Temporal stability of idiographic psychological networks

Evidence-based mental health programs have long conceptualized mental disorders as interactions between thoughts, feelings, behaviours and external factors. Idiographic network models are a relatively novel way of estimating such intra-individual psychological processes. These methods are not without limitations, and concerns have been raised about the stability and accuracy of estimated networks. The extend to which idiographic networks are stable, or vary over time, is unknown. We explored temporal network stability from three angles, exploring variation within people, across different stability metrics, and across people. We reanalysed daily symptom records of people with personality disorders. We fit graphical Vector Autoregressive models separately for the first and second 50 days of consecutive measurements. Contemporaneous but not temporal idiographic networks appeared to be relatively stable within people. The assessment of stability varied considerably across metrics...Show moreEvidence-based mental health programs have long conceptualized mental disorders as interactions between thoughts, feelings, behaviours and external factors. Idiographic network models are a relatively novel way of estimating such intra-individual psychological processes. These methods are not without limitations, and concerns have been raised about the stability and accuracy of estimated networks. The extend to which idiographic networks are stable, or vary over time, is unknown. We explored temporal network stability from three angles, exploring variation within people, across different stability metrics, and across people. We reanalysed daily symptom records of people with personality disorders. We fit graphical Vector Autoregressive models separately for the first and second 50 days of consecutive measurements. Contemporaneous but not temporal idiographic networks appeared to be relatively stable within people. The assessment of stability varied considerably across metrics applied. There was large variation in network stability of contemporaneous structures across people, which could not be explained by subject-specific variables. We illustrate the temporal changes in contemporaneous network structures of two participants with high and low network stability and discuss the most pressing questions to be considered by future research.Show less

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Temporal stability of idiographic psychological networks