Relative Importance Of Changes Research Articles

Forcing for varying boundary layer stability across Antarctica

Abstract. The relative importance of changes in radiative forcing (downwelling longwave radiation) and mechanical mixing (20 m wind speed) in controlling boundary layer stability annually and seasonally at five study sites across the Antarctica continent is presented. From near neutral to extremely strong near-surface stability, radiative forcing decreases with increasing stability, as expected, and is shown to be a major driving force behind variations in near-surface stability at all five sites. Mechanical mixing usually decreases with increasing near-surface stability for regimes with weak to extremely strong stability. For the cases where near neutral, very shallow mixed, and weak stability occur, the wind speed in the very shallow mixed case is usually weaker compared to the near neutral and weak stability cases, while radiative forcing is largest for the near neutral cases. This finding is an important distinguishing factor for the unique case where a very shallow mixed layer is present, indicating that weaker mechanical mixing in this case is likely responsible for the shallower boundary layer that defines the very shallow mixed stability regime. For cases with enhanced stability above a layer of weaker near-surface stability, lower downwelling longwave radiation promotes the persistence of the stronger stability aloft, while stronger near-surface winds act to maintain weaker stability immediately near the surface, resulting in this two-layer boundary layer stability regime.

Future Projection of Mortality From Exposure to PM2.5 and O3 Under the Carbon Neutral Pathway: Roles of Changing Emissions and Population Aging

AbstractA global chemical transport model GEOS‐Chem was applied to examine the concentrations of PM2.5 and O3 in China, related health burdens and the relative importance of changes in air pollutants and population aging over 2015–2060 under carbon neutral pathway (Shared Socioeconomic Pathway limiting end‐of‐century radiative forcing to 1.9 W m−2, SSP1‐1.9). Results showed synergistic reductions of 100.0%, 72.0%, and 24.4% in net CO2 emission, concentration of annual mean PM2.5, and the 90th maximum daily average 8‐hr (MDA8) O3 over China, respectively, during 2015–2060. Pollutants‐related deaths owing to changes in pollutants and population were simulated to increase by 38.1% over 2015–2060 because of population aging. Over 2015–2060, sensitivity studies showed that the decline in pollutants alone would mitigate deaths by 5,172.7 thousand, while the population aging alone would increase deaths by 2,633.3 thousand. Carbon neutrality will avoid 3,520.0 thousand deaths in 2060 relative to a higher‐carbon pathway (SSP5‐8.5).

Climate and fire drivers of forest composition and openness in the Changbai Mountains since the Late Glacial

Ongoing climate changes have a direct impact on forest growth; they also affect natural fire regimes, with further implications for forest composition. Understanding of how these will affect forests on decadal-to-centennial timescales is limited. Here we use reconstructions of past vegetation, fire regimes and climate during the Holocene to examine the relative importance of changes in climate and fire regimes for the abundance of key tree species in northeastern China. We reconstructed vegetation changes and fire regimes based on pollen and charcoal records from Gushantun peatland. We then used generalized linear modelling to investigate the impact of reconstructed changes in summer temperature, annual precipitation, background levels of fire, fire frequency and fire magnitude to identify the drivers of decadal-to-centennial changes in forest openness and composition. Changes in climate and fire regimes have independent impacts on the abundance of the key tree taxa. Climate variables are generally more important than fire variables in determining the abundance of individual taxa. Precipitation is the only determinant of forest openness, but summer temperature is more important than precipitation for individual tree taxa with warmer summers causing a decrease in cold-tolerant conifers and an increase in warmth-demanding broadleaved trees. Both background level and fire frequency have negative relationships with the abundance of most tree taxa; only Pinus increases as fire frequency increases. The magnitude of individual fires does not have a significant impact on species abundance on this timescale. Both climate and fire regime characteristics must be considered to understand changes in forest composition on the decadal-to-centennial timescale. There are differences, both in sign and magnitude, in the response of individual tree species to individual drivers.

