Northeast Pacific warm blobs sustained via extratropical atmospheric teleconnections

Large-scale marine heatwaves in the Northeast Pacific (NEP), identified here and previously as 'warm blobs', have devastating impacts on regional ecosystems. An anomalous atmospheric ridge over the NEP is known to be crucial for maintaining these warm blobs, also causing abnormally cold temperatures over North America during the cold season. Previous studies linked this ridge to teleconnections from tropical sea surface temperature anomalies. However, it was unclear whether teleconnections from the extratropics could also contribute to the ridge. Here we show that planetary wave trains, triggered by increased rainfall and latent heat release over the Mediterranean Sea accompanied by decreased rainfall over the North Atlantic, can transport wave energy to the NEP, guided by the westerly jet, and induce a quasi-barotropic ridge there. Our findings provide insights into extratropical teleconnections sustaining the NEP ridge, offering a source of potential predictability for the warm blobs and temperature fluctuations over North America.

Neuropsychiatric symptoms in Systemic Lupus Erythematosus: mixed methods analysis of patient-derived attributional evidence in the international INSPIRE project

OBJECTIVE

Attribution of neuropsychiatric symptoms in systemic lupus erythematosus (SLE) relies heavily on clinician assessment. Limited clinic time, variable knowledge, and symptom under-reporting contributes to discordance between clinician assessments and patient symptoms. We obtained attributional data directly from patients and clinicians in order to estimate and compare potential levels of direct attribution to SLE of multiple neuropsychiatric symptoms using different patient-derived measures.

METHODS

Quantitative and qualitative data analysed included: prevalence and frequency of neuropsychiatric symptoms, response to corticosteroids, and concurrence of neuropsychiatric symptoms with non-neuropsychiatric SLE disease activity. SLE patients were also compared with controls and inflammatory arthritis (IA) patients to explore attributability of neuropsychiatric symptoms to the direct disease effects on the brain/nervous system.

RESULTS

We recruited 2,817 participants, including 400 clinicians. SLE patients (n = 609) reported significantly higher prevalences of neuropsychiatric symptoms than controls (n = 463) and IA patients (n = 489). SLE and IA patients' quantitative data demonstrated multiple neuropsychiatric symptoms relapsing/remitting with other disease symptoms such as joint pain. Over 45% of SLE patients reported resolution/improvement of fatigue, positive sensory symptoms, severe headache, and cognitive dysfunction with corticosteroids. Evidence of direct attributability in SLE was highest for hallucinations and severe headache. SLE patients had greater reported improvement from corticosteroids (p= 0.008), and greater relapsing-remitting with disease activity (p< 0.001) in the comparisons with IA patients for severe headache. Clinician and patients reported insufficient time to discuss patient-reported attributional evidence. Symptoms viewed as indirectly related/non-attributable were often less prioritised for discussion and treatment.

CONCLUSION

We found evidence indicating varying levels of direct attributability of both common and previously unexplored neuropsychiatric symptoms in SLE patients, with hallucinations and severe headache assessed as the most directly attributable. There may also be-currently under-estimated-direct effects on the nervous system in IA and other systemic rheumatological diseases.

The role of interdecadal climate oscillations in driving Arctic atmospheric river trends

Atmospheric rivers (ARs), intrusions of warm and moist air, can effectively drive weather extremes over the Arctic and trigger subsequent impact on sea ice and climate. What controls the observed multi-decadal Arctic AR trends remains unclear. Here, using multiple sources of observations and model experiments, we find that, contrary to the uniform positive trend in climate simulations, the observed Arctic AR frequency increases by twice as much over the Atlantic sector compared to the Pacific sector in 1981-2021. This discrepancy can be reconciled by the observed positive-to-negative phase shift of Interdecadal Pacific Oscillation (IPO) and the negative-to-positive phase shift of Atlantic Multidecadal Oscillation (AMO), which increase and reduce Arctic ARs over the Atlantic and Pacific sectors, respectively. Removing the influence of the IPO and AMO can reduce the projection uncertainties in near-future Arctic AR trends by about 24%, which is important for constraining projection of Arctic warming and the timing of an ice-free Arctic.

Sea level variability in Gulf of Guinea from satellite altimetry

Coastal zones with dense populations, low elevations and/or inadequate adaptive capacity are on the frontline of unprecedented impacts from climate change. The Gulf of Guinea (GoG), stretching from Liberia to Gabon, is in particular vulnerable to coastal flooding caused by local and/or climate-induced sea level rise. In this region, interannual to decadal coastal sea level changes remain poorly understood, mainly due to a lack of tide gauge stations. Here we use nearly three decades (1993-2021) of satellite altimetry data to study the link between the Equatorial Atlantic and coastal GoG sea level variability. The rate of mean sea level rise increased from 3.47 to 3.89 ± 0.10 mm/yr from the Equatorial oceanic domain to the GoG coastal area, with an acceleration of 0.094 ± 0.050 mm/yr2. This corresponds to a mean sea level rise of about 8.9 cm over the entire altimetry period, 1993-2021. We focus on the (extreme) warm/cold events that occur in both the GoG during Atlantic Niños, and along the Angola-Namibia coast during Benguela Niños. Both events are driven by remote forcing via equatorial Kelvin waves and local forcing by local winds, freshwater fluxes and currents intensifications. Analysis of altimetry-based sea level, sea surface temperature anomalies, 20 °C isotherm based PIRATA moorings, and the Argo-based steric and thermometric sea level allows us to follow the coastal trapped waves (CTWs) along the GoG, and its link with major events observed along the strong Equatorial Atlantic warmings in 2010, 2012, 2019 and 2021. Both 2019 and 2021 warming have been identified as the warmest event ever reported in this region during the last 40 years. A lag of 1 month is observed between equatorial and West African coastal trapped wave propagation. This observation may help to better anticipate and manage the effects of extreme events on local ecosystems, fisheries, and socio-economic activities along the affected coastlines. In order to enable informed decision-making and guarantee the resilience of coastal communities in the face of climate change, it emphasises the significance of ongoing study in this field.

