A service evaluation of phased- and stepped-care psychological support for health and social care workers during the COVID-19 pandemic

BACKGROUND: The COVID-19 pandemic has disproportionally affected the mental health of health and social care workers (HSCWs), with many experiencing symptoms of depression, anxiety and post-traumatic stress disorder. Psychological interventions have been offered via mental health services and in-house psychology teams, but their effectiveness in this context is not well documented. AIMS: To evaluate a stepped-care psychological support pathway for HSCWs from Homerton Healthcare Foundation Trust in London, which offered psychological first aid, evidence-based psychological therapies and group-based well-being workshops. METHOD: The service evaluation used a pre-post approach to assess depression, anxiety, functional impairment and post-traumatic stress disorder symptom change for those who attended sessions of psychological first aid, low- or high-intensity cognitive-behavioural therapy or a combination of these. In addition, the acceptability of the psychological first aid sessions and well-being workshops was explored via feedback data. RESULTS: Across all interventions, statistically significant reductions of depression (d = 1.33), anxiety (d = 1.37) and functional impairment (d = 0.93) were observed, and these reductions were equivalent between the interventions, as well as the demographic and occupational differences between the HSCWs (ethnicity, staff group and redeployment status). HSCWs were highly satisfied with the psychological first aid and well-being workshops. CONCLUSIONS: The evaluation supports the utility of evidence-based interventions delivered as part of a stepped-care pathway for HSCWs with common mental health problems in the context of the COVID-19 pandemic. Given the novel integration of psychological first aid within the stepped-care model as a step one intervention, replication and further testing in larger-scale studies is warranted

The transcriptional response of soil bacteria to long-term warming and short-term seasonal fluctuations in a terrestrial forest

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chowdhury, P. R., Golas, S. M., Alteio, L., Stevens, J. T. E., Billings, A. F., Blanchard, J. L., Melillo, J. M., & DeAngelis, K. M. The transcriptional response of soil bacteria to long-term warming and short-term seasonal fluctuations in a terrestrial forest. Frontiers in Microbiology, 12, (2021): 666558, https://doi.org/10.3389/fmicb.2021.666558.Terrestrial ecosystems are an important carbon store, and this carbon is vulnerable to microbial degradation with climate warming. After 30 years of experimental warming, carbon stocks in a temperate mixed deciduous forest were observed to be reduced by 30% in the heated plots relative to the controls. In addition, soil respiration was seasonal, as was the warming treatment effect. We therefore hypothesized that long-term warming will have higher expressions of genes related to carbohydrate and lipid metabolism due to increased utilization of recalcitrant carbon pools compared to controls. Because of the seasonal effect of soil respiration and the warming treatment, we further hypothesized that these patterns will be seasonal. We used RNA sequencing to show how the microbial community responds to long-term warming (~30 years) in Harvard Forest, MA. Total RNA was extracted from mineral and organic soil types from two treatment plots (+5°C heated and ambient control), at two time points (June and October) and sequenced using Illumina NextSeq technology. Treatment had a larger effect size on KEGG annotated transcripts than on CAZymes, while soil types more strongly affected CAZymes than KEGG annotated transcripts, though effect sizes overall were small. Although, warming showed a small effect on overall CAZymes expression, several carbohydrate-associated enzymes showed increased expression in heated soils (~68% of all differentially expressed transcripts). Further, exploratory analysis using an unconstrained method showed increased abundances of enzymes related to polysaccharide and lipid metabolism and decomposition in heated soils. Compared to long-term warming, we detected a relatively small effect of seasonal variation on community gene expression. Together, these results indicate that the higher carbohydrate degrading potential of bacteria in heated plots can possibly accelerate a self-reinforcing carbon cycle-temperature feedback in a warming climate.Funding for this study was provided by the Department of Energy Terrestrial Ecosystem Sciences program under contract number DE-SC0010740. Sites for sample collection were maintained with funding in part from the National Science Foundation (NSF) Long-Term Ecological Research (DEB 1237491) and the NSF Long-Term Research in Environmental Biology (DEB 1456528) programs

Detection of Cosmic Structures using the Bispectrum Phase. II. First Results from Application to Cosmic Reionization Using the Hydrogen Epoch of Reionization Array

