Flexibility In Data Collection Research Articles

Direct Replication in Psychological Assessment Research

Direct Replication in Psychological Assessment Research

On the Potential for Remote Observations of Coastal Morphodynamics from Surf-Cameras

Recreational surf-cameras (surfcams) are ubiquitous along many coastlines, and yet are a largely untapped source of coastal morphodynamic observations. Surfcams offer broad spatial coverage and flexibility in data collection, but a method to remotely acquire ground control points (GCPs) and initial camera parameter approximations is necessary to better leverage this existing infrastructure to make quantitative measurements. This study examines the efficacy of remotely monitoring coastal morphodynamics from surfcams at two sites on the Atlantic coast of Florida, U.S.A., by leveraging freely available airborne lidar observations to acquire remote-GCPs and open-source web tools for camera parameter approximations, ignoring lens distortion. Intrinsic and extrinsic camera parameters are determined using a modified space resection procedure, wherein parameters are determined using iterative adjustment while fitting to remote-GCPs and initial camera parameter approximations derived from justified assumptions and Google Earth. This procedure is completed using the open-source Surf-Camera Remote Calibration Tool (SurfRCaT). The results indicate root mean squared horizontal reprojection errors at the two cameras of 3.43 m and 6.48 m. Only immobile hard structures such as piers, jetties, and boulders are suitable as remote-GCPs, and the spatial distribution of available points is a likely reason for the higher accuracy at one camera relative to the other. Additionally, lens distortion is not considered in this work. This is another important source of error and including it in the methodology is highlighted as a useful avenue for future work. Additional factors, such as initial camera parameter approximation accuracy, likely play a role as well. This work illustrates that, provided there is sufficient remote-GCP availability and small lens distortion, remote video monitoring of coastal areas with existing surfcams could provide a usable source of coastal morphodynamic observations. This is further explored with a shoreline change analysis from the higher-accuracy camera. It was found that only the largest (>6 m) magnitude shoreline changes exceed the observational uncertainty driven by shoreline mapping error and reprojection error, indicating that remotely calibrated surfcams can provide observations of seasonal or storm-driven signals.

The Search for Real-Time Impact Monitoring for Private Sector Support Programmes

An increasing consensus exists in the impact evaluation literature on using detailed theory-based evaluations to evaluate complex programmes such as private sector development (PSD) programmes. At the same time, PSD managers expect periodic and timely (so-called ‘real-time’) input from evaluators to improve programmes throughout their implementation. This article presents insights from real-time theory-based monitoring and evaluation shaped by the needs of policymakers in two Dutch PSD programmes. To learn about their experiences, we held in-depth interviews with researchers and policymakers involved in the evaluation. The interviews indicated that theory-based evaluation improved reporting on the programmes’ contribution to higher-level impact areas and credibly quantified the importance of that contribution. The insights showed too that real-time monitoring and evaluation of PSD programmes requires more flexibility in data collection and increased interaction with mid-management.

COVID-19 Impact Battery: Development and Validation.

In addition to impacting the physical health of millions of Americans, the novel-coronavirus (COVID-19) pandemic is a significant psychological stressor due to both the threat of the illness itself and the mitigation strategies used to contain the spread. To facilitate understanding of the impact of COVID-19, validated measures are needed. Using a stepwise procedure in line with best-practice measurement procedures, the current report summarizes the procedures employed to create the COVID-19 Impact Battery (CIB). Two independent samples recruited via Amazon Mechanical Turk (N = 175, N = 642) and a third community sample (N = 259) were used for reliability and validity testing. Validation procedures yielded a battery consisting of three scales assessing COVID-19 related behaviors, worry, and disability. The behaviors scale contains three subscales assessing stockpiling, cleaning, and avoidance. The worry subscale also contains three subscales assessing health, financial and catastrophic concerns. In addition, we created a short version of the battery (CIB-S) to allow for more flexibility in data collection. In summary, we have provided reliability and validity information for the CIB and CIB-S, demonstrating that these measures can facilitate evaluation of the broad impact of COVID-19 on mental health functioning.