Cost-utility analysis of a universal pneumococcal vaccination programme for older adults in Norway

ABSTRACT The aim of this study was to establish whether a universal pneumococcal vaccination for older adults in Norway is likely to be cost-effective from the perspective of the health care provider. A decision tree model developed by the Public Health Agency of Sweden was adopted to the Norwegian setting. Two cohorts, consisting of 65-year-olds and 75-year-olds grouped into vaccinated and unvaccinated, were followed over a 5-year time horizon. In the base case, the 23-valent polysaccharide vaccine (PPV23) was used while the 13-valent pneumococcal conjugate vaccine (PCV13) was included in scenario analyses only. The costs and health benefits (measured in quality adjusted life years (QALY) gained) were compared in the two cohorts between the vaccinated and unvaccinated groups. The impact of indirect effects of the vaccine, such as herd immunity and serotype replacement, were not investigated. The relative importance of change in price was assessed by performing one-way sensitivity analyses. Under base-case assumptions, the programme for the 75-year-old cohort is expected to be cost-effective from the health care perspective at the current pharmacy purchasing price and at 75% vaccination coverage as it falls below the lower end of the cost-effectiveness threshold range (NOK 9467/EUR 964). In comparison, for the 65-year-old cohort the cost per QALY gained is approximately NOK 780 206 (EUR 79 451) under the base-case assumptions which falls within the acceptable ranges in a Norwegian context for both the 65- and 75-year-old cohorts. There is no exact cost-effectiveness threshold in Norway. However, introducing a vaccination programme against pneumococcal disease for 65-year-olds and 75-year-olds in Norway is likely to fall within the acceptable cost-effectiveness threshold range.

Fire as a driver and mediator of predator-prey interactions.

ABSTRACTBoth fire and predators have strong influences on the population dynamics and behaviour of animals, and the effects of predators may either be strengthened or weakened by fire. However, knowledge of how fire drives or mediates predator–prey interactions is fragmented and has not been synthesised. Here, we review and synthesise knowledge of how fire influences predator and prey behaviour and interactions. We develop a conceptual model based on predator–prey theory and empirical examples to address four key questions: (i) how and why do predators respond to fire; (ii) how and why does prey vulnerability change post‐fire; (iii) what mechanisms do prey use to reduce predation risk post‐fire; and (iv) what are the outcomes of predator–fire interactions for prey populations? We then discuss these findings in the context of wildlife conservation and ecosystem management before outlining priorities for future research. Fire‐induced changes in vegetation structure, resource availability, and animal behaviour influence predator–prey encounter rates, the amount of time prey are vulnerable during an encounter, and the conditional probability of prey death given an encounter. How a predator responds to fire depends on fire characteristics (e.g. season, severity), their hunting behaviour (ambush or pursuit predator), movement behaviour, territoriality, and intra‐guild dynamics. Prey species that rely on habitat structure for avoiding predation often experience increased predation rates and lower survival in recently burnt areas. By contrast, some prey species benefit from the opening up of habitat after fire because it makes it easier to detect predators and to modify their behaviour appropriately. Reduced prey body condition after fire can increase predation risk either through impaired ability to escape predators, or increased need to forage in risky areas due to being energetically stressed. To reduce risk of predation in the post‐fire environment, prey may change their habitat use, increase sheltering behaviour, change their movement behaviour, or use camouflage through cryptic colouring and background matching. Field experiments and population viability modelling show instances where fire either amplifies or does not amplify the impacts of predators on prey populations, and vice versa. In some instances, intense and sustained post‐fire predation may lead to local extinctions of prey populations. Human disruption of fire regimes is impacting faunal communities, with consequences for predator and prey behaviour and population dynamics. Key areas for future research include: capturing data continuously before, during and after fires; teasing out the relative importance of changes in visibility and shelter availability in different contexts; documenting changes in acoustic and olfactory cues for both predators and prey; addressing taxonomic and geographic biases in the literature; and predicting and testing how changes in fire‐regime characteristics reshape predator–prey interactions. Understanding and managing the consequences for predator–prey communities will be critical for effective ecosystem management and species conservation in this era of global change.

