Citizen perspectives on public services during life events
In 2021, Monash University and colleagues at BehaviourWorks and the Australian Catholic University, partnered with the Department of Prime Minister and Cabinet and APS Reform to research citizen experiences with public services. We analysed seven waves of the Survey of Trust in Australian public services (formerly Citizen Experience Survey) to understand how services could be better tailored to Australians experiencing different life events.
Report context
Citizen-centric approaches to public services, while not new, have accelerated in popularity in the last two decades. There has been an increasing emphasis on the need for services that revolve around ‘life events’, such as changing employment status, transitioning to university, becoming a parent or carer, exiting the workforce, or suffering serious illness or injury. Life event approaches highlight how public service needs span across various agencies and levels of government. However, optimising service provisions to the needs of Australian citizens relies on robust data, and a consideration of long-term trends.
Findings snapshot
Life events
Using the Citizen Experience Survey data, we created a five-part 'life event typology'. Each ‘cluster’ group represents several ‘core’ life events that, statistically, often occur together. These clusters are:
- Family formation
- Family dissolution
- Travel and migration
- Employment
- Health
The clusters in turn, have ‘subclusters’, featuring additional life events that occur alongside one or more of the core events. Rather than viewing a life event as an isolated experience, our typology shows how multiple life events and public service interactions overlap. In doing so, it highlights the value of 'one APS' approaches to service delivery.
Life event typology: clusters and subclusters
Some life events – such as ‘experienced financial hardship’ – appear multiple times in the typology: as both a foundational life event, and as a ripple effect of other life event experiences. This hardship may be seen as an ultimate driver of service access, or, as something for services to consider as part of a holistic approach to service delivery. This may sound intuitive, but the value of our typology is that it begins to map and visualise complex connections between life events in a data-driven way.
Service outcomes
The mean (average) service outcomes for trust in the services used, and over satisfaction with public services for each of our typology groups. Survey responses are on seven point scales (i.e., from ‘strongly agree’ to ‘strongly disagree’). The dataset contains more extreme responses, but the mean response score is largely positive: falling between 4 and 6 across all typology groups.
Selected service outcome measures
Responses to measures like reliability, responsiveness, fairness, openness and honesty, and integrity showed more varied between clusters. Speaking broadly, family formation and travel and migration are areas where positive relationships with public services are found. Family dissolution, employment and health had more negative responses, relatively speaking. The lowest mean satisfaction score is in the family dissolution cluster (4.83), but there is interesting variation in outcomes in subclusters. For example, subcluster 3A) Care arrangements accompanied by travel/migration is the highest mean satisfaction score (5.55).
Despite citizens’ personal experience of stressful life events, such as those associated with family dissolution, they do not appear to be prejudiced against services overall: measures of trust and overall satisfaction are consistently positive (higher scores), and the general perception of all-of-APS is more positive than the perception of individual services. Even if citizens struggle with service interactions or do not agree with the decisions made by services (i.e., measures like fairness), service users still trust the public services and are satisfied with services overall.
We also accounted for the number of services accessed by survey respondents. However, there were no strong relationships. This means that ultimately, the number of services a user accessed did not greatly impact on whether they perceived services positively or negatively.
Research ethics information
This project is considered an analysis of secondary data collected by another party, with no identifiable or reidentifiable human participants.
Should you have any queries about the conduct of the project, please contact the Monash University Human Research Ethics (MUHREC), with the ID number 29229. Phone: +61 3 9905 2052 | Email: muhrec@monash.edu