Equity-Advancing Practices at Public Transit Agencies in the United States

Consistent with federal anti-discrimination and environmental justice law and guidance, public transportation agencies must evaluate the extent to which their decisions benefit and burden different people and groups and they must also conduct public engagement during decision-making. Assessing benefits and burdens and facilitating engagement are critically important for achieving transportation equity. In practice, quantitative analyses of plan impacts can be used to highlight and mitigate disparate benefits and burdens, but analyses are often conducted after major decisions have already been made and agencies have substantial flexibility in data collection and analysis. Public engagement can also affect equity-related outcomes, but agencies still rely heavily on public meetings and one-way information dissemination approaches that alienate potential participants. Considering the shortcomings associated with quantitative analysis and traditional public engagement as well as the open-ended nature of existing regulatory guidance, there is a need to understand the broad range of approaches that public transit agencies use to pursue equity-related goals. In this review of practice, we summarize six measures that agencies are using to advance transportation equity. Each measure is described using information gleaned from semi-structured interviews and primary source materials. We also identify challenges and shortcomings inherent in each approach using perspectives from the academic literature. The results will be useful for practitioners seeking equitable public transit systems and desiring to go beyond the standard approaches suggested by federal law and guidance.

Weakly-supervised progressive denoising with unpaired CT images.

Although low-dose CT imaging has attracted a great interest due to its reduced radiation risk to the patients, it suffers from severe and complex noise. Recent fully-supervised methods have shown impressive performances on CT denoising task. However, they require a huge amount of paired normal-dose and low-dose CT images, which is generally unavailable in real clinical practice. To address this problem, we propose a weakly-supervised denoising framework that generates paired original and noisier CT images from unpaired CT images using a physics-based noise model. Our denoising framework also includes a progressive denoising module that bypasses the challenges of mapping from low-dose to normal-dose CT images directly via progressively compensating the small noise gap. To quantitatively evaluate diagnostic image quality, we present the noise power spectrum and signal detection accuracy, which are well correlated with the visual inspection. The experimental results demonstrate that our method achieves remarkable performances, even superior to fully-supervised CT denoising with respect to the signal detectability. Moreover, our framework increases the flexibility in data collection, allowing us to utilize any unpaired data at any dose levels.

Preregistration in experimental linguistics: applications, challenges, and limitations

AbstractThe current publication system neither incentivizes publishing null results nor direct replication attempts, which biases the scientific record toward novel findings that appear to support presented hypotheses (referred to as “publication bias”). Moreover, flexibility in data collection, measurement, and analysis (referred to as “researcher degrees of freedom”) can lead to overconfident beliefs in the robustness of a statistical relationship. One way to systematically decrease publication bias and researcher degrees of freedom is preregistration. A preregistration is a time-stamped document that specifies how data is to be collected, measured, and analyzed prior to data collection. While preregistration is a powerful tool to reduce bias, it comes with certain challenges and limitations which have to be evaluated for each scientific discipline individually. This paper discusses the application, challenges and limitations of preregistration for experimental linguistic research.

EDU (5-Ethynyl-2'-Deoxyuridine)-Coupled Fluorescence-Intensity Analysis: Determining Absolute Parameters of the Cell Cycle.

The principles and practice of a methodology of cell cycle analysis that allows the estimation of the absolute length (in units of time) of all cell cycle stages (G1, S, and G2) are detailed herein. This methodology utilizes flow cytometry to take full advantage of the excellent stoichiometric properties of click chemistry. This allows detection, via azide-fluorochrome coupling, of the modified deoxynucleoside 5-ethynyl-2'-deoxyuridine (EDU) incorporated into replicated DNA through incremental pulsing times. This methodology, which we designated as EdU-Coupled Fluorescence Intensity (E-CFI) analysis, can be applied to cell types with very distinct cell cycle features, and has shown excellent agreement with established techniques of cell cycle analysis. Useful modifications to the original protocol (Pereira et al., Oncotarget, 8:40514-40,532, 2017) have been introduced to increase flexibility in data collection and facilitate data analysis.

Navigating the garden of forking paths for data exclusions in fear conditioning research.

In this report, we illustrate the considerable impact of researcher degrees of freedom with respect to exclusion of participants in paradigms with a learning element. We illustrate this empirically through case examples from human fear conditioning research, in which the exclusion of 'non-learners' and 'non-responders' is common - despite a lack of consensus on how to define these groups. We illustrate the substantial heterogeneity in exclusion criteria identified in a systematic literature search and highlight the potential problems and pitfalls of different definitions through case examples based on re-analyses of existing data sets. On the basis of these studies, we propose a consensus on evidence-based rather than idiosyncratic criteria, including clear guidelines on reporting details. Taken together, we illustrate how flexibility in data collection and analysis can be avoided, which will benefit the robustness and replicability of research findings and can be expected to be applicable to other fields of research that involve a learning element.

