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Related Concept Videos

Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Reliability and Validity01:29

Reliability and Validity

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.
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

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...
Data Collection II01:29

Data Collection II

The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and family,...
Data Collection by Survey01:07

Data Collection by Survey

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...

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Enactive Phenomenological Approach to the Trier Social Stress Test: A Mixed Methods Point of View
05:26

Enactive Phenomenological Approach to the Trier Social Stress Test: A Mixed Methods Point of View

Published on: January 7, 2019

A mixed methods inquiry into the validity of data.

Erling Kristensen1, Dorte B Nielsen, Laila N Jensen

  • 1StrateKo Aps, Gartnervaenget 2, DK-8680 Ry, Denmark. erling.kristensen@tdcadsl.dk

Acta Veterinaria Scandinavica
|July 24, 2008
PubMed
Summary

Integrating qualitative methods with quantitative herd health research improves data interpretation by addressing potential biases from human experiences and beliefs. This mixed-methods approach enhances understanding and yields more robust results in farm management studies.

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Area of Science:

  • Veterinary Epidemiology
  • Animal Health Management
  • Mixed Methods Research

Background:

  • Quantitative herd health research faces interpretation challenges due to human biases and beliefs influencing data collection.
  • Increased dialogue between researchers and stakeholders is crucial for understanding data collection backgrounds.
  • Mixed methods research, integrating quantitative and qualitative approaches, can mitigate bias and improve data interpretation in farm management.

Purpose of the Study:

  • To illustrate the potential of combining quantitative and qualitative research methods in herd health data analysis.
  • To explore the impact of veterinarians' decision-making on data related to bovine metritis.
  • To enhance the understanding of potential biases in quantitative herd health studies.

Main Methods:

  • A mixed methods approach was employed, combining a quantitative observational study with a qualitative semi-structured interview study.
  • The quantitative study analyzed risk factors for metritis in Danish dairy cows using the Danish Cattle Database.
  • The qualitative study involved interviews with 20 practicing veterinarians regarding their decision-making processes in data collection and processing for metritis.

Main Results:

  • Quantitative analysis of metritis risk factors aligned with previous studies, but herd incidence risk was skewed, suggesting potential underreporting or variations in veterinarian decision-making.
  • Qualitative interviews revealed issues with data correctness and validity concerning metritis occurrence due to differing case definitions and treatment thresholds among veterinarians.
  • Differences in veterinarian practices significantly impact the reliability of quantitative herd health data.

Conclusions:

  • Purely quantitative observational studies on herd health management may benefit from incorporating a qualitative perspective to improve the validity of findings.
  • A combined quantitative and qualitative approach enhances understanding of disease outcomes and management routines.
  • This integrated approach requires interdisciplinary collaboration, openness, and critical reflection, offering benefits for both scientific research and advisory services in animal health.