Objective
The COVID‐19 pandemic has confronted young adults with an unprecedented mental health challenge. Yet, prospective studies examining protective factors are limited.
Methods
In the present ...study, we focused on changes in mental health in a large sample (N = 685) of at‐risk university students, which were measured before and during the pandemic. Network modeling was applied to 20 measured variables to explore intercorrelations between mental health factors, and to identify risk and protective factors. Latent change score modeling was used on a subset of variables.
Results
The main findings indicate that (1) mental health problems increased at group level, especially depression‐anxiety and loneliness; (2) emotional support during the COVID pandemic was associated with smaller increases in loneliness and depression‐anxiety; (3) COVID‐related stress predicted increases in depression‐anxiety; (4) loneliness acted as a bridge construct between emotional support and changes in mental health.
Conclusion
To mitigate the impact of the COVID‐19 pandemic on the mental health of young adults, is it recommended to focus on interventions that strengthen internal resources (stress‐regulating abilities) and reduce loneliness.
No robust relation between larger cities and depression Huth, Karoline B S; Finnemann, Adam; van den Ende, Maarten W J ...
Proceedings of the National Academy of Sciences - PNAS,
01/2022, Letnik:
119, Številka:
2
Journal Article
The “Ising model” refers to both the statistical and the theoretical use of the same equation. In this article, we introduce both uses and contrast their differences. We accompany the conceptual ...introduction with a survey of Ising-related software packages in R. Since the model’s different uses are best understood through simulations, we make this process easily accessible with fully reproducible examples. Using simulations, we show how the theoretical Ising model captures local-alignment dynamics. Subsequently, we present it statistically as a likelihood function for estimating empirical network models from binary data. In this process, we give recommendations on when to use traditional frequentist estimators as well as novel Bayesian options.
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected \(350{,}757\) coin flips to test the ...counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, \(\text{Pr}(\text{same side}) = 0.508\), 95% credible interval (CI) \(0.506\), \(0.509\), \(\text{BF}_{\text{same-side bias}} = 2359\). Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: \(\text{Pr}(\text{heads}) = 0.500\), 95% CI \(0.498\), \(0.502\), \(\text{BF}_{\text{heads-tails bias}} = 0.182\). Furthermore, this lack of heads-tails bias does not appear to vary across coins. Additional exploratory analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for the DHM physics model of coin tossing.
Group 1 innate lymphoid cells (ILCs) comprise a heterogeneous family of cytotoxic natural killer (NK) cells and ILC1s. We identify a population of “liver-type” ILC1s with transcriptional, phenotypic, ...and functional features distinct from those of conventional and liver-resident NK cells as well as from other previously described human ILC1 subsets. LT-ILC1s are CD49a+CD94+CD200R1+, express the transcription factor T-BET, and do not express the activating receptor NKp80 or the transcription factor EOMES. Similar to NK cells, liver-type ILC1s produce IFN-γ, TNF-α, and GM-CSF; however, liver-type ILC1s also produce IL-2 and lack perforin and granzyme-B. Liver-type ILC1s are expanded in cirrhotic liver tissues, and they can be produced from blood-derived ILC precursors in vitro in the presence of TGF-β1 and liver sinusoidal endothelial cells. Cells with similar signature and function can also be found in tonsil and intestinal tissues. Collectively, our study identifies and classifies a population of human cross-tissue ILC1s.
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•scRNA-seq and proteomics identify a “liver-type” (LT) ILC1 subset in human livers•LT-ILC1s accumulate in fibrotic areas of cirrhotic livers•LT-ILC1-like cells can be derived from progenitors in co-culture with TGF-β1/LSECs•Similar cross-tissue ILC1 cells could also be found in tonsil and intestinal tissues
Krämer et al. report a population of human "liver-type" innate lymphocytes that differs from other previously characterized cells. They are expanded in cirrhotic livers and can be generated from precursors in co-culture with liver endothelial cells. Cells with similar properties can also be found in tonsil or intestinal tissue.
Photoplethysmography offers a widely used, convenient and non-invasive approach to monitoring basic indices of cardiovascular function, such as heart rate and blood oxygenation. Systematic analysis ...of the shape of the waveform generated by photoplethysmography might be useful to extract estimates of several physiological and psychological factors influencing the waveform. Here, we developed a robust and automated method for such a systematic analysis across individuals and across different physiological and psychological contexts. We describe a psychophysiologically-relevant model, the Hybrid Excess and Decay (HED) model, which characterises pulse wave morphology in terms of three underlying pressure waves and a decay function. We present the theoretical and practical basis for the model and demonstrate its performance when applied to a pharmacological dataset of 105 participants receiving intravenous administrations of the sympathomimetic drug isoproterenol (isoprenaline). We show that these parameters capture photoplethysmography data with a high degree of precision and, moreover, are sensitive to experimentally-induced changes in interoceptive arousal within individuals. We conclude by discussing the possible value in using the HED model as a complement to standard measures of photoplethysmography signals.
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