Enhanced Data Collection Research Articles

Deep brain stimulation has state-dependent effects on motor connectivity in Parkinson's disease.

Subthalamic nucleus deep brain stimulation is an effective treatment for advanced Parkinson's disease; however, its therapeutic mechanism is unclear. Previous modelling of functional MRI data has suggested that deep brain stimulation has modulatory effects on a number of basal ganglia pathways. This work uses an enhanced data collection protocol to collect rare functional MRI data in patients with subthalamic nucleus deep brain stimulation. Eleven patients with Parkinson's disease and subthalamic nucleus deep brain stimulation underwent functional MRI at rest and during a movement task; once with active deep brain stimulation, and once with deep brain stimulation switched off. Dynamic causal modelling and Bayesian model selection were first used to compare a series of plausible biophysical models of the cortico-basal ganglia circuit that could explain the functional MRI activity at rest in an attempt to reproduce and extend the findings from our previous work. General linear modelling of the movement task functional MRI data revealed deep brain stimulation-associated signal increases in the primary motor and cerebellar cortices. Given the significance of the cerebellum in voluntary movement, we then built a more complete model of the motor system by including cerebellar-basal ganglia interactions, and compared the modulatory effects deep brain stimulation had on different circuit components during the movement task and again using the resting state data. Consistent with previous results from our independent cohort, model comparison found that the rest data were best explained by deep brain stimulation-induced increased (effective) connectivity of the cortico-striatal, thalamo-cortical and direct pathway and reduced coupling of subthalamic nucleus afferent and efferent connections. No changes in cerebellar connectivity were identified at rest. In contrast, during the movement task, there was functional recruitment of subcortical-cerebellar pathways, which were additionally modulated by deep brain stimulation, as well as modulation of local (intrinsic) cortical and cerebellar circuits. This work provides in vivo evidence for the modulatory effects of subthalamic nucleus deep brain stimulation on effective connectivity within the cortico-basal ganglia loops at rest, as well as further modulations in the cortico-cerebellar motor system during voluntary movement. We propose that deep brain stimulation has both behaviour-independent effects on basal ganglia connectivity, as well as behaviour-dependent modulatory effects.

Challenges facing the introduction of SMART patrols in a game reserve, western Tanzania

AbstractThe spatial monitoring and reporting tool (SMART) is being implemented in Tanzania's protected areas to help improve the efficiency of ranger patrols. Unfortunately, there has been no attempt to understand users' perspectives regarding site‐specific factors likely to affect its use. In this study, we investigated the perspectives of staff in Ugalla Game Reserve, a protected area in western Tanzania, to understand the challenges that affect the use of SMART in the reserve. The main challenges included a lack of motivation to use SMART, limited knowledge of SMART among game scouts, insufficient ranger capacity, difficulty collecting data during night patrols, limited resources for patrolling, and difficulty accessing some remote sections of Ugalla. The presence of trophy hunting company patrol teams has led Ugalla rangers to concentrate their effort in less‐patrolled areas. We recommend introducing incentives to encourage game rangers to use SMART alongside improving patrol coverage in wet seasons. Advanced and regular refresher trainings in SMART should be conducted to enhance data collection. Furthermore, game scouts should be trained and equipped to participate effectively in the SMART process. Although SMART is now becoming increasingly popular in Tanzania, understanding local factors that influence its implementation will be important to improve uptake.

College Students’ Perceptions of Influenza Vaccination and Childhood Immunizations

Background: After reviewing the literature on flu vaccinations and childhood immunizations, it was concluded that participation in these preventative measures is beneficial to health in increasing the chances of protection from specific diseases. Further studies show that not all college students receive them or plan to have their prospective children vaccinated. Purpose: The purpose of this study was to determine college students’ perception of influenza vaccination and childhood immunizations. Method: This was a quantitative, non-experimental study with a descriptive design using two open-ended questions to enhance data collection. A total of 120 college students were recruited to participate in this study. The research questions were: “What are college students’ perceptions of influenza vaccination?” and “What are college students’ perceptions of childhood immunizations?” The health belief model was used to guide the study. Results/Conclusion: Survey results showed that many students in a Christian college believe immunization is effective and plan to immunize their future children. However, a few students stated a desire to learn more about immunization.

