Survey-based Dataset Research Articles

Deceleration of Cropland-N2O Emissions in China and Future Mitigation Potentials.

Agricultural soils are the largest anthropogenic emission source of nitrous oxide (N2O). National agricultural policies have been implemented to increase crop yield and reduce nitrogen (N) losses to the environment. However, it is difficult to effectively quantify crop-specific and regional N2O mitigation priorities driven by policies, due to lack of long-term, high-resolution crop-specific activity data, and oversimplified models. Here, we quantify the spatiotemporal changes and key drivers of crop-specific cropland-N2O emissions from China between 1980 and 2017, and future N2O mitigation potentials, using a linear mixed-effect model and survey-based data set of agricultural management measures. Cropland-N2O emissions from China tripled from 102.5 to 315.0 Gg N yr-1 between 1980 and 2017, and decelerated since 1998 mainly driven by country-wide deceleration and decrease in N rate and the changes in sowing structure. About 63% of N2O emissions could be reduced in 2050, primarily in the North China Plain and Northeast China Plain; 83% of which is from the production of maize (33%), vegetables (27%), and fruits (23%). The deceleration of N2O emissions highlights that policy interventions and agronomy practices (i.e., optimizing N rate and sowing structure) are potential pathways for further ambitious N2O mitigation in China and other developing countries.

Stigma May Exacerbate Disproportionately Low Guideline-Concordant Treatment Rates for Patients With Advanced-Stage Lung Cancer in the United States

Stigma May Exacerbate Disproportionately Low Guideline-Concordant Treatment Rates for Patients With Advanced-Stage Lung Cancer in the United States

Participation dynamics in multiple-peril agricultural insurance: Insights from India

Multiple-peril agricultural insurance, although operational in many developing countries, evokes mixed responses among smallholder farmers. In this context, we analyse the farmer-specific characteristics that are most amenable for participation in India's revamped federal agricultural insurance program. A sequential logit model is applied to a primary survey-based dataset of 1332 farmers in order to examine the factors influencing various transitions across categories. Age, female as gender and previous insurance experiences turn out to positively influence participation. Engagement in non-farm occupation and higher access to irrigation reduce the likelihood of participation. In the event that the insurance product is delinked from state supported farm credit, the more educated farmers want to move out while female farmers prefer to stay. These results offer important policy insights amidst the persistent efforts to establish a self-sustaining market for agricultural insurance in developing countries.

Data Resource Profile: The Manitoba Multigenerational Cohort.

Families are important components of society; given their shared genetic and social environments, studying families can provide critical insight into health and social outcomes within family members and across generations. Few places in the world have high-quality linkages within families at a population level; one such location is Manitoba, Canada. The Manitoba Multigenerational Cohort (MMC) has been developed to facilitate health and social research using family-based designs. The MMC is derived from the Manitoba Health Insurance Registry (‘the Registry’)—a population-based registry of all individuals registered with Manitoba Health and Seniors Care (MHSC).1 The Registry is updated at the Manitoba Centre for Health Policy (MCHP) twice a year and is integrated with historical registry data to create a longitudinal population-based registry. Over 80 administrative and survey-based data sets are linkable at the individual level; these data sets make up the Manitoba Population Research Data Repository (‘ the Repository’) and are housed in a secure environment at the MCHP.

Decoupling between ammonia emission and crop production in China due to policy interventions.

Cropland ammonia (NH3 ) emission is a critical driver triggering haze pollution. Many agricultural policies were enforced in past four decades to improve nitrogen (N) use efficiency while maintaining crop yield. Inadvertent reductions of NH3 emissions, which may be induced by such policies, are not well evaluated. Here, we quantify the China's cropland-NH3 emission change from 1980 to 2050 and its response to policy interventions, using a data-driven model and a survey-based dataset of the fertilization scheme. Cropland-NH3 emission in China doubled from 1.93 to 4.02TgNH3 -N in period 1980-1996, and then decreased to 3.50TgNH3 -N in 2017. The prevalence of four agricultural policies may avoid ~3.0Tg NH3 -N in 2017, mainly located in highly fertilized areas. Optimization of fertilizer management and food consumption could mitigate three-quarters of NH3 emission in 2050 and lower NH3 emission intensity (emission divided by crop production) close to the European Union and the United States. Our findings provide an evidence on the decoupling of cropland-NH3 from crop production in China and suggest the need to achieve cropland-NH3 mitigation while sustaining crop yields in other developing economies.

