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Related Concept Videos

Substance Use Disorders Affecting Sleep01:24

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Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
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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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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Developing a Data Trust Model (Not Only) for Sleep Research: Conceptual Study and Quantitative Survey.

Raphael Jan Dressle1, Dieter Riemann1, Nicole Thoma1

  • 1Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Albert-Ludwigs-Universität Freiburg, c/o Medizinische Fakultät, Klinik für Psychiatrie und Psychotherapie, Hauptstraße 5, Freiburg, 79104, Germany, 49 761 270-65570.

JMIR Human Factors
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PubMed
Summary
This summary is machine-generated.

The SouveMed framework enables secure secondary use of health data. It balances stakeholder needs through a data trust, enhancing trust and usability for researchers and patients.

Keywords:
consent managementdata trustdigital infrastructurehealth datainformed consentpatient participationsleepsleep researchsurveytrust

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Area of Science:

  • Health Informatics
  • Medical Data Management
  • Bioethics

Background:

  • Healthcare facilities generate vast amounts of data, but its secondary research use is limited.
  • Balancing diverse stakeholder needs presents a significant challenge to data sharing.
  • Existing solutions for secondary medical data use are often inadequate.

Purpose of the Study:

  • To develop a data trust model and user interface applications for legally and ethically sound secondary use of medical data.
  • To address the need for feasible solutions in secondary medical data utilization.
  • To create a framework based on extensive stakeholder surveys.

Main Methods:

  • Conducted semistructured interviews and online questionnaires with patients, researchers, and institutional representatives.
  • Employed surveys for requirement elicitation and two rounds of evaluation.
  • Utilized independent-samples Welch t tests to compare group means between evaluations.

Main Results:

  • Developed SouveMed, a data trust framework for secondary use of medical data, exemplified in sleep research.
  • SouveMed facilitates secure data subject onboarding, digital consent, and data user interfaces for querying and data access.
  • Data subjects reported high trust (mean 4.23) and improved usability scores for data user systems (4.58/5) after evaluation rounds.

Conclusions:

  • The SouveMed concept offers a comprehensive framework for secondary medical data utilization.
  • The developed processes are adaptable for application in various medical research domains.
  • This framework addresses critical legal and ethical considerations in medical data sharing.