A novel occupancy detection solution using low-power IR-FPA based wireless occupancy sensor

Significant energy savings can be achieved by operating heating, ventilation, and air conditioning control systems with indoor occupancy measurement information. This paper presents a novel plug-and-play occupancy sensing method which will enable temporal minimization of building energy consumption to meet building usage behavior without privacy concerns. The proposed wireless occupancy sensing platform is based on long-wave infra-red (LWIR) focal-plane arrays (FPAs), or thermal imagers, that detect thermal energy rather than visible light. We developed an advanced sensor package consisting of multiple thermal imagers with low-cost optical enhancements to increase field of view and increase sensitivity to occupant detection (filtering building clutter). These imagers can be coupled with radio frequency and ultrasonic-based radar to enhance data collection at key occupant zone boundaries to improve accuracy. Standard filtering and estimation techniques from the image processing and computer vision communities are introduced to overcome the accuracy issues suffered by traditional PIR based sensing, especially when occupants remain relatively still. Accurate low-level counting of individuals can be achieved with minimal impact on privacy. The proposed occupancy detection method can work as a retrofit to enable real-time understanding of the building operational state and usage behavior. Sensor data obtained from real test building zones was used to test the efficacy of the method.

Technology and community-engaged research

The purpose of this case study and discussion is to demonstrate how technology can be harnessed to enhance the performance of research teams involved in community-engaged research. Case examples from an interdisciplinary, community-engaged research project in a midsize city in the southern United States are presented to demonstrate the applicability of certain technology tools. This study examined how researchers used technology in the field to manage the project and facilitate effective communication, enhance data collection, and engage community members. Lessons learned from the field and implications for future research are discussed.

Open Source Mapping in Latin America: Collaborative Approaches in the Classroom and Field

Open source mapping platforms (such as OSM) are innovative tools that can enhance student learning and engagement in Latin American geography courses. Use of these tools can also facilitate new collaborations between students/scholars and communities responding to social and economic challenges in Latin America. In this paper we discuss the use of these tools in three different educational settings. We begin by describing the work of YouthMappers, a new international network of open source mappers that formed in 2015 with chapters in Latin America. YouthMappers can be a resource for geography departments anywhere in the world interested in developing open source mapping skills and projects. We then provide three examples from our own department of how open source mapping is used to build skills, enhance data collection, and foster international collaboration between U.S. and Latin American researchers and students. We conclude by discussing the benefits and challenges of employing these tools in the classroom and the field.

Eliminating malaria by 2040 among agricultural households in Africa: potential impact on health, labor productivity, education and gender equality.

Background: Ambitious goals have been set to eradicate malaria by the year 2040. Given the high poverty levels and the intense levels of malaria transmission in sub-Saharan Africa, suppressing malaria in rural agricultural communities in these regions will be one of the greatest challenges to achieving malaria eradication. This study has two objectives. The first is to estimate how eradicating malaria by 2040 would affect agricultural households in sub-Saharan Africa. The second is to identify where additional research is needed to develop better estimates of how eradicating malaria by 2040 would affect those households. Methods: Using agricultural census data and malaria morbidity data, we developed estimates of the number of malaria cases in 2018 among agricultural households with fewer than 10 hectares of land for 35 countries in sub-Saharan Africa. By combining these estimates with additional evidence from the literature, we analyzed how achieving malaria eradication by 2040 would affect indicators related to four Sustainable Development Goals: health, poverty, education and gender equality. Results: Our analysis found that achieving malaria eradication by 2040 would prevent approximately 841 million cases of malaria and thereby decrease the number of lost workdays among agricultural households by approximately 3.2 billion days. Eradicating malaria by 2040 would also increase the number of school days attended by children by 1.5 billion days while also reducing the number of caregiving days provided by women for malaria cases by approximately 1.1 billion days. Conclusions: This article analyzes the impact of eradicating malaria among agricultural households in sub-Saharan Africa using indicators related to four of the Sustainable Development Goals. Enhanced data collection efforts related to these four indicators would facilitate more rigorous estimates of how eradicating malaria would affect these indicators over the next two decades.

