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Related Concept Videos

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Bias01:22

Bias

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...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
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...
Criticisms of the Evolutionary Perspective01:23

Criticisms of the Evolutionary Perspective

In a study where individuals posing as strangers offered compliments and proposed casual sex to students, the responses differed significantly based on gender. Not a single woman accepted the proposal, while 70% of the men agreed. This outcome provides a useful scenario to explore through the lens of evolutionary psychology and social learning theory, highlighting the diverse perspectives on human sexual behaviors.
Evolutionary psychology provides one explanation for these findings, suggesting...
Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?

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Related Experiment Video

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Ole Isacson: Development of New Therapies for Parkinson's Disease
23:53

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Published on: April 29, 2007

[Paradigm errors in the old biomedical science].

Albertas Skurvydas1

  • 1Laboratory of Human Motorics, Department of Applied Physiology and Sports Medicine, Lithuanian Academy of Physical Education, Lithuania. a.skurvydas@lkka.lt

Medicina (Kaunas, Lithuania)
|June 11, 2008
PubMed
Summary

Deterministic and reductionistic thinking in biomedical science can be harmful. Exploring new paradigms like complex dynamic systems is crucial for advancing research and avoiding the pitfalls of outdated scientific approaches.

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Area of Science:

  • Biomedical Science
  • Philosophy of Science
  • Systems Biology

Background:

  • Current biomedical research often relies on deterministic and reductionistic thinking.
  • These traditional approaches limit the understanding of complex biological phenomena.
  • The scientific community is increasingly discussing a shift towards new paradigms.

Purpose of the Study:

  • To review the limitations of deterministic and reductionistic thinking in biomedicine.
  • To propose strategies for overcoming these drawbacks.
  • To highlight the potential of new scientific paradigms.

Main Methods:

  • Literature review of existing scientific paradigms.
  • Analysis of the impact of deterministic and reductionistic approaches.
  • Discussion of complex dynamic systems and chaos theory.

Main Results:

  • Absolute determinism and reductionism in biomedical science can lead to errors.
  • These errors restrict comprehensive understanding of complex biological mechanisms.
  • The adoption of new paradigms is gaining global traction.

Conclusions:

  • Improper application of deterministic and reductionistic thinking can significantly harm biomedical science.
  • A paradigm shift towards complex dynamic systems offers a promising alternative.
  • The future of biomedical research may depend on embracing systems-level thinking.