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The sudden deterioration of the condition of linear infrastructure networks makes road management a complex task. Knowledge of the surface condition of the pavement is a requirement in order to estimate the causes of instabilities, select the appropriate action and identify all those sections that require urgent intervention. The mobile laser scanning (MLS) technique allows for a fast and safe diagnosis, thus making it possible to plan an early intervention program quickly and cost-effectively. This paper describes a methodology implemented with a twofold purpose: (i) the optimal definition, during the design phase, of the input parameters of the MLS survey (velocity of the vehicle and acquisition rate), defined through the study of the relationship between these parameters and the density of the scanned points and, therefore, with the resolution that allows the analysis of a certain type of pavement distress; (ii) the creation of a Digital Elevation Model with a curved abscissa (DEMc), specific for the analysis of road pavements. The field surveys made and the procedure developed allowed the velocity of the MLS to be associated with the resolution of the DEMc, and thus its capability to highlight distresses at different levels of severity. The creation of the road model is semiautomatic; the height value of each single node of the grid is estimated through spatial interpolation algorithms. Starting from experimental data, a few charts were created that relate the density of the point cloud to the variation of the acquisition rate, together with the minimum resolution. Depending on the type of distress analyzed, it is possible to infer the values to be respected of the parameters. In this way, it should be possible to draw up a few guidelines about MLS surveys addressing linear infrastructures focused on the optimization of the survey design, so as to identify strategies that can maximize benefits with the same available budget.

We respond to a recent call to action for the Pregnancy Risk Assessment Monitoring System (PRAMS) to include a "core" question or validated measure on discrimination to allow for systematic assessment of the impact of racial discrimination on adverse birth outcomes among a large population-based sample in the United States. We outline activities of the CDC PRAMS project that relate to this call to action. [ABSTRACT FROM AUTHOR]

Although civilians across the globe are fleeing conflict in record numbers, the reality is that far more remain behind. In addition to traditional wars, people stay in territories governed by criminal organizations. How might individuals threatened with displacement by a criminal gang manage to resist? Drawing on intensive participant observation and interviews in marginal neighborhoods of Medellín, Colombia, I argue that the urban residents most likely to remain despite being at risk of displacement are the "well connected." Despite threats, they leverage ties to a community figure or member of the armed group to stay. I test a number of related hypotheses using an original survey and survey experiment. Unlike other work stressing that residents are trapped by scant resources or remain only by joining local associations or belligerents, my theory reveals residents' agency and neutrality as they seek safety and security in conditions of state absence. [ABSTRACT FROM AUTHOR]

Recently, the idea of a universal basic income has received unprecedented attention from policymakers, the media and the wider public. This has inspired a plethora of surveys that seek to measure the extent of public support for the policy, many of which suggest basic income is surprisingly popular. However, in a review of past surveys, with a focus on the UK and Finland, we find that overall levels of support for basic income can vary considerably. We highlight the importance of survey design and, by employing new survey data in each country, compare the levels and determinants of support for varied models of basic income. Our results point to the importance of the multi-dimensionality of basic income and the fragility of public support for the idea. The findings suggest that the ability of political actors to mobilise the public in favour of basic income will eventually depend on the precise model they wish to implement. [ABSTRACT FROM AUTHOR]

Declining telephone response rates have forced several transformations in survey methodology, including cell phone supplements, nonprobability sampling, and increased reliance on model-based inferences. At the same time, advances in statistical methods and vast amounts of new data sources suggest that new methods can combat some of these problems. We focus on one type of data source—voter registration databases—and show how they can improve inferences from political surveys. These databases allow survey methodologists to leverage political variables, such as party registration and past voting behavior, at a large scale and free of overreporting bias or endogeneity between survey responses. We develop a general process to take advantage of this data, which is illustrated through an example where we use multilevel regression and poststratification to produce vote choice estimates for the 2012 presidential election, projecting those estimates to 195 million registered voters in a postelection context. Our inferences are stable and reasonable down to demographic subgroups within small geographies and even down to the county or congressional district level. They can be used to supplement exit polls, which have become increasingly problematic and are not available in all geographies. We discuss problems, limitations, and open areas of research. [ABSTRACT FROM AUTHOR]

The uptake of predictive DNA testing in families with a hereditary disease is <50%. Current practice often relies on the proband to inform relatives about the possibility of predictive DNA testing, but not all relatives are informed adequately. To enable informed decision‐making concerning predictive DNA testing, the approach used to inform at‐risk relatives needs to be optimized. This study investigated the preferences of patients, relatives, and the general population from the Netherlands on how to inform relatives at risk of autosomal dominant diseases. Online surveys were sent to people with autosomal dominant neuro‐, onco‐, or cardiogenetic diseases and their relatives via patient organizations (n = 379), and to members of the general population via a commercial panel (n = 1,000). Attitudes of the patient and population samples generally corresponded. A majority believed that initially only first‐degree relatives should be informed, following the principles of a cascade screening approach. Most participants also thought that probands and healthcare professionals (HCPs) should be involved in informing relatives, and a large proportion believed that HCPs should contact relatives directly in cases where patients are unwilling to inform, both for untreatable and treatable conditions. Participants from the patient sample were of the opinion that HCPs should actively offer support. Our findings show that both patients and HCPs should be involved in informing at‐risk relatives of autosomal dominant diseases and suggest that relatives' 'right to know' was considered a dominant issue by the majority of participants. Further research is needed on how to increase proactive support in informing of at‐risk relatives. [ABSTRACT FROM AUTHOR]

