Peer-reviewed article
Path and Bayesian network analyses in the complex design of a well-being survey via New Zealand's Integrated Data Infrastructure.
Zeng IS, Hao J, Foster M, Jones KM ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study used integrated administrative and survey data from New Zealand to understand how school absenteeism, psychosocial factors, and family circumstances relate to mental health and well-being in young people aged 15 and over. Researchers combined path analysis and Bayesian network methods to map complex relationships between these factors. The analysis found that life satisfaction, perceived health, cultural identity acceptance, and trust in education systems were all significantly linked to better mental health outcomes measured by the WHO-5 scale. The study demonstrates how linking existing data sources can provide insights into youth mental health without requiring new interviews or surveys.
Key points
- Overall life satisfaction had the strongest relationship with mental health well-being (standardized coefficient 0.36), followed by perceived health condition (0.34)
- Ease in accepting cultural identity and trust in the education system were also significantly positively related to mental health outcomes
- Perceived health was additionally influenced by fear of crime in the area and the family's overall well-being
- Using integrated data from multiple administrative and survey sources protected participant privacy and reduced costs compared to traditional data collection methods
- The study successfully applied complex survey design methodology to ensure the analysis results were representative of the New Zealand youth population
Limitations
The study is observational and cross-sectional, so it cannot establish causation between the identified factors and mental health outcomes. The analysis is constrained by the variables available in existing administrative and survey datasets, which may not capture all relevant factors affecting youth mental health.
Abstract
Introduction In mental health research involved with sensitive features and privacy issues, using integrated data offers an efficient alternative to traditional approaches such as interviews or in-person data collection. These conventional methods frequently face logistical barriers, including low response rates among study populations. Using integrated data from multiple existing administrative and survey sources provides protection for participants and economic savings for researchers, despite being constrained by the limitations of the original data sources. Our research questions were: 1) Can we conduct path and network analyses of school absenteeism, psychosocial factors, and mental health outcomes using the integrated survey data from New Zealand's Integrated Data Infrastructure (IDI)? and 2) How can we account for the complex design of the General Social Survey (GSS) to ensure representative inference? Materials and methods The study population was New Zealand youth enrolled in school, aged 15 years and older in 2018, who participated in the 2018 GSS. The study analyzed the Ministry of Education data integrated with the 2018 GSS survey data from New Zealand's IDI. To explore the relationship between outcomes of including the WHO-5, "perceived life worthwhileness", "perceived general health", and predictors including school absenteeism, psychosocial factors, and family factors, quantile mixed-effects regression, path analysis, and Bayesian network (BN) analysis were used. The complex survey design was calibrated using replicated weights from the GSS, a design-based method for complex sampling, in path and regression analyses, and bootstrap resampling, in BN analysis. Results In descending order from the weighted path model, overall life satisfaction (standardized path coefficient: 0.36), perceived health condition (0.34), ease in accepting cultural identity (0.12), and trust in the education system (0.07) were all significantly (positively) related to students' mental health well-being (WHO-5). Perceived life worthwhileness correlated with the WHO-5 but was only connected to overall life satisfaction. Similar factors were identified for perceived health, with additional attributing factors, such as fear of crime in the area and the family's overall well-being. Conclusion The integration of Bayesian networks and path analysis offers rigorous methods for detecting complex interrelationships among integrated mental health outcomes from population data and variables from a complex survey design.