This research investigates how to strengthen seasonality knowledge and support in-season food choices. Study 1 examined 317 Italian adults’ knowledge of seasonal foods and its association with self-reported consumption. Study 2 tested whether expository materials and an associative training task improved seasonality knowledge and choices under time pressure. Participants (N = 235) were assigned to a 2 × 2 × 2 full-factorial design manipulating information provision, associative training, and time pressure. Despite the absence of total main effects on seasonal choice, both educational approaches improved seasonality knowledge, which in turn was associated with a higher selection of seasonal products in the simulated shopping task. In addition, the three-way interaction between information, associative training, and time pressure was significant, though close to the conventional significance threshold. Simple-effects analyses indicated that, under time pressure, information provision improved performance only when combined with associative training. At an exploratory two-month follow-up (n = 137), indirect effects of each intervention on self-reported consumption of seasonal vegetables were observed through seasonality knowledge. Moreover, self-reported consumption of exotic or unseasonal fruit was lower among participants in the associative training condition than among those not exposed to this training. Overall, both educational approaches improved seasonality knowledge, whereas evidence of their complementarity for food choice remains preliminary.
Positivity, that is, the tendency to view oneself, one’s life, and one’s future with a favorable outlook, is a key psychological resource for mental and physical well-being. Self-esteem, life satisfaction, and optimism are its expressions, which share a common latent dimension. The present study examined whether positivity reflects qualitatively distinct configurations or a single underlying continuum. Using a person-centered approach, latent profile analysis was applied to a sample of 1346 adult university students in Spain (1375 recruited, of whom 29 were removed as outliers) through two complementary representations of the data. The first (level analysis) identified profiles based on participants’ overall levels of self-esteem, life satisfaction, and optimism. The second (shape analysis) removed overall positivity to examine whether qualitatively distinct configurations of the three components existed. The level analysis identified four profiles ordered along a single positivity continuum; the profiles were weakly separated, and permitting within-class covariance favored a single class. The shape analysis recovered no well-separated structure. Higher positivity profiles were associated with better subsequent self-rated mental and physical health, yet the profiles explained no more variance than a continuous positivity score. The findings support a dimensional account of positivity, where individuals differ primarily in degree, through coordinated variation in self-esteem, life satisfaction, and optimism, rather than in qualitatively distinct subgroups.
Secondary traumatic stress (STS) is a clinically significant consequence of indirect exposure to trauma among healthcare professionals; however, a culturally validated measure for healthcare professionals has been lacking in South Korea. This study developed and evaluated the psychometric properties of a Korean version of the 17-item Secondary Traumatic Stress Scale (STSS). The instrument was translated and culturally adapted through forward–back-translation and expert content review and administered to 300 healthcare professionals indirectly exposed to work-related trauma. The sample was randomly divided into two independent subsamples (n = 150 each) for exploratory and confirmatory factor analyses (EFA and CFA, respectively). Internal consistency, structural validity, and criterion-related validity against the Impactof Event Scale–Revised (IES-R) were also examined. The Korean STSS demonstrated excellent internal consistency (Cronbach’s α = 0.95). EFA yielded a 14-item, two-factor structure—sensory-reactive and cognitive-avoidance symptoms—explaining 67.08% of the variance after removing three weakly loading items, and, in CFA, this two-factor model was the best-performing of the three models compared (one-factor, two-factor, and original three-factor), although none of the models showed fully satisfactory fit (comparative fit index = 0.91, Tucker–Lewis index = 0.89, root mean square error of approximation = 0.11). Criterion-related validity was supported by a strong correlation with the IES-R (r = 0.89, 95% CI [0.86, 0.91]), whereas evidence for discriminant validity was limited: the scale correlated weakly and negatively with perceived social support (r = −0.25) but strongly with general psychological distress (r = 0.81). The Korean STSS shows promising initial psychometric properties among Korean healthcare professionals; however, these findings need to be confirmed in larger and more diverse samples before the instrument can be recommended for routine screening.
Accurate prediction of the risk of progression to clinically diagnosed Alzheimer’s Disease (AD) in cognitively normal (CN) individuals and those with mild cognitive impairment (MCI) is essential for early intervention and prognosis. Structural magnetic resonance imaging (sMRI) provides rich information on brain morphology, but its high dimensionality poses challenges for robust risk prediction, especially with limited sample sizes and censored outcomes. In this study, we extend a prediction-oriented framework based on supervised functional principal component analysis (sFPCA) to extract low-dimensional components from baseline sMRI data in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. sFPCA extracts components that balance dominant imaging variation against their association with the survival outcome, thereby reducing the dimensionality of the sMRI data while retaining relevant imaging information. The resulting components were evaluated using both Cox proportional hazards (Cox PHs) and random survival forest (RSF) models, providing complementary log-linear and nonparametric survival-prediction frameworks. Across ten retained development/test partitions, mean test IAUC was 0.7733 for sFPCA-Cox and 0.7294 for sFPCA-RSF, with corresponding Integrated Brier Scores (IBSs) of 0.08730 and 0.09232, respectively. The matched uFPCA models achieved mean IAUC values of 0.7719 and 0.7357 under Cox PH and RSF, respectively, indicating that the incremental predictive contribution of survival supervision was modest and depended on the downstream survival model. While the primary objective is risk prediction, additional analysis results based on low-, middle- and high-risk groups are used to facilitate interpretation of the learned imaging components. The identified anatomical spatial patterns involve regions such as the hippocampus, amygdala, and prefrontal and temporal cortices, supporting their relevance to AD-related neurodegeneration. These findings demonstrate the feasibility of sMRI-based prediction of conversion to clinically diagnosed AD and suggest that survival supervision may provide modest improvements under some modeling configurations.
With the rapid development of artificial intelligence, concerns about severe dependence on large language models (LLMs) are increasing among university students. This cross-sectional study aims to examine the underlying association between physical activity and LLM dependence, especially the mediating role of self-control and the moderating role of exploratory learning ability underlying them. Using stratified cluster sampling, 602 university students in China were recruited and then completed several standardized measurements, including the Physical Activity Rating Scale-3, Self-Control Scale, Large Language Model Dependence Scale, and Exploratory Learning Scale, and relevant data were analyzed using SPSS 27.0 and PROCESS Model 58. The present work discloses that physical activity was positively correlated with self-control, yet negatively correlated with LLM dependence, and its direct conditional association with LLM dependence was non-significant, whereas the indirect association via self-control was significant. Exploratory learning ability could moderate both the positive association between physical activity and self-control and the negative association between self-control and LLM dependence, and the indirect association between physical activity and LLM dependence via self-control would also be significantly moderated by exploratory learning ability, while this moderating effect might exist only at lower levels of exploratory learning ability. These findings clearly identify self-control as a potential psychological pathway and exploratory learning ability as a boundary condition of physical activity and LLM dependence. The models only explained 8.8% of the variance in self-control and 19.6% of the variance in LLM dependence, so the discovery should be only interpreted as preliminary associations rather than causal evidence.