This paper evaluates the greenhouse gas (GHG) emission impacts that result from individuals participating in carsharing organizations within North America. The authors con- ducted an online survey with members of major carsharing organizations and evaluated the change in annual household emissions (e.g., impact) of respondents that joined carsharing. The results show that a majority of households joining carsharing are increas- ing their emissions by gaining access to automobiles. However, individually, these increases are small. In contrast, the remaining households are decreasing their emissions by shedding vehicles and driving less. The collective emission reductions outweigh the collective emission increases, which implies that carsharing reduces GHG emissions as a whole. The results are reported in the form of an observed impact, which strictly evaluates the changes in emissions that physically occur, and a full impact, which also considers emissions that would have happened but were avoided due to carsharing. The mean observed impact is  −0.58 t GHG/year per household, whereas the mean full impact is −0.84 t GHG/year per household. Both means are statistically significant. We present a sensitivity analysis to evaluate the robustness of the results and find that the overall results hold across a variety of assumptions. The average observed vehicle kilometers traveled (VKT) per year was found to decline by 27%. We conclude with an evaluation of the annual aggregate impacts of carsharing based on current knowledge of the industry membership population.

While the COVID-19 crisis resulted in a vast number of new research projects springing up like mushrooms everywhere, it had severe consequences for ongoing survey research and in particular for running data collections. The Survey of Health, Ageing and Retirement in Europe (SHARE) was hit by the virus in the middle of its Wave 8 data collection, which had to be suspended in all 28 participating countries. Responding to the evolving crisis situation and taking steps to resume fieldwork was especially challenging for SHARE, since (1) the 50+ population is more severely affected by COVID-19 than younger age groups and (2) the measures taken by governments in response to the outbreak differed across the countries. Against this background, we discuss possible solutions for adaptations regarding the mode of data collection, questionnaire content, sample design, and actual fieldwork.

We show that for any n divisible by 3, almost all order-n Steiner triple systems admit a decomposition of almost all their triples into disjoint perfect matchings (that is, almost all Steiner triple systems are almost resolvable).

We propose a new method of constructing questionnaire forms in the three-form planned missing data design (PMDD). The random item allocation (RIA) procedure that we propose promises to dramatically simplify the process of implementing three-form PMDDs without compromising statistical performance. Our method is a stochastic approximation to the currently recommended approach of deterministically spreading a scale's items across the X-, A-, B-, and C-blocks when allocating the items in a three-form design. Direct empirical support for the performance of our method is only available for scales containing at least 12 items, so we also propose a modified approach for use with scales containing fewer than 12 items. We also discuss the limitations of our procedure and several nuances for researchers to consider when implementing three-form PMDDs using our method.● The RIA procedure allows researchers to implement statistically sound three-form planned missing data designs without the need for expert knowledge or results from prior statistical modeling.● The RIA procedure can be used to construct both “paper-and-pencil” questionnaires and questionnaires administered through online survey software.● The RIA procedure is a simple framework to aid in designing three-form PMDDs; implementing the RIA method does not require any specialized software or technical expertise.

The Bayesian truth serum (BTS) is a survey scoring method that creates truth-telling incentives for respondents answering multiple-choice questions about intrinsically private matters, such as opinions, tastes, and behavior. The authors test BTS in several studies, primarily using recognition questionnaires that present items such as brand names and scientific terms. One-third of the items were nonexistent foils. The BTS mechanism, which mathematically rewards 'surprisingly common' answers, both rewarded truth telling, by heavily penalizing foil recognition, and induced truth telling, in that participants who were paid according to their BTS scores claimed to recognize fewer foils than control groups, even when given competing incentives to exaggerate. Survey takers who received BTS-based payments without explanation became less likely to recognize foils as they progressed through the survey, suggesting that they learned to respond to BTS incentives despite the absence of guidance. The mechanism also outperformed the solemn oath, a competing truth-inducement mechanism. Finally, when applied to judgments about contributing to a public good, BTS eliminated the bias common in contingent valuation elicitations. [ABSTRACT FROM AUTHOR]

Abstract Agencies responsible for recovering populations of iconic mammals may exaggerate population trends without adequate scientific evidence. Recently, such populations were termed as “political populations” in the conservation literature. We surmise such cases are manifested when agencies are pressured to estimate population parameters at large spatial scales for elusive species. For example, India's tiger conservation agencies depend on an extrapolation method using index‐calibration models for estimating population size. A recent study demonstrated mathematically the unreliability of this approach in practical situations. However, it continues to be applied by official agencies in Asia and promoted further by global organizations working on tiger conservation. In this article, we aim to: (a) discuss the ecological oddities in the results of India's national tiger surveys, (b) contrast these survey approaches to known statistical approaches for large scale wildlife abundance estimation, (c) demystify the mathematics underlying the problems with the survey methodology, and (d) substantiate these arguments with results from India's national tiger survey of 2014. Our analyses show that the predictions of tiger abundance reported by the 2014 survey, and consequently on tiger population trends, are misleading because of the presence of high sampling‐based overdispersion and parameter covariance due to unexplained heterogeneity in detection probabilities. We plead for designing monitoring programs to answer clearly defined scientific or management questions rather than attempt to meet extraneous social or funding related expectations.