Contribution of climate change to the spatial expansion of West Nile virus in Europe

West Nile virus (WNV) is an emerging mosquito-borne pathogen in Europe where it represents a new public health threat. While climate change has been cited as a potential driver of its spatial expansion on the continent, a formal evaluation of this causal relationship is lacking. Here, we investigate the extent to which WNV spatial expansion in Europe can be attributed to climate change while accounting for other direct human influences such as land-use and human population changes. To this end, we trained ecological niche models to predict the risk of local WNV circulation leading to human cases to then unravel the isolated effect of climate change by comparing factual simulations to a counterfactual based on the same environmental changes but a counterfactual climate where long-term trends have been removed. Our findings demonstrate a notable increase in the area ecologically suitable for WNV circulation during the period 1901-2019, whereas this area remains largely unchanged in a no-climate-change counterfactual. We show that the drastic increase in the human population at risk of exposure is partly due to historical changes in population density, but that climate change has also been a critical driver behind the heightened risk of WNV circulation in Europe.

Prevalence of depressive tendencies among college students and the influence of attributional styles on depressive tendencies in the post-pandemic era

Introduction

Depression symptoms are prevalent globally, including China, with a notable impact on college students. This study aims to not only estimate the prevalence of depressive tendencies and attributional styles among college students in the post-pandemic era but also explore the relationship between the two factors. The findings of this study can provide new insights into early intervention and support services for individuals exhibiting tendencies toward depression.

Methods

The survey was administered to college students from various academic backgrounds at a specific university in southern Jiangxi Province by employing two scales to investigate depressive tendencies and attributional styles. Depressive tendency was evaluated using the Patient Health Questionnaire-9 (PHQ-9), while the attributional styles were assessed using the Multidimensional-Multiattributional Causality Scale (MMCS). Univariate analysis and multiple logistic regressions were conducted to identify the related factors of depressive tendency.

Results

A relatively high (48.9%) prevalence of depression among college students was found in this study. College students with higher grades (OR = 1.574, 95%CI: 1.369-1.810), profession of medicine and allied health sciences (OR = 1.779, 95%CI: 1.203-2.629), experiencing higher study stress (OR = 2.006, 95%CI: 1.601-2.514), and having poor physical condition (OR = 1.527, 95%CI: 1.247-1.869) were identified as risk factors for depressive tendency. The correlation between higher grades and increased learning pressure, coupled with poorer physical condition, heightens the vulnerability of college students to depression. Moreover, the more they attribute these experiences to achievement effort (OR = 0.897, 95%CI: 0.828-0.972), achievement ability (OR = 0.903, 95%CI: 0.838-0.972), and affiliation context (OR = 0.919, 95%CI: 0.860-0.982), the less likely they are to develop depression.

Conclusion

In the group of college students, especially those in higher grades, profession of medicine and allied health sciences or experiencing high learning pressure and poor physical condition, emphasizing the significance of their mental well-being becomes crucial. Offering suitable support and assistance is essential. Additionally, fostering the cultivation of positive attributional and coping strategies by attributing difficulties to controllable factors and instilling a belief in their ability to overcome challenges can help reduce the risk of depression.

Increased Asian aerosols drive a slowdown of Atlantic Meridional Overturning Circulation

Observational evidence and climate model experiments suggest a slowdown of the Atlantic Meridional Overturning Circulation (AMOC) since the mid-1990s. Increased greenhouse gases and the declined anthropogenic aerosols (AAs) over North America and Europe are believed to contribute to the AMOC slowdown. Asian AAs continue to increase but the associated impact has been unclear. Using ensembles of climate simulations, here we show that the radiative cooling resulting from increased Asian AAs drives an AMOC reduction. The increased AAs over Asia generate circumglobal stationary Rossby waves in the northern midlatitudes, which shift the westerly jet stream southward and weaken the subpolar North Atlantic westerlies. Consequently, reduced transport of cold air from North America hinders water mass transformation in the Labrador Sea and thus contributes to the AMOC slowdown. The link between increased Asian AAs and an AMOC slowdown is supported by different models with different configurations. Thus, reducing emissions of Asian AAs will not only lower local air pollution, but also help stabilize the AMOC.

Evidence of human influence on Northern Hemisphere snow loss

Documenting the rate, magnitude and causes of snow loss is essential to benchmark the pace of climate change and to manage the differential water security risks of snowpack declines1-4. So far, however, observational uncertainties in snow mass5,6 have made the detection and attribution of human-forced snow losses elusive, undermining societal preparedness. Here we show that human-caused warming has caused declines in Northern Hemisphere-scale March snowpack over the 1981-2020 period. Using an ensemble of snowpack reconstructions, we identify robust snow trends in 82 out of 169 major Northern Hemisphere river basins, 31 of which we can confidently attribute to human influence. Most crucially, we show a generalizable and highly nonlinear temperature sensitivity of snowpack, in which snow becomes marginally more sensitive to one degree Celsius of warming as climatological winter temperatures exceed minus eight degrees Celsius. Such nonlinearity explains the lack of widespread snow loss so far and augurs much sharper declines and water security risks in the most populous basins. Together, our results emphasize that human-forced snow losses and their water consequences are attributable-even absent their clear detection in individual snow products-and will accelerate and homogenize with near-term warming, posing risks to water resources in the absence of substantial climate mitigation.

What are they in it for? Marginalised group members' perceptions of allies differ depending on the costs and rewards associated with their allyship

Advantaged group allies can incur costs or rewards as a result of their allyship. The present work investigates whether such costs and rewards affect how marginalised group members perceive these allies. Across four experiments that collectively examine marginalised group members' perceptions of individual and corporate allies in the context of allyship for women's rights, Black Lives Matter and the LGBTQI+ community, we find that allies are perceived differently as a function of the costs and rewards associated with their allyship. Allies who face costs are perceived more positively in terms of tenacity and genuine motivations, and are generally evaluated more favourably compared to allies who do not face costs and those who, instead, garner rewards for their allyship. These findings demonstrate that marginalised group members are cognisant of the costs and rewards allies may reap, and that this information can shape their judgements of allies' investment in the cause.

Attribution of neuropsychiatric symptoms and prioritisation of evidence in the diagnosis of neuropsychiatric lupus: mixed methods analysis of patient and clinician perspectives from the international INSPIRE study

OBJECTIVE

Neuropsychiatric lupus (NPSLE) is challenging to diagnose. Many neuropsychiatric symptoms, such as headache and hallucinations, cannot be verified by tests or clinician assessment. We investigated prioritisations of methods for diagnosing NPSLE and attributional views.

METHODS

Thematic and comparative analyses were used to investigate how clinicians prioritise sources of evidence from a 13-item list, and explore discordances in clinician and patient perspectives on attribution.