Describing seasonal differences in tree crown delineation using multispectral UAS data and structure from motion

ABSTRACTUnmanned Aerial Systems (UAS) have emerged as a platform capable of providing valuable data on vegetation structure, health, and productivity. The platform provides maximum temporal flexibility in data collection and customizability of spatial footprints which is important for mapping and monitoring vegetation conditions especially for high spectrally and structurally heterogeneous landscapes. In this letter, we investigate the potential improvement in structural information when using sensor payloads that include infrared bands (730–810 nm) in addition to the typical visible bands of many UAS sensor payloads. Specifically, we use derived point clouds and imagery collected from UAS-mounted sensors at a test site in Louisville, Kentucky, USA to assess whether multispectral sensors improve estimates of vegetation structure for plant greenness (leaf-on) and senescence (leaf-off) periods. Results indicate that including detailed multispectral reflectance information beyond the visible portion of the electromagnetic spectrum aids in estimating structural characteristics of woody vegetation, regardless of season. While both leaf-on and leaf-off periods result in reasonable crown height estimates, leaf-on conditions also improve radial estimates, likely due to continuous canopy surfaces. These findings advance research for remote sensing analyses assessing structural composition in heterogeneous landscapes where varying levels of vegetation structure have implications on land use and land function.

A person-centered approach to study intimacy and sexuality in residential care facility (RCF) clients with dementia: Methodological considerations and a guide to study design.

The person-centered perspective of residential care facility (RCF) residents with dementia with regard to their intimate and sexual lives is largely neglected in research. We aim to provide methodological considerations and reflections on a performed qualitative study. Recommendations and a guide to study design are provided to inform and encourage future research on the inclusion of people with dementia as participants. Methodological recommendations and reflections are described in chronological order of the procedure. Fragments of interviews are included for further illustration and clarification. Considering preparation, close involvement of clinical practice, and extensive deliberation regarding study design tended to be important. Considering procedure, investment in contacts with clinical practice and authorized representatives; an introduction meeting; person-centered inclusion and consent; profound skills in interviewing participants with dementia; and flexibility in data collection were proven of importance. Considering data analysis and study quality, including field notes and aiming at a balance between study quality and practicability to enhance study 'rigor' were found important. Including the person-centered perspective in research on intimacy and sexuality of RCF residents with dementia, is challenging and takes a flexible and creative approach. It is, however, worthwhile to close the gap in literature.

Enrolling African-American and Latino patients with asthma in comparative effectiveness research: Lessons learned from 8 patient-centered studies

African-American and Latino patients are often difficult to recruit for asthma studies. This challenge is a barrier to improving asthma care and outcomes for these populations. We sought to examine the recruitment experiences of 8 asthma comparative effectiveness studies that specifically targeted African-American and Latino patients, and identify the solutions they developed to improve recruitment. Case report methodology was used to gather and evaluate information on study design, recruitment procedures and outcomes from study protocols and annual reports, and in-depth interviews with each research team. Data were analyzed for themes, commonalities, and differences. There were 4 domains of recruitment challenges: individual participant, institutional, research team, and study intervention. Participants had competing demands for time and some did not believe they had asthma. Institutional challenges included organizational policies governing monetary incentives and staff hiring. Research team challenges included ongoing training needs of recruitment staff, and intervention designs often were unappealing to participants because of inconveniences. Teams identified a host of strategies to address these challenges, most importantly engagement of patients and other stakeholders in study design and troubleshooting, and flexibility in data collection and intervention application to meet the varied needs of patients. Asthma researchers may have greater success with recruitment by addressing uncertainty among patients about asthma diagnosis, engaging stakeholders in all aspects of study design and implementation, and maximizing flexibility of study and intervention protocols. However, even with such efforts, engagement of African-American and Latino patients in asthma research may remain low. Greater investment in research on engaging these populations in asthma research may ultimately be needed to improve their asthma care and outcomes.

Generalization Is Everything, or Is It?