Objective: To design and validate a brief set of measures identifying staff and work areas exhibiting low levels of resilience within healthcare organizations. Data sources/Study design: Primary data were gathered via survey administration between April and August of 2016 from 33,622 respondents across 123 facilities. These surveys included pilot items designed to measure resilience and were administered to all employees alongside employee engagement surveys. Data collection/Extraction methods: Following the data collection period for the pilot survey, data from all organizations were integrated into a single analytical dataset. Factor analyses were used to determine the underlying constructs of healthcare worker resilience. Cronbach's alpha and correlation analyses tested the internal consistency and validity of the instrument. Principal findings: A brief set consisting of eight items was identified as a psychometrically validated measure of resilience. This measure consists of two subscales, Activation and Decompression. These measures exist independent of employee engagement, indicating an empirical distinction between the two concepts. Resilience was found to predict 38% of variance in engagement scores. Conclusions: An eight-item instrument can accurately measure resilience to identify burnout risk and serve as a predictor of other workforce outcomes such as engagement.

The randomized response (RR) technique was developed to improve the validity of measures assessing attitudes, behaviors, and attributes threatened by social desirability bias. The RR removes any direct link between individual responses and the sensitive attribute to maximize the anonymity of respondents and, in turn, to elicit more honest responding. Since multivariate analyses are no longer feasible using standard methods, we present the R package RRreg that allows for multivariate analyses of RR data in a user-friendly way. We show how to compute bivariate correlations, how to predict an RR variable in an adapted logistic regression framework (with or without random effects), and how to use RR predictors in a modified linear regression. In addition, the package allows for power analysis and robustness simulations. To facilitate the application of these methods, we illustrate the benefits of multivariate methods for RR variables using an empirical example.

The excellence of a Sudanese universities and academic staff member can be effectively classified by systematic and objective design criteria, which participates in developing the learning outcomes in Sudan. In the first phase of this study, we reviewed the literatures, determined and defined the suitable quantitative and qualitative criteria and then designed & exploited pairwise comparison and evaluation forms through a survey to get experts opinions/preference on the evaluation criteria that are used to measure the universities and academic staff performance. This paper presents a fuzzy logic computational model based on this survey to measure and classify the performance of Sudanese universities and academic staff, which includes computation of criteria weights and overall evaluation of Sudanese universities and academic staff using AHP and TOPSIS techniques.

Introduction: In low- and middle-income countries (LMICs), household survey data are a main source of information for planning, evaluation, and decision-making. Standard surveys are based on censuses, however, for many LMICs it has been more than 10 years since their last census and they face high urban growth rates. Over the last decade, survey designers have begun to use modelled gridded population estimates as sample frames. We summarize the state of the emerging field of gridded population survey sampling, focussing on LMICs. Methods: We performed a systematic scoping review in Scopus of specific gridded population datasets and "population" or "household" "survey" reports, and solicited additional published and unpublished sources from colleagues. Results: We identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, some survey teams interviewed all households in each cluster or segment, and others sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation. Conclusions: For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings. [ABSTRACT FROM AUTHOR]

Interior Alaska, USA, is the least‐studied region in Alaska for breeding shorebirds because of challenging accessibility and expectations of low densities and abundances. We estimated lowland and upland shorebird population sizes on 370,420 ha of military lands in interior Alaska boreal forest from May–July 2016 and 2017. We modified the Program for Regional and International Shorebird Monitoring (PRISM) protocol used elsewhere in Alaska and incorporated a probability‐based sampling design and dependent double‐observer methods. We pooled all lowland shorebird and all upland shorebird observations and estimated abundance using Huggins closed captures models in Program MARK. Estimated abundances of all lowland and upland shorebirds were 42,239 ± 13,431 (SE) and 3,523 ± 494, respectively. The survey area is important for shorebirds in Alaska. We estimate that military lands in interior Alaska support 45,762 ± 13,925 shorebirds, including 7 species of conservation concern. Higher abundance of lowland shorebirds was best explained by lower elevation, lower percent scrub canopy, and higher percent water on plots. Higher abundance of upland shorebirds was best explained by higher elevation and increased distance to wetland. Our modified Arctic PRISM protocol was effective for surveys in the boreal forest and we recommend continued use of method modifications for future shorebird surveys in boreal forests. Identifying baseline abundances of shorebirds using interior Alaska is an important step in monitoring distributional shifts and potential future population declines. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society. [ABSTRACT FROM AUTHOR]

For more than three decades, declining response rates have been of concern to both survey methodologists and practitioners. Still, international comparative studies have been scarce. In one of the first international trend analyses for the period 1980-1997, De Leeuw and De Heer (2002) describe that response rates declined over the years and that countries differed in response rates and nonresponse trends. In this article, we continued where De Leeuw and De Heer (2002) stopped, and present trend data for the next period 1998-2015 from National Statistical Institutes. When we looked at trends over time in this new data set, we found that response rates are still declining over the years. Furthermore, nonresponse trends do differ over countries, but not over surveys. Some countries show a steeper decline in response than others, but all types of surveys show the same downward trend. The differences in (non)response trends over countries can be partly explained by differences in survey design between the countries. Finally, for some countries cost indicators were available, these showed that costs increased over the years and are negatively correlated with noncontact rates. [ABSTRACT FROM AUTHOR]