What drives the active involvement in business angel groups? The role of angels' decision-making style, investment-specific human capital and motivations

This paper sheds light over the operations and internal structure of business angel groups (BAGs), a leading actor inside the informal venture capital industry, due to its capability to build cognitive resources and shared competencies that are eventually provided to funded ventures alongside equity capital. We develop a framework based on the role of business angels' decision-making style, human capital and motivation as major determinants of their active involvement in the many different activities performed by angel groups, either investment related activities or group management activities. Our empirical analysis relies on a novel survey-based dataset containing qualitative and quantitative information provided by the members of two large and rather homogeneous business angel groups located in France and in Italy. Results show that business angels with a control-oriented decision-making style tend to be more actively involved in key angel group activities. Human capital built through investment experience, retirement status, as well as initial motivation to join an angel group are also significant drivers of angel involvement in several key BAG activities.

Does the corporate capital structure theory apply to banks? Evidence from the field

This paper investigates the value relevance of banks’ capital structure voluntary choices, their determinants, and preference in terms of funding mix policy models, using a unique survey-based dataset gathered through a face-to-face interview structured questionnaire, conducted to a sample of 51 Portuguese banks’ CEOs (89.5% survey response rate), over the 1989-1998 period. Survey participants, elicited ownership structure managerial control, growth opportunities, reputation in banking markets, financial flexibility, information signaling, bank size, share listing, business risk, dividend policy, and debt tax-shields, as the most relevant capital structure determinants at the bank level. The supervisory and regulatory discipline was indicated as the more influential external determinants for capital structure choice. A majority of 60 percent of state-owned bank CEOs declared a preference for following pre-determined guidelines on bank funding as capital structure policy model. Almost 53 percent of the privately-owned bank CEOs revealed a significant preference for the tradeoff capital structure policy model. The pecking order and the market-timing theories received moderate to weak preference. The paper extends the literature, providing field evidence that banking capital structure choice do matter and may be explained within the framework of the conventional corporate capital structure theory.

Digital payments and consumer experience in India: a survey based empirical study

Propelled by recent policy initiatives and technological developments, India’s digital payment system is a promising success story in the making. At the same time, the data also points towards an increasing usage of cash. While aggregate country-level data can indicate overall preferences of citizens, we use a novel online survey-based dataset to understand how factors such as ‘perception’ and ‘trust’ in digital payments, and experience with online frauds, affect the payment behaviour of consumers. While demographic factors like age, gender and income are relevant factors which determine this choice, we find compelling evidence that a person’s usage of digital payment methods is influenced by her perception of these instruments, as well as her trust in the overall payments framework and banking system in general. We find that the degree to which past-experience with online fraud deters usage of digital payments varies with the purpose of the transaction.

Improved Estimates of Ammonia Emissions from Global Croplands.

Reducing ammonia (NH3) volatilization from croplands while satisfying the food demand is strategically required to mitigate haze pollution. However, the global pattern of NH3 volatilization remains uncertain, primarily because of the episodic nature of NH3 volatilization rates and the high variation of fertilization practices. Here, we improve a global estimate of crop-specific NH3 emissions at a high spatial resolution using an updated data-driven model with a survey-based dataset of the fertilization scheme. Our estimate of the globally averaged volatilization rate (12.6% ± 2.1%) is in line with previous data-driven studies (13.7 ± 3.1%) but results in one-quarter lower emissions than process-based models (16.5 ± 3.1%). The associated global emissions are estimated at 14.4 ± 2.3 Tg N, with more than 50% of the total stemming from three stable crops or 12.2% of global harvested areas. Nearly three-quarters of global cropland-NH3 emissions could be reduced by improving fertilization schemes (right rate, right type, and right placement). A small proportion (20%) of global harvested areas, primarily located in China, India, and Pakistan, accounts for 64% of abatement potentials. Our findings provide a critical reference guide for the future abatement strategy design when considering locations and crop types.

Impact of mHealth interventions for reproductive, maternal, newborn and child health and nutrition at scale: BBC Media Action and the Ananya program in Bihar, India

