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  2. Pain Assessment in Advanced Dementia - Wikipedia

    en.wikipedia.org/wiki/Pain_Assessment_in...

    Pain Assessment in Advanced Dementia (PAINAD) is a pain scale developed by Victoria Warden, Ann C. Hurley, and Ladislav Volicer to provide a universal method of analysing the pain experienced by people in late stage dementia.

  3. Pain scale - Wikipedia

    en.wikipedia.org/wiki/Pain_scale

    A patient's self-reported pain is so critical in the pain assessment method that it has been described as the "most valid measure" of pain. [2] [3] The focus on patient report of pain is an essential aspect of any pain scale, but there are additional features that should be included in a pain scale. In addition to focusing on the patient's ...

  4. Wong–Baker Faces Pain Rating Scale - Wikipedia

    en.wikipedia.org/wiki/Wong–Baker_Faces_Pain...

    The fourth face represents a pain score of 6, and indicates "hurts even more". The fifth face represents a pain score of 8, and indicates "hurts a whole lot"; the sixth face represents a pain score of 10, and indicates "hurts worst". [2] This pain scale was originally developed for children. However, it can be used with all patients age 3 and ...

  5. Pain assessment - Wikipedia

    en.wikipedia.org/wiki/Pain_assessment

    The patient's history and diagnosis are helpful in deciding whether or not the patient is developing a substance abuse problem. A patient having social or relationship problems may need to meet with a crisis counselor. During every shift that a nurse is on duty, they must do an assessment of the patient.

  6. SOCRATES (pain assessment) - Wikipedia

    en.wikipedia.org/wiki/Socrates_(pain_assessment)

    SOCRATES is used to gain an insight into the patient's condition, and to allow the health care provider to develop a plan for dealing with it. [1] [2] It can be useful for differentiating between nociceptive pain and neuropathic pain. [3]

  7. Automated Pain Recognition - Wikipedia

    en.wikipedia.org/wiki/Automated_Pain_Recognition

    Pain recognition requires the extraction of meaningful characteristics or patterns from the data collected. This is achieved using machine learning techniques that are able to provide an assessment of the pain after training (learning), e.g., "no pain," "mild pain," or "severe pain." [citation needed]