An intersection between IT and psychology – my journey towards an interdisciplinary career

A common question I was asked most often is “What made you transition from software development (IT) to psychology?”. In the past, I wished I could answer it with conviction. It wasn’t until I stumbled across the Digital Health CRC HDR program, where I recently completed my PhD project (https://digitalhealthcrc.com/projects/integrating-mental-wellness-assessment-advice-on-sisu-stations/), that I could.

I still vividly remember that my enthusiasm was apparent to others during the project’s conception, most likely because I had left the IT industry for a few years to study psychology. I was eager to ‘get my hands dirty’ again, hitting goals and achieving outcomes. In the first three months, I developed an ambitious project plan that included multiple qualitative and quantitative studies, aiming to deliver a comprehensive next-generation mental health product by the end of the project.

I spent the first year familiarising myself with the current state of the field through academic references before defining appropriate research aims, objectives, and questions that aligned with the expected deliverables. At that time, I realised this project was NOT just another industry project. I was required to develop a thesis that made an original contribution to the field of mental health. It was no surprise that I received extensive feedback during my confirmation of candidature, which took place 12 months after my candidature began. The project’s scope was drastically reduced so that the review panel could be confident I would complete the project on time.

On reflection, I think a translational research project, as compared to an industry project, focuses less on doing and more on thinking (specifically, critical thinking). An industry project prioritises completing measurable tasks and milestones, with most task executions typically known (e.g., designing and implementing technical solutions). There are times when a proof-of-concept is warranted, but it is short and time-bound (e.g., a “spike” within a Scrum agile framework: https://www.scrum.org/resources/what-scrum-module). In contrast, although a PhD project is technically time-bound, albeit longer, the tasks (studies) are usually confronted by the unknown, which, in general, may or may not align with the industry partner’s goals. For example, a null result study: the experimental result did not support the study’s hypotheses.

The translational project I worked on had multiple constraints, which ultimately I believe became its saving grace. First, the expectation of certain deliverables by the end of the project to the industry partner meant that the project could not afford to indulge in purely academic inquisition, which helped on several occasions when pragmatic decisions were made (see Koh et al., 2023; Koh et al., 2025; Koh et al., 2024). Second, as a PhD project, I was expected to make an original contribution to the field. That was where I found it most challenging but learnt the most during my journey, particularly with regard to critical thinking and communication. Third, the nature of my project had lent itself to a rigorous process widely adopted within the literature. There was no room for unjustified decisions (a.k.a. shortcuts) to speed up the end result.

Ultimately, I learnt a lot during my PhD journey, including how to navigate the tension between the industry partner’s needs, academic rigour (evidence-based) and the requirements of my PhD. At times, I wonder whether the current higher degree research program structure (e.g., thesis-based programs) best meets an industry partner’s needs, or more broadly, how likely an innovation is to deliver the outcome and ROI an industry partner desires.

During my journey, I have also met many supportive peers, collaborators, and mentors, which has further enriched this important milestone in my life. Knowing the limitless sea of knowledge has motivated me to be more curious. In the future, I hope to integrate my experience and learning into an interdisciplinary career (digital mental health, software development, and practising as a psychologist) to contribute positively to society.

References

Koh, Z. H., Serbetci, D., Skues, J., & Murray, G. (2025). Toward Digital Self-Monitoring of Mental Health in the General Population: Scoping Review of Existing Approaches to Self-Report Measurement. JMIR Mental Health, 12, e59351. https://mental.jmir.org/2025/1/e59351

Koh, Z. H., Skues, J., & Murray, G. (2023). Digital self-report instruments for repeated measurement of mental health in the general adult population: A protocol for a systematic review. BMJ Open, 13(1), e065162. https://doi.org/10.1136/bmjopen-2022-065162

Koh, Z. H., Zarnegar, A., Skues, J., & Murray, G. (2024). Complementing semi-automated tools with text-mining techniques for a large-scale systematic review: A hybrid approach. https://osf.io/preprints/psyarxiv/e25tn