Oil-price uncertainty and the U.K. unemployment rate: A forecasting experiment with random forests using 150 years of data

We analyze the predictive role of oil-price uncertainty for changes in the UK unemployment rate using more than a century of monthly data covering the period from 1859 (when the drilling of the first oil well started at Titusville, Pennsylvania, United States) to 2020. To this end, we use a machine-learning technique known as random forests. Random forests render it possible to model the potentially nonlinear link between oil-price uncertainty and subsequent changes in the unemployment rate in an entirely data-driven way, where it is possible to control for the impact of several other macroeconomic variables and other macroeconomic and financial uncertainties. We estimate random forests on rolling-estimation windows and find evidence that oil-price uncertainty predicts out-of-sample changes in the unemployment rate, especially at longer (six and twelve months) forecast horizons. Moreover, the relative importance of oil-price uncertainty has undergone substantial swings during the history of the modern petroleum industry. Relative importance was high in the 1970s and the 1980s, and it was higher than the relative importance of changes in the oil price itself for most of the sample period. We also find that oil-price uncertainty has predictive value for changes in the unemployment rate when we use a Lasso estimator, where random forests have a superior forecasting performance relative to the Lasso forecasts.

The sensitivity of fuel moisture to forest structure effects on microclimate

An understanding of variation in dead fuel moisture content (FMC) is essential for accurate predictions of wildfire risk, particularly in productive wet forests where FMC is a primary control on fire activity. In these systems, forest structure and composition influence microclimate, which in turn effects FMC. However, changing disturbance regimes are altering forest structure and our understanding of the sensitivity of FMC to these variations is incomplete. To explore this, we quantified the relative importance of changes in microclimate resulting from altered forest structure to FMC variability. This was done by modelling FMC using microclimate scenarios extracted from observations at six field sites with contrasting structural profiles. The scenarios related to maximum, mean, and minimum fire-related microclimate conditions. To understand sensitivity in a fire management context, we summarised results using FMC thresholds of fuel availability (FA) across three seasons – corresponding to wildfire and prescribed burning conditions. Distinct differences in FA demonstrate the potential for altered structure to influence fire activity in wet forests. Structure effects on vapour pressure deficit (VPD) and longwave radiation (LWR) exerted the strongest control on FA, resulting in increases of 125% and 87% across all seasons respectively, while shortwave radiation (SWR) had a limited influence. However, FMC sensitivity to microclimate inputs changed with season. Critically, in summer, forest structure effects generating elevated VPD conditions resulted in 8 additional days (of 30) when FMC was less than 10%, a threshold for intense fire behaviour. Our research supports the hypothesis that FMC is sensitive to forest structure change, and that this sensitivity can be mechanistically linked to elevated VPD and LWR in the microclimate resulting from these changes. Given the potential for disturbances to alter forest structure in the future, the potential impact of this on microclimate and FMC should be considered in landscape predictions of wildfire risk.

Contributions of changes in physical activity, sedentary time, diet and body weight to changes in cardiometabolic risk

BackgroundIncreased physical activity (PA), reduced time spent sedentary (SED), healthier diet and reduced body weight may all have a positive impact on cardiometabolic risk. The relative importance of change in each of these variables on cardiometabolic risk, however, is unclear. We therefore sought to investigate the relative contributions of changes in PA, SED, diet and body weight on cardiometabolic risk.MethodsThis is a secondary analysis of data collected from the EuroFIT randomised controlled trial, which was a 12-week group-based lifestyle intervention for overweight middle-aged men delivered by coaches in football club stadia aiming to improve PA, SED, diet, and body weight. PA and SED were assessed by accelerometry, diet using the Dietary Instrument for Nutrition Education (DINE). An overall cardiometabolic risk score was derived from combining z-scores for glucose, HbA1c, insulin, lipids and blood pressure. In total, 707 men (from the overall cohort of 1113) with complete data for these variables at baseline and 12-month follow-up were included in the multivariable linear regression analyses.ResultsIn multivariable analyses, change in number of steps (explaining 5.1% of R2) and dietary factors (less alcohol, fatty and sugary food, and more fruit and vegetables) (together explaining 4.5% of R2), but not changes in standing time or SED, were significantly associated with change in body weight. Changes in number of steps (R2 = 1.7%), fatty food score (R2 = 2.4%), and sugary food score (R2 = 0.4%) were significantly associated with change in cardiometabolic risk score in univariable models. However, in multivariable models which included changes in weight as well as changes in steps and dietary variables, change in weight explained a substantially larger proportion of the change in cardiometabolic risk score, explaining 14.1% of R2 (out of an overall model R2 of 19.0%). When baseline (as well as change) values were also included in the model, 38.8% of R2 for change in cardiometabolic risk score was explained overall, with 14.1% of R2 still explained by change in weight.ConclusionChange in body weight, together with baseline cardiometabolic risk explained most of the change in cardiometabolic risk. Thus, the benefits of increasing physical activity and improving diet on cardiometabolic risk appear to act largely via an effect on changes in body weight.Trial registrationInternational Standard Randomised Controlled Trials, ISRCTN-81935608. Registered 06052015. https://www.isrctn.com/ISRCTN81935608?q=&filters=recruitmentCountry:Portugal&sort=&offset=7&totalResults=92&page=1&pageSize=10&searchType=basic-search