RESULTS

We identified high levels of variability and uncertainty in clinicians' assessments of neuropsychiatric symptoms in SLE patients. In attributional decisions, clinicians (surveys n = 400, interviews n = 50) ranked clinicians' assessments above diagnostic tests (many of which they reported were often unenlightening in NPSLE). Clinicians ranked patient opinion of disease activity last, and 46% of patients reported never/rarely having been asked if their SLE was flaring, despite experienced patients often having "attributional insight". SLE Patients (surveys n = 676, interviews n = 27) estimated higher attributability of neuropsychiatric symptoms to the direct effects of SLE on the nervous system than clinicians (p < 0.001 for all symptoms excluding mania), and 24% reported that their self-assessment of disease activity was never/rarely concordant with their clinicians. Reports of misattributions were common, particularly of non-verifiable diffuse symptoms. Terminology differed between clinicians and influenced attribution estimates.

CONCLUSION

NPSLE diagnostic tests and clinician assessments have numerous limitations, particularly in detecting diffuse neuropsychiatric symptoms that can be directly attributable and benefit from immunosuppression. Our findings suggest that incorporating patient attributional insights-although also subject to limitations-may improve attribution decision-making. Consensus regarding terminology and interpretations of "direct attributability" is required.

The trends of disease burden due to high temperature in Mainland China from 1990 to 2019 and its prediction to 2030

The risk of high-temperature-related diseases is increasing owing to global warming. This study aimed to assess the trend of disease burden caused by high temperatures in Mainland China from 1990 to 2019 and to predict the trend of disease burden over the next 10 years. The latest data were downloaded from the Global Burden of Disease Database (GBD) for analysis, and the disease burden related to high temperature was described by mortality and disability-adjusted life-years (DALYs) and stratified by etiology, sex, and age. Statistical analyses were performed using the R software. In 2019, there were 13,907 deaths attributed to high temperatures in Mainland China, and this was 29.55% higher than the 10,735 deaths in 1990. Overall, the age-standardized mortality and DALYs attributed to high temperatures showed a downward trend from 1990 to 2019. We observed an etiological shift in high-temperature-related diseases. The age-standardized DALYs contribution attributed to high temperatures in 1990 was mainly from communicable, maternal, neonatal, and nutritional diseases (CMNND) (21.81/100,000), followed by injury (18.30/100,000) and non-communicable diseases (10.40/100,000). In 2019, the largest contribution shifted to non-communicable diseases (10.07/100,000), followed by injuries (5.21/100,000), and CMNND (2.30/100,000). The disease burden attributed to high temperatures was higher in males than in females and increased with age. In 2030, the mortality rate and DALYs due to high temperatures are predicted to decrease further, and the largest contribution will come from chronic non-communicable diseases, the occurrence of which will remain at a high level over the next 10 years. The burden of disease due to high temperatures in Mainland China is still heavy, mainly due to population aging and an increase in non-communicable diseases.

Middle east warming in spring enhances summer rainfall over Pakistan

The edge of a monsoon region is usually highly sensitive to climate change. Pakistan, which is located on the northern edge of the Indian monsoon, is highly vulnerable to heavy rainfall and has witnessed several debilitating floods exacerbated by global warming in recent years. However, the mechanisms for the frequent Pakistan floods are yet not fully understood. Here, we show that the Middle East is undergoing an increase in land heating during spring, which is responsible for 46% of the intensified rainfall over Pakistan and northwestern India during 1979-2022. This springtime land warming causes a decline in sea level pressure (SLP), which strengthens the meridional SLP gradient between the Middle East and the southern Arabian Sea and drives the changes of low-level jet (LLJ) subsequently. The impact persists into summer and results in a northward shift of the monsoonal LLJ, accompanied by strong positive vorticity in the atmosphere and enhanced moisture supply to Pakistan. Consequently, the transition region between the summer monsoon in South Asia and the desert climate in West Asia is shifted northwestward, posing significantly enhanced risk of floods over Pakistan and northwestern India.

Aerosols overtake greenhouse gases causing a warmer climate and more weather extremes toward carbon neutrality

To mitigate climate warming, many countries have committed to achieve carbon neutrality in the mid-21st century. Here, we assess the global impacts of changing greenhouse gases (GHGs), aerosols, and tropospheric ozone (O3) following a carbon neutrality pathway on climate and extreme weather events individually using the Community Earth System Model version 1 (CESM1). The results suggest that the future aerosol reductions significantly contribute to climate warming and increase the frequency and intensity of extreme weathers toward carbon neutrality and aerosol impacts far outweigh those of GHGs and tropospheric O3. It reverses the knowledge that the changing GHGs dominate the future climate changes as predicted in the middle of the road pathway. Therefore, substantial reductions in GHGs and tropospheric O3 are necessary to reach the 1.5 °C warming target and mitigate the harmful effects of concomitant aerosol reductions on climate and extreme weather events under carbon neutrality in the future.

Wildfire precursors show complementary predictability in different timescales

In most of the world, conditions conducive to wildfires are becoming more prevalent. Net carbon emissions from wildfires contribute to a positive climate feedback that needs to be monitored, quantified, and predicted. Here we use a causal inference approach to evaluate the influence of top-down weather and bottom-up fuel precursors on wildfires. The top-down dominance on wildfires is more widespread than bottom-up dominance, accounting for 73.3% and 26.7% of regions, respectively. The top-down precursors dominate in the tropical rainforests, mid-latitudes, and eastern Siberian boreal forests. The bottom-up precursors dominate in North American and European boreal forests, and African and Australian savannahs. Our study identifies areas where wildfires are governed by fuel conditions and hence where fuel management practices may be more effective. Moreover, our study also highlights that top-down and bottom-up precursors show complementary wildfire predictability across timescales. Seasonal or interannual predictions are feasible in regions where bottom-up precursors dominate.

Hotspot movement of compound events on the Europe continent

Climate indices are often used as a climate monitoring tool, allowing us to understand how the frequency, intensity, and duration of extreme weather events are changing over time. Here, based on complex statistical analysis we identify highly correlated significant pairs of compound events at the highest spatial resolution, on a monthly temporal scale across Europe. Continental-scale monthly analysis unleashes information on compound events such as high-risk zones, hotspots, monthly shifts of hotspots and trends, risk exposure to land cover and population, and identification of maximum increasing trends. While there are many studies on single or compound climate extremes there are only a few studies that addresses the relationship between pairs of hazards, the incorporation of bioclimatic indices, the determination of a grid best-fit copula approach, and the outlining relevance of this work of compound event risks with exposures. In this respect, here, using 27-bivariate and 10-trivariate copula models, we show that the different hazard pairs have high combined risks of indices related to radiation, temperature, evapotranspiration, bioclimatic-based indices, such as the universal thermal climate index, wind chill index, and heat index, mainly over the northern and eastern European countries. Furthermore, we show that over the last 7 decades, agricultural and coastal areas are highly exposed to the risks of defined hotspots of compound events. In some of the hotspots of compound events-identified by clusters, there is no monthly shifts of hotspots, leading to higher impacts when compounded. Future work needs to integrate the framework and process to identify other compound pairs.