1. IntroductionCase studies are a critical and even attractive research methodology 1 (Bartunek, Rynes & Ireland, 2006; Eisenhardt & Graebner, 2007; Sato, 2009). 2 However, there are sometimes questions about whether the case study method is rigorous enough as a research methodology.In addressing this question, Eisenhardt (1989) is one of the most frequently cited studies on the methodological case study fundamentals in theory construction. Yet most studies that cite Eisenhardt's method emphasize only generalizability. As a result, the potential for theory construction using the case study method has not been sufficiently investigated.2. Case Study Method in Eisenhardt (1989)According to Eisenhardt (1989), the case study is a research strategy which focuses on understanding the dynamics present within single settings. Eisenhardt (1989) focuses on the case study as a research methodology for theory construction in particular. According to Eisenhardt, theory construction consists of nine steps.a) Getting startedWhen conducting a case study, the first thing to do is to formulate the research question. This enables one to specify what kind of organization the survey should study or what data the survey should collect.b) Selecting casesThe next problem is case selection. In a case study that has the goal of theory construction, sample selection usually depends on theoretical sampling.In statistical sampling, the sample is selected randomly from a population. Theoretical sampling on the other hand reiterates previous cases and uses what amounts to an extreme example that reproduces an existing case, builds upon the theory, or corresponds to a theoretical category.c) Crafting instruments and protocolsResearch on theory construction is able to combine multiple data sources. In particular, it combines quantitative and qualitative data. The case study can therefore use both types of data.d) Entering the fieldsAn especially notable characteristic of the case study in theory construction is the overlap of data collection and data analysis.Overlap of data collection and data analysis leads to flexibility in data collection. It enables the researcher to change the data collection methodology in the course of the research when the researchers comes up with a new idea that may generate a new theory.e) Analyzing within-case dataFirst, independent analysis of various cases enables the researcher to avoid becoming overwhelmed by too much data.In addition, by analyzing individual cases before comparing the various cases, the researcher is able to detect the particular patterns of the various cases, thereby deepening his or her understanding of the cases in point and facilitating cross-case comparisons.f) Searching for cross-case patternsBias can occur in cross-case comparisons, which could lead to erroneous conclusions. There are three ways to prevent bias.The first is to separate the cases into categories and look at the similarities within each group and the differences between the groups. The second is to divide the cases into pairs for comparison, then look for differences between the cases that are similar and for similarities between the cases that appear to be different. The third is to divide the data according to the data source and try to gain insight into the particulars of the heterogeneous data.g) Shaping hypothesisThe first step in hypothesis development is clarification of constructs. This step consists of two processes: elaborating on the constructs' definitions and establishing proofs for measuring these constructs. These processes constitute a hypothesis-testing type of research, in that they are similar to formulating a construct from several metrics. However, a case study for theory construction differs in that it is the analysis itself that generates the constructs and their measurement, and that there is no way to group several metrics into one construct. …

Optimal sampling scheme for estimation of intraocular pressure diurnal curves in glaucoma trials.

Effective control of intraocular pressure (IOP) is essential for the successful management of glaucoma. IOP exhibits diurnal variation, yet continuous monitoring is impractical. To date, no clear evidence exists on the number of sampling timepoints required to characterize diurnal IOP and when those measurements should be collected. The objective of this study was to develop an optimized sampling scheme to estimate diurnal IOP and to provide sampling windows for practicality. Baseline IOP values for glaucoma patients were collected from the published literature. A population model-based meta-analysis was performed to develop a model for diurnal IOP that accounts for covariates and inter-study variability. Optimization was performed using the D-optimality criteria to determine optimal sampling times. In addition, various reduced sampling designs were tested to investigate the minimum number of sampling timepoints to precisely estimate diurnal IOP. Also, sampling windows were calculated around the final optimal sampling times to allow flexibility in data collection. The final reduced optimized model was validated by simulating and estimating 500 datasets with reduced optimal sampling times. The final baseline IOP model included type of glaucoma as a covariate. Bootstrap analysis and visual predictive check plots revealed the adequacy of the model to describe the observed IOP data. Optimization results indicated an increasing trend in bias with decreasing sampling timepoints. A reduced model with four sampling times resulted in acceptable precision (<40%). Restricting the sampling time between 8a.m. and 4p.m. underestimates the fluctuation in diurnal IOP. Sampling windows with ≥95% efficiency were calculated around the optimized sampling times. Validation results indicated acceptable precision and relative bias for model estimates in the reduced optimized model. A physiologically based mechanistic model was developed to describe the diurnal variation in baseline IOP and inter-study variability was estimated on key diurnal model parameters. Optimization of the final covariate model indicated a reduced sampling time of at least four samples should be collected at 5:45a.m., 2:15p.m., 8:00p.m., and 12:00a.m. for reliable estimation of diurnal IOP variation.

Data from Paper “False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant”

The data includes measures collected for the two experiments reported in “False-Positive Psychology” [1] where listening to a randomly assigned song made people feel younger (Study 1) or actually be younger (Study 2). These data are useful because they illustrate inflations of false positive rates due to flexibility in data collection, analysis, and reporting of results. Data are useful for educational purposes.

