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Related Concept Videos

Surveys02:16

Surveys

16.2K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
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Types of Surveys01:27

Types of Surveys

183
Surveys are essential for marking property boundaries near water bodies. Different types of surveys are defined, each with its own function. Land surveys mark the property boundaries, while route surveys determine the position of properties on nearby highways. Topographic surveys create maps by capturing the three-dimensional features of the land. Hydrographic surveys focus on the shapes of underwater areas and the movement of streams through the properties. Mine surveys determine the relative...
183
Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

350
Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
350
Data Collection by Survey01:07

Data Collection by Survey

8.0K
The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
8.0K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

191
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
191
Reliability and Validity01:29

Reliability and Validity

13.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.3K

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Related Experiment Video

Updated: Nov 6, 2025

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Lessons learned about harmonizing survey measures for the CSER consortium.

Katrina A B Goddard1, Frank A N Angelo2, Sara L Ackerman3

  • 1Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.

Journal of Clinical and Translational Science
|May 5, 2021
PubMed
Summary

Effective research consortia require dedicated time and resources for developing collaborative practices. Harmonizing measures and ensuring data sharing are crucial for translational genomics initiatives like the Clinical Sequencing Evidence-Generating Research (CSER) consortium.

Keywords:
Team sciencecollaborationexomegenomemultidisciplinary

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Area of Science:

  • Genomics
  • Translational Research
  • Bioinformatics

Background:

  • Genome-scale sequencing in clinical care presents challenges in data interpretation, interdisciplinary coordination, and uncertain clinical utility.
  • Transdisciplinary consortia are vital for addressing these complexities, yet factors influencing their effectiveness are understudied.
  • The Clinical Sequencing Evidence-Generating Research (CSER) consortium provides a case study for examining these dynamics.

Purpose of the Study:

  • To describe the experiences and challenges within the CSER consortium.
  • To identify strategies for effective collaboration and data harmonization in multi-institutional translational genomics research.
  • To highlight the importance of organizational and societal factors in research consortium effectiveness.

Main Methods:

  • Focused on harmonizing site-specific measures with the need for consensus measures related to clinical utility.
  • Emphasized minimizing participant burden, accommodating project-specific needs, and utilizing validated, shareable measures.
  • Leveraged platforms for efficient team communication and materials/data management.

Main Results:

  • Successful harmonization required robust communication platforms and data management strategies.
  • Funding agencies play a key role by clarifying study designs and establishing data-sharing frameworks.
  • Collaborative practices and preparatory work are essential for consortium effectiveness.

Conclusions:

  • Devoting time and resources to collaborative practices at the project outset is critical.
  • Effective harmonization of measures and data sharing are foundational for translational genomics research.
  • Addressing organizational, technological, and societal factors enhances research consortium performance.