Record-breaking heat days disproportionately influence heat perceptions

From heat waves to hurricanes, tangible weather experiences have been shown to strengthen personal belief in climate change. We ask whether a high temperature day that breaks local heat records-which is a mathematical construct not directly accessible to the senses-has additional impacts on perceptions of worsening heat, above and beyond that of the absolute temperatures. Matching historical heat records to survey data from the United States, we find that each record heat day in a county in 2022 increases perceptions that excessive heat is getting worse, even when controlling for average temperatures, the number of extreme heat days, and demographic factors. Our estimates suggest that exposure to sixteen record heat days predicts roughly the same difference in excessive heat perceptions as between the average Democrat respondent and a political independent. This effect is stronger for populations that are more skeptical of climate science, including Republicans, as well as respondents with weaker beliefs in climate change and more frequent consumption of conservative media. We close with recommendations for media framing of local record-breaking heat events and call for more research on how media outlets cover record-breaking heat.

Anthropogenic fingerprints in daily precipitation revealed by deep learning

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1-4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Points for energy renovation (PointER): A point cloud dataset of a million buildings linked to energy features

Rapid renovation of Europe's inefficient buildings is required to reduce climate change. However, evaluating buildings at scale is challenging because every building is unique. In current practice, the energy performance of buildings is assessed during on-site visits, which are slow, costly, and local. This paper presents a building point cloud dataset that promotes a data-driven, large-scale understanding of the 3D representation of buildings and their energy characteristics. We generate building point clouds by intersecting building footprints with geo-referenced LiDAR data and link them with attributes from UK's energy performance database via the Unique Property Reference Number (UPRN). To mimic England's building stock's features well, we select one million buildings from a range of rural and urban regions, of which half a million are linked to energy characteristics. Building point clouds in new regions can be generated with our published open-source code. The dataset enables novel research in building energy modeling and can be easily expanded to other research fields by adding building features via the UPRN or geo-location.

Detection and attribution of intra-annual mass component of sea-level variations along the Norwegian coast

Reliable sea-level observations in coastal regions are needed to assess the impact of sea level on coastal communities and ecosystems. This paper evaluates the ability of in-situ and remote sensing instruments to monitor and help explain the mass component of sea level along the coast of Norway. The general agreement between three different GRACE/GRACE-FO mascon solutions and a combination of satellite altimetry and hydrography gives us confidence to explore the mass component of sea level in coastal areas on intra-annual timescales. At first, the estimates reveal a large spatial-scale coherence of the sea-level mass component on the shelf, which agrees with Ekman theory. Then, they suggest a link between the mass component of sea level and the along-slope wind stress integrated along the eastern boundary of the North Atlantic, which agrees with the theory of poleward propagating coastal trapped waves. These results highlight the potential of the sea-level mass component from GRACE and GRACE-FO, satellite altimetry and the hydrographic stations over the Norwegian shelf. Moreover, they indicate that GRACE and GRACE-FO can be used to monitor and understand the intra-annual variability of the mass component of sea level in the coastal ocean, especially where in-situ measurements are sparse or absent.

Kernel-weighted contribution: a method of visual attribution for 3D deep learning segmentation in medical imaging

Purpose

Explaining deep learning model decisions, especially those for medical image segmentation, is a critical step toward the understanding and validation that will enable these powerful tools to see more widespread adoption in healthcare. We introduce kernel-weighted contribution, a visual explanation method for three-dimensional medical image segmentation models that produces accurate and interpretable explanations. Unlike previous attribution methods, kernel-weighted contribution is explicitly designed for medical image segmentation models and assesses feature importance using the relative contribution of each considered activation map to the predicted segmentation.

Approach

We evaluate our method on a synthetic dataset that provides complete knowledge over input features and a comprehensive explanation quality metric using this ground truth. Our method and three other prevalent attribution methods were applied to five different model layer combinations to explain segmentation predictions for 100 test samples and compared using this metric.

Results

Kernel-weighted contribution produced superior explanations of obtained image segmentations when applied to both encoder and decoder sections of a trained model as compared to other layer combinations (p < 0.0005 ). In between-method comparisons, kernel-weighted contribution produced superior explanations compared with other methods using the same model layers in four of five experiments (p < 0.0005 ) and showed equivalently superior performance to GradCAM++ when only using non-transpose convolution layers of the model decoder (p = 0.008 ).

Conclusion

The reported method produced explanations of superior quality uniquely suited to fully utilize the specific architectural considerations present in image and especially medical image segmentation models. Both the synthetic dataset and implementation of our method are available to the research community.

Targeted Violence as a Risk Factor for Posttraumatic Stress Disorder Among Cisgender Gay, Bisexual, and Other Men Who have Sex with Men in the United States

Gay, bisexual, and other men who have sex with men (GBMSM) in the United States (US) are disproportionately exposed to interpersonal violence, which carries a high conditional risk for developing posttraumatic stress disorder (PTSD) and which is often motivated by sexual prejudice. We determined PTSD prevalence by violence attribution (motivated by sexual prejudice or not) and measured PTSD-attribution associations. Using a 2020 nationwide cross-sectional survey of 2,886 GBMSM who reported ever experiencing interpersonal violence, we performed multivariable modified Poisson regressions with robust variance estimators to examine differences in prevalence of current PTSD by how participants attributed the violence (occurring due to one's same-sex practices, not occurring due to one's same-sex practices, or being unsure if it occurred due to one's same-sex practices). Model results are reported as adjusted prevalence ratios (aPR) with 95% confidence intervals (CI). Median age was 27 years; 78.8% of participants identified as gay, and 62.2% were non-Hispanic White. Violence was attributed to same-sex practices by 45.8% of participants; 46.3% did not make this attribution, and 7.0% were unsure (0.9% preferred not to answer). Overall, 23.0% screened positive for PTSD, and PTSD prevalence was greater for those who attributed violence to same-sex practices (25.9% [342/1,321]; aPR = 1.55, 95% CI [1.34, 1.79]) and those who were unsure (33.5% [68/203]; aPR = 1.80, 95% CI [1.44, 2.25]) compared to those who did not make the attribution (18.1% [242/1,335]). Age modified this association, with participants 15 to 19 years old who made the attribution being significantly more likely to have PTSD relative to 20+ participants who also made the attribution. In addition to violence-prevention and stigma-mitigation efforts, interventions targeting attribution styles may be useful for violence-exposed GBMSM, especially teenagers.