Characterizing the epoch of reionization (EoR) at $z\gtrsim 6$ via the redshifted 21 cm line of neutral Hydrogen (HI) is critical to modern astrophysics and cosmology, and thus a key science goal of many current and planned low-frequency radio telescopes. The primary challenge to detecting this signal is the overwhelmingly bright foreground emission at these frequencies, placing stringent requirements on the knowledge of the instruments and inaccuracies in analyses. Results from these experiments have largely been limited not by thermal sensitivity but by systematics, particularly caused by the inability to calibrate the instrument to high accuracy. The interferometric bispectrum phase is immune to antenna-based calibration and errors therein, and presents an independent alternative to detect the EoR HI fluctuations while largely avoiding calibration systematics. Here, we provide a demonstration of this technique on a subset of data from the Hydrogen Epoch of Reionization Array (HERA) to place approximate constraints on the brightness temperature of the intergalactic medium (IGM). From this limited data, at $z=7.7$ we infer "$1\sigma$" upper limits on the IGM brightness temperature to be $\le 316$ "pseudo" mK at $\kappa_\parallel=0.33$ "pseudo" $h$ Mpc$^{-1}$ (data-limited) and $\le 1000$ "pseudo" mK at $\kappa_\parallel=0.875$ "pseudo" $h$ Mpc$^{-1}$ (noise-limited). The "pseudo" units denote only an approximate and not an exact correspondence to the actual distance scales and brightness temperatures. By propagating models in parallel to the data analysis, we confirm that the dynamic range required to separate the cosmic HI signal from the foregrounds is similar to that in standard approaches, and the power spectrum of the bispectrum phase is still data-limited (at $\gtrsim 10^6$ dynamic range) indicating scope for further improvement in sensitivity as the array build-out continues.Comment: 22 pages, 12 figures (including sub-figures). Published in PhRvD. Abstract may be slightly abridged compared to the actual manuscript due to length limitations on arXi

Bayesian jackknife tests with a small number of subsets: Application to HERA 21cm power spectrum upper limits

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open-source code, CHIBORG, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from the Hydrogen Epoch of Reionization Array (HERA) to assess whether different sub-seasons of observing can justifiably be combined to produce a deeper 21 cm power spectrum upper limit. We find that, with a handful of exceptions, the HERA data in question are statistically consistent and this decision is justified. We conclude by pointing out the wide applicability of this test, including to CMB experiments and the H0 tension

What does an interferometer really measure? Including instrument and data characteristics in the reconstruction of the 21cm power spectrum

Combining the visibilities measured by an interferometer to form a cosmological power spectrum is a complicated process in which the window functions play a crucial role. In a delay-based analysis, the mapping between instrumental space, made of per-baseline delay spectra, and cosmological space is not a one-to-one relation. Instead, neighbouring modes contribute to the power measured at one point, with their respective contributions encoded in the window functions. To better understand the power spectrum measured by an interferometer, we assess the impact of instrument characteristics and analysis choices on the estimator by deriving its exact window functions, outside of the delay approximation. Focusing on HERA as a case study, we find that observations made with long baselines tend to correspond to enhanced low-k tails of the window functions, which facilitate foreground leakage outside the wedge, whilst the choice of bandwidth and frequency taper can help narrow them down. With the help of simple test cases and more realistic visibility simulations, we show that, apart from tracing mode mixing, the window functions can accurately reconstruct the power spectrum estimator of simulated visibilities. We note that the window functions depend strongly on the chromaticity of the beam, and less on its spatial structure - a Gaussian approximation, ignoring side lobes, is sufficient. Finally, we investigate the potential of asymmetric window functions, down-weighting the contribution of low-k power to avoid foreground leakage. The window functions presented in this work correspond to the latest HERA upper limits for the full Phase I data. They allow an accurate reconstruction of the power spectrum measured by the instrument and can be used in future analyses to confront theoretical models and data directly in cylindrical space.Comment: 18 pages, 18 figures, submitted to MNRAS. Comments welcome

Characterization Of Inpaint Residuals In Interferometric Measurements of the Epoch Of Reionization

Radio Frequency Interference (RFI) is one of the systematic challenges preventing 21cm interferometric instruments from detecting the Epoch of Reionization. To mitigate the effects of RFI on data analysis pipelines, numerous inpaint techniques have been developed to restore RFI corrupted data. We examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that capable of inpainting RFI corrupted data in interferometric instruments. We train our network on simulated data and show that our network is capable at inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modeling are best suited for inpainting over narrowband RFI. We also show that with our fiducial parameters Discrete Prolate Spheroidal Sequences (DPSS) and CLEAN provide the best performance for intermittent ``narrowband'' RFI while Gaussian Progress Regression (GPR) and Least Squares Spectral Analysis (LSSA) provide the best performance for larger RFI gaps. However we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We find these results to be consistent in both simulated and real visibilities. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that in the future, as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities of HERA data.Comment: 26 pages, 18 figure

Direct Optimal Mapping Image Power Spectrum and its Window Functions

The key to detecting neutral hydrogen during the epoch of reionization (EoR) is to separate the cosmological signal from the dominating foreground radiation. We developed direct optimal mapping (Xu et al. 2022) to map interferometric visibilities; it contains only linear operations, with full knowledge of point spread functions from visibilities to images. Here we present an FFT-based image power spectrum and its window functions based on direct optimal mapping. We use noiseless simulation, based on the Hydrogen Epoch of Reionization Array (HERA) Phase I configuration, to study the image power spectrum properties. The window functions show $<10^{-11}$ power leakage from the foreground-dominated region into the EoR window; the 2D and 1D power spectra also verify the separation between the foregrounds and the EoR. Furthermore, we simulated visibilities from a $uv$-complete array and calculated its image power spectrum. The result shows that the foreground--EoR leakage is further suppressed below $10^{-12}$, dominated by the tapering function sidelobes; the 2D power spectrum does not show signs of the horizon wedge. The $uv$-complete result provides a reference case for future 21cm cosmology array designs.Comment: Submitted to Ap