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Related Concept Videos

SBAR II: Application of SBAR01:14

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SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Operant Conditioning Intervention01:24

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Operant conditioning serves as a foundational principle in therapeutic interventions aimed at modifying maladaptive behaviors. Central to this approach is the notion that behaviors, both adaptive and maladaptive, are learned through reinforcement. By analyzing the environmental factors that reinforce problematic behaviors, clinicians can design interventions to weaken these reinforcements and replace maladaptive behaviors with healthier alternatives.
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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
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Automated conversational agents for post-intervention follow-up: a systematic review.

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  • 1Section of Vascular Surgery, Department of Surgery and Cancer, Imperial College London, London, UK.

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This systematic review found that chatbots show potential for patient follow-up after physical healthcare interventions, with varying engagement and response rates. Further research is needed to confirm their acceptability and efficacy in routine clinical care.

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Area of Science:

  • Natural Language Processing
  • Machine Learning
  • Healthcare Technology

Background:

  • Automated agents, or chatbots, leverage advances in machine learning and natural language processing to simulate human conversation.
  • Current applications are primarily commercial, with medical uses including symptom checking and psychotherapy.
  • This review focuses on chatbots for post-physical healthcare intervention patient follow-up.

Purpose of the Study:

  • To systematically review the acceptability and implementation success of chatbots in patient follow-up after physical healthcare interventions.

Main Methods:

  • A PRISMA-compliant systematic review of multiple databases (MEDLINE, EMBASE, PsychINFO, CINAHL, CENTRAL) and grey literature up to September 2020.
  • Duplicate abstract screening and data extraction were performed, with risk of bias and quality assessments for included studies.
  • Included studies comprised three randomized controlled trials, one non-randomized clinical trial, and six cohort studies.

Main Results:

  • Ten studies met inclusion criteria, utilizing chatbots for monitoring after interventions for cancer, hypertension, asthma, orthopaedic procedures, ureteroscopy, and varicose veins.
  • All chatbots were deployed on mobile devices, showing engagement rates from 31% to 97% response rates for system-generated questions.
  • No included study assessed patient safety outcomes.

Conclusions:

  • A variety of chatbot designs and applications were identified for patient monitoring.
  • Further investigation into the acceptability, efficacy, and mechanisms of chatbots in outpatient settings is warranted.
  • Evidence may support the integration of chatbots into routine clinical care pathways.