Facing the Nonresponse Challenge

2012 ◽  
Vol 645 (1) ◽  
pp. 23-35 ◽  
Author(s):  
Frauke Kreuter
Keyword(s):  
Data Collection ◽  
Survey Research ◽  
Survey Data ◽  
Quality Measures ◽  
Data Sources ◽  
Collection Process ◽  
Data Collection Process ◽  
Survey Estimates ◽  
Survey Designs

This article provides a brief overview of key trends in the survey research to address the nonresponse challenge. Noteworthy are efforts to develop new quality measures and to combine several data sources to enhance either the data collection process or the quality of resulting survey estimates. Mixtures of survey data collection modes and less burdensome survey designs are additional steps taken by survey researchers to address nonresponse.

scholarly journals Survey Instrument Validity Part I: Principles of Survey Instrument Development and Validation in Athletic Training Education Research

2011 ◽  
Vol 6 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Laura J. Burton ◽  
Stephanie M. Mazerolle
Keyword(s):  
Data Collection ◽  
Survey Research ◽  
Athletic Training ◽  
Heat Stroke ◽  
Survey Instrument ◽  
Stroke Treatment ◽  
Instrument Validity ◽  
Collection Process ◽  
Data Collection Process ◽  
Development And Validation

Context: Instrument validation is an important facet of survey research methods and athletic trainers must be aware of the important underlying principles. Objective: To discuss the process of survey development and validation, specifically the process of construct validation. Background: Athletic training researchers frequently employ the use of survey research for topics such as clinical instruction and supervision, burnout, and professional development; however, researchers have not always used proper procedures to ensure instrument validity and reliability for the data collection process. Description: Four major methods exist to establish the validity of an instrument: face, content, criterion related, and construct. When developing a survey to measure a previously unexplored construct (eg, an athletic trainer's attitudes toward appropriate exertional heat stroke treatment), researchers should employ a four-step process: (1) defining constructs and content domain, (2) generating and judging measurement items, (3) designing and conducting studies to develop a scale, and (4) finalizing the scale. Clinical Advantages: Establishing the validity of a survey instrument strengthens the data yielded from the data collection process, which allows for greater confidence in the interpretation of the results from the survey. Conclusions: Construct validity, although a time-intensive process, is necessary to ensure accuracy and validity of the survey instrument.

scholarly journals A Survey to Assess the Quality of the Data Obtained by Radio-Frequency Technologies and Microelectromechanical Systems to Measure External Workload and Collective Behavior Variables in Team Sports

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2271 ◽  
Author(s):  
Markel Rico-González ◽  
Asier Los Arcos ◽  
Daniel Rojas-Valverde ◽  
Filipe M. Clemente ◽  
José Pino-Ortega
Keyword(s):  
Data Collection ◽  
Radio Frequency ◽  
Collective Behavior ◽  
Microelectromechanical Systems ◽  
Team Sports ◽  
Positioning Systems ◽  
Collection Process ◽  
Data Collection Process ◽  
Global Positioning

Electronic performance and tracking systems (EPTS) and microelectromechanical systems (MEMS) allow the measurement of training load (TL) and collective behavior in team sports so that match performance can be optimized. Despite the frequent use of radio-frequency (RF) technology (i.e., global positioning navigation systems (GNSS/global positioning systems (GPS)) and, local position systems (LPS)) and MEMS in sports research, there is no protocol that must be followed, nor are there any set guidelines for evaluating the quality of the data collection process in studies. Thus, this study aims to suggest a survey based on previously used protocols to evaluate the quality of data recorded by RF technology and MEMS in team sports. A quality check sheet was proposed considering 13 general criteria items. Four additional items for GNSS/GPS, eight additional items for LPS, and five items for MEMS were suggested. This information for evaluating the quality of the data collection process should be reported in the methods sections of future studies.

scholarly journals Validation of Four-dimensional Components for Measuring Quality of the Public Health Data Collection Process: Expert Elicitation (Preprint)

2019 ◽  
Author(s):  
Hong Chen ◽  
Ping Yu ◽  
David Hailey ◽  
Tingru Cui
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Expert Elicitation ◽  
The Public ◽  
Component Framework ◽  
Collection Process ◽  
Data Collection Process ◽  
Public Health Information ◽  
Aids Information