A Web-based Dynamic User Customized Entry System for Public Health Surveillance

Background Web browsers are widely used as an interface to collect relevant data on public health. However, systematic data collection from a web browser requires special expertise using a program technique to create an entry form in conjunction with database fields. The Dynamic User Customized Entry System (DUCES) provides the benefit of reducing the barrier of interface development via the Internet. Methods We developed an application that enables users to easily create a data entry form through a web browser. Through this system, the end user can automatically generate a data entry form without any programming. Based on the relational database architecture, this system contains two major parts: a structure model and a dynamic entry generator. Results The first part was developed to record a series setting of items relevant to the characteristics of data entry. The second part was designed to produce an entry form in reality. The aim of the DUCES project was to provide users flexibility in data collection. In addition, this system had been well-developed and conducted in a community-based integrated screening program. Conclusion The effectiveness of the system can be gauged from the impact of the population-based information convergence. An illustration of data collection using DUCES for colorectal cancer prediction was also demonstrated. The risk factors including smoking, drinking, vegetable intake, and meat intake were obtained from the system. Moreover, a positive association between low vegetable intake and colorectal cancer was assessed using the odds ratio.

Studying High-Quality Teaching in a Highly Charged Policy Environment

ContextPolicy makers have long used policy tools to influence various components of the education system. The passage of No Child Left Behind increased the federal role and the focus on student outcome measures. This change in the policy environment can affect not only teachers and teaching but researchers and research on teaching as well.PurposeThis article examines ways in which the current policy context influences teaching and explores the challenges these influences pose for research on teaching. To illustrate this potential policy impact, we focus on three core dimensions of teaching: who is the teacher, is teaching practice stable or changing, and what constitutes teaching quality.Research DesignWe draw on our High-Quality Teaching study of fourth- and fifth-grade reading and mathematics instruction. For this article, we analyzed classroom observation data, teacher logs of curriculum coverage, and focus group interviews with school personnel. We pay particular attention to changes in instruction over time and in different contexts.ConclusionsAlthough we anticipated that policy pressures might influence conceptions of teaching quality, we were surprised by the scope of these influences. Our findings indicate underreported, multiple influences on student learning due to both local and federal policies; unexpected changes in what is taught and in what kind of teaching occurs within the school day, throughout the year, and across years; and narrowing conceptions of teaching quality. Policy influences on these core dimensions challenge researchers to specify more carefully who is responsible for teaching whom, maintain flexibility in data collection, retain research participants across years, and examine alternative conceptions of quality teaching.

False-Positive Psychology

In this article, we accomplish two things. First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.

Method for assessing impacts on life support functions (LSF) related to the use of ‘fertile land’ in Life Cycle Assessment (LCA)

Degradation of soil quality is a major concern due to the scarcity of fertile land, and needs to be properly addressed in the environmental assessment of agro-forestry systems. This paper addresses the main issues arising in assessing the impacts of fertile land use on “Life Support Functions” in Life Cycle Assessment (LCA). These issues include the assessment of occupation and transformation impacts, the references against which such impacts should be measured, and the concept of natural relaxation versus backup technology for recovery from the impacts. The alternative (or reference) situation is defined using the concept of consequential LCA, which facilitates clarification of the allocation issues arising due to successive land uses. This paper presents soil organic matter (SOM) as a robust indicator for soil quality; even though it does not fully consider all aspects of soil functioning, SOM has been often recognised as the best stand-alone indicator for soil quality. Impacts on biodiversity are not included in this indicator and should be assessed in parallel. Alternative data sources for practical implementation of the method are suggested in a hierarchical way, including locally specific data sets describing changes in SOM; mechanistic models for the prediction of SOM evolution; and general data sources for simplified analyses. Thanks to its flexibility in data collection the method is applicable to any agricultural or forestry LCA to fill an important gap in Life Cycle Impact Assessment (LCIA) of land use.

Building Segment-Based Maps Without Pose Information

Most map building methods employed by mobile robots are based on the assumption that an estimate of robot poses can be obtained from odometry readings or from observing landmarks or other robots. In this paper we propose methods to build a global geometric map by integrating scans collected by laser range scanners without using any knowledge about the robots' poses. We consider scans that are collections of line segments. Our approach increases the flexibility in data collection, since robots do not need to see each other during mapping, and data can be collected by multiple robots or a single robot in one or multiple sessions. Experimental results show the effectiveness of our approach in different types of indoor environments.