Background Mobile health (mHealth) tools have potential for improving the reach and quality of health information and services through community health workers in low- and middle-income countries. This study evaluates the impact of an mHealth tool implemented at scale as part of the statewide reproductive,maternal, newborn and child health and nutrition (RMNCHN) program in Bihar, India. Methods Three survey-based data sets were analysed to compare the health-related knowledge, attitudes and behaviours amongst childbearing women exposed to the Mobile Kunji and Dr. Anita mHealth tools during their visits with frontline workers compared with those who were unexposed. Results An evaluation by Mathematica (2014) revealed that exposure to Mobile Kunji and Dr. Anita recordings were associated with significantly higher odds of consuming iron-folic acid tablets (odds ratio (OR) = 2.3, 95% confidence interval (CI) = 1.8-3.1) as well as taking a set of three measures for delivery preparedness (OR = 2.8, 95% CI = 1.9-4.2) and appropriate infant complementary feeding (OR = 1.9, 95% CI = 1.0-3.5). CARE India's Community-based Household Surveys (2012-2017) demonstrated significant improvements in early breastfeeding (OR = 1.64, 95% CI = 1.5-1.78) and exclusive breastfeeding (OR = 1.46, 95% CI = 1.33-1.62) in addition to birth preparedness practices. BBC Media Action's Usage & Engagement Survey (2014) demonstrated a positive association between exposure to Mobile Kunji and Dr. Anita and exclusive breastfeeding (58% exposed vs 43% unexposed, P < 0.01) as well as maternal respondents' trust in their frontline worker. Conclusions Significant improvements in RMNCHN-related knowledge and behaviours were observed for Bihari women who were exposed to Mobile Kunji and Dr. Anita. This analysis is unique in its rigorous evaluation across multiple data sets of mHealth interventions implemented at scale. These results can help inform global understanding of how best to use mHealth tools, for whom, and in what contexts. Study registration ClinicalTrials.gov number NCT02726230.

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R2, RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were delayed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

Who Is Afraid of Biotic Threats? An Econometric Analysis of Veneto Wine Grape Farmers’ Propensity to Insure

This paper aims at understanding what affects farmers’ choices to buy insurance against biotic threats. Using a survey-based dataset with 1187 observations on Veneto wine grapes farms, we regress a probit model with endogenous variables with a maximum likelihood (ML) routine. The results corroborate the microeconomic theory according to which risk-adverse individuals are more propense to insure. In our framework, the farmers’ socioeconomic characteristics are treated as endogenous variables, which exist/are predetermined before the choice to insure (or not). This paper discusses the results in a policy perspective.

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study.

BackgroundInternet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study.ObjectiveThis study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset.MethodsThis study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets.ResultsOf 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19).ConclusionsTo our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

Do credit constraints always impede innovation? Empirical evidence from Vietnamese SMEs

ABSTRACT Intrigued by literature findings that credit constrained firms are less likely to be innovative and bearing in mind that the evidence has so far largely been from developed economies, this study ventures to explore the relationship in the case of a developing economy. Focussing on Vietnam, using a biennial survey-based dataset spanning the 2005–2013 period, with around 2,500 SMEs per round, and a mix of econometric strategies, the findings of the study shed a new light in the literature on credit constraints vis-à-vis innovation relationships: credit constraints may not always impede innovation. Implications are discussed.

Development of a daily soil moisture product for the period of 2002–2011 in Chinese mainland

Soil moisture is an essential climate variable (ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year (2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Chinese mainland was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature (TB) data into a land surface model (LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau. The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons (spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center.

Measuring youth and college student voter turnout

Young adulthood is a critical period in civic development. However, measuring electoral participation among this group generally—and the many young people who go to college in particular—is fraught with potential pitfalls stemming from a reliance on survey-based measures of voting. In this note, we compare patterns of youth turnout in two large-scale, survey-based datasets commonly used to measure voting, the Current Population Survey and the Cooperative Congressional Election Study, to two voter-file based datasets: the National Study of Learning, Voting, and Engagement (NSLVE) and a comprehensive nationwide voterfile provided by the Data Trust. We find high levels of concordance between measures in the NSLVE, Data Trust, and the CPS. However, despite linking their sample to validated voter records, the CCES does not mirror these benchmarks. We conclude by discussing the challenges and opportunities that shape the study of youth turnout.

Prescriptions for Alpha Agonists and Antipsychotics in Children and Youth with Tic Disorders: A Pharmacoepidemiologic Study

<strong>Background:</strong> Trends in the use of antipsychotics and alpha agonists for the treatment of tic disorders in Canadian children, and how closely these trends align with evidence-based guidelines on the pharmacotherapy of tic disorders, have not been explored. <strong>Methods:</strong> IQVIA’s Canadian Disease and Therapeutic Index, a survey-based data set, was used to identify prescription patterns by physicians. Respondents recorded all patient visits during a 48-hour period in each quarter of the year, including patient age, gender, drug recommendation and therapeutic indication. Recommendations for alpha agonists and antipsychotics from 2012 to 2016 were analysed for children and adolescents with tic disorders. <strong>Results:</strong> Risperidone and clonidine were the most commonly recommended medications for tic disorders over the study period, with 36,868 and 35,500 recommendations in 2016, respectively. Recommendations for clonidine increased over the study period, whereas those for risperidone decreased. Guanfacine (approved in Canada in 2013) was used less frequently than clonidine. Clonidine was more frequently recommended than antipsychotics in children younger than 6, in whom antipsychotic recommendations were uncommon. Aripiprazole was the second most commonly recommended antipsychotic for tic disorders, with 22,892 recommendations in 2016. Of the first-generation antipsychotics, pimozide was most commonly recommended (11,334 recommendations in 2016); haloperidol was infrequently recommended. <strong>Discussion:</strong> The trends observed are in line with guideline recommendations reflected in the decreasing use of risperidone, and the growing use of clonidine and guanfacine. The growing use of aripiprazole is likely due to emerging evidence from clinical trials supporting its efficacy for tics. Recommendations for pimozide and haloperidol were limited, likely due to the greater adverse effects associated with these medications.

