Background: Clinical psychology research emphasizing treatment packages targeted at DSM defined problems obscures individual differences and violates statistical assumptions regarding its applicability to individuals in the sample. An alternative approach maps the relationship between psychological processes and outcomes at the individual level before aggregating results. This study represents the first effort to undertake such an approach using a novel measure, the Process Based Assessment Tool (PBAT), that assesses functionally defined psychological processes linked to intervention and based on modern evolution science. Methods: Data on psychological variation, selection, and retention, domains of psychological distress, life satisfaction, and burnout, were collected twice daily for a 35day period using a smartphone application. These data were analyzed using the SGIMME statistical package to generate group, sub-group, and individual level network models.
Results: S-GIMME models successfully converged for all participants. Network models directed at each of 7 outcomes yielded interpretable subgroups. Elements of the PBAT reliably produced directed pathways impacting elements of psychological distress within the sample. 17 of 18 elements of the PBAT appear in final models which maximized directed pathways toward each of the 7 targeted outcomes.
Discussion: The PBAT demonstrated utility as a daily diary measure and reliably produced directed pathways impacting domains of psychological distress and well-being.
Subgroup formation demonstrated consistency across outcomes directed models.
Individual network models represent potential clinical utility