Bananas and plantains provide food and income for more than 50 million smallholder farmers in East and Central African (ECA) countries. However, banana productivity generally achieves less than optimal yield potential (<30%) in most regions, including Uganda. Numerous studies have been undertaken to identify the key challenges that smallholder banana growers face at different stages of the banana value chain, with one of the main constraints being a lack of policy-relevant agricultural data. The World Bank (WB) initiated a methodological survey design aimed at identifying the distribution of banana varieties across a number of key Ugandan growing regions, at the individual household scale. To achieve this outcome a number of approaches including ground-based surveys, DNA tissue collection of selected banana plants and remote sensing were evaluated. For the remote sensing component, the set objectives were to develop statistical models from the hyperspectral reflectance properties of individual leaves that could differentiate typical ECA banana varieties, as well as their parentage (usage). The study also explored the potential of extrapolating the ground-based hyperspectral measures to high-resolution WorldView-3 (WV3) satellite imagery, therefore creating the potential of mapping the distribution of banana varieties at a regional scale. The DNA testing of 43 banana varieties propagated at the National Banana Research Program site at National Agricultural Research Organization (NARO) research station in Kampala, Uganda, identified 12 genetically different varieties. A canonical powered partial least square (CPPLS) model developed from hyperspectral reflectance properties of the sampled banana leaves successfully differentiated BLU, BOG, GON, GRO and KAY genotypes. The Random Forest (RF) algorithm was also evaluated to determine if spectral bands coinciding with those provided by WV3 data could segregate banana varieties. The results suggested that this was achievable and as such presents an opportunity to extrapolate the hyperspectral classifications to broader areas of land. The ability to spectrally differentiate these five genotypes has merit as they are not typical east African varieties. As such, identifying the distribution and density of these varieties across Uganda provides vital information to the banana breeders of NARO of where their new varieties are being disseminated too, data that has been previously difficult to obtain. Although the results from this pilot study indicated that not all banana varieties could be spectrally differentiated, the methodology developed and the positive results that were achieved do present remote sensing as a complimentary technology to the ongoing surveying of banana and other crop types grown within Ugandan household farming systems. [ABSTRACT FROM AUTHOR]

In the United States the number of health systems that own practices or hospitals have increased in number and complexity leading to interest in assessing the relationship between health organization factors and health outcomes. However, the existence of multiple types of organizations combined with the nesting of some hospitals and practices within health systems and the nesting of some health systems within larger health systems generates numerous analytic objectives and complicates the construction of optimal survey designs. An objective function that explicitly weighs all objectives is theoretically appealing but becomes unwieldy and increasingly ad hoc as the number of objectives increases. To overcome this problem, we develop an alternative approach based on constraining the sampling design to satisfy desired statistical properties. For example, to support evaluations of the comparative importance of factors measured in different surveys on health system performance, a constraint that requires at least one organization of each type (corporate owner, hospital, practice) to be sampled whenever any component of a system is sampled may be enforced. Multiple such constraints define a nonlinear system of equations that "couples" the survey sampling designs whose solution yields the sample inclusion probabilities for each organization in each survey. A Monte Carlo algorithm is developed to solve the simultaneous system of equations to determine the sampling probabilities and extract the samples for each survey. We illustrate the new sampling methodology by developing the constraints and solving the ensuing systems of equations to obtain the sampling design for the National Surveys of United States Health Care Systems, Hospitals and Practices. We illustrate the virtues of "coupled sampling" by comparing the proportion of eligible systems for whom the corporate owner and both a hospital and a practice that are expected to be sampled to that expected under alternative sampling designs. Comparative and descriptive analyses that illustrate features of the sampling design are also presented. [ABSTRACT FROM AUTHOR]

Effective environmental management hinges on efficient and targeted monitoring, which in turn should adapt to increasing disturbance regimes that now characterize most ecosystems. Habitats and biodiversity of Australia's Great Barrier Reef (GBR), the world's largest coral reef ecosystem, are in declining condition, prompting a review of the effectiveness of existing coral monitoring programs. Applying a regional model of coral cover (i.e., the most widely used proxy for coral reef condition globally) within major benthic communities, we assess the representation and complementarity of existing long‐term coral reef monitoring programs on the GBR. We show that existing monitoring has captured up to 45% of the environmental diversity on the GBR, while some geographic areas (including major hotspots of cyclone activity over the last 30 yr) have remained unmonitored. Further, we identified complementary groups of reefs characterized by similar benthic community composition and similar coral cover trajectories since 1996. The mosaic of their distribution across the GBR reflects spatial variation in the cumulative impact of multiple acute disturbances, as well as spatial gradients in coral recovery potential. Representation and complementarity, in combination with other performance assessment criteria, can inform the cost‐effective design and stratification of future surveys. Based on these results, we formulate recommendations to assist with the design of future long‐term coral reef monitoring programs. [ABSTRACT FROM AUTHOR]

There is an increasing number of shared decision-making (SDM) interventions in paediatrics. However, there is little consensus as to the best instruments to assess the feasibility and impact of these interventions. This narrative review aims to answer: (1) what feasibility, knowledge and decision-making instruments have been used to assess paediatric SDM interventions and (2) what are the psychometric properties of used decision-making instruments, guided by the 'consensus-based standards for the selection of health measurement instrument' criteria. We conducted a review of the peer-reviewed literature. We identified 23 studies that evaluated a paediatric intervention to facilitate SDM for a specific health decision. Eighteen studies assessed intervention feasibility, with a wide variability in assessment between studies. Twelve studies assessed objective knowledge, and four studies assessed subjective knowledge with all but one study aggregating correct responses. We identified nine decision-making instruments that had been assessed psychometrically, although few had been thoroughly evaluated. The Decisional Conflict Scale was the most commonly-used instrument and the only instrument evaluated in paediatrics. Our study revealed a lack of consistency in the instruments used to evaluate decision-making interventions in paediatrics, making it difficult to compare interventions. We provide several recommendations for researchers to improve the assessment of SDM interventions in paediatrics. [ABSTRACT FROM AUTHOR]