Holism and Causal Responsibility: The Role of Number and Valence of Event Consequences

The present research examines the effect of holistic-analytic thinking style on causal responsibility. Across seven studies (N = 4,103), participants' thinking style was either measured or manipulated. Then, the valence or number of consequences varied in several scenarios involving a cause-consequence relationship. As a dependent measure, participants indicated the degree of responsibility attributed to the cause mentioned in each scenario. The results revealed that holistic (vs. analytic) participants assigned more responsibility to the cause when the consequences presented were a combination of positive and negative outcomes (vs. univalent), and when multiple (vs. single) consequences were triggered in the scenario. To explore the explanatory factor for these results, a final study manipulated the complexity of the consequences, along with the number. The results of this research suggested that holistic (vs. analytic) individuals consider the degree of complexity of consequences to establish causal attribution.

Adoption of climate-resilient groundnut varieties increases agricultural production, consumption, and smallholder commercialization in West Africa

As part of the climate-smart agriculture approach, the adoption of climate-resilient crop varieties has the potential to build farmers' climate resilience but could also induce agricultural transformation in developing nations. We investigate the relationship between adoption of climate-resilient groundnut varieties and production, consumption, and smallholder commercialization using panel data from Ghana, Mali, and Nigeria. We find adoption of climate-resilient groundnut varieties to increase smallholder production, consumption, and commercialization. The biggest adoption impact gains are observed under the sustained use of these climate-resilient varieties. We show that adoption benefits all households, but the biggest gains are found among smaller producers, suggesting that adoption is inclusive. Furthermore, we provide suggestive evidence that yield increases could explain commercialization, although household consumption also matters. We conclude that adoption of climate-resilient groundnut varieties can at least partially reduce production constraints and promote smallholder consumption and commercialization, with implications for agricultural transformation.

Broadband radiometric measurements from GPS satellites reveal summertime Arctic Ocean Albedo decreases more rapidly than sea ice recedes

New measurements from the Arctic ± 40 days around the summer solstice show reflected sunlight from north of 80°N decreases 20-35%. Arctic sea ice coverage decreases 7-9% over this same time period (as reported by the NSIDC) implying Arctic sea ice albedo decreases in addition to the sea ice receding. Similar Antarctic measurements provide a baseline to which Arctic measurements are compared. The Antarctic reflected sunlight south of 80°S is up to 30% larger than the Arctic reflectance and is symmetric around the solstice implying constant Antarctic reflectivity. Arctic reflected sunlight 20 days after solstice is > 100W/m2 less than Antarctic reflected sunlight. For perspective, this is enough heat to melt > 1 mm/hour of ice. This finding should be compared with climate models and in reanalysis data sets to further quantify sea ice albedo's role in Arctic Amplification. The measurements were made with previously unpublished pixelated radiometers on Global Positioning System satellites from 2014 to 2019. The GPS orbits give each radiometer instantaneous and continuous views of 37% of the Earth, two daily full views of the Arctic and Antarctic. Furthermore, the GPS constellation gives full-time full-Earth coverage that may provide data that complements existing limited field of view instruments that provide a less synoptic Earth view.

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a-1 for oil-gas and 32.7 ± 5.2 Tg a-1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a-1 or 18%.

Detecting and attributing the causes of biodiversity change: needs, gaps and solutions

This issue addresses the multifaceted problems of understanding biodiversity change to meet emerging international development and conservation goals, national economic accounting and diverse community needs. Recent international agreements highlight the need to establish monitoring and assessment programmes at national and regional levels. We identify an opportunity for the research community to develop the methods for robust detection and attribution of biodiversity change that will contribute to national assessments and guide conservation action. The 16 contributions of this issue address six major aspects of biodiversity assessment: connecting policy to science, establishing observation, improving statistical estimation, detecting change, attributing causes and projecting the future. These studies are led by experts in Indigenous studies, economics, ecology, conservation, statistics, and computer science, with representations from Asia, Africa, South America, North America and Europe. The results place biodiversity science in the context of policy needs and provide an updated roadmap for how to observe biodiversity change in a way that supports conservation action via robust detection and attribution science. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

The footprint of human-induced climate change on heat-related deaths in the summer of 2022 in Switzerland

Human-induced climate change is leading to an increase in the intensity and frequency of extreme weather events, which are severely affecting the health of the population. The exceptional heat during the summer of 2022 in Europe is an example, with record-breaking temperatures only below the infamous 2003 summer. High ambient temperatures are associated with many health outcomes, including premature mortality. However, there is limited quantitative evidence on the contribution of anthropogenic activities to the substantial heat-related mortality observed in recent times. Here we combined methods in climate epidemiology and attribution to quantify the heat-related mortality burden attributed to human-induced climate change in Switzerland during the summer of 2022. We first estimated heat-mortality association in each canton and age/sex population between 1990 and 2017 in a two-stage time-series analysis. We then calculated the mortality attributed to heat in the summer of 2022 using observed mortality, and compared it with the hypothetical heat-related burden that would have occurred in absence of human-induced climate change. This counterfactual scenario was derived by regressing the Swiss average temperature against global mean temperature in both observations and CMIP6 models. We estimate 623 deaths [95% empirical confidence interval (95% eCI): 151-1068] due to heat between June and August 2022, corresponding to 3.5% of all-cause mortality. More importantly, we find that 60% of this burden (370 deaths [95% eCI: 133-644]) could have been avoided in absence of human-induced climate change. Older women were affected the most, as well as populations in western and southern Switzerland and more urbanized areas. Our findings demonstrate that human-induced climate change was a relevant driver of the exceptional excess health burden observed in the 2022 summer in Switzerland.

Forensic Discrimination of Smokeless Powders Using Carbon and Nitrogen Isotope Ratios

Improvised explosive devices pose a threat to the public by way of terrorism and criminal activities. In the United States a commonly used low explosive in improvised explosive devices is smokeless powder (SP), due to its ease of access. Traditionally, forensic examinations are often sufficient in determining the physical and chemical characteristics of SPs. However, these exams are limited in differentiating or associating SPs when comparing two materials which are physically and/or chemically consistent. Stable isotope analysis of carbon and nitrogen has been used for explosives to further forensic chemical comparisons and aid in sample differentiation. In this manuscript we explore the utility of stable isotope analysis of SPs to differentiate manufacturer and geographic origin. Both bulk isotope analysis and component isotope analysis of carbon and nitrogen via an extraction method using dichloromethane were evaluated to compare the overall isotope signature of individual SPs. Through the combination of bulk and component isotope measurements of SPs, we were able to identify geographic relationships; however, the manufacturer origins were not as clearly discriminated. This technique demonstrates a potential improvement to traditional forensic examinations of smokeless powder by adding additional information when explosives are chemically and/or physically consistent.