Banking in the Shadows: A Comparative Study of China and India

In recent years there has been increasing interest in the rise of shadow banking in China and India. In this paper, we aim to get a better understanding of the differences in trends and investigate the factors leading to the increase of shadow banking in these two major emerging economies. We find that financial exclusion is a common factor leading to the growth of shadow banking in both countries. While financial reform has taken place in India, financially repressive policies still prevail in China. Although several regulatory measures have been adopted in India and China, the size of the shadow banking sector in these two countries remains underestimated. Thus, streamlining and enhancing data collection is a key priority for both nations. We argue that regulation in both countries should be more activity focused (specific field in which a shadow bank is focused on) rather than sector or entity based, and it should be at par with banks. The shadow banks provide last mile connectivity to remote, distant, and ignored segments of the population not serviced by the formal financial sector. As this enhances financial inclusion, a balanced approach is required keeping in view both costs and benefits of the shadow banking system.

The practice of transfusion and fluid bolus therapy in neonates

There is increasing uncertainty over the potential benefits and harms of volume expansion in paediatric and adult critical care settings. In addition, there are increasing numbers of reports of adverse effects and association with RBC transfusions in neonates, including transfusion‐associated necrotizing enterocolitis. Preterm infants <28 weeks’ gestation in particular are likely more vulnerable to volume shifts and changes in blood pressure due to their unique physiology. This review paper will provide an overview of the current evidence base supporting the use of RBC transfusion thresholds and the use of fluid bolus therapy in neonates. We will argue that enhanced data collection and collaborations through neonatal networks, development of international consensus definitions of transfusion adverse effects and associations, as well as haemodynamic compromise in neonates, are needed to further advance research in these areas.

Reduction of greenhouse gases (GHGs) and short-lived climate pollutants (SLCPs) from municipal solid waste management (MSWM) in the Philippines: Rapid review and assessment

Municipal solid waste management (MSWM) is considered one of the serious environmental issues in the Philippines, with corresponding linkages to the climate change and Sustainable Development Goals (SDGs). However, methane (CH4) linked with indiscriminate dumping of municipal solid waste has received the much attention with regard to public health and climate change. The impacts of black carbon (BC) are less documented and understood. This paper aims to review the status of MSWM in the Philippines and makes efforts to assess the scale of short-lived climate pollutants (SLCPs), including both CH4, and BC, associated with the country’s waste sector. Utilising available national level data and following a life-cycle assessment (LCA) approach, the paper offers preliminary projections of SLCP emissions resulting from present MSWM practices. In addition, it examines model mitigation scenarios based on priority actions identified within the country’s national policy on waste management, Republic Act 2003 (RA 9003). Data analysis was conducted using an Emission Quantification Tool (EQT) developed by the Institute for Global Environmental Strategies (IGES) through its work under the Climate and Clean Air Coalition (CCAC) – Municipal Solid Waste Initiative (MSWI). Following a summary of key findings, the paper affirms that control of methane from disposal practices and of BC from waste collection and open burning requires urgent attention in the Philippines. Continued awareness raising, institutionalising regulatory policies on SLCPs, and further enhancing data collection and capacity building on waste-related BC emissions remain key priorities for the country.

Eliminating malaria by 2040 among agricultural households in Africa: potential impact on health, labor productivity, education and gender equality

Background: Ambitious goals have been set to eradicate malaria by the year 2040. Given the high poverty levels and the intense levels of malaria transmission in sub-Saharan Africa, suppressing malaria in rural agricultural communities in these regions will be one of the greatest challenges to achieving malaria eradication. This study has two objectives. The first is to estimate how eradicating malaria by 2040 would affect agricultural households in sub-Saharan Africa. The second is to identify where additional research is needed to develop better estimates of how eradicating malaria by 2040 would affect those households. Methods: Using agricultural census data and malaria morbidity data, we developed estimates of the number of malaria cases in 2018 among agricultural households with fewer than 10 hectares of land for 35 countries in sub-Saharan Africa. By combining these estimates with additional evidence from the literature, we analyzed how achieving malaria eradication by 2040 would affect indicators related to four Sustainable Development Goals: health, poverty, education and gender equality. Results: Our analysis found that achieving malaria eradication by 2040 would prevent approximately 841 million cases of malaria and thereby decrease the number of lost workdays among agricultural households by approximately 3.2 billion days. Eradicating malaria by 2040 would also increase the number of school days attended by children by 1.5 billion days while also reducing the number of caregiving days provided by women for malaria cases by approximately 1.1 billion days. Conclusions: This article analyzes the impact of eradicating malaria among agricultural households in sub-Saharan Africa using indicators related to four of the Sustainable Development Goals. Enhanced data collection efforts related to these four indicators would facilitate more rigorous estimates of how eradicating malaria would affect these indicators over the next two decades.