The Office for Students’ (OfS) aims are clear that it wants to increase robust evidence to understand the impact of outreach activities. There are different mechanisms to collate this evidence which outreach departments can use. To support the collection of robust evidence, this paper outlines the development of Students’ Intentions towards University (SITU), a survey that practitioners can use as part of evaluating outreach activities such as ad hoc events or intensive interventions. This paper outlines the four stages that were undertaken to develop SITU to ensure a reliable and valid measure was constructed. At each stage, young people (aged 13 to 18) were consulted to ensure the measure was fit for purpose. The final survey comprises 15 items and is a quick, easy-to-administer survey that practitioners can use confidently. It is proposed that the survey will provide a valid data-collection tool to measure the outcome of outreach activities and the paper will be used as a guide for outreach departments to construct their own measures. Further research is required to test the application of the measure. [ABSTRACT FROM AUTHOR]

In 2014, many innovations were introduced in the Italian Household Budget Survey (HBS) in response to changes in European recommendations and purchasing behaviours and to an increased demand for information in the context of social and economic research. New instruments and techniques have been introduced, together with more accurate methodologies, with the aim of improving the survey, by both reducing the bias and variance of survey estimates and supplying estimation for additional subpopulations and variables. Given the parallel conduction of the former and new HBS in 2013, it has been possible to evaluate the effects of the abovementioned changes on consumption expenditure and inequality estimates and to compare the sample representativeness of selected subpopulations in both surveys. [ABSTRACT FROM AUTHOR]

Motivated by recent failures of polling to estimate populist party support, we propose and analyze two methods for asking sensitive multiple-choice questions where the respondent retains some privacy and therefore might answer more truthfully. The first method consists of asking for the true choice along with a choice picked at random. The other method presents a list of choices and asks whether the preferred one is on the list or not. Different respondents are shown different lists. The methods are easy to explain, which makes it likely that the respondent understands how her privacy is protected and may thus entice her to participate in the survey and answer truthfully. The methods are also easy to implement and scale up. [ABSTRACT FROM AUTHOR]

In 2012 Germany's Federal Ministry of Transport and Digital Infrastructure (BMVI) initiated several projects in preparation of the new Federal Transport Infrastructure Plan (BVWP) 2030. This included an update of the general methodology and in particular of its cost–benefit analysis which is used to evaluate the effects of hundreds of German infrastructure projects under study. As part of the work the first official values of time (VOT) and values of reliability (VOR) for personal and business travel for Germany derived from a stated preference survey were estimated. From May 2012 until January 2013 nationwide data of more than 3000 participants was collected in a combined two-stage revealed and stated preference survey. This paper discusses the survey design, reports experience of the field phase and analyses the response behaviour of the sample. The stated choice experiments address mode, route, time of departure, workplace and residential location choice. The complex multi-attribute experiments of different types cover various aspects of short and long-term travel choice attributes which the respondent has to take into consideration during his decision process. Furthermore overlapping variables of the stated and revealed preference experiments enabled a joint estimation of the whole data for deriving the VOTs and VORs. Additionally numerous socio-demographic and attitudinal questions plus the large sample size for business and non-business trips make it a unique dataset offering various aspects of travel behaviour and their valuations to explore. [ABSTRACT FROM AUTHOR]

This paper reviews the process that led to the development of a national survey instrument used to gather over 20,000 observations across Canada. This survey captured aspects of household preferences and behavioural intentions towards electric vehicles through a choice experiment and a comprehensive suite of attitudinal questions. Background information on demographics, residential location and context, vehicle ownership and purchase plans, and travel patterns among other aspects were also collected. Important survey design decisions are examined that include: the choice and implications of using a survey panel, screening criteria for the sample, conceptualization of the observational unit for the sample, critical aspects relating to the choice experiment, and tactics employed to manage and measure survey cognitive burden. Novel aspects associated with the survey design are discussed in this paper and these have enabled new research works on the implications of vehicle body type on choice of powertrain and insights into spatial variation in electric vehicle preferences. Results and insights discussed are seen as relevant for a range of survey practitioners including those with a focus on the consumer. [ABSTRACT FROM AUTHOR]

Offshore wind farms often co-occur with biodiverse marine ecosystems with high ecological, economic, and cultural value. Yet there are many uncertainties about how wind farms affect marine organisms and their environment. The before–after–control–impact (BACI) design, an approach that compares an impact location with an unaffected control both before and after the intervention, is the most common method used to study how offshore wind farms affect finfish. Unfortunately, this design has several methodological limitations that undermine its ability to detect effects in these studies. An alternative approach, the before–after-gradient (BAG) design, would sample along a gradient with increasing distance from the turbines both before and after the intervention, and could overcome many of the limitations of BACI. The BAG design would eliminate the difficult task of finding a suitable control, allow for the assessment of the spatial scale and extent of wind farm effects, and improve statistical power by incorporating distance as an independent variable in analytical models rather than relegating it to the error term. This article explores the strengths and weaknesses of the BACI and BAG designs in the context of offshore wind development and suggests an approach to incorporating the BAG design into existing fisheries surveys and a regional monitoring framework. [ABSTRACT FROM AUTHOR]

Although researchers have directed scholars toward investigating the effectiveness of the nonwork personal time of athletic trainers (ATs), no one has characterized the occupational recovery experiences of ATs. To examine the reliability and validity of the Recovery Experience Questionnaire (REQ) for use in AT populations. Cross-sectional study. Web-based survey. A total of 144 ATs (71 men, 73 women) working in a variety of National Collegiate Athletic Association sports across all levels of competition. The REQ was administered to assess the AT recovery experience. Preliminary evidence emerged for the reliability (ω = 0.80–0.90) and validity of the REQ for use in AT populations. Weak linear relationships were identified between stress and perceptions of psychological detachment (r = −0.314, P <.001), mastery (r = −0.179, P =.32), control (r = −0.284, P =.001), and relaxation (r = −0.157, P =.06). Our results support measuring and applying occupational recovery for AT stress and work-life balance. Given that occupational recovery as a construct was only weakly related to stress, it is clearly a unique and distinct variable worth considering within the work-life balance line of inquiry. [ABSTRACT FROM AUTHOR]