Prescriptions for Alpha Agonists and Antipsychotics in Children and Youth with Tic Disorders: A Pharmacoepidemiologic Study.

BackgroundTrends in the use of antipsychotics and alpha agonists for the treatment of tic disorders in Canadian children, and how closely these trends align with evidence-based guidelines on the pharmacotherapy of tic disorders, have not been explored.MethodsIQVIA’s Canadian Disease and Therapeutic Index, a survey-based data set, was used to identify prescription patterns by physicians. Respondents recorded all patient visits during a 48-hour period in each quarter of the year, including patient age, gender, drug recommendation and therapeutic indication. Recommendations for alpha agonists and antipsychotics from 2012 to 2016 were analysed for children and adolescents with tic disorders.ResultsRisperidone and clonidine were the most commonly recommended medications for tic disorders over the study period, with 36,868 and 35,500 recommendations in 2016, respectively. Recommendations for clonidine increased over the study period, whereas those for risperidone decreased. Guanfacine (approved in Canada in 2013) was used less frequently than clonidine. Clonidine was more frequently recommended than antipsychotics in children younger than 6, in whom antipsychotic recommendations were uncommon. Aripiprazole was the second most commonly recommended antipsychotic for tic disorders, with 22,892 recommendations in 2016. Of the first-generation antipsychotics, pimozide was most commonly recommended (11,334 recommendations in 2016); haloperidol was infrequently recommended.DiscussionThe trends observed are in line with guideline recommendations reflected in the decreasing use of risperidone, and the growing use of clonidine and guanfacine. The growing use of aripiprazole is likely due to emerging evidence from clinical trials supporting its efficacy for tics. Recommendations for pimozide and haloperidol were limited, likely due to the greater adverse effects associated with these medications.

The Role of Hazard and Vulnerability in Modulating Economic Damages of Inland Floods in the United States Using a Survey-Based Dataset

This study investigates the trends in economic damages caused by three types of inland floods (flash flood, flood, and heavy rain) in the United States and the variations in related hazard and vulnerability indicators between 1996 and 2016. We explore the underlying mechanisms based on a survey-based dataset maintained by the National Oceanic and Atmospheric Administration (NOAA) National Weather Service. An annual average of 6518 flood occurrences was reported, which caused economic damages of 3351 million USD per year. Flash flood and flood contributed to 53% and 32% of total occurrences and was associated with a larger share of damaging events (SDE). Results show that the higher impacts by flood and flash flood on property and crop are partly attributed to the greater intensity of rainfall. In addition, flood has the highest unit cost of damages. Notably, despite an upward tendency in economic damages by flash floods, no evident change trend is observed for inland floods as a whole. Further analysis shows changes in economic damages by heavy rain and flash flood are mainly governed by the increased annual frequency and hazard intensity, but the change of trend in their vulnerability indicators (i.e., SDE and Damage Per Event (DPE)) is not obvious. Regarding floods, it was not possible to attribute the variations in economic losses to hazard and vulnerability, as no significant tendency is found except for an increasing SDE. Despite limitations of length of records, data collection, and methodology, the difference in economic impacts and the related hazard and vulnerability revealed in this study can help better target future adaptation and mitigation measures.

Psychological and Social Determinants that Influence Interest in Residential Photovoltaic (RPV)

This study aims to assess the psychological and social determinants that influence interest towards RPV through an empirical investigation of a new survey-based dataset collected in Jakarta Metro, Indonesia. The theory of planned behaviour (TPB) framework was tested using survey data from 174 non-adopters, providing recommendations of potential intervention for policy makers and RPV installers in alleviating key barriers of RPV adoption. Overall, each of TPB components; attitudes, subjective norms and perceived behavioral control have significant direct and indirect impact towards interest. Individuals perceiving RPV personally and environmentally beneficial are more interested in RPV. Perception of RPV adoption will be supported by peers also increases interest. In contrast, belief of unsuitable house decreases interest. Notably, individuals seeing RPV as a complex technology are more interested to gain information about RPV.