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Evaluation of the teaching process enables the nurse to determine if the patient's learning needs were met and if training was effective. If the expected outcomes are not met, the care plan is revised, and additional education or reinforcement is provided. Nurses can ask questions after the session or obtain feedback to assess the patient's understanding of the topic.
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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
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Behavioral approaches have often been criticized for ignoring mental processes and focusing solely on observable behavior. However, these approaches provide an optimistic perspective for individuals seeking to change their behaviors. Rather than concentrating on intrinsic personality traits, behavioral approaches suggest that even longstanding habits can be modified by changing the reward contingencies that maintain them.
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The Connections Matter: Bi-Directional Learning in Program Evaluation and Practice-Oriented Research.

Susan Douglas1, Andrew C Page2, Christian Moltu3,4

  • 1Department of Leadership, Policy and Organizations, Vanderbilt University, Peabody College, 230 Appleton Place PMB #414, Nashville, TN, 37203-5721, USA. susan.douglas@vanderbilt.edu.

Administration and Policy in Mental Health
|September 28, 2023
PubMed
Summary
This summary is machine-generated.

Embedded program evaluation, using a human-centered systems lens, enhances practice-oriented research. This approach fosters evaluator-practitioner partnerships for improved evidence-based practice and patient outcomes.

Keywords:
Embedded evaluationHuman-centered designPractice-oriented researchProgram evaluationProgress feedbackRoutine outcome monitoringSystems thinking

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Area of Science:

  • Health Services Research
  • Program Evaluation
  • Systems Science

Background:

  • Practice-oriented research requires systematic evaluation integrated into clinical workflows.
  • Existing evaluation methods may not fully capture the complexity of healthcare settings.
  • A need exists for frameworks that bridge practice-based evidence and evidence-based practice.

Purpose of the Study:

  • To propose a novel conceptual framework for embedded program evaluation in clinical settings.
  • To leverage a human-centered systems lens to guide evaluation practices.
  • To enhance the partnership between evaluators and practitioners for bi-directional learning.

Main Methods:

  • Utilizing a human-centered systems lens, incorporating design thinking and systems thinking principles.
  • Emphasizing evaluator-practitioner collaboration and mutual learning.
  • Recommending tools such as systems mapping, program theory development, and logic models.

Main Results:

  • The proposed framework facilitates the integration of evaluation into clinical routine.
  • It promotes awareness of individual and systemic biases within healthcare institutions.
  • Case examples from routine outcome monitoring and progress feedback illustrate the framework's application.

Conclusions:

  • Embedded program evaluation, guided by a human-centered systems lens, is well-suited for practice-oriented research.
  • Strengthening the evaluator-practitioner partnership is crucial for local and system-level healthcare improvement.
  • Further research is needed to refine collaborative models and enhance evaluation's impact.