Plant diversity promotes soil fungal pathogen richness under fertilization in an alpine meadow

Abstract Aims The effects of fertilization on fungal plant pathogens in agricultural soils have been studied extensively. However, we know little about how fertilization affects the relative abundance and richness of soil fungal plant pathogens in natural ecosystems, either through altering the soil properties or plant community composition. Methods Here, we used data from a 7-year nitrogen (N) addition experiment in an alpine meadow on the Qinghai-Tibetan Plateau to test how N addition affects the relative abundance and richness of soil fungal plant pathogens, as determined using Miseq sequencing of ITS1 gene biomarkers. We also evaluated the relative importance of changes in soil properties versus plant species diversity under N addition. Important Findings Using general linear model selection and a piecewise structural equation model, we found that N addition increased the relative abundance of soil fungal plant pathogens by significantly altering soil properties. However, higher host plant species richness led to higher soil fungal plant pathogen richness, even after excluding the effects of N addition. We conclude that the relative abundance and richness of soil fungal plant pathogens are regulated by different mechanisms in the alpine meadow. Continuous worldwide N inputs (through both fertilizer use and nitrogen deposition) not only cause species losses via altered plant species interactions, but also produce changes in soil properties that result in more abundant soil fungal plant pathogens. This increase in pathogen relative abundance may seriously threaten ecosystem health, thus interrupting important ecosystem functions and services.

Disentangling the effects of photosynthetically active radiation and red to far-red ratio on plant photosynthesis under canopy shading: a simulation study using a functional-structural plant model.

Background and AimsShading by an overhead canopy (i.e. canopy shading) entails simultaneous changes in both photosynthetically active radiation (PAR) and red to far-red ratio (R:FR). As plant responses to PAR (e.g. changes in leaf photosynthesis) are different from responses to R:FR (e.g. changes in plant architecture), and these responses occur at both organ and plant levels, understanding plant photosynthesis responses to canopy shading needs separate analysis of responses to reductions in PAR and R:FR at different levels.MethodsIn a glasshouse experiment we subjected plants of woody perennial rose (Rosa hybrida) to different light treatments, and so separately quantified the effects of reductions in PAR and R:FR on leaf photosynthetic traits and plant architectural traits. Using a functional–structural plant model, we separately quantified the effects of responses in these traits on plant photosynthesis, and evaluated the relative importance of changes of individual traits for plant photosynthesis under mild and heavy shading caused by virtual overhead canopies.Key ResultsModel simulations showed that the individual trait responses to canopy shading could have positive and negative effects on plant photosynthesis. Under mild canopy shading, trait responses to reduced R:FR on photosynthesis were generally negative and with a larger magnitude than effects of responses to reduced PAR. Conversely, under heavy canopy shading, the positive effects of trait responses to reduced PAR became dominant. The combined effects of low-R:FR responses and low-PAR responses on plant photosynthesis were not equal to the sum of the separate effects, indicating interactions between individual trait responses.ConclusionsOur simulation results indicate that under canopy shading, the relative importance of plant responses to PAR and R:FR for plant photosynthesis changes with shade levels. This suggests that the adaptive significance of plant plasticity responses to one shading factor depends on plant responses to the other.

