researcher, up to 90% of your time can be spent managing and understanding the data prior to analysis commencing.
- Supervision and mentoring is crucial, and can be a great support when inevitable questions emerge around handling data. Having a network of EMCRs is also helpful.
- “Love and hug the data” for a long time before you do the analysis – it’s not wasted time. Learning how to work with and link data sets are important skills.
- There are lots of different software packages for analysing big data. Before you start, find out which type of software makes sense for your statistical analysis.
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