Just how do More SMAs Relate with brand new QoL Factors and other Resilience Factors?
While earlier analyses suggest that especially SMA is an important factor, it remains unclear what specific self-management abilities are crucially involved. Through exploratory analyses, we aimed to establish whether there are substantial differences in the importance of the six SMA facets included in the SMAS. A third GGM again highlighted that almost all nodes were (in)directly connected to each other and revealed similar associations between the QoL facets (Figure 5A; Supplementary Table 4). Edge weights of connections among nodes of the individual facets of the SMAS, as well as the other resilience factors, are reported in Supplementary Table 5. Not surprisingly, we observed a particularly strong connection between PAS and the PFM facet of the SMAS, and a relatively weak (and less stable) connection between PAS and VAR (p<0.05, Figure 5A; Supplementary Figures 9, 10). 05; Figure 5B) and influenced each other equally. SEF was directly related to PHY, with SEF exerting a larger influence on PHY than vice versa (4.7% vs. 2.6%; p<0.05; Figures 6A,C). This builds on the relationship between SMA and PHY observed in the previous networks and suggests that physical activity may indirectly enhance QoL, through increased self-efficacy, but that increasing self-efficacy specifically may also strongly (and even to a larger extent than vice versa) boost physical activity. In addition to the previously established connection with PAS, BC was also directly related to the SEF (not consistently, 30.6% of the bootstraps set to zero), INI, and MUL facets of the SMAS in this network. Taking all these edges together, the total instrength value of BC was higher compared with the outstrength value (19.0% vs. 15.2%, p>0.05). This is in line with earlier suggestions that boosting (specific) SMAs may not only improve QoL, but also other resilience factors (e.g., BC or PHY) that can indirectly further enhance QoL.
Contour 5. Gaussian visual design (GGM; A) and you will directed relative characteristics system (B) from individual elements of QoL (green), the latest aspects of the fresh SMAS (pink) or any other strength situations serwis randkowy the perfect match (purple), additionally the stringency directory (blue). Maximum really worth stands for the best edge loads included in the circle.
Figure 6. The difference between overall outstrength and instrength of the nodes in the third network (A), and the difference in outstrength and instrength of the relationships between the resilience factors and QoL facets only (B, left), and the relationships between the QoL facets and the resilience factors (B, right). Colors correspond to the nodes in the network in Figure 5. In plots (C,D), the bootstrapped mean is depicted in black and the sample mean in red. * p<0.05, nodes with quantile intervals containing zero are deemed to have an insignificant instrength and outstrength difference.
Exploratory Analyses
Of all the SMAS facets, MUL had the most direct connections with facets of QoL (i.e., SAB, SOP, INT, and PPF; Figure 5A and Supplementary Table 6) and the largest total outstrength–instrength difference (69.7–49.8%; p<0.05; Figures 5B, 6A,C), even when excluding the relationships with other resilience factors (22.8–15.7%). However, in the latter situation, the estimation of the difference was relatively unstable, resulting in a large quantile interval that contained zero (p>0.05; Figures 6B,D). The connection of MUL with the PPF facet (7.7% vs. 6.4%, p>0.05) was of particular interest, since PPF was not directly related to overall SMA in the second GGM. Moreover, this connection appeared to be stronger than the edge between PPF and PAS, although not significantly (p>0.05; Supplementary Figures 9, 10). These exploratory findings suggest that, potentially, when aiming to improve the PPF facet of QoL, one should focus on enhancing multifunctionality of resources specifically, rather than PAS. Due to the considerably high total outstrength value of PPF on other facets of QoL (79.0%, vs. 48.4% instrength, p<0.05), this may also be an excellent strategy to indirectly enhance AUT (29.7%), SOP (29.3%), INT (14%), DAD (4.3%), and SAB (1.7%), and thereby QoL as a whole. Several other positive (and some negative) relationships between the individual SMAs and QoL facets were observed as well, although most of them were considerably unstable (see Figures 5, 6 and Supplementary Figures 9, 10).