PURPOSE/ OBJECTIVES: To derive symptom clusters occurring in a large group of older pediatric patients with cancer in Taiwan and to examine whether each cluster differed based on gender, type of cancer and disease, pain, and functional status. DESIGN: Descriptive, correlational study. SETTING: Pediatric oncology inpatient unit and outpatient clinics in Taiwan. SAMPLE: 144 pediatric patients with cancer, aged 10-18 years. METHODS: Subjects completed the Memorial Symptom Assessment Scale 10-18, the Play Performance Scale for Children, and a demographic questionnaire. Medical records provided disease and treatment data. Cluster analysis techniques were used to identify the symptoms that clustered together by demographic characteristics, as well as disease, pain, and functional status. MAIN RESEARCH VARIABLES: Symptom cluster, pain status, and functional status. FINDINGS: Five clusters were identified from the statistical analysis. The symptoms that clustered together were somewhat surprising, and some can be explained by cultural differences. Patients with pain reported statistically significant higher distress in all five clusters. CONCLUSIONS: Five symptom clusters are identified in older Taiwanese children with cancer. The way and possible rationale of how these symptoms clustered together is discussed. IMPLICATIONS FOR NURSING: This is the first study that used a statistical procedure to derive symptom clusters experienced by pediatric oncology patients. Knowledge from this study can provide a starting point to investigate the stability of symptom clusters with different states of disease, different populations, and over various periods of time.
PURPOSE/ OBJECTIVES: To derive symptom clusters occurring in a large group of older pediatric patients with cancer in Taiwan and to examine whether each cluster differed based on gender, type of cancer and disease, pain, and functional status. DESIGN: Descriptive, correlational study. SETTING: Pediatric oncology inpatient unit and outpatient clinics in Taiwan. SAMPLE: 144 pediatric patients with cancer, aged 10-18 years. METHODS: Subjects completed the Memorial Symptom Assessment Scale 10-18, the Play Performance Scale for Children, and a demographic questionnaire. Medical records provided disease and treatment data. Cluster analysis techniques were used to identify the symptoms that clustered together by demographic characteristics, as well as disease, pain, and functional status. MAIN RESEARCH VARIABLES: Symptom cluster, pain status, and functional status. FINDINGS: Five clusters were identified from the statistical analysis. The symptoms that clustered together were somewhat surprising, and some can be explained by cultural differences. Patients with pain reported statistically significant higher distress in all five clusters. CONCLUSIONS: Five symptom clusters are identified in older Taiwanese children with cancer. The way and possible rationale of how these symptoms clustered together is discussed. IMPLICATIONS FOR NURSING: This is the first study that used a statistical procedure to derive symptom clusters experienced by pediatric oncology patients. Knowledge from this study can provide a starting point to investigate the stability of symptom clusters with different states of disease, different populations, and over various periods of time.
Authors: Tyler W Buckner; Jichuan Wang; Darren A DeWalt; Shana Jacobs; Bryce B Reeve; Pamela S Hinds Journal: Pediatr Blood Cancer Date: 2014-03-15 Impact factor: 3.167
Authors: Rebecca Williamson Lewis; Karen E Effinger; Karen Wasilewski-Masker; Ann Mertens; Canhua Xiao Journal: Support Care Cancer Date: 2021-07-06 Impact factor: 3.603
Authors: Anna Spathis; Sara Booth; Sarah Grove; Helen Hatcher; Isla Kuhn; Stephen Barclay Journal: J Adolesc Young Adult Oncol Date: 2015-03 Impact factor: 2.223
Authors: Christina Baggott; Bruce A Cooper; Neyssa Marina; Katherine K Matthay; Christine Miaskowski Journal: Cancer Nurs Date: 2012 Jan-Feb Impact factor: 2.592
Authors: L Lee Dupuis; Cindy Milne-Wren; Marilyn Cassidy; Maru Barrera; Carol Portwine; Donna L Johnston; Mariana Pradier Silva; Cathryn Sibbald; Michael Leaker; Stacey Routh; Lillian Sung Journal: Support Care Cancer Date: 2009-06-10 Impact factor: 3.603
Authors: Marilyn J Hockenberry; Olga A Taylor; Alice Pasvogel; Cheryl Rodgers; Kathy McCarthy; Patricia Gundy; David W Montgomery; Phillip Ribbeck; Michael E Scheurer; Ida M Ki Moore Journal: Oncol Nurs Forum Date: 2014-07-01 Impact factor: 2.172
Authors: Mary C Hooke; Michelle A Mathiason; Audrey Blommer; Jessica Hutter; Pauline Mitby; Olga Taylor; Michael E Scheurer; Alicia S Kunin-Batson; Wei Pan; Marilyn J Hockenberry Journal: Cancer Nurs Date: 2022 Mar-Apr 01 Impact factor: 2.592