BACKGROUND Identification of the essential components of quality of data collection is the starting point for the design of effective data quality management strategies in public health information systems. An inductive analysis of global public health informatics literature on the data collection process derived a four-dimensional (4D) component framework that focuses on four dimensions of the process: management, personnel, data collection system, and environment. It is necessary to empirically validate the framework for further research and practice. OBJECTIVE This study aimed to obtain empirical evidence to confirm the components of the 4D framework, and if needed, to further develop this preliminary framework. METHODS Expert elicitation was used to evaluate the preliminary framework in the context of Chinese national AIDS information management system. The research processes included the development of an interview guide and data collection form, data collection, and data analysis. Twenty-eight experts, including three public health administrators, fifteen public health work-ers, and ten healthcare practitioners participated in the elicitation session. A framework quali-tative data analysis approach was followed to elicit themes from interview transcripts and to compare with the elements of the 4D framework. RESULTS A total of 302 codes were extracted from the interview transcripts, which verified 116 (78%) original indicators and generated 47 new indicators. The final 4D component framework consists of 116 indicators including 82 facilitators and 34 barriers. The first component, data collection management, includes data collection protocol and quality assurance, which is measured by 41 (35% of the 116) indicators. It was followed by data collection environment measured by 37 (32%) indicators, which comprises leadership, training, and funding, as well as three newly added subcomponents, i.e., organisational policy, high-level management support, collaboration among parallel organisations. The third component, data collection personnel, is described by a perception of data collection, skill/competence, communication, and staffing pattern, which is measured by 22 (19%) indicators. The fourth, data collection system, contain-ing functions, integration of different data collection systems, technical support, and device for data collection, is measured by 16 (14%) indicators. CONCLUSIONS This expert elicitation study situated in national AIDS information management systems validated and made improvements to the 4D component framework measuring the quality of the data collection process for public health information systems. The validated 4D component framework can be applied by researchers and practitioners in designing and managing the public health data collection process.

scholarly journals Revisiting Mobile Crowdsensing: An Open Challenge

2021 ◽  
Author(s):  
Vittalis Ayu
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Context Awareness ◽  
Data Exchange ◽  
Data Availability ◽  
Mobility Patterns ◽  
Mobile Crowdsensing ◽  
Collection Process ◽  
Data Collection Process

Mobile crowdsensing has become a new paradigm that enables citizens to participate in the sensing process by voluntarily gathering data from their smartphones to accomplish some given task. However, performing the sensing task generate lots of data resulting in various quality of the sensed data and high sensing cost in term of resource consumption. This matter became a significant concern in mobile crowdsensing as the mobile nodes which act as crowd sensors have limited resources. Moreover, an opportunistic mobile crowdsensing mechanism does not require user involvement, so the data collection process must be autonomous and intelligent to sense the data in the proper context. That is why context-awareness is also essential in opportunistic crowdsensing to maintain the sensed data quality. In this mini-review, we revisit the possibility of enhancing the mobile crowdsensing mechanism. We argue that improving the data collection process, including context-awareness, can optimize in-node data availability and sensed data quality. Besides, we also argue that finding optimization on inter-node data exchange mechanisms will increase the quality of the in-node data. Furthermore, smartphones that are related to humans as their owners reflect humans' physical and social behavior. We believe that considering contexts such as human social relationships and human mobility patterns can benefit the optimization strategies.

scholarly journals An Ethnographic Account of Doing Survey Research in Prison: Descriptions, Reflections, and Suggestions from the Field

2011 ◽  
Vol 7 (2) ◽  
pp. 45-63
Author(s):  
James Sutton
Keyword(s):  
United States ◽  
Data Collection ◽  
Survey Research ◽  
Quantitative Research ◽  
The United States ◽  
Collection Process ◽  
Scholarly Publications ◽  
Data Collection Process ◽  
Interpretive Frame ◽  
Personal Reflections

This article presents an ethnographic account of my day-to-day experiences as a survey researcher in men’s prisons in the United States. I outline challenges I encountered in the field and share personal reflections on interviewing people who are incarcerated. I then put forth a series of implications and suggestions for those who plan to conduct similar studies. Researchers’ firsthand accounts of the data collection process and research settings are crucial because they provide instruction for other scholars. Yet, these aspects of doing research are conventionally ignored in survey researchers’ scholarly publications. Accordingly, this article presents an examination of my work as a survey researcher through an interpretive frame, calls for reflective approaches to conducting quantitative research, and provides a primer on doing research in prison settings.

scholarly journals Dampak Keberadaan Pasar Modern Terhadap Eksistensi Pasar Tradisional Di Kota Tobelo Kabupaten Halmahera Utara