Machine learning and BIM visualization for maintenance issue classification and enhanced data collection

Occupant-generated work orders are recognized as a good potential data to support Facility Management (FM) activities, however they are unstructured and rarely contain the specific information engineers require to resolve the reported issues. Instead, this often requires multiple trips are often needed to identify the required trade, identify the problem and required parts/tools, and resolve. A key challenge is data quality: free-form (unstructured) text is collected that frequently lacks necessary detail for problem diagnosis. Machine Learning provides new opportunities within the FM domain to improve the quality of information collected through online work order reporting systems by automatically classifying WOs and prompting building occupants with appropriate FM team-developed questions in real time to gather the required specific information in structured form. This paper presents the development, comparison, and application of two sets of supervised machine learning models to perform this classification for WOs generated from occupant complaints. A set of ∼150,000 historical WOs was used for model development and textual classification using with various term and itemset frequency approaches was tested. Classifier prediction accuracies ranged from 46.6% to 81.3% for classification by detailed subcategory; this increased to between 68% (simple term frequency) to 90% (random forest) when the dataset only included the ten most common (accounting for 70% of all WOs) subcategories. Hierarchical classification decreased performance. An FM-BIM integration approach is finally presented using the resultant classifiers to provide facilities management teams with spatio-temporal visualization of the work order categories across a series of buildings to help prioritize and streamline operations and maintenance task assignments.

Active case-finding and enhanced data collection to identify neglected tropical diseases

ObjectiveTo strengthen public health surveillance to monitor neglected tropical diseases (NTDs) like leprosy as a control measure to avert disabilities in the Kingdom of Swaziland.IntroductionLeprosy is a chronic infectious disease caused by Mycobacterium leprae. It is a contagious disease that affects the skin, mucous membrane, and nerves causing discoloration and lumps on the skin and in severe cases disfigurement and deformities. The mode of transmission remains uncertain, but is believed that M.leprae is spread from person to person primarily as a nasal droplet infection. The incubation period for a bacterial disease generally is 5 – 7 years. Progress in the fight against leprosy has been one of the greatest public health success and in the country, was eliminated in the mid-1990s. However on the 22nd August 2017 a confirmed leprosy cases was reported by the National Referral Hospital.MethodsFollowing the confirmed case an investigation was conducted to fully understand the possible source of the case and identify further cases. The assessment was done in three parts that is, hospital visit to follow up on the index case; conducting home visits to collect data for leprosy and their contact and a file review of all clients who were once diagnosed as having leprosy.ResultsThe index case was identified and his condition is improving as he has been initiated on MDT which he will be taking for a minimum of six months. Eleven clients were visited in their homes. Their age range was 31 to 91 years but the majority were above 60 years with a median age of 70 years. There were 7 females and 4 males. . The clients presented with permanent nerve damage either from the face, upper or lower limbs. The common disabilities and deformities post treatment were sagging of face, nasal collapse, blindness and clawing of fingers and feet. Other patients had plantar-palmar ulcers and abscesses from trauma, injuries or burns sustained due to nerve damage and inadequate protection. They reported to be experiencing stigma and are being discriminated. None of the clients presented with clinical signs and symptoms suggestive of leprosy. There were 18 files that were reviewed out of 58 who are known to exist. Six of the 18 files belonged to clients who were seen during home visits. One of the clients was epidemiologically linked to the index case as they used to live together in 1994.ConclusionsThe country seem to be experiencing the re-emerging of leprosy. Since the index case is epidemiologically linked to one of the old cases this therefore confirms the incubation period of leprosy being from 15 to 20 years. There is need to strengthen leprosy prevention and control measures as well as strengthening of leprosy surveillance in the context of IDSR. There is an urgent need to raise public awareness and provide clients with protective clothing. Furthermore, there is need to strengthen the Bilharzia and Worms Control Program to incorporate leprosy as it is one of the NTDs targeted for elimination in Swaziland.