Adolescent Cyberbullies' Attributions: Longitudinal Linkages to Cyberbullying Perpetration

The aim of the present study was to examine cyberbullies' attributions pertaining to their perpetration of cyberbullying, and how such attributions relate to their cyberbullying behaviors six months later. Participants were 216 adolescents (M = 13.46, SD = 0.62 years; 55% female) from the suburbs of a large Midwestern city in the United States. They were interviewed face-to-face in the fall of 2018 concerning why they acted in negative ways toward peers online or through text messages. They also answered questionnaires regarding how often they perpetrated face-to-face bullying and cyberbullying during the fall of 2018 and spring of 2019. The attributions of revenge, convenience, anger, and anonymity each predicted cyberbullying at the second time point while controlling for face-to-face bullying perpetration. Results from this study provide important information to the literature regarding cyberbullies' attributions for perpetrating cyberbullying, and how such attributions predict future cyberbullying perpetration. These findings are important for the development of antibullying programs that might aim to change adolescents' attributions for cyberbullying perpetration to reduce continued engagement in these behaviors.

Complaining, Regret, Superiority, and Discovery: Chinese Patients' Sense Making of Depression in an Online Forum

Drawing on observations of a Chinese online depression community, this article explored the members' sense making of depression by analyzing their narrative accounts of depression. Four types of sense making were predominant among the depression sufferers: complaining, regret, superiority, and discovery. The complaining narrative is the members' telling about the pain caused by family (parental control or neglect), school bullying, stress from study or work, and social norms. The regret narrative is the members' reflection on their habit of perfectionism and lack of self-disclosure. The superiority narrative is the members' attribution of depression to their intelligence and morality that surpass the average people. The discovery narrative is the members' novel understanding of the self, significant others, and key events. The findings suggest that the social and psychological explanation of the causes of depression, instead of the medical model, is popular among the Chinese patients. Their stories of depression are also stories of marginalization, visions for the future, and realizing the normalization of identity as depression patients. The findings have implications for public policy around support for mental health.

Making sense of punishment: Transgressors' interpretation of punishment motives determines the effects of sanctions

Punishment is expected to have an educative, behaviour-controlling effect on the transgressor. Yet, this effect often remains unattained. Here, we test the hypothesis that transgressors' inferences about punisher motives crucially shape transgressors' post-punishment attitudes and behaviour. As such, we give primacy to the social and relational dimensions of punishment in explicating how sanctions affect outcomes. Across four studies using different methodologies (N = 1189), our findings suggest that (a) communicating punishment respectfully increases transgressor perceptions that the punisher is trying to repair the relationship between the transgressor and their group (relationship-oriented motive) and reduces perceptions of harm-oriented and self-serving motives, and that (b) attributing punishment to relationship-oriented (vs. harm/self-oriented, or even victim-oriented) motives increases prosocial attitudes and behaviour. This research consolidates and extends various theoretical perspectives on interactions in justice settings, providing suggestions for how best to deliver sanctions to transgressors.

Regime shift in Arctic Ocean sea ice thickness

Manifestations of climate change are often shown as gradual changes in physical or biogeochemical properties¹. Components of the climate system, however, can show stepwise shifts from one regime to another, as a nonlinear response of the system to a changing forcing². Here we show that the Arctic sea ice regime shifted in 2007 from thicker and deformed to thinner and more uniform ice cover. Continuous sea ice monitoring in the Fram Strait over the last three decades revealed the shift. After the shift, the fraction of thick and deformed ice dropped by half and has not recovered to date. The timing of the shift was preceded by a two-step reduction in residence time of sea ice in the Arctic Basin, initiated first in 2005 and followed by 2007. We demonstrate that a simple model describing the stochastic process of dynamic sea ice thickening explains the observed ice thickness changes as a result of the reduced residence time. Our study highlights the long-lasting impact of climate change on the Arctic sea ice through reduced residence time and its connection to the coupled ocean-sea ice processes in the adjacent marginal seas and shelves of the Arctic Ocean.

Effect of attribution on the emotions and behavioral intentions of third-party observers toward intergroup discriminators during the COVID-19 pandemic

The global outbreak of novel coronavirus disease COVID-19 has caused intergroup discrimination associated with the disease to become increasingly prominent. Research demonstrates that the attitudes and behaviors of third-party observers significantly impact the progression of discrimination incidents. This study tested a parallel mediating model in which the attribution tendencies of observers influence their behavioral intentions through the mediating effect of the emotions of anger and contempt. The first two studies confirmed the proposed model with discrimination incidents reported against "returnees from Wuhan" and "returning workers from Hubei." Study 3 further manipulated the attribution tendencies of observers, providing empirical evidence for the causality from attribution tendencies to emotions, confirming the validity of the model. These findings enrich the cognitive (attribution)-emotion-action model, further enhancing our understanding of the role of third parties in intergroup conflicts, with implications for the management of people's emotions and behaviors in social crises.

Greenhouse warming and internal variability increase extreme and central Pacific El Niño frequency since 1980

El Niño has been recorded to change its properties since the 1980s, characterized by more common extreme El Niño and Central Pacific (CP) El Niño events. However, it is still unclear whether such change is externally forced or part of the natural variability. Here, we find that the frequency of the extreme and CP El Niño events also increased during the period 1875-1905, when the anthropogenic CO2 concentration was relatively lower, but with a positive phase of the Atlantic Multidecadal Oscillation (AMO). Models and palaeoclimate proxies reveal that a positive AMO enhances the zonal sea surface temperature gradient in the CP, which strengthens zonal advective feedback, favoring extreme and CP El Niño development. Moreover, we estimate that internal variability contributed to ~65% of the increasingly extreme and CP El Niño events, while anthropogenic forcing has made our globe experience ~1 more extreme and ~2 more CP events over the past four decades.

Effects of scenario-based attribution on collective emotions and stigma toward persons with COVID-19: A cross-sectional survey

Background and Aims

During this COVID-19 pandemic, many people experience and share emotions such as fear, anxiety, sadness, anger, and disgust, which can be regarded as collective emotions. This study investigated the effects of scenario-based attribution for serious diseases on collective emotions and social stigma.