JURNAL PUNDI ◽  
2018 ◽  
Vol 2 (3) ◽  
Author(s):  
Putra Sian Arimawa ◽  
Feri Leasiwal
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Data Collection ◽  
Traditional Markets ◽  
Collection Process ◽  
Data Collection Process ◽  
Number Of Customers ◽  
Descriptive Qualitative

Abstract: This study aims to find out how traders perceive the existence of modern markets and how consumers perceive the existence of modern markets.The type of this research is descriptive qualitative research. As for the data collection process in this study is to use interview, observation and documentation techniques. Data analysis was carried out by reducing data, presenting data and drawing conclusions.The results of this study indicate that with the existence of a modern market, based on the results of the study it can be concluded that after the modern market, the income of traders in traditional markets has decreased, other findings also found that the three traditional markets in Tobelo city not only experienced the decrease in income in addition to that income and the number of customers who came also decreased, so that many traders suffered losses.The lack of facilities in traditional markets, the quality of the goods sold is also different between traditional markets and modern markets, so that many consumers prefer to shop in the modern market rather than traditional markets.Keywords: Impacts, Perceptions of Traders and Communities, Modern Markets, Traditional Markets

Pemanfaatan Sistem Informasi Sebagai Alat Untuk Pendataan Masyarakat Di Pasuruan

2020 ◽  
Vol 2 (3) ◽  
pp. 145-150
Author(s):  
Syaifuddin Syaifuddin ◽  
Wildan Suharso
Keyword(s):  
Information System ◽  
Data Collection ◽  
Human Resources ◽  
Regional Government ◽  
Community Based ◽  
Collection Process ◽  
Data Collection Process ◽  
Service Activity ◽  
Development Plans ◽  
Collection Time

Pendataan yang bersifat manual menjadikan permasalahan pada proses dilakukannya pendataan, hal ini juga terjadi pada Dinas Pendidikan dan Kebudayaan Kota Pasuruan dimana pendataan masih bersifat manual dengan keterbatasan jumlah Sumber Daya Manusia (SDM) yang ditugaskan untuk melakukan pendataan, oleh karena itu pada kegiatan pengabdian ini dilakukan pelatihan sistem informasi untuk meningkatkan waktu pendataan dan mengurangi kompleksitas dalam proses pendataan pada pegawai di Dinas Pendidikan dan Kebudayaan Kota Pasuruan. Pelatihan sistem informasi yang dimaksud adalah sistem informasi pendataan berbasis masyarakat, yang berisikan data dasar yang diperlukan oleh Pemerintah Daerah dalam rangka penyusunan rencana pembangunan. Data informasi tidak akan memberikan manfaat jika tidak dijadikan sebagai bahan acuan dalam penyusunan rencana pembangunan sehingga pelatihan dan pendampingan perlu dilakukan untuk tercapainya tujuan.Kata Kunci : Sistem Informasi, Berbasis Masyarakat, PendataanABSTRACT Manual data collection causes problems in the data collection process, this also occurs in the Pasuruan City Education and Culture Office where data collection is still manual with a limited number of Human Resources (HR) assigned to collect data, therefore this service activity is carried out information system training to increase data collection time and reduce complexity in the data collection process for employees at the Pasuruan City Education and Culture Office. The information system training referred to is a community-based data collection information system, which contains basic data required by the Regional Government in the framework of formulating development plans. Information data will not provide benefits if it is not used as a reference in the preparation of development plans so that training and assistance are needed to achieve the goals.Keywords : Information System, Community Based, Data Collection 

The MID5 Dataset, 2011–2014: Procedures, coding rules, and description

2021 ◽  
pp. 073889422199574
Author(s):  
Glenn Palmer ◽  
Roseanne W McManus ◽  
Vito D’Orazio ◽  
Michael R Kenwick ◽  
Mikaela Karstens ◽  
...  
Keyword(s):  
Data Collection ◽  
Descriptive Statistics ◽  
Collection Process ◽  
Data Collection Process ◽  
Interstate Conflicts ◽  
Coding Manual ◽  
Militarized Interstate Dispute ◽  
Coding Rules

This article introduces the latest iteration of the most widely used dataset on interstate conflicts, the Militarized Interstate Dispute (MID) 5 dataset. We begin by outlining the data collection process used in the MID5 project. Next, we discuss some of the most challenging cases that we coded and some updates to the coding manual that resulted. Finally, we provide descriptive statistics for the new years of the MID data.

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