Symptom Cluster Profiling

Symptom Cluster Profiling is a methodological framework within symptom science that identifies, characterizes, and quantifies recurring patterns of co-occurring symptoms in a given population or clinical context, distinguishing itself by its systematic integration of temporal, severity, and functional interrelationship data to define distinct symptom constellations.

176

Publications

8.9K

Citations

1.1K

Authors

589

Institutions

Publications per year

2017–2026

76

Authors

1.1K

  1. BA
    Bruce A. Cooper

    University of California, San Francisco, United States

    10 publications · 794 citations

    10

    h-index

  2. CM
    Christine Miaskowski

    University of California, San Francisco, United States

    9 publications · 710 citations

    9

    h-index

  3. SM
    Steven M. Paul

    University of California, San Francisco, United States

    7 publications · 593 citations

    7

    h-index

  4. YP
    Yvette P. Conley

    University of Pittsburgh, United States

    5 publications · 173 citations

    5

    h-index

  5. CW
    Claudia West

    University of California, San Francisco, United States

    4 publications · 470 citations

    4

    h-index

1–5 of 1.1K

Venues

  1. Journal of Pain and Symptom Management

    13 publications · 686 citations

    13

    h-index

  2. Cancer Nursing

    6 publications · 246 citations

    6

    h-index

  3. Nursing Research

    5 publications · 230 citations

    5

    h-index

  4. Supportive Care in Cancer

    5 publications · 556 citations

    5

    h-index

  5. PubMed

    Repository · 5 publications · 130 citations

    4

    h-index

1–5