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Related Concept Videos

Ethical Issues01:27

Ethical Issues

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Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
Ethical Concerns in Healthcare:
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Ethics and Bioethics01:22

Ethics and Bioethics

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Ethics is a philosophical study of moral actions. Ethics attempts to determine what is valuable for individuals and society. It examines the rational justification of moral judgments and analyzes what is morally just, fair, and right. Bioethics is a sub-discipline of applied ethics that analyzes the philosophical, social, and legal issues in life sciences and medicine. Ethical theories serve as a foundation for decision-making and represent the viewpoints from which people seek direction. They...
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Ethical Dilemmas II01:30

Ethical Dilemmas II

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Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:
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Ethical Dilemmas I01:17

Ethical Dilemmas I

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Ethical dilemmas in nursing are of utmost importance, as they often arise from the tension between adhering to core ethical principles and the practical realities of healthcare delivery. These dilemmas require nurses to navigate complex situations where competing ethical considerations pull them in different directions.
Let us explore some examples to understand the potentially complex moral decisions nurses face.
Take the case of caring for minors, particularly in areas related to reproductive...
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Ethical Standards I01:25

Ethical Standards I

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The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
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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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Related Experiment Video

Updated: Mar 5, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Beyond privacy and exposure: ethical issues within citizen-facing analytics.

Peter Grindrod1

  • 1Mathematical Institute, University of Oxford, Oxford, UK grindrod@maths.ox.ac.uk.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|March 25, 2017
PubMed
Summary
This summary is machine-generated.

Data science and analytics operate differently across corporate, public, and academic spheres. Ethical data use requires transparency and a fair balance of benefits, with data scientists bearing responsibility for preventing misuse.

Keywords:
analyticsdata scienceethicsmodelling

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Area of Science:

  • Data Science
  • Analytics
  • Ethics

Background:

  • Digital transformation blurs lines between corporate, public, and academic spheres.
  • Citizen data exploitation hinges on perceived benefit balance, transparency, and justification.
  • Corporate analytics often anonymizes data for strategic decision-making, distinct from citizen-focused applications.

Purpose of the Study:

  • To analyze governing forces in data analytics across different institutional spheres.
  • To explore the ethical implications of data usage, model transparency, and personal data evolution.
  • To advocate for clear definitions and ethical responsibilities in data science and analytics.

Main Methods:

  • Comparative analysis of analytics across corporate, public, and academic sectors.
  • Examination of 'black-box' models, data provenance, and evolving personal data ownership.
  • Review of regulatory impacts on data access and innovation.

Main Results:

  • Aspirations and missions vary significantly by sphere, despite digital convergence.
  • Citizens' data permissions depend on transparent and justifiable benefit-sharing.
  • Concerns arise regarding opaque models and the complex ownership of uniquely identifying personal data tokens.

Conclusions:

  • Professional data scientists must uphold ethical responsibility to prevent data misuse and abuses.
  • Clear, inclusive definitions for 'data science and analytics' are crucial.
  • Balancing innovation with regulation is key for responsible data utilization.