Methods

Participants were 297 healthy adults who met two conditions: (1) not having tested positive for COVID-19 (including their family members or close friends) and no experience of self-quarantine; and (2) not having been diagnosed with lung cancer, and not having family members or close friends diagnosed with it. Three hundred participants were recruited, through a company conducting online surveys. A total of 297 data sets were analyzed, excluding data supplied by three participants who might have responded unreliably to the filler question. Scenarios were recorded according to attribution type (internal vs. external) and disease (COVID-19 vs. lung cancer). A 2 × 2 factorial design was used, whereby participants were randomly assigned to one of four conditions.

Results

The COVID-19 condition showed higher scores on the perceived risk and fear of the disease compared to the lung cancer one. The COVID-19/internal attribution condition showed the highest scores for fear and anger toward scenario characters, and the lung cancer/external attribution condition showed higher sympathy scores than other conditions. Although attribution to COVID-19 was not directly related to social stigma, it could evoke negative emotions toward infected people.

Conclusion

The findings suggest that attributions of serious diseases such as COVID-19 to infected persons can influence collective emotions and the level of social stigma associated with the disease. Attention to the collective emotions and stigma associated with disease is a key component for communities and countries to recover from and respond to its impacts.

Anthropogenic influence on extremes and risk hotspots

Study of the frequency and magnitude of climate extremes as the world warms is of utmost importance, especially separating the influence of natural and anthropogenic forcing factors. Record-breaking temperature and precipitation events have been studied using event-attribution techniques. Here, we provide spatial and temporal observation-based analyses of the role of natural and anthropogenic factors, using state-of-the-art time series methods. We show that the risk from extreme temperature and rainfall events has severely increased for most regions worldwide. In some areas the probabilities of occurrence of extreme temperatures and precipitation have increased at least fivefold and twofold, respectively. Anthropogenic forcing has been the main driver of such increases and its effects amplify those of natural forcing. We also identify risk hotspots defined as regions for which increased risk of extreme events and high exposure in terms of either high Gross Domestic Product (GDP) or large population are both present. For the year 2018, increased anthropogenic forcings are mostly responsible for increased risk to extreme temperature/precipitation affecting 94%/72% of global population and 97%/76% of global GDP relative to the baseline period 1961-1990.

Parents of Children With High Weight Are Viewed as Responsible for Child Weight and Thus Stigmatized

Courts in seven U.S. states have removed children with "obesity" from parental custody until children could maintain "healthy weights." These rulings-alongside qualitative reports from parents of children with high weight (PoCHs)-suggest that PoCHs are judged as bad parents. Yet little work has tested whether people genuinely stigmatize PoCHs or what drives this phenomenon. In three experiments with U.S. online community participants (N = 1,011; two preregistered), we tested an attribution theory model: Social perceivers attribute children's weights to parents and thus stigmatize those parents. Experiments 1 and 2 support this model (across parent and child gender). Experiment 3 manipulated attributions of parental responsibility for child weight, revealing attenuated stigma with low attributions of responsibility. Findings are among the first to describe and explain stigma toward a large demographic (parents of children with obesity)-with real-world implications (e.g., for family separation, health care)-and may additionally illuminate the psychology underlying stigma toward parents of children with other potentially stigma-evoking identities.

Understanding variability in petroleum jet fuel life cycle greenhouse gas emissions to inform aviation decarbonization

A pressing challenge facing the aviation industry is to aggressively reduce greenhouse gas emissions in the face of increasing demand for aviation fuels. Climate goals such as carbon-neutral growth from 2020 onwards require continuous improvements in technology, operations, infrastructure, and most importantly, reductions in aviation fuel life cycle emissions. The Carbon Offsetting Scheme for International Aviation of the International Civil Aviation Organization provides a global market-based measure to group all possible emissions reduction measures into a joint program. Using a bottom-up, engineering-based modeling approach, this study provides the first estimates of life cycle greenhouse gas emissions from petroleum jet fuel on regional and global scales. Here we show that not all petroleum jet fuels are the same as the country-level life cycle emissions of petroleum jet fuels range from 81.1 to 94.8 gCO₂e MJ^-1, with a global volume-weighted average of 88.7 gCO₂e MJ^-1. These findings provide a high-resolution baseline against which sustainable aviation fuel and other emissions reduction opportunities can be prioritized to achieve greater emissions reductions faster.

An increase in marine heatwaves without significant changes in surface ocean temperature variability

Marine heatwaves (MHWs)-extremely warm, persistent sea surface temperature (SST) anomalies causing substantial ecological and economic consequences-have increased worldwide in recent decades. Concurrent increases in global temperatures suggest that climate change impacted MHW occurrences, beyond random changes arising from natural internal variability. Moreover, the long-term SST warming trend was not constant but instead had more rapid warming in recent decades. Here we show that this nonlinear trend can-on its own-appear to increase SST variance and hence MHW frequency. Using a Linear Inverse Model to separate climate change contributions to SST means and internal variability, both in observations and CMIP6 historical simulations, we find that most MHW increases resulted from regional mean climate trends that alone increased the probability of SSTs exceeding a MHW threshold. Our results suggest the need to carefully attribute global warming-induced changes in climate extremes, which may not always reflect underlying changes in variability.

Quantification of human contribution to soil moisture-based terrestrial aridity

Current knowledge of the spatiotemporal patterns of changes in soil moisture-based terrestrial aridity has considerable uncertainty. Using Standardized Soil Moisture Index (SSI) calculated from multi-source merged data sets, we find widespread drying in the global midlatitudes, and wetting in the northern subtropics and in spring between 45°N-65°N, during 1971-2016. Formal detection and attribution analysis shows that human forcings, especially greenhouse gases, contribute significantly to the changes in 0-10 cm SSI during August-November, and 0-100 cm during September-April. We further develop and apply an emergent constraint method on the future SSI's signal-to-noise (S/N) ratios and trends under the Shared Socioeconomic Pathway 5-8.5. The results show continued significant presence of human forcings and more rapid drying in 0-10 cm than 0-100 cm. Our findings highlight the predominant human contributions to spatiotemporally heterogenous terrestrial aridification, providing a basis for drought and flood risk management.

