## 4 Discussion
This methodological choice may have introduced systematic measurement error that could affect the interpretation of developmental patterns in our findings. Relatedly, in this developmental age range of 8- to 21-year-olds, it is possible the \"c\" factor has not had sufficient time to manifest, or perhaps its cognitive and clinical indicators manifest on different time scales. This developmental timing issue raises important questions about the nature of \"c\" itself--i.e., if cognitive and clinical manifestations emerge asynchronously, this could suggest that \"c\" is not a unitary construct but rather a developmental process that unfolds over time. More insight could be gained from future studies using a larger age range, particularly if these studies can track the emergence and stability of \"c\" across different developmental periods. A third limitation is that the sample used here was mostly cross-sectional, with only a small proportion used in longitudinal analysis. Most of this longitudinal sub-sample included only two time points, which fundamentally limits our ability to draw causal inferences and test alternative theories about how \"c\" arises. For example, because of the well-established links among perception, cognition, and psychopathology [92; 93], it is possible that negative events give rise to negative thoughts, which give rise to negative affect, and so on, with the opposite also occurring (positive events \(\rightarrow\) positive affect), making \"c\" a construct that arises only longitudinally given individual differences in experience. This theoretical model suggests that \"c\" might be better conceptualized as an emergent property of recursive cognitive-affective processes rather than a stable trait. More longitudinal data would allow testing of such a theory in comparison to other theories discussed above, such as whether (1) \"c\" represents a stable individual difference factor that influences the interpretation of events, or (2) \"c\" emerges from the cumulative effects of experience on neural development. Nonetheless, the validation of \"c\" with longitudinal clinical outcomes in this study suggests that it may be useful for predicting clinical outcomes beyond its cross-sectional explanatory power. Finally, it is worth noting that the \"p\" factor of psychopathology, a central component of \"c\", has some limitations that directly impact our theoretical framework [94; 95; 96]. Chief among these are that (1) the consistently superior fit indices of bifactor models of \"p\" (or anything) are not evidence that the bifactor configuration is \"true\" because the bifactor model is less parsimonious than competing models, and (2) theories of why the \"p\" factor exists (if it does) are weak, difficult to falsify, or not rigorously tested against alternative explanations for the \"positive manifold\" of psychiatric symptoms. These methodological and theoretical concerns suggest that our conceptualization of \"c\" may need substantial revision if the underlying \"p\" factor proves to be an artifact of measurement rather than a meaningful construct. Perhaps despite the acceptable fit of bifactor and higher-order models of psychopathology, the relationships among symptoms are better modeled by alternative approaches, such as network models [97], which would suggest that \"c\" might be better understood as an emergent property of interconnected cognitive-clinical networks rather than a latent factor. If this is true of the \"p\" factor, the conceptualization of the \"c\" factor presented here would need fundamental modifications to align with a network-based understanding of psychopathology. Despite these limitations and their theoretical implications, the present study provides some new insight into the feasibility of using a \"c\" factor in large-scale studies.