This study explores the variability in the relationship between psychological processes and well-being outcomes across individuals, challenging the assumption that group-level findings apply universally. Using three intensive daily diary studies with over 50 within-person measurement occasions each, researchers applied an idiographic algorithm, i-ARIMAX, to determine the strength of relationships between processes and outcomes within individuals. The results showed significant individual differences in these relationships, surpassing the homogeneity typically seen in meta-analyses. While some processes had group-level effects, no process was universally beneficial when considered individually. For example, processes involving social behavior, like being assertive, did not show group-level links to loneliness but had significant individual-level effects that varied from positive to negative. The study highlights the importance of personalized interventions, as the size and pattern of i-ARIMAX betas could guide tailored approaches. Traditional methods often assume group-level findings apply to individuals, but this study shows that such assumptions may not hold. The i-ARIMAX approach allows for more accurate identification of individual-level relationships, reducing the number of candidate variables for complex within-person analyses. The findings suggest that individual differences in process-outcome associations are substantial, and that group-level averages may not accurately reflect individual experiences. This has implications for clinical practice, where personalized interventions are needed to address individual needs and contexts. The study also emphasizes the need for idiomatic analysis, focusing on individual-level data rather than group-level averages, to better understand and address individual differences in well-being.This study explores the variability in the relationship between psychological processes and well-being outcomes across individuals, challenging the assumption that group-level findings apply universally. Using three intensive daily diary studies with over 50 within-person measurement occasions each, researchers applied an idiographic algorithm, i-ARIMAX, to determine the strength of relationships between processes and outcomes within individuals. The results showed significant individual differences in these relationships, surpassing the homogeneity typically seen in meta-analyses. While some processes had group-level effects, no process was universally beneficial when considered individually. For example, processes involving social behavior, like being assertive, did not show group-level links to loneliness but had significant individual-level effects that varied from positive to negative. The study highlights the importance of personalized interventions, as the size and pattern of i-ARIMAX betas could guide tailored approaches. Traditional methods often assume group-level findings apply to individuals, but this study shows that such assumptions may not hold. The i-ARIMAX approach allows for more accurate identification of individual-level relationships, reducing the number of candidate variables for complex within-person analyses. The findings suggest that individual differences in process-outcome associations are substantial, and that group-level averages may not accurately reflect individual experiences. This has implications for clinical practice, where personalized interventions are needed to address individual needs and contexts. The study also emphasizes the need for idiomatic analysis, focusing on individual-level data rather than group-level averages, to better understand and address individual differences in well-being.