A potential explanation for the global increase in tropical cyclone rapid intensification

Tropical cyclone rapid intensification events often cause destructive hurricane landfalls because they are associated with the strongest storms and forecasts with the highest errors. Multi-decade observational datasets of tropical cyclone behavior have recently enabled documentation of upward trends in tropical cyclone rapid intensification in several basins. However, a robust anthropogenic signal in global intensification trends and the physical drivers of intensification trends have yet to be identified. To address these knowledge gaps, here we compare the observed trends in intensification and tropical cyclone environmental parameters to simulated natural variability in a high-resolution global climate model. In multiple basins and the global dataset, we detect a significant increase in intensification rates with a positive contribution from anthropogenic forcing. Furthermore, thermodynamic environments around tropical cyclones have become more favorable for intensification, and climate models show anthropogenic warming has significantly increased the probability of these changes.

The disambiguation of people names in biological collections

Scientific collections have been built by people. For hundreds of years, people have collected, studied, identified, preserved, documented and curated collection specimens. Understanding who those people are is of interest to historians, but much more can be made of these data by other stakeholders once they have been linked to the people's identities and their biographies. Knowing who people are helps us attribute work correctly, validate data and understand the scientific contribution of people and institutions. We can evaluate the work they have done, the interests they have, the places they have worked and what they have created from the specimens they have collected. The problem is that all we know about most of the people associated with collections are their names written on specimens. Disambiguating these people is the challenge that this paper addresses. Disambiguation of people often proves difficult in isolation and can result in staff or researchers independently trying to determine the identity of specific individuals over and over again. By sharing biographical data and building an open, collectively maintained dataset with shared knowledge, expertise and resources, it is possible to collectively deduce the identities of individuals, aggregate biographical information for each person, reduce duplication of effort and share the information locally and globally. The authors of this paper aspire to disambiguate all person names efficiently and fully in all their variations across the entirety of the biological sciences, starting with collections. Towards that vision, this paper has three key aims: to improve the linking, validation, enhancement and valorisation of person-related information within and between collections, databases and publications; to suggest good practice for identifying people involved in biological collections; and to promote coordination amongst all stakeholders, including individuals, natural history collections, institutions, learned societies, government agencies and data aggregators.

Dokha brand differentiation by elemental analysis measured by inductively coupled plasma-mass spectrometry

Dokha is a tobacco product commonly used in Middle Eastern and Northern African regions. It is available in three blends purportedly corresponding to the degree of "buzz" experienced by the user. The "buzz" has been linked in part to nicotine levels, which are higher than those found in cigarettes and is believed to be the reason dokha is abused as a "legal high." There have been reports of seizure activity from dokha users, and elevated concentrations of toxic metals have been measured in dokha tobacco. The purpose of this work was to determine whether we could use dokha's elemental content, measured by inductively coupled plasma-mass spectrometry, to link dokha back to its brand. This could aid investigators in identifying brands and/or distribution routes in the case of adverse effects resulting from dokha use. We measured the concentrations of Mg, K, Mn, Ni, Cu, Rb, Sr, and Ba in Medwakh, Nirvana, Scorpion, Enjoy, Kingdom, and Iconic dokha brands. Analysis of variance revealed statistical differences in concentrations of elements among groups. Discriminant function analysis (using leave-one-out classification) was 58.3% successful at differentiating brands. Enjoy dokha was the most, and Kingdom dokha the least, correctly classified among groups. Attempts to further link dokha blends back to light, medium, and heavy blends were less successful. These results indicate potential for using elemental content to discriminate among dokha brands. Our data may also help to understand the degree of additional processing and/or adulteration of dokha products available to users in the United States.

Underlying Mechanisms of Brand Feedback's Mixed Effects in E-Commerce: Roles of Perceived Controllability, Stability, and Brand Trust

The study (N = 879) investigated underlying mechanisms of the effects of brand feedback (a business' written response) to negative electronic word of mouth (eWOM) messages (e.g., online product reviews) using the theoretical framework of the attribution theory. Findings suggest that brand feedback can positively (via an indirect route) as well as negatively (via a direct route) affect prospective consumers' purchase intentions. Brand feedback positively affects purchase intentions in part through a reduction in consumers' perceptions of the brand's volitional control over the problem (controllability) and long-lasting nature (stability) of the cause of the problem described in a negative eWOM. Brand trust also partially mediates these indirect positive effects.

The Effect of Observational Learning on Self-Efficacy by Sport Competition Condition, Performance Level of Team Members, and Whether You Win or Lose

This study examined the effect of athletes' competition conditions, personal performance level, and attributions toward winning or losing on the relationship between observational learning (OL) and self-efficacy (SE) based on social cognitive theory and social comparison theory. Study 1 verified the validity and reliability of the Korean versions of the Functions of Observational Learning Questionnaire (FOLQ) and the SE Questionnaire. Study 2 investigated differences in the degree to which OL predicts SE in different pressure conditions and personal performance levels. The results showed that OL increased SE in high-performing athletes in high-pressure games and better predicted SE in low-performing athletes in low-pressure games. Study 3 tested the double-mediating effects of effect and OL on the effect of attributions about winning or losing on SE. The results showed that a stronger perception that the cause of winning was internal was associated with increased pride, OL, and SE.

Calibrating statistical tools: Improving the measure of Humanity's influence on the climate

Over the last twenty-five years, climate scientists working on the attribution of climate change to humans have developed increasingly sophisticated statistical models in a process that can be understood as a kind of calibration: the gradual changes to the statistical models employed in attribution studies served as iterative revisions to a measurement(-like) procedure motivated primarily by the aim of neutralizing particularly troublesome sources of error or uncertainty. This practice is in keeping with recent work on the evaluation of models more generally that views models as tools for particular tasks: what drives the process is the desire for models that provide more reliable grounds for inference rather than accuracy to the underlying mechanisms of data generation.

Muslim = Terrorist? Attribution of violent crimes to terrorism or mental health problems depend on perpetrators' religious background

The present work investigates whether the assumed religious background of a perpetrator in a carried out (Study 1) and attempted mass shooting (Study 2) influences attribution of the crime to mental health problems or terrorist motives as well as to evaluation of appropriate punishment. In two experimental studies (n =  113 and n =  340) participants were confronted with a scenario depicting an (attempted) mass shooting that was either carried out by a perpetrator with a German or an Arabic/Muslim name. Results indicate that compared to a perpetrator with a German name, a shooting carried out by a perpetrator with an Arabic/Muslim name led to increased attributions to a terrorist motive and fewer attributions to mental health problems. Moreover, in Study 2, this attribution pattern was accompanied by increased punitiveness. The findings are discussed against the background of previous work showing comparable results as well as practical implications.