Analysis of a School Social Work Consultation Instrument: Findings from a National Exploratory Study

Multidisciplinary professional literature depicts consultation as a multidimensional method with multiple models and sets of practice tasks. Classical and contemporary school social work task analyses consistently include questions about consultation but rarely define the term. Without a definition, we do not know what the researchers are really asking and what the findings truly mean. To address this issue, a national exploratory survey was conducted to gain a better understanding of current school social work consultation practice tasks. This article presents (a) the development of a researcher-constructed consultation questionnaire, and (b) the findings of a principal component analysis used to refine and revise the items measuring six consultation models. The goal was to establish the reliability and validity of the instrument, enhance data collection on the topic, provide confidence in the interpretation of school social workers’ self-report on their current consultation practice, and expand the literature on evidence-based school social work consultation.

213 (PB-114) - Potentiality of tablet devices to enhance data collection in epidemiological research

213 (PB-114) - Potentiality of tablet devices to enhance data collection in epidemiological research

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.

Using REDCap for ambulatory assessment: Implementation in a clinical trial for smoking cessation to augment in-person data collection

ABSTRACTBackground: The use of ambulatory assessment to study behavior and physiology in daily life is becoming more common, yet barriers to implementation remain. Limitations in budget, time, and expertise may inhibit development or purchase of dedicated ambulatory assessment software. Research Electronic Data Capture (REDCap) is widely used worldwide, offering a cost-effective and accessible option for implementing research studies. Objectives: To present a step-by-step guideline on how to implement ambulatory assessment using REDCap and provide preliminary evidence of feasibility. Methods: Feasibility and acceptability data are presented for randomized participants (N ranged from 19 to 36, depending on analysis) from an ongoing 8-week smoking cessation pharmacological clinical trial (ClinicalTrials.gov Identifier: NCT02737358). Participants (N = 36; 50% female) completed up to three ambulatory assessment surveys per day, depending on the phase of the study. These included self-report and video confirmation of smoking biomarkers and medication adherence. Results: Participants completed 74.8% of morning reports (86.6% for study completers), 73.8% of videos confirming smoking biomarkers, and 70.4% of videos confirming medication adherence. Study completers reported that the REDCap assessments were easy to use, and 78.9% of participants preferred the REDCap assessments to traditional, paper measures. Conclusions: These data from a pharmacological trial suggest feasibility of remote data collection using REDCap. As REDCap functionality is continually evolving, it is likely that options for collecting ambulatory assessment data via this platform will progressively improve allowing for greater individualization of assessment scheduling for enhancing data collection in clinical trials.

Foundational insights into the estimation of whole-body metabolic rate.

Since 2013, this journal has promoted the publication of thematic reviews (Taylor in Eur J Appl Physiol 113:1634, 2013), where leading groups were invited to review the critical literature within each of several sub-topics. The current theme is historically based, and is focussed on estimating the metabolic rate in humans. This review charts the development of our understanding of those methods, from the discovery of oxygen and carbon dioxide, to the introduction of highly sophisticated modern apparatus to examine the composition of expired gas and determine respiratory minute volume. An historical timeline links the six thematic vignettes on this theme. Modern advances have greatly enhanced data collection without significant decrements in measurement accuracy. At the same time, however, conceptual errors, particularly steady-state requirements, are too often ignored. Indeed, it is recognised that we often neglect the past, leading to errors in research design, experimental observations and data interpretation, and this appears to be increasingly prevalent within the open-access literature. Accordingly, the Editorial Board, in recognition of a widening gap between our experimental foundations and contemporary research, embarked on developing a number of thematic review series, of which this series is the first. The intent of each accompanying overview is to introduce and illuminate seminal investigations that led to significant scientific or intellectual breakthroughs, and to thereby whet the appetite of readers to delve more deeply into the historical literature; for it is only when the foundations are understood that we can best understand where we are now, and in which directions we should head.

