| Literature DB >> 35735404 |
Maria Balle1, Aina Fiol-Veny1, Alejandro de la Torre-Luque2, Jordi Llabres1, Xavier Bornas1.
Abstract
Growing evidence supports the hypothesis that temperamental traits are not static throughout adolescence. The known links between both reactive and regulatory temperament and anxiety symptoms should be investigated bearing this hypothesis in mind. This study collected self-reported data on behavioral inhibition system (BIS) sensitivity, attentional control (AC), and anxiety symptomatology, from 296 adolescents (64.2% girls; M = 12.96 years at the first assessment, SD = 0.47) every six months, four times over eighteen months. The relationships between temperament factors (AC and BIS sensitivity), considered longitudinally (by means of their trajectories) and anxiety symptoms were investigated using Multigroup Latent Growth Modeling (MLGM), as well as the mediating effect of sex on trajectories and anxiety. BIS sensitivity decreased over time and showed differential patterns across sexes. AC remained relatively stable and we found no sex influence on its trajectory. On the other hand, we observed that the BIS sensitivity trajectory was a significant predictor of anxiety symptomatology at age 15. In conclusion, temperamental changes between the ages of 13 and 15 seem to play a relevant role in explaining subsequent anxiety symptomatology, under the mediating influence of sex.Entities:
Keywords: adolescence; anxiety; temperamental change; vulnerability
Year: 2022 PMID: 35735404 PMCID: PMC9219936 DOI: 10.3390/bs12060194
Source DB: PubMed Journal: Behav Sci (Basel) ISSN: 2076-328X
Figure 1Temperament trajectories according to sex. Box (A) shows the attention control trajectories over our assessment period. Box (B) displays the behavioral inhibition system sensitivity trajectories over our assessment period. Solid line depicts the trajectories of boys. Dashed line depicts the trajectories of girls. BIS = Behavioral inhibition system. Error bars depict the standard error of the mean.
Measurement invariance model fit summary for RCADS Total anxiety.
| Scaled χ2 (df) | RMSEA | CFI | TLI | SRMR | Model Comparison | |||
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| Model | ΔCFI | ΔRMSEA | ΔSRMR | |||||
| Configural |
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| Latent mean MI | 127.75 (56) | 0.093 | 0.95 | 0.93 | 0.073 | −0.011 | 0.007 | 0.017 |
| Partial mean MI (BIS) |
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| Partial mean MI (AC) | 110.92 (54) | 0.084 | 0.96 | 0.94 | 0.058 | 0.001 | −0.002 | 0.002 |
| Latent variance MI |
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| Partial variance MI (BIS) | 122.80 (56) | 0.090 | 0.95 | 0.93 | 0.075 | 0.001 | −0.004 | 0.002 |
| Partial variance MI (AC) | 111.66 (56) | 0.082 | 0.96 | 0.95 | 0.060 | −0.010 | −0.010 | −0.013 |
| Full MI | 137.87 (64) | 0.087 | 0.95 | 0.94 | 0.077 | −0.001 | −0.001 | 0.002 |
| Partial full MI (BIS) | 129.05 (58) | 0.089 | 0.95 | 0.94 | 0.076 | 0.001 | 0.001 | 0.001 |
| Partial full MI (AC) | 112.89 (58) | 0.079 | 0.96 | 0.95 | 0.061 | 0.012 | −0.009 | −0.014 |
Note. All χ2-based tests were statistically significant with a p < 0.01. Selected models are diplayed in bold face. Each nested model was compared with the simpler one selected. The measurement invariance models were increasingly constrained: latent mean, latent variance (latent means + variances), full MI (latent means + variances + regressors). The partial MI models involved constraints on either BIS path parameters or AC path parameters. MI = Measurement invariance. BIS = Behavioral inhibition system. AC = Attentional control. df = degrees of freedom. RMSEA = root mean square error of approximation index. CFI = comparative fit index. TLI = Tucker-Lewis index. SRMR = standardised root mean square residual. ΔCFI = incremental CFI. ΔRMSEA = incremental RMSEA. ΔSRMR = incremental SRMR.