Background: Current healthcare professional consensus-generating methodologies work by forcing consensus, which risks corrupting original opinions and often fails to assess prior expert knowledge awareness. Experience gained with a novel method in a progressive life-long rare disease, X-linked hypophosphataemia, which addresses these risks is presented here.Methods: Four case-studies are reported, presenting a novel methodology comprised of two survey rounds. Round 1 generated a list of items from healthcare professionals in response to an open-ended research question, alongside systematic literature reviews (when appropriate). These responses were thematically coded into mutually exclusive items then used to develop a structured questionnaire (Round 2), for which each participant identified their level of agreement using Likert scales; all responses were analyzed anonymously. Item awareness, observed agreement, consensus and prompted agreement were objectively measured.Results: The free-text responses to Round 1 tested the awareness of specific items regarding establishing a European registry for X-linked Hypophosphatemia (XLH), limitations of empirical treatment for XLH (adults and paediatrics), and triggers for treatment of XLH in adults. The four cases showed different levels of item awareness, observed consensus and degrees of prompted agreement. All participants agreed or strongly agreed with statements based on the most frequent items listed in Round 1. Less frequent Round 1 items had various degrees of prompted agreement consensus; some did not reach the consensus threshold of >50% participant agreement.Conclusions: Observed proportional group awareness and consensus is quicker than the Delphi technique and its variants, providing objective assessments of expert knowledge and standardized categorization of items regarding awareness, consensus and prompting. Further, it offers tailored management of each item in terms of educational need and further investigation. [ABSTRACT FROM AUTHOR]

Traditional occupancy models that record detection/non‐detection (DND) of a species typically rely on either spatial or temporal survey replication to estimate model parameters. Recording the time until a species is first encountered after starting a survey is often possible with little extra effort and such time‐to‐detection (TTD) surveys may be more efficient than pure DND surveys. Using continuous time data, TTD occupancy models can in theory estimate occupancy and detection parameters using a single TTD survey. However, the robustness and general applicability of TTD models has not been widely addressed and their effectiveness in different study systems remains unknown.We use simulations and bird data of 63 species from a field study in the Karoo region of South Africa to explicitly compare estimates of occupancy, detection and species richness between DND and TTD models under various levels of survey replication and for species with different occupancy and detection characteristics.Simulations revealed that for inconspicuous species single survey TTD models can perform better or equally as well as DND models with a higher number of replicates. This effect was attenuated in widespread species. The benefits of TTD models were more pronounced at low survey replicates and performance of the two methods converged quickly as the number of survey replicates increased. However, results from the field data showed that a single TTD survey was not adequate to reliably estimate occupancy, detection and species richness; especially in rare and inconspicuous species. Increasing the number of TTD surveys to two replicates improved the models substantially.Our results demonstrate that the general utility of TTD surveys depends on the characteristics of the species considered in the study. A single TTD survey may be sufficient in some study designs but is unlikely to be sufficient in most multi‐species field scenarios where communities are made up of species that have a wide range of detection and occupancy probabilities. TTD surveys do provide benefits, however, in that data can be used to construct detection curves which can be used to guide survey effort in the design of future studies. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effect of home-based 'educational multi-correlates', an inter-related group of factors relating to a child's home environment, on academic achievement in a primary school in Rwanda. The specific educational multi-correlates considered in this study were parental education level, parental involvement in the child's education, and family socio-economic status. The students enrolled in the study were 334 children – 167 boys and 167 girls – at a private primary school in post-genocide Rwanda. The primary instrument used to gather data was a Likert scale survey. This, along with the students' academic records and test scores, was used to answer the following research question: To what extent do specific home-based educational multi-correlates impact academic achievement based on gender within a Rwandan primary school context? The relationships between the independent home-based variables and the dependent variable of academic achievement were measured using descriptive statistics, correlations, multiple regressions, and t-tests. The results confirmed the hypothesis that gender was a relevant factor in explaining differences in the educational correlates and the students' test scores. Student gender was also found to have a significant effect on parental involvement and family socio-economic status as measured against test scores. [ABSTRACT FROM AUTHOR]

This article focuses on how principals can use parallel surveys that tap multiple perspectives to identify improvement needs, priorities, and the relevance and effectiveness of actions and strategies implemented, and ultimately use this data to support ongoing improvement. We explore the use of survey data that couples principals' self-assessment of their practice with teachers' assessment of those practices, and the value of reports that reconcile the data from these items along with a formal conversation with principals to facilitate reflective use of data. We conclude with recommendations for how to develop school surveys, how to report survey data, and how to facilitate reflective practice and school improvement actions. [ABSTRACT FROM AUTHOR]

An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper, we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Survey Design. In particular, we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey, we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens' satisfaction with their national government. [ABSTRACT FROM AUTHOR]

Conjoint analysis is a common tool for studying political preferences. The method disentangles patterns in respondents' favorability toward complex, multidimensional objects, such as candidates or policies. Most conjoints rely upon a fully randomized design to generate average marginal component effects (AMCEs). They measure the degree to which a given value of a conjoint profile feature increases, or decreases, respondents' support for the overall profile relative to a baseline, averaging across all respondents and other features. While the AMCE has a clear causal interpretation (about the effect of features), most published conjoint analyses also use AMCEs to describe levels of favorability. This often means comparing AMCEs among respondent subgroups. We show that using conditional AMCEs to describe the degree of subgroup agreement can be misleading as regression interactions are sensitive to the reference category used in the analysis. This leads to inferences about subgroup differences in preferences that have arbitrary sign, size, and significance. We demonstrate the problem using examples drawn from published articles and provide suggestions for improved reporting and interpretation using marginal means and an omnibus F-test. Given the accelerating use of these designs in political science, we offer advice for best practice in analysis and presentation of results. [ABSTRACT FROM AUTHOR]

