This study aims to develop personalized interventions by identifying critical processes or psychological drivers that significantly impact an individual's well-being. The research conducted three intensive daily diary studies, each with over 50 measurement occasions, across three data sets, to investigate individual differences in the strength of within-person associations between distinct process measures and various outcomes. A unique idiographic algorithm, i-ARIMAX (Autoregressive Integrated Moving Average), was used to determine the strength of the relationship (Beta) between each process and outcome within individuals. The results revealed that the process-outcome links varied significantly between individuals, surpassing the homogeneity typically seen in meta-analyses. While several processes showed group-level effects, no process was universally beneficial when considered individually. For example, social behavior processes like assertiveness did not demonstrate group-level links to loneliness but still had significant individual-level effects that varied from positive to negative. The study suggests that using i-ARIMAX can help reduce the number of candidate variables for complex within-person analyses and that the size and pattern of i-ARIMAX betas could guide personalized interventions. The findings highlight the importance of individual-level analysis in understanding the relationship between processes and outcomes, challenging the ergodic assumption that group averages accurately reflect individual experiences.This study aims to develop personalized interventions by identifying critical processes or psychological drivers that significantly impact an individual's well-being. The research conducted three intensive daily diary studies, each with over 50 measurement occasions, across three data sets, to investigate individual differences in the strength of within-person associations between distinct process measures and various outcomes. A unique idiographic algorithm, i-ARIMAX (Autoregressive Integrated Moving Average), was used to determine the strength of the relationship (Beta) between each process and outcome within individuals. The results revealed that the process-outcome links varied significantly between individuals, surpassing the homogeneity typically seen in meta-analyses. While several processes showed group-level effects, no process was universally beneficial when considered individually. For example, social behavior processes like assertiveness did not demonstrate group-level links to loneliness but still had significant individual-level effects that varied from positive to negative. The study suggests that using i-ARIMAX can help reduce the number of candidate variables for complex within-person analyses and that the size and pattern of i-ARIMAX betas could guide personalized interventions. The findings highlight the importance of individual-level analysis in understanding the relationship between processes and outcomes, challenging the ergodic assumption that group averages accurately reflect individual experiences.