Population dynamics of small endotherms under global change: Greater white-toothed shrews Crocidura russula in Mediterranean habitats

Small endotherms would be especially exposed to main global change drivers (habitat and climate changes) but would also be able to withstand them by adjusting population dynamics locally to changing climate- and habitat-driven food and predation conditions. We analyse the relative importance of changes in climate (mean and variability, including relevant time-lags) and habitat conditions on the abundance, age structure and growth rate of Mediterranean populations of a small endotherm, the greater white-toothed shrew Crocidura russula, along a 10-year period (2008–2017). Habitat type and season were the key factors shaping shrew population dynamics, which showed consistent peak numbers in open habitats in autumn, after the spring-summer reproductive period. Significant increases in aridity (increasing temperature and decreasing rainfall) along the study period did not explain variation in shrew numbers, although short-term variations in abundance were negatively related to relative air humidity and temperature over three last months prior to the surveys. Overall, ongoing climate change have not yet affected shrew population dynamics in its core areas of the Mediterranean region, in spite of expectations based on climate change rate in this region and small endotherm sensitivity to these changes. Reliance on open habitats with lower predation pressure would explain the resilience of shrew populations to climate change. However, current trends of land use change (land abandonment and afforestation) threaten Mediterranean open habitats, so that resilience would not last for long if these trends are not counteracted.

Outsourcing, trade, technology, and greenhouse gas emissions

U.S. output has steadily outpaced the rise in greenhouse gas (GHG) emissions over the past several decades. The decoupling of these two trends represents a decline in aggregate GHG emission intensity. Using recently released national datasets covering industry-specific GHG emissions and shipments, this paper decomposes the relative importance of changes in various channels underlying changes in aggregate GHG emissions in the U.S. from 1997 to 2015: scale or national output growth, cross-sector composition changes, and a technique effect capturing other factors lowering emission intensities within the country’s productive industries. The results demonstrate that reductions in within-sector techniques explain two-thirds, and cross-sector shifting of economic activity towards cleaner industries explains one-third of the increasing gap. Using data on industry exports and imports, this paper further investigates the relative environmental effect of trade on GHG emissions. Together, increased exporting, and importing, of both intermediate and final goods, has corresponded to a relatively small expansion of cleaner sectors and appears to have contributed slightly to the relative expansion of cleaner U.S. industries. In 2015, U.S. imports of intermediate and final goods account for the displacement of roughly 290 million metric tons of U.S. GHG emissions, representing less than 5% of U.S. GHG emissions in the same year.

Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution.

Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red‐eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated‐detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit improved only marginally when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red‐eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. The weak correlation between vital rates and temporal changes in covariates indicated that we have yet to identify the most relevant components of global change influencing the distributions of these species and, more importantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.

Patient Treatment Preferences for Relapsed/Refractory Multiple Myeloma: Are Patients Willing to Trade Off Efficacy for Tolerability?

Patient Treatment Preferences for Relapsed/Refractory Multiple Myeloma: Are Patients Willing to Trade Off Efficacy for Tolerability?

Three Methods for Anticipating and Understanding Uncertainty of Outputs from Transportation and Land Use Models

This study demonstrates three methods for uncertainty propagation in transportation and land-use models (LUMs): Local Sensitivity Analysis with Interaction (LSAI), Monte Carlo (MC), and Bayesian Melding (BM). Two case-study settings are used to illustrate how these methods work, allowing for inter-method comparisons. LSAI can provide the sign of change implied by changes in model inputs, the relative importance of changes in different inputs, and a decomposition of changes in outputs due to the impact of inputs’ individual and interactive. LSAI is limited to relatively small-size problems because its computing time rises exponentially with the number of (groups of) inputs. Moreover, LSAI obtains only point estimates, while MC and BM methods can deliver entire distributions of each output through an understanding of the uncertainty in all model inputs and parameters. MC delivers each output’s distribution and requires hundreds of samples, especially for more accurate results. Fortunately, MC methods are especially useful for high-dimensional problems because convergence rates are not a function of model dimensionality and errors depend only on sample size and input uncertainties. BM delivers posterior distributions for model outputs, using prior probability distributions and likelihoods of inputs and parameters, along with validation of/comparison to intermediate model outputs. A BM approach can be extremely expensive, in terms of computing time, since it requires several hundred model runs.