There is growing interest in using online outsourcing platforms that are part of the "gig economy" to conduct surveys for academic research. This interest has been driven in part by the belief that compared to traditional survey data collection methods, internet-based marketplaces such as Amazon Mechanical Turk (MTurk) enable one to collect survey data cheaper and faster from a larger, more diverse participant pool. However, many have questioned whether models based on survey data from these online marketplaces are similar to models based on survey data from more traditional platforms. To investigate this research question, we used MTurk and Qualtrics (a traditional market research firm) to survey air travelers. Our results showed that MTurk and Qualtrics respondents had distinct socio-demographic characteristics, but we found no statistical evidence for different air trip characteristics. In our data, proportionately more MTurk respondents were in the younger, single, male, and lower-income categories than for Qualtrics respondents. We found that airline itinerary choice models estimated from the MTurk and Qualtrics survey data were similar, with the key difference related to price sensitivities. Although our results provide evidence that MTurk can be used for travel demand modeling applications, we offer words of caution for others planning to conduct surveys in online marketplaces, particularly for those seeking to recruit more than 1000 participants or for those targeting specific geographic areas. [ABSTRACT FROM AUTHOR]

Understanding how the value of environmental goods and services is influenced by their location relative to where people live can help identify the economically optimal spatial distribution of conservation interventions across landscapes. However, capturing these spatial relationships within the confines of a stated preference study has proved challenging. We propose and implement a novel approach to incorporating space within the design and presentation of stated preference choice experiments (CE). Using an investigation of preferences concerning land use change in Great Britain, CE scenarios are presented through individually generated maps, tailored to each respondent's home location. Each choice situation is generated in real time and is underpinned by spatially tailored experimental designs that reflect current British land uses and incorporate locational attributes relating to physical and administrative dimensions of space. To the best of our knowledge, this represents the first CE study to integrate space into both the survey design and presentation of choice tasks in this way. Presented methodology provides means for testing how presentation of spatial information influence stated preferences. We contrast our spatially explicit (mapped) approach with a commonly applied tabular CE approach finding that the former exhibits a number of desirable characteristics relative to the latter. [ABSTRACT FROM AUTHOR]

Quantitative survey findings are important in measuring health-related phenomena, including on sensitive topics such as respectful maternity care (RMC). But how well do survey results truly capture respondent experiences and opinions? Quantitative tool development and piloting often involve translating questions from other settings and assessing the mechanics of implementation, which fails to deeply explore how respondents understand survey questions and response options. To address this gap, we conducted cognitive interviews on survey questions (n = 88) adapted from validated RMC instruments used in Ethiopia, Kenya and elsewhere in India. Cognitive interviews with rural women (n = 21) in Madhya Pradesh, India involved asking the respondent the survey question, recording her response, then interviewing her about what the question and response options meant to her. We analysed the interviews to revise the tool and identify question failures, which we grouped into six areas: issues with sequencing, length and sensitivity; problematic response options; inappropriate vocabulary; temporal and spatial confusion; accessing different cognitive domains; and failure to resonate with the respondent's worldview and reality. Although women tended to provide initial answers to the survey questions, cognitive interviews revealed widespread mismatch between respondent interpretation and question intent. Likert scale response options were generally incomprehensible and questions involving hypothetical scenarios could be interpreted in unexpected ways. Many key terms and concepts from the international RMC literature did not translate well and showed low resonance with respondents, including consent and being involved in decisions about one's care. This study highlights the threat to data quality and the validity of findings when translating quantitative surveys between languages and cultures and showcases the value of cognitive interviews in identifying question failures. While survey tool revision can address many of these issues, further critical discussion is needed on the use of standardized questions to assess the same domains across contexts. [ABSTRACT FROM AUTHOR]

Many sampling techniques rely on taking measurements along a transect; an example is underwater imagery from towed platforms used for marine ecological studies. Despite transect‐based sampling being commonly used, methods to generate randomized survey designs have not hitherto been developed.We develop methods to generate random transect designs, which respect the user‐defined probability of sampling each grid cell (the cell inclusion probabilities). We show how to: (a) define transect inclusion probabilities from user‐specified cell inclusion probabilities, which allows particular environments to be sampled more often; (b) alter the cell and transect inclusion probabilities so that when transects are sampled the frequencies of sampling cells approximate the cell inclusion probabilities, and; (c) draw a spatially balanced probability sample of transects.The spatially balanced transect designs approximately maintain the cell inclusion probabilities. The greatest of the small departures occur near the extreme corners of our convex study region, which are difficult to place transects into. The proposed designs also exhibit superior spatial balance compared to the non‐balanced counterparts. We illustrate the successful application of the method to a towed‐camera survey of deep‐sea (500–2,000 m depths) seamounts off Tasmania, Australia. This was a challenging application due to the complex topology of the setting, and uneven inclusion probabilities for the property of interest – the presence of a stony coral.Our approach develops the randomization approach to transect‐based surveys, thereby ensuring that transect‐based surveys can enjoy the same benefits as random point‐based surveys. The method approximates the cell inclusion probabilities, and does so while spatially balancing the transects throughout the study area. Practitioners can access the methods through the R‐package MBHdesign, which is available from CRAN. We anticipate that it will act as a cornerstone for transect‐based ecological monitoring programmes. [ABSTRACT FROM AUTHOR]

