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Related Concept Videos

Bias01:22

Bias

3.9K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
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Surveys02:16

Surveys

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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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Ethics in Research01:56

Ethics in Research

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Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
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Reliability and Validity01:29

Reliability and Validity

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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.
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Updated: Jun 13, 2025

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Data Integrity Issues With Web-Based Studies: An Institutional Example of a Widespread Challenge.

Blandine French1, Camilla Babbage1, Katherine Bird1

  • 1School of Psychology, University of Nottingham, Nottingham, United Kingdom.

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|September 16, 2024
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Summary

Web-based health research faces data integrity issues from non-genuine participants. Implementing mitigation strategies is crucial for reliable online study results and credibility.

Keywords:
data integrity, misrepresentationmental healthqualitative studiessurveysweb-based researchweb-based studies

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Area of Science:

  • Health Research Methodology
  • Online Data Collection
  • Research Integrity

Background:

  • Web-based research is increasingly common in health studies.
  • Challenges include non-genuine participants, repeat responses, and data misrepresentation.
  • These issues significantly threaten the integrity of research findings.

Purpose of the Study:

  • To highlight challenges in web-based health research.
  • To present case studies and propose mitigation strategies.
  • To emphasize the need for clear guidelines and transparent practices.

Main Methods:

  • Review of existing literature on data integrity in online research.
  • Presentation of seven institutional case studies, primarily in mental health research.
  • Identification and discussion of strategies to combat participant-related issues.

Main Results:

  • Non-genuine participants and data misrepresentation pose significant threats to web-based health research.
  • Case studies illustrate the practical impact of these challenges.
  • Proactive strategies are essential throughout the research lifecycle.

Conclusions:

  • Clear guidelines and mandatory reporting of mitigation efforts are needed.
  • Researchers must implement strategies like protocol development and continuous monitoring.
  • Upholding credibility in web-based research requires addressing these integrity challenges.