Preferences for vaccines against children’s diarrheal illness among mothers in Poland and Hungary

PurposeAlthough the World Health Organization recommends universal rotavirus immunization, uptake of the vaccine is low in Poland and Hungary, where it is not covered by the National Immunization Program. This study aimed to quantify mothers’ preferences for vaccines preventing children’s diarrheal illness and to examine whether willingness to vaccinate varies with working status. MethodsMothers of children aged <3 years living in Poland and Hungary completed an online discrete-choice experiment survey. In each of 9 choice questions, respondents indicated whether they preferred no vaccination or one of two hypothetical vaccine profiles described in terms of 6 features. Vaccine preference parameters were estimated for working and non-working mothers using a random-parameter logit model and were used to calculate the relative importance of changes in vaccine features. Results350 mothers in Poland and 350 mothers in Hungary were surveyed. Of the attributes evaluated, changes in vaccine cost were most important in both countries, followed by changes in severity of illness prevented, vaccine effectiveness, mode of administration, duration of illness prevented, and number of doses. Mothers in both countries had a strong preference for vaccination versus no vaccination, which was more pronounced among working mothers. In Poland, working mothers placed less weight on effectiveness, illness severity, and cost than non-working mothers and were more likely to rate disruptions in work, child care, and routines as important reasons to vaccinate. In Hungary, working mothers were statistically significantly less likely to opt out of vaccination than non-working mothers. Preference for vaccination itself, relative to improving vaccine effectiveness (from 50% to 90% effective), was 7 times greater among working than among non-working mothers in Poland but was not considerably different between working and non-working mothers in Hungary. ConclusionsPolish and Hungarian working mothers are more likely to vaccinate children against diarrheal illness than non-working mothers.

Silvopastoral systems of the Chaco forests: Effects of trees on grass growth

The area devoted to Silvopastoral systems is increasing worldwide due to its complementary production of beef and wood. Understanding the competition between trees and grasses is critical to identify potential trade-offs in plant production. This article had three objectives: (1) to estimate the seasonal variation of gatton panic (Megathyrsus maximus) productivity and quality in two sites with different annual rainfall, (2) to analyse the effects of tree shadow (“guayacán”, Caesalpinia paraguariensis) on gatton panic above ground primary production (ANPP), and 3) to determine the relative importance of changes in radiation use efficiency (RUE) and incoming radiation (PARi), in defining grass ANPP under trees or exposed to full sunlight. Tree presence reduced gatton panic ANPP by nearly 50%, mainly throughout a reduction in APAR. APAR decrease was not compensated by the RUE increase observed in the wet site and it was exacerbated by a decrease in RUE in the dry site. The decrease in APAR under trees was better explained rather by a decrease in PARi than by the fraction of intercepted PAR. A small increase in shoot grass digestibility was observed under the tree canopy.

Pain catastrophizing, activity engagement and pain willingness as predictors of the benefits of multidisciplinary cognitive behaviorally-based chronic pain treatment.

Pain catastrophizing and pain acceptance have been shown to be associated with improvements after participation in cognitive behaviorally-based treatment (CBT) for chronic pain. However, it is not yet clear how important each of these factors is relative to the other. Furthermore, it is also not clear if multidisciplinary pain treatment has the same impact on the two primary dimensions of pain acceptance (activity engagement and pain willingness), and whether their role in explaining treatment outcome differs as a function of the outcomes under study. The aim of this study was to examine the relative importance of changes in pain catastrophizing, activity engagement and pain willingness as predictors of the benefits of a multidisciplinary CBT for chronic pain. 186 adults with chronic pain participated. Pain catastrophizing and activity engagement, but not pain willingness, were significantly associated with treatment outcome. Moreover, each one evidenced different patterns of associations with outcomes. Specifically, while changes in both were associated with improvements in depressive symptoms, only catastrophizing was associated with improvements in pain intensity and only activity engagement was associated with improvements in pain-related disability.