Abstract P3-17-03: Concordance of real world progression free survival (PFS) on endocrine therapy as first line treatment for metastatic breast cancer using electronic health record with proper quality control versus conventional PFS from a phase 3 trial

Abstract Background: There is growing interest to assess treatment effect with clinical endpoints that are reflective of real world clinical practice based on data systemically collected from the electronic health record (EHR). This study compared real world PFS (rwPFS) among a cohort of female patients (pts) treated with letrozole (LET) monotherapy as first-line therapy for metastatic breast cancer (MBC) in routine clinical practice to PFS using RECIST criteria from the LET alone cohort in a randomized clinical trial (PALOMA-2). Methods: For rwPFS, assessments were based on clinician notes, radiological reports, and pathological reports available in the EHR. Data were extracted from the EHR using technology-enabled abstraction; relevant documents were presented to trained human experts and data were entered into an electronic interface mimicking a case report form, with centralized management and quality controls. The patient cohort was derived from a large, longitudinal, demographically and geographically diverse EHR database of pts receiving cancer care at U.S. community-based and academic clinics (Flatiron Health); pts were all females who began treatment with LET for MBC as first-line treatment between January 1, 2011 and September 30, 2015. PFS in the clinical trial used a conventional definition based on RECIST; data were from the Pfizer clinical study PALOMA-2 database; 222 post-menopausal women in the LET alone arm met pre-specified inclusion/exclusion criteria and assessment intervals with enhanced data collection as previously detailed (Finn, NEJM 2016). All data were de-identified. Propensity score matching using a nearest neighbor algorithm with caliper=0.10 (maximum difference in propensity scores for a match) was performed to assess the consistency between the two approaches to PFS assessment. Kaplan-Meier estimates of median rwPFS/PFS are reported. Results: 107 pts met eligibility criteria from the EHR subset. Pts were younger and had less extensive disease in the PALOMA 2 cohort: The mean age was 60.6 vs 68.6 years and the proportion stage IV at diagnosis was 32.4% versus 39.3% in the LET alone cohort in PALOMA-2 compared to the EHR cohort, respectively. Propensity matching with caliper=0.10 based on age, stage at diagnosis and # of disease sites identified 79 pts from each cohort. Summary of Progression-Free Survival in Matched Data Using Propensity Score Matching Method (Kaplan-Meier estimates) rwPFSRECIST PFSSourceFlatironPALOMA-2Unmatched results N (pts)107222median PFS (months)18.714.595% Confidence Interval(14.6, 24.1)(12.9, 17.1)Matching with Caliper (=0.10) N (pts)7979median PFS (months)18.519.295% Confidence Interval(13.7, 24.1)(13.7, not estimated) Conclusion: This analysis showed concordance between rwPFS and RECIST-based PFS for LET-treated MBC matched pts using a caliper=0.10 in the first line setting. Clinically meaningful information on treatment effect could be derived from a rwPFS assessment based on EHR data abstraction that incorporates proper quality controls. Impact: These data increase confidence in the use of rwPFS as a primary outcome in real-world studies. Citation Format: Bartlett CH, Mardekian J, Cotter M, Huang X, Zhang Z, Parrinello CM, Abernethy AP, Koehler M. Concordance of real world progression free survival (PFS) on endocrine therapy as first line treatment for metastatic breast cancer using electronic health record with proper quality control versus conventional PFS from a phase 3 trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-17-03.

An online survey to enhance the understanding of car drivers route choices

Abstract The increasing application of advanced behavioral choice models, reflecting the stochasticity of individuals’ preferences and the complex nature of human decision-making process, requires enhanced data collection methods to obtain detailed data without significantly increasing the respondent burden. In this study, we present the development and deployment of a general data collection framework adapted for behavioral route choice studies. The main objectives of the proposed framework are to observe drivers’ route choices, and to identify important factors, including observable attributes and latent behavioral traits, affecting those decisions. More specifically, the survey has been designed to reveal drivers’ consideration set of route alternatives from which they pick their final choices. The detailed analysis of survey’s response behavior will help improve the framework to gather travel data even more efficiently.