In recent years, researchers have devoted greater attention to insufficient effort responding (IER), in which participants fail to attend to instructions, do not read item content carefully, or intentionally engage in random responding. While IER is typically considered a purely methodological concern, recent research has begun to examine whether it also has a substantive basis (e.g., personality). Here we extend the nomological network surrounding IER by examining the role of implicit aggression. In three studies, we demonstrate that higher levels of implicit aggression are indeed related to IER even after controlling for previously established correlates of IER. Furthermore, we also demonstrate that IER, as measured by the selection of illogical responses to Conditional Reasoning Tests of Aggression, can predict theoretically relevant behavioral criteria. The theoretical and practical implications of this work are discussed. [ABSTRACT FROM AUTHOR]

Science, technology and innovation have a fundamental role in the development of a society, and can be observed in the investment that countries execute in the sector. Most of these funds are channeled through public organisms by the financing of project. In Argentina, universities lead a significant assignment in the allocation and distribution of resources, so that the activities related to project management become imperative. The increasing complexity of these tasks, which usually fall on the main teachers/researchers, means extra dedication to their daily responsibilities and limits the development of other activities for which their participation is essential. Now there are no systematic studies in the country to estimate the potential increase in the availability of time dedicated to research that could be achieved through the incorporation of methodologies and management processes of R&D projects. This paper presents the design of a tool to diagnose the activities related to R&D projects management carried out by teachers/researchers in universities. Questionnaire relieves the time spent by teachers/researchers in different tasks (Teaching, Research, Community engagement, and Others) and the time taken to manage on-going projects. Finally, it is highlighted that the instrument, developed to be used in a research program, was validated with teachers/researchers who develop their activities in participating universities, which allowed modifications to arrive at its final design.

Background: Internet has been broadly employed as a facilitator for epidemiological surveys, as a way to provide a more economical and practical alternative to traditional survey modes. A current trend in survey research is to combine Web-based surveys with other survey modes by offering the participant the possibility of choosing his/her preferred response method (i.e. mixed-mode approach). However, studies have also demonstrated that the use of different survey modes may produce different responses to the same questions, posing potential challenges on the use of mixed-mode approaches.Methods: In this paper, we have implemented a statistical comparison between mixed-mode survey responses collected via mail (i.e. paper) and Web methods obtained from a cross-sectional study in non-urban areas of Denmark. Responses provided by mail and Web participants were compared in terms of: 1) the impact of reminder letters in increasing response rates; 2) differences in socio-demographic characteristics between response groups; 3) changes on the likelihood of reporting health symptoms and negative attitudes towards environmental stressors. Comparisons were mainly performed by two sample t-test, Pearson's Chi-squared test and multinomial logistic regression models.Results: Among 3104 contacted households, 1066 residents decided to participate on the study. Out of those, 971 selected to respond via mail, whereas 275 preferred the Web method. The majority of socio-demographic characteristics between these two groups of respondents were shown to be statistically different. The use of mailed surveys increased the likelihood of reporting health symptoms and negative attitudes towards environmental stressors, even after controlling for demographic characteristics. Furthermore, the use of reminder letters had a higher positive impact in increasing responses of Web surveys when compared to mail surveys.Conclusions: Our main findings suggest that the use of mail and Web surveys may produce different responses to the same questions posed to participants, but, at the same time, may reach different groups of respondents, given that the overall characteristics of both groups considerably differ. Therefore, the tradeoff between using mixed-mode survey as a way to increase response rate and obtaining undesirable measurement changes may be attentively considered in future survey studies. [ABSTRACT FROM AUTHOR]

For bumble bees and other social organisms, colonies are the functional unit of the population rather than the individual workers. Estimates of bumble bee nest density are thus critical for understanding population distribution and trends of this important pollinator group. Yet, surveys of bumble bee nests and other taxa with sessile life stages rarely account for imperfect detection. Here, we demonstrate the use of mark-recapture methods to estimate the density of bumble bee nests at multiple sites using standardized survey protocols. We detected ~ 30% of nests in a 2-h survey of each 3000 m2 plot. We determined that 4–5 visits were sufficient to estimate the total number of nests at our site with reasonable precision, equating to one-third the effort previously assumed necessary to reliably estimate nest density. Mark-recapture approaches can be used to generate unbiased estimates of density with reduced search effort, while simultaneously increasing the rate at which nests are discovered. [ABSTRACT FROM AUTHOR]

Objectives The present study analyzed whether estimates of health inequalities in old age are sensitive to the exclusion of people living in institutions and nonuse of proxy interviews. Method Pooled data from the 2004 wave (n = 1,180, aged 69–100, primarily interviewed over the phone) and the 2011 wave (n = 931, aged 76–101, primarily interviewed face-to-face) of the Swedish Panel Study of Living Conditions of the Oldest Old were used to compare absolute and relative differences in disability and mortality between people with compulsory education and people with more than compulsory education. Results Both absolute and relative health inequalities would have been underestimated in a survey that excluded institutionalized people and proxy-interviewed community dwellers. The same patterns were found in men and women and regardless of the mode of data collection (telephone or face-to-face interview). The degree of underestimation was lower in those 85 years and older than in those 69 to 84 years. Discussion A survey that only includes people who live in the community and can participate without the help of a proxy might give the impression that those with low levels of education have less extensive health disadvantages than they actually have. [ABSTRACT FROM AUTHOR]