PREFERENCES OF PATIENTS WITH MULTIPLE SCLEROSIS FOR ATTRIBUTES OF INJECTABLE MULTIPLE SCLEROSIS TREATMENTS IN THE UNITED KINGDOM AND FRANCE.

Adherence to injectable disease-modifying treatments in patients with multiple sclerosis (MS) impacts outcomes and can be influenced by perceptions of treatment efficacy, side effects, injection frequency, and the duration of injection. This study aimed to quantify preferences for selected attributes of injectable treatments among individuals with MS in the United Kingdom and France. Respondents with a self-reported diagnosis of MS completed an online discrete-choice-experiment survey, consisting of a series of treatment-choice questions. Each choice question presented two hypothetical treatments, each with six attributes (years until disability progression, relapses in the next 4 years, injection time, injection frequency, flu-like symptoms (FLS), and injection-site reactions), each with various levels. Mixed-logit regression analysis was used to estimate preference weights for attribute levels and to calculate the relative importance of changes in treatment attributes (vertical distance between preference weights). Minimum acceptable efficacy estimates indicate improvement in efficacy that respondents would require in exchange for worsening injection frequency and FLS. In both countries, 100 respondents completed the survey. In the United Kingdom and France, respectively, improving the time until disability progression from 2 to 4 years, reducing injection frequency from "daily" to "every 2 weeks", and reducing FLS from 3 days after every injection to none had a relative importance of 2.9 and 2.6, 3.0 and 3.5, and 2.5 and 3.1. Given the ranges included in the study, changes in these attributes were more important than most changes in other attributes assessed. Reductions in the injection frequency of MS treatments and FLS can be as important to patients as improvements in treatment efficacy.

Mortgage Modifications after the Great Recession: New Evidence and Implications for Policy

In the aftermath of the Great Recession, various mortgage modification programs were introduced to help homeowners struggling to make their monthly mortgage payments remain in their homes. We use mortgage data at the individual borrower level, joined to credit card spending and deposit account data, to investigate the relative importance of changes in monthly mortgage payments and long-term mortgage debt on default and consumption. We first quantify the variation in payment reduction offered by these modification programs and then use the variation in payment and principal reduction experienced by program recipients to estimate the impact of payment and principal reduction on default and consumption. First, we find that payment reduction for borrowers with similar payment burdens varied by two to three times across different modification programs. Borrowers with a high mortgage payment to- income (PTI) ratio received more than twice the payment reduction from HAMP compared to the GSE program. Borrowers with a low mortgage PTI ratio received three times the payment reduction from the GSE program compared to HAMP. Second, a 10 percent mortgage payment reduction reduced default rates by 22 percent. Third, for borrowers who remained underwater, mortgage principal reduction had no effect on default. This suggests that “strategic default” was not the primary driver of default decisions for these underwater borrowers. Fourth, for borrowers who remained underwater, mortgage principal reduction had no effect on consumption. Finally, default was correlated with income loss, regardless of debt-to-income ratio or home equity. Mortgage default closely followed a substantial drop in income. This pattern held regardless of pre-modification mortgage PTI or loan-to-value ratio, suggesting that it was an income shock rather than a high payment burden or negative home equity that triggered default. These findings suggest that mortgage modification programs that are designed to target substantial payment reduction will be most effective at reducing mortgage default rates. Modification programs designed to reach affordability targets based on debt-to-income measures without regard to payment reduction or target a specific LTV ratio while leaving borrowers underwater may be less effective at reducing defaults. Furthermore, policies that help borrowers establish and maintain a suitable cash buffer that can be used to offset an income shock could be an effective tool to prevent mortgage default. Both high and low mortgage PTI borrowers experienced a similar income drop just prior to default, suggesting that even among those borrowers with “unaffordable” mortgages, it was a drop in income rather than a high level of payment burden that triggered default.