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Related Concept Videos

Psychodynamic Perspectives on Personality01:27

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The psychodynamic perspective in psychology asserts that most personality functions operate unconsciously, outside of awareness. This means that the motives and emotions driving behavior often remain hidden, automatically buried in the unconscious mind as a defense mechanism to shield us from psychological distress. According to this theory, the unconscious mind contains thoughts, memories, and emotions that are too disturbing to face directly.
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Social cognitive perspectives on personality emphasize the importance of conscious awareness, beliefs, expectations, and goals in shaping behavior. These perspectives incorporate behaviorist principles, such as learning through reinforcement and conditioning, but extend beyond them by highlighting human reasoning and planning. Unlike traditional behaviorist views, social cognitive theory focuses on how individuals reflect on their past experiences and plan for future outcomes by considering...
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Behaviorists view personality as primarily shaped by environmental reinforcements and consequences. According to this perspective, behavior is influenced by external stimuli, and individuals adjust their actions based on rewards and punishments. Over time, learning histories — accumulated patterns of reinforcement — play a significant role in shaping personality. Behaviors that lead to positive outcomes are reinforced, while those resulting in negative outcomes are diminished.
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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Related Experiment Video

Updated: Feb 16, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
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Personal Health Self-Management in a Data Perspective.

Yiqin Yu1, Xiang Li1, Gang Hu1

  • 1IBM Research - China, Beijing, China.

Studies in Health Technology and Informatics
|January 4, 2018
PubMed
Summary
This summary is machine-generated.

Personal health self-management is crucial for chronic disease patients. This study introduces a Personal Health Advisor (PHA) application with data flow, risk assessment, and patient profiling to aid self-management.

Keywords:
Health EducationRisk AssessmentSelf Care

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Area of Science:

  • Digital Health
  • Personalized Medicine
  • Health Informatics

Background:

  • Increasing prevalence of chronic diseases necessitates effective patient self-management strategies.
  • Heterogeneous patient needs complicate the design and implementation of self-management programs.
  • Existing solutions may lack personalized approaches to health self-management.

Purpose of the Study:

  • To introduce a novel Personal Health Advisor (PHA) application designed to support personal health self-management.
  • To present a robust personal health data flow mechanism for integrated health monitoring.
  • To develop and integrate key modules for personalized health management within the PHA.

Main Methods:

  • Development of a Personal Health Advisor (PHA) application.
  • Implementation of a personal health data flow mechanism.
  • Integration of modules for personal health risk assessment, similar patient profiling, and health question answering.

Main Results:

  • The PHA application provides a framework for personalized health self-management.
  • The data flow mechanism enables efficient handling of personal health information.
  • Integrated modules offer tailored risk assessments, patient comparisons, and health information retrieval.

Conclusions:

  • The Personal Health Advisor (PHA) application offers a promising approach to address the complexities of personal health self-management.
  • The proposed data flow and integrated modules enhance the capability to deliver personalized health support.
  • This system can potentially improve outcomes for individuals managing chronic diseases.