Connecting precariousness and depression: From causal discovery to intervention simulation

Precariousness and depression are closely linked, but the potential causal structure of this relationship and the extent to which feedback between them may shape intervention responses remain unclear. Using cross-sectional data from more than 21,000 adults in the multi-ethnic HELIUS study, we use constraint-based causal discovery methods that allow for latent confounding and feedback to generate hypotheses about candidate graph structures linking precariousness domains and depressive symptoms. Because the data are cross-sectional and many edge orientations are not uniquely determined, we summarize the findings in terms of their stability across specifications and resampling, and treat suggested directions as tentative, data-compatible hypotheses rather than identified causal effects. Across specifications and algorithms, financial stress is the precariousness domain most consistently linked to depression in the causal discovery summaries. Directional edge marks are less stable: in FCI summaries, the edge pattern is more often consistent with financial stress preceding depression, whereas CCI and PC tend to leave the same relation unresolved. In addition, several symptom-level configurations suggest that depressive symptoms may contribute to downstream social precariousness. We then use a calibrated simulation model to examine how depression and precariousness could co-evolve under intervention scenarios across different feedback strengths compatible with the observed data. In the simulation model, slower but more persistent improvement follows intervention under stronger internal feedback, whereas faster but less durable change follows under weaker feedback. These findings suggest that intervention responses may depend not only on the size of the external change but also on the feedback structure linking precariousness and depression. Longitudinal and quasi-experimental studies are needed to clarify directionality, estimate feedback strengths, and assess the policy relevance of these patterns. • Causal discovery maps candidate structure linking precariousness and depression • Financial stress emerges as the most consistently recovered link to depression • Cross-method disagreement in edge directions keeps causal ordering unresolved • A reduced simulation model examines responses to reduced financial stress • Stronger feedback slows improvement but makes it more persistent over time

Authors

Institutions

Publication Details

Journal
SSM - Mental Health
Published
2026-04-27
DOI
https://doi.org/10.1016/j.ssmmh.2026.100637
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Connecting precariousness and depression: From causal discovery to intervention simulation

Vítor V. Vasconcelos, Kyuri Park, Karien Stronks, Leonie K. Elsenburg et al.
SSM - Mental Health
Advanced Causal Inference Techniques
article

Connecting precariousness and depression: From causal discovery to intervention simulation

Vítor V. Vasconcelos, Kyuri Park, Karien Stronks, Leonie K. Elsenburg, Mary Nicolaou
article en

Abstract

Precariousness and depression are closely linked, but the potential causal structure of this relationship and the extent to which feedback between them may shape intervention responses remain unclear. Using cross-sectional data from more than 21,000 adults in the multi-ethnic HELIUS study, we use constraint-based causal discovery methods that allow for latent confounding and feedback to generate hypotheses about candidate graph structures linking precariousness domains and depressive symptoms. Because the data are cross-sectional and many edge orientations are not uniquely determined, we summarize the findings in terms of their stability across specifications and resampling, and treat suggested directions as tentative, data-compatible hypotheses rather than identified causal effects. Across specifications and algorithms, financial stress is the precariousness domain most consistently linked to depression in the causal discovery summaries. Directional edge marks are less stable: in FCI summaries, the edge pattern is more often consistent with financial stress preceding depression, whereas CCI and PC tend to leave the same relation unresolved. In addition, several symptom-level configurations suggest that depressive symptoms may contribute to downstream social precariousness. We then use a calibrated simulation model to examine how depression and precariousness could co-evolve under intervention scenarios across different feedback strengths compatible with the observed data. In the simulation model, slower but more persistent improvement follows intervention under stronger internal feedback, whereas faster but less durable change follows under weaker feedback. These findings suggest that intervention responses may depend not only on the size of the external change but also on the feedback structure linking precariousness and depression. Longitudinal and quasi-experimental studies are needed to clarify directionality, estimate feedback strengths, and assess the policy relevance of these patterns. • Causal discovery maps candidate structure linking precariousness and depression • Financial stress emerges as the most consistently recovered link to depression • Cross-method disagreement in edge directions keeps causal ordering unresolved • A reduced simulation model examines responses to reduced financial stress • Stronger feedback slows improvement but makes it more persistent over time

SSM - Mental HealthVol. 9
Department of Public (IN), Public Health Service of Amsterdam (NL), Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NL), University of Amsterdam (NL)
ZonMw
Openalex Percentile: Top 13%
Advanced Causal Inference Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.